State of the Great Lakes 2011

State of the Great Lakes 2011

State of the Great Lakes

2011

Indicators to assess the status and trends of the Great Lakes ecosystem

Environment Canada and the

U.S. Environmental Protection Agency

ISSN 2292-1222

EPA 950-R-13-002

Cat No. En161-3/1-2011E-PDF

Suggested Citation:

Environment Canada and the U.S. Environemntal Protection Agency. 2014.

State of the Great

Lakes 2011.

Cat No. En161-3/1-2011E-PDF. EPA 950-R-13-002. Available at http://binational.net

Front Cover Photo Credits:

Blue Heron, Don Breneman

Sleeping Bear Dunes, Robert de Jonge, courtesy of Michigan Travel Bureau

Port Huron Mackinac Race, Michigan Travel Bureau

Presque Isle, U.S. Army Corps of Engineers

State of the Great

Lakes 2011

By the Governments of

Canada and the

United States of America

Prepared by

Environment Canada and the

U.S. Environmental Protection Agency

Table of Contents

Preface ..........................................................................................................................................................................vi

1.

Introduction ........................................................................................................................................................... 1

Key Messages ............................................................................................................................................................ 1

2.

What Is Being Done .................................................................................................................................................. 2

Indicator Organization .......................................................................................................................................... 3

What are Great Lakes indicators? ............................................................................................................................. 3

What is the geographic scope of the indicator reports? ............................................................................................. 3

How are the indicators organized? ............................................................................................................................ 3

How are the indicators and the Great Lakes Water Quality Agreement connected? ................................................. 4

3.

State of the Great Lakes Indicator Reporting Framework ......................................................................................... 5

Indicator status and trend definitions ........................................................................................................................ 6

State of the Great Lakes ........................................................................................................................................ 7

3.1

Assessment of Water Quality (Chemical Integrity) ..................................................................................... 7

Integrating Indicators: Using Indicators to Describe Water Quality Issues .............................................................. 9

Harmful and Nuisance Algae ................................................................................................................................ 9

Low Oxygen Levels ............................................................................................................................................ 10

Clear Water ......................................................................................................................................................... 10

Chemical Substances .......................................................................................................................................... 11

3.2

Assessment of Aquatic-Dependent Life (Biological Integrity) .................................................................. 13

Integrating Indicators: Using Indicators to Describe Aquatic-Dependent Life Issues ............................................ 15

Invasive Species .................................................................................................................................................. 15

3.3

Fish Struggle to Survive...................................................................................................................................... 16

Coastal Wetland Communities ........................................................................................................................... 18

Assessment of Landscapes and Natural Processes (Physical Integrity) ..................................................... 20

Integrating Indicators: Using Indicators to Describe Landscapes and Natural Process Issues ................................ 21

Lake Levels ......................................................................................................................................................... 22

Dams and Other Barriers .................................................................................................................................... 23

4.

4.1

Transforming Watersheds ................................................................................................................................... 24

Indicator Reports ................................................................................................................................................. 26

Indicator Assessments (Status and Trend) Summary Table ....................................................................... 26

4.2

Full Indicator Reports ................................................................................................................................ 29

Air Temperature .................................................................................................................................................. 29

Aquatic Habitat Connectivity ............................................................................................................................. 34

Aquatic Non-Native Species ............................................................................................................................... 41

iii

Atmospheric Deposition of Toxic Chemicals ..................................................................................................... 55

Base Flow Due to Groundwater Discharge ......................................................................................................... 68

Beach Advisories ................................................................................................................................................ 79

Benthos Diversity and Abundance ...................................................................................................................... 89

Botulism Outbreaks ............................................................................................................................................ 99

Cladophora

....................................................................................................................................................... 111

Coastal Wetland Amphibians ........................................................................................................................... 123

Coastal Wetland Birds ...................................................................................................................................... 131

Coastal Wetland Fish Community Health......................................................................................................... 139

Coastal Wetland Invertebrate Communities ..................................................................................................... 146

Coastal Wetland Landscape Extent and Composition ...................................................................................... 150

Coastal Wetland Plants ..................................................................................................................................... 156

Conserving and Protecting Forest Lands .......................................................................................................... 164

Conserving Soil, Improving Water Quality and Enhancing Wildlife Habitat on Agricultural Lands ............... 169

Contaminants in Waterbirds ............................................................................................................................. 188

Contaminants in Whole Fish ............................................................................................................................. 196

Contamination in Sediment Cores .................................................................................................................... 213

Diporeia

............................................................................................................................................................ 221

Dreissenid Mussels – Zebra and Quagga mussels ............................................................................................ 226

Drinking Water Quality .................................................................................................................................... 235

Economic Prosperity (Unemployment) ............................................................................................................ 242

Energy Consumption ........................................................................................................................................ 250

Extreme Precipitation Events ............................................................................................................................ 259

Fish Consumption Restrictions Advisory Rating Scale .................................................................................... 264

Forest Cover ...................................................................................................................................................... 273

Greenhouse Gas Emissions ............................................................................................................................... 280

Hardened Shorelines ......................................................................................................................................... 289

Harmful Algal Blooms (HABs) ........................................................................................................................ 296

Human Population ............................................................................................................................................ 306

Ice Duration on the Great Lakes ....................................................................................................................... 317

Inland Water Quality Index .............................................................................................................................. 322

Land Cover ....................................................................................................................................................... 330

Lake Sturgeon ................................................................................................................................................... 339

Lake Trout ........................................................................................................................................................ 353

Nutrients in Lakes ............................................................................................................................................. 362

iv

Phytoplankton Populations ............................................................................................................................... 372

Preyfish Populations ......................................................................................................................................... 376

Remediating Contaminated Sediment ............................................................................................................... 386

Sea Lamprey ..................................................................................................................................................... 394

Surface Water Temperature .............................................................................................................................. 406

Terrestrial Non-Native Species ......................................................................................................................... 411

Toxic Chemicals in Offshore Waters ................................................................................................................ 418

Treating Wastewater ......................................................................................................................................... 431

Tributary Flashiness .......................................................................................................................................... 440

Walleye ............................................................................................................................................................. 452

Water Chemistry ............................................................................................................................................... 460

Water Clarity .................................................................................................................................................... 479

Water Levels ..................................................................................................................................................... 499

Watershed Stressor Index (WSI)....................................................................................................................... 514

Zooplankton Biomass ....................................................................................................................................... 529

5.

6.

Acronyms and Abbreviations ........................................................................................................................... 535

Acknowledgements ........................................................................................................................................... 541

Appendix A: Assessing Data Quality ........................................................................................................................ 547

v

Preface

The Governments of Canada and the United States are committed to providing public access to environmental information about the Great Lakes basin ecosystem through the State of the Great Lakes reporting process. The work is undertaken in accordance with the Great Lakes Water Quality Agreement, and is integral to the mission to restore and maintain the chemical, physical and biological integrity of the waters of the Great Lakes. Knowing the environmental condition of the Great Lakes can allow for effective decision-making by all Great Lakes stakeholders.

The information in this report,

State of the Great Lakes 2011

, has been assembled with involvement from more than 125 scientists and experts from the Great Lakes community within Canada and the United States. The data are based on indicator reports and presentations from the State of the Lakes Ecosystem Conference (SOLEC), held in

Erie, Pennsylvania, October 26-27, 2011. Some indicator reports have been augmented with more recent information.

SOLEC and the subsequent indicator reports provide science-based reporting on the state of the health of the Great

Lakes basin ecosystem. Four objectives for the SOLEC process include:

• To assess the state of the Great Lakes ecosystem based on accepted indicators

• To strengthen decision-making and environmental management concerning the Great Lakes

• To inform local decision-makers of Great Lakes environmental issues

• To provide a forum for communication and networking amongst all Great Lakes stakeholders

SOLEC provides Great Lakes decision-makers and scientists with the opportunity to receive the most comprehensive, up-to-date, clear and concise information on the state of the Great Lakes, see thought-provoking presentations and network with hundreds of stakeholders. SOLEC enables environmental managers to make better decisions. Although SOLEC is primarily a reporting venue rather than a management program, many SOLEC participants are involved in decision-making processes throughout the Great Lakes basin.

State of the Great Lakes 2011.

This technical report contains the full indicator reports as prepared by the primary authors, the indicator category assessments for water quality (chemical integrity), aquatic-dependent life (biological integrity) and landscapes and natural processes (physical integrity) as well as identifies Key Messages and efforts to remediate and protect the ecosystem. It also contains detailed references to data sources.

State of the Great Lakes 2011 Highlights.

The Highlights report is a synopsis of the environmental indicator reports prepared for SOLEC 2011. This report provides a snapshot of current conditions in the “Key Indicators” and

“Conditions” sections.

For more information about Great Lakes indicators and the State of the Lakes Ecosystem Conference, visit: www.binational.net

or www.epa.gov/glnpo/solec or www.ec.gc.ca/greatlakes .

For more information about data quality see Appendix 1.

vi

1.

Introduction

The Great Lakes are a global environmental and economic wonder. Lakes Superior, Huron, Michigan, Erie and

Ontario contain 84% of North America’s fresh surface water, the source of drinking water for more than 24 million people. Millions of jobs are dependent on Great Lakes basin fisheries, forests, farmland, industry and recreation.

Ongoing and emerging problems such as invasive species, chemical contaminants, and climate change impact the

Great Lakes ecosystem. Understanding ecosystem conditions and knowing whether conditions are getting better or worse are necessary to address these problems. Using status and trend assessments, this report describes the health of the Great Lakes to answer the question, “How are the Great Lakes doing?”

Key Messages

The status for water quality is fair and the trend is deteriorating.

Harmful and nuisance algae in nearshore areas and coastal bays, particularly in the western Lake Erie basin, Green Bay, Saginaw Bay, and parts of Lake Ontario are impacting human and ecosystem health.

Algal trends are worsening.

Low oxygen levels in the central Lake Erie basin are causing seasonal “dead zones” for aquatic life.

Increasing water clarity is accelerating the proliferation of nuisance algae along some shorelines and signifies a lack of food for fish offshore.

Levels of many legacy chemicals are declining in offshore waters; however, while declining, levels in fish and waterbird eggs still exceed guidelines in some areas. Mercury levels in fish have been slowly increasing since 1990.

New substances of concern are being detected in the environment.

The status for aquatic-dependent life is fair and the trend is deteriorating.

No new non-native species have been detected in the lakes since 2006, but earlier invaders continue to impact the ecosystem.

In some areas, native species are struggling to survive in an ecosystem where invasive species have altered the food web and habitats have been lost or degraded.

Coastal wetland plant and animal communities are diminishing due to loss of habitat; however, protection and restoration of wetland habitats have begun.

The status for landscapes and natural processes that influence the Great Lakes is fair and the trend is improving.

Dams and other barriers prevent fish access to spawning and nursery habitats, but access is improving through dam removals and riparian restoration.

Human uses can transform and stress Great Lakes watersheds. However, some positive signs in watersheds include marginal increases in forest cover and better land management.

Water levels in lakes Superior, Huron and Michigan have been below average since the 1990s, and there are concerns that climate change will cause greater fluctuations and possibly lower water levels.

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What Is Being Done

Work to prevent and reduce harmful levels of substances entering the Great Lakes, especially nutrients (specifically phosphorus), legacy chemicals and new substances of concern by:

Adopting best management practices such as adequate manure storage, proper fertilizer application and installation of vegetative strips along streams and rivers;

Updating and better maintaining septic systems and investing in wastewater treatment infrastructure;

Restoring wetlands and riparian zones (the interface between the land and a river or stream) to reduce excess nutrients to waterways;

Reducing legacy chemicals through a combination of regulations, rehabilitation of contaminated sites, and voluntary actions by industry and citizens; and,

Researching the impacts of legacy chemicals and substances of emerging concern and conducting longterm monitoring of these substances to show improving or deteriorating trends.

Work to restore and protect native species and habitats, while preventing and controlling invasive species where possible by:

Researching and monitoring the causes of the changing food web and declining populations of native species;

Identifying and managing priority habitats at risk and habitats suitable for restoration;

Supplementing fish stocking programs needed to maintain native fish species by restoring habitats such as reefs;

Using new information from coastal wetlands monitoring to direct wetland protection and restoration actions and to evaluate restoration success; and,

Preventing and controlling invasive species through research, vigilant monitoring, major projects such as the electric carp barrier, and individual actions such as cleaning recreational boats of mussels and plants.

Work to implement local land use decisions that plan for the long term, account for cumulative impacts and reflect the value of forests, fields, streams and wetlands by:

Implementing long-term conservation plans and tracking cumulative impacts of local land use decisions;

Guiding management decisions to conserve and improve watersheds by providing decision support tools;

Supporting programs and projects that are economically and environmentally sustainable;

Removing or mitigating dams and barriers where feasible in order to restore access to critical fish habitats; and,

Including climate change considerations in all Great Lakes activities, including land use decisions.

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2.

Indicator Organization

What are Great Lakes indicators?

An indicator is a piece of evidence that helps us to understand the condition of something. Great Lakes indicators can provide insight on how the lakes are doing right now and over time, and whether we are meeting our ecosystem goals. Reporting on a suite of Great Lakes indicators produces a big picture perspective on the condition and trends of the complex ecosystem. Indicators have been used to report on Great Lakes ecosystem components since the first

SOLEC in 1994. In 2010, the Great Lakes indicator suite was reviewed. The purpose of the review was to deliver an improved, updated and representative indicator suite that reports on the state of the Great Lakes in a comprehensive, understandable and scientific manner and allows for well

‐ informed decision-making in the Great Lakes basin. The review also aimed to build consensus on indicators among federal, state, provincial and local management organizations, which is necessary to ensure that all related data are being collected, analyzed, and reported in an effective manner as no single organization has the resources or mandate to examine the conditions of the entire

Great Lakes ecosystem.

Great Lakes indicators are used to:

Assess conditions and track changes in the ecosystem;

Understand existing and emerging issues and solutions;

Guide programs and policies needed to prevent or address harmful environmental problems; and,

Provide information to set priorities for research and program implementation.

Great Lakes indicators serve the decision-makers working to restore and maintain the largest freshwater ecosystem on the planet. Over 70 complementary indicators have been identified and placed within an organizational framework that provides decision-makers with the maximum use of the information.

What is the geographic scope of the indicator reports?

Indicator reports will provide the status and trend for the Great Lakes overall and, where possible, on an individual lake basin scale. Additionally, status and trends will be reported for certain indicators at the scale of each lake’s open and nearshore waters.

How are the indicators organized?

As a result of the 2010 review, the Driving Force – Pressure – State – Impact – Response (DPSIR) framework was adopted with ten top-level reporting categories (see reverse side for DPSIR framework, categories and indicators).

The DPSIR framework is an underlying tool to help select, organize and report on indicators. The DPSIR framework allows decision-makers to understand the linkages between the condition of the ecosystem, pressures on the ecosystem, and how human activities are related.

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Decision-makers are responsible for the STATE of chemical, physical and biological integrity of the Great Lakes because it IMPACTS the quality of life of humans, fish and wildlife. We are therefore working together on

PRESSURES such as invasive species. Together we are asked to RESPOND to ecosystem conditions through restoration and protection efforts.

How are the indicators and the Great Lakes Water Quality Agreement connected?

The Great Lakes Water Quality Agreement (GLWQA) provides the context for selecting appropriate indicators and reporting categories. Ecosystem objectives identified by the GLWQA and supporting programs are the reference values for assessing status and trends within the Great Lakes indicators.

4

State of the Great Lakes Indicator Reporting Framework

DPSIR Framework Reporting Areas:

Driving Forces; Pressures; State; Impacts; Responses

Top Level

Categories

Economic/ Social Pollution & Nutrients

Invasive

Species

Resource Use &

Physical Stressors

Water Quality

Aquatic-Dependent

Life

Landscape & Natural

Processes

Human Fish & Wildlife

Restoration &

Protection

Indicators

Human population

Economic prosperity

Energy consumption

Value of Great

Lakes

Greenhouse gas emissions

Contamination in sediment

Atmospheric deposition

Inland water quality index

Nutrients in tributaries

Pesticides in tributaries

Bacterial loadings from tributaries

Municipal wastewater loadings

Industrial loadings

Aquatic nonnative species

including a watch list of high risk species

Terrestrial non-native species

Sea lamprey

Dreissenid mussels

Watershed stressor index

Forest disturbance

Artificial coastal structures

Hardened shorelines

Surface water temperature

Air temperature

Precipitation events

Toxic chemicals in offshore waters

Contaminants in whole fish

Contaminants in waterbirds

Groundwater quality

Nutrients in lakes

Major ions

Water clarity

Water chemistry

Wetland fish

Wetland plants

Wetland birds

Wetland invertebrates

Wetland amphibians

Walleye

Lake Trout

Preyfish

Benthos

Diporeia

Zooplankton Health

Zooplankton Biomass

Phytoplankton

Threatened species

Bald eagle

Lake Sturgeon

Piping Plover

Land cover

Aquatic habitat connectivity

Fish habitat

Base flow due to groundwater

Water levels

Ice duration

Forest cover

Sediment coastal nourishment

Tributary flashiness

Wetland landscape extent and composition

Drinking water

Beach advisories

Fish consumption restrictions

Harmful Algal

Blooms

Cladophora

Botulism outbreaks

Fish disease occurrences

Endocrine disruption

Note:

bold denotes existing indicators for which reports can be found in the Indicator Reports section

and

italic denotes indicators under development

Note: indicator report names are shortened in some cases

Withdrawing water sustainably

Conserving and protecting forest land

Remediating contaminated sediment

Treating wastewater

Protection and restoration of habitats and species

Conserving soil, improving water quality and enhancing wildlife on agricultural lands

Stocking native fish

Protecting special lakeshore areas

Implementing industrial efficiency measures

Educating Great Lakes basin residents

5

Indicator status and trend definitions

The status for each indicator is defined as follows:

GOOD - Meeting GLWQA or other ecosystem objectives or otherwise in acceptable condition.

FAIR - Exhibiting minimally acceptable conditions, but not meeting established GLWQA or other ecosystem objectives.

POOR - Severely negatively impacted and not displaying even minimally acceptable conditions.

UNDETERMINED - Data are not available or are insufficient to assess the status of ecosystem components.

The trend for each indicator is defined as follows:

IMPROVING - Metrics show a change toward more acceptable conditions.

DETERIORATING - Metrics show a change away from acceptable conditions.

UNCHANGING - Metrics show no change.

UNDETERMINED - Metrics indicate a balance of both improving and deteriorating conditions, or data are not available to report on a trend.

For more information about Great Lakes indicators, SOLEC and the technical report, visit: www.ec.gc.ca/greatlakes ; www.epa.gov/greatlakes/solec ; www.binational.net

or email: [email protected]

.

6

3.

State of the Great Lakes

3.1

Assessment of Water Quality (Chemical Integrity)

Water Quality State Indicators 2011 Assessment (Status and Trend)

Indicators

LS LM

Contaminants in Waterbirds

Contaminants in Whole Fish

Groundwater Quality

Lake

LH

Under development

LE

Major Ions

Nutrients in Lakes

Toxic Chemicals in Offshore Waters

Water Chemistry

Water Clarity

Under development increasing increasing increasing

LO

increasing

Water Quality Supporting Indicators 2011 Assessment (Status and Trend)

Indicators

LS LM

Atmospheric Deposition

Beach Advisories – U.S. Beaches

Beach Advisories – Canada Beaches

Cladophora

Contamination in Sediment Cores

Dreissenid Mussels – Zebra and Quagga

Drinking Water Quality

Not assessed

Conserving Soil, Improving Water Quality and

Enhancing Wildlife Habitat on Agricultural Lands

Fish Consumption Restrictions Advisories

Harmful Algal Blooms (HABs) Offshore

Harmful Algal Blooms (HABs) Nearshore

Inland Water Quality Index

Nutrients in Tributaries

Pesticides in Tributaries

Protection and Restoration of Habitats and Species

Remediating Contaminated Sediment

Lake

LH

Increasing

Under development

Under development

Increasing

LE

*

Under development

*

*

LO

* Note: Orange represents Poor to Fair status as assessed by the authors of the Fish Consumption Restrictions Advisories and

Harmful Algal Blooms indicators.

7

Water quality status is fair and the trend is deteriorating.

The overall status for water quality in the Great Lakes is fair. There are currently low concentrations of toxic chemicals in offshore waters, and a decreased concentration of some legacy chemicals, such as PCBs and DDT, in fish. However, not all water quality guidelines are being met. Despite a mix of trends for the various monitored contaminants, the overall water quality trend is deteriorating. Nearshore symptoms of nutrient enrichment persist and algal trends are worsening in some areas of the Great Lakes.

Phosphorus concentrations in offshore waters are becoming too low in some lakes to support productive food webs. Increasing mercury concentrations in fish are being observed in some areas of the lakes, after years of steady decline.

The following four indicators were used to justify the water quality status and trend determination. A short summary of each follows and the full indicator reports can be found in the Indicator Reports section.

Contaminants in Waterbirds*

Concentrations of contaminants that have been managed and monitored since the 1970s and 1980s have decreased in herring gull eggs, including significant declines in DDE (a breakdown product of DDT) and other banned pesticiderelated compounds. However, over the last decade there has been a mixture of chemical concentration trends in herring gull eggs, with some contaminant trends showing continuing improvements but other contaminant trends showing no significant change. The overall assessment is good with an improving trend.

Contaminants in Whole Fish*

Total mercury concentrations in fish are below the 1987 GLWQA guidelines in all lakes. However, concentrations appear to be increasing in lakes Superior, Huron and Erie. Concentrations of pentaPBDEs are currently above the

Federal Environmental Quality Guidelines developed by Environment Canada in lake trout and walleye in all the

Great Lakes, but are declining in most monitored fish. Total PCB concentrations in fish are above 1987 GLWQA guidelines in all lakes.

* These indicators are in the Water Quality assessment because long-term trends of contaminants in aquatic biota provide valuable insight into how chemicals get into and move throughout the food web.

Nutrients in Lakes

In lakes Michigan, Huron and Ontario, offshore total phosphorus concentrations are currently below 1987 GLWQA targets but may be too low to support healthy levels of lake productivity. In Lake Erie, targets are frequently exceeded and conditions are deteriorating. Only in Lake Superior are offshore targets being met and conditions acceptable. The assessment for nutrients in lakes in offshore waters is fair and deteriorating. Nearshore symptoms of nutrient enrichment persist and are getting worse in some areas of the Great Lakes resulting in greater extent and duration of nuisance and harmful algal blooms.

Toxic Chemicals in Offshore Waters

Concentrations of many compounds are still detected in offshore waters, although they are at very low concentrations, so the status of this indicator is considered fair. Overall, the trends of toxic chemicals in offshore waters are undetermined because there is a mixture of trends observed. Trends for the majority of organochlorine compounds are improving, while trends for PAHs and in-use pesticides vary. The highest concentrations of total mercury in Great Lakes surface waters are observed in the western basin of Lake Erie; however, there have been no observed exceedances of the Canadian Council of Ministers of the Environment water quality guideline.

8

Integrating Indicators: Using Indicators to Describe Water Quality Issues

Building from the water quality assessment, four important stories are explained below to answer questions such as

“Are the increasing amounts of nutrients and algae in the lakes dangerous to people?”, “Doesn’t clearer water mean cleaner water?”, and “Where are the chemical substances still coming from?” Understanding the Great Lakes conditions requires information not just on the

state

of the ecosystem but also includes information on the

pressures

on the environment, the

impact

of conditions on humans, aquatic species and wildlife, and how society can

respond

.

Harmful and Nuisance Algae

Despite early successes in reducing phosphorus loads to the lakes after the 1972 Great Lakes Water Quality

Agreement was implemented, algae have reappeared in recent years in nearshore areas. The resurgence of excessive algal growth in the Great Lakes is stressing ecosystem health and posing threats to human well-being and the tourism and recreational fishing industries.

Increased nutrients in water stimulate unwanted algal growth. In particular, too much phosphorus is entering rivers and lakes from land runoff and point sources. In 2011, delivery of a record-breaking amount of dissolved reactive phosphorus from the Maumee River in the spring preceded one of the worst harmful algal blooms ever observed in

Lake Erie. Dissolved reactive phosphorus is a form of phosphorus that algae can use more easily compared to other phosphorus forms.

Compounding this problem, in-lake nutrient cycling has changed due to the spread of invasive zebra and quagga mussels that became established in the 1990s. Invasive mussels retain and recycle nutrients in nearshore areas through their filtering and excretion activities. This alteration of nutrient flow is resulting in greater nuisance algal growth in the nearshore regions, closer to where humans interact with the lakes, while deeper offshore waters are deprived of nutrients. As they comprise the base of the food chain, some algae are desirable and necessary to promote fish production. However, harmful and nuisance algae are having a negative impact on ecosystem conditions.

9

Harmful algal blooms are highly noticeable growths of cyanobacteria, also known as blue-green algae. After largely being absent in the 1980s, blooms have reappeared in parts of the Great Lakes. Lake Erie is the most severely impacted with blooms becoming more widespread in the 1990s and 2000s. In 2011, Lake Erie’s algal bloom consisted mostly of

Microcystis aeruginosa,

which produces a liver toxin (called microcystin) that is harmful to humans. In the summer of 2011, measurements of microcystin in Lake Erie were 50 times higher than the World

Health Organization (WHO) recommendation for safe recreation, and 1,200 times higher than the WHO safe drinking water limit. Fortunately, microcystin is removed by municipal water treatment. In addition to the western basin of Lake Erie, algal blooms are prevalent in Green Bay, Saginaw Bay, and parts of Lake Ontario. Note that a regional drought in the spring of 2012 resulted in reduced nutrient runoff into the lakes, and as a result there was a marked reduction in Lake Erie harmful algal blooms.

Cladophora

is a form of nuisance green algae that grows on hard surfaces. Excessive

Cladophora

can clog water intake pipes, decay and foul beaches and promote bacterial growth that may pose a risk to human health. The total amount of

Cladophora

varies from year to year, but observations and modeling indicate that the amount and resulting shoreline fouling have increased since the mid-1990s. Since that time, incidences of nuisance

Cladophora

growth have been recorded in each Great Lake, with the exception of Lake Superior.

Other changes contributing to the resurgence of algae include the loss of wetlands and riparian vegetation that once trapped nutrients. Shifting communities of phytoplankton, increased water clarity and climate issues such as warmer waters and extreme precipitation events also play a role.

Low Oxygen Levels

Closely related to the excess nutrients and algae problem is the issue of low dissolved oxygen levels in Lake Erie.

Since 2003, the total extent and duration of low oxygen levels have increased, particularly in the central basin. These areas are sometimes called “dead zones”, as few animal species can survive under such conditions. Note that the dead zone impact was evident in September 2012, when tens of thousands of fish washed onto the shores of Lake

Erie after being exposed to waters with low levels of oxygen that were brought to the surface during an upwelling event.

Seasonal declines of oxygen in the deep parts of all of the Great Lakes are a natural occurrence. However, in Lake

Erie the natural declines are aggravated by increased nutrient inputs that stimulate excessive algal growth. When large quantities of algae die and sink to the bottom, they are decomposed by bacteria which deplete the supply of oxygen in the deeper waters. To improve dissolved oxygen levels in Lake Erie, levels of algae need to be reduced.

Clear Water

With a few exceptions, including the central and western basins of Lake Erie, all offshore areas of the lakes are clearer now than compared to 30 years ago. Offshore Lake Ontario water clarity doubled from a depth of approximately 3-4 meters to a depth of 6-8 meters during this period. Water clarity is determined by the amount of phytoplankton, dissolved organic materials and suspended materials in the water. Increased water clarity allows sunlight to penetrate to greater depths, which allows algae and rooted plants to grow in deeper areas of the lakes. It is also a significant factor in the resurgence of nearshore

Cladophora

blooms.

10

The increase in offshore water clarity is attributed to two factors. First, the zebra and quagga mussel invasion coincides with increasing water clarity and declining concentrations of calcium. The invasive mussels filter algae and calcium out of the water, leaving fewer particles in the water to absorb light. Reductions in offshore phosphorus loadings as a result of invasive mussel filtration and excretion have also limited algal productivity in the open waters, which further increases water clarity.

The reduction of nutrients and plankton in the offshore waters of Lakes Huron, Michigan and Ontario has led to significant changes in the ecosystem, including alterations to the food web as discussed in the “Fish Struggle to

Survive” section of this report on page 23.

Chemical Substances

Chemical substances that have been the focus of management actions for decades are known as legacy chemicals and include PCBs and mercury. Legacy chemicals are now present in much lower concentrations in water, air and sediment than the peak concentration period in the 1970s and their levels generally continue to decline at very slow rates. In most colonial-nesting fish-eating birds, such as herring gulls, toxic chemical levels have decreased to where ecological effects, such as eggshell thinning, hatching failures, and population declines are no longer apparent.

The manufacture of PCBs was banned in North America in the 1970s, and levels in lake trout and walleye have been declining since that time. However, concentrations in these fish still exceed 1987 GLWQA guidelines and the rate of decline has slowed or in some cases halted since the early 2000s. Many transformers, capacitors, electric motors and other products built before the 1980s can still contain PCBs and thereby serve as sources of PCBs to the lakes. The concentration of PCBs and other contaminants in sediments are substantially lower than the peak levels that occurred in the mid-1950s through the early 1970s. However even with declines, contaminated sediments remain a source of harmful pollutants to the Great Lakes.

Mercury is found throughout the Great Lakes, with the highest concentrations in surface waters of the western basin of Lake Erie and nearshore areas of Lake Ontario, although levels in all lakes have dropped significantly over the past four decades. Levels of mercury in the offshore surface waters are low and are declining. Mercury levels in fish have been slowly increasing since 1990, reaching levels seen in the 1980s. Although mercury levels in fish are below 1987 GLWQA guideline levels, fish consumption advisories for mercury are in place for many fish caught in the Great Lakes. World-wide, the largest remaining source of mercury emissions to the atmosphere is coal-fired power plants. Regionally, many sources are reducing emissions; however, additional local and global actions may be

11

needed to reduce the transport and deposition of mercury to the Great Lakes. Atmospheric deposition is also a significant route by which other persistent toxic chemicals, such as PCBs, currently enter the Great Lakes. Overall, the atmospheric deposition of toxic chemicals appears to be decreasing although different chemicals have different decline rates.

Many chemical substances of emerging concern are being assessed for environmental impact, and a broad basinwide determination of their status and trend is not yet possible. Both the U.S. and Canadian governments are incorporating the monitoring of many chemical substances of emerging concern, including perfluorooctane sulfonate

(PFOS) and flame retardants, into their routine monitoring programs. PFOS has been used in non-stick cookware, water-repellent clothing and stain-resistant carpets, as well as in a wide range of industrial applications.

Concentrations of many PBDEs, a group of flame retardants, found in lake trout and walleye have been decreasing over the past 10 years; however, concentrations are still above the Federal Environmental Quality Guidelines developed by Environment Canada. These reductions are likely due to a voluntary North American manufacturing phase-out of penta-BDE and octa-BDE flame retardant formulations. However, concentrations of some of the other chemicals that are replacing the PBDEs are beginning to increase in the environment.

12

3.2

Assessment of Aquatic-Dependent Life (Biological Integrity)

Aquatic-Dependent Life State Indicators 2011 Assessment (Status and Trend)

Indicators

Bald Eagle

LS LM

Lake

LH

Under development

LE

Benthos Diversity and Abundance

Coastal Wetland Amphibians

Coastal Wetland Birds

Coastal Wetland Fish Communities

Coastal Wetland Invertebrate Communities

Coastal Wetland Plants

Diporeia

Lake Sturgeon

Lake Trout

Phytoplankton Populations

Piping Plover

Preyfish Populations

Threatened Species

Walleye

Zooplankton Biomass

Under development

Under development

Zooplankton Health Under development

Aquatic-Dependent Life Supporting Indicators 2011 Assessment (Status and Trend)

Indicators

LS LM

Lake

LH

Aquatic Non-Native Species

Botulism Outbreaks

Dreissenid Mussels – Zebra and Quagga

Hardened Shorelines

Sea Lamprey

Surface Water Temperature

Terrestrial Non-Native Species

Water Levels

Increasing Increasing Increasing

LE

LO

LO

13

Aquatic-dependent life status is fair and the trend is deteriorating.

The overall status of aquatic-dependent life in the Great Lakes is fair because many locations support self-sustaining fish populations and a healthy food web; however, other areas are degraded. Predatory fish populations are being fairly well maintained through stocking programs, and in some cases natural reproduction, but most populations do not meet target levels. The overall deteriorating trend for aquatic-dependent life is a result of decreasing preyfish populations, the declining population of

Diporeia

(a source of food for small fish), and the declining populations of many coastal wetland species. The food web has been drastically altered. No new non-native species have been detected since 2006; however, the impacts of established invasive species continue to harm the ecosystem.

The following nine indicators were used to justify the aquatic-dependent life status and trend determination. A short summary of each follows and the full indicator reports can be found in the Indicator Reports section.

Benthos Diversity and Abundance

Changes in the benthic (or bottom-dwelling) community, as measured by the tolerance of certain freshwater benthic worm communities to nutrient enrichment, are indicating that some nearshore sites in Lake Ontario and Lake

Michigan have become more rich in nutrients. This nutrient enrichment promotes the proliferation of plant life (i.e. more eutrophic). The majority of offshore sites in Lake Huron have seen a reduction in nutrient levels (i.e. increasingly oligotrophic), potentially causing problems for the aquatic ecosystem since there is a lack of food. Lake

Erie is consistently and significantly more eutrophic than the other lakes while Lake Superior is oligotrophic.

Coastal Wetland Amphibians

Between 1995 and 2010, the occurrence of five species was stable, two species increased and one decreased.

Indices of relative occurrence for these eight species are below proposed targets established by the Marsh

Monitoring Program.

Coastal Wetland Bird Communities

The abundance of half the species that regularly or always nest in Great Lakes wetlands declined significantly between 1995 and 2010 and is below proposed targets established by the Marsh Monitoring Program. However, the abundance of trumpeter swan, sandhill crane and common yellowthroat increased.

Coastal Wetland Plant Communities

The conditions of the plant community in coastal wetlands naturally differ across the Great Lakes basin due to differences in underlying geomorphic and climatic conditions. Some individual wetlands have healthy plant communities, as indicated by their conservatism index score and other measures. The conservatism index score measures the specificity of a particular plant species to a specific habitat. Overall, the status for Lake Ontario coastal wetland plant communities is poor, and the other lakes are in fair condition. Note that the overall lake assessments can mask the good, fair, or poor conditions observed in individual wetland marsh types within a lake basin.

Diporeia

Populations of the small, native, shrimp-like

Diporeia

have declined for more than a decade and are almost completely gone in lakes Michigan, Ontario and Huron, while Lake Erie populations have been virtually gone since

1998. The population in Lake Superior, although highly variable, remains good and unchanging.

Lake Sturgeon

Once an important commercial species, only remnant populations of lake sturgeon remain in each of the Great

Lakes. Populations have been considered fair and slowly increasing in all lakes over the last decade, with stocking programs and habitat restoration contributing to the increased abundance.

14

Lake Trout

Lake trout, historically the top predator fish of the Great Lakes, now only have self-reproducing populations throughout Lake Superior and many smaller populations in Lake Huron. Populations in lakes Michigan, Erie and

Ontario are mostly below Great Lakes Fishery Commission Lake Committee target levels for relative abundance and natural reproduction is low. Although populations remain low in Lake Ontario, there was a sharp recovery in adult lake trout numbers in 2010. Some population increases are being observed with support of stocking and other restoration efforts.

Preyfish Populations

Basinwide, preyfish biomass (total weight) has been decreasing since 1988. A combination of pressures is causing the decline including salmonid predation and the compounding impacts resulting from the expansion of zebra and quagga mussels and other invasive species. However, the Lake Superior preyfish community is considered improving because of an increase in the proportion of native species comprising the assemblage and the preybase’s ability to support the recovery of the wild lake trout population.

Walleye

Walleye populations in lakes Huron and Michigan are good, with improving trends since approximately 2003 and

2007, respectively. Populations in Lake Ontario have stabilized or increased slightly compared to declines observed in the 1990s. Lake Erie populations are lower than the highs experienced in the 1990s and early 2000s. Lake

Superior populations are lower than historical levels, with healthy self-sustaining populations only in the St. Louis and Kaministiquia rivers.

Integrating Indicators: Using Indicators to Describe Aquatic-Dependent Life Issues

Building on the state of aquatic-dependent life assessment, three important stories are explained below to answer questions such as “What problems are invasives causing and how are they getting into the Great Lakes?”, “Why are there fewer sport fish?”, and “Why is it important to restore wetlands?” Understanding the Great Lakes conditions requires information not just on the

state

of the ecosystem but also includes information on the

pressures

on the environment, the

impact

of conditions on humans, aquatic species and wildlife, and how society can

respond

.

Invasive Species

Since the 1830s, non-native aquatic species have significantly changed the Great Lakes ecosystem by altering aquatic food webs and degrading water quality and physical habitats. Although introductions have slowed, the 184 established non-native aquatic species continue to persist and expand their ranges within the Great Lakes. While the majority of non-native aquatic species have no known negative impact on the overall health of the Great Lakes, approximately 10 percent are considered invasive and harmful to the Great Lakes ecosystem.

One well-known invader is the sea lamprey, which has preyed on fish in the Great Lakes such as lake trout for decades. Control efforts have reduced the abundance of this invasive species by about 90 percent from peak levels, but the number of sea lamprey still currently exceeds Great Lakes Fishery Commission target ranges for lakes

Huron, Michigan and Erie. Another invader, the quagga mussel, continues to expand its range into offshore habitats.

The presence of quagga mussel contributes to or is implicated in a number of issues such as harmful and nuisance algal growth, food-web alterations, and Type E botulism which can cause large-scale mortalities in fish and waterbirds.

15

A lack of new aquatic invasive species being detected in recent years is likely the result of effective ballast water and solid ballast management in ocean-going ships. While the primary risk of invasion from transoceanic shipping has been reduced, other potential pathways such as canals and the trade of live organisms for bait, food and pets need to continue to be addressed. The Chicago Sanitary and Ship Canal, in particular, has been the focus of much attention regarding the potential migration of Asian carp from the Mississippi River into the Great Lakes basin.

Further, rising lake temperatures associated with climate change may increase the range of existing aquatic nonnative species and provide favorable conditions for new introductions. The prevention of new and the control of existing aquatic non-native invasive species is a necessary, expensive and ongoing management challenge for the foreseeable future.

Terrestrial invasive species are pervasive and some pose direct threats to the Great Lakes. The emerald ash borer, for example, is an invasive insect that has killed millions of trees in the basin.

Phragmites australis

is an invasive grass that creates monoculture stands that replace complex wetland plant communities. Prevention, detection, rapid response, and management have been limited to local programs such as the Lake Superior Invasive Free Zone, where priority is given to removing non-native species in targeted areas. Degradation, fragmentation, and loss of habitats can render the Great Lakes basin even more vulnerable to further invasions.

Fish Struggle to Survive

Great Lakes fishes are struggling to survive due to food web changes. Historically, the food web of the Great Lakes was relatively simple. Microscopic plant life, called phytoplankton, and green algae in particular, served as the base of the food web. Phytoplankton was consumed by

Diporeia

and zooplankton. In turn, these organisms were eaten by a host of small and important preyfish species. In general, lake trout was the top predator; except in Lake Erie and some of the other shallow embayments of the upper Great Lakes where walleye was the top predator.

16

Changes to the food web are ongoing. The phytoplankton communities of lakes Michigan and Huron in particular have seen a notable reduction in size and extent in the spring. Zooplankton communities are changing and declining throughout much of the basin. Larger-sized zooplankton species, typically located in waters of low biotic productivity, are making up an increasing proportion of the community during the summer in most of the upper lakes while smaller zooplankton decline.

Diporeia

, once the main food source for small fish in the Great Lakes is now almost gone, except in Lake Superior. The

Diporeia

decline has resulted in a change in the diets of small fish as well as reductions in small fish weight and energy. The causes of the

Diporeia

decline are not clear and a better understanding of this significant loss to the food web is essential in order to identify additional areas of the lakes that may be at risk.

The overall decline of zooplankton has strong implications for the food web because these organisms are an important link between phytoplankton and healthy fish populations. Preyfish population numbers are near historic lows in lakes Michigan and Huron for several species, such as alewife, rainbow smelt, and deepwater sculpin. In

Lake Erie, preyfish populations have increased since the early 1990s, but are fluctuating considerably.

Historically, lake trout were the keystone predator fish for most of the Great Lakes. Today, self-reproducing populations of lake trout are only present in Lake Superior, and in some areas of Lake Huron. Stocked mature lake trout have been observed basinwide in Lake Huron and abundant young wild lake trout are now entering the adult portion of the population. In lakes Michigan, Erie and Ontario, lake trout populations are mostly below the Great

Lakes Fishery Commission target levels. Walleye are present in fair to good numbers throughout the nearshore areas of the Great Lakes. However, in Lake Erie, walleye recruitment (survival) has been below average since 2003.

Habitat restoration and supplemental stocking programs continue to be necessary to re-establish and maintain native fish species.

17

Lake sturgeon is the largest fish in the Great Lakes, and can live to be well over a hundred years old. These prehistoric fish were once estimated to number in the millions, but are now considered rare or endangered. Despite many hurdles, and with the support of dedicated and long-term restoration and protection efforts such as reef construction in the St. Clair and Detroit rivers and stream-side rearing programs, sturgeon populations are slowly increasing. In 2011, lake sturgeon successfully reproduced in the St. Louis River in Minnesota for the first time in over a century.

One illustration of the complex changes and challenges facing the food web today is the history of the non-native invasive preyfish, called the alewife. Alewives entered the upper Great Lakes through the Welland Canal in the

1940s. The alewife thrived because it had very few predators. Alewife populations grew to incredibly high numbers by the 1950s, and winter die-offs became a nuisance on the beaches of many metropolitan areas. New top predators, non-native Chinook and coho salmon, were intentionally introduced to the Great Lakes through a large, cooperative stocking program, in part to control alewife populations. Today, alewives remain part of the Great Lakes food web, and continue to challenge the survival of some other species by eating juvenile lake trout and creating conditions that can lead to a lethal vitamin deficiency in newly hatched lake trout and Atlantic salmon.

Coastal Wetland Communities

Great Lakes coastal wetlands are found throughout the entire basin and span a diversity of types, from freshwater estuaries to lagoons and marshes. They provide valuable ecosystem services, such as storing and cycling nutrients from the land to the lake, cleansing impurities in the water, and providing habitat for fish to spawn and migratory birds to feed. People also benefit from the flood control, erosion protection and recreational opportunities provided by coastal wetlands. Despite providing significant ecosystem and societal benefits, in many areas 50 to 90 percent of coastal wetlands have been lost due to development, pollution, invasive species, unnatural water level fluctuations and climate change impacts. Conservation of remaining coastal wetlands and restoration of those previously destroyed are a necessary component to restoring and maintaining the integrity of the Great Lakes.

18

Recently, coastal wetland experts from universities, agencies and organizations developed a binational Great Lakes coastal wetland classification system and monitoring program. A five-year program to establish a baseline of coastal wetland conditions is progressing. By 2015, 100 percent of remaining Great Lakes coastal wetlands that are greater than 4 hectares in size will be assessed using established indicators that include marsh birds, amphibian populations, invertebrates, fish, wetland plants, and water chemistry. Once this baseline has been completed, protection and restoration actions will be targeted to coastal wetlands most in need of conservation.

19

3.3

Assessment of Landscapes and Natural Processes (Physical Integrity)

Landscapes and Natural Processes State Indicators 2011 Assessment (Status and Trend)

Indicators

LS LM

Lake

LH

Aquatic Habitat Connectivity

Base Flow Due to Groundwater Discharge

Fish Habitat Under development

LE

Forest Cover – Watershed

Forest Cover – Riparian Zones

Ice Duration on the Great Lakes

Land Cover

Sediment Coastal Nourishment

Tributary Flashiness

Under development

Water Levels

Coastal Wetland Landscape Extent and Composition

Landscapes and Natural Processes Supporting Indicators 2011 Assessment (Status and Trend)

Indicators

Air Temperature

LS LM

Lake

LH

Increasing

LE

Conserving Soil, Improving Water Quality and

Enhancing Wildlife Habitat on Agricultural Lands

Extreme Precipitation Events

Increasing

Increasing

Economic Prosperity

Energy Consumption Increasing

Greenhouse Gas Emissions

Hardened Shorelines

Human Population

Sea Lamprey

Surface Water Temperature

Watershed Stressor Index

Withdrawing Water Sustainability

LO

LO

Decreasing Increasing Increasing Increasing Increasing

Increasing Increasing Increasing

Under development

Landscapes and natural processes status is fair and the trend is improving.

The overall status of landscapes and natural processes of the Great Lakes is fair. Despite degradation in some areas, many watersheds and tributaries continue to serve as important spawning or nursery habitat for Great Lakes fish and continue to provide important functions such as water purification. The overall trend is improving because dam mitigation and barrier removal projects are increasing habitat connectivity for fish; forested lands in lakes Superior,

20

Huron, and Michigan basins are increasing slightly; and some rivers and streams are exhibiting more stable streamflow conditions. Climate change impacts on natural processes of the Great Lakes, such as water level fluctuations and ice cover, are being observed.

The following three indicators were used to justify the status and trend of landscapes and natural processes. A short summary of each follows and the full indicator reports can be found in the Indicator Reports section.

Aquatic Habitat Connectivity

Thousands of dams are found on Great Lakes tributaries and are a key factor in the decline of several species of fishes. Many dams are near the end of their functional life. Several dam mitigation projects occurring throughout the basin are restoring connectivity between aquatic habitats.

Forest Cover

Percentage of Forested Lands within a Watershed by Lake Basin

Forested lands, as measured by satellite imagery, cover a large percentage of land area within the Lake Superior and

Lake Huron basins, a moderate amount in the Lake Michigan and Lake Ontario basins and a low percentage in the

Lake Erie basin. Recent data for basin-wide trends indicate that forest cover for lakes Superior, Michigan and Huron are increasing, but are decreasing overall for lakes Erie and Ontario. However, it is important to note that the forest cover trends being seen in the Great Lakes basin are quite small. Changes in forest types, composition and localized decreases in forest cover remain a concern.

Percentage of Forested Lands within Riparian Zones by Watershed

Forested cover in the riparian zone of water bodies is high in the Lake Superior basin, moderate in the Lake

Michigan, Lake Huron and Lake Ontario basins and low in the Lake Erie basin. Trends are undetermined as data are not available.

Tributary Flashiness

Tributary flashiness is a measure that reflects the frequency of short-term changes in streamflow; the flow of a flashy stream increases and decreases dramatically in hours or a few days in response to rainfall. On average, tributary flashiness has significantly decreased in five out of 11 selected tributaries over a ten-year period, meaning flow conditions are becoming more stable. Flashiness in one of the tributaries (the Maumee River) has significantly increased, while flashiness in the remaining five tributaries studied did not exhibit significant trends. Periodic changes in flow rates are natural in streams and rivers and organisms that live in these systems adapt to them.

However, changes in hydrologic regimes, either reductions or increases in flashiness, can lead to displacement of native biotic communities. Status and trends in tributary flashiness have not been analyzed for each lake basin.

Integrating Indicators: Using Indicators to Describe Landscapes and Natural Process

Issues

Building from the landscapes and natural processes assessment, three important stories are explained below to answer questions such as “Why do lake levels change and what are the impacts?”, “How does land use relate to water condition?”, and “Why does dam removal benefit fish in streams?” Understanding the Great Lakes conditions requires information not just on the

state

of the ecosystem but also includes information on the

pressures

on the environment, the

impact

of conditions on humans, aquatic species and wildlife, and how society can

respond

.

21

Lake Levels

Since the late 1990s, water levels in lakes Superior, Huron and Michigan have been below average. This pattern follows nearly three decades of higher levels. Lake levels in the basin fluctuate on time scales that vary from hours to millennia; therefore, the extent of the water level record is insufficient to capture a complete understanding of trends in lake level variability. However, short- and long-term lake level fluctuations are critical to maintain healthy coastal habitats, especially coastal wetlands. Lake level fluctuations are the result of both natural and anthropogenic changes to water supply and storage.

Natural causes of long-term water level changes include overlake precipitation, runoff, evaporation, groundwater inflow/outflow and movements of the earth’s crust. Human influences, such as water level regulation, diversions into and out of the Great Lakes, changes in land use affecting runoff, consumptive uses, and dredging in connecting channels, have different impacts in each lake. Of all the anthropogenic factors, control structures and dredging in channels have had the largest impact on water levels.

Lake levels can impact the economy. For example, a drop in lake level can reduce the cargo capacity of ships, increase dredging needs and reduce hydropower production. Lake level increases can cause flooding and erosion and worsen the impacts of storm damage.

Multi-lake level regulation through the building of new dams in connecting channels could help mitigate water level changes in currently unregulated lakes Michigan, Huron and Erie. However, this regulation will not fully eliminate the risk of extreme lake level fluctuations, and could take decades to implement, cost billions of dollars, and possibly come with significant ecological effects.

It is predicted climate change will affect lake levels. Projections vary, with some climate models predicting that water levels will decrease by 30 to 90 centimeters, depending on the lake, while more recent studies suggest that both extremely high and low water levels are possible. High or low lake levels should be of concern, though the

22

magnitude and timing of these changes remain highly unpredictable. Despite this unpredictability, records show physical changes are occurring. For example, surface waters are warming earlier in the season and ice cover is decreasing, with freeze-up occurring later in the fall and ice-out occurring earlier in the spring.

Dams and Other Barriers

Streams and rivers provide spawning and nursery habitats for over one-third of Great Lakes fishes. However, fish access to these habitats has been significantly limited by thousands of dams, culverts and other barriers. For example, only 13 percent of the original stream passages in the Lake Huron basin are accessible to fishes. This loss of access to habitat has been a key factor in the historic decline of walleye, lake sturgeon and coaster brook trout populations.

23

Several restoration projects are underway throughout the Great Lakes basin to remove or bypass dams. These projects provide an opportunity to restore aquatic habitat connectivity which will promote healthy fish populations.

Other benefits include lower water temperatures, higher nutrient transport, natural flood cycles, and increased riparian and coastal wetland cover. Historical fishing grounds and culturally significant species such as coaster brook trout benefit from these restoration activities.

Transforming Watersheds

The watersheds of the Great Lakes have been and continue to be transformed to benefit the communities within the

Great Lakes region. The region boasts prime agricultural lands, world-class cities and transportation corridors, renewable energy sources and more. However, these changes to the watersheds also impact the Great Lakes. Rivers and streams, which are conduits for fish passage and sediment nourishment to the lakes, have been straightened and dammed, disrupting natural flow regimes and hydrology. Coastal areas are dynamic, productive and rich in natural resources but some have been altered by development and hardened shorelines. The uplands furthest from the lakes—where groundwater is recharged, soils are productive, habitats sustain numerous species and water is naturally regulated and stored—are being converted to hard surfaces or used for other human purposes.

Recent research has identified five human-related stressors from the watersheds that can be particularly disruptive to

Great Lakes. They are population density, road density, agricultural activity, area of non-natural land cover and number of point source discharges. When the five variables are combined, watersheds exerting the most stress on nearshore areas can be identified, and areas for protection and restoration can be prioritized.

Many changes are taking place to benefit or protect natural conditions in watersheds. Agricultural producers are improving field productivity while minimizing impacts to the Great Lakes. The number of best management practices adopted to conserve soil, improve water quality and enhance wildlife habitat has increased since 2005.

Adoption of practices including the establishment of permanent vegetative filter strips at field edges, construction of manure storage structures, fencing livestock out of riparian areas, erosion control structures, and practicing integrated pest and nutrient management are helping to sustainably produce food while better managing

24

environmental risks. Over the past 30 years, forest cover has increased overall in the U.S. Great Lakes basin, although there is concern that original forest types, such as boreal, are changing in some local and regional areas.

Cities and communities are also working to manage infrastructure renewal and growth with respect to established environmental goals. While restoration to pre-settlement conditions is unrealistic, an ecosystem that supports a balance between healthy environments and use by people is achievable.

25

4.

Indicator Reports

4.1

Indicator Assessments (Status and Trend) Summary Table

Indicators

Air Temperature (No status or individual lake assessment)

Aquatic Habitat Connectivity

Aquatic Non-Native Species

Atmospheric Deposition (no individual lake assessment)

Baseflow due to Groundwater

Discharge (no individual lake assessment)

Beach Advisories – U.S. Beaches

Lake

Superior

Lake

Michigan

Lake

Huron

Increasing

Lake

Erie

Lake

Ontario

Top Level Reporting

Category

Pressure

– Resource Use and Physical Stressors

State

– Landscapes and

Natural Processes

Pressure

- Invasive

Species

Pressure –

Pollution and

Nutrients

State –

Landscape and

Natural Processes

Impacts -

Human

Beach Advisories – Canada Beaches

Impacts - Human

Benthos (Freshwater Oligochaete)

Diversity & Abundance

Botulism Outbreaks

Cladophora

Coastal Wetland Amphibians

Coastal Wetland Birds

Coastal Wetland Fish Communities (no individual lake assessment)

Coastal Wetland Invertebrates (no individual lake assessment)

Coastal Wetland Extent and

Composition (No individual lake assessment)

Coastal Wetland Plants

Conserving and Protecting Forest Land

(no status or individual lake assessment)

Conserving Soil, Improving Water

Quality and Enhancing Wildlife

Habitat on Agricultural Lands

Contaminants in Waterbirds

Contaminants in Whole Fish

Contamination in Sediment Cores

Increasing

Not assessed

State –

Aquatic-dependent

Life

Impacts –

Fish and

Wildlife

Impacts -

Human

State –

Aquatic-dependent

Life

State –

Aquatic-dependent

Life

State –

Aquatic-dependent

Life

State –

Aquatic-dependent

Life

State –

Landscape and

Natural Processes

State –

Aquatic-dependent

Life

Response –

Restoration &

Protection

Response –

Restoration &

Protection

State –

Water Quality

State –

Water Quality

Pressures

– Pollution and

Nutrients

26

Indicators

Diporeia

Dreissenid Mussels

Drinking Water Quality (no individual lake assessment)

Economic Prosperity (No status or individual lake assessment)

Energy Consumption (No status or individual lake assessment)

Extreme Precipitation Events (No status or individual lake assessment)

Fish Consumption Restrictions

Forest Cover

% of forested lands within a watershed

Forest Cover

% of forested lands within riparian zones

Greenhouse Gas Emissions (No status or individual lake assessment)

Hardened Shorelines

Harmful Algal Blooms (HABs)

Offshore

Harmful Algal Blooms (HABs)

Nearshore

Human Population

Ice Duration (No individual lake assessment)

Inland Water Quality Index decreasing

Land Cover

Lake Sturgeon

Lake Trout

Nutrients in Lakes

Phytoplankton

Preyfish Populations

Lake

Superior

Lake

Michigan

Lake

Huron

Lake

Erie

increasing

Increasing

Increasing

*

Lake

Ontario

Top Level Reporting

Category

State –

Aquatic –

Dependent Life

Pressures

– Invasive

Species

Impacts

– Human

Driving Forces –

Economic / Social

Driving Forces

Economic / Social

Pressure

– Resource Use and Physical Stressors

Impacts

– Human

State

– Landscapes and

Natural Resources

State

– Landscapes and

Natural Resources increasing

Driving Forces -

Economic / Social

Pressures

– Resource Use and Physical Stressors

Impacts

– Human *

* increasing increasing

Driving Forces

Economic / Social

State

– Landscapes and

Natural Processes

Pressures

– Pollution and

Nutrients

State –

Landscape and

Natural Processes

State

– Aquatic –

Dependent Life

State

– Aquatic –

Dependent Life

State

- Water Quality

State

– Aquatic –

Dependent Life

State –

Aquatic –

Dependent Life

*

Orange represents Poor to Fair status as assessed by the authors of the Fish Consumption Restrictions Advisories and Harmful

Algal Blooms indicators.

27

Indicators

Remediating Contaminated Sediment

(No status or individual lake assessment)

Sea Lamprey

Surface Water Temperature (No status assessment)

Terrestrial Non-Native Species (No individual lake assessment)

Toxic Chemicals in Offshore Waters

Treating Wastewater (No status assessment)

Tributary Flashiness (no individual lake assessment)

Walleye

Water Chemistry (No individual lake assessment)

Water Clarity

Water Levels (No individual lake assessment)

Watershed Stressor Index (no tend assessment possible at this time)

Zooplankton Biomass increasing increasing increasing

Lake

Superior

Lake

Michigan

increasing increasing

Increasing

Lake

Huron

increasing increasing

Lake

Erie

Lake

Ontario

Top Level Reporting

Category

Response

– Restoration and Protection increasing increasing

Pressures

– Invasive

Species

Pressures

– Resource Use and Physical Stressors

Pressures

– Invasive

Species

State

– Water Quality

Response

– Restoration and Protection

State

– Landscape and

Natural Processes

State

– Aquatic –

Dependent Life

State –

Water Quality increasing

State –

Water Quality

State –

Landscape and

Natural Processes

Pressure –

Resource Use and Physical Stressors

State

– Aquatic –

Dependent Life

28

4.2

Full Indicator Reports

Air Temperature

Overall Assessment

Trend

:

Increasing

Rationale: Unavailable

Purpose

To assess trends in air temperature and to examine the observed evidence and effects of climate changes in and on the Great Lakes region.

The Air Temperature indicator is used in the Great Lakes indicator suite as a Pressure indicator in the

Resource Use and Physical Stressor top level reporting category.

Ecosystem Objective

The Great Lakes Water Quality Agreement Act’s General Objectives (1987) state, “these water should be free from materials and heat directly or indirectly entering the water as a result of human activity that...produces conditions that are toxic or harmful to human, animal, or aquatic life.” Furthermore, this indicator relates to Annex 1 of the

Great Lakes Water Quality Agreement which states, “there should be no change in temperature that would adversely affect any local or general use of the waters.”

Ecological Condition

Trends

According to the Intergovernmental Panel on Climate Change’s (IPCC) 2007 Synthesis report, “warming of the climate system is unequivocal, as is now evident from observations of increases in global average air and ocean temperatures, widespread melting of snow and ice, and rising global average sea level.” This finding is supported in part by global temperature data showing that of the last twelve years (1995-2007), eleven were among the warmest in the instrumental record of global surface temperature dating back to 1850

(Bernstein et al., 2007)

. At the local and regional scale climate data can be naturally quite variable

(Kling et al., 2003)

. As a result, the identification of the contribution of anthropogenic warming within long-term trends on this scale can be problematic. As most changes in the Great Lakes region are still within the bounds of natural variability, it can be difficult to definitively attribute observed trends to human induced climate change. Nevertheless, the similarity between regionally and globally observed trends supports a connection between observed changes in the basin and climatic shifts

(Hayhoe et al., 2009)

.

Based on the analysis of data from the National Climate Data Center (1985-2001) and the Midwest Climate Center

(1900-2000) of the Great Lakes region, over the last thirty years, temperatures have hovered near or slightly above long-term averages. The data also suggests a recent shift in temperature. In the last four years the annual average temperatures have ranged from 2 to 4

˚

F (1 to 2

˚

C) warmer than the long-term average with up to a 7

˚

F (4

˚

C) increase above average in the winter. It is important to note, however, that this warming is comparable in magnitude to warm periods experienced during the 1930s and 1950s. Furthermore, the hottest months in history have occurred in the past two decades and most years have been characterized by a decrease in cold waves

(Kling et al., 2003)

.

Based on the predictions of climate models, temperature in the region are expected to warm by 5 to 12

˚

F (3 to 7

˚

C) in the winter months and by 5 to 20

˚

F (3 to 11

˚

C) in the summer months. Examining the data at a finer resolution, models also suggest a larger increase in night-time temperatures than daytime temperatures and an increase in extreme heat events (Kling et al., 2003).

29

Data Source

Data from this report was generated using climate data from the NOAA climate divisions found in Table 1. These divisions were chosen based on an approximation of the boundaries of the Great Lakes basin.

Linkages

According to findings from the IPCC, “there is high confidence that recent regional changes in temperature have had discernible impacts on physical and biological systems.” In this report, the term ‘high confidence’ is characterized by an 8 out of 10 chance of being correct. Furthermore, there is ‘very high confidence’ (characterized by at least a 9 out of 10 chance of being correct) that species within terrestrial biological systems have already been strongly affected by earlier timing of spring events, bird migrations, and egg-laying, and poleward and upward range shifts in plant and animal species. With regard to freshwater systems, there is ‘high confidence’ that observed changes in aquatic biological systems are associated with increases in water temperature and, subsequently, related to alterations in ice cover, oxygen levels, and circulation. Observed changes include increases in algal and zooplankton abundance in high latitude lakes and range changes and temporal shifts in fish migration patterns

(Bernstein et al., 2007)

. This assessment is reflected in the Great Lakes region through trends indicating an earlier occurrence of the last spring freeze, to the magnitude of one week earlier than was experienced at the beginning of the 1990s, and a lengthening of the growing season over the past two decades (Kling et al., 2003).

Additional observed changes include:

Declines in the duration of winter ice (see

Ice Duration Report

)

Increases in surface water temperatures and a corresponding increase in the duration of the period of summer stratification (see

Surface Water Temperature Report

)(Kling et al., 2003)

Alterations of patterns of precipitation (see

Extreme Precipitation Indicator Report

)

The time in which plants bloom has been altered on the magnitude of two weeks earlier than in the early- to mid- 1900s (Glick, 2011)

Additional expected changes include:

Reduction in coldwater species such as lake trout, brook trout, and whitefish and cool-water species such as northern pike and walleye in southern parts of the basin. Conversely, the distribution of warm water fish such as smallmouth bass and bluegill are likely to expand northward

Increased likelihood of invasions from warm-water non-native species

Altered timing of hydrologic flows characterized by increased variability in timing, frequency, and duration of events

Altered distribution of plant distribution likely characterized by a northward shift in forest communities

Range shifts in insect species including such forest and agricultural pests as gypsy moths and bean leaf beetles (Kling et al., 2003)

Management Challenges/Opportunities

The realm of response options to address climate change is classified into two categories, the first of which is adaptation, or “initiatives and measures designed to reduce the vulnerability of natural and human systems against actual or expected climate change effects” (Koslow, 2010). Although a wide range of adaptation strategies exist, there are significant financial, technological, cognitive, behavioral, political, social, institutional, and cultural constraints resulting in limited implementation and effectiveness of adaptive strategies. Such limitations are apparent even in countries with high adaptive capacity as was showcased by the 2003 heat wave in Europe that resulted in significant human mortality, especially among the elderly population (Bernstein et al., 2007).

In the Great Lakes basin there has been significant progress in defining what adaptation means for conservation and restoration efforts in the region. For example, tools to help managers incorporate adaptation strategies into planning efforts have been developed by such organizations as the National Wildlife Federation, the Climate Adaptation

Knowledge Exchange, regional Sea Grant offices, NOAA, and Natural Resources Canada to name a few (Koslow,

30

2010 and Natural Resources Canada). A few examples of projects or programs which have integrated adaptive strategies into management processes include the following:

The Great Lakes-St Lawrence River Basin Water Resources Compact: The Compact is a law that required withdrawal standards be reviewed to, “give substantive consideration to climate change or other significant threats to Basin Waters and take into account the current state of scientific knowledge, or uncertainty, and appropriate measures to exercise cause in cases of uncertainty if serious damage may result” (Koslow, 2010).

City of Grand Rapids, Michigan: In the City, in order to adapt to changes in temperature, there is a plan to increase the percentage of tree canopy to reduce the urban heat island effect and thus the impact on human and ecological health from heat events (Koslow, 2010).

Despite relatively recent advances in the field of climate adaptation, there exist several limitations which present barriers to progress. In 2011, the National Wildlife Federation and the National Council for Science and the

Environment convened a meeting of 80 natural resource and climate change experts. These respondents included representation from federal agencies, state agencies, tribes, and non-profit organizations. Findings from this summit highlighted the current need for funding, downscaled climate information, planning guidance for adaptation projects, guidance on project implementation, and case studies of on-the-ground adaptation efforts (Inkley, 2011). These findings mirror those of the 2010 workshop, organized by the National Wildlife Federation, the Great Lakes

Commission, and the Council of Great Lakes Industries which drew representation from states and cities, federal agencies, Canada, the International Joint Commission, industry, environmental non-governmental groups, First

Nations, Tribes, and academic institutions titled Climate Change in the Great Lakes: Advancing the Regional

Discussion (Hinderer, 2010). Findings from this meeting suggest the need for the following actions to overcome barriers to success:

Increased application of climate science in on-the-ground restoration and protection efforts such as wildlife management, habitation restoration, and urban planning.

Increased focus on building cross-sector partnerships to increase knowledge sharing

Place increased emphasis quality of life improvement from climate change adaptation in order to better inform the public of the need and benefits of such actions

Increased use of economic incentives to increase the use of adaptive strategies (Hinderer, 2010)

The other way in which climate change can be addressed is through mitigation, or technological change and substitution that reduce resource inputs and emissions per unit of output (Koslow, 2010).

Both mitigation and adaptation strategies are necessary to lessen the future impacts of climate change. However, there is ‘high confidence’ that neither adaptation nor mitigation can eliminate all threats. Furthermore, in a scenario of unmitigated climate change, in the long-term it is likely that the capacity of the world’s natural, managed, and human systems to adapt will be severely limited. In other words, sole reliance on adaptation to address the impacts of climate change may result in the creation of a world in which the magnitude of the effects of climate change grow to the extent in which human and natural populations are either unable to adapt or confronted with solutions with very high social, environmental, and economic costs (Bernstein et al., 2007).

Assessing Data Quality

Data Characteristics

1. Data are documented, validated, or qualityassured by a recognized agency or organization

2. Data are traceable to original sources

Strongly

Agree

X

X

Agree

Neutral or

Unknown

Disagree

Strongly

Disagree

Not

Applicable

31

Data Characteristics

3. The source of the data is a known, reliable and respected generator of data

4. Geographic coverage and scale of data are appropriate to the Great Lakes basin

5. Data obtained from sources within the U.S. are comparable to those from Canada

6. Uncertainty and variability in the data are documented and within acceptable limits for this indicator report

Strongly

Agree

X

X

Agree

X

Neutral or

Unknown

Disagree

Strongly

Disagree

Not

Applicable

X

Acknowledgments

Authors:

Sarah Neville, ORISE Research Fellow Appointed to the U.S. Environmental Protection Agency Great Lakes

National Program Office

Contributors:

Deke Arndt, Chief, Climate Monitoring Branch, National Oceanic and Atmospheric Administration

Information Sources

(2011). Retrieved September 5, 2011, from Natural Resourcs Canada: http://adaptation.nrcan.gc.ca/index_e.php

Bernstein, L., Bosch, P., Canziani, O., & Chen, Z. (2007).

Climate Change 2007: Synthesis Report An Assessment of the Intergovernmental Panel on Climate Change.

Glick, P., Hoffman, J., Koslow, M., Kane, A., & Inkley, D. (2011).

Restoring the Great Lakes' Coastal Future

Technical Guidance for the Design and Implementation of Climate-Smart Restoration Projects.

Ann Arbor:

National Wildlife Federation.

Hayhoe, K., Croley II, T., VanDorn, J., Schlegal, N., & Wuebbles, D. (2009). Regional Cliamte Change Projections for Chicago and the US Great Lakes.

Journal of Great Lakes Research , 36

(2010), 7-21.

Hinderer, J., Haven, C., & Koslow, M. (2010).

Climate Change in the Great Lakes: Advancing the Regional

Discussion.

Kling, G., Hayhoe, J., Magnuson, J., Robinson, S., Shuter, B., Wander, M., et al. (2003).

Confronting Climate

Change in the Great Lakes region: Impacts on Our Communities and Ecosystems.

Union of Concerned Scientists and the Ecological Society of America.

Koslow, M. (2010).

Improving the Odds: using Climate-Readiness Planning to Reduce the Impacts of Climate

Change on the Great Lakes Ecosystem.

National Wildlife Federation.

List of Tables

Table 1

. Climate Divisions

Source: National Oceanic and Atmospheric Administration

List of Figures

Figure 1

. Trends in Air Temperature in the Great Lakes Basin.

Source: National Climate Data Center (1985-2001) and the Midwest Climate Center (1900-2000)

Last Updated

State of the Great Lakes 2011

32

State

Minnesota

Wisconsin

Illinois

Indiana

Michigan

Ohio

Pennsylvania

New York

Climate Division

3,6

1,2,3,6,9

2

1,2,3

1,2,3,4,5,6,7,8,9,10

1,2,3,4

10

1,9,10

Table 1

. Climate Divisions

Source: National Oceanic and Atmospheric Administration

Figure 1

. Trends in Air Temperature in the Great Lakes Basin.

Source: National Climate Data Center (1985-2001) and the Midwest Climate Center (1900-2000)

33

Aquatic Habitat Connectivity

Overall Assessment

Status: Fair

Trend: Improving

Rationale: Dams and barriers have been significantly impacting the health of aquatic ecosystems in the Great

Lakes for over a century and are a key factor in the decline of several species of fishes. In addition to limiting access of fishes to spawning and nursery habitats, loss of aquatic connectivity impacts nutrient flows and riparian and coastal processes. There are thousands of dams and barriers (road-stream, crossings) on Great Lakes tributaries. Many dams are near the end of their functional life and will need to be replaced or decommissioned in the next decade. Several dam mitigation projects are occurring throughout the basin, which are restoring aquatic connectivity. An increase interest in micro-hydro projects could result in additional dams, but in most cases these new projects include measures to provide for the passage of fish.

Lake-by-Lake Assessment

Lake Superior

Status: Fair

Trend: Improving

Rationale: A comprehensive assessment of barriers to aquatic connectivity has not been completed for Lake

Superior. The Lakewide Management Plan reports that a binational dataset has been created that includes dams and barriers to fish passage (Environment Canada and Environmental Protection Agency,

2011). Several dam mitigation projects have been proposed.

Lake Michigan

Status: Fair

Trend: Improving

Rationale: Aquatic habitat connectivity is being examined in the Biodiversity Conservation Strategy that was initiated in 2010. Several dam removal and mitigation projects have been initiated in the last few years through the Great Lakes Restoration Initiative (e.g. Boardman River dam removal will connect over 250 km of stream habitat back to Lake Michigan - the dam closest to the river mouth will be modified to allow for fish passage while blocking access for sea lamprey.)

Lake Huron

Status: Fair

Trend: Improving

Rationale: Status is based on the Lake Huron Biodiversity Conservation Strategy (Franks Taylor et al., 2010).

Expert review and opinion was used to determine that access to spawning areas is limiting the population size of migratory fishes. This report notes that one sub-basin (Eastern Georgian Bay) has a status of “good” (sufficient spawning habitat to maintain population) while another (Saginaw Bay) has a status of “poor” (spawning habitat is severely limiting population size).

Lake Erie

Status: Fair

Trend: Improving

Rationale: Aquatic habitat connectivity is being examined in the Biodiversity Conservation Strategy that was initiated in 2010. Several dam removal and mitigation projects have been initiated in the last few years through the Great Lakes Restoration Initiative (e.g. Ballville Dam on the Sandusky River will open up

35 km of river habitat for walleye).

34

Lake Ontario

Status: Fair

Trend: Improving

Rationale: Status is based on the Lake Ontario Biodiversity Conservation Strategy (Lake Ontario Biodiversity

Conservation Strategy Working Group, 2009). Expert review of maps developed for the migratory fishes target used to provide an assessment. Several dam mitigation projects have been initiated (e.g. dam removal in the Duffins Creek watershed by the Toronto Region Conservation Authority to improve access for Atlantic salmon).

Purpose

To determine the amount of accessible tributary habitat for Great Lakes fishes.

To summarize initiatives to improve connectivity of aquatic habitat.

To highlight some of the issues related to barrier removal.

The Aquatic Habitat Connectivity indicator is used in the Great Lakes indicator suite as a State indicator in the Landscapes and Natural Processes top level reporting category.

Ecosystem Objective

To reduce the impacts of barriers to aquatic connectivity on fish populations and nearshore/coastal health.

Dams and barriers have been identified as a significant threat in the Lake Ontario and Huron biodiversity conservation strategies (Franks Taylor et al., 2010) and have been identified as recovery actions for at risk Great

Lakes fishes such as for lake sturgeon (Golder Associates Ltd., 2011) and American eel (MacGregor, 2010).

Mitigation of this pressure will need to be assessed on case-by-case basis to ensure that barrier mitigation does not impact efforts to reduce the spread on aquatic invasive species and sea lamprey.

Ecological Condition

Background

Streams and rivers provide critical spawning and nursery habitat for over one-third of Great Lakes fishes. This includes walleye, lake sturgeon, (coaster) brook trout, suckers and native lamprey. Dams and barriers have been having a significant impact on the aquatic ecosystems of the Great Lakes for over a century and are a key factor in the decline of several species of fishes. As early as 1861, southern Ontario alone had over 2,000 mills reported in the annual census (Fischer & Harris, 2007). Accessibility to streams has been reduced by a variety of anthropogenic barriers such as dams, culverts at road-stream crossings and dikes. In addition to improvements for migratory fishes, improving aquatic connectivity can also have a number of benefits for restoring aquatic systems. These include: reducing water temperatures, increasing levels of oxygen, transport of nutrients and woody debris, restoring natural flood cycles and increasing the amount of riparian and coastal wetland cover.

Measure

Aquatic habitat connectivity can be measured at a landscape level though Geographical Information Systems by intersecting the hydrology network with dams. The distance between the Great Lake and the first barrier can be measured to provide an assessment of the amount of accessible riverine habitat that is available. Information on the distribution of dams can be obtained from the National Inventory of Dams (U.S. Army Corps of Engineers) and the

Ontario Dam Registry (Ontario Ministry of Natural Resources). More detailed spatial information on dams occurs for some lake basins and watersheds (e.g. Great Lakes Fisheries Commission, Conservation Authorities).

Road-stream crossings can also reduce aquatic habitat connectivity. While road-stream crossing can be easily identified by intersecting the hydrology network with roads (Figure 3), field verification is required to determine if the crossing do actually cause a disruption to connectivity (such as a “perched” culvert). In general, road-stream crossings are only an issue on small tributaries where culverts are installed.

35

Aquatic habitat connectivity is a pressure measure (i.e. it measures a threat). Other potential measures would include a direct measure of the population of key migratory fishes that will benefit from access to tributaries (e.g.

SOLEC has indicators for lake sturgeon and walleye). The number of barrier mitigation projects could also be measured as a response indicator.

Linkages

Sea Lamprey: Barrier mitigation must be coordinated with efforts to limit the access of seam lamprey to spawning areas.

Walleye and Sturgeon: Loss of aquatic connectivity has contributed to the decline of the species.

Watershed Stressor Index: The number of dams and barriers is an important factor in assessing watershed stress.

Management Challenges/Opportunities

There has been an increase in dam and barrier removal projects over the last few years. This activity has been initiated because of an increase in funding availability (e.g. Great Lakes Restoration Initiative) and because many dams are deteriorating. Most dams in the basin are 50 years+ will require repair or removal in the next decade to avoid failure. This presents a significant opportunity to restore aquatic habitat connectivity.

With the increase in interest in dam removal, there are now several Best Management Practices and assistance programs available in the U.S. and Ontario. While a comprehensive bi-national database of the dams in the basin, describing current use and ownership, does not exist, efforts in both countries may combine to produce this important source of information. For example, in Ontario an on-going province-wide inventory of dams will include a registration program by 2012.

Improvements in aquatic connectivity must be coordinated with efforts to limit the spread of aquatic invasive species, sea lamprey and VHS. Some dams and barriers may be a key management tool for mitigating these other pressures. Decisions about fish passage or dam removal need to be assessed on the basis of local conditions.

Comments from the author(s)

Improving access to spawning habitats is one of the key strategies to restoring populations of Great Lakes fishes.

While other pressures that had a major impact on fish populations in the past have had significant success, such as overfishing and water quality, basin-wide mitigation actions to restore the historic riverine spawning and nursery habitats is just beginning.

Assessing Data Quality

Data Characteristics

Strongly

Agree

Agree

Neutral or

Unknown

Disagree

Strongly

Disagree

Not

Applicable

1. Data are documented, validated, or quality-assured by a recognized agency or organization

2. Data are traceable to original sources

X

X

3. The source of the data is a known, reliable and respected generator of data

4. Geographic coverage and scale of data are appropriate to the Great Lakes basin

5. Data obtained from sources within the

U.S. are comparable to those from

Canada

X

X

X

6. Uncertainty and variability in the data are documented and within acceptable

X limits for this indicator report

Clarifying Notes: Information on barriers to aquatic connectivity is available, but not complete. Not all dams are included in the database, and current databases do not include information on fish passages.

36

Acknowledgments

Authors:

Dan Kraus, Nature Conservancy of Canada, Guelph ON ( [email protected]

)

Information Sources

Environment Canada and Environmental Protection Agency (2011).

Lake Superior Lakewide Management Plan

Annual Report.

U.S. Environmental Protection Agency and Environment Canada.

Fischer, G., & Harris, M. (2007).

Ontario's Historic Mills.

Erin, Ontario: Boston Mills Press.

Franks Taylor, R., A. Derosier, K. Dinse, P. Doran, D. Ewert, K. Hall, M. Herbert, M. Khoury, D. Kraus, A.

Lapenna, G. Mayne, D. Pearsall, J. Read, and B. Schroeder. 2010. The Sweetwater Sea: An International

Biodiversity Conservation Strategy for Lake Huron – Technical Report. A joint publication of The Nature

Conservancy, Environment Canada, Ontario Ministry of Natural Resources Michigan Department of Natural

Resources and Environment, Michigan Natural Features Inventory Michigan Sea Grant, and The Nature

Conservancy of Canada. 264 pp. with Appendices.

Golder Associates Ltd. (2011).

DRAFT Recovery Strategy for Lake Sturgeon (Acipenser fulvescens) – Northwestern

Ontario, Great Lakes-Upper St. Lawrence River and Southern Hudson Bay-James Bay populations in Ontario

Peterborough, Ontario: Ontario Ministry of Natural Resources.

Lake Ontario Biodiversity Conservation Strategy Working Group . (2009).

The Beautiful Lake - A Bi-national

Biodiversity Conservation Strategy for Lake Ontario.

U.S. Environmental Protection Agency and Environment

Canada.

MacGregor, R. J. (2010).

DRAFT Recovery Strategy for the American Eel (Anguilla rostrata) in Ontario.

Peterborough, Ontario.: Ontario Recovery Strategy Series. Prepared for Ontario Ministry of Natural Resources, .

Nature Conservancy of Canada. (2011).

Eastern Georgian Bay Coast Natural Area Conservation Plan

. Nature

Conservancy of Canada, Toronto.

List of Figures

Figure 1.

Aquatic Connectivity for Lake Ontario

Source: Lake Ontario Biodiversity Conservation Strategy Working Group (2009)

Figure 2.

Location of dams and accessible tributaries in Lake Huron

Source: Franks Taylor et al. (2010)

Figure 3.

Example of Road-Stream Crossing Analysis for Eastern Georgian Bay

Source: The Nature Conservancy of Canada (2011)

Last Updated

State of the Great Lakes 2011

37

Figure 1

. Aquatic Connectivity for Lake Ontario.

Source: Lake Ontario Biodiversity Conservation Strategy Working Group (2009)

38

Figure 2.

Location of dams and accessible tributaries in Lake Huron

Source: Franks Taylor et al. (2010)

39

Figure 3.

Example of Road-Stream Crossing Analysis for Eastern Georgian Bay

Source: The Nature Conservancy of Canada (2011)

40

Aquatic Non-Native Species

Overall Assessment

Status: Poor

Trend: Deteriorating

Rationale: Although no new aquatic nonindigenous species (ANS) have been discovered in the Great Lakes over the past five years, the impacts of established invaders persist and the ranges of ANS within the lakes are expanding. New negative impacts, including synergistic disruptions, are becoming evident.

Lake-by-Lake Assessment

Lake Superior

Status: Poor

Trend: Deteriorating

Rationale: Lake Superior is the site of greatest ballast water discharge in the Great Lakes, but this pathway has led to comparatively fewer ANS establishments. Intrabasin movement of ANS is likely to be of greater consequence, as in the case of recent establishment of Viral Hemorrhagic Septicemia (VHS).

Lake Michigan

Status: Poor

Trend: Deteriorating

Rationale: Established invaders continue to exert negative impacts on native species.

Diporeia

populations continue to decline and are rarely found at shallow sites. Viral Hemorrhagic Septicemia (VHS) has recently become established in this lake.

Lake Huron

Status: Poor

Trend: Deteriorating

Rationale: Established invaders continue to exert negative impacts on native species.

Diporeia

populations continue to decline and are rarely found at shallow sites.

Lake Erie

Status: Poor

Trend: Deteriorating

Rationale: Established invaders continue to exert negative impacts on native species. A possible link exists between waterfowl deaths due to botulism and established ANS (i.e. round goby and dreissenids). Viral

Hemorrhagic Septicemia has caused mass die-offs of fish.

Diporeia

has been extirpated.

Lake Ontario

Status: Poor

Trend: Deteriorating

Rationale: Native

Diporeia

populations, and the condition and growth of lake whitefish, continue to decline. At shallow sites,

Diporeia

is now absent. A possible link exists between waterfowl deaths due to botulism and established ANS. Viral Hemorrhagic Septicemia has caused mass die-offs of fish.

Purpose

To assess the presence, number, and distribution of aquatic nonindigenous species (ANS) in the Laurentian

Great Lakes, and to understand the means by which these species are introduced

41

To aid in the assessment of the status of biotic communities, as ANS alter both the structure and function of ecosystems thereby compromising the biological integrity of these systems

Ecosystem Objective

The goal of the United States and Canadian Great Lakes Water Quality Agreement (GLWQA) of 1987 is, in part, to restore and maintain the biological integrity of the Great Lakes ecosystem . Fundamental to this goal is to control existing, and prevent further introduction of, aquatic nonindigenous species through tracking the number of invasions and pathways of introduction. Note: the renewed GLWQA of 2012 includes an Annex on Aquatic

Invasive Species.

Ecological Condition

Background

The National Oceanic and Atmospheric Administration (NOAA) currently reports a total of 184 Great Lakes ANS.

At least 10% of all ANS introduced to the Great Lakes have had significant impacts on ecosystem health, a percentage consistent with findings in the United Kingdom (Williamson and Brown 1986) and in the Hudson River of North America (Mills et al. 1997). However, considering socioeconomic as well as environmental impacts, this percentage appears to be considerably higher (18%). In the Great Lakes, transoceanic ships have been the primary invasion vector. Other vectors, such as canals, intrabasin transport, and private sector activities (e.g., aquarium and bait industries), however, may play increasingly important roles. Considering the high costs of ANS control, prevention of new introductions continues to be the most effective and economically viable strategy mitigating this ecosystem pressure.

Status of ANS

The total number of ANS introduced and established in the Great Lakes has increased steadily since the 1830s, with some indication of stabilization over the last five years (Fig. 1a). Although there have been 34 invasions since the

GLWQA was signed in 1987, no new species have been discovered since 2006. Furthermore, more invasions occurred in the decades from 1950 to 2000 than the preceding or most recent decades. Release of contaminated ballast water by transoceanic ships has been implicated in 65% of faunal ANS introductions to the Great Lakes since the opening of the St. Lawrence Seaway in 1959 (Grigorovich et al. 2003; Ricciardi 2006), although this trend may also be slowing (Fig. 1b).

NOAA-developed impact assessment tool (GLANSIS in prep.) has been applied to 147 of the Great Lakes’ 184 established ANS. Briefly, this questionnaire-style assessment considered three main categories of impact: environmental, socio-economic, and beneficial. Scores under criteria for each impact category were determined based on literature review and expert evaluation, with the results assigned a qualitative score of High, Moderate,

Low, or Unknown. Of the species assessed to date, 16% have had high environmental impacts, 6% have had high socioeconomic impacts (all but 2 all also had high environmental impact), and 6% have had high beneficial effects

(7 of which also had high environmental impact) (Table 1).

The overall economic impact of ANS on the Great Lakes region—spanning direct operating costs, decreased productivity, and reduced demand within sport and commercial fishing, power generation, industrial facilities, tourism and recreation, water treatment, and households—is estimated at well over $100 million annually (Rosaen et al. 2012). This figure includes both basinwide efforts such as that of Great Lakes Fishery Commission’s sea lamprey control program, with an annual budget of about $18 million, and local responses, such as the $1,040-$26,000 cost per acre of Eurasian watermilfoil removal (Rosaen et al. 2012). Economic impacts from dreissenid mussel control and monitoring are estimated at $1.2 million annually per power plant, $1.97 million for removal of 400 yd

3

at a paper plant, and $480,000-$540,000 annually at a water treatment plant (Rosaen et al. 2012).

Recent studies suggest that each of the Great Lakes may differ in vulnerability to invasion. Lake Superior receives a

42

disproportionately high number of discharges by both BOB and NOBOB ships, yet it has sustained surprisingly few initial invasions (Fig. 2). Conversely, the corridor connecting Lake Huron and Lake Erie is an invasion ‘hotspot’ despite receiving disproportionately few ballast discharges (Grigorovich et al. 2003). The greatest number of ANS range expansion species (native or cryptogenic to a portion of the basin but introduced to other areas of the basin) have become established in Lake Superior and Lake Huron, suggesting that intrabasin movement of species should not be ignored. Other vectors, including canals and the private sector, continue to deliver ANS to the Great Lakes and may increase in relative importance in the future.

Human activities associated with transoceanic shipping are responsible for over one-third of ANS introductions to the Great Lakes (Fig. 3). During the 1980s, the importance of ship ballast water as a vector for ANS introductions was recognized, prompting ballast management measures in the Great Lakes. In the wake of Eurasian ruffe and zebra mussel introductions, Canada introduced voluntary ballast exchange guidelines in 1989 for ships declaring

“ballast on board” (BOB) following transoceanic voyages; this action followed recommendations by the Great

Lakes Fishery Commission and the International Joint Commission. In 1990, the United States Congress passed the

Nonindigenous Aquatic Nuisance Prevention and Control Act, producing the Great Lakes’ first ballast exchange and management regulations in May of 1993. The National Invasive Species Act (NISA) followed in 1996, but this act expired in 2002. A stronger version of NISA entitled the Nonindigenous Aquatic Invasive Species Act has been drafted and awaits Congressional reauthorization. In September 2009, the U.S. Coast Guard proposed a two-phase standard for the allowable concentration of living organisms in ballast water discharge within U.S. waters. If proven practical, this rule would be implemented by 2016 and include discharge standards that are 1000x more restrictive than the International Maritime Organization standards (less than 10 viable organisms per cubic meter) ratified by

Canada and 24 other countries.

Following initiation of voluntary guidelines in 1989 and mandated regulations in 1993, the overall rate of Great

Lakes invasion did not decline until recently (Grigorovich et al. 2003; Holeck et al. 2004; Ricciardi 2006). However, more than 90% of transoceanic ships that entered the Great Lakes during the 1990s declared “no ballast on board”

(NOBOB; Colautti et al. 2003; Grigorovich et al. 2003; Holeck et al. 2004; Fig. 4) and were not required to exchange ballast, despite their tanks containing residual sediments and water that could be discharged in the Great

Lakes. Residual water and sediment in these ships have been found to contain several species previously unrecorded in the basin; such species could be discharged after the ship undergoes sequential ballasting operations as it travels between ports within the Great Lakes to offload and take on cargo (Duggan et al. 2005, Ricciardi and MacIsaac

2008). In June 2006, Canada implemented new regulations for the management of residuals contained within

NOBOB tanks and requires the salinity of all incoming ballast water to be at least 30 ppt (Government of Canada

2006). In the decade since, we have seen no new ballast water ANS introductions (the last being

Hemimysis anomala,

collected in May 2006) despite a fairly steady number of NOBOB transits.

Second only to shipping, unauthorized release, transfer, and escape have introduced ANS into the Great Lakes. Of particular concern are private sector activities related to aquaria, garden ponds, baitfish, and live food fish markets.

Silver and bighead carp escapees from southern United States fish farms have developed large populations in the middle and lower segments of the Illinois River, which connects the Mississippi River to Lake Michigan via the

Chicago Sanitary and Ship Canal (CSSC). A prototype electric barrier on the CSSC was activated in April 2002 to block the transmigration of species between the Mississippi River system and the Great Lakes basin. The U.S. Army

Corps of Engineers (partnered by the State of Illinois) completed construction of second and third permanent barriers in 2005 and 2011, respectively. Since 2009, environmental DNA (eDNA) surveillance has been used to complement the use of traditional monitoring and suppression tools. Between 2009 and 2010, DNA of both bighead and silver carp was detected past the electric barriers; however, only a single bighead carp was subsequently found

(Lake Calumet, June 2010). As of August of the 2011 monitoring year, only silver carp DNA had been detected on the lake side of these barriers for that year; despite an intensive sampling effort in response to three consecutive

43

rounds of positive eDNA tests in the Lake Calumet area, no Asian carp were seen or captured.

Nearly a million Asian carp, including bighead and black carp, are sold annually at fish markets within the Great

Lakes basin. Until recently, most of these fish were sold live. All eight Great Lakes states and the province of

Ontario now have some restriction on the sale of live Asian carp. Enforcement of many private transactions, however, remains a challenge. The U.S. Fish and Wildlife Service published a final rule in March 2011, officially adding the bighead carp to the federal injurious wildlife list and codifing the Asian Carp Prevention and Control Act.

Bighead, silver, and black carp are now listed as nuisance species under the Lacey Act, prohibiting interstate transport. There are currently numerous shortcomings in legal safeguards relating to commerce in exotic live fish in

Great Lakes and Mississippi River states, Quebec, and Ontario, as identified by Alexander (2003). These include: express and de facto exemptions for the aquarium pet trade; de facto exemptions for the live food fish trade; inability to proactively enforce import bans; lack of inspections at aquaculture facilities; allowing aquaculture in public waters; inadequate triploidy (sterilization) requirements; failure to regulate species of concern (e.g., Asian carp); regulation through “dirty lists” only (e.g., banning known nuisance species); and failure to regulate transportation.

Linkages

Invasion Meltdown: Evidence indicates that newly invading species may benefit from the presence of previously established invaders. That is, the presence of one ANS may facilitate the establishment or population growth of another (Ricciardi 2001). For example, the sea lamprey (

Petromyzon marinus

) may have created enemy-free space that facilitated the alewife’s (

Alosa pseudoharengus

) invasion, and the round goby (

Neogobius melanostomus

) and

Echinogammarus ischnus

(amphipod) have thrived in the presence of previously established zebra (

Dreissena polymorpha

) and quagga mussels (

Dreissena bugensis

). In effect, dreissenids have set the stage to increase the number of successful invasions, particularly those of co-evolved species in the Ponto-Caspian assemblage.

[Indicators: Sea Lamprey, Dreissenid Mussels]

Multi-stressors: Changes in water quality, global climate change, and land use also may make the Great Lakes more hospitable for the arrival of new invaders. [Indicators: Nutrients in Lakes, Dissolved Oxygen, Water Clarity]

Secondary Shifts in Native Populations: ANS may exert significant direct and indirect pressures upon native species, including facilitation of parasitism, transmission of viral/bacterial infections, magnification of toxins, competition, food-web alteration, genetic introgression, degradation of water quality, and degradation of physical habitat. ANS have promoted the proliferation of native nuisance species, including cyanobacteria (Skubinna et al. 1995;

Vanderploeg et al. 2001). [Indicators: Wetland Species, Lake Trout, Walleye, Preyfish, Benthos,

Diporeia

,

Zooplankton Biomass and Health, Threatened Species, Sturgeon, Botulism Outbreaks, Fish Disease Occurrences,

Harmful Algal Blooms,

Cladophora

]

Aquatic Habitat Connectivity: The potential for ANS to colonize new locations is increased with removal of dams.

In contrast, ecological separation of the Great Lakes from the Mississippi River basin is currently being discussed as a way to limit transfer of ANS between these basins.

Fish Habitat: Many nonindigenous plants are capable of forming dense mats that may exclude fish from nearshore habitats. Colonization of lakebed areas by dreissenid mussels and the consequent filling of remaining interstitial spaces with pseudofeces and fine-grained sediments led to the exclusion of lake trout from their native spawning grounds (S. Mackey, Habitat Solutions NA, pers. comm.).

Management Challenges/Opportunities

ANS have invaded the Great Lakes basin from regions around the globe (Fig. 5). Increasing world trade and travel elevates the risk that additional species (Table 2) will continue to gain access to the Great Lakes. Indeed, the arrival of

Hemimysis anomala

was predicted (Ricciardi and Rasmussen 1998). Existing connections between the Great

44

Lakes watershed and systems outside the watershed, such as the Chicago Sanitary and Ship Canal, and growth of industries such as aquaculture, live food markets, and aquarium retail stores will also increase the risk that new ANS will be introduced.

Researchers are seeking to better understand links between vectors and donor regions, the receptivity of the Great

Lakes ecosystem, and the biology of new invaders in order to make recommendations to reduce the risk of future invasion. To protect the biological integrity of the Great Lakes, it is essential to closely monitor routes of entry for

ANS, to introduce effective safeguards, and to quickly adjust safeguards as needed. The rate of invasion may increase if positive interactions involving established ANS or native species facilitate the establishment of new

ANS. Ricciardi (2001) suggested that such a scenario of “invasional meltdown” is occurring in the Great Lakes, although Simberloff (2006) cautioned that most of these cases have not been well substantiated. Moreover, each new invader can interact in unpredictable ways with previously established invaders, potentially creating synergistic impacts (Ricciardi 2001, 2005). For example, recurring outbreaks of avian botulism in the lower Great Lakes are thought to result from the effects of dreissenid mussels and round gobies, in which the mussels create environmental conditions that promote the pathogenic bacterium and the gobies transfer bacterial toxin from the mussels to higher levels of the food web.

To be effective in preventing new invasions, management strategies must focus on linkages between ANS, vectors, and donor and receiving regions, and have available to them resources in support of early detection and rapid response. However, without measures that effectively eliminate or minimize the role of ship-borne and other emerging vectors (such as live trade and recreational boating, see Mandrak and Cudmore 2010), we can expect the number of ANS in the Great Lakes to continue to rise, with an associated loss of native biodiversity and an increase in unforeseen ecological disruptions. Furthermore, increasing lake temperatures associated with climate change will lead to increased potential for ANS introduced from warmer climates to establish overwintering populations (see

Adebayo et al. 2011; Mandrak 1989).

Comments from the author(s)

Lake-by-lake assessments should include Lake St. Clair and connecting channels (Detroit River, St. Clair River).

Species first discovered in these waters were assigned to Lake Erie for the purposes of this report. Moreover, range expansion ANS (those native or cryptogenic to a portion of the basin but introduced to other areas of the basin) should be included in lake-by-lake assessments and perhaps incorporated into future figures. Environmental and socioeconomic impacts, as well as beneficial effects of ANS should also receive additional treatment (e.g., Table 1).

In preliminary reviews of this report, it was suggested that there also be a discussion of prevention, spread, and control options for ANS. However, that sort of information would shift the focus from a Great Lakes ecosystem pressure indicator to one of response. The National Oceanic and Atmospheric Administration (NOAA) Great Lakes

Aquatic Nonindigenous Species Information System (GLANSIS) is already in the process of compiling management options for each introduced and high risk “watchlist” species and could help support future integration of that information into one of the existing response indicator reports (e.g., “Protecting and Restoring Habitat and

Species”).

Assessing Data Quality

Data Characteristics

Strongly

Agree

Agree

Neutral or

Unknown

Disagree

Strongly

Disagree

Not

Applicable

1. Data are documented, validated, or qualityassured by a recognized agency or organization

2. Data are traceable to original sources

X

X

45

Data Characteristics

Strongly

Agree

Agree

Neutral or

Unknown

Disagree

Strongly

Disagree

Not

Applicable

3. The source of the data is a known, reliable and respected generator of data

4. Geographic coverage and scale of data are appropriate to the Great Lakes basin

X

X

5. Data obtained from sources within the U.S. are comparable to those from Canada

X

6. Uncertainty and variability in the data are documented and within acceptable limits for X this indicator report

Clarifying Notes: Assessment data in Tables 1 and 2 are currently in the process of being collected and reviewed; completion is expected in 2013.

Acknowledgments

Authors:

Abigail J. Fusaro, NOAA Great Lakes Environmental Research Laboratory, Ann Arbor, MI

Kristen T. Holeck, Department of Natural Resources, Cornell University, Bridgeport, NY

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Bioscience

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Water as Vectors for Non-indigenous Species Introductions to the Great Lakes

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Atmospheric Administration, Great Lakes Environmental Research Laboratory, and University of Michigan,

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Cooperative Institute for Limnology and Ecosystems Research, Ann Arbor. 287 pp. Available at http://www.glerl.noaa.gov/res/projects/nobob/products/NOBOBFinalReport.pdf

Kipp, R., Bailey, S.A., MacIsaac, H., and Ricciardi, A. 2010. Transoceanic ships as vectors for nonindigenous freshwater bryozoans.

Diversity and Distributions

16:77-83.

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Science

298:1233-1236.

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Hypophthalmichthys

(Pisces, Cyprinidae) - A biological synopsis and environmental risk assessment.

Report to US Fish and Wildlife Service per Interagency Agreement 94400-3-0128

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Mandrak, N.E. 1989. Potential invasion of the Great Lakes by fish species associated with climatic warming.

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Great Lakes Res

. 15:306-316.

Mendoza-Alfaro, R.E., Cudmore, B., Orr, R., Fisher, J.P., Balderas, S.C., Courtenay, W.R., Osorio, P.K., Mandrak,

N., Torres, P.A., Damián, M.A., Gallardo, C.E., Sanguinés, A.G., Greene, G., Lee, D., Orbe-Mendoza, A.,

Martínez, C.R., and Arana, O.S.. 2009.

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Mills, E.L., Leach, J.H., Carlton, J.T., and Secor, C.L. 1993. Exotic species in the Great Lakes: A history of biotic crises and anthropogenic introductions.

J. Great Lakes Res

. 19(1):1-54.

Mills, E.L., Scheuerell, M.D., Carlton, J.T., and Strayer, D.L. 1997. Biological invasions in the Hudson River. NYS

Museum Circular No. 57. Albany, NY.

Ricciardi, A. 2001. Facilitative interactions among aquatic invaders: is an “invasional meltdown” occurring in the

Great Lakes?

Can. J. Fish. Aquat. Sci

. 58:2513-2525.

Ricciardi, A. 2005. Facilitation and synergistic interactions among introduced aquatic species. In Invasive Alien

Species: A New Synthesis. H.A. Mooney, R.N. Mack, J. McNeely, L.E. Neville, P.J. Schei, and J.K. Waage, eds., pp. 162–178. Washington, DC: Island Press.

Ricciardi, A. 2006. Patterns of invasions in the Laurentian Great Lakes in relation to changes in vector activity.

Diversity and Distributions

12:425-433.

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Lakes.

Ecol. Appl

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Ricciardi, A., and Rasmussen, J.B. 1998. Predicting the identity and impact of future biological invaders: a priority for aquatic resource management.

Can. J. Fish. Aquat. Sci

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Rixon, C.A.M., Duggan, I.C., Bergeron, N.M.N., Ricciardi, A., and MacIsaac, H.J. 2005. Invasion risks posed by the aquarium trade and live fish markets on the Laurentian Great Lakes.

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Lakes states. Report prepared by the Anderson Economic Group LLC.

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Ecol. Letters

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List of Tables

Table 1

. Nonindigenous species assessed to have the greatest environmental, socioeconomic, and/or beneficial

47

impacts in the Great Lakes. This list represents an update to Mills (1993) categorization of invasive species in the

Great Lakes. (Note: As of report preparation, 147 of 184 established species had been assessed. The remaining assessments are targeted for completion by NOAA/GLANSIS in 2013.)

Source: Great Lakes Aquatic Nonindigenous Species Information System, http://www.glerl.noaa.gov/res/Programs/glansis/glansis.html (in prep.)

Table 2

. Nonindigenous species predicted in the scientific literature to have a high probability of introduction to the

Great Lakes. Probability of introduction, establishment, and predicted level of impact (Environmental,

Socioeconomic, Beneficial) are given as High, Moderate, Low, or Unknown. (Note: As of report preparation, detailed risk assessments on each species were incomplete. Missing assessments are targeted for completion by

NOAA/GLANSIS in 2013.)

Source: Adebayo et al. 2011; Bailey et al. 2005; Cole 2001; Cudmore and Mandrak 2005; Cudmore-Vokey and

Crossman 2000; Great Lakes Aquatic Nonindigenous Species Information System, http://www.glerl.noaa.gov/res/Programs/glansis/glansis.html (in prep.); Grigorovich et al. 2003; Herborg et al. 2007;

Johengen et al. 2005; Kipp et al. 2010; Kolar and Lodge 2002; Kolar et al. 2005; Mandrak 1989; Mendoza-Alfaro et al. 2009; A. Ricciardi, McGill University; Ricciardi and Rasmussen 1998; Rixon et al. 2005; Stepien and Tumeo

2006; U.S. EPA 2008.

List of Figures

Figure 1

. Cumulative number of aquatic nonindigenous species (ANS) established in the Great Lakes basin since the 1830s attributed to (a) all vectors and (b) only the ship vector.

Source: Grigorovich et al. 2003; Mills et al. 1993; Ricciardi 2001; Ricciardi 2006.

Figure 2

. Release mechanisms for aquatic nonindigenous species (ANS) established in the Great Lakes basin since the 1830s. Unintentional release encompasses ornamental plant escape, research escape, and parasites/pathogens through fish stocking.

Source: Great Lakes Aquatic Nonindigenous Species Information System, http://www.glerl.noaa.gov/res/Programs/glansis/glansis.html; Grigorovich et al. 2003; Mills et al. 1993; Ricciardi

2001; Ricciardi 2006.

Figure 3

. Lake of first discovery for ANS established in the Great Lakes basin since the 1830s.

Discoveries in connecting waters between Lakes Huron, Erie, and Ontario were assigned to the downstream lake.

Species that were widespread at the time of discovery were assigned to the unknown category.

Source: Great Lakes Aquatic Nonindigenous Species Information System, http://www.glerl.noaa.gov/res/Programs/glansis/glansis.html.

Figure 4

. Numbers of upbound transoceanic ballasted (BOB) and cargo laden (NOBOB) vessels entering the Great

Lakes from 1959 to 2010.

Source: Colautti et al. 2003; Grigorovich et al. 2003; Holeck et al. 2004; Saint Lawrence Seaway Development

Corporation Annual Traffic Reports, http://www.greatlakes-seaway.com/en/seaway/facts/traffic/index.html.

Figure 5

. Regions of origin for aquatic nonindigenous species (ANS) established in the Great Lakes basin since the

1830s.

Source: Great Lakes Aquatic Nonindigenous Species Information System, http://www.glerl.noaa.gov/res/Programs/glansis/glansis.html; Grigorovich et al. 2003; Mills et al. 1993; Ricciardi

2001; Ricciardi 2006.

Last Updated

State of the Great Lakes 2011

48

Table 1. Nonindigenous species assessed to have the greatest environmental, socioeconomic, and/or beneficial impacts in the Great Lakes.

Species Common Name

Environmental

Impact

Socio-

Economic

Impact

Beneficial

Effect

Alosa pseudoharengus

alewife High High High

Bithynia tentaculata

Bythotrephes longimanus

faucet snail spiny waterflea

High

High

Moderate

Low

Low

Low

Cercopagis pengoi

Cyprinus carpio

Dreissena polymorpha

Dreissena rostriformis bugensis

Echinochloa crus-galli

Frangula alnus

Heterosporis

sp.

Ichthyocotylurus pileatus

Iris pseudacorus

Morone americana

Myxobolus cerebralis

Neogobius melanostomus

Nitellopsis obtusa

Novirhabdovirus

sp. VHSV-IVb

Oncorhynchus kisutch

Oncorhynchus mykiss

Oncorhynchus tshawytscha

Osmerus mordax

Petromyzon marinus

Ranavirus

sp.

Rhabdovirus carpio

Renibacterium salmoninarum

Salmo trutta

fishhook waterflea common carp zebra mussel quagga mussel barnyard grass glossy buckthorn microsporidian parasite digenean fluke yellow iris white perch salmonid whirling disease round goby starry stonewort viral hemorrhagic septicemia virus coho salmon rainbow trout

Chinook salmon rainbow smelt sea lamprey largemouth bass virus spring viremia of carp bacterial kidney disease brown trout

High

High

High

High

Moderate

High

High

High

High

High

High

High

Moderate

High

Moderate

High

Moderate

High

High

High

High

High

High

High

Low

Low

Low

Unknown

High

Low

Low

High

Low

Low

Unknown

High

High

High

Low

Low

Low

Moderate

Moderate

Low

High

High

High

High

High

High

Low

Low

Low

Low

High

Low

High

Low

Low

Moderate

Moderate

Low

Low

Moderate

High

Low

Low

Low

Low

Typha angustifolia

narrow-leaved cattail High Low High

This list represents an update to Mills (1993) categorization of invasive species in the Great Lakes. (Note: As of report preparation, 147 of 184 established species had been assessed. The remaining assessments are targeted for completion by NOAA/GLANSIS in 2013.)

Source: Great Lakes Aquatic Nonindigenous Species Information System, http://www.glerl.noaa.gov/res/Programs/glansis/glansis.html

(in prep.)

49

Table 2 Nonindigenous species predicted in the scientific literature to have a high probability of introduction to the Great Lakes.

2.1 Non-indigenous Fish Species

Species

Alburnus alburnus

Atherina boyeri

Babka gymnotrachelus

Benthophilus stellatus

Channa argus

Predicted pathway (source)

ballast water

(Eurasia) ballast water

(Eurasia) ballast water

(Eurasia) ballast water

(Eurasia) unintentional release (Asia)

Clupeonella cultriventris

Cottus gobio

Ctenopharyngodon idella

Cyprinella whipplei

Hypophthalmichthys molitrix

Hypophthalmichthys nobilis

Knipowitschia caucasica

Leuciscus leuciscus

Neogobius fluviatilis

Oncorhynchus keta

Perca fluviatilis

Perccottus glenii

Phoxinus phoxinus

Rutilus rutilus

ballast water

(Eurasia) ballast water

(Eurasia) canal (Mississippi basin) canal (Mississippi basin) canal (Mississippi basin) canal (Mississippi basin) ballast water

(Eurasia) ballast water

(Eurasia) ballast water

(Eurasia) deliberate release

(Pacifique) ballast water

(Eurasia) ballast water

(Eurasia) ballast water

(Eurasia) ballast water

(Eurasia)

Probability of

Introduction

Low

Probability of

Establishment

High

Probability of

Impact (E/S/B)

High/Low/High

Unk./Mod./High

High/Low/High

High/High/High

High/High/High

High/Low/Mod.

Reference

Kolar and Lodge 2002

Kolar and Lodge 2002

Kolar and Lodge 2002; Stepien and

Tumeo 2006

Kolar and Lodge 2002; Ricciardi and

Rasmussen 1998

Cudmore and Mandrak 2005;

Herborg et al. 2007; Mendoza-Alfaro et al. 2009; Rixon et al. 2005

Kolar and Lodge 2002; Ricciardi and

Rasmussen 1998

Kolar and Lodge 2002

Herborg et al. 2007; Mandrak and

Cudmore 2005; Rixon et al. 2005

Cudmore-Vokey and Crossman

2000; Mandrak 1989

Herborg et al. 2007; Kolar and Lodge

2002; Kolar et al. 2005; Mandrak and

Cudmore 2005

Herborg et al. 2007; Kolar et al.

2005; Mandrak and Cudmore 2005;

Rixon et al. 2005

Kolar and Lodge 2002

Kolar and Lodge 2002

Kolar and Lodge 2002; Ricciardi and

Rasmussen 1998

Kolar and Lodge 2002

Kolar and Lodge 2002

A. Ricciardi pers. comm.

Kolar and Lodge 2002

Kolar and Lodge 2002

2.2 Non-indigenous Cladocerans

Species

Cornigerius maeoticus maeoticus

Daphnia cristata

Podonevadne trigona ovum

Predicted pathway (source)

ballast water

(Eurasia) ballast water

(Eurasia) ballast water

(Eurasia)

Probability of

Introduction

2.3 Non-indigenous Copepods

Species

Calanipeda aquaedulcis

Cyclops kolensis

Ectinosoma abrau

Heterocope appendiculata

Heterocope caspia

Paraleptastacus spinicaudus triseta

Predicted pathway (source)

ballast water

(Eurasia) ballast water

(Eurasia) ballast water

(Eurasia) ballast water

(Eurasia) ballast water

(Eurasia) ballast water

(Eurasia)

Probability of

Introduction

Probability of

Establishment

Probability of

Impact (E/S/B)

Reference

Grigorovich et al. 2003

Grigorovich et al. 2003

Grigorovich et al. 2003

Probability of

Establishment

Probability of

Impact (E/S/B)

Reference

Grigorovich et al. 2003

Grigorovich et al. 2003

Grigorovich et al. 2003

Grigorovich et al. 2003

Grigorovich et al. 2003

Grigorovich et al. 2003

50

2.4 Non-indigenous Amphipods

Species Predicted pathway (source)

Chelicorophium curvispinum

Dikerogammarus haemobaphes

Dikerogammarus villosus

Echinogammarus warpachowskyi

Obesogammarus aralensis

Obesogammarus crassus

Obesogammarus obesus

Pontogammarus robustoides

ballast water

(Eurasia) ballast water

(Eurasia) ballast water

(Eurasia) ballast water

(Eurasia) ballast water

(Eurasia) ballast water

(Eurasia) ballast water

(Eurasia) ballast water

(Eurasia)

Probability of

Introduction

High

2.5 Non-indigenous Mysids

Species Predicted pathway (source)

Limnomysis benedeni

Paramysis (Mesomysis) intermedia

Paramysis

(Serrapalpisis) lacustris

Paramysis (Metamysis) ullskyi

ballast water

(Eurasia) ballast water

(Eurasia) ballast water

(Eurasia) ballast water

(Eurasia)

Probability of

Introduction

2.6 Non-indigenous Bivalves

Species

Monodacna colorata

Predicted pathway (source)

ballast water

(Eurasia)

Probability of

Introduction

2.7 Non-indigenous Polychaetes

Species

Hypania invalida

Leyogonimus polyoon

Predicted pathway (source)

ballast water

(Eurasia) canal (Mississippi basin)

Probability of

Introduction

Moderate

Probability of

Establishment

High

Probability of

Impact (E/S/B)

High/Low/Low

Reference

Ricciardi and Rasmussen 1998

Grigorovich et al. 2003; Ricciardi and

Rasmussen 1998

Grigorovich et al. 2003; Ricciardi and

Rasmussen 1998

Grigorovich et al. 2003

Grigorovich et al. 2003

Ricciardi and Rasmussen 1998

Ricciardi and Rasmussen 1998

Grigorovich et al. 2003; Ricciardi and

Rasmussen 1998

Probability of

Establishment

Probability of

Impact (E/S/B)

Mod./Low/Unk.

Reference

Ricciardi and Rasmussen 1998

Ricciardi and Rasmussen 1998

Ricciardi and Rasmussen 1998

Ricciardi and Rasmussen 1998

Probability of

Establishment

Probability of

Impact (E/S/B)

Reference

Ricciardi and Rasmussen 1998

Probability of

Establishment

High

Probability of

Impact (E/S/B)

Reference

Ricciardi and Rasmussen 1998

Cole 2001

2.8 Non-indigenous Bryozoans

Species Predicted pathway (source)

Fredericella sultana

ballast water

(Europe)

Probability of

Introduction

Probability of

Establishment

Probability of

Impact (E/S/B)

High/High/Unk.

Reference

Kipp et al. 2010

2.9 Non-indigenous Rotifers

Species Predicted pathway (source)

Brachionus leydigii

Filinia cornuta

Filinia passa

ballast water

(widespread) ballast water

(widespread) ballast water

(widespread)

Probability of

Introduction

2.10 Non-indigenous Plants

Species

Egeria densa

Eichhornia crassipes

Hydrilla verticillata

Predicted pathway

(source)

unintentional release

(S. America) unintentional release

(S. America) unintentional release

(widespread)

Probability of

Introduction

Probability of

Establishment

Probability of

Impact (E/S/B)

Reference

Bailey et al. 2005; Johengen et al.

2005

Bailey et al. 2005; Johengen et al.

2005

Bailey et al. 2005; Johengen et al.

2005

Probability of

Establishment

Probability of

Impact (E/S/B)

Reference

Rixon et al. 2005

Adebayo et al. 2011

U.S. EPA 2008

51

Species

Hygrophila polysperma

Myriophyllum aquaticum

Pistia stratiotes

Predicted pathway

(source)

unintentional release

(Asia) unintentional release

(S. America) unintentional release

(S. America)

Probability of

Introduction

High

Probability of

Establishment

High

Probability of

Impact (E/S/B)

Mod./Mod./Low

High/Mod./Low

Reference

Rixon et al. 2005

Rixon et al. 2005

Adebayo et al. 2011

Table 2

Probability of introduction, establishment, and predicted level of impact (Environmental, Socioeconomic,

Beneficial) are given as High, Moderate, Low, or Unknown. (Note: As of report preparation, detailed risk assessments on each species were incomplete. Missing assessments are targeted for completion by

NOAA/GLANSIS in 2013.)

Source: Adebayo et al. 2011; Bailey et al. 2005; Cole 2001; Cudmore and Mandrak 2005; Cudmore-Vokey and

Crossman 2000; Great Lakes Aquatic Nonindigenous Species Information System, http://www.glerl.noaa.gov/res/Programs/glansis/glansis.html

(in prep.); Grigorovich et al. 2003; Herborg et al. 2007;

Johengen et al. 2005; Kipp et al. 2010; Kolar and Lodge 2002; Kolar et al. 2005; Mandrak 1989; Mendoza-Alfaro et al. 2009; A. Ricciardi, McGill University; Ricciardi and Rasmussen 1998; Rixon et al. 2005; Stepien and Tumeo

2006; U.S. EPA 2008.

Figure 1.

Cumulative number of aquatic nonindigenous species (ANS) established in the Great Lakes basin since the 1830s attributed to (a) all vectors and (b) only the ship vector.

Source: Grigorovich et al. 2003; Mills et al. 1993; Ricciardi 2001; Ricciardi 2006.

52

Figure 2

. Release mechanisms for aquatic nonindigenous species (ANS) established in the Great Lakes basin since the 1830s. Unintentional release encompasses ornamental plant escape, research escape, and parasites/pathogens through fish stocking.

Source: Great Lakes Aquatic Nonindigenous Species Information System, http://www.glerl.noaa.gov/res/Programs/glansis/glansis.html

; Grigorovich et al. 2003; Mills et al. 1993; Ricciardi

2001; Ricciardi 2006.

Figure 3

. Lake of first discovery for ANS established in the Great Lakes basin since the 1830s.

Discoveries in connecting waters between Lakes Huron, Erie, and Ontario were assigned to the downstream lake.

Species that were widespread at the time of discovery were assigned to the unknown category.

Source: Great Lakes Aquatic Nonindigenous Species Information System, http://www.glerl.noaa.gov/res/Programs/glansis/glansis.html

53

Figure 4

. Numbers of upbound transoceanic ballasted (BOB) and cargo laden (NOBOB) vessels entering the Great

Lakes from 1959 to 2010.

Source: Colautti et al. 2003; Grigorovich et al. 2003; Holeck et al. 2004; Saint Lawrence Seaway Development

Corporation Annual Traffic Reports, http://www.greatlakes-seaway.com/en/seaway/facts/traffic/index.html

Figure 5

. Regions of origin for aquatic nonindigenous species (ANS) established in the Great Lakes basin since the

1830s.

Source: Great Lakes Aquatic Nonindigenous Species Information System, http://www.glerl.noaa.gov/res/Programs/glansis/glansis.html

; Grigorovich et al. 2003; Mills et al. 1993; Ricciardi

2001; Ricciardi 2006.

54

Atmospheric Deposition of Toxic Chemicals

Overall Assessment

Status: Fair

Trend: Improving (for PAHs, organochlorine pesticides, dioxins and furans) / Unchanging or slightly improving (for mercury and PCBs)

Rationale: Fair because different chemical groups have different trends and rates of decline over time. Levels of toxic chemicals in urban areas can be much higher than in rural areas.

Levels of persistent bioaccumulative toxic (PBT) chemicals in air tend to be lowest over Lake

Superior, Lake Huron, and northern Lake Michigan, but their surface area is larger, resulting in a greater importance of atmospheric inputs (Strachan and Eisenreich 1990; Kreis 2005).

Connecting channels inputs dominate for Lake Erie and Lake Ontario, which have smaller surface areas.

While concentrations of some toxic chemicals are very low at rural sites, they may be much higher in “hotspots” such as urban areas. Lake Michigan, Lake Erie, and Lake Ontario have greater inputs from urban areas. The Lake Erie station tends to have higher levels than the other remote master stations, most likely since it is located closer to an urban area (Buffalo, NY) than the other master stations. It may also receive some influence from the East Coast of the U.S.

Atmospheric deposition of chemicals of emerging concern, such as brominated flame retardants and other compounds that may currently be under the radar, could be future stressors to the

Great Lakes. Efforts are being made to screen for other chemicals of potential concern.

Lake-by-Lake Assessment

Each lake was not specifically categorized for status and trend. Site specific trends for some chemicals are available

(Venier and Hites 2010a). Calculated loadings for each lake, including trends over time, are also available (U.S.

EPA and Environment Canada 2008).

Purpose

To determine temporal trends in concentrations of PBT chemicals in the atmosphere over the Great Lakes

To estimate the annual average loadings of PBT chemicals from the atmosphere to the Great Lakes

To track the progress of various Great Lakes programs toward virtual elimination of toxic chemicals to the

Great Lakes

Ecosystem Objective

The Great Lakes Water Quality Agreement (GLWQA, United States and Canada 1987) and the Binational Toxics

Strategy (Environment Canada and U.S. Environmental Protection Agency 1997) both state the virtual elimination of toxic substances in the Great Lakes as an objective. Additionally, GLWQA General Objective (d) states that the

Great Lakes should be free from materials entering the water as a result of human activity that will produce conditions that are toxic to human, animal, or aquatic life. The amended GLWQA of 1987 included a separate

Annex (Annex 15) which provided the mandate for both Parties (US and Canada) to establish the Integrated

Atmospheric Deposition Network (IADN) to conduct surveillance and monitoring of toxic contaminants.

Ecological Condition

The Integrated Atmospheric Deposition Network (IADN) consists of five master monitoring stations, one near each of the Great Lakes, and several satellite stations. This joint United States-Canada monitoring network has been in operation since 1990. Since that time, over a million measurements of the concentrations of PCBs, pesticides, PAHs,

55

flame retardants, and trace metals have been made at these sites. Concentrations of PBT chemicals are measured in the atmospheric gas and particle phases and in precipitation. Spatial and temporal trends of these concentrations and atmospheric loadings to the Great Lakes can be examined using these data. Data from other networks are used here to supplement the IADN data for mercury, dioxins and furans.

PCBs

Total PCBs (ΣPCBs) is a suite of congeners that make up most of the PCB mass and that represent the full range of

PCBs. Concentrations of gasphase ΣPCBs have generally decreased over time at the master stations (Figure 1, Sun

et al

. 2007, Venier and Hites 2010a, Venier and Hites 2010b), but the rate of change is remarkably slow considering that the manufacture of PCBs was banned in North America over 30 years ago. Some increases are seen during the late 1990s and early 2000s that remain unexplained. There is some evidence of connections with atmospheric circulation phenomena such as North Atlantic Oscillations (NAO) or El Nino events (Ma

et al

. 2004); however, similar increases were not seen for other compounds making this perhaps an unlikely explanation (Venier and Hites

2010b). PCB measurements in precipitation samples were stopped at the rural master stations after 2005 because concentrations were nearing levels of detection.

The Lake Erie site consistently shows relatively elevated ΣPCB concentrations compared to the other master stations. Back-trajectory analyses have shown that this is due to possible influences from upstate New York and the

East Coast (Hafner and Hites 2003). Figure 2 shows that ΣPCB concentrations at urban satellite stations in Chicago and Cleveland are about fifteen and ten times higher, respectively, than the remote master stations at Eagle Harbor

(Lake Superior), Sleeping Bear Dunes (Lake Michigan) and Burnt Island (Lake Huron) and the rural master station at Point Petre (Lake Ontario).

In comparison to other PBT chemicals measured by IADN, PCBs have a long halving time (13 to 17 years) and are generally showing the slowest rate of decline (Venier and Hites 2010a, Venier and Hites 2010b). The slow rate of decline, despite PCBs being banned in the US in 1976, is likely due to large amounts of PCBs still in transformers, capacitors, and other electrical equipment and in storage and disposal facilities (Venier and Hites 2010a, Hsu et al.

2003). It is assumed that PCB concentrations will continue this slow decline in the future.

Organochlorine Pesticides

In general, concentrations of banned or restricted pesticides measured by IADN are decreasing over time in air and precipitation (Sun

et al

. 2006a; Sun

et al

. 2006b; Venier and Hites 2010a, Venier and Hites 2010b). Concentrations of endosulfans, DDT, chlordane, α-HCH and γ-HCH in all phases are decreasing steadily (Figure 3). The fastest rates of decline are in α-HCH and γ-HCH, which have halving times of 3 to 4 years in all phases (Venier and Hites

2010a, Venier and Hites 2010b). The slowest rate of decline is for endosulfans, which has a halving time of 11 to 14 years (Venier and Hites 2010a, Venier and Hites 2010b). This is not surprising as endosulfans are still used in agriculture with a complete phase-out scheduled in the U.S. in 2016. Until the phase out is complete, the slow rate of decline is expected to continue.

Concentrations of chlordane are about ten times higher at the urban stations than at the more remote master stations, most likely due to the use of chlordane as a termiticide in buildings (Figure 4, Venier and Hites 2010a, Sun et al.

2006b). Dieldrin and ΣDDTs show similar increases in urban locales.

On the other hand, numerical modeling studies have shown that long-range transport of pesticides (e.g. lindane and toxaphene) emitted in regions outside of the Great Lakes may contribute significantly to the occurrence and deposition of these contaminants in the Great Lakes Basin (Ma et al., 2003; Ma et al., 2005).

Polycyclic aromatic Hydrocarbons (PAHs)

Concentrations of PAHs, such as phenanthrene and chrysene, have been slowly decreasing in all phases at the

56

master and urban stations and are decreasing more rapidly than PCB concentrations (Venier and Hites 2010b).

Concentrations of PAHs can be roughly correlated with human population, with highest levels in Chicago and

Cleveland, followed by the semi-urban site at Sturgeon Point, and lower concentrations at the other remote master stations (Venier and Hites 2010a). In general, PAH concentrations in Chicago and Cleveland are about ten to one hundred times higher than at the rural master stations.

Dioxins and Furans

Concentrations of dioxins and furans have decreased over time (Figure 5) with the largest declines in areas with the highest historical concentrations (unpublished data, T. Dann, Environment Canada 2006). Data collected as part of the IADN program between 2004 and 2007 show no significant changes in concentration of dioxins and furans which is not surprising given the short time scale (Venier

et al

. 2009). Data do suggest that urban and industrial areas act as source of these chemicals to the atmosphere.

Mercury

An analysis of data from the Mercury Deposition Network (MDN) through 2005 show that concentrations of mercury in precipitation were decreasing for nearly half of the network’s sites, particularly across Pennsylvania and into the Northeast. However, the sites in the Great Lakes region do not generally show this decreasing trend, except for 1 site in Indiana (Prestbo and Gay 2009).

A recent analysis of annual and weekly mercury concentrations, precipitation depths, and mercury wet deposition in the Great Lakes region found that mercury wet deposition was mostly unchanged from 2002 to 2008, with any small decreases in concentration offset with increases in precipitation (Risch et al. 2011).

Flame Retardants (FRs)

There does not appear to be any strong trend for flame retardants in the atmosphere around the Great Lakes (Figure

6), with a few notable exceptions. With the voluntary phase-out of the penta- and octa-BDE formulations by the only U.S. manufacturer in 2004, concentrations of these congeners appear to be decreasing, with an overall halving time in the atmosphere of about 6 years (Salamova and Hites 2011). These rates of decline are much faster than those for other persistent organic pollutants such as PCBs (~17 years), PAHs (~10 years), and sum-DDTs (~9 years) indicating that the production restrictions are having immediate benefits. The overall concentrations don't appear to be changing in the graphic because concentrations of other flame retardants that are still in production are not yet decreasing. For example, deca-BDE, which is still in production, is not yet decreasing. Deca-BDE accounts for about 25% of the total flame retardant concentrations. However, deca-BDE contributes a relative large fraction of the total flame retardant concentrations at Cleveland and Sturgeon Point, indicating that there may be a local source in the vicinity of Cleveland (Venier and Hites 2008, Salamova and Hites 2011). Perhaps, when restrictions on production and use of Deca-BDE go into effect after 2013, its concentration will start to decline. It should be noted, though, that even when these commercial mixtures will be completely retired from the market, large amounts of flame retardants will still be present in the environment since they have been used in a variety of consumer products that have a long life (i.e. mattresses, sofas, electronics, and upholstery).

Similar observations were found at the two Canadian master stations as described above for the U.S. stations (see

Figure 7). Figure 7 shows the trend plots in the atmosphere derived for PBDE congeners 47 and 99 for Point Petre and Burnt Island in the gas and particle phases. BDE-47 and 99 appear to be decreasing. Their halflives at Point

Petre (3 and 3.1 years, respectively) are both shorter than at Burnt Island (13 and 5.2 years, respectively). Due to proximity of Point Petre to urban areas, the decline is reflective of both reduction in use and environmental removal processes from the atmosphere (e.g. degradation and partitioning into other media). Burnt Island is more remote, and therefore, the decline observed probably reflects mainly environmental removal.

Figure 7 also shows the trend plots derived for BDE-209 in the gas and particle phases. For BDE-209, BNT

57

(halflife 7.3 years) shows a decreasing trend, but PPT shows an increasing trend (doubling every 12 years). This increasing trend may be attributed to the proximity of PPT to urban locations and the continued usage of DecaBDE technical mixture.

Recently, IADN and tree bark data was also used to identify the source(s) of dechlorane plus (another recently identified flame retardant in the environment) in Niagara Falls, New York (Qiu and Hites 2008, Salamova and Hites,

2010).

Loadings

An atmospheric loading is the amount of a pollutant entering a lake from the air, which equals wet deposition (rain) plus dry deposition (falling particles) plus gas absorption into the water minus volatilization out of the water.

Absorption minus volatilization equals net gas exchange, which is the most significant part of the loadings for many semi-volatile PBT pollutants. For many banned or restricted substances that IADN monitors, net atmospheric inputs to the lake are headed toward equilibrium; that is, the amount going into the lake equals the amount volatilizing out.

Currentuse pesticides, such as γ-HCH (lindane) and endosulfan, as well as PAHs and trace metals, still have net deposition from the atmosphere to the Lakes.

A report on the atmospheric loadings of these compounds to the Great Lakes for data through 2005 is available online at: http://www.epa.gov/glnpo/monitoring/air2/iadn/reports/IADN_Toxics_Deposition_Thru_2005.pdf

. To receive a hardcopy, please contact one of the agencies listed at the end of this report.

Summary

Atmospheric deposition of toxic compounds to the Great Lakes is likely to continue into the future. The levels of compounds no longer in use, including many organochlorine pesticides, may decrease to undetectable levels.

Residual sources of PCBs remain in the U.S. and throughout the world; therefore, atmospheric deposition will still be significant at least decades into the future. PAHs and metals continue to be emitted and therefore concentrations of these substances may not decrease or will decrease very slowly depending on further pollution reduction efforts or regulatory requirements. Even though emissions from many sources of mercury and dioxin have been reduced over the past decade, both pollutants are still seen at elevated levels in the environment. This problem will continue unless the emissions of mercury and dioxin are reduced further.

Atmospheric deposition of chemicals of emerging concern, such as brominated flame retardants and other compounds that may currently be under the radar, could also serve as a future stressor on the Great Lakes. Efforts are being made to screen for other chemicals of potential concern, with the intent of adding such chemicals to Great

Lakes monitoring programs given available methods and sufficient resources.

Linkages

Atmospheric deposition is a significant route by which persistent bioaccumulative toxic chemicals, such as PCBs, currently enter the Great Lakes. Increases in the concentration and loadings of atmospheric PBTs may result in increased contamination in sediment, toxic chemicals in offshore waters and contaminants in whole fish and waterbirds. Bioaccumulation of these PBTs in fish may result in fish consumption advisories.

Management Challenges/Opportunities

Although concentrations of PCBs continue to decline slowly, somewhat of a “leveling-off” trend seems to be occurring in air, fish, and other biota as shown by various long-term monitoring programs. Remaining sources of

PCBs, such as contaminated sediments, sewage sludge, and in-use electrical equipment, may need to be addressed more systematically through efforts like the Canada-U.S. Binational Toxics Strategy and national regulatory programs in order to see more significant declines. Many such sources are located in urban areas, which is reflected

58

by the higher levels of PCBs measured in Chicago and Cleveland by IADN, and by other researchers in other areas

(Wethington and Hornbuckle 2005; Totten et al. 2001). Research to investigate the significance of these remaining sources is underway. This is important because fish consumption advisories for PCBs exist for all five Great Lakes.

In terms of in-use agricultural chemicals, further restrictions on the use of these compounds may be warranted.

Recently the agricultural chemical lindane was phased out in the U.S. and Canada and endosulfans are scheduled to be phased out in the U.S. and Canada by 2016 (Federal Register, 2010; Health Canada Pest Management Regulatory

Agency, 2011). These restrictions will hopefully result in an increased rate of decline in their concentrations in the atmosphere.

PAH inputs to the Great Lakes may be reduced through controls on the emissions of combustion systems, such as those in factories and motor vehicles.

Progress has been made in reducing emissions of dioxins and furans, particularly through regulatory controls on incinerators. Residential garbage burning (burn barrels) is now the largest current source of dioxins and furans

(Environment Canada and U.S. Environmental Protection Agency 2003). Basin and nationwide efforts are underway to eliminate emissions from burn barrels.

World-wide, the largest remaining source of mercury emissions to the atmosphere is coal-fired power plants.

Regionally, many sources are reducing emissions; however, additional local and global actions may be needed to reduce the transport and deposition of mercury to the Great Lakes.

Pollution prevention activities, technology-based pollution controls, screening of in-use and new chemicals, and chemical substitution (for pesticides, household, and industrial chemicals) can aid in reducing the amounts of toxic chemicals deposited to the Great Lakes. Efforts to achieve reductions in use and emissions of toxic substances worldwide through international assistance and negotiations should also be supported, since PBTs used in other countries can reach the Great Lakes through long-range transport.

Continued long-term monitoring of the atmosphere is necessary in order to measure progress brought about by toxic reduction efforts. Environment Canada and U.S. EPA recently added routine monitoring of PBDEs and some non-

PBDE flame retardants to the IADN program. Screening and method development for additional non-PBDE flame retardants is currently under way. Additional urban monitoring is needed to better characterize atmospheric deposition to the Great Lakes.

Assessing Data Quality

Data Characteristics

1. Data are documented, validated, or qualityassured by a recognized agency or organization

2. Data are traceable to original sources

3. The source of the data is a known, reliable and respected generator of data

4. Geographic coverage and scale of data are appropriate to the Great Lakes basin

5. Data obtained from sources within the U.S. are comparable to those from Canada

6. Uncertainty and variability in the data are documented and within acceptable limits for this indicator report

Strongly

Agree

X

X

X

X

Agree

X

X

Neutral or

Unknown

Disagree

Strongly

Disagree

Not

Applicable

59

Acknowledgments

Author:

This report was prepared on behalf of the IADN Steering Committee by Todd Nettesheim, IADN Program Manager,

U.S. Environmental Protection Agency, Great Lakes National Program Office, Michelle Craddock, Oak Ridge

Institute for Science and Education Research Fellow, appointed to the U.S. Environmental Protection Agency, Great

Lakes National Program Office, Sum Chi Lee, IADN Research Manager, Environment Canada, Science and

Technology Branch, and Hayley Hung, IADN Principal Investigator, Environment Canada, Science and Technology

Branch,, (2011).

Contributors:

Thanks to Tom Dann of Environment Canada’s National Air Pollution Surveillance Network for dioxin and furan information, David Gay of the Mercury Deposition Network for mercury in precipitation information, and Ron Hites and Marta Venier of Indiana University and Ken Brice and Nick Alexandrou of Environment Canada for PBDE data.

IADN Contacts:

Hayley Hung, IADN Principal Investigator, Environment Canada, Science and Technology Branch, 4905 Dufferin

Street, Toronto, Ontario, M3H 5T4, [email protected]

, 416-739-5944.

Todd Nettesheim, IADN Program Manager, Great Lakes National Program Office, U.S. Environmental Protection

Agency, 77 West Jackson Boulevard (G-17J), Chicago, IL, 60604, [email protected]

, 312-353-9153.

Link to IADN data: http://www.on.ec.gc.ca/natchem/Login/Login.aspx, or contact Helena Dryfhout-Clark, IADN

Data Manager, Environment Canada, Science and Technology Branch, 6248 Eighth Line, Egbert (Ontario)

L0L 1N0, [email protected]

, 705 458-3316.

Link to IADN websites: http://www.ec.gc.ca/rs-mn/ , and http://epa.gov/greatlakes/monitoring/air2/index.html

Information Sources

Environment Canada and U.S. Environmental Protection Agency. 1997. Canada - United States Strategy for the

Virtual Elimination of Persistent Toxic Substances in the Great Lakes. http://binational.net/bns/strategy_en.pdf

.

Environment Canada and U.S. Environmental Protection Agency. 2003. The Great Lakes Binational Toxics Strategy

2002 Annual Progress Report. http://binational.net/bns/2002/index.html

, last accessed 11.03.05.

Federal Register. 2006. Lindane Cancellation Order, 13 December 2006, Volume 71, Number 239, pp. 74905-

74907. Online at: http://www.epa.gov/fedrgstr/EPA-PEST/2006/December/Day-13/p21101.htm

.

Federal Register. 2010. Endosulfan Final Product Cancellation Order, FR Doc No: 2010-28138 , 10 November

2010, Volume 75, Number 217, pp 69065-69069. Online at http://www.regulations.gov/#!documentDetail;D=EPA-HQ-OPP-2002-0262-0188;oldLink=false

Hafner, W.D., and Hites, R.A. 2003. Potential Sources of Pesticides, PCBs, and PAHs to the Atmosphere of the

Great Lakes. Environmental Science and Technology 37(17):3764-3773.

Health Canada Pest Management Regulatory Agency, 2011. Re-evaluation Note, Discontinuation of Endosulfan.

REV2011-01, 8 February 2011. ISSN: 1925-0630 (print version), ISSN: 1925-0649 (PDF version), 8 pp.

Online at http://www.hc-sc.gc.ca/cps-spc/pubs/pest/_decisions/rev2011-01/index-eng.php

Hsu, Y-

K, Holsen, T.M., and Hopke, P.K. 2003. Locating and Quantifying PCB Sources in Chicago:  Receptor

Modeling and Field Sampling.

Environ. Sci. Technol.

, 2003,

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(4), pp 681–690

Kreis, R. 2005. Lake Michigan Mass Balance Project: PCB Results. October 28, 2005. Grosse Ile, MI. Online at: http://www.epa.gov/med/grosseile_site/LMMBP/

Ma, J. Daggupaty, S. M., Harner, T. and Li, Y. 2003. Impacts of lindane usage in the Canadian prairies on the Great

Lakes ecosystem - 1: Coupled atmospheric transport model and modeled concentrations in air and soil.

Envionmental Science and Technology 37:3774-3781.

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Ma, J., Hung, H., and Blanchard, P. 2004. How Do Climate Fluctuations Affect Persistent Organic Pollutant

Distribution in North America? Evidence from a Decade of Air Monitoring. Environmental Science and

Technology 38(9):2538-2543

Ma, J., Venkatesh, S., Li, Y., Cao, Z. and Daggupaty, S. M.. 2005. Tracking toxaphene in the North American Great

Lakes basin – 2. A strong episodic long-range transport event. Environmental Science and Technology 39:

8123-8131.

Prestbo, E.M. and Gay, D.A. 2009, Wet deposition of mercury in the U.S. and Canada, 1996-2005: Results and analysis of the NADP mercury deposition network (MDN). Atmospheric Environment 43: 4223-4233.

Qiu, X. and Hites, R.A. 2008. Dechlorane Plus and other Flame Retardants in Tree Bark from the Northeastern

United States. Environmental Science and Technology, 42(1): 31-36.

Risch, M.R., Gay, D.A., Fowler, K.F., Keeler, G.J., Backus, S.M., Blanchard, P., Barres, J.A., Dvonch, J.T. 2011.

Environmental Pollution, in press, doi: 10.1016/j.envpol.2011.05.030.

Salamova, A. and Hites, R.A. 2010. Evaluation of Tree Bark as a Passive Atmospheric Sampler for Flame

Retardants, PCBs, and Organochlorine Pesticides Environ. Sci. Technol., 44 (16), pp 6196–6201

Salamova, A. and Hites, R.A. 2011. Discontinued and Alternative Brominated Flame Retardants in the Atmsosphere and Precipitation from the Great Lakes Basin. Environmental Science and Technology , 45 (20), pp 8698–

8706.

Strachan, W. M. J.; Eisenreich, S. J. 1990. Mass Balance Accounting of Chemicals in the Great Lakes. In Long

Range Transport of Pesticides, ed. D. A. Kurtz, pp. 291-301. Chelsea, Michigan: Lewis Publishers.

Sun, P., Basu, I., Blanchard, P., Brice, K. A., Hites, R. A. 2007. Temporal and Spatial Trends of Atmospheric

Polychlorinated Biphenyl Concentrations near the Great Lakes Environmental Science and Technology 41(4):

1131-1136.

Sun, P., Backus, S., Blanchard, P., Hites, R.A. 2006a. Temporal and Spatial Trends of Organochlorine Pesticides in

Great Lakes Precipitation. Environmental Science and Technology 40(7): 2135 -2141.

Sun, P., Blanchard, P., Brice, K.A., Hites, R.A. 2006b. Atmospheric Organochlorine Pesticide Concentrations near the Great Lakes: Temporal and Spatial Trends. Environmental Science and Technology, 40(21): 6587-6593.

Totten, L.A., Brunciak, P.A., Gigliotti, C.L., Dachs, J., Glenn, T.R., IV, Nelson, E.D., and Eisenreich, S.J. 2001.

Dynamic Air-Water Exchange of Polychlorinated Biphenyls in the New York-New Jersey Harbor Estuary.

Environmental Science and Technology 35(19):3834-3840.

U.S. EPA and Environment Canada. 2008. Atmospheric Deposition of Toxic Substances to the Great Lakes: IADN

Results through 2005. ISBN: En56-156/2005E. Public Works and Government Services Canada Catalogue

Number: 978-0-662-48287-1. US EPA Report Number: EPA-905-R-08-001

United States and Canada. 1987.

Great Lakes Water Quality Agreement of 1978, as amended by Protocol signed

November 18, 1987

. Ottawa and Washington.

Venier, M., and Hites, R.A. 2008. Flame Retardants in the Atmosphere near the Great Lakes. Environmental

Science and Technology 42(13): 4745-4751.

Venier, M. Ferrario, J. and Hites, A. 2009. Polychlorinated Dibenzo-p-dioxans and Dibenzofurans in the

Atmosphere Around the Great Lakes 43(4): 1036-1041.

Venier, M. and Hites, R.A. 2010a. Regression Model of Partial Pressures of PCBs, PAHs, and Organochlorine

Pesticides in the Great Lakes’ Atmosphere,

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(2), pp 618–623.

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Region Since 1990. Environmental Science and Technology 44(21): 8050-8055.

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Michigan. Environmental Science and Technology 39(1):57-63.

List of Figures

Figure 1.

Partial residuals versus sampling date for vapor and particle phase PCBs. (The partial residual analysis identifies the relationship between time and the natural logarithm of concentration.)

61

Source: Venier and Hites 2010b.

Figure 2.

Annual average gas phase concentration of total PCBs at rural and urban IADN stations.

Source: IADN Steering Committee, unpublished, 2011.

Figure 3.

Partial residuals versus sampling date for vapor and particle phase organochlorine pesticides. (The partial residual analysis identifies the relationship between time and the natural logarithm of concentration.)

Source: Venier and Hites 2010b.

Figure 4.

Annual average gas phase concentration of total chlordanes at rural and urban IADN stations.

Source: IADN Steering Committee, unpublished, 2011.

Figure 5.

Concentrations of dioxins and furans expressed as TEQ (Toxic Equivalent) in fg/m

3

in Windsor, Ontario.

The centre box is bounded by the 25th and 75th percentiles, and whiskers indicate the 10th and 90th percentiles.

Asterisks are outliers of the 10th and 90th percentiles. The red horizontal line represents the median.

Source: Environment Canada National Air Pollution Surveillance (NAPS) Network, unpublished, 2006.

Figure 6

. Annual Averages of Total Flame Retardant Concentrations (Vapor + Particle Phases; U.S. Stations).

Source: IADN Steering Committee, unpublished, 2011.

Figure 7

. Atmospheric trends of BDE-49, 99 and 209 at the Canadian Master stations (Point Petre (PPT) and Burnt

Island (BNT)) in the Great Lakes region.

Source: IADN Steering Committee, unpublished 2011.

Last Updated

State of the Great Lakes 2011

62

Figure 1.

Partial residuals versus sampling date for vapor and particle phase PCBs. (The partial residual analysis identifies the relationship between time and the natural logarithm of concentration.)

Source: Venier and Hites 2010b.

Figure 2.

Annual average gas phase concentration of total PCBs at rural and urban IADN stations.

Source: IADN Steering Committee, unpublished, 2011.

63

Figure 3.

Partial residuals versus sampling date for vapor and particle phase organochlorine pesticides. (The partial residual analysis identifies the relationship between time and the natural logarithm of concentration.)

Source: Venier and Hites 2010b.

64

1000

100

10

1

Supe rio r

Mi ch iga n

Hu ron

Eri e

Ont ari o

Sample Location

Ch ica go

Cle ve lan d

2003

2004

2005

2006

2007

2008

1996

1997

1998

1999

2000

2001

2002

Figure 4.

Annual average gas phase concentration of total chlordanes at rural and urban IADN stations.

Source: IADN Steering Committee, unpublished, 2011.

Figure 5.

Concentrations of dioxins and furans expressed as TEQ (Toxic Equivalent) in fg/m

3

in Windsor, Ontario.

The centre box is bounded by the 25th and 75th percentiles, and whiskers indicate the 10th and 90th percentiles.

Asterisks are outliers of the 10th and 90th percentiles. The red horizontal line represents the median.

Source: Environment Canada National Air Pollution Surveillance (NAPS) Network, unpublished, 2006.

65

1000

Annual Averages of Total Flame Retardant Concentrations

(Vapor + Particle Phases; U.S. Stations)

2005 2006 2007 2008 2009

100

10

1

Chicago Cleveland Sturgeon Point Sleeping Bear

Dunes

Eagle Harbor

Figure 6

. Annual Averages of Total Flame Retardant Concentrations (Vapor + Particle Phases; U.S. Stations).

Source: IADN Steering Committee, unpublished, 2011.

66

Figure 7

. Atmospheric trends of BDE-49, 99 and 209 at the Canadian Master stations (Point Petre (PPT) and Burnt

Island (BNT)) in the Great Lakes region.

Source: IADN Steering Committee, unpublished 2011.

67

Base Flow Due to Groundwater Discharge

Overall Assessment

Status: Fair

Trend: Undetermined

Rationale: Human activities are estimated to have detrimentally impacted groundwater discharge on at least a local scale in some areas of the Great Lakes basin; although discharge in other areas of the basin has not been significantly impaired. Trends in baseflow with time have not been analyzed for the basin.

Lake-by-Lake Assessment

Individual lake basin assessments were not prepared for this report.

Purpose

This indicator measures the contribution of base flow due to groundwater discharge to total stream flow by

• sub-watershed (lake-scale).

To detect the impacts of anthropogenic factors on the quantity of the groundwater resource.

The Base Flow Due to Groundwater indicator is used in the Great Lakes indicators suite as a State indicator in the Landscapes and Natural Processes top level reporting category.

Ecosystem Objective

The capacity of groundwater discharge to maintain in-stream conditions and aquatic habitat at, or near, potential is not compromised by anthropogenic factors.

Ecological Condition

Measure

Aquatic ecosystems in the streams in the Great Lakes Basin have developed in response to natural variations in flow including low-flow conditions. In the Great Lakes Basin, streams generally receive groundwater discharge as evidenced by increasing streamflow volumes downstream, and this groundwater discharge during times of low precipitation is often referred to as baseflow. Because baseflow maintains both streamflow volume and stream temperature during times of low precipitation it is considered important in maintenance of aquatic ecosystem. Long term average base flow relative to stream flow is referred to as base flow index. Base flow index is a dimensionless value between 0 and 1 where increasing values of the index indicate increasing groundwater discharge and base flow. For example, a base flow index value of 0.28 indicates that 28% of stream flow is estimated to be base flow.

Significant extents of sand and gravel within a watershed often result in relatively large values of base flow index while significant extents of clay often result in relatively small values. Human impacts on base flow can potentially be detected using trend analysis of base flow over time and by identifying areas where base flow index is higher or lower than expected based on climate, geology, and other land cover characteristics.

Endpoint

Anthropogenic factors are not responsible for deviations in the base flow characteristics of sub-watersheds. No endpoint or reference value is available at this time.

Background

A significant portion of precipitation over the inland areas of the Great Lakes basin returns to the atmosphere by evapotranspiration. Water that does not return to the atmosphere either flows across the ground surface or infiltrates into the subsurface and recharges groundwater. Water that flows across the ground surface discharges into surface water features (rivers, lakes, and wetlands) and then flows toward and eventually into the Great Lakes. Water that

68

infiltrates into the subsurface and recharges groundwater also results in flow toward the Great Lakes. Most recharged groundwater flows at relatively shallow depths at local scales and discharges into adjacent surface water features. However, groundwater also flows at greater depths at regional scales and discharges either directly into the

Great Lakes or into distant surface water features. The quantities of groundwater flowing at these greater depths can be significant locally but are generally believed to be modest relative to the quantities flowing at shallower depths.

The component of stream flow due to runoff from the ground surface is rapidly varying and transient, and results in the peak discharges of a stream. Groundwater discharge to surface water features in response to precipitation is greatly delayed relative to surface runoff. The stream flow resulting from groundwater discharge is, therefore, more uniform. In the Great Lakes region, groundwater discharge is often the dominant component of base flow. Base flow is the less variable and more persistent component of total stream flow.

Natural groundwater discharge is not the only component of base flow however, as various human and natural factors also contribute to the base flow of a stream. Flow regulation, the storage and delayed release of water using dams and reservoirs, creates a steady stream flow signature that is similar to that of groundwater discharge. Lakes and wetlands also moderate stream flow, transforming rapidly varying surface runoff into more slowly varying flow that approximates the dynamics of groundwater discharge. It is important to note that these varying sources of base flow affect surface water quality, particularly with regard to temperature.

Status of Base Flow

Base flow is frequently determined using a mathematical process known as hydrograph separation. This process uses stream flow monitoring information as input and partitions the observed flow into rapidly and slowly varying components, i.e., surface runoff and base flow, respectively. The stream flow data that are used in these analyses are collected across the Great Lakes basin using networks of stream flow gauges that are operated by the United States

Geological Survey (USGS) and Environment Canada. Neff et al. (2005) summarize the calculation and interpretation of base flow for 3,936 gauges in Ontario and the Great Lakes states using six methods of hydrograph separation and length-of-record stream flow monitoring information for the periods ending on December 31, 2000 and September 30, 2001, respectively. The results reported by Neff et al. (2005) are the basis for this report.

Results corresponding to the United Kingdom Institute of Hydrology (UKIH) method of hydrograph separation

(Piggott et al. 2005) are referenced throughout this report in order to maintain consistency with the previous report for this indicator. However, results calculated using the five other methods are considered to be equally probable outcomes.

Figure 1 illustrates the daily stream flow monitoring information and the results of hydrograph separation for the

Nith River at New Hamburg, Ontario, for January 1 to December 31, 1993. The rapidly varying response of stream flow to precipitation and snow melt are in contrast to the more slowly varying base flow.

Application of hydrograph separation to daily stream flow monitoring information results in lengthy time series of output. Various measures are used to summarize this output. For example, base flow index is a simple, physical measure of the contribution of base flow to stream flow that is appropriate for use in regional scale studies. Base flow index is defined as the average rate of base flow relative to the average rate of total stream flow, is unitless, and varies from zero to one where increasing values indicate an increasing contribution of base flow to stream flow. The value of base flow index for the data shown in Figure 1 is 0.28, which implies that 28% of the observed flow is estimated to be base flow.

Neff et al. (2005) used a selection of 960 gauges in Ontario and the Great Lakes states to interpret base flow. Figure

2 indicates the distribution of the values of base flow index calculated for the selection of gauges relative to the gauged and ungauged portions of the Great Lakes basin.

69

The variability of base flow within the basin is apparent. However, further processing of the information is required to differentiate the component of base flow that is due to groundwater discharge and the component that is due to delayed flow through lakes and wetlands upstream of the gauges.

An approach to the differentiation of base flow calculated using hydrograph separation into these two components is summarized in the following paragraphs of this report.

Variations in the density of the stream flow gauges and discontinuities in the coverage of monitoring are also apparent in Figure 2 and may have significant implications relative to the interpretation of base flow.

The values of base flow index calculated for the selection of gauges using hydrograph separation are plotted relative to the extents of surface water upstream of each of the gauges in Figure 3. The extents of surface water are defined as the area of lakes and wetlands upstream of the gauges relative to the total area upstream of the gauges. While there is considerable scatter among the values, the expected tendency for larger values of base flow index to be associated with larger extents of surface water is confirmed.

Neff et al. (2005) modeled base flow index as a function of surficial geology and the spatial extent of surface water.

Surficial geology is assumed to be responsible for differences in groundwater discharge and is classified into coarse and fine textured sediments, till, shallow bedrock, and organic deposits.

The modeling process estimates a value of base flow index for each of the geological classifications, calculates the weighted averages of these values for each of the gauges based on the extents of the classifications upstream of the gauges, and then modifies the weighted averages as a function of the extent of surface water upstream of the gauges.

A non-linear regression algorithm was used to determine the values of base flow index for the geological classifications and the parameter in the surface water modifier that correspond to the best match between the values of base flow index calculated using hydrograph separation and the values predicted using the model. The process was repeated for each of the six methods of hydrograph separation.

Extrapolation of base flow index from gauged to ungauged watersheds was performed using the results of the modeling process. The ungauged watersheds consist of 67 tertiary watersheds in Ontario and 102 eight-digit hydrologic unit code (HUC) watersheds in the Great Lakes states. The extents of surface water for the ungauged watersheds are shown in Figure 4 where the ranges of values used in the legend match those used to average the values of base flow index shown in Figure 3.

A component of base flow due to delayed flow through lakes and wetlands appears to be likely over extensive portions of the Great Lakes basin.

The distribution of the classifications of geology is shown in Figure 5. Organic and fine textured sediments are not differentiated in this rendering of the classifications because both classifications have estimated values of base flow index due to groundwater discharge in the range of 0.0 to 0.1. However, organic deposits are of very limited extent and represent, on average, less than 2% of the area of the ungauged watersheds.

The spatial variation of base flow index shown in Figure 5 resembles the variation shown in Figure 2. However, it is important to note that the information shown in Figure 2 includes the influence of delayed flow through lakes and wetlands upstream of the gauges while this influence has been removed, or at least reduced, in the information shown in Figure 5.

Figure 6 indicates the values of the geological component of base flow index for the ungauged watersheds obtained

70

by calculating the weighted averages of the values for the geological classifications that occur in the watersheds.

This map therefore represents an estimate of the length-of-record contribution of base flow due to groundwater discharge to total stream flow that is consistent and seamless across the Great Lakes basin.

The pie charts indicate the range of values of the geological component of base flow index for the six methods of hydrograph separation averaged over the sub-basins of the Great Lakes. Averaging the six values for each of the sub-basins yields contributions of base flow due to groundwater discharge of approximately 60% for Lakes Huron,

Michigan, and Superior and 50% for Lakes Erie and Ontario. There is frequently greater variability of this contribution within the sub-basins than among the sub-basins as the result of variability of geology that is more uniformly averaged at the scale of the sub-basins.

Mapping the geological component of base flow index, which is assumed to be due to groundwater discharge, across the Great Lakes basin in a consistent and seamless manner is an important accomplishment in the development of this indicator.

Additional information is, however, required to determine the extent to which human activities have impaired groundwater discharge. There are various alternatives for the generation of this information. For example, the values of base flow index calculated for the selection of stream flow gauges using hydrograph separation can be compared to the corresponding modeled values. If a calculated value is less than a modeled value, and if the difference is not related to the limitations of the modeling process, then base flow is less than expected based on physiographic factors and it is possible that discharge has been impacted by human activities. Similarly, if a calculated value is greater than a modeled value, then it is possible that the increased base flow is the result of human activities such as flow regulation and wastewater discharge. Time series of base flow can also be used to assess these impacts. No attempt has yet been made to systematically assess change at the scale of the Great Lakes basin.

Change in base flow over time may be subtle and difficult to quantify (e.g., variations in the relation of base flow to climate) and may be continuous (e.g., a uniform increase in base flow due to aging water supply infrastructure and increasing conveyance losses) or discrete (e.g., an abrupt reduction in base flow due to a new consumptive water use). Change may also be the result of cumulative impacts due to a range of historical and ongoing human activities, and may be more pronounced and readily detected at local scales than at the scales that are typical of continuous stream flow monitoring.

A local-scale approach to illustrating the impact of flow regulation on base flow is shown in Figure 7, with data for the Grand River at Galt, Ontario. The cumulative depth of base flow calculated annually as the total volume of flow at the location of the gauge during each year divided by the area that is upstream of the gauge, is plotted relative to cumulative total flow. The base flow index is the slope of the accumulation of base flow relative to the accumulation of total flow shown in Figure 7. The change in slope and increase in base flow index from a value of 0.45 prior to the construction of the reservoirs that are located upstream of the gauge to 0.57 following the construction of the reservoirs clearly indicates the impact of active flow regulation to mitigate low and high flow conditions.

Calculating and interpreting diagnostic plots such as Figure 7 for hundreds to thousands of stream flow gauges in the

Great Lakes basin will be a large and time consuming, but perhaps ultimately necessary, task.

Pressures

The discharge of groundwater to surface water features is the end-point of the process of groundwater recharge, flow, and discharge. Human activities impact groundwater discharge by modifying the components of this process where the time, scale, and to some extent the severity, of these impacts is a function of hydrogeological factors and the proximity of surface water features. Increasing the extent of impervious surfaces during residential and commercial development and installation of drainage to increase agricultural productivity are examples of activities that may reduce groundwater recharge and ultimately groundwater discharge.

71

Withdrawals of groundwater as a water supply and during dewatering (pumping groundwater to lower the water table during construction, mining, etc.) remove groundwater from the flow regime and may also reduce groundwater discharge. Groundwater discharge may be impacted by activities such as the channelization of water courses that restrict the motion of groundwater across the groundwater and surface water interface. Human activities also have the capacity to intentionally, or unintentionally, increase groundwater discharge. Induced storm water infiltration, conveyance losses within municipal water and wastewater systems, and closure of local water supplies derived from groundwater are examples of factors that may increase groundwater discharge. Climate variability and change may compound the implications of human activities relative to groundwater recharge, flow, and discharge.

Linkages

Base flow due to the discharge of groundwater to the rivers, inland lakes and wetlands of the Great Lakes basin is a significant and often major component of stream flow, particularly during low flow periods. Base flow frequently satisfies flow, level, quality and temperature requirements for aquatic species and habitat. Water supplies and the capacity of surface water to assimilate wastewater discharge are also dependent on base flow. Base flow due to groundwater discharge is therefore critical to the maintenance of water quantity, quality, and integrity of aquatic species and habitat. Natural factors such as climate variability modify both average rates of base flow and the annual distribution of flow. Pressures such as urban development and water use, in combination with the potential for climate change impacts, may alter base flow. Reductions in base flow may compromise the assimilative capacity of surface water for wastewater discharge during periods of otherwise low flow and result in reduced water quality.

Management Challenges/Opportunities

Groundwater has important societal and ecological functions across the Great Lakes basin. Groundwater is typically a high quality water supply that is used by a significant portion of the population, particularly in rural areas where it is often the only available source of water. Groundwater discharge to rivers, lakes, and wetlands is also critical to aquatic species and habitat and to in-stream water quantity and quality. These functions are concurrent and occasionally conflicting.

Pressures such as urban development and water use, in combination with the potential for climate impacts and further contamination of the resource, may increase the frequency and severity of these conflicts. In the absence of systematic accounting of groundwater supplies, use, and dependencies, it is the ecological function of groundwater that is most likely to be compromised.

Managing the water quality of the Great Lakes requires an understanding of water quantity and quality within the inland portion of the basin, and this understanding requires recognition of the relative contributions of surface runoff and groundwater discharge to stream flow. The results described in this report indicate the significant contribution of groundwater discharge to flow within the tributaries of the Great Lakes. The extent of this contribution has tangible management implications. There is considerable variability in groundwater recharge, flow, and discharge that must be reflected in the land and water management practices that are applied across the basin.

The dynamics of groundwater flow and transport are different than those of surface water flow. Groundwater discharge responds more slowly to climate and maintains stream flow during periods of reduced water availability, but this capacity is known to be both variable and finite. Contaminants that are transported by groundwater may be in contact with geologic materials for years, decades, and perhaps even centuries or millennia. As a result, there may be considerable opportunity for attenuation of contamination prior to discharge. However, the lengthy residence times of groundwater flow also limit opportunities for the removal of contaminants, in general, and non-point source contaminants, in particular.

Comments from the author(s)

The indicated status and trend are estimates that the authors consider to be a broadly held opinion of water resource

72

specialists within the Great Lakes basin. Further research and analysis is required to confirm these estimates and to determine conditions on a lake by lake basis.

Base flow information cited in the report is a product of the study, Groundwater and the Great Lakes: A Coordinated

Binational Basin-wide Assessment in Support of Annex 2001 Decision Making, conducted by the U.S. Geological

Survey in cooperation with Environment Canada’s National Water Research Institute and the Great Lakes Protection

Fund. Data are published in Neff et al. (2005), cited below.

Recent investigations on trends in streamflow characteristics (Hodgkins and others, 2007) could be expanded to the

Canadian part of the basin. Similarly, analyses of trends in groundwater recharge (Rivard and others, 2009) could be completed in greater detail across both the Canadian and U.S. portions of the basin.

Assessing Data Quality

Data Characteristics

1. Data are documented, validated, or qualityassured by a recognized agency or organization

2. Data are traceable to original sources

3. The source of the data is a known, reliable and respected generator of data

4. Geographic coverage and scale of data are appropriate to the Great Lakes basin

5. Data obtained from sources within the U.S. are comparable to those from Canada

6. Uncertainty and variability in the data are documented and within acceptable limits for this indicator report

Strongly

Agree

X

X

X

Agree

X

X

X

Neutral or

Unknown

Disagree

Strongly

Disagree

Not

Applicable

Acknowledgments

Authors:

Howard Reeves, U.S. Geological Survey, [email protected]

Andrew Piggott, Environment Canada, [email protected]

Brian Neff of the U.S. Geological Survey and Marc Hinton of Geological Survey of Canada were authors of the previous version of this report.

Contributors:

Lori Fuller and Jim Nicholas of U.S. Geological Survey were contributors to the previous version of this report.

Information Sources

Hodgkins, G.A, Dudley, R.W., and Aichele, S.S., 2007, Historical changes in precipitation and streamflow in the

U.S. Great Lakes Basin, 1915-2004: U.S. Geological Survey Scientific Investigations Report 2007-5118, 31 p.

Neff, B.P., Day, S.M., Piggott, A.R., and Fuller, L.M. 2005.

Base Flow in the Great Lakes Basin

: U.S. Geological

Survey Scientific Investigations Report 2005-5217, pp. 23.

Piggott, A.R., Moin, S., and Southam, C. 2005. A revised approach to the UKIH method for the calculation of baseflow: Hydrol. Sci. J., 50:911-920.

Rivard, C., Vigneault, H., Piggott, A.R., Larocque, M., and Anctil, F. 2009. Groundwater recharge trends in Canada:

Can. J. Earth Sci., 46:841-854.

List of Figures

Figure 1

. Hydrograph of observed total stream flow (black) and calculated base flow (red) for the Nith River at New

Hamburg during 1993.

Source: Environment Canada and the U.S. Geological Survey.

73

Figure 2

. Distribution of the calculated values of base flow index relative to the gauged (light grey) and ungauged

(dark grey) portions of the Great Lakes basin.

Source: Environment Canada and the U.S. Geological Survey.

Figure 3

. Comparison of the calculated values of base flow index to the corresponding extents of surface water. The step plot (red) indicates the averages of the values of base flow index within the four intervals of the extent of surface water.

Source: Environment Canada and the U.S. Geological Survey.

Figure 4

. Distribution of the extents of surface water for the ungauged watersheds.

Source: Environment Canada and the U.S. Geological Survey.

Figure 5

. Distribution of the geological classifications. The classifications are shaded using the estimated values of the geological component of base flow index shown in parentheses.

Source: Environment Canada and the U.S. Geological Survey.

Figure 6.

Distribution of the estimated values of the geological component of base flow index for the ungauged watersheds. The pie charts indicate the estimated values of the geological component of base flow index for the

Great Lakes sub-basins corresponding to the six methods of hydrograph separation. The charts are shaded using the six values of base flow index and the numbers in parentheses are the range of the values.

Source: Environment Canada and the U.S. Geological Survey.

Figure 7

. Cumulative base flow as a function of cumulative total flow for the Grand River at Galt prior to (red), during (green), and following (blue) the construction of the reservoirs that are located upstream of the stream flow gauge. The step plot indicates the cumulative storage capacity of the reservoirs where the construction of the largest four reservoirs is labeled. The dashed red and blue lines indicate uniform accumulation of flow based on data prior to and following, respectively, the construction of the reservoirs.

Source: Environment Canada and the U.S. Geological Survey.

Last Updated

State of the Great Lakes 2009

report.

A partial update was completed for the 2011 reporting

74

Figure 1.

Hydrograph of observed total stream flow (black) and calculated base flow (red) for the Nith River at New

Hamburg during 1993.

Source: Environment Canada and the U.S. Geological Survey.

Figure 2

. Distribution of the calculated values of base flow index relative to the gauged (light grey) and ungauged

(dark grey) portions of the Great Lakes basin.

Source: Environment Canada and the U.S. Geological Survey

75

Figure 3

. Comparison of the calculated values of base flow index to the corresponding extents of surface water.

The step plot (red) indicates the averages of the values of base flow index within the four intervals of the extent of surface water. Source: Environment Canada and the U.S. Geological Survey

Figure 4

. Distribution of the extents of surface water for the ungauged watersheds.

Source: Environment Canada and the U.S. Geological Survey

76

Figure 5

. Distribution of the geological classifications.

The classifications are shaded using the estimated values of the geological component of base flow index shown in parentheses. Source: Environment Canada and the U.S. Geological Survey

Figure 6

. Distribution of the estimated values of the geological component of base flow index for the ungauged watersheds.

The pie charts indicate the estimated values of the geological component of base flow index for the Great Lakes subbasins corresponding to the six methods of hydrograph separation. The charts are shaded using the six values of base flow index and the numbers in parentheses are the range of the values.

Source: Environment Canada and the U.S. Geological Survey

77

Figure 7

. Cumulative base flow as a function of cumulative total flow for the Grand River at Galt prior to (red), during (green), and following (blue) the construction of the reservoirs that are located upstream of the stream flow gauge.

The step plot indicates the cumulative storage capacity of the reservoirs where the construction of the largest four reservoirs is labeled. The dashed red and blue lines indicate uniform accumulation of flow based on data prior to and following, respectively, the construction of the reservoirs.

Source: Environment Canada and the U.S. Geological Survey

78

Beach Advisories

Overall Assessment

Status: Fair

Trend: Unchanging

Rationale: The percentage of monitored U.S. Great Lakes beaches that were open and safe for swimming during 2008 - 2010 is an average of 93%. This standard differs from the last report in that the focus of lake summary information in the U.S. is now exclusively on monitored beaches. The percentage of monitored Canadian Great Lakes beaches that were open and safe for swimming during 2008-2010 is an average of 79%. Differences in the percentage of open and posted beaches between the U.S. and Canada may reflect differing posting criteria. Please note that for consistency, all 2006 and 2007 results for Great Lakes beaches have been recalculated and reassessed based on the new beach indicator reporting method. Beach advisories are now calculated based on the number of days a monitored beach is open and safe for swimming during the summer season rather than assessing the percentage of monitored and non-monitored beaches that are open 95% of the swimming season. Only those beaches that are monitored by beach safety programs are included in the analysis. It should also be noted that the statistics have changed from the 2009 State of the Great Lakes report due to the new reporting methods used in this report.

Lake-by-Lake Assessment

Lake Superior

Status: Good

Trend: U.S.: Unchanging; Canada: Deteriorating

Rationale: During 2008 through 2010, on average, 97% of monitored Lake Superior beaches were open and safe for swimming in the U.S. In addition, efforts to identify and remediate sources of contamination are being conducted at several Lake Superior beaches. In Canada, during 2008 through 2010, 88% of monitored Lake Superior beaches were open and safe for swimming during the swimming season. The trend shows deteriorating conditions, from 96% in 2006-2007; however, there was an increase in 30% more beaches being monitored from the last reporting cycle.

Lake Michigan

Status: Good

Trend: Unchanging

Rationale: During 2008 through 2010, on average, 93% of monitored Lake Michigan beaches were open and safe for swimming.

In addition, efforts to identify and remediate sources of contamination are being conducted at several Lake Michigan beaches.

Lake Huron

Status: Good

Trend: U.S.: Unchanging; Canada: Deteriorating

Rationale: During 2008 through 2010, on average, 98% of U.S. monitored Lake Huron beaches were open and safe for swimming. In addition, efforts to identify and remediate sources of contamination are being conducted at several Lake Huron beaches. In Canada, during 2008 through 2010, 83% of monitored

Lake Huron beaches were open and safe for swimming. The trend appears to be deteriorating from 94% in 2006-2007.

79

Lake Erie

Status: Fair

Trend: Deteriorating

Rationale: During 2008 through 2010, on average, 86% of U.S. monitored Lake Erie beaches were open and safe for swimming. While there has been an annual 2% decline in the percentage of Lake Erie beaches that are open and safe for swimming since 2008, efforts are being conducted to identify sources of contamination so measures can be taken to mitigate the contamination. In Canada, during 2008 through

2010, 78% of Lake Erie monitored beaches were open and safe for swimming. The trend appears to be deteriorating from 87% in 2006-2007.

Lake Ontario

Status: Good

Trend: U.S.: Improving; Canada: Unchanging

Rationale: During 2008 through 2010, on average, 93% of U.S. monitored Lake Ontario beaches were open and safe for swimming. Although the trend is improving, efforts continue to be conducted to identify sources of contamination so measures can be taken to mitigate the contamination. In Canada, during

2008 through 2010, 75% of Lake Ontario monitored beaches were open and safe for swimming during the swimming season. The trend appears to be slightly deteriorating from 79% in 2006 – 2007.

Purpose

To assess the number of days that Great Lakes beaches are open and safe for swimming by assessing the health-related swimming posting (advisories or closings) days for recreational areas (beaches).

To infer potential harm from pathogens to human health through body contact with nearshore recreational waters.

The Beach Advisories indicator is used in the Great Lakes indicator suite as an indicator in the Human

Impacts top level reporting category.

Ecosystem Objective

Waters should be safe for recreational use. Waters used for recreational activities involving body contact should be substantially free from pathogens, including bacteria, parasites, and viruses, that may harm human health. This indicator supports Annexes 1, 2, and 13 of the GLWQA (1987).

Ecological Condition

Measure

The percentage of days in the beach season that monitored Great Lakes beaches are open and safe for swimming.

Previous reports used a measure of percentage of beaches with beach advisories during the swimming season. For example, a sentence stating “93% of beaches were open and safe for swimming” does not indicate that the beaches were open 93 days of the season; it indicates that the beaches were, on average, open and safe for swimming 104 days out of the 112 days in the swimming season (.i.e. 93%). The beach season is generally from the Memorial

Day/Victoria Day weekend to Labor Day; however, some health units/counties vary so all beach days that are reported on by counties and health units will be used.

Endpoint

For each Canadian lake basin, the status will be considered good if 80% or more of the beach season for monitored

Great Lakes beaches are open and safe for swimming. For each U.S. lake basin, the status will be considered good if

90-100% of the monitored Great Lakes beaches are open and safe for swimming. The previous beach reports used criteria of 90% of monitored, high priority beaches meeting bacteria standards for more than 95% of the swimming season.

80

Background

Beach monitoring is conducted primarily to detect bacteria that indicate the possible presence of disease-causing microbes (pathogens) from fecal pollution. People swimming in water contaminated with pathogens can contract diseases of the gastrointestinal tract, eyes, ears, skin, and upper respiratory tract. When monitoring results reveal elevated levels of indicator bacteria, the state or local government/health units issue a beach advisory or closure notice until further sampling shows that the water quality is meeting the applicable water quality standards.

A health-related advisory day is one that is based upon elevated levels of

E. coli

, or other indicator organisms, as reported by county health departments (U.S.), Public Health Units (Ontario), or municipal health departments in the

Great Lakes basin.

E. coli

, Enterococci, and other bacterial organisms are measured in beach water samples because they act as indicators for the potential presence of pathogens which can potentially harm human health through body contact with nearshore recreational waters

The Ontario provincial standard is 100

E. coli

colony forming units (cfu) per 100 mL, based on the geometric mean

(GM) of a minimum of one sample per week from each of at least 5 sampling sites per beach (Ontario Ministry of

Health and Long-Term Care, 2008).

The Beach Management Protocol states that beaches of 1000 meters of length or greater require one sampling site per 200 meters, with a minimum of 5 samples taken at each site. In some cases local Health Units in Ontario have implemented a more frequent sampling procedure than is outlined by the provincial government. When

E. coli

levels exceed the standard, beach waters are posted as unsafe for the health of bathers until further sampling shows that the water quality is meeting the applicable water quality standards. The average swimming season in Ontario begins at the end of May and continues until the first weekend in September, but some health units may have a longer or shorter season than the norm. The difference in the swimming season length, the number of beaches sampled each season, as well as the frequency of sampling are all factors that may skew the final result of the percent of beaches open and safe for swimming throughout the season.

In the U.S., the water quality criteria for bacteria for fresh coastal recreation waters are a single sample maximum

(SSM) value of 235

E. coli

colony forming units (cfu) per 100 ml of water (State of Michigan uses 300 cfu per 100 ml), and an SSM of 61 Enterococci cfu per 100 ml (Federal Register 2004). When levels of these indicator organisms exceed water quality standards, swimming at beaches is prohibited or advisories are issued to inform beachgoers that swimming may be unsafe. The swimming season starts Memorial Day weekend and ends on Labor

Day. The U.S. Environmental Protection Agency (U.S. EPA) annually publishes a summary report and data about beach closings and advisories for the previous year's swimming season statistics. The report is based on b each monitoring and notification data submitted each year by the states to U.S. EPA.

The Beaches Environmental Assessment and Coastal Health (BEACH) Act amended the Clean Water Act in 2000 and authorizes U.S. EPA to award grants to coastal and Great Lakes states, territories and eligible tribes to help local authorities monitor their coastal and Great Lakes beaches and notify the public of water quality conditions that may be unsafe for swimming. Great Lakes beach managers are now able to regularly monitor beach water quality and advise bathers of potential risks to human health when water quality standards for bacteria are exceeded. The

BEACH Act also requires states that have coastal recreation waters, including the Great Lakes, to adopt bacteriological criteria as protective as EPA’s recommended criteria (under Section 304(a) of the Clean Water Act) at their coastal waters. In December 2012, U.S. EPA released its revised nationally recommended recreational water quality criteria to protect human health in inland and coastal waters. The revised criteria, which meet the

BEACH Act requirements, reflect the latest scientific knowledge and are designed to protect the public from exposure to harmful levels of pathogens while participating in water-contact activities.

Status of Great Lakes Beach Advisories

Since the last reporting period, the percentage of U.S. Great Lakes beaches open and safe for swimming has remained about the same (Figure 1). Overall, the percentage of monitored Great Lakes beaches that were open and

81

safe for swimming during 2007 – 2010 was an average of 94% (percent of beach days not under an action).

The percentage of U.S. beaches open the entire swimming season (100% of the time) from 2007 to 2009 decreased for Lakes Erie, Huron, and Ontario (Figure 3). From 2009 to 2010, while there appears to be a significant decrease in the percentage of beaches open the entire swimming season, it is because only monitored beaches are now included in the assessment. The prior Beach Advisories, Postings and Closures reports (and the 2007-2009 data in

Figure 3) also included non-monitored beaches. The non-monitored beaches were listed as open and safe for swimming for 100% of the beach season because the lack of monitoring resulted in no postings or advisories. It is important to include only the beaches for which we have data in order to get an accurate assessment of Great Lakes beach water quality and all Beach Advisory reports moving forward will only include information for Great Lakes monitored beaches. It is also important to note that previous Beach Advisory indicator reports included older data; however, data from 1999 to 2005 were not available in the format needed to allow for the recalculations based on the new reporting methods.

In Canada, overall the percentage of Great Lakes beaches open and safe to swim during 2008-2010 was 79%. The trend appears to be slightly deteriorating from 82% in 2006-2007 (Figure 2). This analysis is based on the number of days within a swimming season that beaches are open and safe to swim. Please note that this analysis differs from past SOLEC reports, which focused on the number of postings within each swimming season. The last reporting cycle was based on the U.S. standard that beaches should be open 95% or more of the entire swimming season. The proposed new Ontario Public Health standard (Ministry of Health

in draft

, 2008) indicates that beaches should be open 80% or more of the swimming season. This standard better reflects the difference in beach posting standards between the U.S. and Canada. The number of beach postings within each swimming season was calculated based on this new standard to provide a consistent analysis with the past SOLEC report. All 2006 and 2007 results have been recalculated and reassessed based on the Ontario Public Health standards used in this report to provide consistency.

The original data set included only those beaches monitored throughout the beach season; therefore there has been no change in the type of reporting for Canadian beaches. All Canadian health units with beaches residing on the

Great Lakes provided their 2008-2010 beach data for this report.

The percentage of Canadian beaches open the entire (100%) swimming season slightly improved from 26% during

2006 to 2007 to 30% during 2008 to 2010 (Figure 4). The percentage of Canadian Great Lakes beaches open 80% or more of the swimming season during 2008 – 2010 was 64%. This shows a deteriorating trend from 80% during the 2006 – 2007 reporting cycle. It is also evident that between 2008 to 2010, the percentage of Canadian Great

Lakes beaches that were open 80% or more of the swimming season also deteriorated. In 2008, the percentage of beaches open more than 80% or more of the swimming season was 69%, in 2009, the percentage of beaches open more than 80% or more of the swimming season was 62%, and in 2010 the percentage of beaches open more than

80% or more of the swimming season was 60%. Within 3 years, the percentage of beaches open more than 80% or more of the swimming season decreased by 9%. However, from 2006 to 2007, the percentage of beaches open more than 80% or more of the swimming season increased from 74% in 2006 to 85% in 2007. Annual variability in weather may affect the variability in bacterial counts between each swimming season.

Comparisons of the frequency of beach closings between Canada and the U.S. will be limited due to use of different water quality criteria in the Great Lakes. The change in the Canadian standard, indicating that beaches should be open 80% or more of the swimming season, rather than the entire beach season, provides a slightly improved comparison of beach postings in the Great Lakes.

Management Challenges/Opportunities

Annual variability in the data may result from the variability in monitoring frequencies among beach management entities and variations in reporting, and may not be solely attributable to actual increases or decreases in levels of bacterial indicators. In addition, annual variability of weather may affect the variability in bacterial counts.

82

Additional point and non-point source pollution at coastal areas due to population growth and increased land use may result in additional beach postings, particularly during wet weather conditions. Unless contaminant sources are reduced or removed (or new sources introduced), Great Lakes beach sample results generally contain similar bacteria levels after events with similar meteorological conditions (primarily wind direction and the volume and duration of rainfall). If episodes of poor recreational water quality can be associated with specific events (such as meteorological events of a certain threshold), then forecasting for episodes of elevated bacterial counts may become more accurate.

There are a number of activities being conducted in the U.S. to make the Great Lakes cleaner and safer for swimming. In 2010, the Great Lakes Restoration Initiative (GLRI) provided funding to numerous Great Lakes entities to conduct sanitary surveys at more than 400 Great Lakes beaches to identify sources of contamination affecting beach water quality. Identification of pollution sources at beaches is a critical first step to enabling beach managers to reduce pollution and increase the time that beaches are safe for recreation. GLRI funds have also been issued in 2011 to implement projects to reduce or eliminate contamination sources that have been identified through the use of sanitary surveys.

Identification of pollution sources affecting beach water quality followed by the implementation of actions to reduce or eliminate the pollution will help reduce the presence of bacteria, viruses and pathogens to levels in which water quality standards can be met, one of the long term goals of the

Great Lakes Restoration Initiative Action Plan

. This goal is addressed by two

Action Plan

objectives, “By 2014, 50% of high priority Great Lakes beaches will have been assessed using a standardized sanitary survey tool to identify sources of contamination” and “By 2014, 20% of high priority Great Lakes beaches will have begun to implement measures to control, manage or remediate pollution sources identified through the use of sanitary surveys.” It is important for the source identification and remediation work to continue in order to improve water quality, better protect public health, and increase the opportunities for safe recreation at Great Lakes beaches.

There may be new indicators and new detection methods available through current research efforts occurring binationally in both public and private sectors and academia. Although currently a concern in recreational waters, viruses and parasites are difficult to isolate and quantify, and feasible measurement techniques have yet to be implemented. Although considered reliable indicators of potential harm to human health, the presence of

E. coli

and/or Enterococcus may not necessarily be related to fecal contamination.

Many Ontario health units are participating in beach management programs to monitor public bathing beaches and to improve public awareness. Although each health unit differs slightly, most improve recreational water quality by participating in assisting in enhanced beach grooming; in-water and land debris clean-up; waterfowl and gull deterrent; and public campaigns to encourage people to dispose of food scraps rather than feeding the birds which further pollutes the recreational water (City of Toronto, 2006). The Blue Flag program is becoming a well known program and an effective way of promoting clean beaches in Canada. It is an eco-label that is internationally recognized and only awarded to beaches that achieve high standards in areas such as water quality, education, environmental management and safety (Environmental Defense, 2010). In 2010, Ontario already had nine awarded

Blue Flag beaches on the Great Lakes.

In Ontario, the first Great Lakes beach data depository, the Seasonal Water Monitoring and Reporting System

(SWMRS) was launched in the summer of 2011. This web-based application, partnered by Environment Canada and the Ontario Ministry of Health and Long-Term Care, provides local Health Units with a tool to manage beach sampling data. Health Unit beach data from the past decade is currently being entered into the system. The result will be a system that can potentially have predictive modeling capability, as well as improve the interface for public use. The system will help identify areas of chronic beach postings and, as a result, will aid in improved targeting of programs to address the sources of bacterial contamination.

83

In the U.S., one of the biggest challenges is the proposed elimination of BEACH Act funding in 2014. Without these funds many health departments will have to eliminate beach water testing and public notification programs, which would significantly reduce the amount of the beach data available which enables reporting on beach water quality conditions in the Great Lakes.

Linkages

Beach postings may be the result of pressures including bacterial loadings from tributaries and extreme precipitation events. Improved wastewater treatment in response to these pressures may limit the number of beach postings.

Implementation of best management practices and green infrastructure to reduce the volume of storm water runoff may also limit the number of beach advisories.

Comments from the author(s)

This indicator was updated in 2011 to more closely reflect the impacts to human health and the national metric used in the U.S. Non-monitored beaches will no longer be included in the measure for this indicator as they had been in the U.S. in the past. Non-monitored beaches are entered into U.S. databases as open and safe for swimming for

100% of the beach season because the lack of monitoring resulted in no postings. This assumption that nonmonitored beaches were always safe for swimming may have resulted in an overstatement of the safety of Great

Lakes beaches.

The new Great Lakes beach metric is “Percent of days of the beach season that the Great Lakes beaches monitored by state beach safety programs are open and safe for swimming.” This metric is consistent with EPA’s Office of

Water National Program Guidance beach measure (SP-9) and with the language proposed to be revised in the GLRI

Action Plan. This change in reporting structure and status justification poses challenges to establish a basin-wide trend and to compare current status with that previously reported through SOLEC. The use of both monitored and non-monitored (U.S.) beaches in past State of the Great Lakes reports also complicates comparisons between previous and current status situations.

Assessing Data Quality

Data Characteristics

Strongly

Agree

Agree

Neutral or

Unknown

Disagree

1. Data are documented, validated, or qualityassured by a recognized agency or organization

2. Data are traceable to original sources

3. The source of the data is a known, reliable and respected generator of data

4. Geographic coverage and scale of data are appropriate to the Great Lakes basin

5. Data obtained from sources within the U.S. are comparable to those from Canada

6. Uncertainty and variability in the data are documented and within acceptable limits for this indicator report

Acknowledgments

Authors:

X

X

X

X

X

X

Tracie Greenberg, Environment Canada, Burlington, Ontario; [email protected]

Holly Wirick, U.S. EPA, Region 5, Chicago, IL; [email protected]

Contributors:

Jacqueline Adams, U.S. EPA; [email protected]

Stacey Cherwaty-Pergentile; [email protected]

Strongly

Disagree

Not

Applicable

84

Kristin Stevens, U.S. EPA; [email protected]

Information Sources

Great Lakes beach data provided by U.S. EPA http://water.epa.gov/type/oceb/beaches/seasons_2010_index.cfm

Canadian Great Lakes Beach data provided by the following Ontario Health Units with beaches residing along the

Great Lakes: Algoma; Chatham Kent; Durham Region; Elgin St. Thomas; Grey Bruce; Haldimand Norfolk:

Haliburton Kawartha Pine Ridge District; Halton Region; Hamilton; Hastings and Prince Edward Counties;

Huron County; Lambton County; Niagara Region; North Bay Parry Sound District; Peel Region; Simcoe

Muskoka District; Sudbury & Distruct; Thunder Bay District; Toronto; Windsor-Essex County

City of Toronto. 2006.

Toronto beaches officially open for 2006. http://wx.toronto.ca/inter/it/newsrel.nsf/0/7d9eb361438b6a7885257187004f9983?OpenDocument

, last accessed

10 April, 2008.

Environmental Defense. 2010. Blue Flag Canada. http://environmentaldefence.ca/campaigns/blue-flag-canada, last accessed 20 August, 2011.

Federal Register. 2004.

Water Quality Standards for Coastal and Great Lakes Recreation Waters; Final Rule

67218-67243, November 16, 2004.

http://edocket.access.gpo.gov/2004/pdf/04-25303.pdf

Great Lakes Restoration Initiative Action Plan. 2010. http://greatlakesrestoration.us/pdfs/glri_actionplan.pdf

Health Canada. 2010.

Guidelines for Canadian Recreational Water Quality, 1992

. http://www.hc-sc.gc.ca/ewhsemt/pubs/water-eau/guide_water-1992-guide_eau/index-eng.php

, last updated 14 June 2010.

Ontario Ministry of Health. 2008.

Beach management protocol 2008 - safe water program.

www.health.gov.on.ca/ebr/beach_management_protocol.pdf

,

last accessed 20 August 2011.

U.S. Environmental Protection Agency. 1986.

Ambient Water Quality Criteria for Bacteria - 1986

. http://water.epa.gov/scitech/swguidance/standards/upload/2009_04_13_beaches_1986crit.pdf

last accessed 18

August 2008.

U.S. Environmental Protection Agency’s Beach Advisory and Closing On-line Notification (BEACON) system. http://water.epa.gov/type/oceb/beaches/summarylist.cfm

U.S. Environmental Protection Agency. 2012.

Recreational Water Quality Criteria

. http://water.epa.gov/scitech/swguidance/standards/criteria/health/recreation/index.cfm

United States and Canada. 1987. Great Lakes Water Quality Agreement of 1978, as amended by Protocol signed

November 18, 1987. Ottawa and Washington. http://www.ijc.org/en_/1987_Agreement

List of Figures

Figure 1

. Percentage of beach days that U.S. Great Lakes beaches are open and safe for swimming (2010 data includes only monitored beaches while 2007-2009 data includes both monitored and non-monitored beaches).

Source: Data collected from U.S. states and reported to U.S. EPA’s Beach Advisory and Closing On-Line

Notification (BEACON) system.

Figure 2

. Percentage of beach days that Canadian monitored Great Lakes beaches are open and safe for swimming.

Source: Data collected from Ontario Health Units located along the Great Lakes (see Health Units listed in information source section), 2010.

Figure 3

. Overview of U.S. beach advisories 2007 – 2010 within each lake basin swimming season (2010 data includes only monitored beaches while 2007-2009 data includes both monitored and non-monitored beaches).

Source: Data collected from U.S. states and reported to U.S. EPA’s Beach Advisory and Closing On-Line

Notification (BEACON) system.

Figure 4

. Overview of Canadian beach advisories 2006 – 2010 within each lake basin swimming season.

Green represents those beaches that were open 100% of the swimming season; blue represents those beaches that were open between 80-100% of the swimming season; yellow represents those beaches that were open 50-80% of the swimming season; and red represents those beaches that were open less than 50% of the swimming season. For

85

example, in 2010, in Lake Ontario, 19% of monitored beaches were open 100% of the swimming season, which is approximately 12 monitored beaches.

Source: Data collected from Ontario Health Units located along the Great Lakes (see Health Units listed in information source section), 2010.

Last Updated

State of the Great Lakes 2011

Figure 1

. Percentage of beach days that U.S. Great Lakes beaches are open and safe for swimming (2010 data includes only monitored beaches while 2007-2009 data includes both monitored and non-monitored beaches).

Source: Data collected from U.S. states and reported to U.S. EPA’s Beach Advisory and Closing On-Line

Notification (BEACON) system.

86

Figure 2

. Percentage of beach days that Canadian monitored Great Lakes beaches are open and safe for swimming.

Source: Data collected from Ontario Health Units located along the Great Lakes (see Health Units listed in information source section), 2010.

Figure 3

. Overview of U.S. beach advisories 2007 – 2010 within each lake basin swimming season (2010 data includes only monitored beaches while 2007-2009 data includes both monitored and non-monitored beaches).

Source: Data collected from U.S. states and reported to U.S. EPA’s Beach Advisory and Closing On-Line

Notification (BEACON) system.

87

Figure 4

. Overview of Canadian beach advisories 2006 – 2010 within each lake basin swimming season.

Green represents those beaches that were open 100% of the swimming season; blue represents those beaches that were open between 80-100% of the swimming season; yellow represents those beaches that were open 50-80% of the swimming season; and red represents those beaches that were open less than 50% of the swimming season. For example, in 2010, in Lake Ontario, 19% of monitored beaches were open 100% of the swimming season, which is approximately 12 monitored beaches.

Source: Data collected from Ontario Health Units located along the Great Lakes (see Health Units listed in information source section), 2010.

88

Benthos Diversity and Abundance

Overall Assessment

Status: Mixed

Trend: Unchanging to deteriorating

Rationale: Based on the benthic community, the trends in the trophic condition of the lakes are mixed in the period from 1998 through 2009. Some near shore sites are becoming more eutrophic while some off-shore, deep water sites more oligotrophic.

Lake-by-Lake Assessment

Lake Superior

Status: Good

Trend: Unchanging

Rationale : All sites in Lake Superior were classified as oligotrophic based on the oligochaete community index since 1997.

Lake Michigan

Status: Good

Trend: Unchanging

Rationale: Most sites in Lake Michigan have a trophic index value below 0.6 indicating an oligotrophic condition. Since 2002 nearshore sites on the eastern side of the southern basin and in southern Green

Bay have oscillated between meso- and eutrophic. Since 2006 only the nearshore site near the

Kalamazoo River outlet and one Green Bay site were above 1.

Lake Huron

Status: Undetermined

Trend: Undetermined

Rationale: Most sites in Lake Huron have been below 0.6 over the past decade; since 2006 all but two sites would be considered oligotrophic. The site in Saginaw Bay oscillates between mesotrophic and eutrophic. The nearshore site located on the eastern shore near the outlet of Saugeen River in Ontario,

Canada has been eutrophic since 2008 and has very high densities of oligochaetes, the highest densities of all of all sites sampled in Lake Huron.

Lake Erie

Status: Poor

Trend: Unchanging

Rationale: Most sites sampled over the past decade in Lake Erie were above 1.0 and would be classfied as eutrophic. Since 2000 sites in the eastern basin tended to be more eutrophic than the central or

Lake Ontario

Status: Fair western basin sites; however, in 2008-2009 all sites in the western basin were classified as eutrophic.

Sites in the central basin tended to be the lest eutrophic.

Trend: Deteriorating

Rationale: All of the off-shore deep water sites in Lake Ontario would be classified as oligotrophic since 2003.

Nearshore sites however have tended toward mesotrophic and eutrophic, and since 2003 western basin sites along the southern shore of Lake Ontario have become increasingly eutrophic.

89

Purpose

The purpose of this analysis is to assess trends in the benthic community composition over time with respect to trophic status of the Great Lakes

The Benthos and Diversity and Abundance indicator is used in the Great Lakes indicator suite as a State of indicator in the Aquatic-dependent Life top level reporting category.

Ecosystem Objective

With respect to the benthos of the Great Lakes, the ecosystem objective is that the composition of benthic community in the Great Lakes should remain relatively constant over time and space and be comparable to unimpaired waters with similar depth and substrate conditions. One estimate of benthic community status is based on Milbrink’s Modified Envrionmental Index (1983) which uses oligochaete diversity, trophic classifications, and abundances to compute the trophic status of a body of water. Trophic classifications are based on individual species responses to organic enrichment. This indicator supports Annex 2 of the 1987 Great Lakes Water Quality

Agreement.

Calculation of Oligochaete Trophic Index (OTI)

To evaluate trends in the benthic community of the Great Lakes, SOLEC uses an Oligochaete Trophic Index (OTI).

The OTI was initially described by Mosley and Howmiller (1977) with subsequent modifications by Howmiller and

Scott (1977), Milbrink (1983), and Lauritsen et al. (1985). The SOLEC indicator primarily follows Milbrink’s formula; however since there are different interpretations of the formula we have defined our process below in an attempt to clarify the calculations going forward. Milbrink classifies Tubificids and Lumbriculids oligochaetes into four ecological classes relative to trophic status of the lake. The values range from 0 indicating intolerant of enrichment (oligotrophic conditions) to 3 indicating tolerant of enrichment (highly eutrophic conditions). The index is calculated as:

c

* [(1/2∑n

0

+ ∑n

1

+2

∑n

2

+3∑n

3

) / (∑n

0

+ ∑n

1

+ ∑n

2

+ ∑n

3

)] where n

0

, n

1

, n

2

, and n

3

indicate the abundances of organisms in each of the four trophic categories (Table 1) and c is a density coefficient that scales the index to absolute densities of Tubificids and Lumbriculids. The c coefficient is as follows (Milbrink 1983):

c

=1 if n > 3,600

c

=0.75 if 1,200 < n <3,600

c

=0.5 if 400 < n < 1,200

c

=0.25 if 130< n < 400

c

=0 if n < 130

There are several parts of the OTI calculation that are open to interpretation so we have included a clarification of how we interpreted these points below:

• we only used lumbriculids and tubificids to calculate the index;

• all immature lumbriculids were classified as

Stylodrilus heringianus (

Styheri

);

• the

c

coefficient was estimated from abundances (n) of mature and immature lumbriculids and tubificids;

Milbrink (1983) assigned the tubificid

Tubifex tubifex

(Tubtubi) dual classifications depending on the dominance of Styheri or

Limnodrilus hoffmeisteri

(Limhoff). We formalized the dual classifications as follows: if the ratio of abundances of n

0

oligochaetes to n

3

oligochaetes (Limhoff) > 1 then Tubtubi is classified as a 3; if the ratio is < 1 then Tubtubi is classified as a 0; however, if the ratio is close to one

(0.75 to 1.25) then Tubtubi is a 3 if

c

≥ 0.5 and a 0 if

c

< 0.5;

90

• if Limhoff density is zero and n

0

is relatively high and/or total density is low, then Tubtubi is 0, otherwise

3; and,

• if the total density of oligochaetes is zero, then the index is zero.

Trophic classifications were obtained from literature for the Great Lakes and are shown in Table 1.

Ecological Condition

Annex 2 of the 1987 Great Lakes Water Quality Agreement states that there should be no impairment of Great

Lakes benthos. SOLEC uses the oligochaete based trophic condition index (Milbrink, 1983; a modification of

Howmiller and Scott, 1977) to assess trophic status of each site. The trophic condition index is calculated based on known organic enrichment tolerances and abundances of oligochaete taxa (see attached summary of calculation procedure). The index ranges from 0 – 3: scores less than 0.6 (the lower line in Figure 1) indicate oligotrophic conditions; scores above 1 (the top line in Figure 1) indicate eutrophic conditions; and, scores between 0.6 and 1.0 suggest mesotrophic conditions. Scores approaching 3 indicate high densities of oligochaetes dominated by the pollution tolerant

Limnodrilus hoffmeisteri

and

Tubifex tubifex

.

During the study period of 1998 through 2009 we observed a consistent difference in trophic conditions between

Lakes and a few trends within Lake basins. Averaged across the study period, Lake Erie was consistently and significantly more eutrophic than all the other Lakes followed in order of increasing oligotrophication by Lakes

Ontario, Michigan, Huron and Superior. Lakes Huron and Superior had significantly lower average trophic index scores than the other three Lakes. Summarized by Lake, we observed no significant trends in trophic condition over the study period. Summarized by Lake basin, there were a few trends noted: increasing eutrophication in the eastern and central basins of Lake Erie, in the southern basin of Lake Michigan, and in the western basin of Lake Ontario.

In Lakes Ontario and Michigan these trends are driven by increasing OTI scores for nearshore sites.

In Lake Erie, the most eutrophic conditions were found in the eastern basin, which tended to increase up until about

2003 and remain between 2.0 and 2.5 through 2009. There was a similar trend in the data for central basin although the OTI scores were less eutrophic. The western basin varied substantially but no trends were obvious.

Lake Huron sites were mostly classified as oligotrophic since 2007. In the period from 1998 through 2001, the southernmost site was classified as mesotrophic or eutrophic but has been consistently oligotrophic since 2002 (one minor exception in 2006). The Saginaw Bay site was extremely eutrophic from 1997 through 2001, improved to mesotrophic, but has trended towards eutrophic again starting in 2007. One site in the central basin, HU96B (44m) off Southampton, Ontario, near the outlet of the Saugeen River, was very eutrophic in 2004, 2008 and 2009 (Figure

1). At this site counts of dreissenids were about 50 /m

2

in 2004 and increased to 2,800/m

2

in 2008; counts of oligochaetes (mature and immature) increased from 450/m

2

in 2000, 1,700/m

2

in 2004, and 11,560/m

2

in 2009.

Most sites in Lake Michigan were classified as oligotrophic. The exceptions were the nearshore sites along the southern and central Michigan basins’ eastern coast (near the Grand and Kalamazoo River outlets) and along the western coast near Green Bay. The sites in Green Bay have been consistently mesotrophic to mildly eutrophic.

Deepwater sites in Lake Ontario have been classified as oligotrophic throughout the study period. Average scores in the western basins showed a trend toward increasing eutrophication since 2001, primarily due to increasingly eutrophic nearshore sites along the southern shore.

Pressures

The oligochaete indicator used for SOLEC assesses trophic status of the Lakes and may suggest pressures due to organic enrichment. Some nearshore sites and sites near large river mouths do show increasing eutrophication

91

across all five Lakes. This suggests that pollution abatement mitigation in the upland watersheds could help to improve water quality and sediment conditions at these sites. Other pressures not accounted for in the oligochaete trophic index include invasive species, regional climate change, water level changes, toxic or other contaminats, and other unforeseen changes to the ecosystem. Recent changes due to invasive species, especially the invasive dreissenid mussles, pose severe threats to the ecosystem function. Incorporating indicators to track community composition changes due to new invasive species are needed to better track benthos changes as invasive species pressures change throughout the basin.

Management Challenges/Opportunities

The Milbrink Environmental Index is a good tool to assess changes in organic enrichment in sediments and detect changes in the trophic status of the benthic community. Some nearshore sites across the Lakes are becoming increasingly eutrophic. Some of these changes may be related to terrestrial inputs from large rivers. However, many of the recent changes in the benthic community have been due to invasive species, especially dreissenid mussels. Likely consequences have been the loss of the native amphipod

Diporeia

sp. from many sites in the lower

Lakes and changes in the relative abundances of other species. For example, our analysis has shown a trend toward decreasing densities of sphaeriid clams in Lakes Michigan, Huron and Ontario which could be related to direct competition with dreissenid mussles. In addition, some researchers have found that oligochaeta densities may increase with presence of dreissenid mussels becaue the oligochaetes can feed off the dreissenid feces and pseudofeces (although others have found no changes or decreasing densities of oligochaetes; see Soster et al. 2011).

Although our analyses did not detect signficant upward trends in the abundances of oligocheates over time, these changes may occur on a site-by-site basis. If dreissenid mussels resulted in an increase in the numbers of oligochaetes, this could result in an elevated MIlbrink’s index indicating organic enrichment causes of commnunity change instead of impacts due to invasive species. Additional indices need to be developed that can track changes in the benthic community independent of changes due to trophic status and more accrurately assess trends in the benthic community.

Comments from the author(s)

Dreissenid populations are expected to have altered the ecology of all four lower Lakes and may be part of the cause of the suspected oligotrophication of Lake Huron and other changes such as algae blooms and

Cladophora

fouling of beaches. However, the Milbrink’s trophic index did not detect Lake Huron oligotrophication using the benthic coummunity as indicator taxa. This suggests a need for develoment of additional indices that can better track changes in the benthic community composition with respect to other changes that are occuring in the Lakes.

Additional environmental variables are needed to enable the development of additonal benthic community indicators that together with the Milbrink’s index, will better assess the lake condition based on trends in the benthic community.

Assessing Data Quality

Data Characteristics

1. Data are documented, validated, or quality-assured by a recognized agency or organization

2. Data are traceable to original sources

3. The source of the data is a known, reliable and respected generator of data

4. Geographic coverage and scale of data are appropriate to the Great Lakes basin

5. Data obtained from sources within the

U.S. are comparable to those from Canada

Strongly

Agree

Agree

x x x

Neutral or

Unknown

Disagree

Strongly

Disagree

x

Not

Applicable

x

92

Data Characteristics

Strongly

Agree

Agree

Neutral or

Unknown

Disagree

Strongly

Disagree

Not

Applicable

6. Uncertainty and variability in the data are documented and within acceptable x limits for this indicator report

Clarifying Notes: Number 4: missing near shore sites; Dreissenid data is missing from prior to 2007. Number 6: uncertain about

1997 data.

Acknowledgments

Authors:

Dr. Catherine Riseng, University of Michigan, Ann Arbor, MI, [email protected]

Glenn Carter, Univeristy of Michigan, Ann Arbor, MI, [email protected]

Dr. Kurt Schmude, University of Wisconsin – Superior, Superior, WI

Dr. Sara Adlerstein, University of Michigan, Ann Arbor, MI

Dr. Rick Barbiero, CSC and Loylola University, Chicago, IL

Information Sources

Barbour, M.T., J. Gerritsen, B.D. Snyder, and J.B. Stribling. 1999. Rapid Bioassessment Protocols for Use in

Streams and Wadeable Rivers: Periphyton, Benthic Macroinvertebrates and Fish, Second Edition. EPA 841-B-

99-002. U.S. Environmental Protection Agency; Office of Water; Washington, D.C.

Howmiller, R. P. and M. A. Scott. 1977. An environmental index based on relative abundance of oligochaete species. Journal of Water Pollution Control Federation 46:809-815.

Krebs, C. 1989.

Ecological Methodology.

HarperCollins, New York.

Kreiger, K.A. 1984. Benthic macroinvertebrates as indicators of environmental degradation in the southern nearshore zone of the central basin of Lake Erie. Journal of Great Lakes Research 10(2):197-209.

Magnussen, S. and T.J.B. Boyle. 1995. Estimating sample size for inference about the Shannon-Weaver and

Simpson indices of species diversity. Forest Ecology and Management 78: 71-84.

Milbrink, G.A. 1983. An improved environmental index based on the relative abundance of oligochaete species.

Hydrobiologia 102:89-97.

Peet, K. 1974. The measurement of species diversity. Annual Review of Ecology and Systematics 5: 285-307.

References

Howmiller, R. P. and M. A. Scott. 1977. An environmental index based on relative abundance of oligochaete species. Journal of Water Pollution Control Federation 46:809-815.

Krebs, C. 1989.

Ecological Methodology.

HarperCollins, New York.

Kreiger, K.A. 1984. Benthic macroinvertebrates as indicators of environmental degradation in the southern nearshore zone of the central basin of Lake Erie. Journal of Great Lakes Research 10(2):197-209.

Lauritsen, D.D., S.C. Mozley, and D.S. White. 1985. Distribution of oligochaetes in Lake Michigan and comments on their use as indices of pollution. J. Great Lakes Res. 11(1): 67-76.

Magnussen, S. and T.J.B. Boyle. 1995. Estimating sample size for inference about the Shannon-Weaver and

Simpson indices of species diversity. Forest Ecology and Management 78: 71-84.

Milbrink, G.A. 1983. An improved environmental index based on the relative abundance of oligochaete species.

Hydrobiologia 102:89-97.

Nalepa, T.F., D.L. Fanslow, S.A. Pothoven, A.J. Foley, and G.A. Lang. 2007. Long-term trends in benthic macroinvertebrates populations in Lake Huron over the past four decades. Journal of Great Lakes Research

33:421-436.

Soster, F.M., P.L. McCall, and K.A. Herrman. 2011. Decadal changes in the benthic community in western Lake

Erie between 1981 and 2004. Journal of Great Lakes Research 37: 226-237

93

List of Tables

Table 1

. Trophic classifications for select mature lumbriculids and tubificids taken from Howmiller and Scott

(1977), Milbrink (1983) with additions from Kreiger (1984), Lauritsen et al. (1985). If Milbrink classifications differed from Howmiller and Scott, Howmiller and Scott was used.

List of Figures

Figure1

. Scatterplot of the index values for Milbrink’s (1983) Modified Environmental Index, applied to data from

GLNPO’s 1998 through 2009 summer surveys. Values ranging from 0 to less than 0.6 indicate oligotrophic conditions; values from 0.6 to 1.0 indicate mesotrophic coniditons; and values greater than 1.0 indicate eutrophic conidtions. Index values for taxa were taken from literature (Barbour et al. 1994, Howmiller and Scott 1997,

Krieger 1984, Milbrink 1983).

Data points represent the average of triplicate samples taken at each sampling site; immature specimens were included in the analysis for calculation of overall density used to establish the coefficent

c

but only mature specimens were used to calculate the number belonging to each ecological group of oligochaetes

(see attached description of index calculation).

Figure 2

. Map of the Great Lakes showing the trophic status at each sampling site calculated for 2009. Trophic status was based on the modified trophic index for oligochaete worms from Milbrink (1983). One site in the western basin of Lake Superior had no oligochaetes and two sites had only Enchytraeidae in the samples. Given that there were no oligochaetes and previous years had indices <0.2, these sites were shown as oligotrophic.

Figure 3

. Maps of the Great Lakes showing differences in trophic status between 2000 and 2009 (3A) and between

2005 and 2009 (3B). Values represent the difference between mean index values calculated at each site in 2000,

2005, and 2009. The differences were then standardized by the mean and standard deviation for each lake.

Increased oligotrophication or eutrophication indicates a rate of change greater than one standard deviation above or below the mean.

Last Updated

State of the Great Lakes 2011

94

Trophic classifications for select mature lumbriculids and tubificids

SPECCODE GENUS SPECIES

Trophic

Class

Source

RHYCOCC

TASAMER

LIMPROF

Rhyacodrillus

Tasserkidrilus

Limnodrilus coccineus americanus profundicola

0

0

0

Howmiller and

Scott 1977

Howmiller and

Scott 1977

Howmiller and

Scott 1977

RHYMONT Rhyacodrilus montana 0 Kreiger 1984

RHYSP

SPINIKO

Rhyacodrilus

Spirosperma spp. nikolskyi

0

0

STYHERI

TASSUPE

AULAMER

AULLIMN

AULPIGU

Stylodrilus

Tasserkidrilus

Aulodrilus

Aulodrilus

Aulodrilus heringianus superiorensis americanus limnobius pigueti

0

0

1

1

1

Kreiger 1984

Kreiger 1984

Howmiller and

Scott 1977

Kreiger 1984

Howmiller and

Scott 1977

Milbrink 1983

Milbrink 1983

Comment

Same classification as Krieger 1984 &

Lauritsen et al. 1985 formerly

T. kessler

i in both Lauritsen et al.

1985 and Kreiger

Same classification as Krieger 1984 &

Lauritsen et al. 1985

Same classification as Lauritsen et al. 1985

Same classification as Lauritsen et al. 1985

Same classification as Lauritsen et al. 1985

General agreement from all sources for this taxon

Same classification as Lauritsan et al. 1985

Classification based on Aulodrilus sp.

ILYTEMP

ISOFREY

SPIFERO

AULPLUR

LIMANGU

LIMCERV

LIMCECL

LIMCLAP

LIMMAUM

LIMUDEK

Ilyodrilus

Isochaetides

Spirosperma

Aulodrilus

Limnodrilus

Limnodrilus

Limnodrilus

Limnodrilus

Limnodrilus

Limnodrilus templetoni freyi ferox pluriseta angustipenis cervix cervix/ claparedeianus claparedeianus maumeensis udekemianus

1

1

1

2

2

2

2

2

2

2

Kreiger 1984

Kreiger 1984

Howmiller and

Scott 1977

Milbrink 1983

Howmiller and

Scott 1977

Howmiller and

Scott 1977

Howmiller and

Scott 1977

Howmiller and

Scott 1977

Howmiller and

Scott 1977

Howmiller and

Scott 1977

Milbrink 1983

Milbrink 1983

Same classification as Milbrink 1983 &

Lauritsen et al. 1985

Same classification as Lauritsen et al. 1985

Same classification as Krieger 1984 &

Lauritsen et al. 1985 same as Milbrink 1983 same as Milbrink 1983 same as Milbrink 1983 same as Milbrink 1983

POTBEDO

POTMOLD

Potamothrix

Potamothrix bedoti moldaviensis

2

2 Same classification as Lauritsen et al. 1985

POTVEJD Potamothrix vejdovskyi 2 Milbrink 1983 Same classification as Lauritsen et al. 1985

QUIMULT

LIMHOFF

TUBTUBI

Quistadrilus

Limnodrilus

Tubifex multisetosus hoffmeisteri tubifex

2

3

0 or 3

Howmiller and

Scott 1977

Milbrink 1983

Milbrink 1983

Differs from classification in Lauritsen et al.

1985

Depends on densities of LIMHOFF and

STYHERI and total oligochaete density

Table 1

. Trophic classifications for select mature lumbriculids and tubificids taken from Howmiller and Scott

(1977), Milbrink (1983) with additions from Kreiger (1984), Lauritsen et al. (1985). If Milbrink classifications differed from Howmiller and Scott, Howmiller and Scott was used.

95

Figure 1

. Scatterplot of the index values for Milbrink’s (1983) Modified Environmental Index, applied to data from

GLNPO’s 1998 through 2009 summer surveys. Values ranging from 0 to less than 0.6 indicate oligotrophic conditions; values from 0.6 to 1.0 indicate mesotrophic coniditons; and values greater than 1.0 indicate eutrophic conidtions. Index values for taxa were taken from literature (Barbour et al. 1994, Howmiller and Scott 1997,

Krieger 1984, Milbrink 1983).

Data points represent the average of triplicate samples taken at each sampling site; immature specimens were included in the analysis for calculation of overall density used to establish the coefficent

c

but only mature specimens were used to calculate the number belonging to each ecological group of oligochaetes

(see attached description of index calculation).

96

Figure 2

. Map of the Great Lakes showing the trophic status at each sampling site calculated for 2009. Trophic status was based on the modified trophic index for oligochaete worms from Milbrink (1983). One site in the western basin of Lake Superior had no oligochaetes and two sites had only Enchytraeidae in the samples. Given that there were no oligochaetes and previous years had indices <0.2, these sites were shown as oligotrophic.

97

Figure 3

. Maps of the Great Lakes showing differences in trophic status between 2000 and 2009 (3A) and between

2005 and 2009 (3B). Values represent the difference between mean index values calculated at each site in 2000,

2005, and 2009. The differences were then standardized by the mean and standard deviation for each lake.

Increased oligotrophication or eutrophication indicates a rate of change greater than one standard deviation above or below the mean.

98

Botulism Outbreaks

Overall Assessment

Trend: Undetermined

Rationale: Avian mortality estimates vary greatly due to fluctuations in anthropogenic and environmental factors as well as inconsistencies in data collection and monitoring.

Lake-by-Lake Assessment

Lake Superior

Trend: No Change

Rationale: Avian mortality estimates due to

Clostridium botulinum

type E are infrequent and small in scale.

Lake Michigan

Trend: Undetermined

Rationale: Avian mortality estimates fluctuate substantially between years during which records were provided.

Lake Huron

Trend: Undetermined

Rationale: Avian mortality estimates were recorded for the United States in the 1960s and either no outbreaks or monitoring has occurred since that time. Canadian estimates exist as of 1998 but are skewed due to insufficient monitoring.

Lake Erie

Trend: Undetermined

Rationale: Avian mortality estimates are consistently in the thousands for the United States during 2000 to 2008, however, no recorded data exist before or after this time frame. Canadian estimates are considerably lower during these same years.

Lake Ontario

Trend: Undetermined

Rationale: Avian mortality estimates for recorded years show numbers in the hundreds and thousands for both the

United States and Canada. Existing data are less than 10 years for both countries and monitoring discontinued in 2010 due to budgetary constraints.

Purpose

To estimate the number of bird mortalities (by species) in the Great Lakes related to

Clostridium botulinum

• type E (avian botulism)

To infer the effects of invasive species and seasonality on incidence of botulism outbreaks

The Botulism Outbreaks indicator is used in the Great Lakes indicators suite as an Impact indicator in the

Fish & Wildlife top level reporting category.

Ecosystem Objective

The goal is to ultimately reduce or, if possible, eliminate the number of bird, fish and other species mortalities due to the toxin produced by active bacterium spores of

Clostridium botulinum

type E

.

The favorable conditions through which the toxin is released and has the potential to move through the food chain, may be the result of various environmental and anthropogenic factors. The Great Lakes Regional Collaboration recommends in the GLRC

Strategy to Restore and Protect the Great Lakes that further “research [is needed] to clarify sources and transport of biotoxins (i.e., botulism) through the foodweb.”

99

This indicator supports the Great Lakes Water Quality Agreement objectives under Annex 1 addressing microbial agents that can affect human health, Annex 2 listing impairment of beneficial uses and Annex 17 delineating

“research need to support the achievement of the goals of this Agreement” (GLWQA 1987). Lakewide Management

Plan managers also consider outbreaks of Type E botulism to be a significant ongoing and emerging issue and recommend further research.

Ecological Condition

Background

The type E strain of

Clostridium botulinum

is one of seven different types of botulism bacteria. This strain in particular is responsible for vast mortalities of water birds in the Great Lakes region and in other parts of the United

States, generally during the late summer through fall seasons.

Botulism is a neuromuscular disease that can affect a variety of species from invertebrates, amphibians and reptiles to fish and birds. Some species are more susceptible to contracting the toxin than others primarily due to their eating habits. For instance, a diving duck may ingest the botulism toxin through consumption of mussels that have strained the active toxin-producing bacteria from their environment (Fig 1). It is through the food chain that many water birds may then contract botulism, in turn acting as a highly visible indicator of the toxin’s presence in the environment.

Birds that have ingested the toxin will often display outward signs of paralysis before dying, including an inability to fly, to utilize their neck muscles and hold the head erect (known as limberneck) and unresponsive inner eyelids.

Generally the birds will drown before reaching shore, however, those that do reach land tend to die soon afterward of respiratory failure (Locke and Friend 1989). The severity of poisoning depends upon the amount of toxin ingested and the species of bird, however the incubation period is generally 12 hours and mortality can occur anytime within a three-day period (personal communication with Steven Riley 2011; Gross 1971).

Dormant spores of the botulism bacterium are naturally abundant in sediments, soils and even the intestinal tracts of live, healthy animals and are endemic to the Great Lakes region. Under certain conditions, namely an anoxic environment with suitable nutrients and favorable temperatures and pH, these dormant spores reach the vegetative or active growth stage and begin producing the botulism toxin (Brand et al. 1988). The spores are resistant to extreme temperatures and desiccations, and so are capable of remaining in the ecosystem for long periods of time (Domske

2003).

Status of type E botulism

Avian mortalities are currently our primary indicator for the presence of active toxin-producing type E botulism in the environment. Monitoring programs are generally run through state/federal agencies and universities or concerned citizens send in reports. Due to budgetary constraints both past and present as well as differences in data collection procedures and analysis, the number of avian mortalities estimated for each of the Great Lakes is not always representative of the far-ranging effects of the toxin in both Canada and the United States.

Total estimated avian mortalities for U.S. Great Lakes states were aggregated using data from the USGS National

Wildlife Health Center’s wildlife mortality database and from the State of Michigan’s Department of Natural

Resources. Represented are only the years during which data were collected and estimates provided. The data are limited in that they do not encompass all the mortality events that have occurred for both reported and non-reported years. However, despite the limitations in established reporting mechanisms the data illustrate that at least 116,265 avian mortalities have occurred on the United States side since the 1960s (Fig 2). It is important to note that not all of these birds were tested for botulism, however, a subset of birds from these locations tested positive for the toxin in those years.

Canadian data are also limited due to a lack of consistent reporting mechanisms. Estimates for avian mortalities

100

attributed to type E botulism have only been monitored since 1998 and because of differences in data collection and analysis these numbers are likely not representative of actual mortality events in the lakes. The notable increase in estimated mortalities in 2004 is the result of further monitoring efforts by the Canadian Wildlife Service in Lake

Ontario. Funding for this monitoring was again reduced in 2010 and we once again see a decline in the number of mortalities (Fig 3).

Lake Superior

While Lake Superior is not traditionally associated with type E botulism outbreaks and is not included in the lakeby-lake graphical assessment (Fig 4), there have been recorded instances according to records kept by Michigan

Department of Natural Resources. In 1967, 39 gull and three common loon mortalities were reported. Similarly the subsequent year, 19 gulls, nine loons and one unknown species of duck succumbed to botulism intoxication. Then, no cases were reported until 1981 when 13 common loons found on the coast of southeast Lake Superior at

Whitefish Point in Chippewa County tested positive for type E botulism (Cooley 2011). No other known cases of type E botulism events have been monitored or reported and all reports have been on the U.S. side of the Great

Lakes. However, knowing that incidents have occurred in the past demonstrates a need for further understanding of the presence of the toxin in the Lakes.

Lake Michigan

Reports for type E botulism outbreaks date back as far as 1963 and 1964, with massive mortalities estimated at

7,725 and 12,650 water birds respectively. A variety of bird species were impacted, but most commonly found among the mortalities were loons, gulls, grebes and ducks. The number of water bird deaths was likely due to the major alewife population crash resulting in large numbers of alewives washing up on shore and decaying. Scientists confirmed their suspicions after examining deceased gulls and loons to determine that alewives were the dominant food item showing up in their gizzards (Fay 1966). Prior to these incidences, no known wild bird die-offs had occurred due to type E botulism in North America. In 1965 and 1966 water bird die-offs continued to occur, but no estimates were determined and are therefore not included in the graphical assessment (Fig 4). Botulism outbreak estimates were collected sporadically for the next three decades either when a large enough event occurred or reports were available. It was not until recently that botulism outbreaks have once again become particularly severe in Lake

Michigan. In 2006, the number of deceased water birds increased with over 3,000 mortalities in the Sleeping Bear

Dunes National Lakeshore area. The next year brought an even greater die-off with over 4,000 mortalities ranging from Ludington State Park north and including most of the Michigan beaches in the Upper Peninsula (Zuccarino-

Crowe 2009). The most recent large-scale outbreak occurred in 2010 with an estimated 2,677 bird mortalities spanning the Upper Peninsula, Sleeping Bear Dunes National Lakeshore and other locations north along the

Michigan shoreline (personal communication with Thomas Cooley 2011). Lake Michigan has the most extensive data record and to date accounts for an estimated 34,269 water bird mortalities.

Lake Huron

Documented cases of type E botulism outbreaks for Lake Huron began in 1965 with an estimated 400 deceased gulls in the Saginaw Bay area. Then again in 1967 with 579 gull kills at the mouth of Saginaw River, Saginaw Bay and north to Tawas Point and Oscoda (personal communication with Thomas Cooley 2011). According to data from the

USGS National Wildlife Health Center, another estimated 1,300 water birds were killed in 1969 on the U.S. side of

Lake Huron. No mortalities were reported again until 1998 presumably a combination of fewer occurrences, less notable outbreak events, and insufficient monitoring and reporting. At this time, the Canadian Cooperative Wildlife

Health Center is the only known entity keeping track of avian mortalities from type E botulism in Lake Huron. As evident in the lake-by-lake graphical assessment, mortality numbers appear to be very low (Fig 5). The low mortality numbers are in part due to the available reporting mechanism. Only water birds that have tested positive for type E botulism and those that are of the same species found in the same location qualify as mortalities. It is likely that a greater number of mortalities are occurring, however, without additional monitoring we will not know for certain.

101

Lake Erie

As opposed to the previous three lakes, Lake Erie presents the opportunity to compare data from the United States and Canada. In 1999, both countries began tracking mortalities from botulism outbreaks presumably due to greater or more noticeable mortalities in the lake. The increase in mortalities could be attributed to environmental conditions such as water level changes, storm events and temperature fluctuations as well as anthropogenic factors like increases in nutrient loading to the lake. Since Lake Erie is more shallow than the other Great Lakes, fluctuations tend to have a greater impact and as a result it is possible that the conditions needed to foster germination of the botulism bacteria can more easily occur. At any rate since 2000, Lake Erie has continuously experienced annual mortalities in the thousands. One year in particular, 2002 had a record estimate of 21,000 mortalities in the eastern basin according to the USGS National Wildlife Health Center. Testing on a subset of carcasses was performed and botulism was confirmed. The deaths were thus presumed to be the result of type E botulism and comprised of thousands of gulls, common loons, grebes, cormorants and shorebirds. Fish kills were also in the thousands, mostly sheepshead and a few sturgeon (Robinson 2008). The opportunity for comparison is reflected in the lake-by-lake graphical assessments for the United States and Canada (Fig 4 and Fig 5). According to data from the USGS

National Wildlife Health Center there have been over 62,000 estimated water bird mortalities from 1999 to 2008.

Data provided by the Canadian Cooperative Wildlife Health Center for the same time frame shows an estimated 111 water bird mortalities. Reasons for the disparity could be due in part to data collection and reporting methods, available monitoring and reporting mechanisms or perhaps even environmental causes. Regardless the difference is significant and requires further study.

Lake Ontario

Annual reporting for Lake Ontario began in 2002 with the advent of a significant botulism outbreak killing an estimated 1,046 water birds. Since that time annual die-offs have been in the thousands. In 2006 and 2007, the number of die-offs escalated to an estimated 5,553 and 3,649 mortalities respectively (USGS-NWHC 2011). It is possible that environmental conditions were at play, for instance higher temperatures, due to the fact that increases in avian mortalities were seen during the same years for Lake Erie and Lake Michigan. The U.S. data for Lake

Ontario was compiled by the USGS National Wildlife Health Center, however, the New York State Department of

Environmental Conservation is the agency responsible for collecting, counting and conducting pathology on the birds. The U.S. data for Lake Erie was compiled by the New York Department of Environmental Conservation. In the past two years, budgetary constraints have impacted NY DEC’s ability to continue monitoring botulism outbreaks, which is apparent in the data (personal communication with Helen Domske 2011).

Canadian data for Lake Ontario were provided by the Canadian Cooperative Wildlife Health Centre and the

Canadian Wildlife Service. As previously mentioned, the number of recorded avian mortality estimates began in

2003, but the data show a drastic increase in 2004. This increase is due to additional data provided by Chip Weseloh looking at colonial water bird mortalities offshore on five islands in the eastern basin and one island in the central basin (Weseloh et al. 2011). Funding for this project continued through to 2009, at which point the data once again reflect a decrease likely due to a reduction in monitoring efforts (Fig 5). The addition of the data from this one monitoring project also influences the overall Canadian avian mortalities that we see attributed to type E botulism

(Fig 3). Lake Ontario serves as a prime example of how additional monitoring efforts would provide researchers and decision makers with a better idea of which species and areas are most heavily impacted, as well as some insight into how anthropogenic factors may play into this process.

Linkages

As aforementioned many anthropogenic and environmental factors may contribute to the conditions suitable for

Clostridium botulinum

type E germination. Excess nutrient run-off, climate shifts and the impact of invasive species in the food chain and in fostering these conditions, have all been listed as probable factors leading to proliferation of botulism and the notable wide-spread mortalities in the Great Lakes.

102

The amount of dissolved oxygen in the water is key not only to the survival of oxygen-dependent species, but also because its absence satisfies one of the conditions needed to foster proliferation of the botulism pathogen.

Temperature is inversely correlated with the amount of dissolved oxygen in the water, the higher the temperature the less dissolved oxygen. Similarly, the depth of the water can also affect concentrations of dissolved oxygen, although it may vary depending upon the processes of respiration, decomposition and photosynthesis (University of Maine

2006). The National Oceanic and Atmospheric Administration predicts climate change may potentially lead to decreases in lake-wide water levels and warmer water temperatures, meaning a greater likelihood of anoxic conditions leading to future botulism outbreaks in the Great Lakes (Quinn 1998).

The role of invasive species in this process only builds upon the impacts of climate change.

Cladophora glomerata

, for instance, is thought to be structurally rich in simple organics and may work with climate factors to produce an anoxic environment when decomposition occurs. Scientists have found that at Sleeping Bear Dunes National

Lakeshore, incidences of avian die-offs due to type E botulism coincide with massive blooms of green algae, consisting mostly of

Cladophora

. Further research is needed to determine whether or not

Cladophora

may be providing the perfect substrate for germination and growth of

Clostridium botulinum

, and in turn providing a pathway into the food chain.

Zebra and quagga mussels are also thought to be a pathway for

Clostridium botulinum

type E into the food chain.

Numerous species may rely on the mussels as a food source from fish and birds to reptiles and amphibians (Fig 1).

Since the mussels are filter feeders and not known to be susceptible to the toxin produced by

Clostridium botulinum

, they may accumulate the toxin within their bodies and transfer it to other species. It is also believed that similar to

Cladophora

, the mussels themselves are organically rich and at times produce an anoxic substrate in which

Clostridium botulinum

may proliferate (personal communication with Thomas Cooley 2011; Getchell and Bowser

2006).

Management Challenges/Opportunities

Through the objectives of the Great Lakes Water Quality Agreement as well as the Great Lakes Regional

Collaboration and the Lakewide Management Plans, the goal is to further understand the epidemiology of

Clostridium botulinum

type E to identify methods of reducing its impact on fish and wildlife populations and potential effects on human health.

Clearly identifying the factors that may produce an anoxic and nutrient rich environment that fosters proliferation of the pathogen is a necessary step in moving forward. It has been identified thus far that various anthropogenic and environmental factors may contribute to not only germination of the pathogen but its movement throughout the food web. Although it may likely be impossible to ever know the actual number of birds and other species dying, knowing more about species sensitivity, effects of seasonality and location of actual ingestion of the toxin may help us identify problem areas and target monitoring, research and on-the-ground efforts.

At this time we have no affordable real-time technology that would allow us to sample for the toxin on site and rely heavily on water birds either demonstrating symptoms of botulism poisoning or testing carcasses. Removal of carcasses early on is one of the few preventative measures that currently exist.

Of the monitoring efforts currently in place, data collection and analysis varies greatly for each country depending upon the organization involved. Consistency in these procedures may provide researchers and management with a clearer picture in regards to focusing future monitoring and research.

Comments from the author(s)

The number of avian mortalities will always be an estimate due to the nature of this indicator and the inability of researchers to record with accuracy all the species that succumb to the

Clostridium botulinum

toxin. It may instead be useful to develop consistent data collection methods that include susceptible species, geospatial data and correlate

103

this information with the probable contributing factors listed in the linkages section.

Also, it may be possible to identify specific water bird species as strong indicators of the presence of the toxin. One challenge with figuring out target areas is that most water birds can fly for a short time after ingesting the toxin or may drown and wash up on shore elsewhere. Identifying species that remain in a particular location during the late summer and fall season may assist researchers further in pinpointing target areas. The Red-Necked Grebe may be a potential indicator species due to its loss of primary feathers at that time of year and thus inability to travel far from its food source. However, further research is necessary to determine the benefit of using this species or any other as an indicator (personal communication with Thomas Cooley 2011).

Assessing Data Quality

Data Characteristics

Strongly

Agree

Agree

Neutral or

Unknown

Disagree

Strongly

Disagree

Not

Applicable

1. Data are documented, validated, or qualityassured by a recognized agency or organization

2. Data are traceable to original sources X

X

3. The source of the data is a known, reliable and respected generator of data

4. Geographic coverage and scale of data are appropriate to the Great Lakes basin

X

X

5. Data obtained from sources within the U.S. are comparable to those from Canada

6. Uncertainty and variability in the data are documented and within acceptable limits for

X this indicator report

Clarifying Notes:

Budgetary constraints for monitoring have made it difficult to obtain sufficient scope of data, and many years

X have no reported estimates despite knowing that outbreak events did occur. Due to inconsistencies in data collection and analysis between organizations, the data is highly variable and not every case is documented. Although data is included for each of the

Great Lakes, detailed geographic coverage is not always available and limited to areas that are actually monitored. Furthermore, not all birds reported as dead were tested for avian botulism, as such, many may have died from other causes.

Acknowledgments

Authors:

Shelley Cabrera, Oak Ridge Institute for Science and Education (ORISE) Research Fellow on appointment to the

U.S. Environmental Protection Agency (U.S. EPA), Great Lakes National Program Office (GLNPO), Chicago IL

Contributors:

Judy Beck, U.S. EPA GLNPO, Chicago, IL

Stacey Cherwaty, Environment Canada, Burlington, Ontario

Jennifer Chipault, USGS National Wildlife Health Center, Madison, WI

Thomas Cooley, Wildlife Biologist and Pathologist, Michigan Department of Natural Resources, Lansing, MI

David Cristo, BScH, Communications Coordinator, Canadian Cooperative Wildlife Health Centre, Guelph, Ontario

Helen Domske, Coastal Education Specialist, New York Sea Grant, Buffalo, NY

Joe Kaplan, Common Coast Research & Conservation, Hancock, MI

David Moore, Canadian Wildlife Service, Burlington, Ontario

Kevin O’Donnell, Ph.D., U.S. EPA GLNPO, Chicago, IL

Daniel O’Riordan, U.S. EPA GLNPO, Chicago, IL

Stephen Riley, Research Fishery Biologist, USGS Great Lakes Science Center, Ann Arbor, MI

D.V. Chip Weseloh, Ph.D., Senior Population Assessment Biologist, Canadian Wildlife Service, Toronto, Ontario

Chiara Zuccarino-Crowe, Michigan State University, East Lansing, MI

U.S. Fish and Wildlife Service

104

National Park Service

U.S Forest Service

Illinois Department of Natural Resources

Common Coast Research and Conservation, Michigan

New York State Department of Environmental Conservation

Presque Isle State Park, Pennsylvania

Pennsylvania Sea Grant

Wisconsin Department of Natural Resources

Information Sources

Brand, C.J., Schmitt, S.M., Duncan, R.M., and Cooley, T.M. 1988. An outbreak of Type E botulism among common loons (

Gavia immer

) in Michigan’s Upper Peninsula.

Journal of Wildlife Diseases

24(3): 471-476.

Byappanahalli, M.N. and Whitman, R.L. 2009. Clostridium botulinum type E occurs and grows in the alga

Cladophora glomerata. Can. J. Fish. Aquat. Sci. 66: 879-882 (2009)

Cooley, T.M. 2011. Type E Botulism in Michigan: A Historical Review. Michigan Department of Natural

Resources Wildlife Disease Laboratory.

Domske, H. 2003. Botulism in Lake Erie 2003 Workshop Proceedings. New York Sea Grant, Ohio Sea Grant and

Pennsylvania Sea Grant. http://seagrant.psu.edu/publications/proceedings/Botulism(2003).pdf

Fay, L.D. 1966. Type E botulism in Great Lakes water-birds.

Michigan Department of Conservation, Research and

Development Report No. 54.

March 3, 1966. Rose Lake Wildlife Research Center, East Lansing, MI.

Getchell, R.G. and Bowser, P.R. 2006. Ecology of Type E Botulism Within Dreissenid Mussel Beds.

Aquatic

Invaders.

Vol. 17, No. 2

Gross, W.B. and Smith, L. DS. 1971. Experimental Botulism in Gallinaceous Birds.

Avian Diseases

, Vol 15, No. 4

(Oct. – Dec., 1971), pp. 716-722

International Joint Commission, United States and Canada. 1987. Revised Great Lakes Water Quality Agreement of

1978. Amended by Protocol signed November 18, 1987.

Locke, L.N. and Friend, M. 1989. 13.2.4. Avian Botulism: Geographic Expansion of a Historic Disease.

Waterfowl

Management Handbook.

U.S. Fish and Wildlife Service National Wildlife Health Research Center.

Quinn, F.H. 1998. Impacts of Climate Change on the Great Lakes Basin. National Oceanic and Atmospheric

Administration Great Lakes Environmental Research Laboratory. http://www.glerl.noaa.gov/res/Task_rpts/1996/ccquinn11-2.html

Robinson, J. 2008. Fish and Wildlife Deaths Due to Botulism Type E.

Lake Erie Lakewide Management Plan

, April

2008, §11.9.

University of Maine. 2006. Temperature and Dissolved Oxygen. http://pearl.maine.edu/windows/community/Water_Ed/Dissolved%20Oxygen/DO_whatisit.htm

Weseloh, D.V., Shutt, J.L., Moore, D.M., Andrews, D.W., Herbert, C.E., Campbell, D., Williams, K. 2011

(unpublished data).

Mortality of Colonial Waterbirds and Type E Botulism in Eastern Lake Ontario, 2004-

2009.

Zuccarino-Crowe, C. 2009. 5.7 Type E Botulism.

Nearshore Areas of the Great Lakes 2009.

Environment Canada and U.S. Environmental Protection Agency. ISBN 978-1-100-13563-2.

List of Figures

Figure 1

. Consumption of

Clostridium botulinum

. This figure is a simplified food web demonstrating the pathways through which

Clostridium botulinum

type E may transfer by way of ingestion.

Source: Cooley, T.M. 2011. Type E Botulism in Michigan: A Historical Review. Michigan Department of Natural

Re-sources Wildlife Disease Laboratory.

Figure 2

. Overall United States avian mortalities attributed to type E botulism. This figure shows the aggregated avian mortality totals for all five Great Lakes on the U.S. side during years with recorded estimates.

105

Source: Mortality figures compiled through the coordination of USGS National Wildlife Health Center and the

Michigan Department of Natural Resources. Estimated totals supplied via personal communication with Jennifer

Chipault, August 2011 and Thomas Cooley, September 2011.

Figure 3

. Overall Canadian avian mortalities associated with type E botulism. This figure shows the aggregated avian mortality totals for all four Great Lakes on the Canadian side during years with recorded estimates.

Source: Mortality figures compiled through the coordination of the Canadian Cooperative Wildlife Health Centre and the Canadian Wildlife Service. Estimated totals supplied via personal communication with David Cristo, June

2011 and Chip Weseloh, September 2011.

Figure 4

. United States water bird mortalities associated with confirmed cases of type E botulism. The four graphs on the left-hand side represent recorded data from 1963-1983. A gap in the data set exists between 1983 and 1999, during which time no data was recorded for any Lake. The four graphs to the right display data recorded between the years 1999-2010. If no data is available for a Lake it will read ‘No Reported Data.’ Any years with no recorded data are designated with black stars.

Note: This data was provided by several sources and may vary. A comprehensive historical dataset of suspected botulism mortalities is not maintained by one entity at this time.

Source: Mortality figures compiled through the coordination of USGS National Wildlife Health Center and the

Michigan Department of Natural Resources. Estimated totals supplied via personal communication with Jennifer

Chipault, August 2011 and Thomas Cooley, September 2011.

Figure 5

. Canadian lake-by-lake graphical assessment of

Clostridium botulinum

in water birds. The three graphs on the left-hand side are presented as a comparison to U.S. historical data from 1963-1983, however there is no known reported data during this time frame. A gap in the data set exists between 1983 and 1999, during which time no data was recorded for any Lake. The three graphs to the right display data recorded between the years 1999-2010. If no data is available for a Lake it will read ‘No Reported Data.’ Any years with no recorded data are designated with black stars.

Note: This data was provided by several sources and may vary. A comprehensive historical dataset of suspected botulism mortalities is not maintained by one entity at this time.

Source: Mortality figures compiled through the coordination of the Canadian Cooperative Wildlife Health Centre and the Canadian Wildlife Service. Estimated totals supplied via personal communication with David Cristo, June

2011 and Chip Weseloh, September 2011.

Last Updated

State of the Great Lakes 2011

106

Figure 1

. Consumption of

Clostridium botulinum

. This figure is a simplified food web demonstrating the pathways through which

Clostridium botulinum

type E may transfer by way of ingestion.

Source: Cooley, T.M. 2011. Type E Botulism in Michigan: A Historical Review. Michigan Department of Natural

Resources Wildlife Disease Laboratory.

107

Figure 2

. Overall United States avian mortalities attributed to type E botulism. This figure shows the aggregated avian mortality totals for all five Great Lakes on the U.S. side during years with recorded estimates.

Source: Mortality figures compiled through the coordination of USGS National Wildlife Health Center and the

Michigan Department of Natural Resources. Estimated totals supplied via personal communication with Jennifer

Chipault, August 2011 and Thomas Cooley, September 2011.

Figure 3

. Overall Canadian avian mortalities associated with type E botulism. This figure shows the aggregated avian mortality totals for all four Great Lakes on the Canadian side during years with recorded estimates.

Source: Mortality figures compiled through the coordination of the Canadian Cooperative Wildlife Health Centre and the Canadian Wildlife Service. Estimated totals supplied via personal communication with David Cristo, June

2011 and Chip Weseloh, September 2011.

108

Figure 4

. United States water bird mortalities associated with confirmed cases of type E botulism. The four graphs on the left-hand side represent recorded data from 1963-1983. A gap in the data set exists between 1983 and 1999, during which time no data was recorded for any Lake. The four graphs to the right display data recorded between the years 1999-2010. If no data is available for a Lake it will read ‘No Reported Data.’ Any years with no recorded data are designated with black stars.

Note: This data was provided by several sources and may vary. A comprehensive historical dataset of suspected botulism mortalities is not maintained by one entity at this time.

Source: Mortality figures compiled through the coordination of USGS National Wildlife Health Center and the

Michigan Department of Natural Resources. Estimated totals supplied via personal communication with Jennifer

Chipault, August 2011 and Thomas Cooley, September 2011.

109

Figure 5

. Canadian lake-by-lake graphical assessment of

Clostridium botulinum

in water birds. The three graphs on the left-hand side are presented as a comparison to U.S. historical data from 1963-1983, however there is no known reported data during this time frame. A gap in the data set exists between 1983 and 1999, during which time no data was recorded for any Lake. The three graphs to the right display data recorded between the years 1999-2010. If no data is available for a Lake it will read ‘No Reported Data.’ Any years with no recorded data are designated with black stars.

Note: This data was provided by several sources and may vary. A comprehensive historical dataset of suspected botulism mortalities is not maintained by one entity at this time.

Source: Mortality figures compiled through the coordination of the Canadian Cooperative Wildlife Health Centre and the Canadian Wildlife Service. Estimated totals supplied via personal communication with David Cristo, June

2011 and Chip Weseloh, September 2011.

110

Cladophora

Overall Assessment

Status: Fair

Trend: Undetermined

Rationale: Cladophora is widely distributed over hard surfaces (e.g. bedrock, boulders, piers, etc.) in the nearshore of all the Laurentian Great Lakes and reaches nuisance levels in lakes Ontario, Erie

Michigan, and isolated locations in Lake Huron. Fouling of shoreline by beached algae, composed mostly of Cladophora, is now an annual feature across many beaches and harbors in these lakes.

Quantitative monitoring information is limited in geographic coverage and sporadic in duration.

There is inadequate information to track temporal trends in the distribution or abundance of

Cladophora at this time with the exception of Lake Michigan.

Lake-by-Lake Assessment

Lake Superior

Status: Good

Trend: Unchanging

Rationale: Shore fouling by

Cladophora

has not historically been an issue in Lake Superior. There is no observational evidence that the occurrence of

Cladophora

has changed in recent years.

Lake Michigan

Status: Poor

Trend: Unchanging

Rationale:

Cladophora

is widely abundant in the nearshore over parts of the western shores of the lake covering a high proportion of the lakebed composed of hard surfaces. Reported biomass levels exceed the thresholds for shore fouling consistent with observations of shore fouling in multiple geographic areas.

There have been surveys of the regional distribution of

Cladophora

and detailed area-specific studies of

Cladophora

productivity and ecology in recent years. Circumstantial evidence and simulation models suggest that growth rates and bloom formations increased following dreissenid mussel invasion.

Monitoring of biomass levels annually since 2006 indicates that while peak biomass varies among years there is no trend.

Lake Huron

Status: Fair

Trend: Undetermined

Rationale:

Cladophora

grows near suspected points of nutrient input over the Canadian and U.S. shorelines of the main basin where adjacent shoreline may also be fouled. In the absence of point sources of nutrients,

Cladophora

growth and biomass accrual is minimal in the main basin. Recently

Cladophora

has been detected at low densities at depths where wave scouring is reduced. However, there is insufficient monitoring information to determine if this represents a recent change. Shore fouling by algae thought to be composed partially of

Cladophora

has been reported in areas of Saginaw Bay (see below).

Lake Erie

Status: Poor

Trend: Undetermined

Rationale:

Cladophora

is widely distributed in the shallow nearshore Lake Erie, notably the northern shoreline of the eastern basin where hard substrate is widely distributed.

Cladophora

biomass reached nuisance levels following dreissenid invasion, and shoreline fouling is widespread along the Canadian portion of

111

the eastern basin. Circumstantial evidence and simulation models indicate that biomass and shoreline fouling increased following dreissenid invasion.

Lake Ontario

Status: Poor

Trend: Undetermined

Rationale:

Cladophora

is widely distributed in the nearshore covering a high proportion of the lakebed composed of hard substrate. Reported biomass levels at multiple locations, particularly at sites influenced from point sources of nutrients, exceed threshold nuisance conditions. There have been surveys of the regional distribution of

Cladophora

and detailed area-specific studies of

Cladophora

ecology in recent years. There is insufficient information to determine if the distribution and abundance of

Cladophora

has changed in recent years.

Other Spatial Scales

Saginaw Bay

Status: Undetermined

Trend: Undetermined

Rationale: Periodic fouling of shoreline and beaches in Saginaw Bay by decaying plant material of mixed composition termed "muck" appears to be a long-standing feature of parts of Saginaw Bay which predates the arrival of dreissenid mussels (Craig Stow personal communications).

Cladophora

contributes to the varying mix of plants that includes macrophytes,

Chara

, other filamentous algae and diatoms (periphyton) that accumulates on the shoreline. The contribution of

Cladophora

to shore fouling is not well defined at this time.

Purpose

To evaluate temporal and spatial trends in biomass and areal coverage of

Cladophora

in the Great Lakes.

Data can be used to infer the availability of

Cladophora

to be transported to the lake shore where it may foul beaches and clog water intakes.

The

Cladophora

indicator is used in the Great Lakes indicators suite as an indicator in the Human Impacts top level reporting category.

Ecosystem Objective

Cladophora

should not be found at nuisance levels (criteria discussed below). Waters and beaches should be safe for recreational use and be free from nuisance algae which may negatively impact water intake infrastructure and beach use. This indicator supports Annexes 3 and 11 of the GLWQA.

Ecological Condition

Background

Prior to the mid-1980s, fouling of shorelines by rotting mats of the filamentous green algae

Cladophora

was common place in parts of the lower Great Lakes. Excessive

Cladophora

growth and bloom formation during this period were associated with phosphorus pollution. An apparent hiatus of

Cladophora

blooms and shore fouling from the mid 1980s until the mid 1990s has been interpreted, based on limited field monitoring and hind casting using field-calibrated growth models and historical water quality data, as a positive outcome of the reduction in phosphorus loading to the Great Lakes set in place by the Great Lakes Water Quality Agreement. Beginning in the mid-1990 there have been growing numbers of reports of shore fouling including areas that did not experience shore fouling in the past. Today

Cladophora

contributes to degradation of the aesthetic value of Great Lakes beaches and waterfronts and sporadically fouls water intakes of power plants. Researchers in Canada and the US have examined the present day occurrence of

Cladophora

in parts of lakes Ontario, Erie, Michigan and Huron and confirm the

112

overabundance of

Cladophora

and associated shore fouling dispersed over wide areas around the Great Lakes.

Detailed accounts of

Cladophora

as a nuisance algae in the Great Lakes and the recent changes in environmental condition facilitating the proliferation of

Cladophora

today are given by Auer and Bootsma (2008), Auer et al.

(2010), Bootsma et al. (2004) and Higgins et al. (2008).

The colonization of the Great Lakes by zebra and quagga mussels (dreissenid mussels) has had a strong effect on lake ecosystems including features which are influential to the growth of benthic algae such as increased bioavailability of nutrients, increased water clarity and increased distribution of hard surfaces (dreissenid shells) that

Cladophora

filaments can attach. Increased water clarity associated with particle-filtering activity of dreissenid mussels acts to reduce light limitation of algae growth with depth and increase the area of lakebed available to support growth of benthic algae. In short, the more light reaching the lakebed means more habitat available for growth. The positive effects of changed water clarity on

Cladophora

production have been documented for lakes

Ontario, Erie and Michigan (Higgins et al. 1995; Malkin et al. 2008; Tomlinson et al. 2010).

Recent surveys across lakes Erie, Ontario, Michigan, and Huron indicate that

Cladophora

growth in these lakes are limited by phosphorus availability. A challenging and still evolving question concerns the role that dreissenid mussels play in facilitating the supply of phosphorus to support the growth of algae on the lakebed including

Cladophora.

Dreissenid mussels scavenge nutrients in particulate form from the water column through active filtration and subsequently release phosphorus in dissolved form and in particulate form as feces, or pseudofeces. It remains to be determined whether increased quantity and bioavailability of phosphorus associated with dreissenid waste products are a significant part of the nutrient budget of

Cladophora

, and under what conditions. From a management perspective, understanding the role of dreissenid mussels in the nutrition of

Cladophora

is critical because this knowledge is needed to predict how growth rates and bloom formations will react to changes in phosphorus loading at various geographic scales (e.g. local point sources, basin scale, regional scale). The potential management of

Cladophora

(lakewide and at locally enriched sites) is dependent on an accurate understanding of the relationship between external inputs of phosphorus and

Cladophora

productivity. While it is currently possible to predict

Cladophora

growth rates (and the potential for blooms) based on ambient phosphorus concentrations, it remains difficult to make such predictions based on external loads due to the uncertain role of the dreissenids in modifying exposure to phosphorus. What is clear is that the proliferation of

Cladophora

in Lake Ontario and Lake

Michigan is not attributable to increased basin-scale nutrient concentrations. Open lake concentrations of phosphorus have been trending downward in both lakes over the period of the apparent resurgence in

Cladophora

.

Paradoxically, the wide dispersal of high

Cladophora

biomass over the nearshore areas of lakes Erie, Ontario and

Michigan indicates that at some base level the overabundance is supported by basin-scale nutrient levels. Such changes suggest that the bioavailability of Phosphorus has increased since dreissenid invasion. The absence of wide-spread

Cladophora

in the more phosphorus-poor lakes Huron and Superior is consistent with this hypothesis.

Nutrient regimes in the nearshore can be highly variable with scope for local and/or regional nutrient inputs to affect productivity of

Cladophora

as has historically been the case in Lake Huron. Recent studies in Lake Ontario indicate that

Cladophora

biomass is higher in urbanized areas than over less developed shoreline (Higgins et al. pending).

Biomass and Areal Cover of

Cladophora

as Metrics of Occurrence

Field based assessment of the distribution and abundance of

Cladophora

is challenging due to the high spatial and temporal variability that characterize

Cladophora

growth, biomass accrual, and sloughing (e.g. detachment from lake bottom and physical transport to beaches or depositional zones).

Cladophora

biomass can be highly variable across relatively short timeframes (days to weeks), complicating the comparison of biomass (e.g. evaluating trends) over space (e.g. between lakes) or over longer time frames (between years). The effects of variable growth rate on standing biomass is further complicated by the ongoing and erratic sloughing of the attached algae by water movement which periodically transports algae to the shoreline with increasing frequency as water temperature rise over the summer. Such complications are well documented features of the ecology of

Cladophora

in the Great

Lakes (see Journal of Great Lakes Research 1982

Cladophora

special issue; Higgins et al. 2008).

113

Nonetheless, given appropriate consideration for seasonality, biomass, areal coverage, and nutrient content of filaments can be useful indicators of the status of

Cladophora

and water quality. First, sub-optimal timing of sampling will tend to underestimate biomass and areal coverage. None-the-less, where field measurements of biomass or cover indicate that nuisance conditions exist, they most likely do. Second, while estimates of biomass suffer from problems of accuracy and precision, it is generally possible to determine whether nuisance conditions are a lake-wide phenomenon or a response to localized conditions (e.g. point source nutrient loading). Such a distinction is critical for management, since the management response should occur at the appropriate spatial scale to effectively address the problem (i.e. lake wide or localized nutrient abatement strategies). The capacity of

Cladophora

to respond to localized areas of nutrient input at the shoreline, especially obvious in areas where

Cladophora

does not occur on a regional scale, complicates the reporting of occurrence data. Random placement of measurement sites over the nearshore can provide an area-wide appraisal of conditions; however, it may not detect problematic shoreline fouling that is focused at localized areas of

Cladophora

growth along the shoreline. Reliance on broader scale assessment of areal cover using remote or visual semi-qualitative methods may offer means to augment surveys. The depth distribution of

Cladophora

is variable among areas. Abundance with depth is influenced by onshore-offshore gradients in water clarity, nutrients, physical disturbance, substrate, temperature and possibly abundance of dreissenid mussels. Since the depth of maximal biomass is variable there is no one optimal depth of where sampling should occur. Typically, biomass is highest below the wave zone (> 0.5m depth) where scouring can reduce standing crop, and above the depth where light becomes growth limiting (variable among sites).

In general it is optimal to survey several depths at each site. Available data for

Cladophora

biomass and coverage is reported in Figures 1 and 2. Where data was available for multiple depths, the finding for the depth of maximum development of

Cladophora

is reported.

Previous efforts have indicated that areal density (areal coverage x height of the

Cladophora

bed from the lake bottom) can be effectively used to provide reasonable estimates of biomass (Howell 1998, Higgins et al. 2005).

Such an approach, combined with deployable camera systems, or hydroacoustics (Depew et al. 2009), may be a useful means to increase the spatial coverage of sampling activities. A three level status evaluation is suggested until a more robust approach is developed and tested: 1) Poor is the condition where there is high surface cover

(>50%) of

Cladophora

over optimal habitat on a regional-scale and where multiple locations surveyed by random sampling designs reach biomass levels that exceed the nuisance threshold of 50 g/m

2

dry weight ( see Canale and

Auer 1982), 2) Fair is when neither of the criteria for poor are met but where there are multiple areas of localized growth of

Cladophora

on the lakebed which result in public complaints of fouling over limited portions of shoreline, and, 3) Good is when

Cladophora

is largely absent in quantities that result in shore fouling prompting public complaint. See figures 1 to 3 for a summary of

Cladophora

occurrence data.

The nutrient content of

Cladophora

filaments is a useful metric of the potential for nutrient abatement programs to be effective in controlling growth. While quantities of potentially limiting nutrients may be highly variable

(spatially and temporally) in the overlying water column, or below analytical detection limits, values of these nutrients within

Cladophora

tissues represent their availability for growth. While concentrations of carbon, nitrogen and phosphorus in Cladophora biomass are sometimes measured, it is phosphorus that most often limits growth rates in the Great Lakes region and is the most informative (Higgins et al. 2008). Levels of phosphorus are typically expressed as a proportion of dry mass (Q

P

). There has been a significant amount of research devoted to linking tissue concentrations of phosphorus to potential growth rates (e.g. Auer and Canale 1982, Painter and Jackson

1989). Generally, values of Q

P

exceeding 1.6 mg P/g are considered saturated in P, values between 0.16 and 0.06 mg P/g are considered P limited, and values below 0.06 mg P/g are insufficient to sustain growth rates and are thus critically limiting. As with biomass, Q

P

exhibits intra-site variability and care is required to account for the effects of seasonality and of non-nutrient related factors affecting Q

P

(e.g. light level) when comparing Q

P

among areas or years.

114

Availability of

Cladophora

Monitoring data

The 2008 Great Lakes/SOLEC report "

Cladophora

in the Great Lakes: Guidance for Water Quality Managers" critiques monitoring of

Cladophora

in the Great Lakes. Briefly, monitoring of the status of

Cladophora

in the Great

Lakes after about 1985 was largely lacking until recently when the apparent resurgence was reported in Lake

Ontario, Erie and Michigan. Monitoring is sporadic and proceeds largely independently in pockets often supported by area-specific research activities. The lack of any systematic, Great lakes-wide monitoring of

Cladophora

has been repeatedly cited as a shortcoming in understanding present day

Cladophora

shore fouling problems. Despite being a widespread problem in the lower Great Lakes, information on the occurrence of

Cladophora

is primarily associated with the work of a small number of research groups examining the environmental basis for the apparent resurgence following dreissenid invasion, and is generally geographically-focused in areas where algae fouling problems occur. There have been agency based monitoring surveys of

Cladophora

distribution over parts of Lakes

Ontario, Erie, Michigan and Huron. Surveys of the distribution of

Cladophora

in Lake Ontario were included in the study design for the bi-national cooperative monitoring of the coastal zone in 2008 (Higgins et al. pending).

At present there is little information with which to assess year to year variability in the occurrence of

Cladophora

in areas of high abundance.

It is not known whether the abundance of

Cladophora

is changing in any consistent manner with the exception of Lake Michigan where biomass has been monitored on a regular basis since 2006 by researchers at the University of Wisconsin-Milwaukee (Figure 4). Notable in this work is the attention to through time data collection to identify peak seasonal abundance allowing robust comparisons of

Cladophora

biomass among years. The wide variability in biomass among years in the absence of a temporal trend (Figure 4) suggests that monitoring of

Cladophora

to detect change will be demanding.

Development of a Great Lakes

Cladophora

Monitoring Strategy

Recent publications have made recommendations on how monitoring of

Cladophora

in the Great Lakes might be improved. Auer et al. (2010) recommended that biomass and nutrient status of

Cladophora

tissues are the most practical choice of metrics for characterizing nuisance

Cladophora

conditions over space and time. The assessment of

Cladophora

biomass and nutrient status at a limited number of sentinel sites around the Great Lakes would be a useful means to determine temporal trends (within and between years) and provide data for calibrating/validating

Cladophora

growth models. Sites within each lake should be geographically dispersed, include areas where growth is driven primarily by lake-wide nutrient concentrations and also sites where growth is driven by point sources (i.e. tributaries, sewage or industrial discharges, etc.). Methodologies for such monitoring programs are relatively simple and low-cost, but are labor intensive and sensitive to the timing of surveys (Higgins et al. 2005, 2008; Auer et al.

2010). While useful as sentinels, the ability of a monitoring program focused on a limited number of sites to capture the status of

Cladophora

at larger spatial scales (i.e. basin, lake, region) is limited.

New and emerging tools are potentially available to augment, and increase the efficacy of, survey techniques to assess the distribution and abundance of

Cladophora

. Recently, hydro-acoustic technologies have been used to map

Cladophora

distribution patterns across larger spatial scales (kilometers) than could be accomplished with snorkeling or diver based (meters) surveys (Depew et al. 2009). The use of remote sensing to determine large-scale distribution patterns of

Cladophora

is being evaluated by researchers at Michigan Technological University (Sayers et al. 2011) and elsewhere. Images in the visible light range collected by satellite are evaluated using algorithms which interpret the presence of algae on the shallow lakebed in terms of surface coverage and biomass concentration. Examples of remotely estimated distributions of

Cladophora

on the shores of Lake Michigan and

Ontario are presented in Figure 5. Such an approach holds promise to assess distribution of

Cladophora

in the Great

Lakes at lake-wide and regional scales.

Originally developed during the late 1970’s (Auer et al. 1982),

Cladophora

growth models have recently been revised to address conditions post-dreissenid invasion (Higgins et al. 2005, 2006; Tomlinson et al. 2010). Such models are useful to assess management options at local, and to some degree, lake-wide scales. However, such

115

models require intensive sampling efforts to provide model inputs (e.g. solar insolation, water clarity, temperature, soluble phosphorus) at sufficient spatial and temporal resolution for model simulations to be meaningful. Efforts are currently underway to link

Cladophora

growth models with three-dimensional lake-wide hydrodynamic-biological models that provide the necessary environmental input data required to estimate

Cladophora

growth at moderate spatial scales (e.g. 50m x 50m). If successfully calibrated and validated, such models will be highly useful tools to advise potential management approaches to controlling

Cladophora

blooms at local, lake-wide and regional scales.

Ideally, opportunities for the testing and evaluation of candidate techniques can be integrated with ongoing monitoring and research studies with the aim of working towards more in depth monitoring of

Cladophora

distribution in the future.

Linkages

The growth of

Cladophora

in an area is potentially affected by a range of factors both operating within the lake ecosystem and acting externally upon the lake. The linkages to other SOLEC indicators vary in directness. For example indicators for Nutrients in Lakes and Water Clarity under the Water Quality suite of indictors describe measures which relate to growth limiting factors for

Cladophora

. Whereas the indicators Dreissenid Mussels and

Benthos Diversity and Abundances may be correlated with the occurrence levels of

Cladophora

and connected by indirect mechanisms that may or may not be understood. Similarly, indicators under the Landscape and Natural

Processes as well as the Pollution and Nutrients Suite capture changes in the broader environment which may contribute to a changing nutrient regime in the lake (Inland Water Quality Index and Tributary Flashiness ) or inlake growing conditions (Water Levels and Surface Water Temperatures) that may be correlated with

Cladophora

.

Management Challenges/Opportunities

The fouling of shoreline by

Cladophora

and other forms of algae elicits public complaint and is perceived as a sign of deteriorating water quality. Limited information on the extent and temporal features of shore fouling, and the underlying causative factors (i.e. abundance of algae on the lakebed) have made it difficult to understand the scope of the problem in any robust sense. This indicator can work towards a better understanding of the extent of the problem assuming that more effort goes into monitoring of

Cladophora

. The reported interactions between dreissenid mussels and environmental conditions which may promote the growth of

Cladophora

means that greater incidence of shore fouling today then in the resent past does not necessarily mean that external nutrient pollution is changing. Education to help the public better understand shore fouling by

Cladophora

will need to be an ongoing.

The indicator may have a role as part of a broader communication effort.

Comments from the author(s)

The ability to fit

Cladophora

biomass or cover data to end points predicting adverse levels of shore fouling is a desirable attribute of an environmental indicator for

Cladophora

. The often cited value of 50 gDW m

2

as a threshold for transition to nuisance conditions was developed prior to colonization by dreissenid mussels and should be re-examined under present day conditions considering that the depth distribution of

Cladophora

is generally deeper today and that the shoreline may accumulate algae from deeper depths then in the past. A metric describing incidence of shoreline fouling based on field observation or public complaints to responsible authorities, or beach postings should be considered as a complimentary element of a

Cladophora

indicator. Notwithstanding the significance of the occurrence of

Cladophora

on the lakebed as an indicator of ecosystem condition, the overabundance of

Cladophora

is considered a water quality problem primarily due to the fouling of shoreline and beaches by detached algae.

While

Cladophora

represents the bulk of the shore fouling algae at many locations, there are additional species of benthic green algae which can occur in areas affected by

Cladophora

shore fouling. Filamentous green algae of the family zgnemataceae (e.g.

Spirogyra

,

Zygnema

and

Mougeotia

) are often observed co-occurring with

Cladophora.

In parts of lakes Huron and Michigan, the filamentous green algae

Chara

also contributes to fouling of shoreline. A

116

further contributor to the organic material dominated by

Cladophora

which washes up on the shoreline is a diverse assemblage of micro algae which grow amongst and upon

Cladophora

and are more generally termed periphyton.

In some cases there may be a "muck-like" appearance to beached material which is likely due to the contribution of periphyton.

Assessing Data Quality

Data Characteristics

1. Data are documented, validated, or quality-assured by a recognized agency or organization

2. Data are traceable to original sources

3. The source of the data is a known, reliable and respected generator of data

4. Geographic coverage and scale of data are appropriate to the Great Lakes basin

5. Data obtained from sources within the

U.S. are comparable to those from Canada

6. Uncertainty and variability in the data are documented and within acceptable limits for this indicator report

Strongly

Agree

Agree

X

X

X

X

X

X

Neutral or

Unknown

X

Disagree

Strongly

Disagree

Not

Applicable

X

Acknowledgments

Authors:

Todd Howell, Ontario Ministry of the Environment and Scott Higgins, Department of Fisheries and Ocean Canada

Contributors:

Harvey Bootsma, Great Lakes Water Institute, University of Wisconsin-Milwaukee, Milwaukee, Wisconsin, USA

Chris Pennuto, Biology Department and Great Lakes Research Center, Buffalo, USA

Craig Stow. NOAA Great Lakes Environmental Research laboratory, Ann Arbor, Michigan, USA

Mike Sayers, Michigan Tech Research Institute, Ann Arbor, Michigan, USA

References

Auer, M.T., and Bootsma, H.A. 2008. Nearshore areas of the Great Lakes 2008 - Draft,

Cladophora

in the Great

Lakes: guidance for water quality managers. State of the Lakes Ecosystem Conference 2008.

Auer, M.T., Tomlinson, L.M., Higgins, S.N. Malkin, S.Y. Howell, E.T. and Bootsma, H.A. 2010. Great Lakes

Cladophora

in the 21st century: same algae -different ecosystem. J. Great Lakes Res. 36:248-255.

Bootsma, H.A., Jensen, E.T., Young, E.B., Berges, J.A. 2005.

Cladophora

research and management in the Great

Lakes. Proceeding of a workshop held at the Great Lakes Water Institute, University of Wisconsin-

Milwaukee, December 8, 2004. Great Lakes Water Institute Special Report 2005-01.

Canale, R.P. and Auer, M.T. 1982. Ecological studies and mathematical modeling of

Cladophora

in lake Huron: 7.

Model verification and system response. J.Great Lakes Res. 8: 134-143

Depew, D.C., Stevens, A.W., Smith, R.E.H., Hecky, R.E. 2009. Detection and characterization of benthic filamentous algae stands (

Cladophora

sp.) on rocky substrata using a high-frequency echosounder. Limnol.

Oceanogr.: Methods 7: 693-705.

Higgins, S.N., Hecky, R.E., Hecky, R.E., and Guildford S.J. 2006. Environmental controls of Cladophora growth dynamics in eastern Lake Erie: application of the Cladophora growth model (CGM). J. Great Lakes Res.

32: 629-63.

Higgins, S.N., Howell, E.T., Hecky, R.E., Guildford, S.J., Smith R.E. 2005. The wall of green: the status of

Cladophora glomerata

on the northern shores of Lake Erie's eastern basin, 1995-2002.. J. Great Lakes Res.

31:547-63.

117

Higgins, S.N., Malkin, S.Y, Howell, E.T., Guildford, S.J., Campbell, L., Hiriart-Baer, V., Hecky, R.E., 2008. An ecological review of the

Cladophora glomerata

(Chlorophyta) in the Laurentian Great Lakes. J. Phycol.

44: 839- 854.

Higgins, S,N. , Pennuto, C.M., Howell, E.T., Lewis, T. and Makarewicz, J.C. 2012. Urban influences on

Cladophora

blooms in Lake Ontario. J. Great Lakes Res. 38 (supplement 4): 116-123

Howell, E.T. 1998. Occurrence of the alga

Cladophora

along the north shore of eastern Lake Erie in 1995. Ontario

Ministry of the Environment. PIBS 3716E

Malkin, S.Y., Guilford, S.J., Hecky, R.E., 2008. Modelling the growth response of

Cladophora

in a Laurentian

Great Lake to the exotic invader Dreissena and to lake warming. Limnol. Oceanogr. 53, 1111-1124.

Painter, D.S. and Jackson, M.B. 1989.

Cladophora

internal P modelling: verification. J.Great Lakes Res. 15: 1522-7

Sayers, M.J., Brooks, C.N. and Shuchman, R.A. 2011. Mapping

Cladophora

in the Great Lakes using multi-scale satellite imagery. Abstract. 54th Conference of the International Association for Great Lakes Research

Tomlinson, L.M, Auer, M.T., Bootsma, H.A. and Owens, E.M. 2010. Great Lakes

Cladophora

Model:

Development, testing and application to Lake Michigan J. Great Lakes Res. 36:287-297.

Additional Cladophora information sources:

Depew, D.C. 2009.

Cladophora

growth in littoral environments of large lakes: spatial complexity and ecological interpretations. Ph.D. thesis. University of Waterloo.

Garrison, P and Greb, S. 2005.

Cladophora

and water quality of Lake Michigan: A systematic survey of Wisconsin

Nearshore Area. In

Cladophora

Research and Management in the Great Lakes. Proceeding of a workshop held at the Great Lakes Water Institute, University of Wisconsin-Milwaukee, December 8, 2004. Great

Lakes Water Institute Special Report 2005-01.

Garrison, P.J. Greb, S.R., Labiberte, G. 2008. Western Lake Michigan Nearshore Survey of Water Chemistry and

Cladophora

Distribution. Wisconsin Department of Natural Resources, Bureau of Science Services. PUB-

SS-1038.

Cladophora "Hot Spots" http://www.ngdc.noaa.gov/mgg/greatlakes/michigan.html

Saginaw Bay algae muck. http://www.oar.noaa.gov/spotlite/archive/2009/articles/multiple_stressors.html

List of Figures

Figure 1

. Maximum biomass levels reported for Great Lakes sites since 2005.

Source:

Lake Ontario

- Depew 2009; Higgins et al. 2012, Malkin et al. 2008;

Lake Erie

- Depew 2009, T. Howell unpublished data, ;

Lake Huron

- Depew 2009, T. Howell unpublished data;

Lake Michigan

- H. Bootsma unpublished data, Garrison et al. 2008, Tomlinson et al. 2010.

Figure 2

. Maximum percent cover levels reported for Great Lakes sites since 2005.

Source:

Lake Ontario

T. Howell unpublished data, C. Pennuto unpublished;

Lake Erie

- T. Howell unpublished data;

Lake Huron

- T. Howell unpublished data.

Figure 3

. Locations where there have been reports of nuisance

Cladophora

since 1995. Nuisance defined broadly as including: causing fouling of shoreline and beaches, fouling of water intakes and areas reported with conspicuous presence of

Cladophora

.

Source:

Lake Ontario

- Howell unpublished data, C. Pennuto unpublished data;

Lake Erie

- Howell 1998, C.

Pennuto unpublished data;

Lake Huron

- Saginaw Bay algae muck. http://www.oar.noaa.gov/spotlite/archive/2009/articles/multiple_stressors.html, Howell unpublished data;

Lake

Michigan

- H. Bootsma unpublished data, Cladophora "Hot Spots" http://www.ngdc.noaa.gov/mgg/greatlakes/michigan.html, Garrison and Greb 2005.

Figure 4.

Seasonal biomass of

Cladophora

from 2006 to 2011 in the nearshore of Lake Michigan at a site near

Milwaukee.

Source: Graph provided courtesy of Harvey Bootsma, Great Lakes Water Institute, University of Wisconsin-

Milwaukee.

118

Figure 5

. Examples of Areal distribution of

Cladophora

determined by remote sensing.

Source: Images courtesy of by M. Sayers, Michigan Tech Research Institute.

Last Updated

State of the Great Lakes 2011

Figure 1

. Maximum biomass levels of Macro Algae (

Cladophora

) on the lakebed reported for Great Lakes sites since 2005.

Source:

Lake Ontario

- Depew 2009; Higgins et al. 2012, Malkin et al. 2008;

Lake Erie

- Depew 2009, T. Howell unpublished data, ;

Lake Huron

- Depew 2009, T. Howell unpublished data;

Lake Michigan

- H. Bootsma unpublished data, Garrison et al. 2008, Tomlinson et al. 2010.

119

Figure 2

. Maximum percent surface cover levels by Macro Algae (

Cladophora)

reported for Great Lakes sites since 2005.

Source:

Lake Ontario

T. Howell unpublished data, C. Pennuto unpublished;

Lake Erie

- T. Howell unpublished data;

Lake Huron

- T. Howell unpublished data.

120

Figure 3

. Locations where there have been reports of nuisance

Cladophora

since 1995. Nuisance defined broadly as including: causing fouling of shoreline and beaches, fouling of water intakes and reported areas of conspicuous presence of

Cladophora

.

Source:

Lake Ontario

- Howell unpublished data, C. Pennuto unpublished data;

Lake Erie

- Howell 1998, C.

Pennuto unpublished data;

Lake Huron

- Saginaw Bay algae muck. http://www.oar.noaa.gov/spotlite/archive/2009/articles/multiple_stressors.html

, Howell unpublished data;

Lake

Michigan

- H. Bootsma unpublished data, Cladophora "Hot Spots" http://www.ngdc.noaa.gov/mgg/greatlakes/michigan.html

, Garrison and Greb 2005

Figure 4

. Seasonal biomass of

Cladophora

from 2006 to 2011 in the nearshore of Lake Michigan (~5 km north of

Milwaukee, depth = 9 m).

Source: Graph provided courtesy of Harvey Bootsma, Great Lakes Water Institute, University of Wisconsin-

Milwaukee.

121

Figure 5

. Distribution of

Cladophora

in NE Lake Michigan and NW Lake Ontario determined by remote sensing.

Source: Images courtesy of by M. Sayers, Michigan Tech Research Institute.

122

Coastal Wetland Amphibians

Overall Assessment

Status: Poor

Trend: Unchanging

Rationale: The occurrence of over half the species was stable between 1995 and 2010 (5 of 8 [63%]), whereas the occurrence of two species significantly increased (25%) and one significantly decreased (12%).

The occurrence of each species is below its endpoint.

Lake-by-Lake Assessment

Lake Superior

Status:

Trend:

Undetermined

Undetermined

Lake Michigan

Status: Poor

Trend: Unchanging

Rationale: The occurrence of about half of the species significantly decreased between 1995 and 2010 (3 of 7

[43%]), whereas the occurrence of one species significantly increased (14%) and three were stable

(43%). The occurrence of each species is below its endpoint.

Lake Huron

Status: Poor

Trend: Unchanging

Rationale: The occurrence of about half of the species significantly decreased between 1995 and 2010 (3 of 7

[43%]), whereas the occurrence of one species significantly increased (14%) and three were stable

(43%). The occurrence of each species is below its endpoint.

Lake Erie

Status:

Trend:

Poor

Unchanging

Rationale: The occurrence of over half of the species was stable between 1995 and 2010 (4 of 7 [57%]), whereas the occurrence of one species significantly increased (14%) and two significantly decreased (29%). The occurrence of each species is below its endpoint.

Lake Ontario

Status: Poor

Trend: Unchanging

Rationale: The occurrence of about half of the species significantly increased between 1995 and 2010 (3 of 7

[43%]), whereas the occurrence of one species significantly decreased (14%) and three were stable

(43%). The occurrence of each species is below its endpoint.

Purpose

To assess changes in the relative occurrence of wetland-breeding anuran species (i.e., belonging to an order of amphibians comprised of frogs, toads, and tree frogs that lay their eggs in wetlands)

To infer condition of wetland habitat as it relates to factors that influence this ecologically and culturally important resource

The Coastal Wetland Amphibian indicator is used in the Great Lakes indicators suite as a State indicator in the Aquatic Dependent Life top level reporting category.

123

Ecosystem Objective

To restore and maintain self-sustaining populations of Great Lakes wetland-breeding anuran species across their historic ranges. Numerous wetlands in the Great Lakes basin are threatened by urban and agricultural development and other incompatible land uses and these wetlands should be identified, preserved, and where necessary rehabilitated (GLWQA Annex 13). Monitoring and assessment activities provide information on the location, severity, aerial or volume extent, and frequency of Great Lakes wetlands (Annex 11 GLWQA). This indicator supports the restoration and maintenance of the chemical, physical and biological integrity of the Great Lakes basin and beneficial uses dependent on healthy wetlands (Annex 2 GLWQA).

Ecological Condition

Measure

Changes in relative occurrence of wetland-breeding amphibians are based on data from nighttime surveys using Bird

Studies Canada’s Great Lakes Marsh Monitoring Program (MMP) anuran point count protocol or a modification of it (Marsh Monitoring Program 2009). MMP data from coastal and inland wetlands throughout the Great Lakes basin or throughout each individual lake basin (e.g., Lake Erie; Fig. 1) are used to calculate annual indices of relative occurrence for a suite of wetland anuran species. Wetlands dominated by non-woody emergent plants such as cattails (

Typha

spp.) and sedges (e.g.,

Carex

spp.) are targeted by the program. Species-specific population trends over time are calculated using repeated measures logistic regression in a Bayesian mode of inference with uninformative priors (Kéry 2010).

Endpoint

Populations of most wetland-breeding anuran species have declined or remained stable since data collection began for this indicator in 1995. Therefore, one endpoint is population indices for nearly all wetland-breeding anuran species that are as high as or higher than population indices reported by the MMP in the late 1990s, when the program began. A potentially better endpoint, however, might be based on MMP occurrence indices from pristine or near-pristine wetlands throughout the Great Lakes basin (i.e., least disturbed based on indices of anthropogenic disturbance within and surrounding the wetland) —guided by a literature search of other current and historical data and expert opinion. Population indices from this approach are likely to be higher than those reported by the MMP in the late 1990s, given that many wetlands throughout the Great Lakes basin were degraded by that time (e.g., Hecnar and M’Closkey 1996, 1998). Presumably the two approaches estimate the extremes of a range of occurrence that is likely to contain the carrying capacity that the landscape is currently capable of supporting and, therefore, somewhere near the middle of the range is the most suitable endpoint. This is the endpoint used in this report.

Background

Wetland-breeding amphibians are influenced by the physical, chemical, and biological components of the wetlands and surrounding landscapes in which they breed. The abundance and/or reproductive success of multiple species in the Great Lakes basin, for example, declines as (1) wetland size decreases; (2) wetland habitat and natural cover in the surrounding landscape decreases; and (3) pesticide, herbicide, and runoff from other sources of pollution into wetlands from the surrounding landscape increases (Hecnar 1995; Hecnar and M’Closkey 1996; Bishop et al. 1999;

Crosbie and Chow Fraser 1999; Kolozsvary and Swihart 1999; Houlahan and Findlay 2003; Price et al. 2004;

Brazner et al. 2007a,b; Gagné and Fahrig 2007; Eigenbrod et al. 2008b). Thus, the abundance of wetland-breeding amphibians is a valuable indicator of the health of wetlands and the surrounding landscape.

Status of Wetland Amphibians

A grand total of 13 anuran species were recorded across all surveys and years throughout the Great Lakes basin between 1995 and 2010. Of these, the data for eight species were suitable for analysis at the scale of the Great Lakes basin, whereas the data for seven species were suitable in each individual Great Lakes basin (Table 1). Data were suitable if the species occurred at >15 routes per year on average.

124

Great Lakes Basin

The occurrence of over half of the species was stable between 1995 and 2010 (5 of 8 [63%]), whereas the occurrence of Green Frog (

Rana clamitans

; see Table 1 for a list of scientific names for all subsequent common names) and Spring Peeper significantly increased and Chorus Frog significantly decreased (Fig. 2). Species that significantly increased made up 25% of the species analyzed and species that significantly decreased made up 12%.

Pollution from agricultural and urban areas is often identified as one of the leading causes of anuran declines in the

Great Lakes basin (e.g., Bishop et al. 1999). The relative resistance of Green Frogs to nitrates from fertilizer runoff may partly explain the increase in this species; nitrate resistance in Spring Peepers is unknown (Hecnar 1995, Rouse et al. 1999). By contrast, Chorus Frogs are more sensitive to nitrates, which may partly explain the decrease in this species (Hecnar 1995). The resistance of different anuran species to pollution, however, is complicated by variability in resistance among populations within species and by interactions with other factors such as habitat loss, which makes relationships difficult to identify. Spring Peeper is reportedly the most sensitive anuran to human disturbance in the Great Lakes basin, so its significant increase between 1995 and 2010 may be a positive sign, although it currently remains below its endpoint (Brazner et al. 2007a, Price et al. 2007). The status of the indicator is similar in previous reports, whereas the deteriorating trend in the previous report is now unchanging. The apparent improvement in the trend may be short-lived because there is high year-to-year variation in populations of most anuran species in the Great Lakes basin. Given that the occurrence of each species is below its endpoint and the occurrence of most species was stable between 1995 and 2010, the overall status is poor and the trend is unchanging.

Lake Michigan

The occurrence of about half of the species significantly decreased between 1995 and 2010 (3 of 7 [43%]), whereas the occurrence of one species significantly increased (14%) and three where stable (43%). The occurrence of each species is below its endpoint. The status of the indicator is similar in previous reports, whereas the deteriorating trend in the previous report is now unchanging. The apparent improvement in the trend may be short-lived because there is high year-to-year variation in populations of most anuran species in the Lake Michigan basin. Given that the occurrence of each species is below its endpoint and the occurrence of about half of the species was stable between

1995 and 2010, the overall status is poor and the trend is unchanging (Table 1).

Lake Huron

The occurrence of about half of the species significantly decreased between 1995 and 2010 (3 of 7 [43%]), whereas the occurrence of one species significantly increased (14%) and three where stable (43%). The occurrence of each species is below its endpoint. The status of the indicator is similar in previous reports, whereas the deteriorating trend in the previous report is now unchanging. The apparent improvement in the trend may be short-lived because there is high year-to-year variation in populations of most anuran species in the Lake Huron basin. Given that the occurrence of each species is below its endpoint and the occurrence of about half of the species was stable between

1995 and 2010, the overall status is poor and the trend is unchanging (Table 1).

Lake Erie

The occurrence of over half of the species was stable between 1995 and 2010 (4 of 7 [57%]), whereas the occurrence of one species significantly increased (14%) and two significantly decreased (29%). The occurrence of each species is below its endpoint. The status of the indicator is similar in previous reports, whereas the deteriorating trend in the previous report is now unchanging. The apparent improvement in the trend may be short-lived because there is high year-to-year variation in populations of most anuran species in the Lake Huron basin. Given that the occurrence of each species is below its endpoint and the occurrence of over half of the species was stable between

1995 and 2010, the overall status is poor and the trend is unchanging (Table 1).

Lake Ontario

The occurrence of about half the species significantly increased between 1995 and 2010 (3 of 7 [43%]), whereas the occurrence of one species significantly decreased (14%) and three where stable (43%). The occurrence of each

125

species is below its endpoint. The status and trend of the indicator is similar in previous reports. Given that the occurrence of each species is below its endpoint and the occurrence of about half of the species decreased between

1995 and 2010, the overall status is poor and the trend is unchanging (Table 1).

Linkages

Wetland-breeding amphibians are influenced by numerous characteristics of the wetlands and surrounding landscapes in which they breed, many of which are monitored as SOLEC indicators. The wetland anuran indicator can be expected to co-vary with indicators that track wetland breeding anuran habitat (e.g., #4863: Coastal Wetland

Plant Community; #4863: Land Cover Adjacent to Coastal Wetlands) and prey (#4501 Coastal Wetland Invertebrate

Community Health) and factors that indirectly influence them, such as pollution runoff from surrounding uplands

(#7100 Natural Groundwater Quality and Human-induced Changes), which reduces anuran prey abundance

(Camargo et al. 2005) and which also directly lowers survivorship of anuran eggs and/or adults. Wetland amphibians also can be expected to co-vary with road density (#7200 Land Cover/Land Conversion) and vehicle use

(#7064 Vehicle Use), given dispersing individuals are extremely vulnerable to vehicle collisions (Eigenbrod et al.

2008a), and amount of wetland buffering via natural vegetation (#7028 Sustainable Agriculture Practices), given pollution in runoff is trapped by such buffers (Rouse et al. 1999).

Management Challenges/Opportunities

Maintain or improve the quality of wetlands and adjacent uplands for breeding wetland amphibians by mitigating or eliminating influences that are detrimental to wetland health such as water level fluctuations, invasive species, and inputs of toxic chemicals, nutrients and sediments. Restoration programs are underway for many degraded wetland areas through the work of local citizens, organizations and governments. Although significant progress has been made, considerably more conservation and restoration work is needed to ensure maintenance of healthy and functional wetlands throughout the Great Lakes basin.

Comments from the author(s)

The utility of the Wetland Amphibians indicator is dependent on the continuation of the MMP across the Great

Lakes basin. Therefore, recruitment and retention of volunteer surveyors has been, and will continue to be, high priority. Despite this, there are areas where coverage is too sparse for analysis and could be improved (e.g., Lake

Superior). As a result, a power analysis was conducted to quantify the MMP’s ability to detect changes in occurrence of wetland-breeding anuran species at the scales explored in this report. The analysis suggests that the

MMP has 80% power to detect percent annual changes in occurrence as small as 1.0% in the Great Lakes basin;

2.0% in the Lake Erie and Ontario basins; and 2.5% in the Lake Michigan and Huron basins for most species (Fig.

3). These numbers should be considered preliminary and exploratory, however, until the effects of spatial and temporal dependence amongst surveys and detection probability can be fully assessed, which is an ongoing and evolving area of study (Seavy and Reynolds 2007, Patuxent Wildlife Research Center 2003).

Assessing Data Quality

Data Characteristics

1. Data are documented, validated, or qualityassured by a recognized agency or organization

2. Data are traceable to original sources

3. The source of the data is a known, reliable and respected generator of data

4. Geographic coverage and scale of data are appropriate to the Great Lakes basin

5. Data obtained from sources within the U.S. are comparable to those from Canada

Strongly

Agree

x x x x x

Agree

Neutral or

Unknown

Disagree

Strongly

Disagree

Not

Applicable

126

Data Characteristics

6. Uncertainty and variability in the data are documented and within acceptable limits for this indicator report

Strongly

Agree

x

Agree

Neutral or

Unknown

Disagree

Strongly

Disagree

Not

Applicable

Acknowledgments

Author:

Douglas C. Tozer, Aquatic Surveys Biologist, Bird Studies Canada, P.O. Box 160, 115 Front Street, Port Rowan,

ON N0E 1M0, [email protected]

; www.bsc-eoc.org/volunteer/glmmp/

Contributors:

Hundreds of volunteers who generously donate their time, equipment, and skills to ensure long-term, broad-scale monitoring of the health of Great Lakes wetlands.

Robert W. Rankin, Data Analyst, Bird Studies Canada, P.O. Box 160, 115 Front Street, Port Rowan, ON N0E

1M0. Rob provided much-appreciated analytical assistance.

Information Sources

Bishop, C.A., Mahony, N.A., Struger, J., Ng, P., and Pettit, K.E. 1999. Anuran development, density and diversity in relation to agricultural activity in the Holland River watershed, Ontario, Canada (1990-1992). Environmental monitoring and assessment 57:21-43.

Brazner, J.C., Danz, D.P., Niemi, G.J., Regal, Trebitz, A.S., Howe, R.W., Hanowski, J.M., R.R., Johnson, L.B.,

Ciborowski, J.J.H., Johnston, C.A., Reavie, E.D., Brady, V.J., and Sgro, G.V. 2007a. Evaluation of geographic and human influences on Great Lakes wetland indicators: a multi-assemblage approach. Ecological Indicators

7:610-635.

Brazner, J.C., Danz, D.P., Trebitz, A.S., Niemi, G.J., Regal, R.R., Hollenhorst, T., Host, G.E., Reavie, E.D., Brown,

T.N., Hanowski, J.M., Johnston, C.A., Johnson, L.B., Howe, R.W., and Ciborowski, J.J.H. 2007b.

Responsiveness of Great Lakes wetland indicators to human disturbances at multiple spatial scales: a multiassemblage assessment. Journal of Great Lakes Research 33(Special Issue 3):42-66.

Camargo, J.A., Alonso, A., Salamanca, A. Nitrate toxicity to aquatic animals: a review with new data for freshwater invertebrates. Chemosphere 58:1255-1267.

Crosbie, B. and Chow Fraser, P. 1999. Percentage land use in the watershed determines the water and sediment quality of 22 marshes in the Great Lakes basin. Canadian Journal of Fisheries and Aquatic Sciences 56:1781-

1791.

Eigenbrod, F., Hecnar, S.J., Fahrig, L. 2008a. Accessible habitat: an improved measure of the effects of habitat loss and roads on wildlife populations. Landscape Ecology 23:159-168.

Eigenbrod, F., Hecnar, S.J., Fahrig, L. 2008b. The relative effects of road traffic and forest cover on anuran populations. Biological Conservation 141:35-46.

Gagné, S.A. and Fahrig, L. Effect of landscape context on anuran communities in breeding ponds in the National

Capital Region, Canada. Landscape Ecology 22:205-215.

Hecnar, S.J. 1995. Acute and chronic toxicity of ammonium nitrate fertilizers to amphibians from southern Ontario.

Environmental Toxicology and Chemistry 14:2131-2137.

Hecnar, S.J. and M’Closkey, R.T. 1996. Regional dynamics and the status of amphibians. Ecology 77:2091-2097.

Hecnar, S.J. and M’Closkey, R.T. 1998. Species richness patterns of amphibians in southwestern Ontario ponds.

Journal of Biogeography 25:763-772.

Houlahan, J.E. and Findlay, C.S. 2003. The effects of adjacent land use on wetland amphibian species richness and community composition. Canadian Journal of Fisheries and Aquatic Sciences 60:1078-1094.

Kéry, M. 2010. Introduction to WinBUGS for ecologists: a Bayesian approach to regression, ANOVA, mixed models and related analyses. Academic Press, Amsterdam.

Kolozsvary, M.B. and Swihart, R.K.. 1999. Habitat fragmentation and the distribution of amphibians: patch and

127

landscape correlates in farmland. Canadian Journal of Zoology 77:1288-1299.

Marsh Monitoring Program. 2009. Marsh Monitoring Program participant’s handbook for surveying amphibians, revised 2008. Published by Bird Studies Canada in cooperation with Environment Canada and the U.S.

Environmental Protection Agency.

Patuxent Wildlife Research Center. 2003. Status of the “Monitor” web site [online]. Available from http://www.pwrc.usgs.gov/resshow/droege3rs/salpower.htm

[accessed 28 June 2011].

Price, S.J., Howe, R.W., Hanowski, J.M., Regal, R.R., Niemi, G.J., and Smith, C.R. 2007. Are anurans of Great

Lakes coastal wetlands reliable indicators of ecological condition? Journal of Great Lakes Research 33:211-223.

Price, S.J., Marks, D.R., Howe, R.W., Hanowski, J.M., and Niemi, G.J. 2004. The importance of spatial scale for conservation and assessment of anuran populations in coastal wetlands of the western Great Lakes, USA.

Landscape Ecology 20:441-454.

Rouse, J.D., Bishop, C.A., and Struger, J. Nitrogen pollution: an assessment of its threat to amphibian survival.

Environmental Health Perspectives 107:799-803.

Seavy, N.E. and M.H. Reynolds. 2007. Is statistical power to detect trends a good assessment of population monitoring? Biological Conservation 140:187-191.

List of Tables

Table 1. Population trends of wetland-breeding anuran species used to assess the health of wetlands and their surrounding landscapes in the Lake Michigan, Huron, Erie, and Ontario basin, based on occurrence indices derived from Marsh Monitoring Program point count surveys between 1995 and 2010. Statistically significant trends are indicated by * (i.e., Bayesian credible intervals do not overlap zero). Note that sample sizes were insufficient to analyze Wood Frog within individual lake basins.

Source: Great Lakes Marsh Monitoring Program.

List of Figures

Figure 1.

Mean (±SD) number of Marsh Monitoring Program routes surveyed for amphibians per year in the Great

Lakes basin (All) and in each individual Great Lakes basin (e.g., Superior) between 1995 and 2010. A route consists of multiple, spatially-clustered point count survey locations, typically located in the same wetland, all of which can be surveyed by the same person in a single visit.

Source: Great Lakes Marsh Monitoring Program.

Figure 2.

Percent annual change of occurrence indices for some wetland-breeding anuran species from 1995 to 2010 in the Great Lakes basin. Indices estimated with repeated-measures logistic regression. Statistically significant positive trends are green, significant negative trends are red, and stable (non-significant) trends are white. Bayesian credible intervals did not overlap zero for significant trends.

Source: Great Lakes Marsh Monitoring Program.

Figure 3.

Box-and-whisker plots showing minimum detectable annual change (%) of occurrence indices of some wetland-breeding anuran species in the Great Lakes basin (All) and in individual Great Lakes basins (e.g.,

Michigan), derived from Great Lakes Marsh Monitoring Program data. The figure summarizes the 7 (Michigan,

Huron, Erie, Ontario) or 8 (All) species used to assess wetland health in this report.

Source: Great Lakes Marsh Monitoring Program.

Last Updated

State of the Great Lakes 2011

report

128

320

280

240

200

160

120

80

40

0

Population trends of wetland-breeding anuran species

Common Name Scientific Name Michigan

American Toad

Bullfrog

Chorus Frog

Green Frog

Gray Treefrog

Northern Leopard Frog

Spring Peeper

Wood Frog

TOTAL

Bufo americanus

Rana catesbeiana

Pseudacris triseriata

Rana clamitans

Hyla versicolor

Rana pipiens

Pseudacris crucifer

Rana sylvatica

8

+0.7

+4.0

+1.0

*+4.9

*-5.6

*-5.5

*-8.3

7

Huron

*-5.5

*+4.0

*-8.6

*-4.0

+0.4

-1.2

+2.8

7

Erie

+0.2

-1.2

*-9.9

*+3.4

+0.5

*-1.4

+1.4

7

Ontario

-2.1

-1.8

*-5.1

*+5.8

-0.9

*+2.5

*+9.4

7

Table 1

. Population trends of wetland-breeding anuran species used to assess the health of wetlands and their surrounding landscapes in the Lake Michigan, Huron, Erie, and Ontario basin, based on occurrence indices derived from Marsh Monitoring Program point count surveys between 1995 and 2010. Statistically significant trends are indicated by * (i.e., Bayesian credible intervals do not overlap zero). Note that sample sizes were insufficient to analyze Wood Frog within individual lake basins.

Source: Great Lakes Marsh Monitoring Program

Figure 1

. Mean (±SD) number of Marsh Monitoring Program routes surveyed for amphibians per year in the Great

Lakes basin (All) and in each individual Great Lakes basin (e.g., Superior) between 1995 and 2010. A route consists of multiple, spatially-clustered point count survey locations, typically located in the same wetland, all of which can be surveyed by the same person in a single visit.

Source: Great Lakes Marsh Monitoring Program

129

Figure 2

. Percent annual change of occurrence indices for some wetland-breeding anuran species from 1995 to 2010 in the Great Lakes basin. Indices estimated with repeated-measures logistic regression. Statistically significant positive trends are green, significant negative trends are red, and stable (non-significant) trends are white. Bayesian credible intervals did not overlap zero for significant trends.

Source: Great Lakes Marsh Monitoring Program

4%

3%

2%

1%

0%

Figure 3

. Box-and-whisker plots showing minimum detectable annual change (%) of occurrence indices of some wetland-breeding anuran species in the Great Lakes basin (All) and in individual Great Lakes basins (e.g.,

Michigan), derived from Great Lakes Marsh Monitoring Program data. The figure summarizes the 7 (Michigan,

Huron, Erie, Ontario) or 8 (All) species used to assess wetland health in this report.

Source: Great Lakes Marsh Monitoring Program

130

Coastal Wetland Birds

Overall Assessment

Status: Poor

Trend: Deteriorating

Rationale: The abundance of half of the species that regularly or always nest in wetlands declined significantly between 1995 and 2010 (10 of 19 [52%]). By contrast, the abundance of only three such species significantly increased (16%]). Similar patterns occur in previous reports.

Lake-by-Lake Assessment

Lake Superior

Status: Undetermined

Trend: Undetermined

Lake Michigan

Status: Poor

Trend: Deteriorating

Rationale: The abundance of nearly half of the species that regularly or always nest in wetlands declined significantly between 1995 and 2010 (7 of 15 [47%]). By contrast, the abundance of no such species significantly increased. Similar patterns occur in previous reports.

Lake Huron

Status: Poor

Trend: Deteriorating

Rationale: The abundance of nearly half of the species that regularly or always nest in wetlands declined significantly between 1995 and 2010 (7 of 16 [44%]). By contrast, the abundance of only two such species significantly increased (12%). Similar patterns occur in previous reports.

Lake Erie

Status: Poor

Trend: Deteriorating

Rationale: The abundance of over half of the species that regularly or always nest in wetlands declined significantly between 1995 and 2010 (12 of 18 [67%]). By contrast, the abundance of only three such species significantly increased (17%). Similar patterns occur in previous reports.

Lake Ontario

Status: Poor

Trend: Deteriorating

Rationale: The abundance of almost half of the species that regularly or always nest in wetlands declined significantly between 1995 and 2010 (7 of 17 [41%]). By contrast, the abundance of only three such species significantly increased (18%). Similar patterns occur in previous reports.

Purpose

To assess changes in the relative abundance of wetland-dependent breeding bird species

To infer condition of wetland habitat as it relates to factors that influence this ecologically and culturally important resource

The Coastal Wetland Birds indicator is used in the Great Lakes indicators suite as a State indicator in the

Aquatic Dependent Life top level reporting category.

131

Ecosystem Objective

To restore and maintain self-sustaining populations of Great Lakes wetland-dependent breeding bird species across their historic ranges. Numerous wetlands in the Great Lakes basin are threatened by urban and agricultural development and other incompatible land uses and these wetlands should be identified, preserved, and where necessary rehabilitated (GLWQA Annex 13). Monitoring and assessment activities provide information on the location, severity, aerial or volume extent, and frequency of Great Lakes wetlands (Annex 11 GLWQA). This indicator supports the restoration and maintenance of the chemical, physical and biological integrity of the Great

Lakes basin and beneficial uses dependent on healthy wetlands (Annex 2 GLWQA).

Ecological Condition

Measure

Changes in relative abundance of wetland-dependent breeding birds are based on data from morning or evening surveys using Bird Studies Canada’s Great Lakes Marsh Monitoring Program (MMP) bird point count protocol or a modification of it (Marsh Monitoring Program 2009). MMP data from coastal and inland wetlands throughout the

Great Lakes basin or throughout each individual lake basin (e.g., Lake Erie; Fig. 1) are used to calculate annual indices of relative abundance for a suite of wetland bird species. Wetlands dominated by non-woody emergent plants such as cattails (

Typha

spp.) and sedges (e.g.,

Carex

spp.) are targeted by the program. Species-specific population trends over time are calculated using repeated measures Poisson regression in a Bayesian mode of inference with uninformative priors (Kéry 2010).

Endpoint

Populations of most wetland-dependent breeding bird species have declined since data collection began for this indicator in 1995. Therefore, one endpoint is population indices for nearly all wetland-dependent breeding bird species that are as high as or higher than population indices reported by the MMP in the late 1990s, when the program began. A potentially better endpoint, however, might be based on MMP abundance indices from pristine or near-pristine wetlands throughout the Great Lakes basin (i.e., least disturbed based on indices of anthropogenic disturbance within and surrounding the wetland) —guided by a literature search of other current and historical data and expert opinion. Population indices from this approach are likely to be higher than those reported by the MMP in the late 1990s, given that many wetlands throughout the Great Lakes basin were degraded by that time. Presumably the two approaches estimate the extremes of a range of abundance that is likely to contain the carrying capacity that the landscape is currently capable of supporting and, therefore, somewhere near the middle of the range is the most suitable endpoint. This is the endpoint used in this report.

Background

Wetland-dependent breeding birds are influenced by the physical, chemical, and biological components of the wetlands and surrounding landscapes in which they breed. The abundance and/or reproductive success of multiple species in the Great Lakes basin, for example, declines as (1) wetland size decreases; (2) wetland habitat and natural cover in the surrounding landscape decreases; (3) pesticide, herbicide, and runoff from other sources of pollution into wetlands from the surrounding landscape increases; and (4) generalist predators (e.g., raccoons [

Procyon lotor

]) associated with anthropogenic habitats in the surrounding landscape increase (Brazner et al. 2007a,b; Crosbie and

Chow-Fraser 1999; Howe et al. 2007; Grandmaison and Niemi 2007; Naugle et al. 2000; Smith and Chow-Fraser

2010 a,b; Tozer et al. 2010). Thus, the abundance of wetland-dependent breeding birds is a valuable indicator of the health of wetlands and the surrounding landscape.

Status of Coastal Wetland BirdsA grand total of 56 bird species that use marshes (e.g., for feeding, loafing, nesting) were recorded across all surveys and years throughout the Great Lakes basin between 1995 and 2010. Of these, 19 species regularly or always nest in emergent wetlands. Members of this latter group of species were used to assess the health of wetlands and their surrounding landscapes in this report because they rely completely or nearly

132

completely on resources within or relatively close to their nesting wetlands (i.e., within a few kilometres). Only a subset of these 19 species, however, was observed in each individual Great Lakes basin (Table 1).

Great Lakes Basin

The abundance of half of the species that regularly or always nest in wetlands declined significantly between 1995 and 2010 (10 of 19 [52%]; Fig. 2). By contrast, the abundance of only three species that regularly or always nest in wetlands significantly increased between 1995 and 2010 (16%; Fig. 2). The Trumpeter Swan (

Cygnus buccinator

; see Table 1 for a list of scientific names for all subsequent common names) increased primarily due to relatively recent reintroductions after the species was nearly extirpated about a century ago (Mitchell and Eichholz 2010) and the Sandhill Crane continues to increase following continental population lows in the early 1900s (Tacha et al.

1992), both of which may have little to do with the health of wetlands in the Great Lakes basin between 1995 and

2010; these two species are also responsible for most of the significant population increases identified within individual Great Lakes basins in the following sections. The abundance of the remaining six species that regularly or always nest in wetlands was stable between 1995 and 2010 (32%). Similar patterns occur across the Great Lakes basin for this indicator in previous reports. Given that populations of half the species that regularly or always nest in wetlands continue to decline below each of the suggested endpoints, the overall status is poor and the trend is deteriorating.

Lake Michigan

The abundance of nearly half of the species that regularly or always nest in wetlands declined significantly between

1995 and 2010 (7 of 15 [47%]). By contrast, the abundance of no such species significantly increased. The abundance of the remaining eight species that regularly or always nest in wetlands was stable between 1995 and

2010 (53%). Similar patterns occur in the Lake Michigan basin for this indicator in previous reports. Given that populations of nearly half of the species that regularly or always nest in wetlands continue to decline below each of the suggested endpoints, the overall status is poor and the trend is deteriorating (Table 1).

Lake Huron

The abundance of nearly half of the species that regularly or always nest in wetlands declined significantly between

1995 and 2010 (7 of 16 [44%]). By contrast, the abundance of only two such species significantly increased (12%).

The abundance of the remaining seven species that regularly or always nest in wetlands was stable between 1995 and 2010 (44%). Similar patterns occur in the Lake Huron basin for this indicator in previous reports. Given that populations of nearly half the species that regularly or always nest in wetlands continue to decline below each of the suggested endpoints, the overall status is poor and the trend is deteriorating (Table 1).

Lake Erie

The abundance of over half of the species that regularly or always nest in wetlands declined significantly between

1995 and 2010 (12 of 18 [67%]). By contrast, the abundance of only three such species significantly increased

(17%). The abundance of the remaining three species that regularly or always nest in wetlands was stable between

1995 and 2010 (17%). Similar patterns occur in the Lake Erie basin for this indicator in previous reports. Given that populations of over half the species that regularly or always nest in wetlands continue to decline below each of the suggested endpoints, the overall status is poor and the trend is deteriorating (Table 1).

Lake Ontario

The abundance of almost half of the species that regularly or always nest in wetlands declined significantly between

1995 and 2010 (7 of 17 [41%]). By contrast, the abundance of only three such species significantly increased (18%).

The abundance of the remaining seven species that regularly or always nest in wetlands was stable between 1995 and 2010 (17%). Similar patterns occur in the Lake Ontario basin for this indicator in previous reports. Given that populations of almost half of the species that regularly or always nest in wetlands continue to decline below each of the suggested endpoints, the overall status is poor and the trend is deteriorating (Table 1).

133

Linkages

Wetland-dependent breeding birds are influenced by numerous characteristics of the wetlands and surrounding landscapes in which they breed, many of which are monitored as Great Lakes (SOLEC) indicators. For instance, populations of some of the 19 wetland-dependent breeding bird species used to assess Great Lakes wetland health in this report are known to co-vary with changing water levels at local and individual Great Lakes basin scales

(Timmermans et al. 2008, Jobin et al. 2009). Thus, the Coastal Wetland Bird indicator will co-vary with the Water

Levels indicator report. The Coast al Wetland Bird indicator can also be expected to co-vary with indicators that track wetland breeding bird habitat (e.g., Coastal Wetland Plant Community Health; Coastal Wetland Landscape

Extent and Composition) and prey (Coastal Wetland Invertebrate Community Health; Coastal Wetland Fish

Community Health) and factors that indirectly influence them, such as invasive plant species that encroach upon preferred native vegetation and pollution runoff from surrounding uplands that reduce prey abundance and/or availability.

Management Challenges/Opportunities

Maintain or improve the quality of wetlands and adjacent uplands for breeding coastal wetland birds by mitigating or eliminating influences that are detrimental to wetland health such as water level fluctuations, invasive species, and inputs of toxic chemicals, nutrients and sediments. Restoration programs are underway for many degraded wetland areas through the work of local citizens, organizations and governments. Although significant progress has been made, considerably more conservation and restoration work is needed to ensure maintenance of healthy and functional wetlands throughout the Great Lakes basin.

Comments from the author(s)

The utility of the Coastal Wetland Birds indicator is dependent on the continuation of the MMP across the Great

Lakes basin. Therefore, recruitment and retention of volunteer surveyors has been, and will continue to be, high priority. Despite this, there are areas where coverage is too sparse for analysis and could be improved (e.g., Lake

Superior). As a result, a power analysis was conducted to quantify the MMP’s ability to detect changes in population sizes of wetland-dependent breeding bird species at the scales explored in this report. The analysis suggests that the

MMP has 80% power to detect percent annual changes in occurrence indices as small as 1.5% in the Great Lakes basin; 3% in the Lake Huron, Erie, and Ontario basins; and 4% in the Lake Michigan basin for most species (Fig. 3).

These numbers should be considered preliminary and exploratory, however, until the effects of spatial and temporal dependence amongst surveys and detection probability can be fully assessed, which is an ongoing and evolving area of study (Seavy and Reynolds 2007, Patuxent Wildlife Research Center 2003).

Assessing Data Quality

Data Characteristics

1. Data are documented, validated, or qualityassured by a recognized agency or organization

2. Data are traceable to original sources

3. The source of the data is a known, reliable and respected generator of data

4. Geographic coverage and scale of data are appropriate to the Great Lakes basin

5. Data obtained from sources within the U.S. are comparable to those from Canada

6. Uncertainty and variability in the data are documented and within acceptable limits for this indicator report

Strongly

Agree

X

X

X

X

X

X

Agree

Neutral or

Unknown

Disagree

Strongly

Disagree

Not

Applicable

134

Acknowledgments

Author:

Douglas C. Tozer, Aquatic Surveys Biologist, Bird Studies Canada, P.O. Box 160, 115 Front Street, Port Rowan,

ON N0E 1M0, [email protected]

; www.bsc-eoc.org/volunteer/glmmp

Contributors:

Hundreds of volunteers who generously donate their time, equipment, and skills to ensure long-term, broad-scale monitoring of the health of Great Lakes wetlands.

Robert W. Rankin, Data Analyst, Bird Studies Canada, P.O. Box 160, 115 Front Street, Port Rowan, ON N0E 1M0.

Rob provided statistical assistance.

Information Sources

Brazner, J.C., Danz, D.P., Niemi, G.J., Regal, Trebitz, A.S., Howe, R.W., Hanowski, J.M., R.R., Johnson, L.B.,

Ciborowski, J.J.H., Johnston, C.A., Reavie, E.D., Brady, V.J., and Sgro, G.V. 2007a. Evaluation of geographic and human influences on Great Lakes wetland indicators: a multi-assemblage approach. Ecological Indicators

7:610-635.

Brazner, J.C., Danz, D.P., Trebitz, A.S., Niemi, G.J., Regal, R.R., Hollenhorst, T., Host, G.E., Reavie, E.D., Brown,

T.N., Hanowski, J.M., Johnston, C.A., Johnson, L.B., Howe, R.W., and Ciborowski, J.J.H. 2007b.

Responsiveness of Great Lakes wetland indicators to human disturbances at multiple spatial scales: a multiassemblage assessment. Journal of Great Lakes Research 33(Special Issue 3):42-66.

Crosbie, B. and Chow Fraser, P. 1999. Percentage land use in the watershed determines the water and sediment quality of 22 marshes in the Great Lakes basin. Canadian Journal of Fisheries and Aquatic Sciences 56:1781-

1791.

Grandmaison, D.D. and Niemi, G. 2007. Local and landscape influence on Red-winged Blackbird (

Agelaius phoenicius

) nest success in Great Lakes coastal wetlands. Journal of Great Lakes Research 33(Special Issue

3):292-304.

Howe, R.W., Regal, R.R., Hanowski, J., Niemi, G.J., Danz, D.P., and Smith C.R. 2007. An index of ecological condition based on bird assemblages in Great Lakes coastal wetlands. Journal of Great Lakes Research

33(Special Issue 3):93-105.

Jobin, B., Robillard, L., Latendresse, C. 2009. Response of a Least Bittern (

Ixobrychus exilis

) population to interannual water level fluctuations. Waterbirds 32:73-80.

Kéry, M. 2010. Introduction to WinBUGS for ecologists: a Bayesian approach to regression, ANOVA, mixed models and related analyses. Academic Press, Amsterdam.

Marsh Monitoring Program. 2009. Marsh Monitoring Program participant’s handbook for surveying marsh birds, revised 2008. Published by Bird Studies Canada in cooperation with Environment Canada and the U.S.

Environmental Protection Agency.

Mitchell, C.D. and Eichholz, M.W. 2010. Trumpeter Swan (

Cygnus buccinator

), The Birds of North America

Online (A. Poole, Ed.). Ithaca: Cornell Lab of Ornithology; Retrieved from the Birds of North America Online: http://bna.birds.cornell.edu.cat1.lib.trentu.ca:8080/bna/species/105doi:10.2173/bna.105

Naugle, D.E., Higgins, K.F., Estey, M.E., Johnson, R.R., Nusser, S.M. 2000. Local and landscape-level factors influencing Black Tern habitat suitability. Journal of Wildlife Management 64:253-260.

Patuxent Wildlife Research Center. 2003. Status of the “Monitor” web site [online]. Available from http://www.pwrc.usgs.gov/resshow/droege3rs/salpower.htm

[accessed 28 June 2011].

Seavy, N.E. and M.H. Reynolds. 2007. Is statistical power to detect trends a good assessment of population monitoring? Biological Conservation 140:187-191.

Smith, L.A. and P. Chow-Fraser. 2010a. Impacts of adjacent land use and isolation on marsh bird communities.

Environmental Management 45:1040-1051.

Smith, L.A. and P. Chow-Fraser. 2010b. Implications of the species-area relationship on sampling effort for marsh birds in southern Ontario. Wetlands 30:553-563.

135

Tacha, T.C., Nesbitt, S.A., and Vohs, P.A. 1992. Sandhill Crane (

Grus canadensis

), The Birds of North America

Online (A. Poole, Ed.). Ithaca: Cornell Lab of Ornithology; Retrieved from the Birds of North America Online: http://bna.birds.cornell.edu.cat1.lib.trentu.ca:8080/bna/species/031doi:10.2173/bna.31

Timmermans, S.T.A., Badzinski, S.S., and Ingram, J.W. 2008. Associations between breeding marsh bird abundances and Great Lakes hydrology. Journal of Great Lakes Research 34:351.

Tozer, D.C., Nol, E., and Abraham, K.F. 2010. Effects of local and landscape-scale habitat variables on abundance and reproductive success of wetland birds. Wetlands Ecology and Management 18:679-693.

List of Tables

Table 1.

Population trends of wetland-nesting bird species used to assess the health of wetlands and their surrounding landscapes in the Lake Michigan, Huron, Erie, and Ontario basin, based on abundance indices derived from Marsh Monitoring Program point count surveys between 1995 and 2010. Statistically significant trends are indicated by * (i.e., Bayesian credible intervals do not overlap zero).

Source: Great Lakes Marsh Monitoring Program.

List of Figures

Figure 1.

Mean (±SD) number of Marsh Monitoring Program routes surveyed for birds per year in the Great Lakes basin (All) and in each individual Great Lakes basin (e.g., Superior) between 1995 and 2010. A route consists of multiple, spatially-clustered point count survey locations, typically located in the same wetland, all of which can be surveyed by the same person in a single morning or evening.

Source: Great Lakes Marsh Monitoring Program.

Figure 2.

Percent annual change of population indices for some wetland-nesting bird species from 1995 to 2010 in the Great Lakes basin. Indices estimated with a Bayesian mixed-model framework, assuming a Poisson distribution.

Statistically significant positive trends are green, significant negative trends are red, and stable (non-significant) trends are white.

Source: Great Lakes Marsh Monitoring Program.

Figure 3.

Box-and-whisker plots showing minimum detectable annual change (%) of population indices of some wetland-nesting bird species in the Great Lakes basin (All) and in individual Great Lakes basins (e.g., Superior), derived from Great Lakes Marsh Monitoring Program data. The figure summarizes the 19 species used to assess wetland health in this report, with the exception of Trumpeter Swan, which was considered an outlier and removed for ease of interpretation; for this species, minimum detectable annual change was 7% in the Great Lakes basin and

10 and 25% in the Lake Ontario and Erie basins, respectively.

Source: Great Lakes Marsh Monitoring Program.

Last Updated

State of the Great Lakes 2011

report

136

Population trends of wetland-nesting bird species

Common Name Scientific Name Michigan

American Bittern

American Coot

Botaurus lentiginosus

Fulica americana

*-14.1

Black Tern

Canada Goose

Common Grackle

Chlidonias niger

Branta canadensis

Quiscalus quiscula

*-18.3

-2.0

+0.07

Common Moorhen

Common Yellowthroat

Forster’s Tern

Least Bittern

Marsh Wren

Mute Swan

Pied-billed Grebe

Gallinula chloropus

Geothlypis trichas

Sterna forsteri

Cygnus olor

Ixobrychus exilis

Cistothorus palustris

Podilymbus podiceps

*-16.9

+0.63

*-6.1

-1.5

-5.2

*-7.7

Huron

*-0.5

*-11.2

*-12.2

+1.94

*-3.4

*-11.8

*+2.21

*-4.2

+1.43

*-5.6

Erie

*-2.8

*-15.5

*-4.6

*-5.7

*-2.7

*-13.7

*+1.66

*-13.7

*-7.0

*-2.5

-3.3

-2.7

Ontario

-1.1

*-5.4

*-13.3

+0.61

-0.3

*-6.8

*+1.34

*-2.9

-0.9

+2.74

*-8.1

Red-winged Blackbird

Sandhill Crane

Sora

Swamp Sparrow

Trumpeter Swan

Agelaius phoeniceus

Grus canadensis

Porzana carolina

Melospiza georgiana

Cygnus buccinator

+0.04

+6.16

*-4.0

-0.6

-0.7

*+14.51

+0.04

-1.2

*-1.1

*+13.89

*-4.1

*-0.9

*+77.68

*-0.7

-2.1

*+1.2

*+32.38

Virginia Rail

Wilson’s Snipe

Rallus limicola

Gallinago delicata

*-8.6

*-2.5

-1.3

*-4.9

*-3.4

+9.85

TOTAL 19 15 16 18 17

Table 1

. Population trends of wetland-nesting bird species used to assess the health of wetlands and their surrounding landscapes in the Lake Michigan, Huron, Erie, and Ontario basin, based on abundance indices derived from Marsh Monitoring Program point count surveys between 1995 and 2010. Statistically significant trends are indicated by * (i.e., Bayesian credible intervals do not overlap zero).

Source: Great Lakes Marsh Monitoring Program.

240

200

160

120

80

40

0

Figure 1

. Mean (±SD) number of Marsh Monitoring Program routes surveyed for birds per year in the Great Lakes basin (All) and in each individual Great Lakes basin (e.g., Superior) between 1995 and 2010. A route consists of multiple, spatially-clustered point count survey locations, typically located in the same wetland, all of which can be surveyed by the same person in a single morning or evening.

Source: Great Lakes Marsh Monitoring Program.

137

Figure 2

. Percent annual change of population indices for some wetland-nesting bird species from 1995 to 2010 in the Great Lakes basin. Indices estimated with a Bayesian mixed-model framework, assuming a Poisson distribution.

Statistically significant positive trends are green, significant negative trends are red, and stable (non-significant) trends are white.

Source: Great Lakes Marsh Monitoring Program.

7%

6%

5%

4%

3%

2%

1%

0%

Figure 3

. Box-and-whisker plots showing minimum detectable annual change (%) of population indices of some wetland-nesting bird species in the Great Lakes basin (All) and in individual Great Lakes basins (e.g., Superior), derived from Great Lakes Marsh Monitoring Program data. The figure summarizes the 19 species used to assess wetland health in this report, with the exception of Trumpeter Swan, which was considered an outlier and removed for ease of interpretation; for this species, minimum detectable annual change was 7% in the Great Lakes basin and

10 and 25% in the Lake Ontario and Erie basins, respectively.

Source: Great Lakes Marsh Monitoring Program.

138

Coastal Wetland Fish Community Health

Overall Assessment

Status: Not Assessed

Trend: Not Assessed

Rationale: This indicator will be evaluated as part of an overall analysis of biological communities of Great

Lakes coastal wetlands and nearshore aquatic systems.

Note: This is a progress report towards implementation of this indicator. The indicator is currently being used throughout the entire Great Lakes basin, but data will not be available until 2012. The following evaluation was constructed using input from investigators collecting fish community composition data from Great Lakes coastal wetlands over the last several years.

Regarding the following, neither experimental design nor statistical rigor has been used to specifically address the status and trends of fish communities of coastal wetlands of the five Great Lakes. However, in the spring of 2011, an effort was put forth by a consortium of universities that established a statistically sound basin-wide coastal wetland monitoring program. This indicator will be used, along with others, at the majority of coastal wetlands with a surface water connection to the Great Lakes that are greater than 4 hectares in size. The effort is bi-national and basin wide and will produce scientifically-defensible information on the status and trends of Great Lakes coastal wetlands.

Lake-by-Lake Assessment

Each lake was categorized with a not assessed status and an undetermined trend, indicating that data were not available yet.

Purpose

To assess the fish community composition, and to infer suitability of habitat and water quality for Great

Lakes coastal wetland fish communities.

Ecosystem Objective

Restore and maintain the diversity of the fish community of Great Lakes coastal wetlands, while indicating overall ecosystem health. Significant wetland areas in the Great Lakes System that are threatened by urban and agricultural development and waste disposal activities should be identified, preserved and, where necessary, rehabilitated

(Annex 13 GLWQA). This indicator supports the restoration and maintenance of the chemical, physical and biological integrity of the Great Lakes basin and beneficial uses dependent on healthy wetlands (Annex 2 GLWQA).

Ecological Condition

Development of this indicator is complete and the indicator is currently be implemented. However, data are not available at this time. Several different fish metrics developed by the Great Lakes Coastal Wetlands Consortium are being utilized.

Mean abundance and richness per (fyke) net-night of resident fish species within dominant inundated vegetation zones; primarily bulrush (

Schoenoplectus

) and cattail (

Typha

); across survey stations specific to a vegetation zone; percent non-native richness; mean Shannon Diversity index; mean evenness; and, mean abundance and richness of

Omnivores, insectivores, piscivores, and carnivores (insectivores+ piscivore+zooplanktivore).

In order to properly manage the Great Lakes coastal wetland fish community health there must be consistent sampling methods. Sampling is being conducted no earlier than mid June and no later than August due to migration patterns of the fish communities. Dominant vegetation zones are being identified because different zones support different types of fish. Two main vegetation zones are

Schoenoplectus

-Bulrush and

Typha

-cattail, but all are being included. When sampling fish using fyke netting it is recommended to use a minimum of three replicate fyke nets with 4.8mm mesh for each dominate vegetation zone. There are two sizes of fyke nets that can be used 0.5-m x 1-m opening and 1-m x 1-m opening. The smaller nets are placed in water that is 0.25-0.5 m deep and the larger fyke nets are placed in water that is greater than 0.50 m deep. The leads are 7.3 m long with 1.8 m long wings . Nets are

139

randomly placed a minimum of 20 m apart in each vegetation zone. The fyke nets are placed perpendicular to the vegetation zone, therefore, fish swimming along the edge of the vegetation zone are captured.

Any fish collected that is greater than 25mm should be identified down to species. The number of the fish caught per fyke net should be recorded. Also 10 to 20 specimens of each species, life stage and size at age should be chosen randomly to record.

Using the methods stated above, scientists have determined the composition of fish communities is related to plant community type within wetlands (Uzarski

et al

. 2005, Wei

et al

. 2004). Uzarski

et al

. (2005) found no relationship between wetland fish composition and a specific Great Lake, suggesting that fish communities of any single Great

Lake were no more impacted than those from any other Great Lake. However, of the 61 wetlands sampled in 2002 from all five lakes, Lake Erie and Lake Ontario tended to have more wetlands containing cattail communities (a plant community type that correlates with nutrient enrichment), and the fish communities found in cattails tended to have lower richness and diversity than fish communities found in other vegetation types. Wetlands found in northern

Lake Michigan and Lake Huron tended to have relatively high quality coastal wetland fish communities. The seven wetlands sampled in Lake Superior contained relatively unique vegetation types, so fish communities of these wetlands were not directly compared with those of wetlands of other lakes.

When the fish communities of reference wetlands are compared across the entire Great Lakes, the most similar sites come from the same ecological province rather than from any single Great Lake or specific wetland types. Data from several GLEI project studies indicate that the characteristic groups of fish species in reference wetlands from each ecological province tend to have similar water temperature and aquatic productivity preferences.

John Brazner and co-workers from the U.S. EPA Laboratory in Duluth, MN, sampled fishes of Green Bay (Lake

Michigan) wetlands in 1990, 1991, 1995, 2002, and 2003. They sampled three lower bay and one middle bay wetland in 2002 and 2003. Their data suggested that these sites were improving in water clarity and plant cover, and that they supported a greater diversity of both macrophyte and fish species, especially more centrarchid species, than they had in previous years. They also noted that the 2002, and especially 2003, year classes of yellow perch were very large. Brazner’s observations suggest that the lower Green Bay wetlands are improving slowly and the middle bay site seems to be remaining relatively stable in moderately good condition (J. Brazner, personal observation). The most turbid wetlands in the lower bay were characterized by mostly warm-water, turbidity-tolerant species such as gizzard shad (

Dorosoma cepedianum)

, white bass (

Morone chrysops

), freshwater drum (

Aplodinotus grunniens),

common shiners (

Luxilus cornutus),

and common carp (

Cyprinus carpio).

Meanwhile the least turbid wetlands in the upper bay were characterized by several centrarchid species, golden shiner (

Notemigonus chrysoleucas

), logperch (

Percina caprodes),

smallmouth bass (

Micropterus dolomieu)

and northern pike (

Esox lucius)

. Green sunfish (

Lepomis cyanellus)

was the only important centrarchid in the lower bay in 1991, while in 1995, bluegill and pumpkinseed sunfishes (

L. macrochirus

and

L. gibbosus)

had become much more prevalent, and a few largemouth bass (

M. salmoides)

were also present. There were more banded killifish (

Fundulus diaphanous)

in 1995 and 2003 compared with 1991, and white perch (

Morone americana)

were very abundant in 1995 as this non-native species became dominant in the bay. The upper bay wetlands were in relatively good condition based on the fish and macrophyte communities that were observed. Although mean fish species richness was significantly lower in developed wetlands across the whole bay, differences between less developed and more developed wetlands were most pronounced in the upper bay where the highest quality wetlands in Green Bay are found (Brazner 1997).

Round gobies (

Neogobius melanostomus)

were introduced to the St. Clair River in 1990 (Jude and Pappas 1992), and they have since spread to all of the Great Lakes. Jude studied them in many tributaries of the Lake Huron-St.

Clair River-Lake Erie corridor and found that both round and tubenose gobies (

Proterorhinus marmoratus

) were very abundant at river mouths and had colonized far upstream. They were also found at the mouth of Old Woman

Creek in Lake Erie, but not within the wetland proper. Jude and Janssen’s work in Green Bay wetlands showed that

140

round gobies had not invaded three of the five sites sampled, but a few were found in lower Green Bay along the sandy and rocky shoreline west of Little Tail Point.

Uzarski and Burton (unpublished) consistently collected a few round gobies from a fringing wetland near Escanaba,

MI, where cobbles were present. In the Muskegon River-Muskegon Lake wetland complex on the eastern shoreline, round gobies are abundant in the heavily rip-rapped harbor entrance to Lake Michigan, and they have just begun to enter the river/wetland complex on the east side of Muskegon Lake (Cooper

et

al. 2007; D. Jude, personal observations). Based on intensive fish sampling prior to 2003 at more than 60 sites spanning all of the Great Lakes, round gobies have not been sampled in large numbers at any wetland or been a dominant member of any wetland fish community (Jude

et al

. 2005). Round gobies were collected at 11 of 80 wetlands sampled by the GLEI project

(Johnson

et al

. unpublished data). Lapointe (2005) assessed fish-habitat associations in the shallow (less than 3 m)

Canadian waters of the Detroit River in 2004 and 2005 using boat-mounted electrofishing and boat seining techniques. The round goby avoided complex macrophytes in all seasons at upper, mid-, and downstream segments of the Detroit River. However, in 2006, beach seining surveys at shoreline sites in Canadian waters of Lake St.

Clair, the Detroit River, and western Lake Erie, both tubenose and round gobies were collected in areas with aquatic vegetation (Corkum, Univ. of Windsor, unpublished data). It seems likely that wetlands may be a refuge for native fishes, at least with respect to the influence of round gobies (Jude

et al

. 2005), however, small gobies seem to be increasing in abundance in many Great Lakes coastal wetlands.

There is little information on the habitat preferences of the tubenose goby within the Great Lakes with the exception of studies on the Detroit River (Lapointe 2005), Lake St. Clair and the St. Clair River (Jude and DeBoe 1996, Pronin

et al

. 1997, Leslie

et al

. 2002). Within the Great Lakes, tubenose goby that were studied at a limited number of sites along the St. Clair River and on the south shore of Lake St. Clair occurred in turbid water associated with rooted submersed vegetation (

Vallisneria americana, Myriophyllum spicatum, Potamogeton richardsonii

and

Chara

sp.;Leslie

et al

. 2002). Few specimens were found on sandy substrates devoid of vegetation, supporting similar findings by Jude and DeBoe (1996). Leslie

et al

. (2002) collected tubenose goby in water with no or slow flow on clay or alluvium substrates, where turbidity varies and where rooted vegetation was sparse, patchy or abundant.

Lapointe (2005) found that the association between tubenose goby and aquatic macrophytes differed seasonally in the Detroit River. For example, tubenose goby was strongly negatively associated with complex macrophytes in the spring and summer, but positively associated with complex macrophytes in the fall (Lapointe 2005). Because tubenose goby shared habitats with fishes representing most ecoethological guilds, Leslie

et al

. (2002) suggested that the tubenose goby would expand its geographic range within the Great Lakes.

Ruffe (

Gymnocephalus cernuus

) have never been found in high densities in coastal wetlands anywhere in the Great

Lakes. In their investigation of the distribution and potential impact of ruffe on the fish community of a Lake

Superior coastal wetland, Brazner

et al

. (1998) concluded that coastal wetlands in western Lake Superior provide a refuge for native fishes from competition with ruffe. The mudflat-preferring ruffe actually avoids wetland habitats due to foraging inefficiency in dense vegetation that characterizes healthy coastal wetland habitats. This suggests that further degradation of coastal wetlands or heavily vegetated littoral habitats could lead to increased dominance of ruffe in shallow water habitats elsewhere in the Great Lakes.

There are a number of carp introductions that have the potential for substantial impact on Great Lakes fish communities, including coastal wetlands. Goldfish (

Carassius auratus

) are common in some shallow habitats, and they occurred along with common carp young-of-the-year in many of the wetlands sampled along Green Bay. In addition, there are several other carp species, e.g., grass carp (

Ctenopharyngodon idella),

bighead carp

(

Hypophthalmichthys nobilis)

and silver carp (

Hypophthalmichthys molitrix)

that escaped aquaculture operations and are now in the Illinois River and migrating toward the Great Lakes through the Chicago Sanitary and Ship

Canal. Most of these species attain large sizes. Some are planktivorous, but also eat phytoplankton, snails, and mussels, while the grass carp eats vegetation. These species represent yet another substantial threat to food webs in

141

wetlands and nearshore habitats with macrophytes (U.S. Fish and Wildlife Service (USFWS) 2002).

In 2003, Jude and Janssen (unpublished data) determined that bluntnose minnows (

Pimephales notatus)

and johnny darters (

Etheostoma nigrum)

were almost absent from lower Green Bay wetland sites, but they comprised 22% and

6%, respectively, of upper bay catches. In addition, other species, usually associated with plants and/or clearer water, such as rock bass, sand shiners (

Notropis stramineus

) and golden shiners (

Notemigonus crysoleucus),

were also present in upper bay samples, but not in lower bay samples. In 2003, Jude and Janssen found that there were no alewife (

Alosa pseudoharengus)

or gizzard shad in upper Green Bay site catches, but in lower bay wetland sites, they composed 2.7% and 34%, respectively, of the catches by number.

Jude and Pappas (1992) found that fish assemblage structure in Cootes Paradise, a highly degraded wetland area in

Lake Ontario, was very different from other less degraded wetlands analyzed. They used ordination analyses to detect fish-community changes associated with degradation.

According to a study completed by Seilheimer and Chow-Fraser northern coastal wetlands had higher water quality indices than southern lakes coastal wetlands. Lake Superior had a good status while Lake Huron and Georgian Bay were classified with a very good status. Southern coastal wetlands in Lake Ontario, Erie and Michigan were classified as moderately degraded (Seilheimer and Chow-Fraser, 2007).

During this study pumpkinseed (

Lepomis gibbosus

) occurred in 94 out of 100 wetlands studied, and over 6,000 pumpkinseed individuals were captured. Brown bullhead (

Ameiurus nebulosus

) was the second most abundant fish captured and it was found in 80 wetlands. Another abundant species was the Spottail shiner (

Notropis hudsonius

) which was found in 39 coastal wetlands with a little less than 3,800 individual captured. Other abundant species found in the Great Lakes coastal wetlands are the Largemouth bass (

Micropterus salmoides

), Bluntnose minnow

(

Pimephales notatus

), and the Bluegill (

Lepomis macrochirus

).

Pressures

Agriculture

Agriculture degrades wetlands in several ways, including nutrient enrichment from fertilizers, increased sediments from erosion, increased rapid runoff from drainage ditches, introduction of agricultural non-native species (reed canary grass), destruction of inland wet meadow zone by plowing and diking, and addition of herbicides. In the southern lakes, Saginaw Bay, and Green Bay, agricultural sediments have resulted in highly turbid waters which support few or no submergent plants.

Urban development

Urban development degrades wetlands by hardening shoreline, filling wetland, adding a broad diversity of chemical pollutants, increasing stream runoff, adding sediments, and increased nutrient loading from sewage treatment plants.

In most urban settings, almost complete wetland loss has occurred along the shoreline. Thoma (1999) and Johnson

et al

. (2006) were unable to find coastal wetlands on the U.S. side of Lake Erie that experienced minimal anthropogenic disturbances. According to Seilheimer and Chow-Fraser there has been accelerated loss of wetland fish habitat in Lake Ontario, Lake Erie and Lake Michigan near urban areas and agriculture.

Residential shoreline development

Along many coastal wetlands, residential development has altered wetlands by nutrient enrichment from fertilizers and septic systems, shoreline alterations for docks and boat slips, filling, and shoreline hardening. Agriculture and urban development are usually less intense than local physical alteration which often results in the introduction of non-native species. Shoreline hardening can completely eliminate wetland vegetation, which results in degradation of fish habitat. It appears that when a wetland becomes affected by human development, the fish community changes to that typical of a warmer, richer, more southerly wetland. This finding may help researchers anticipate the likely effects of regional climate change on the fish communities of Great Lakes coastal wetlands.

142

Mechanical alteration of shoreline

Mechanical alteration takes a diversity of forms, including diking, ditching, dredging, filling, and shoreline hardening. With all of these alterations, non-native species are introduced by construction equipment or in introduced sediments. Changes in shoreline gradients and sediment conditions are often adequate to allow nonnative species to become established.

Introduction of non-native species

Non-native species are introduced in many ways. Some were purposefully introduced as agricultural crops or ornamentals, later colonizing in native landscapes. Others came in as weeds in agricultural seed. Increased sediment and nutrient enrichment allow many of the worst aquatic weeds to out-compete native species. Most of the worst non-native species are either prolific seed producers or reproduce from fragments of root or rhizome. Non-native animals have also been responsible for increased degradation of coastal wetlands. One of the worst invasive species has been Asian carp, who’s mating and feeding result in loss of submergent vegetation in shallow marsh waters.

Pressures were described by Dennis Albert in the Coastal Wetland Plant Communities Indicator.

Management Challenges/Opportunities

Although monitoring protocols have been developed for this indicator by the Great Lakes Coastal Wetlands

Consortium, monitoring on basin wide scale has not yet occurred. Implementations of a long term coastal wetland monitoring program is pending, however support for this program is need4ed by resource managers throughout the basin.

Assessing Data Quality

Data Characteristics

1. Data are documented, validated, or qualityassured by a recognized agency or organization

2. Data are traceable to original sources

3. The source of the data is a known, reliable and respected generator of data

4. Geographic coverage and scale of data are appropriate to the Great Lakes basin

5. Data obtained from sources within the U.S. are comparable to those from Canada

6. Uncertainty and variability in the data are documented and within acceptable limits for this indicator report

Strongly

Agree

X

X

X

X

X

X

Agree

Neutral or

Unknown

Disagree

Strongly

Disagree

Not

Applicable

Acknowledgments

Authors:

Danielle J. Sass, Oak Ridge Institute of Science and Education (ORISE) Research Fellow, Appointed to the U.S.

Environmental Protection Agency (U.S. EPA), Great Lakes National Program Office (GLNPO) (2008)

Donald G. Uzarski, Institute for Great Lakes Research, CMU Biological Station, and Department of Biology ,

Central Michigan University, Mount Pleasant, MI

Thomas M. Burton, Departments of Zoology and Fisheries and Wildlife, Michigan State University, East Lansing,

MI (2006)

John Brazner, US Environmental Protection Agency, Mid-Continent Ecology Division, Duluth, MN (2006)

David Jude, School of Natural Resources and the Environment, University of Michigan, Ann Arbor, MI (2006)

Jan J.H. Ciborowski, Department of Biological Sciences, University of Windsor, Windsor, ON

143

Information Sources

Bhagat, Y. 2005. Fish indicators of anthropogenic stress at Great Lakes coastal margins: multimetric and multivariate approaches. M.Sc. Thesis, University of Windsor. 120 p.

Bhagat, Y., Ciborowski, J.J.H., Johnson, L.B., Uzarski, D.G., Burton, T.M., Timmermans, S.T.A., and Cooper, M.J.

In press. Testing a fish index of biotic integrity for responses to different disturbance regimes on Great Lakes coastal wetlands.

Journal of Great Lakes Research.

Brazner, J. C. 1997. Regional, habitat, and human development influences on coastal wetland and beach fish assemblages in Green Bay, Lake Michigan. J. Great Lakes Res. 23(1):36-51.

Brazner, J.C., Tanner, D.K., Jensen, D.A., and Lemke, A. 1998. Relative abundance and distribution of ruffe

(

Gymnocephalus cernuus

) in a Lake Superior coastal wetland fish assemblage.

J. Great Lakes Res.

24(2):293-

303.

Brazner, J.C., Danz, N.P., Niemi, G.J., Regal, R.R., Trebitz, A.S., Howe, R.W., Hanowski, J.M., Johnson, L.B.,

Ciborowski, J.J.H., Johnston, C.A., Reavie, E.D., Brady, V.J., and Sgro, G.V. 2007. Evaluating geographic, geomorphic and human influences on Great Lakes wetland indicators: multi-assemblage variance partitioning.

Ecological Indicators

7:610-635.

Cooper, M.J., Ruetz, C.R. III, Uzarski, D.G., and Burton, T.M. 2007. Distribution of round gobies (

Neogobius melanostromus

) in Lake Michigan drowned river mouth lakes and wetlands: do coastal wetlands provide refugia for native species?

J. Great Lakes Res.

33(2):303-313.

Johnson, L.B., Olker, J., Ciborowski, J.J.H., Host, G.E., Breneman, D., Brady, V., Brazner, J., and Danz, N. 2006.

Identifying Response of Fish Communities in Great Lakes Coastal Regions to Land Use and Local Scale

Impacts.

Bull.

N. Am. Benthol. Soc

. [also in prep for submission to

J. Great Lakes Research

]

Jude, D.J. and DeBoe, S.F. 1996. Possible impact of gobies and other introduced species on habitat restoration efforts.

Can. J. Fish. Aquat. Sci.

53:136-141.

Jude, D. J., and Pappas, J. 1992. Fish utilization of Great Lakes coastal wetlands.

J. Great Lakes Res.

18(4):651-672.

Jude, D. J., Reider, R.H., and Smith, G. 1992. Establishment of Gobiidae in the Great Lakes basin.

Can. J.Fish.

Aquat. Sci.

49:416-421.

Jude, D.J., Albert, D., Uzarski, D.G., and Brazner, J. 2005. Lake Michigan’s coastal wetlands: Distribution, biological components with emphasis on fish and threats. In

The State of Lake Michigan: Ecology, Health and

Management. Ecovision World Monograph Series

, eds. M. Munawar and T. Edsall Aquatic Ecosystem Health and Management Society. pp. 439-477

Lapointe, N.W.R. 2005. Fish-habitat associations in shallow Canadian waters of the Detroit River. M.Sc. Thesis,

University of Windsor, Windsor, Ontario.

Leslie, J.K., Timmins, C.A., and Bonnell, R.G. 2002. Postembryonic development of the tubenose goby

Proterorhinus marmoratus

Pallas (Gobiidae) in the St. Clair River/Lake system, Ontario.

Arch. Hydrobiol

.

154:341-352.

Pronin, N.M., Fleischer, G.W., Baldanova, D.R., and Pronin, S.V. 1997. Parasites of the recently established round goby (

Neogobius melanostomis)

and tubenose goby (

Proterorhinus marmoratus

) (Cottidae) from the St. Clair

River and Lake St. Clair, Michigan, U.S.A.

Folia Parasitol

. 44-1-6.

Seilheimer, T.S. and Chow-Fraser, P. 2006. Development and use of the Wetland Fish Index to assess the quality of coastal wetlands in the Laurentian Great Lakes. Submitted to

Can. J. Fish. Aquat. Sci

. 63:354-366.

Seilheimer, T.S. and Chow-Fraser, P. 2007. Application of the Wetland Fish Index to Northern Great Lakes Marshes with Emphasis on Georgian Bay Coastal Wetlands. Journal of Great Lakes Research. 33.3

Thoma. R.F. 1999. Biological monitoring and an index of biotic integrity for Lake Erie’s nearshore waters. In

Assessing the sustainability and biological integrity of water resources using fish communities

ed. T.P. Simon.

CRC Press, Boca Raton, FL. pp. 417-461.

U.S. Fish and Wildlife Service. 2002. Asian Carp, Key to Identification. Pamphlet. LaCross Fishery Resources

Office, Onalaska, WI. http://www.fws.gov/midwest/lacrossefisheries/reports/asian_carp_key.pdf

Uzarski, D.G., Burton, T.M., Cooper, M.J., Ingram, J., and Timmermans, S.

2005. Fish Habitat Use Within and

144

Across Wetland Classes in Coastal Wetlands of the Five Great Lakes: Development of a Fish Based Index of

Biotic Integrity.

Journal of Great Lakes Research

31(1):171-187.

Uzarski, D. G., Burton, T. B., Brazner, J. C. and Ciborowski, J. J. H.. March 2008. Great Lakes Coastal Wetlands

Monitoring Plan, Chapter Five Fish Community Indicators. Developed by the Great Lakes Coastal Wetlands

Consortium, A project of the Great Lakes Commission.

Wei, A., Chow-Fraser, P. and Albert, D. 2004. Influence of shoreline features on fish distribution in the Laurentian

Great Lakes.

Can. J. Fish. Aquat. Sci

. 61:1113-1123.

Last Updated

State of the Great Lakes 2009

report.

An editor’s note was added for the 2011 reporting cycle

145

Coastal Wetland Invertebrate Communities

Overall Assessment

Status: Not Assessed

Trend: Not Assessed

Rationale: Part of an overall analysis of biological communities of Great Lakes coastal wetlands.

Note: This is a progress report towards implementation of this indicator. The indicator is currently being used throughout the entire Great Lakes basin, but data will not be available until 2012. The following evaluation was constructed using input from investigators collecting invertebrate community composition data from Great Lakes coastal wetlands over the last several years.

Regarding the following, neither experimental design nor statistical rigor has been used to specifically address the status and trends of invertebrate communities of coastal wetlands of the five Great Lakes. However, in the spring of 2011, an effort was put forth by a consortium of universities that established a statistically sound basin-wide coastal wetland monitoring program. This indicator will be used, along with others, at the majority of coastal wetlands with a surface water connection to the Great Lakes that are greater than 4 hectares in size. The effort is bi-national and basin wide and will produce scientifically-defensible information on the status and trends of Great Lakes coastal wetlands.

Lake-by-Lake Assessment

Each lake was categorized with a not assessed status and an undetermined trend, indicating that data were not available yet.

Purpose

To directly measure specific components of invertebrate community composition

To infer the chemical, physical and biological integrity and range of degradation of Great Lakes coastal wetlands

Ecosystem Objective

Significant wetland areas in the Great Lakes System that are threatened by urban and agricultural development and waste disposal activities should be identified, preserved and, where necessary, rehabilitated (Annex 13 GLWQA).

Conducting monitoring and surveillance activities will gather definitive information on the location, severity, aerial or volume extent, and frequency of the Great Lakes coastal wetlands (Annex 11 GLWQA). This indicator supports the restoration and maintenance of the chemical, physical and biological integrity of the Great Lakes basin and beneficial uses dependent on healthy wetlands (Annex 2 GLWQA).

Ecological Condition

Teams of Canadian and American researchers from several research groups (e.g. the Great Lakes Coastal Wetlands

Consortium, the Great Lakes Environmental Indicators project investigators, the U.S. Environmental Protection

Agency (U.S. EPA) Regional Environmental Monitoring and Assessment Program (REMAP) group of researchers, and others) sampled large numbers of Great Lakes wetlands. In 2002 the Great Lakes Coastal Wetlands Consortium conducted extensive surveys of wetland invertebrates of the four lower Great Lakes. The Consortium-adopted Index of Biotic Integrity (IBI, Uzarski

et al.

2004) was applied in wetlands of northern Lake Ontario. The results can be obtained from Environment Canada (Environment Canada and Central Lake Ontario Conservation Authority 2004).

These methods are now being used basin-wide by a consortium of universities but these data will not be available until 2012.

Uzarski

et al.

(2004) collected invertebrate data from 22 wetlands in Lake Michigan and Lake Huron during 1997 through 2001. They determined that wetland invertebrate communities of northern Lakes Michigan and Huron generally produced the highest IBI scores. IBI scores were primarily based on richness and abundance of Odonata,

Crustacea plus Mollusca taxa richness, total genera richness, relative abundance Gastropoda, relative abundance

Sphaeriidae, Ephemeroptera plus Trichoptera taxa richness, relative abundance Crustacea plus Mollusca, relative

146

abundance Isopoda, Evenness, Shannon Diversity Index, and Simpson Index. Wetlands near Escanaba and

Cedarville, Michigan, scored lower than most in the area. A single wetland near the mouth of the Pine River in

Mackinac County, MI, consistently scored low. In general, all wetlands of Saginaw Bay scored lower than those of northern Lakes Michigan and Huron. However, impacts are more diluted near the outer bay and IBI scores reflect this. Wetlands near Quanicassee and Almeda Beach, MI, consistently scored lower than other Saginaw Bay sites.

Burton and Uzarski also studied drowned river mouth wetlands of eastern Lake Michigan quite extensively since

1998. Invertebrate communities of these systems show linear relationship with latitude. However, this relationship also reflects anthropogenic disturbance. Based on the metrics used (Odonata richness and abundance, Crustacea plus

Mollusca richness, total genera richness, relative abundance Isopoda, Shannon Index, Simpson Index, Evenness, and relative abundance Ephemeroptera), the sites studied were placed in increasing community health in the order

Kalamazoo, Pigeon, Muskegon, White, Pentwater, Pere Marquette, Manistee, Lincoln, and Betsie. The most impacted systems of eastern Lake Michigan are located along southern edge and impacts decrease to the north.

Wilcox

et al.

(2002) attempted to develop wetland IBIs for the upper Great Lakes using microinvertebrates. While they found attributes that showed promise during a single year, they concluded that natural water level changes were likely to alter communities and invalidate metrics. They found that Siskiwit Bay, Bark Bay, and Port Wing had the greatest overall taxa richness with large catches of cladocerans. They ranked microinvertebrate communities of Fish

Creek and Hog Island lower than the other four western Lake Superior sites. Their work in eastern Lake Michigan testing potential metrics placed the sites studied in decreasing community health in the order Lincoln River, Betsie

River, Arcadia Lake/Little Manistee River, Pentwater River, and Pere Marquette River. This order was primarily based on the median number of taxa, the median Cladocera genera richness, and also a macroinvertebrate metric

(number of adult Trichoptera species).

Pressures

Physical alteration and eutrophication of wetland ecosystems continue to be a threat to invertebrates of Great Lakes coastal wetlands. Both can promote establishment of non-native vegetation, and physical alteration can destroy plant communities altogether while changing the natural hydrology to the system. Invertebrate community composition is directly related to vegetation type and densities; changing either of these components will negatively impact the invertebrate communities.

Agriculture

Agriculture degrades wetlands in several ways, including nutrient enrichment from fertilizers, increased sediments from erosion, increased rapid runoff from drainage ditches, introduction of agricultural non-native species (reed canary grass), destruction of inland wet meadow zone by plowing and diking, and addition of herbicides.

Urban development

Urban development degrades wetlands by hardening shoreline, filling wetland, adding a broad diversity of chemical pollutants, increasing stream runoff, adding sediments, and increased nutrient loading from sewage treatment plants.

In most urban settings, almost complete wetland loss has occurred along the shoreline.

Residential shoreline development

Along many coastal wetlands, residential development has altered wetlands by nutrient enrichment from fertilizers and septic systems, shoreline alterations for docks and boat slips, filling, and shoreline hardening. Agriculture and urban development are usually less intense than local physical alteration which often results in the introduction of non-native species.

Mechanical alteration of shoreline

Mechanical alteration takes a diversity of forms, including diking, ditching, dredging, filling, and shoreline hardening. With all of these alterations, non-native species are introduced by construction equipment or in

147

introduced sediments.

Introduction of non-native species

Non-native species are introduced in many ways. Some were purposefully introduced as agricultural crops or ornamentals, later colonizing in native landscapes. Others came in as weeds in agricultural seed. Increased sediment and nutrient enrichment allow many of the worst aquatic weeds to out-compete native species. Most of the worst non-native species are either prolific seed producers or reproduce from fragments of root or rhizome. Non-native animals have also been responsible for increased degradation of coastal wetlands.

Pressures were described by Dennis Albert in the Coastal Wetland Plant Communities Indicator.

Management Challenges/Opportunities

Although monitoring protocols have been developed for this indicator by the Great Lakes Coastal Wetlands

Consortium, monitoring on basin wide scale has not yet occurred. Implementations of a long term coastal wetland monitoring program is pending, however support for this program is need4ed by resource managers throughout the basin.

Assessing Data Quality

Data Characteristics

1. Data are documented, validated, or qualityassured by a recognized agency or organization

2. Data are traceable to original sources

3. The source of the data is a known, reliable and respected generator of data

4. Geographic coverage and scale of data are appropriate to the Great Lakes basin

5. Data obtained from sources within the U.S. are comparable to those from Canada

6. Uncertainty and variability in the data are documented and within acceptable limits for this indicator report

Strongly

Agree

X

X

X

X

X

X

Agree

Neutral or

Unknown

Disagree

Strongly

Disagree

Not

Applicable

Acknowledgments

Authors:

Donald G. Uzarski, Institute for Great Lakes Research, CMU Biological Station, and Department of Biology,

Central Michigan University, Mount Pleasant, MI.

Thomas M. Burton, Departments of Zoology and Fisheries and Wildlife, Michigan State University, East Lansing,

MI, 48824. (2006)

Contributors:

Danielle J. Sass, Oak Ridge Institute of Science and Education (ORISE) Research Fellow, Appointed to the U.S.

Environmental Protection Agency (U.S. EPA), Great Lakes National Program Office (GLNPO) (2008)

Information Sources

Environment Canada and Central Lake Ontario Conservation Authority. 2004.

Durham Region Coastal Wetland

Monitoring Project: year 2 technical report.

Downsview, ON. ECB-OR.

Uzarski, D.G., Burton, T.M., and Genet, J.A. 2004. Validation and performance of an invertebrate index of biotic integrity for Lakes Huron and Michigan fringing wetlands during a period of lake level decline.

Aquat.

Ecosystem Health & Manage.

7(2):269-288.

Wilcox, D.A., Meeker, J.E., Hudson, P.L., Armitage, B.J., Black, M.G., and Uzarski, D.G. 2002. Hydrologic variability and the application of index of biotic integrity metrics to wetlands: a Great Lakes evaluation.

148

Wetlands

22(3):588-615

Last Updated

State of the Great Lakes 2009

report.

An editor’s note was added for the 2011 reporting cycle

149

Coastal Wetland Landscape Extent and Composition

Overall Assessment

Status:

Fair

Trend:

Rationale:

Deteriorating

To monitor losses of coastal wetland area due to human actions and gains to coastal wetlands due to restoration activities.

Note: In the spring of 2011, an effort was put forth by a consortium of universities that established a statistically sound basinwide coastal wetland monitoring program. This indicator will be used, along with others, at the majority of coastal wetlands with a surface water connection to the Great Lakes that are greater than 4 hectares in size. The effort is bi-national and basin wide and will produce scientifically-defensible information on the status and trends of Great Lakes coastal wetlands.

Lake-by-Lake Assessment

Each lake was categorized with a not assessed status and an undermined trend, indicating that assessments were not made on an individual lake basis.

Purpose

To assess the periodic changes in area (particularly losses) of coastal wetland types, taking into account natural lake level variations

Ecosystem Objective

Maintain total aerial extent of Great Lakes coastal wetlands, ensuring adequate representation of coastal wetland types across their historical range (Great Lakes Water Quality Agreement, Annexes 2 and 13,

United States and Canada 1987).

State of the Ecosystem

The status of this indicator has not been updated since the

State of the Great Lakes 2005

report. Future updates to the status of this indicator will require the repeated collection and analysis of remotely-sensed information.

Currently, technologies and methods are being assessed for an ability to estimate wetland extent. Next steps, including determination of funding and resource needs, as well as pilot investigations, must occur before an indicator status update can be made. The timeline for this is not yet determined. However, once a methodology is established, it will be applicable for long-term monitoring for this indicator, which is imperative for an improved understanding of wetland functional responses and adaptive management. The 2005 assessment of this indicator follows.

Despite the fact that several wetland restoration and protection efforts have improved specific areas, wetlands continue to be lost and degraded. The ability to track and determine the extent and rate of this loss in a standardized way is not yet feasible.

In an effort to estimate the extent of coastal wetlands in the basin, the Great Lakes Coastal Wetland Consortium

(GLCWC) coordinated completion of a binational coastal wetland database. The project involved building from existing Canadian and U.S. coastal wetland databases (Environment Canada and Ontario Ministry of Natural

Resources 2003; Herdendorf

et al

. 1981a-f) and incorporating additional auxiliary federal, provincial and state data to create a more complete, digital Geographic Information System (GIS) vector database. All coastal wetlands in the database were classified using a Great Lakes hydrogeomorphic coastal wetland classification system (Albert

et al

.

2005). The project was completed in 2004. The GIS database provides the first spatially explicit seamless binational summary of coastal wetland distribution in the Great Lakes system. Coastal wetlands totaling 216,743 ha (535,582 acres) have been identified within the Great Lakes and connecting rivers up to Cornwall, ON (Fig. 1). However, due

150

to existing data limitations, estimates of coastal wetland extent, particularly for the upper Great Lakes are acknowledged to be incomplete.

Despite significant loss of coastal wetland habitat in some regions of the Great Lakes, the lakes and connecting rivers still support a diversity of wetland types. Barrier protected coastal wetlands are a prominent feature in the upper Great Lakes, accounting for over 60,000 ha (150,000 acres) of the identified coastal wetland area in Lake

Superior, Lake Huron and Lake Michigan (Fig. 2). Lake Erie supports 22,000 ha (54,500 acres) of coastal wetland, with protected embayment wetlands accounting for over one third of the total area (Fig. 2). In Lake Ontario, barrier protected and drowned rivermouth coastal wetlands account for 19,000 ha (47,000 acres), approximately three quarters of the total coastal wetland area.

Connecting rivers within the Great Lakes system also support a diverse and significant quantity of wetlands (Fig. 3).

The St. Clair River delta occurs where the St. Clair River outlets into Lake St. Clair, and it is the most prominent single wetland feature accounting for over 13,000 ha (32,000 acres). The Upper St. Lawrence River also supports a large area of wetland habitats that are typically numerous small embayment and drowned rivermouth wetlands associated with the Thousand Island region and St. Lawrence River shoreline.

Pressures

There are many stressors which have contributed and continue to contribute to the loss and degradation of coastal wetland area. These include: filling, dredging and draining for conversion to other uses such as urban, agricultural, marina, and cottage development; shoreline modification; water level regulation; sediment and nutrient loading from watersheds; adjacent land use; invasive species, particularly non-native species; and climate variability and change.

The natural dynamics of wetlands must be considered in addressing coastal wetland stressors. Global climate variability and change have the potential to amplify the dynamics by reducing water levels in the system in addition to changing seasonal storm intensity and frequency, water level fluctuations and temperature.

Agriculture

Agriculture degrades wetlands in several ways, including nutrient enrichment from fertilizers, increased sediments from erosion, increased rapid runoff from drainage ditches, introduction of agricultural non-native species (reed canary grass,

Phalaris arundinacea

), destruction of inland wet meadow zones by plowing and diking, and addition of herbicides. In the southern lakes, Saginaw Bay, and Green Bay, agricultural sediments have resulted in highly turbid waters which support few or no submergent plants.

Urban development

Urban development degrades wetlands by hardening shoreline, filling wetlands, adding a broad diversity of chemical pollutants, increasing stream runoff, adding sediments, and increasing nutrient loading from sewage treatment plants. In most urban settings, almost complete wetland loss has occurred along the shoreline.

Residential shoreline development

Residential development has altered many coastal wetlands by nutrient enrichment from fertilizers and septic systems, shoreline alterations for docks and boat slips, filling, and shoreline hardening. Agriculture and urban development are usually less intense than local physical alteration which often results in the introduction of nonnative species. Shoreline hardening can completely eliminate wetland vegetation.

Mechanical alteration of shoreline

Mechanical alteration takes a diversity of forms, including diking, ditching, dredging, filling, and shoreline hardening. With all of these alterations, non-native species are introduced via construction equipment or in introduced sediments. Changes in shoreline gradients and sediment conditions are often adequate to allow nonnative species to become established.

151

Introduction of non-native species

Non-native species are introduced in many ways. Some were purposefully introduced as agricultural crops or ornamentals, later colonizing in native landscapes. Others came in as weeds in agricultural seed. Increased sediment and nutrient enrichment allow many of the most damaging aquatic weeds to out-compete native species. Most of the most damaging non-native species are either prolific seed producers or reproduce from fragments of root or rhizome.

Non-native animals have also been responsible for increased degradation of coastal wetlands. One of the most damaging non-native species has been Asian carp; these species’ mating and feeding result in loss of submergent vegetation in shallow marsh waters.

Pressures were described by Dennis Albert in the Coastal Wetland Plant Communities Indicator.

Management Implications

Although monitoring protocols have been developed for this indicator by the Great Lakes Coastal Wetlands

Consortium, monitoring on a basin-wide scale has net yet occurred. Implementations of a long-term coastal wetland monitoring program is pending, however support for this program is needed by resource managers throughout the basin.

Many of the pressures result from direct human actions, and thus, with proper consideration of the impacts, can be reduced. Several organizations have designed and implemented programs to help reduce the trend toward wetland loss and degradation.

Because of growing concerns around water quality and supply, which are key Great Lakes conservation issues, and the role of wetlands in flood attenuation, nutrient cycling and sediment trapping, wetland changes will continue to be monitored closely. Providing accurate useable information to decision-makers from government to private landowners is critical to successful stewardship of the wetland resource.

Comments from the author(s)

Development of improved, accessible, and affordable remote sensing technologies and information, along with concurrent monitoring of other Great Lakes indicators, will aid in implementation and continued monitoring and reporting of this indicator.

The GLCWC database represents an important step in establishing a baseline for monitoring and reporting on Great

Lakes coastal wetlands including extent and other indicators. Affordable and accurate remote sensing methodologies are required to complete the baseline and begin monitoring change in wetland area by type in the future. Other

GLCWC-guided research efforts are underway to assess the use of various remote sensing technologies in addressing this current limitation. Preliminary results from these efforts indicate the potential of using radar imagery and methods of hybrid change detection for monitoring changes in wetland type and conversion.

The difficult decisions on how to address human-induced stressors causing wetlands loss have been considered for some time. Several organizations and programs continue to work to reverse the trend, though much work remains.

A better understanding of wetland functions, through additional research and implementation of biological monitoring within coastal wetlands, will help ensure that wetland quality is maintained in addition to areal extent.

An educated public is critical to ensuring that wise decisions about the stewardship of the Great Lakes basin ecosystem are made.

152

Assessing Data Quality

Data Characteristics

1. Data are documented, validated, or qualityassured by a recognized agency or organization

2. Data are traceable to original sources

3. The source of the data is a known, reliable and respected generator of data

4. Geographic coverage and scale of data are appropriate to the Great Lakes basin

5. Data obtained from sources within the U.S. are comparable to those from Canada

6. Uncertainty and variability in the data are documented and within acceptable limits for this indicator report

X

Strongly

Agree

Agree

X

X

X

X

Neutral or

Unknown

Disagree

Strongly

Disagree

Not

Applicable

X

Acknowledgments

Authors: (2006)

Joel Ingram, Canadian Wildlife Service, Environment Canada

Lesley Dunn, Canadian Wildlife Service, Environment Canada

Krista Holmes, Canadian Wildlife Service, Environment Canada

Dennis Albert, Michigan Natural Features Inventory, Michigan State University Extension

Contributors

Greg Grabas and Nancy Patterson, Canadian Wildlife Service, Environment Canada;

Laura Simonson, Water Resources Discipline, U.S. Geological Survey;

Brian Potter, Conservation and Planning Section-Lands and Waters Branch, Ontario Ministry of Natural Resources;

Tom Rayburn, Great Lakes Commission,

Laura Bourgeau-Chavez, General Dynamics Advanced Information Systems

Sources

Albert, D.A., Wilcox, D.A., Ingram, J.W., and Thompson, T.A. 2005. Hydrogeomorphic classification for Great

Lakes coastal wetlands.

J. Great Lakes Res

31(1):129-146.

Environment Canada and Ontario Ministry of Natural Resources. 2003.

The Ontario Great Lakes Coastal Wetland

Atlas: a summary of information (1983 - 1997)

. Canadian Wildlife Service (CWS), Ontario Region,

Environment Canada; Conservation and Planning Section-Lands and Waters Branch, and Natural Heritage

Information Center, Ontario Ministry of Natural Resources.

Herdendorf, C.E., Hartley, S.M., and Barnes, M.D. (eds.). 1981a.

Fish and wildlife resources of the Great Lakes coastal wetlands within the United States, Vol. 1: Overview

. U.S. Fish and Wildlife Service, Washington, DC.

FWS/OBS-81/02-v1.

Herdendorf, C.E., Hartley, S.M., and Barnes, M.D. (eds.). 1981b.

Fish and wildlife resources of the Great Lakes coastal wetlands within the United States, Vol. 2: Lake Ontario

. U.S. Fish and Wildlife Service, Washington,

DC. FWS/OBS-81/02-v2.

Herdendorf, C.E., Hartley, S.M., and Barnes, M.D. (eds.). 1981c.

Fish and wildlife resources of the Great Lakes coastal wetlands within the United States, Vol. 3: Lake Erie

. U.S. Fish and Wildlife Service, Washington, DC.

FWS/OBS-81/02-v3.

Herdendorf, C.E., Hartley, S.M., and Barnes, M.D. (eds.). 1981d.

Fish and wildlife resources of the Great Lakes coastal wetlands within the United States, Vol. 4: Lake Huron

. U.S. Fish and Wildlife Service, Washington,

DC. FWS/OBS-81/02-v4.

Herdendorf, C.E., Hartley, S.M., and Barnes, M.D. (eds.). 1981e.

Fish and wildlife resources of the Great Lakes

153

coastal wetlands within the United States, Vol. 5: Lake Michigan

. U.S. Fish and Wildlife Service, Washington,

DC. FWS/OBS-81/02-v5.

Herdendorf, C.E., Hartley, S.M., and Barnes, M.D. (eds.). 1981f.

Fish and wildlife resources of the Great Lakes coastal wetlands within the United States, Vol. 6: Lake Superior

. U.S. Fish and Wildlife Service, Washington,

DC. FWS/OBS-81/02-v6.

United States and Canada. 1987.

Great Lakes Water Quality Agreement of 1978, as amended by Protocol signed

November 18, 1987.

Ottawa and Washington.

List of Figures

Figure 1.

Great Lakes coastal wetland distribution and total area by lake and river.

Source: Great Lakes Coastal Wetlands Consortium

Figure 2.

Coastal wetland area by geomorphic type within lakes of the Great Lakes system.

Source: Great Lakes Coastal Wetlands Consortium

Figure 3.

Coastal wetland area by geomorphic type within connecting rivers of the Great Lakes system.

Source: Great Lakes Coastal Wetlands Consortium

Last Updated

State of the Great Lakes 2009

report.

An editor’s note was added for the 2011 reporting cycle.

The “Mixed” status term used in the 2009 report were replaced with the “Fair” status term to be consistent with definitions used for the 2011 reporting cycle.

Figure 1.

Great Lakes coastal wetland distribution and total area by lake and river.

Source: Great Lakes Coastal Wetlands Consortium

154

Figure 2.

Coastal wetland area by geomorphic type within lakes of the Great Lakes system.

Source: Great Lakes Coastal Wetlands Consortium

Figure 3.

Coastal wetland area by geomorphic type within connecting rivers of the Great Lakes system.

Source: Great Lakes Coastal Wetlands Consortium

155

Coastal Wetland Plants

Overall Assessment

Status: Fair

Trend: Undetermined

Rationale: The status of the coastal wetland plant community in the Great Lakes is mixed because Lake

Superior and Lake Ontario have individual wetlands plant communities that have a good status.

Lake Michigan, Lake Huron, and Lake Erie are all listed with a fair status of their coastal

wetland plant community health.

Note: In the spring of 2011, an effort was put forth by a consortium of universities that established a statistically sound basinwide coastal wetland monitoring program. This indicator will be used, along with others, at the majority of coastal wetlands with a surface water connection to the Great Lakes that are greater than 4 hectares in size. The effort is binational and basin wide and will produce scientifically-defensible information on the status and trends of Great Lakes coastal wetlands.

Lake-by-Lake Assessment

Lake Superior

Status: Fair

Trend: Undetermined

Rationale: Degradation around major urban areas. Coastal wetlands plants in Lake Superior generally have a good status.

Lake Michigan

Status: Fair

Trend: Undetermined

Rationale: High quality wetlands in the northern part of the lake. Lakes Michigan’s northern open embayments and protected embayment are higher quality compared to the coastal wetlands in the drowned river mouth.

Lake Huron

Status: Fair

Trend: Undetermined

Rationale: Plowing, raking and mowing on Saginaw Bay wetland during low water causing degradation.

Northern wetlands are higher quality. Lake Huron’s northern protected embayments and open embayments generally have fair to good status with individual wetlands having good status.

However, in Saginaw Bay the open embayment have poor to fair status. Loss of emergent vegetation has occurred in wetlands bordering the St. Marys River, connecting river between

Lakes Superior and Huron during 1999 to 2011 low-water conditions, probably the result of both winter ice and ship wakes on exposed sediments and vegetation beds.

Lake Erie

Status: Fair

Trend: Deteriorating

Rationale: Generally poor on U.S. shore with some restoration at Metzger Marsh Ohio. Presque Isle,

Pennsylvania and Long Point, Ontario have high quality wetlands. Lake Erie’s open and sand-spit embayments have a fair status. The lake is also classified as deteriorating based on historically data from 1975 in Lake Erie.

156

Lake Ontario

Status: Poor

Trend: Unchanging

Rationale: Degraded by nutrient loading and water level control. Some scattered Canadian wetlands of higher quality. Lake Ontario’s barrier beach lagoons have higher quality than the drowned river mouths and the protected embayments. However, individual coastal wetlands in the protected embayments have good status.

Purpose

To assess the level of native vegetative diversity and cover for use as a surrogate measure of quality of coastal wetlands which are impacted by coastal manipulation or input of sediments.

The Coastal Wetland Plant Communities indicator is used in the Great Lakes indicator suite as a State indicator in the Aquatic-dependent Life top level reporting category.

Ecosystem Objective

Coastal wetlands throughout the Great Lakes basin should be dominated by native vegetation, with low numbers of invasive and non-native plants species that have low levels of coverage. Significant wetland areas in the Great Lakes

System that are threatened by urban and agricultural development and waste disposal activities should be identified, preserved and, where necessary, rehabilitated (Annex 13 GLWQA). This indicator supports the restoration and maintenance of the chemical, physical and biological integrity of the Great Lakes basin and beneficial uses dependent on healthy wetlands (Annex 2 GLWQA).

Ecological Condition

The conditions of the plant community in coastal wetlands naturally differ across the Great Lakes basin, due to differences in geomorphic and climatic conditions. The characteristic size and plant diversity of coastal wetlands vary by wetland type, lake, and latitude; in this document these differences will be described broadly as “regional wetland types.”

Regional Wetland Types

Coastal wetlands are divided into three main categories based on the hydrology of the area. Lacustrine wetlands are connected to the Great Lakes, and they are largely impacted by fluctuations in lake levels. Riverine wetlands occur near rivers that are found in the Great Lakes basin. Typically, the quality of riverine wetlands are dominated by the river drainage system, however coastal process can cause lakes to flood back into these wetlands. The last type of coastal wetlands is barrier protected. Barrier protected wetlands are derived from coastal processes that separate the wetland from the Great Lakes by barrier beaches. All coastal wetlands contain different zones (swamp, meadow, emergent, submergent), some of which may be absent in certain types of wetlands. Great Lakes wetlands were classified and mapped in 2004 (see http://glc.org/wetlands/inventory.html

). United States coastal wetlands inventory map (see http://glc.org/wetlands/us_mapping.html

) and Canada coastal wetland inventory map (see http://glc.org/wetlands/can_mapping.html

).

Lake Variations

Physical properties such as the type of shoreline and chemical and physical water quality parameters vary between great lakes. The variation of nutrient levels creates a north to south gradient, and nutrient levels also increase in lake basins further to the east. This includes Lake Erie, Lake Ontario, and in the upper St. Lawrence River. Lake

Superior is the most distinct great lake due to its low alkalinity and prevalence of bedrock shoreline.

Differences in Latitude

Latitudinal variations result in different climatic conditions based on the location of the coastal wetlands.

Temperature differences between the north and south lead to differences in the species of plants found in coastal

157

wetlands. The southern portion of the Great Lakes also has increased agricultural activity along the shorelines, resulting in increased nutrient loads, sedimentation and non-native species introductions.

There are characteristics of coastal wetlands that make usage of plants as indicators difficult in certain conditions.

Among these are:

Water level fluctuation

Great Lakes water levels fluctuate greatly from year to year. Either an increase or decrease in water level can result in changes in numbers of species or overall species composition in the entire wetland or in specific zones. Such a change makes it difficult to monitor change over time. Changes are great in two zones: the wet meadow, where grasses and sedges may disappear in high water or new annuals may appear in low water, and in shallow emergent or submergent zones, where submergent and floating plants may disappear when water levels drop rapidly. Recent studies indicate that prolonged periods of low water favor rapid expansion of invasive species like Phragmites australis (Albert and Brown 2008, Lishawa etal. 2010)

Lake-wide alterations

For the southern lakes, most wetlands have been dramatically altered by both intensive agriculture and urban development of the shoreline. Alterations of coastal wetland especially in the wet meadow and upper emergent zone will lead to drier conditions which may allow invasive species to establish.

There are several hundred species of plants that occur within coastal wetlands. To evaluate the status of wetlands using plants as indicators, several different plant metrics have been suggested. These are discussed briefly here.

Invasive Plant Cover

The invasive plant cover for an entire site and all coastal wetlands zones including wet meadows, dry emergent, flooded emergent and submergent zones that are considered high quality should not have any invasive plants present. For low quality coastal wetlands all zones are expected to have 25 to 50% cover of invasive plants. Invasive plant cover that is more than 50% is considered to be very low quality (Albert, 2008). Invasive plant cover includes both native and non-native invasive plants.

Invasive Frequency

The invasive frequency is measured similar to invasive plant cover. Invasive plants are expected to be absent in all coastal wetland zones to be considered a high quality coastal wetlands. When invasive frequency is consider low to very low quality invasive plants are present in 25 to more than 50% of the coastal wetland (Albert, 2008). Invasive frequency includes both native and non-native invasive plants.

Mean Conservatism (Native Species)

Conservatism indices were developed using the Floristic Quality Assessment (FQA) program. The mean conservatism is an index that measures the specificity of a particular species of plant to a specific habitat (Albert,

2008). The mean conservatism index also evaluates the intactness of coastal wetlands, which is based on all of the plant species in the wetlands. A species is considered conservative if it only grows in a specific, high quality environment. Plant species that are ubiquitous receive a low conservatism score (0) however plant species that are rare and only found in specific habitats are assigned a high conservatism score (10) (Swink, and Wilhelm, 1994).

The mean conservatism index includes all of the species found in a habitat.

Mean conservatism ratios may also be calculated. The ratio is derived by taking the mean conservatism index for all species present divided by the mean conservatism index for native species. Mean conservatism ratios that are less than 0.79 are expected to represent large numbers of exotic species present with degraded conditions. Mean conservatism ratios that are 0.8 and above represent medium to high quality conservatism with many native species present (Albert, 2008). See Table 1.

158

Lake Assessment Scale for Mean Conservatism Scores

Good – 6.0 and above

Fair – 3.0 - 5.9

Poor – 0.0 - 2.9

Mixed – Combination of two categories

The total marsh in Lake Superior appears to have the highest quality wetlands when compared to the other lakes with a 6.4 conservatism index. Lake Michigan and Lake Huron have very similar total marsh conservatism indices ranging from 4.5 to 5.6. Lake Erie has a fair conservatism index ranging from 3.1 to 4.5. However, compared to historic ratings the coastal wetlands are deteriorating. Lastly, Lake Ontario has a fair conservatism index with a range consisting of 3.9 to 5.7. Overall, a majority of the lake fall into the fair quality of coastal wetland based on the conservatism index.

The state of the wetland plant community is quite variable, ranging from good to poor across the Great Lakes basin.

The wetlands in individual lake basins are often similar in their characteristics because of water level controls and lake-wide near-shore management practices. There is evidence that the plant component in some wetlands is deteriorating in response to extremely low water levels in some of the Great Lakes, but this deterioration is not seen in all wetlands within these lakes. In general, there is slow deterioration in many wetlands as shoreline alterations introduce non-native species. However, the turbidity of the southern Great Lakes has reduced with expansion of zebra mussels, resulting in improved submergent plant diversity in many wetlands.

Trends in wetland health based on plants have not been well established. In the southern Great Lakes (Lake Erie,

Lake Ontario, and the Upper St. Lawrence River), almost all wetlands are degraded by either water level control, nutrient enrichment, sedimentation, or a combination of these factors. Probably the strongest demonstration of this is the prevalence of broad zones of cat-tails, reduced submergent diversity and coverage, and prevalence of non-native plants, including reed (

Phragmites australis

), reed canary grass (

Phalaris arundinacea

), purple loosestrife (

Lythrum salicaria

), curly pondweed (

Potamogeton crispus

), Eurasian milfoil (

Myriophyllum spicatum

), and frog bit

(

Hydrocharis morsus-ranae

). In the remaining Great Lakes (Lake St. Clair, Lake Huron, Lake Michigan, Georgian

Bay, Lake Superior, and their connecting rivers), intact, diverse wetlands can be found for most geomorphic wetland types. However, low water conditions have resulted in the almost explosive expansion of reed in many wetlands, especially in Lake St. Clair and southern Lake Huron, including Saginaw Bay (Albert and Brown 2008). As water levels rise, the response of reed should be monitored.

One of the disturbing trends is the expansion of frog bit, a floating plant that forms dense mats capable of eliminating submergent plants, from the St. Lawrence River and Lake Ontario westward into Lake Erie. This expansion will probably continue into all or many of the remaining Great Lakes, and has been seen since 2008, when additional populations have been documented in Lake St. Clair and the St. Clair River delta, as well as along the St. Marys River connecting Lakes Huron and Superior.

Studies in the northern Great Lakes have demonstrated that non-native species like reed, reed canary grass, and purple loosestrife have become established throughout the Great Lakes, but that the abundance of these species is low, often restricted to only local disturbances such as docks and boat channels. It appears that undisturbed marshes are not easily colonized by these species. However, as these species become locally established, seeds or fragments of plants may be able to establish themselves when water level changes create appropriate sediment conditions.

Hybrid cat-tail (

Typha

x

glauca

) expansion has also been recently documented in northern Lakes Michigan andHuron and the St. Marys River (Lishawa etal. 2010).

159

Pressures

Agriculture

Agriculture degrades wetlands in several ways, including nutrient enrichment from fertilizers, increased sediments from erosion, increased rapid runoff from drainage ditches, introduction of agricultural non-native species (reed canary grass), destruction of inland wet meadow zone by plowing and diking, and addition of herbicides. In the southern lakes, Saginaw Bay, and Green Bay, agricultural sediments have resulted in highly turbid waters which support few or no submergent plants.

Urban development

Urban development degrades wetlands by hardening shoreline, filling wetland, adding a broad diversity of chemical pollutants, increasing stream runoff, adding sediments, and increased nutrient loading from sewage treatment plants.

In most urban settings, almost complete wetland loss has occurred along the shoreline.

Residential shoreline development

Along many coastal wetlands, residential development has altered wetlands by nutrient enrichment from fertilizers and septic systems, shoreline alterations for docks and boat slips, filling, and shoreline hardening. Agriculture and urban development are usually less intense than local physical alteration which often results in the introduction of non-native species. Shoreline hardening can completely eliminate wetland vegetation.

Mechanical alteration of shoreline

Mechanical alteration takes a diversity of forms, including diking, ditching, dredging, filling, shoreline hardening, and disking and plowing of coastal vegetation by private landowners. With all of these alterations, non-native species are introduced by construction equipment or in introduced sediments. Changes in shoreline gradients and sediment conditions are often adequate to allow non-native species to become established. Disking and plowing of coastal wetlands continues through 2011 in exposed coastal marshes along Saginaw Bay, Grand Traverse Bay, and on islands within the St. Clair River delta.

Introduction of non-native species

Non-native species are introduced in many ways. Some were purposefully introduced as agricultural crops or ornamentals, later colonizing in native landscapes. Others came in as weeds in agricultural seed. Increased sediment and nutrient enrichment allow many of the worst aquatic weeds to out-compete native species. Most of the worst non-native species are either prolific seed producers or reproduce from fragments of root or rhizome. Non-native animals have also been responsible for increased degradation of coastal wetlands. One of the worst invasive species has been Asian carp, who’s mating and feeding result in loss of submergent vegetation in shallow marsh waters.

Pressures were described by Dennis Albert in the Coastal Wetland Plant Communities Indicator.

Management Challenges/Opportunities

Although monitoring protocols have been developed for this indicator by the Great Lakes Coastal Wetlands

Consortium, monitoring on basin wide scale has net yet occurred. Implementations of a long term coastal wetland monitoring program is pending, however support for this program is need4ed by resource managers throughout the basin.

While plants are currently being evaluated as indicators of specific types of degradation, there are limited examples of the effects of changing management on plant composition. Restoration efforts at Cootes Paradise, Oshawa

Second, and Metzger Marsh have recently evaluated a number of restoration approaches to restore submergent and emergent marsh vegetation, including carp elimination, hydrologic restoration, sediment control, and plant introduction. The effect of agriculture and urban sediments may be reduced by incorporating buffer strips along streams and drains. Nutrient enrichment could be reduced by more effective fertilizer application, thereby reducing algal blooms. However, even slight levels of nutrient enrichment cause dramatic increases in submergent plant

160

coverage. For most urban areas it may prove impossible to reduce nutrient loads adequately to restore native aquatic vegetation. Mechanical disturbance of coastal sediments appears to be one of the primary vectors for introduction of non-native species. Thorough cleaning of equipment to eliminate seed source and monitoring following disturbances might reduce new introductions of non-native plants.

Assessing Data Quality

Data Characteristics

Strongly

Agree

Agree

Neutral or

Unknown

Disagree

Strongly

Disagree

Not

Applicable

1. Data are documented, validated, or qualityassured by a recognized agency or organization

2. Data are traceable to original sources

3. The source of the data is a known, reliable and respected generator of data

4. Geographic coverage and scale of data are appropriate to the Great Lakes basin

5. Data obtained from sources within the U.S. are comparable to those from Canada

X

X

X

X

X

6. Uncertainty and variability in the data are documented and within acceptable limits for X this indicator report

Clarifying Notes: Data was collected by the Great Lakes Coastal Wetlands Consortium using the Great Lakes Coastal Wetland

Monitoring Plan. There has been a lot of sampling, with most of the larger marshes in all of the Great Lakes being sampled. The only exception is Georgian Bay, where the sampling has been spottier and the overall development of indicators less detailed.

Acknowledgments

Author:

Dennis Albert, Michigan Natural Features Inventory, Michigan State University Extension. (2006-2008). Curently

Senior Research Faculty, Horticulture Department, Oregon State University.

Danielle J. Sass, Oak Ridge Institute of Science and Education (ORISE) Research Fellow, Appointed to the U.S.

Environmental Protection Agency (U.S. EPA), Great Lakes National Program Office (GLNPO) (2008)

Contributor:

Great Lakes Coastal Wetlands Consortium

Information Sources

Albert, D. A., and P. Brown. Coastal wetlands in Michigan: Effect of isolation on Pragmites australis expansion.

Michigan Natural Features Inventory report 2008-14.

Albert, D.A., and Minc, L.D. 2001. Abiotic and floristic characterization of Laurentian Great Lakes’ coastal wetlands. Stuttgart, Germany.

Verh. Internat. Verein. Limnol

. 27:3413-3419.

Albert, D.A., Wilcox, D.A., Ingram, J.W., and Thompson, T.A. 2006. Hydrogeomorphic Classification for Great

Lakes Coastal Wetlands.

J. Great Lakes Res

31(1):129-146

..

Albert, D.A., March 2008. Great Lakes Coastal Wetlands Monitoring Plan, Chapter Three Vegetation Community

Indicators. Developed by the Great Lakes Coastal Wetlands Consortium, A project of the Great Lakes

Commission.

Environment Canada and Central Lake Ontario Conservation Authority. 2004.

Durham Region Coastal Wetland

Monitoring Project: Year 2 Technical Report.

Environment Canada, Downsview, ON: ECB-OR.

Great Lakes Commission. Great lakes Coastal Wetlands Consortium. Inventory and Classification. Last updated:

June 30, 2007. http://glc.org/wetlands/inventory.html

Great Lakes Commission. Great lakes Coastal Wetlands Consortium. Coastal Wetlands Inventory-Great Lakes

Region. Last updated: April 20, 2004. http://glc.org/wetlands/us_mapping.html

Great Lakes Commission. Great lakes Coastal Wetlands Consortium. Canadian Mapping Resources. Last updated:

161

April 20, 2004. http://glc.org/wetlands/can_mapping.html

Herdendorf, C.E. 1988.

Classification of geological features in Great Lakes nearshore and coastal areas. Protecting

Great Lakes Nearshore and Coastal Diversity Project

. International Joint Commission and The Nature

Conservancy, Windsor, ON.

Herdendorf, C.E., Hakanson, L., Jude, D.J., and Sly, P.G. 1992. A review of the physical and chemical components of the Great Lakes: a basis for classification and inventory of aquatic habitats. In

The development of an aquatic habitat classification system for lakes eds

. W.-D. N. Busch and P. G. Sly, pp. 109-160. Ann Arbor,

MI: CRC Press.

Herdendorf, C.E., Hartley, S.M., and Barnes, M.D. (eds.). 1981a.

Fish and wildlife resources of the Great Lakes coastal wetlands within the United States, Vol. 1

: Overview. U.S. Fish and Wildlife Service, Washington, DC.

FWS/OBS- 81/02-v1.

Jaworski, E., Raphael, C.N., Mansfield, P.J., and Williamson, B.B. 1979.

Impact of Great Lakes water level fluctuations on coastal wetlands

. U.S. Department of Interior, Office of Water Resources and Technology,

Contract Report 14-0001-7163, from Institute of Water Research, Michigan State University, East Lansing,

MI, 351pp.

Keough J.R., Thompson, T.A., Guntenspergen, G.R., and Wilcox, D.A. 1999. Hydrogeomorphic factors and ecosystem responses in coastal wetlands of the Great Lakes.

Wetlands

19:821-834.

Lishawa, S.C., D.A. Albert, and N.C. Tuchman. 2010. Natural water level decline drives invasive species establishment and vegetation change in Great Lakes coastal wetlands.

Wetlands:

30(6) 1085-1097.

Minc, L.D. 1997.

Great Lakes coastal wetlands: An overview of abiotic factors affecting their distribution, form, and species composition

. Michigan Natural Features Inventory, Lansing, MI.

Minc, L.D., and Albert, D.A. 1998.

Great Lakes coastal wetlands: abiotic and floristic characterization

. Michigan

Natural Features Inventory, Lansing, MI.

Swink, F., and Wilhelm, G. 1994. Plants of the Chicago Region 4 th

Edition. Lisle, Illinois. The Indiana Academy of

Science.

United States and Canada. 1987. Great Lakes Water Quality Agreement of 1978, as amended by Protocol signed

November 18, 1987. Ottawa and Washington.

Wilcox, D.A., and Whillans, T.H. 1999. Techniques for restoration of disturbed coastal wetlands of the Great Lakes.

Wetlands

19:835-857.

List of Tables

Table 1

. Mean Conservatism Scores for the Great Lakes Coastal Wetlands Plant Communities in Meadow, and

Emergent zones, and the Total Marsh

Source: Central Michigan University and Oregon State University. Data were collected and interpreted from Table

3-4 written by Albert, D.A., March 2008. Great Lakes Coastal Wetlands Monitoring Plan, Chapter Three Vegetation

Community Indicators. Developed by the Great Lakes Coastal Wetlands Consortium, A project of the Great Lakes

Commission

Last Updated

State of the Great Lakes 2009

report.

An editor’s note was added for the 2011 reporting cycle.

The “Mixed” status term used in the 2009 report were replaced with the “Fair” status term to be consistent with definitions used for the 2011 reporting cycle.

162

Mean Conservatism Scores for the Great Lakes Coastal Wetlands Plant Communities

LAKE or REGIONAL MARSH TYPE MEADOW EMERGENT

ZONE ZONE

Lake Erie Open Embayments**

Lake Erie Sand-spit Embayments

Georgian Bay Protected Embayments*

Lake Huron (northern) protected Embayments

Lake Huron (northern) Open Embayments (Rich

Fens)

3.1 (4.6)

4.3 (4.5)

5.1 (6.5)

5.1

5.5

3.8 (5.3)

4.4 (6.1)

6.4 (7.2)

5.6

4.5

Lake Huron’s Saginaw Bay Open Embayment

Lake Huron Swale Complex (Barrier Enclosed)

Lake Michigan Drowned River Mouths

Lakes Michigan (northern) Open Embayments

(Rich Fens)

3.2

-

4.0

5.5

4.5

-

4.9

4.5

Lake Michigan (northern) Protected Embayments

Lake Michigan Swale Complex (Barrier Enclosed)

Lake Ontario Barrier Beach Lagoons

Lake Ontario Drowned River Mouths

Lake Ontario Protected Embayments*

Lake St. Clair Open Embayments**

Lake Superior Barrier Beach Lagoons & Riverine

Wetlands

Lake Superior Swale Complex (Barrier Enclosed)

St. Clair River Delta

St. Lawrence River Drowned River Mouths

St. Marys River Connecting Channel

5.1

-

5.0

4.2

4.7 (6.4)

3.1

6.3

-

4.2

4.4

5.1

5.6

-

5.7

4.3

3.9 (5.8)

3.8

6.7

-

5.5

5.5

5.6

TOTAL

MARSH

3.7 (5.3)

4.5 (4.8)

5.8 (6.8)

5.6

5.1

3.9

4.9 (6.4)

4.5

5.1

5.6

5.3 (6.3)

5.3

4.2

4.5 (6.3)

3.7

6.4

5.9 (6.9)

4.7

5.0

5.6

Table 1.

Mean Conservatism Scores for the Great Lakes Coastal Wetlands Plant Communities in Meadow, and

Emergent zones, and the Total Marsh

* For Lake Ontario and Georgian Bay protected wetlands the mean scores for each zone are based on the score of several wetlands rather on a mean coverage value for all of the marshes studies. The maximum score of a single wetland for each zone is shown in parenthesis when the data is available ( ).

**For Lake Erie, mean C scores from historic data collected in high quality wetland at Perry's Victory Monument

(Stuckey 1975) is show in brackets [ ].

Source: Central Michigan University and Oregon State University. Data were collected and interpreted from Table

3-4 written by Albert, D.A., March 2008. Great Lakes Coastal Wetlands Monitoring Plan, Chapter Three Vegetation

Community Indicators. Developed by the Great Lakes Coastal Wetlands Consortium, A project of the Great Lakes

Commission

163

Conserving and Protecting Forest Lands

Overall Assessment

Trend: Undetermined

Rationale: Previously, SOLEC reported province-wide and state-wide on forest certifications only and tracked an increasing trend in forest certifications. On further consideration it was concluded that the forest certification measure did not fully capture the intent of the indicator. The increasing trend in certifications did not necessarily reflect any increase in well managed forests since the certification programs were new and the trend reflected start-up. Furthermore the lack of specificity to the basin geography was problematic. This report establishes baseline Great

Lakes basin specific data for future trend reporting; as such the current trend could not be stated.

However, anecdotally the relatively mature sustainable forest management infrastructure in

Canada and the United States suggests that publicly owned forests would be managed sustainably as a matter of course, and that the opportunity for variation in management quality lies primarily with privately held forests.

Lake-by-Lake Assessment

Note:

Lake-by-Lake assessment is not possible at this time. Some data is spatial at this time and some is available at county resolution, but considerable information must still be estimated proportionally from statebased summaries. Further extrapolation to lake basins was not attempted.

Other Spatial Scales: State-by-State

Illinois: Lake Michigan

Trend: Undetermined

Rationale: The very limited extent of the Lake Michigan basin (25,782 ha) in Illinois is dominated by urban development, being Chicago and surrounds, with considerable hardened surfaces. The state’s basin has six per cent (1,522 ha) forest cover in what would be considered forest stands. These residual forests appear to be entirely under local government jurisdiction as park and natural areas protected spaces. It is notable that most residential urban neighborhoods are mature and exhibit considerable forest cover that on visual inspection often exceeds 25%.

Indiana: Lake Michigan and Lake Erie

Trend: Undetermined

Rationale: A number of significant urbanized areas are located in the Indiana basins of both Lake Michigan (East

Chicago, Gary, Michigan City) and Lake Erie (Fort Wayne); however, urbanization does not dominate the landscape patterns overall. Tree cover is significant in the Lake Michigan basin portion. In the Lake

Erie basin the agricultural land base dominates but has dispersed forest cover both as a component of the farms but also as protected spaces in and outside urban areas. No certified forests are identified in the Indiana Great Lakes basin but due to various agencies attached to protected spaces there is some uncertainty here as these lands were not quantified but would qualify as managed forests for indicator purposes. Identified managed forests include ATFS certified holdings (4,923 ha) being six per cent of the identified forest area in the landscape and an estimate extrapolated to the Great Lakes basin from

2008 county specific data for the tax incentive managed forests (13,750 ha) (Indiana Classified Forest and Wildlands program which provides an option to join the Indiana Classified Forest Certified Group which provides certification through the American Tree Farm System).

Michigan: Lake Superior, Lake Michigan, Lake Huron, and Lake Erie

Trend: Undetermined

164

Rationale: Significant certified forest lands were identified being 45 per cent (2.5 million ha) of the identified forested area in the Michigan Great Lakes basin (5.5 million ha). The managed forests may be larger but the actual enrollment of lands in the tax incentive forests category was not determined and may increase the area under management were it determined and included in the sum. Thirty seven per cent (5.5 million ha) of the basin is forest area.

Minnesota: Lake Superior

Trend: Undetermined

Rationale: The Lake Superior basin in Minnesota has 53 per cent (840,253 ha) forest cover. A total of 45 per cent

(376,404 ha) of the forest area was identified as well managed for the purposes of the indicator.

New York: Lake Erie, Lake Ontario

Trend: Undetermined

Rationale: New York State has 48 per cent (2,500,783 ha) of the Great Lakes basin in forest cover. Three per cent of the basin was identified as well managed forests.

Ohio: Lake Erie

Trend: Undetermined

Rationale: The Ohio Great Lakes basin is 14 per cent (433,626 ha) forest cover and 9 per cent (41,086 ha) of this was identified as well managed forest.

Ontario: Lake Superior, Lake Huron, Lake Erie, Lake Ontario

Trend: Undetermined

Rationale: In the Great Lakes basin 66 per cent (almost 15 million ha) is forest cover. The identified managed forest is 78% (11.5 million ha) of the forest area. The westerly half of the Lake Ontario basin in Ontario is heavily agricultural and/or urban with very little forest cover.

Pennsylvania: Lake Erie

Trend: Undetermined

Rationale: Only one per cent (931 ha) of the 46 per cent (71,034 ha) of the Great Lakes basin which is forest cover was identified as well managed. This is likely an underestimate as the forest tax law program (Clean and

Green Program) land area was not ascertained.

Wisconsin: Lake Superior, Lake Michigan

Trend: Undetermined

Rationale: While 95 per cent (1.5 million ha) of the forest cover in the Wisconsin Great Lakes basin was identified as well managed, the forest cover is highly concentrated in the north of Wisconsin. The southern three quarters of the Wisconsin Lake Erie basin is heavily agricultural with very limited forest cover.

Purpose

Forest management objectives relating to water resources are to minimize downstream water yield

• fluctuations, water quality degradation, and the harmful alteration, disruption, or destruction of fish habitat.

To assess proportion of forests and forest management activities that meet best management practices, as

• reflected by a sustainable forest management third-party certification or other relevant legislation determining forest management standards, to protect water-related resources (using Criterion 4.3.a of the

Montreal Process).

Third-party certifications as those endorsed by the Programme for the Certification of Forest Certification schemes (PEFC) such as the Sustainable Forestry Initiative (SFI), the Canadian Standards Association

(CSA), the Forest Stewardship Council (FSC), and the American Tree Farm System (ATFS).

165

Relevant legislation specifies signing and approval of forest management plans by competent forest managers, normally registered professionals, and under such programs as provincial and state tax incentive enrollment programs (e.g. Wisconsin Managed Forest Law) and uncertified but official forest management plans (e.g. Ontario Forest Management Plans).

The Conserving and Protecting Forest Lands indicator is used in the Great Lakes indicator suite as a

Response indicator in the Restoration and Protection top level reporting category.

Ecosystem Objective

To minimize effects of forest management practices on water quality (GLWQA Annex 2).

Forest management objectives relating to water resources are to minimize downstream water yield fluctuations, water quality degradation, and the harmful alteration, disruption, or destruction of fish habitat. Sustainable forest management practices include standards (roads, water crossings, soil protection, vegetative cover) implemented during harvesting operations by the forest industry that maintain the quantity and quality of water within, and flowing from, forested ecosystems. The primary focus for water conservation centers on producing potable water for human and wildlife use, and suitable aquatic environments for fish, plants and other animals.

The indicator considers change in forest lands certified by programs endorsed by the Programme for the

Certification of Forest Certification schemes (PEFC). The relevant programs in North America include the

Sustainable Forestry Initiative (SFI), the Canadian Standards Association (CSA), the Forest Stewardship Council

(FSC), and the American Tree Farm System (ATFS). The indicator also considers forest lands managed under a plan accepted by credible government authorities as being sustainable forest management. These plans include forest management plans signed by registered professionals in such programs as provincial and state tax incentive enrollment programs (e.g. Wisconsin Managed Forest Law) and sustainable forest management plans (e.g. Ontario

Forest Management Plans). These third-party certifications and professionally endorsed plans ensure forests are grown and harvested in ways that protect local ecosystems.

Linkages

Forests reduce concentrations of greenhouse gases in the atmosphere, minimize sedimentation in lakes and rivers, and protect against flooding, mudslides and erosion.

Management Challenges/Opportunities

Costs for certifications and their maintenance, plus land title encumbrances associated with government programs promoting private land forestry deter many land owners from participating in formal agreements but they may practice good management voluntarily.

Many private and public land parcels with forest cover of some type in the Great Lakes watersheds might never be considered well managed forest lands either due to limited size of the parcel or due to the main use being residential or protected (e.g. park land or a conservation designation, although some have been certified for instance as in

Wisconsin).

Comments from the author

The hypothesis that well managed forest lands is a suitable proxy measure of the degree of protection afforded water quality from the terrestrial watershed is tenable but still constitutes an assumption. Goodly portions of the basin are dominated by agricultural lands. Water quality in these agricultural lands is being managed with mitigation which would not qualify as well managed forest. While some mitigation techniques would employ tree cover in buffer strips these would not be captured in managed or certified forest area. Non-tree cover measures also mitigate the effects of agriculture and so one must be careful not to jump to conclusions but rather use the indications here to decide what further tests may be warranted before conclusions are drawn.

166

Assessing Data Quality

Data Characteristics

Strongly

Agree

Agree

Neutral or

Unknown

Disagree

Strongly

Disagree

Not

Applicable

1. Data are documented, validated, or quality-assured by a recognized agency or organization

2. Data are traceable to original sources

3. The source of the data is a known, reliable and respected generator of data

4. Geographic coverage and scale of data are appropriate to the Great Lakes basin

5. Data obtained from sources within the

U.S. are comparable to those from

Canada

6. Uncertainty and variability in the data are documented and within acceptable limits for this indicator report

Clarifying Notes:

X

X

X

X

X

X

Data for documenting water yield trends and timing, water quality, and the health of aquatic flora and fauna is not currently collected in association with individual forest management operations. Detailed, long-term local monitoring is also required to separate the effects of forest management from natural variation. A proxy indicator has therefore been used to monitor forest water resources.

Information is incomplete due to survey response rate variability.

Acknowledgments

Author:

William Dalton, Ontario MNR, [email protected]

Information Sources

Andrew Arends, Minnesota DNR, [email protected]

Quincey Blanchard, American Tree Farm System, [email protected]

Sloan Crawford, New York Bureau of Private Land Services, [email protected]

Dale Gormanson, USDA Forest Service, Northern Research Station, St. Paul, MN

Carl Hauser, Indiana DNR, [email protected]

Brenda Huter, Indiana DNR, [email protected]

Courtney Klaus, Wisconsin DNR, [email protected]

Greg Pawson, Ontario MNR, [email protected]

Justin Perry, New York Division of Lands and Forests, [email protected]

Paul Pingrey, Forest Stewardship Council, [email protected]

Cotton Randall, Ohio DNR, [email protected]

Julie Rosalez, Minnesota DOR, [email protected]

Robert Spence, Ontario MNR, [email protected]

Kenneth Symes, Wisconsin DNR, [email protected]

Chad R. Voorhees, Pennsylvania DCNR, [email protected]

Larry Watkins, Ontario MNR, [email protected]

List of Tables

Table 1

. Estimates of Great Lakes basin well managed forest area.

Last Updated

State of the Great Lakes 2011

167

Table 1 Estimates

1

of Great Lakes basin well managed forest

2

area.

State or

Province

Illinois

Indiana

Michigan

Minnesota

New York

Ohio

Ontario

Total area in GL basin

25,782

906,881

14,845,392

1,590,090

5,170,230

3,015,390

22,567,592

Forested area in the

GL basin

3

1,522

86,980

5,565,634

840,253

2,500,783

433,626

14,785,506

% of GL basin area forested

6%

10%

37%

53%

48%

14%

66%

American

Tree Farm

System

(ha)

0

4,923

334,355

0

23,709

9,066

0

Third

Party

Certifications

4

(ha) (CSA,

SFI, FSC)

0

0

2,149,987

338,185

36,459

2,091

8,297,605

Tax

Incentive

Program

Managed

Forests

(ha)

0

13,750

485,623

38,219

41,881

19,804

392,469

Not quantified

Other managed forest

(ha)

1,522

Not quantified

Not quantified

Not quantified

Not quantified

19,191

2,831,818

Not quantified

Estimate

5 of well managed forest (ha)

1,522

13,750

2,484,342

376,404

78,341

41,086

11,521,892

Forest identified as well managed

100%

16%

45%

45%

3%

9%

78%

Pennsylvania 155,341 71,034 46% 931 0 931 1%

Wisconsin 4,453,613 1,561,647 35% 288,537 858,997 403,212 342,352 1,489,886

1

Great Lakes basin specific data, GIS datasets, are rare at this time (Wisconsin), so data is largely extrapolated from county sums.

2

Well managed forest = forest area managed sustainably under a forest management plan, or equivalent mechanism, supervised by a competent authority.

3

Satellite thematic data forest and forested wetlands, Dale Gormanson, USDA Forest Service, Northern Research Station, St.

Paul, MN

4

Double counting avoided. Private certifications were included where geographic locale of the forest holding was identifiable to the Great Lakes basin. CSA - Canadian Standards Association; SFI - Sustainable Forestry Initiative, FSC - Forest Stewardship

Council

5

Sums derived to avoid double counting to the extent possible, row totals are therefore not necessarily the sum across the columns; for example, American Tree Farm System certifications are often also enrolled in a tax incentive programs, and so on

95%

168

Conserving Soil, Improving Water Quality and Enhancing Wildlife Habitat on

Agricultural Lands

Overall Assessment

Trend: Increasing

Rationale: The number of best management practices implemented on private agricultural lands aimed at conserving soil, improving water quality and enhancing wildlife habitat has increased from 2005 to present.

Lake-by-Lake Assessment

Lake Superior

Canadian Trend: Undetermined

Canadian Rationale: Small proportion of agricultural land in the Ontario portion of this lakeshed.

U.S. Trend: Increasing

U.S. Rationale: The area of land removed from previous agricultural production has increased. The area of agricultural land affected by best management practices aimed at conserving soil, improving water quality and enhancing wildlife habitat has increased.

Lake Michigan

Canadian Trend: Not Applicable

Canadian Rationale: Lake Michigan entirely within U.S. boundary.

U.S. Trend: Increasing

U.S. Rationale: The area of land removed from previous agricultural production has increased. The area of agricultural land affected by best management practices aimed at conserving soil, improving water quality and enhancing wildlife habitat has increased.

Lake Huron

Canadian Trend: Increasing (for part of lakeshed assessed)

Canadian Rationale: The number of best management practices aimed at conserving soil, improving water quality and enhancing wildlife habitat has increased.

U.S. Trend: Increasing

U.S. Rationale: The area of land removed from previous agricultural production has increased. The area of agricultural land affected by best management practices aimed at conserving soil, improving water quality and enhancing wildlife habitat has increased.

Lake Erie

Canadian Trend: Increasing

Canadian Rationale: The number of best management practices aimed at conserving soil, improving water quality and enhancing wildlife habitat has increased

U.S. Trend: Increasing

U.S. Rationale: The area of land removed from previous agricultural production has increased. The area of agricultural land affected by best management practices aimed at conserving soil, improving water quality and enhancing wildlife habitat has increased.

169

Lake Ontario

Canadian Trend: Increasing

Canadian Rationale: The number of best management practices aimed at conserving soil, improving water quality and enhancing wildlife habitat has increased

U.S. Trend: Increasing

U.S. Rationale: The area of land removed from previous agricultural production has increased. The area of agricultural land affected by best management practices aimed at conserving soil, improving water quality and enhancing wildlife habitat has increased.

Other Spatial Scales

Lower Fox River Watershed (U.S.)

Trend: Increasing

Rationale: The area of land removed from previous agricultural production has increased. The area of agricultural land affected by best management practices aimed at conserving soil, improving water quality and enhancing wildlife habitat has increased.

Saginaw River Watershed (U.S.)

Trend: Increasing

Rationale: The area of land removed from previous agricultural production has increased. The area of agricultural land affected by best management practices aimed at conserving soil, improving water quality and enhancing wildlife habitat has increased.

Maumee River Watershed (U.S.)

Trend: Increasing

Rationale: The area of land removed from previous agricultural production has increased. The area of agricultural land affected by best management practices aimed at conserving soil, improving water quality and enhancing wildlife habitat has increased.

Purpose

To quantify the number of field-scale best management practices (BMPs), both structural and practice/technology, implemented and assumed maintained on private agricultural land in Great Lakes

• basin portions of Canada and the United States

To determine progress towards the general goals of reducing on- and off-site impacts of agricultural production on water quality and quantity, soil quality and wildlife habitat/populations.

The Conserving Soil, Improving Water Quality and Enhancing Wildlife Habitat on Agricultural Lands indicator is used in the Great Lakes indicator suite as a response indicator in the Restoration and Protection top level reporting category.

Ecosystem Objective

This indicator supports Annexes 2, 3, 12 and 13 of the GLWQA.

Ecological Condition

Measure

The most readily accessible and reliable source of data for this type of indicator at this scale is the databases used to track the number of best management practices (BMPs) financially supported by U.S. and Canadian federal agrienvironmental cost-share and incentive programs.

170

Adoption of practices in the U.S. is quantified by participation in Farm Bill programs including:

• the Conservation Reserve Program (CRP),

Conservation Reserve Enhancement Program (CREP),

Wildlife Habitat Incentives Program (WHIP),

Conservation Stewardship Program (CSP), and,

Environmental Quality Incentives Program (EQIP).

This participation is documented by the Farm Service Agency (FSA) database and the Natural Resources

Conservation Service (NRCS) Protracts database.

Adoption of practices in Ontario, Canada is documented by participation in:

Federal/Provincial Canada Ontario Farm Stewardship Program (COFSP: 2005-2011),

Greencover Canada (GC: 2005-2009 only, Ontario only) and,

Canada-Ontario Water Supply Expansion Program (COWSEP: 2005-2009 only).

Databases for these agri-environmental programs do not include practices that may have been solely supported by state/provincial or local programs or implemented by agricultural producers without federal government financial support. Thus, they are a conservative estimate of the agricultural sector’s response to conserving soil, improving water quality/quantity and enhancing wildlife habitat.

The practices tabulated include both structural and practice/technology activities. Examples of structural activities include:

• establishment of permanent vegetative filter strips at field edges to reduce non-point source pollutant movement to surface water;

• construction of manure storages so that nutrients can be applied at the most appropriate times of the year and to prevent runoff from manure piles;

• construction of retention ponds to trap runoff from confined animal feeding operations; diversion of clean water around agricultural facilities; fencing livestock out of riparian areas; erosion control structures; nutrient recovery and water treatment technologies; and complete retirement of fields and marginal land from agricultural production by tree planting and natural vegetative succession.

Examples of practice/technology activities include:

• practicing integrated pest management(IPM) so that pesticides are used judiciously;

• practicing nutrient management (NM) to match nutrient application with crop needs using optimal timing, rates and methods of nutrient application to increase plant utilization and avoid field losses from runoff or leaching;

• using precision farming tools to maintain specified distances from streams and wells, and minimize overlap of applications of pesticides and nutrients;

• irrigation scheduling; field wind strips; and cover crops.

For the indicator, the number of selected practices funded are tabulated for fiscal years since April 1, 2005 in

Ontario and October 1, 2004 in the United States. The number of practices is normalized by the number of hectares of agricultural land for each spatial unit as determined by the Canada 2006 Census of Agriculture or United States

171

2006 National Land Cover Data (NLCD).

Overall Assessment - Canada

In Ontario, the number of BMPs funded and implemented per hectare of agricultural land has been cumulatively increasing since 2005. The Environmental Farm Plan Program directs farmers to priority actions on their farms through a process of education and risk assessment. Associated cost-share funding helps to accelerate their adoption of these practices or actions. Over the past 6 years, funding has accelerated the implementation of almost 19,000 best management practices by producers in Ontario (Figure1). The rate of increase has slowed as agrienvironmental program funding available for cost share has decreased since 2008. The distribution by county

(Figure 2) shows the areas of the province which have had the most BMPs per 1000 ha of agricultural land cumulatively adopted. Southwestern Ontario, with the greatest proportion of cropland and livestock production in the province, has generally had the greatest intensity of funding and adoption of BMPs.

A spatial analysis of the adoption of nutrient management related BMPs over the period 2005-2010 was also conducted. From the overall number of BMPs supported, a subset of 33 practices for both livestock and crop production nutrient management were selected. The crop spatial analysis compared the number of crop nutrient management BMPs adopted to the area receiving commercial fertilizer inputs on a county basis (Figure 3). This relationship is highly significant with 87% of the variation in adoption being explained. The livestock spatial analysis compared the number of livestock nutrient management BMPs adopted with the amount of nutrients produced in manure on a county basis. Figure 4 illustrates the BMP adoption relationship with phosphorus produced from manure; 92% of the variation in adoption is explained by total manure P generated in each county.

The breakpoints used for mapping high, medium and low categories are included in the captions for each figure.

Both analyses show there is a higher adoption of nutrient management BMPs in Ontario where there is an increased risk of excess nutrients.

Overall Assessment - United States

The number of active contracts between the USDA Farm Service Agency and private landowners that remove land from agricultural production increased from 34,662 in 2005 to 44, 965 in 2010. This increase in contracts translates into an increase in area from 189,153 hectares (468,202 acres) to 239, 128 hectares (591,903 acres). This increase represents 2.1% of agricultural land use based on 2006 National Land Cover Data (NLCD) representing both cultivated cropland and hayland/pasture land.

The cumulative number of applied best management practices on privately owned agricultural land and cost shared by the USDA Natural Resources Conservation Service (NRCS) implemented under the Environmental Quality

Incentive Program, Conservation Stewardship Program, or Wildlife Habitat Incentives Program increased from

4,131 to 14,173. It is important to note that these numbers assume a BMP applied using NRCS cost-share monies from 2005-2010 are assumed to be present and maintained for the expected lifespan of the respective BMP as well as in 2010 following termination of any NRCS contracts made during the period of interest (2005-2010). While some contracts may be active as of 2010, earlier contracts made between NRCS and a landowner (e.g., 2005-2007) may have expired.

This increase in best management practices translated into an increase in cumulative area of agricultural land treated from 7,496,810 hectares (18,556,459 acres) to 10,943,513 hectares (27,087,902 acres). It is important to note that differences in NRCS program goals, implementation, and tracking may affect these calculated areas of land affected.

While programs like EQIP and WHIP are focused on particular BMPs implemented in specific areas of an agricultural operation, CSP provides annual payments for operation-level environmental benefits. Therefore, acreage accounted for by EQIP/WHIP may be characterized as practice-level where CSP acreage may be characterized as operation-level. When viewed relative to area of agricultural land (2006 NLCD) and USGS 8-digit

HUCs, cumulative implementation of NRCS practices from 2005 to 2010 ranges from 0 to 58 practices/1000

172

hectares (Figure 5). The largest implementation relative to agricultural land (58) occurs along the north shore of

Lake Superior. However, closer inspection of this area indicates the smallest total area of agricultural land (243 ha) and only 14 implemented practices.

A closer inspection of watersheds dominated by agricultural land use (cultivated crops and hayland/pastureland) indicated central and southern portions of the U.S. side of the basin have the greatest potential for implementation of agricultural best management practices (Figure 6). Some of these watersheds include the Lower Fox River

(Wisconsin), Saginaw Bay watersheds (Michigan), and Western Lake Erie watersheds (Michigan, Ohio, and

Indiana).

Lakeshed Analysis - Ontario, Canada

In the Canada Ontario Farm Stewardship Program (COFSP) database, practices are located in a county and a

Conservation Authority (CA). Figure 7 illustrates the watersheds selected that were comparable to CA designations in the COFSP database and used to calculate the indicator on a lakeshed basis in Canada. To estimate practices adopted on a watershed basis, the area of agricultural land in a fundamental drainage area (as defined by Atlas of

Canada) is interpolated from the 2006 Census of Agriculture information using an area-weighted approach. Thus error is introduced into the indicator when calculated on a watershed basis. This representation is also limited because not all lake basins have full CA coverage in Ontario so only Lakes Ontario, Erie and part of Huron are analyzed. Practices that are outside these boundaries are excluded from the lakeshed analysis (2434 practices or 13% of total for 6 years).

The number of BMPs implemented are cumulatively increasing in all lakesheds (Table 2). In Ontario, the Lake Erie basin has the greatest number of BMPs cost-shared per ha of agricultural land. The portion of the Lake Huron basin included for this indicator is next, followed by Lake Ontario. The acceleration of BMP adoption per ha of agricultural land is slowing similarly in all lakesheds as program funding has been reduced.

A categorization of practices by major effect was performed to aid in interpretation of trends by lakeshed.

Categorization attempts to identify a major agri-environmental effect of a practice, however multiple benefits from application of a practice could occur. There has been no double counting of practices between categories, so some categories may be under-represented. Figure 8 illustrates that the type of the BMPs adopted can vary in each lakeshed. BMPs having a nutrient management effect are the highest proportion adopted in all lakesheds. Practices in the “Other” category cannot be simply classified in the water, nutrient management, habitat or soil categories.

Examples of Other practices that were commonly adopted include berms for secondary containment around permanent on-farm storages for agricultural products, and equipment modifications, such as rate controllers, foam marker systems and air induction tips, to improve pesticide management.

Lakeshed Analysis - United States

On the U.S. side of the basin, area of agricultural land removed from production due to the Conservation Reserve

Program (CRP) and Conservation Reserve Enhancement Program (CREP) currently ranges from 1,063 to 353,052 acres for lake basins (Figure 9a). Trends in agricultural land retired from production indicates the percent of land retired has increased to greater than 3% in Lake Erie basin, whereas all other lake basins are relatively steady or have decreased from their 2005 levels (Figure 9b). An exception is Lake Huron where percent of agricultural land retired from production peaked in 2007, followed by a decrease to about 2.5% (Figure 9b).

One hundred and six (106) different NRCS practices were reported to be applied in the Great Lakes Basin from

2005 to 2010 and represent a range of environmental concerns addressed on individual farms. A categorization of selected NRCS practices, performed to aid interpretation of trends, indicated varying application of practices on cropland, hayland/pastureland, and both land uses combined referred to as ag land (Figure 10). While this categorization attempts to identify a major environmental concern associated with agricultural operations, multiple benefits from application of these practices are expected. However, no double counting of practices between

173

categories occurred. Approximately 6% to 13% of croplands in lake basins now adopt practices that reduce tillage/soil erosion (Figure 10a). Lake Erie and Ontario employ practices to reduce the impact of land managed for hay production and grazing on greater than 7% of that land use type (Figure 10b). Nutrient management practices

(Figure 10c) that increase efficiencies of applied agrochemicals/nutrients while decreasing off-site losses are the most applied practices in many lake basins. Less than one percent of agricultural land in all lake basins is accounted for by practices implemented to intercept/redirect surface runoff and improve water quality of neighboring water bodies (Figure 10d) or improve habitat for wildlife (Figure 10e).

Other Spatial Scales

Closer examination of U.S. watersheds with a higher proportion of agricultural land use indicate variable distribution of cropland, pasture/hayland, and resulting implementation of NRCS practices. In Western Lake Erie watersheds, cropland is concentrated in the central portion of this watershed (Figure 11a), whereas pasture/hayland is concentrated in the northern portion (Figure 11b). Number of NRCS practices relative to agricultural land is distributed relatively evenly throughout these watersheds, both in central and northern areas (Figure 11c).

Identification of NRCS practices which are likely to have the largest effect on reducing phosphorus losses from agricultural operations show largest implementation densities in northern portions of this watershed. Similar patterns in cropland and pasture/hayland distribution were present in the Saginaw Bay and Lower Fox River watersheds, showing concentrations of the land uses and associated operations differing in location (Figure 12a, 12b,

13a, and 13b). NRCS practices were also distributed throughout these watersheds and no apparent spatial pattern was evident based on land use data alone (Figure 12c, 12d, 13c, and 13d).

Linkages

This indicator is linked to the following Great Lakes indicators: nutrients in tributaries, pesticides in tributaries, watershed stressor index, land cover, nutrients in lakes, Cladophora, inland water quality index, bacterial loadings from tributaries, groundwater quality, beach postings, baseflow due to groundwater, sediment coastal nourishment, forest cover.

Management Challenges/Opportunities

The indicator quantifies adoption of BMPs by agricultural producers who participate in federally funded/tracked cost-shared incentive programs. The indicator is affected by government budget constraints, market forces, industry and consumer expectations and other socio-economic factors which affect the adoption of BMPs. The indicator is not expected to necessarily respond or reflect directly the state of environment due to: the temporal lag between

BMP implementation and environmental effect; the influence of the spatial distribution of BMP uptake on environmental conditions; and, unmanageable factors such as aquatic invasive species and climate change. In addition, cumulative thresholds of BMP uptake might be needed before a causal effect between BMP uptake and change in environmental conditions can be measured. There is currently no standard way of measuring the condition or maintenance of these BMPs over their expected lifespan.

Comments from the author(s)

Programs differ between Ontario, Canada and the U.S. and thus do not necessarily have common definitions of agricultural best management practices or levels of funding. As the programs and jurisdictional context change

(legislation, budget, and policies) over time, different agricultural practices have been emphasized, added or removed to these programs which may influence the number of BMPs funded and implemented in any one year.

Based on eligibility criteria and funding available the number and rate of BMPs adopted can vary greatly between the two countries and in time.

Some practices may contribute to more than one outcome, or may even be somewhat antagonistic to each other. No attempt has been made in this analysis to rank or calculate net benefits or tabulate outcomes (i.e. soil quality vs. water quality vs. habitat) separately of different practices. Funding of management plans for such things as grazing, pesticide, irrigation, erosion and nutrient use are included as practices as they are assumed to be implemented.

174

Assessing Data Quality

Data Characteristics

Strongly

Agree

Agree

Neutral or

Unknown

Disagree

Strongly

Disagree

Not

Applicable

1. Data are documented, validated, or qualityassured by a recognized agency or organization

2. Data are traceable to original sources

3. The source of the data is a known, reliable and respected generator of data

4. Geographic coverage and scale of data are appropriate to the Great Lakes basin

5. Data obtained from sources within the U.S. are comparable to those from Canada

6. Uncertainty and variability in the data are documented and within acceptable limits for this indicator report

X

X

X

X

X

X

Clarifying Notes: The data source for each country is similar but the number/variety of BMPs funded and the information collected when a BMP is implemented (e.g. hectares treated) is not similar for the separate programs in each country. Because all selected practices funded are included in the tabulation there is no statistical sampling from which to calculate uncertainty or variability.

Acknowledgments

Authors:

Pamela Joosse, Ph.D. – Agriculture and Agri-Food Canada - [email protected]

T. Kevin O’Donnell, Ph.D. – USEPA-Great Lakes National Program Office - [email protected]

Peter Roberts – Ontario Ministry of Agriculture, Food and Rural Affairs - [email protected]

Elisabeth Woyzbun – Agriculture and Agri-Food Canada - [email protected]

Information Sources

Agriculture and Agri-Food Canada and Statistics Canada,

Customized tabulations, Census of Agriculture CGC Base 1996, 2001, 2006, Census of Agriculture Regular

Base 1971, 1976, 1981, 1986, 1991

Department of Natural Resources Canada. All rights reserved.

North American Atlas – Waterbody

Atlas of Canada 1:1,000,000 National Frameworks Data, Hydrology – Fundamental Drainage Area

Atlas of Canada – Provincial Boundaries – 1:2,000,000

Canada-Ontario Farm Stewardship Program Database provided by the Ontario Soil and Crop Improvement

Association

USGS 2006 National Land Cover Dataset

USDS NRCS Protract Database (Data as of 7-11-11)

USDA FSA CRP/CREP Database (Data as of 7-13-11)

List of Tables

Table 1

. Total BMPs adopted by Lakeshed per 1000 hectares of farmland by Funding Period.

List of Figures

Figure 1.

Cumulative adoption of BMPs in Ontario (from 2005 to 2011)

Source: Canada-Ontario Farm Stewardship Program Database provided by the Ontario Soil and Crop Improvement

Association

Figure 2

. Distribution of BMPs per 1000 hectares of agricultural land cumulatively adopted by county in Ontario

(2005-2011)

175

Source: Canada-Ontario Farm Stewardship Program Database provided by the Ontario Soil and Crop Improvement

Association; Agriculture and Agri-Food Canada and Statistics Canada, Customized tabulations, Census of

Agriculture CGC Base 1996, 2001, 2006, Census of Agriculture Regular Base 1971, 1976, 1981, 1986, 1991; Atlas of Canada – Provincial Boundaries – 1:2,000,000

Figure 3

. Comparison of number of crop nutrient management related BMPs adopted during COFSP (April 2005-

March 2010) and the area receiving commercial fertilizer inputs in 2005 by municipality

Source: Canada-Ontario Farm Stewardship Program Database provided by the Ontario Soil and Crop Improvement

Association; Agriculture and Agri-Food Canada and Statistics Canada, Customized tabulations, Census of

Agriculture CGC Base 1996, 2001, 2006, Census of Agriculture Regular Base 1971, 1976, 1981, 1986, 1991; Atlas of Canada – Provincial Boundaries – 1:2,000,000

Figure 4

. Comparison of number of livestock nutrient management related BMPs adopted during COFSP (April

2005-March 2010) and phosphorus produced from manure in 2006 per hectare of farmland by municipality

Source: Canada-Ontario Farm Stewardship Program Database provided by the Ontario Soil and Crop Improvement

Association; Agriculture and Agri-Food Canada and Statistics Canada, Customized tabulations, Census of

Agriculture CGC Base 1996, 2001, 2006, Census of Agriculture Regular Base 1971, 1976, 1981, 1986, 1991; Atlas of Canada – Provincial Boundaries – 1:2,000,000

Figure 5

. Number of USDA NRCS practices implemented in USGS 8-digit HUC watersheds per 1000 hectares of agricultural land.

Source: USGS 2006 National Land Cover Dataset & USDA Protracts Database

Figure 6

. Percent area of USGS 8-digit HUC watersheds in agricultural land use including cultivated cropland and pasture/hayland.

Source: USGS 2006 National Land Cover Dataset

Figure 7

. Agricultural Lakesheds of Ontario

Source: Atlas of Canada – Provincial Boundaries – 1:2,000,000; Atlas of Canada 1:1,000,000 National Frameworks

Data, Hydrology – Fundamental Drainage Area; North American Atlas – Waterbody.

Figure 8

. Proportion of cumulative adoption of BMPs by major effect by lakeshed in Ontario.

Source: Source: Canada-Ontario Farm Stewardship Program Database provided by the Ontario Soil and Crop

Improvement Association.

Figure 9

. Trends in USDA Conservation CRP and CREP contracts and percent of agricultural land in retirement.

Source: USGS 2006 National Land Cover Dataset & USDA FSA CRP/CREP Database

Figure 10

. Trends in grouped NRCS EQIP, CSP, and WHIP practices implemented per unit of area. Practices grouped by tillage/erosion reduction (a), pasture/grazing management (b), nutrient management (c), water quality improvement through interception of surface runoff (d), and habitat improvements for wildlife (e)

Source: USGS 2006 National Land Cover Dataset & USDA Protracts Database

Figure 11

. Western Lake Erie 12-digit HUC watersheds represent percent cropland (a), percent pasture/hayland (b), number of NRCS practices per area of agricultural land (c) and number of NRCS practices identified has high impact on phosphorus.

Source: USGS 2006 National Land Cover Dataset & USDA Protracts Database

Figure 12

. Saginaw Bay 12-digit HUC watersheds represent percent cropland (a), percent pasture/hayland (b), number of NRCS practices per area of agricultural land (c) and number of NRCS practices identified has high impact on phosphorus.

Source: USGS 2006 National Land Cover Dataset & USDA Protracts Database

Figure 13

. Lower Fox River 12-digit HUC watersheds represent percent cropland (a), percent pasture/hayland (b), number of NRCS practices per area of agricultural land (c) and number of NRCS practices identified has high impact on phosphorus.

Source: USGS 2006 National Land Cover Dataset & USDA Protracts Database

176

Last Updated

State of the Lakes 2011 report

Total BMPs adopted by Lakeshed per 1000 hectare of farmland by Funding Period

Lakeshed 2005-2008* 2008-2009 2009-2010 2010-2011

All Funding Years

2005-2011

Lake Erie

Lake Huron

3.15

2.64

0.69

0.67

0.36

0.40

0.33

0.33

4.52

4.04

Lake Ontario 2.24 0.55 0.34 0.30 3.42

* The first column for 2005-2008 represents 3 years cumulative adoption of practices as the COFSP database has combined these program years .

Table 1

. Total BMPs adopted by Lakeshed per 1000 hectares of farmland by Funding Period in Ontario

Figure 1.

Cumulative adoption of BMPs in Ontario (from 2005 to 2011)

Source: Canada-Ontario Farm Stewardship Program Database provided by the Ontario Soil and Crop Improvement

Association

177

Figure 2

. Distribution of BMPs per 1000 hectares of agricultural land cumulatively adopted by county (2005-2011)

Source: Canada-Ontario Farm Stewardship Program Database provided by the Ontario Soil and Crop Improvement

Association; Agriculture and Agri-Food Canada and Statistics Canada, Customized tabulations, Census of

Agriculture CGC Base 1996, 2001, 2006, Census of Agriculture Regular Base 1971, 1976, 1981, 1986, 1991; Atlas of Canada – Provincial Boundaries – 1:2,000,000; North American Atlas – Waterbody

178

Number of Crop Nutrient Management Related BMPs

High >95

Medium 31-95

Low 0-30

Amount of Land receiving fertilizer (ha)

High >65,000

Medium 30,000-65,000

Low 0-30,000

Figure 3

. Comparison of number of crop nutrient management related BMPs adopted during COFSP (April 2005-

March 2010) and the area receiving commercial fertilizer inputs in 2005 by municipality

Source: Canada-Ontario Farm Stewardship Program Database provided by the Ontario Soil and Crop Improvement

Association; Agriculture and Agri-Food Canada and Statistics Canada, Customized tabulations, Census of

Agriculture CGC Base 1996, 2001, 2006, Census of Agriculture Regular Base 1971, 1976, 1981, 1986, 1991; Atlas of Canada – Provincial Boundaries – 1:2,000,000

179

Number of Livestock Nutrient Management Related BMPs

High >200

Medium 46-200

Low 0-45

Amount of Phosphorus Produced from Manure (kg P/ha)

High >11

Medium 6-11

Low 0-5

Figure 4

. Comparison of number of livestock nutrient management related BMPs adopted during COFSP (April

2005-March 2010) and phosphorus produced from manure in 2006 per hectare of farmland by municipality

Source: Canada-Ontario Farm Stewardship Program Database provided by the Ontario Soil and Crop Improvement

Association; Agriculture and Agri-Food Canada and Statistics Canada, Customized tabulations, Census of

Agriculture CGC Base 1996, 2001, 2006, Census of Agriculture Regular Base 1971, 1976, 1981, 1986, 1991; Atlas of Canada – Provincial Boundaries – 1:2,000,000; North American Atlas – Waterbody

180

Figure 5

. Number of USDA NRCS practices implemented in USGS 8-digit HUC watersheds per 1000 hectares of agricultural land.

Source: USGS 2006 National Land Cover Dataset & USDA Protracts Database

Figure 6

. Percent area of USGS 8-digit HUC watersheds in agricultural land use including cultivated cropland and pasture/hayland.

Source: USGS 2006 National Land Cover Dataset

181

Figure 7

.

Agricultural Lakesheds of Ontario

Source: Atlas of Canada – Provincial Boundaries – 1:2,000,000; Atlas of Canada 1:1,000,000 National Frameworks

Data, Hydrology – Fundamental Drainage Area; North American Atlas – Waterbody

182

nutrient management soil water habitat other

100%

90%

80%

70%

60%

50%

40%

30%

20%

10%

18%

6%

14%

18%

44%

14%

6%

13%

16%

50%

32%

5%

15%

10%

38%

0%

Lake Erie Lake Huron Lake Ontario

Figure 8

.

Proportion of cumulative adoption of BMPs by major effect (nutrient management, soil conservation, water quality protection, habitat enhancement or other) by lakeshed

Source: Canada-Ontario Farm Stewardship Program Database provided by the Ontario Soil and Crop Improvement

Association.

Figure 9

. Trends in USDA Conservation CRP and CREP contracts and percent of agricultural land in retirement.

Source: USGS 2006 National Land Cover Dataset & USDA FSA CRP/CREP Database

183

Figure 10

. Trends in grouped NRCS EQIP, CSP, and WHIP practices implemented per unit of area. Practices grouped by tillage/erosion reduction (a), pasture/grazing management (b), nutrient management (c), water quality improvement through interception of surface runoff (d), and improvements for wildlife habitat (e)

Source: USGS 2006 National Land Cover Dataset & USDA Protracts Database

184

Figure 11

. Western Lake Erie 12-digit HUC watersheds represent percent cropland (a), percent pasture/hayland (b), number of NRCS practices per area of agricultural land (c) and number of NRCS practices identified has high impact on phosphorus.

Source: USGS 2006 National Land Cover Dataset & USDA Protracts Database

185

Figure 12

. Saginaw Bay 12-digit HUC watersheds represent percent cropland (a), percent pasture/hayland (b), number of NRCS practices per area of agricultural land (c) and number of NRCS practices identified has high impact on phosphorus.

Source: USGS 2006 National Land Cover Dataset & USDA Protracts Database

186

Figure 13

. Lower Fox River 12-digit HUC watersheds represent percent cropland (a), percent pasture/hayland (b), number of NRCS practices per area of agricultural land (c) and number of NRCS practices identified has high impact on phosphorus.

Source: USGS 2006 National Land Cover Dataset & USDA Protracts Database

187

Contaminants in Waterbirds

Overall Assessment

Status: Good

Trend: Improving

Rationale: The long term trends (1974 to present) of virtually all legacy contaminants are declining. The short term trends, those over the last decade, are a mixture of some showing significant declines but others showing no significant change.

Lake-by-Lake Assessment

Lake Superior

Status: Good

Trend: Improving.

Rationale: The traditional legacy contaminants, DDE, SUM PCBs and TCDD, have declined significantly in long term (1974-2009) and short term (2000-2009). Hg has declined significantly in the long term but neither it, nor SUM BDE, has declined significantly in the short term. Refer to Figure 2 for more detail on the long- and short-term trends by compound and water body.

Lake Michigan

Status: Good

Trend: Improving.

Rationale: The traditional legacy contaminants, DDE, SUM PCBs and TCDD, have declined significantly both since the 1970s (1974-2009) and in the last decade (2000-2009). Hg has declined significantly in the long term but neither it, nor SUM BDE, has declined significantly in the short term.

Lake Huron

Status: Good

Trend: Improving.

Rationale: The traditional legacy contaminants, DDE, SUM PCBs and TCDD and Hg, have declined significantly both since the 1970s (1974-2009) and in the last decade (2000-2009). No significant change for SUM

BDE in the short term.

Lake Erie

Status: Fair

Trend: Unchanging.

Rationale: The legacy contaminants, DDE, SUM PCBs, TCDD and Hg, have all declined significantly since the

1970s (1974-2009). However, none of them, as well as SUM BDEs has declined significantly in the last decade (2000-2009).

Lake Ontario

Status: Fair

Trend: Unchanging.

Rationale: The legacy contaminants, DDE, SUM PCBs, TCDD and Hg, have all declined significantly since the

1970s (1974-2009). However, none of them, as well as SUM BDEs has declined significantly in the last decade (2000-2009).

Purpose

To assess the current chemical concentrations and trends in representative colonial waterbirds (gulls, terns,

188

• cormorants and/or herons) on the Great Lakes.

To infer and measure the impact of contaminants on the health, i.e. the physiology and breeding characteristics of the waterbird population.

To assess ecological and physiological endpoints in representative colonial waterbirds on the Great Lakes.

The Contaminants in Waterbirds indicator is used in the Great Lakes indicators suite as a State indicator in the Water Quality top level reporting category.

Ecosystem Objective

Tracking progress of fish-eating colonial waterbirds on the Great Lakes toward an environmental condition in which there is no difference in contaminant levels and related biological endpoints between birds on and off the Great

Lakes. As part of this indicator, contaminant levels are also measured in herring gull eggs to ensure that levels continue to decline.

Ecological Condition

Measure

Annual concentrations of the DDT complex, PCBs/PCDFs/PCDDs and other organic contaminants, and Hg and other metals in Herring Gull eggs from 15 sites from throughout the Great Lakes (U.S. and Canada).

Periodic measurement of biological features of gulls and other colonial waterbirds known to be directly or indirectly impacted by contaminants and other stressors. These include (but are not limited to): clutch size, eggshell thickness, hatching and fledging success, size and trends in breeding population, various physiological biomarkers including vitamin A, immune and thyroid function, stress (corticosterone) and growth hormone levels, liver enzyme induction, PAH levels in bile and porphyrins and genetic and chromsomal abnormalities. Additional monitoring considerations include: tracking porphyria, vitamin A deficiencies, and the evaluation of avian immune systems.

Endpoint

Chemical levels and biological measures in colonial nesting waterbirds are not different from those from reference sites in Atlantic Canada or from the Prairies.

Decreasing contaminant trends.

Additional Information

Since 1974, 10-13 eggs have been collected annually from up to 13 nesting colonies in the Great Lakes and in connecting channels (Figure 1). Egg contents were selected because, collection is rather easy and inexpensive and because lipid contents in eggs is less variable than in other tissues (Weseloh et al 2006). Further details are described in Pekarik and Wesoleh (1998).

Although there are Great Lakes wildlife species that are more sensitive to contaminants than Herring Gulls, and colonial nesting waterbird species in general, there is no other species which has the historical dataset that the

Herring Gull does. As contaminant levels continue to decline (if they do), the usefulness of the Herring Gull as a biological indicator species may lessen (due to its reduced sensitivity to low levels of contamination) but its value as a chemical indicator will remain and probably increase - as levels become harder and harder to measure in other media. It is an excellent accumulation tracker since many of the above biological measures are correlated with contaminant levels in their eggs. In other colonial waterbirds, there are similar correlations between contaminant levels in eggs and various biological measures. Contaminant levels in eggs of other colonial waterbirds are usually correlated with those in Herring Gulls. Adult Herring Gulls nest on all the Great Lakes and the connecting channels and remain on the Great Lakes year-round. Because their diet is usually made up primarily of fish, they are an

189

excellent terrestrially-nesting indicator of the aquatic community. The Herring Gull egg contaminants dataset is also the longest running continuous (annual) contaminants dataset for wildlife in the world.

The Contaminants in Waterbirds indicators is included in the Water Quality assessment for the Great Lakes because long term trends of contaminants in biota provide valuable insight into the relative abundance of contaminants in the vicinity of fish and waterbird populations. It is important to note, however, that contaminant levels in biota represent not just quantities of contaminants in the water, but are the result of the integration of many biological, chemical and physical interactions (e.g. bioaccumulation and biomagnification processes, variations in diet and growth rates).

Historical data on levels of chemical contamination in gull eggs are available, on an annual basis, for most sites in both the Canadian and U.S. Great Lakes dating back to the early 1970s. An immense database of chemical levels and biological measures from the Great Lakes, as well as many off-Lakes sites, is available from the Ecotoxicology and Wildlife Health Division at Environment Canada. Data on temporal trends, portrayed as annual contaminant levels over time, for 1974-present in most instances, are available for each site and each compound. For example,

DDE, from 1974-2008, is available for Toronto Harbour and could be displayed graphically. Geographical patterns in contaminant levels, showing all sites relative to one another, are also available for most years from 1974-present and for most compounds. For example, PCBs, 2008, at 15 Great Lakes sites from Lake Superior to the St. Lawrence

River (including U.S. sites) and could be displayed on both maps and graphs.

The size and distribution of the waterbird populations which breed on the Great Lakes is also an indicator of ecosystem health. Declining waterbird populations (number of breeding pairs or nests) and vital rates (hatching success, fledging success, mortality rates, etc.) can be indicators of local environmental stress. The Great Lakeswide population of colonial waterbirds has been censused jointly, by the Canadian Wildlife Service and the U.S.

Fish and Wildlife Service since the 1970s, approximately every 10 years; four “decadal” censuses have been conducted to date: in the 1970s, 1980s, 1990s and 2000s. Briefly, and in the long-term (from the 1970s to the

2000s), these censuses have shown that the breeding numbers of six species have increased: Double-crested

Cormorants, Black-crowned Night-Herons, Great Egrets, Ring-billed Gulls, Great Black-backed Gulls, and Caspian

Terns. Unfortunately, the numbers of three species, Great Blue Heron, Herring Gull and Common Tern, have gone declined. In the short-term (from the 1990s to 2000s), numbers of night-herons, the three gull species and Common

Terns have declined. For Common Terns, which have declined continuously since the first census, the trend is alarming; numbers have declined from approximately 8,600 pairs to just 5,000 pairs (42%; Figure 3). The reasons for this decline are unclear but it is partially due to competition for nest sites with Ring-billed Gulls and habitat loss.

Although the Herring Gull population is much more numerous (approximately 32,000 pairs), their decline should be monitored, especially in Lake Huron, where numbers have declined from approximately 33,500 pairs in the 1970s to

22,000 pairs in the 2000s (34%). Currently, drivers such as habitat change and loss, changes in trophic structure and abundance of fish prey, reduced access to alternate sources of food (for gulls, due to changes in agricultural and waste disposal practices), inter-specific competition for nesting space (e.g. increased pressure from overabundant species such as cormorants and Ring-billed Gulls) and stressors in overwintering areas likely play a larger role in regulating waterbird populations than contaminant-related impairments.

Linkages

There are many linkages between the contaminant levels in fish-eating waterbirds indicator and many other indicators within the Great Lakes (SOLEC) reporting suite. There is a link between Contaminants in fish-eating waterbirds and Contaminants in Whole Fish as well as with Top Predator Fish and Preyfish. Trends seen in fisheating colonial waterbirds are also likely linked to those seen in Bald Eagles. A link has also been shown by Dr.

Craig Hebert between contaminant levels in Herring Gull eggs and Ice Duration. There is a direct link between

Herring Gull contaminants and Endocrine Disruption and, in terms of the health of Great Lakes fish-eating birds, between Herring Gulls and both Botulism Outbreaks and the Occurrence of Fish Diseases.

190

Data Limitations

Herring Gulls are highly tolerant of persistent contamination and may underestimate biological effects occurring in other less monitored, more sensitive species. Also, some adult Herring Gulls from the upper lakes, especially Lake

Superior, move to the lower lakes, especially Lake Michigan, during harsh winters. This has the potential to confound the contaminant profile of a bird from the upper Lakes. Most of the gull’s time is still spent on its home lake and this has not been noted as a serious limitation up to this point. Using contaminant accumulation by young, flightless gulls would eliminate this problem but their contaminant levels and effects would be less due to the much reduced contaminant exposure/intake.

It is difficult to show consistent differences in biological effects among colony sites within the Great Lakes. This is probably due to the great overall reduction in contaminant levels as well as the lessening in differences among Great

Lakes sites. The comparisons which show the greatest differences for biological effects of contaminants are between sites on and off the Great Lakes.

Also, contaminant concentrations in most colonially-nesting, fish-eating birds are at levels where gross ecological effects, such as eggshell thinning, reduced hatching and fledging success, and population declines, are no longer apparent. Greater reliance for detecting biological effects of contaminants is being put upon physiological and genetic biomarkers. These are not as well characterized, nor are they understood as easily by the public. Other complementary species include: Double-crested Cormorant (

Phalacrocorax auritus

), Common Tern (

Sterna hirundo

), Caspian Tern (

Hydroprogne caspia

) and Black-crowned Night-Heron (

Nycticorax nycticorax

).

Assessing Data Quality

Data Characteristics

1. Data are documented, validated, or qualityassured by a recognized agency or organization

2. Data are traceable to original sources

3. The source of the data is a known, reliable and respected generator of data

4. Geographic coverage and scale of data are appropriate to the Great Lakes basin

5. Data obtained from sources within the U.S. are comparable to those from Canada

6. Uncertainty and variability in the data are documented and within acceptable limits for this indicator report

Strongly

Agree

x x x x x x

Agree

Neutral or

Unknown

Disagree

Strongly

Disagree

Not

Applicable

Acknowledgments

Shane de Solla, Science and Technology, Environment Canada, Canada Centre for Inland Waters, Box 5050,

Burlington, Ontario L7R 4A6. [email protected]

D.V. Chip Weseloh, Environment Canada, Canadian Wildlife Service, 4905 Dufferin St. Toronto, Ontario M3H

5T4. [email protected]

Dave Moore, Environment Canada, Canadian Wildlife Service, Canada centre for Inland Waters, Box 5050,

Burlington, Ontario L7R 4A6. [email protected]

Cooperators

Guy Savard, National Wildlife Research Centre, Environment Canada, Carleton University, Ottawa, Ontario K1A

0H3. [email protected]

Craig Hebert, National Wildlife Research Centre, Environment Canada, Carleton University, Ottawa, Ontario K1A

0H3. [email protected]

Robert.Letcher, National Wildlife Research Centre, Environment Canada, Carleton University, Ottawa, Ontario

191

K1A 0H3. [email protected]

Ray Faber, Saint Mary's University of Minnesota 700 Terrace Heights #1524, Winona MN 55987

Information Sources

Weseloh D.V.C., Pekarik C. and S.R. de Solla. 2006. Spatial patterns and rankings of contaminant concentrations in herring gull eggs from 15 sites in the Great Lakes and connecting channels, 1988-2002. Environ. Monitor.

Assess. 113: 265-284. de Solla, S.R., D.V.C, Weseloh, C.E. Hebert and C. Pekarik. 2010. Impact of changes in analytical techniques for the measurement of polychlorinated biphenyls and organochlorine pesticides on temporal trends in Herring

Gull eggs. Environ. Toxicol. Chem. 9999 (120: 1-8).

Pekarik, C. and D. V. Weseloh. 1998. Organochlorine contaminants in herring gull eggs from the Great Lakes,

1974-1995: Change point regression analysis and short-term regression. Environ. Monit. Assess. 53: 77-115.

Weseloh, D.V.C., D.J. Moore, C.E. Hebert, S.R. de Solla, B.M. Braune and D. McGoldrick. In press. Current concentrations and spatial and temporal trends in mercury in Great Lakes Herring Gull eggs, 1974-2009.

Ecotoxicology.

Environment Canada, unpublished data.

List of Figures

Figure 1

. Locations of annual Herring Gull egg collection sites on the Great Lakes and connecting channels.

Source: Canadian Wildlife Service, Environment Canada – Burlington/Downsview.

Figure 2

. Change in concentration of DDE, sum PCBs, mercury (Hg) (ug/g, wet weight), 2,3,7,8-TCDD and sum

BDEs (pg/g, wet weight) in Great Lakes Herring Gull eggs from year of first measurement (green bars) compared to values for 2000 (orange bars) and the most recent measurement (2009, yellow bars). Values in first year of measurement have been set to 100%. Years of first and most recent measurement are indicated below compound names on the x-axis. No eggs were available from Fighting in 2009, so the 2008 value has been used; similarly,

1973 DDE and Hg values were used for Lake Michigan. Values associated with each bar are the actual concentrations. Symbols above green bars indicate p-values from regressions on ln-transformed concentrations for the entire dataset (1st to last measured, red text) and the period from 1999-2009 (black text): *

*, p≤0.0001; *, p≤0.001; ^, p ≤0.01; #, p ≤0.05, ns, not significant.

Source: Ecotoxicology and Wildlife Health Division, Environment Canada – Burlington.

Figure 3.

Changes in the number of Common Tern nests (red) and breeding colonies (blue) in Canadian waters of the Great Lakes and connecting channels during four “decadal” survey periods (1976-80, 1989-90, 1997-2000 and

2007-2009). Not shown: Lake Superior had 25 nests at a single colony during the second census period.

Source: Canadian Wildlife Service, Environment Canada – Burlington/Downsview.

Last Updated

State of the Great Lakes 2011

192

1

1.

Granite I.

2.

Agawa Rks.

3.

Big Sister I.

4.

Gull I.

5.

Channel-Shelter I.

6.

Double I.

7.

Chantry I.

8.

Fighting I.

9.

Middle I.

10.

Port Colborne

11.

Niagara R.

12.

Hamilton Harbour

13.

Toronto Harbour

14.

Snake I.

N

15.

Strachan I.

Lake Superior

IJC annual monitoring colonies

( N=15 )

2

St. Marys River

6

4

3

5

Lake

Michigan

St. Clair River

Lake St. Clair

Detroit River

8

Lake

Huron

St. Lawrence River

15

14

7

12

13

Lake Ontario

10

11

Niagara River

Lake Erie

N

9

Figure 1.

Locations of annual Herring Gull egg collection sites on the Great Lakes and connecting channels.

Source: Canadian Wildlife Service, Environment Canada – Burlington/Downsview.

193

Figure 2

. Change in concentration of DDE, sum PCBs, mercury (Hg) (ug/g, wet weight), 2,3,7,8-TCDD and sum

BDEs (pg/g, wet weight) in Great Lakes Herring Gull eggs from year of first measurement (green bars) compared to values for 2000 (orange bars) and the most recent measurement (2009, yellow bars). Values in first year of measurement have been set to 100%. Years of first and most recent measurement are indicated below compound names on the x-axis. No eggs were available from Fighting in 2009, so the 2008 value has been used; similarly,

1973 DDE and Hg values were used for Lake Michigan. Values associated with each bar are the actual concentrations. Symbols above green bars indicate p-values from regressions on ln-transformed concentrations for the entire dataset (1st to last measured, red text) and the period from 1999-2009 (black text

): **, p≤0.0001; *, p≤0.001; ^, p ≤0.01; #, p ≤0.05, ns, not significant.

Source: Ecotoxicology and Wildlife Health Division, Environment Canada – Burlington.

194

Figure 3

.

Changes in the number of Common Tern nests (red) and breeding colonies (blue) in Canadian waters of the Great Lakes and connecting channels during four “decadal” survey periods (1976-80, 1989-90, 1997-2000 and

2007-2009). Not shown: Lake Superior had 25 nests at a single colony during the second census period.

Source: Canadian Wildlife Service, Environment Canada – Burlington/Downsview

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Contaminants in Whole Fish

Overall Assessment

Status: Fair

Trend: Deteriorating

Rationale: The assessment incorporates multiple contaminants and considers potential effects of exposure to fish eating wildlife. Total mercury concentrations remain below the target of 0.5ug/g ww in all lakes.

However, concentrations appear to be increasing at locations within the basin signaling a deterioration of this indicator. Concentrations of PCBs and pentaPBDEs are currently above guidelines in Lake Trout and Walleye in all the Great Lakes; however concentrations of these contaminants are declining in most monitored fish.

Lake-by-Lake Assessment

Lake Superior

Status: Fair

Trend: Deteriorating

Rationale: Concentrations of PCBs and pentaBDEs are above guidelines in Lake Trout in Lake Superior and declining. Total Hg concentrations, although still below the target of 0.5 µg/g ww, have returned to levels observed in the 1980s and appear to be increasing.

Lake Michigan

Status: Fair

Trend: Unchanging

Rationale: Concentrations of PCBs and pentaBDEs are above guidelines in Lake Trout from the lake and declining. Total Hg concentrations are similar to observations in the other lakes but there is not enough data from recent years to confirm a significant trend.

Lake Huron

Status: Fair

Trend: Deteriorating

Rationale: Concentrations of PCBs and pentaBDEs are above guidelines in Lake Trout in Lake Huron and declining. Total Hg concentrations, although still below the target of 0.5 µg/g ww, have returned to levels observed in the 1980s and are increasing.

Lake Erie

Status: Fair

Trend: Deteriorating

Rationale: Concentrations of PCBs and pentaBDEs are above guidelines in Walleye from Lake Erie and declining.

Total Hg concentrations, although still below the target of 0.5 µg/g ww, have returned to levels observed in the 1980s and are increasing.

Lake Ontario

Status: Fair

Trend: Unchanging

Rationale: Concentrations of PCBs and pentaBDEs are above guidelines in Lake Trout from Lake Ontario and declining. Total Hg concentrations are no longer declining and may be increasing as observed in fish from Lakes Superior, Huron and Erie.

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Purpose

To describe temporal and spatial trends of bioavailable contaminants in representative open water fish species from throughout the Great Lakes

To infer the effectiveness of remedial actions related to the management of critical pollutants

To identify the nature and severity of new and emerging pollutants of concern

The Contaminants in Whole Fish indicator is used in the Great Lakes indicators suite as a State indicator in the Water Quality top level reporting category.

Ecosystem Objective

Great Lakes waters should be free of toxic substances that are harmful to fish and wildlife populations and the consumers of this biota. Data on status and trends of contaminant conditions, using fish as biological indicators, support decisions about beneficial uses about degradation of fish populations and the requirements of the Great

Lakes Water Quality Agreement (GLWQA, United States and Canada 1987) Annexes 1 (Specific Objectives), 2

(Remedial Action Plans and Lakewide Management Plans), 11 (Surveillance and Monitoring), and 12 (Persistent

Toxic Substances).

Ecological Condition

Background and Methods

Long-term (greater than 25 years), basin-wide monitoring programs that measure whole body concentrations of contaminants in top predator fish (Lake Trout and/or Walleye) are conducted by both the U.S. Environmental

Protection Agency (U.S. EPA) Great Lakes National Program Office through the Great Lakes Fish Monitoring and

Surveillance Program, and Environment Canada’s (EC) Water Quality Monitoring Surveillance Division, through the Fish Contaminants Monitoring and Surveillance Program, to identify the risk of contaminants to wildlife consumers of fish and to monitor trends in time. “The

Contaminants in Whole Fish

indicator is included in the

Water Quality assessment for the Great Lakes because long term trends of contaminants in biota provide valuable insight into the relative abundance of bioaccumulative contaminants in the environment. Fish integrate exposure to contaminants over time and across their range and thus provide a broader assessment of environmental exposure than would a water sample taken at a single location at a point in time. Bioaccumulative contaminants are also found at higher concentrations in biota than they are in water, allowing for more accurate and cost effective determination of levels in the environment. It is important to note, however, that contaminant levels in biota represent not just quantities of contaminants in the water, but are the result of the integration of many biological, chemical and physical interactions (e.g. bioaccumulation and biomagnification processes, variations in diet and growth rates).

Environment Canada reports annually on contaminant burdens in similarly aged Lake Trout (4+ through 6+ year range) and Walleye (Lake Erie) as well as in Rainbow Smelt (

Osmerus mordax

), a common forage species. The U.S.

EPA monitors contaminant burdens in similarly sized lake trout (600-700 mm total length) and walleye (Lake Erie,

400-500 mm total length) annually from alternating locations by year in each lake. Monitoring stations for both EC and U.S. EPA are shown in Figure 1. One additional difference between the EC and U.S. EPA programs, which limits the combination of data for statistical analyses, is that EC measures contaminants in individual fish and U.S.

EPA measures contaminants in composite samples. As a result of these differences, all analyses and summary statistics are reported separately for each dataset. Unless stated otherwise, trends through time were assessed using first-order log-linear regression models of annual median concentrations to estimate percent annual declines. Trends were deemed significant if the slope of model was greater or less than zero at α = 0.05. When applicable, contaminant concentrations and trends are compared to criteria established in the GLWQA or other relevant guidelines developed to protect ecosystem quality. The GLWQA, first signed in 1972, renewed in 1978, and amended in 1987, expresses the commitment of Canada and the United States to restore and maintain the chemical, physical and biological integrity of the Great Lakes basin ecosystem. At present, negotiations between the governments of Canada and the United States to develop a new agreement are underway. When a new agreement is

197

reached, the fish contaminant monitoring programs will be evaluated and modified to meet new requirements and objectives.

More information on the monitoring programs can be found at the following websites: http://www.epa.gov/glnpo/monitoring/fish/index.html

and http://www.ec.gc.ca/scitech/default.asp?lang=en&n=828EB4D2-1

Chemical Concentrations in Whole Great Lakes Fishes

Since the late 1970s, concentrations of legacy organochlorine contaminants such as polychlorinated biphenyls

(PCBs) and dichlorodiphenyltrichloroethane (DDT) have declined in most monitored fish species. Conversely, the declines in concentrations of total mercury in fish through the 1980s have reversed in most lakes and are now increasing to levels observed at the onset of monitoring in the basin. In recent years, contaminants, such as polybrominated diphenyl ethers (PBDEs) and perfluorooctane sulphonate (PFOS), have garnered the attention of monitoring and regulatory agencies in the Great Lakes Basin. In general, the levels of regulated compounds are slowly declining or have stabilized in the tissues of Great Lakes top predatory fish. Basin wide, the changes are often lake-specific as they are dependant, in part, on the physio-chemical characteristics of the contaminants, hydrological characteristics of the lake, and the biological composition of the fish community and associated food webs.

Total polychlorinated biphenyls (PCBs)

Basin Wide Status: Fair; Improving

Total PCB concentrations in Great Lakes top predator fish have continuously declined since their phase-out in the

1970s (Figure 2). Median PCB concentrations in Lake Trout in Lakes Superior, Huron, and Ontario and Walleye in

Lake Erie continue to decline; however, they are still above the target of 0.1 µg/g ww in the GLWQA (Table 1).

Log-linear regression of Environment Canada data show the continued long-term annual declines of 5% in Lake

Trout from Lake Superior and 7% in Lakes Huron and Ontario while PCBs in Lake Erie Walleye are declining by

3% per year. Similar analyses of U.S. EPA data show no significant annual declines of total PCB in Lake Trout from

Lake Superior and 4%, 6%, 7%, and 4% annual declines in total PCB in Lake Trout from Lakes Huron, Michigan,

Ontario, and Lake Erie Walleye, respectively. Data collected since the last SOLEC indicator report (2006-2009), show that total PCB concentrations in composited Rainbow Smelt measured by Environment Canada were all less than 0.1 µg/g ww in Lakes Superior and Huron. In Lake Erie, total PCB measured in 83% of Rainbow Smelt were below 0.1 µg/g ww, compared to only 34% of measurements in smelt from Lake Ontario. In Lake Ontario, total

PCB concentrations in Rainbow Smelt are declining by ~8% per year since monitoring began in 1977.

Recent studies have suggested that rates of decline of PCB residues in fish are slowing or have stopped in some lakes in recent years (Bhavsar et al. 2007; Carlson et al. 2010). Despite potential changes in annual rates of decline, first-order log-linear regression models are still a good fit to observed concentrations in the lakes through time

(Figure 2). Results generated in the next few years of monitoring should clarify whether or not the rates of decline are slowing and statistical methods to assess trends will be altered as required.

Dichlorodiphenyltrichloroethane (DDT) and metabolites

Basin Wide Status: Good; Improving

The concentration of opDDT and its metabolites, opDDD and opDDE, (sumDDT) in Great Lakes top predator fish have continuously declined since the use of the chemical was banned in 1972. Concentrations measured since the last indicator report (2006-2009) remain well below the GLWQA target of 1.0 µg/g ww across the basin (Table 2).

Based on data collected at EC monitoring locations, annual rates of decline are 6.8% in L. Superior, 7.1% in L.

Huron, 7.5% in L. Erie, and 7.3% in L. Ontario. Since the last indicator report, the rates of decline appear to be consistent with historical trends. Annual rates of decline determined using U.S. EPA data are slightly lower at 4.5% in L. Superior, 5.9% in L. Michigan, 5.9% in L. Huron, 6.0% in L. Erie, and 6.7% in L. Ontario. Rates of decline at

198

the U.S. monitoring stations in the years since the last indicator report appear to be increasing (i.e. declining faster) in lakes Michigan, Huron, and Ontario compared to historical trends while rates remain consistent with historical trends in Lakes Superior and Erie.

Total mercury

Basin Wide Status: Good; Deteriorating

There have been several studies on spatial and temporal trends of mercury in fish in the Great Lakes region since the last SOLEC indicator report (Bhavsar et al 2010; Monson et al. in press; Zananski et al. 2011). Both studies found that generally, the declines in mercury concentrations observed up until approximately 1990 have ceased and that mercury concentrations in fish have started to increase. EC and U.S. EPA data were used in the analyses of both studies and correspond with their findings (Figure 3). Concentrations of mercury are similar across all fish in all

Great Lakes consistent with the assumption that concentrations of mercury in top predator fish are atmospherically driven and the recent increases may be a reflection, in part, of increased global mercury emissions (Pacyna et al.

2006). It is important to note that since the last indicator report (2006-2009) median concentrations of mercury in all top predator fish collected in Lakes Ontario, Erie, Huron and Michigan are below the GLWQA guideline of 0.5 µg/g and exceedances of the guideline only occurred in ~4% of the Lake Trout captured in Lake Superior (Table 3).

Mercury concentrations in top predator fish are currently equal to or approaching the concentrations measured at the inception of the monitoring program in the late 1970s. Two segment linear piecewise regression of the EC dataset show that declines in mercury ceased in the late 1980s in lakes Superior and Huron and the early 1990s in lakes Erie and Ontario. Following the change points in each lake, mercury levels have been stable in lakes Huron and Ontario and appear to be increasing in lakes Superior and Erie. Mercury levels at U.S. EPA monitoring locations since 1999 mirror the EC results with one exception, in Lake Huron there has been a significant annual increase of mercury in

Lake Trout of ~7%. Similar temporal patterns in mercury concentrations are also observed in Rainbow Smelt, a common forage fish for many fish and birds in the Great Lakes basin (Figure 4). The observed trend reversal in mercury concentrations in fish is consistent with recent findings (Monson 2009; Raymond & Rossmann 2009;

Bhavsar et al. 2010; Monson et al. 2011) of mercury. Unfortunately, the data gap from the mid to late 1990s does not leave a sufficient number of data points to determine the current rates increase due to low statistical power.

Continued monitoring of Hg levels in fish is required to definitively determine the rate of increase in mercury in all the lakes and adequately assess the future risk to wildlife consumers of fish in the Great Lakes basin.

Σα- & γ-Chlordane

Basin Wide Status: Good; Unchanging

Concentrations of α- + γ-chlordane in whole Lake Trout and Walleye have consistently declined since the chemical was banned by the U.S. EPA in 1988. In recent years, the concentrations in fish appear to have reached a steady state with no significant increases or decreases. The highest observed median concentrations since the last indicator report (2006-2009) are in Lake Trout from Lake Michigan (0.018 µg/g ww), followed by Lake Ontario (0.012 µg/g ww). Median concentration in Lakes Superior, Huron, and Erie are all below 0.01 µg/g ww. There is no target for chlordane in whole fish in the GLWQA. A report on the levels of chlordane in fish will not appear in future SOLEC indicator reports as focus is shifted to contaminants with established environmental quality guidelines or targets.

Mirex

Basin Wide Status: Good; Improving

Mirex is regularly detected only in fish from Lake Ontario due to historical releases in the Niagara River and other locations within the lake’s watershed. Since the last indicator report (2006-09), median concentrations in Lake Trout were 0.061 µg/g ww (EC) and 0.041 µg/g ww (U.S. EPA). Declines in the concentration of mirex in Lake Trout from Lake Ontario are still declining at historical rates of between 4 and 12 % annually. According to the guidelines listed in the GLWQA, Mirex should be “substantially absent” from Great Lakes fish.

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Dieldrin

Basin Wide Status: Good; Improving

The highest concentrations of dieldrin (and related compounds endrin and andrin) in top predator fish are observed in Lake Michigan (median = 0.034 µg/g ww) and Lake Ontario (median = 0.021 ug/g ww). Concentrations have declined substantially since monitoring began in the lakes and are still declining basin wide at rates ranging from 2 to 18% annually. There is no guideline for dieldrin in whole fish in the GLWQA. This will be the last report on the levels of dieldrin and related compounds SOLEC as focus is shifted to contaminants with established environmental quality guidelines or targets.

Toxaphene

Basin Wide Status: Fair; Improving

Decreases in toxaphene concentrations have been observed throughout the Great Lakes in all media following its ban in the mid-1980s. A recent study on toxaphene trends in Great Lakes fish show that concentrations remain the highest in Lake Superior (up to ~480 ng/g) and lowest in Lake Erie (up to ~50 ng/g) (Xia et al. 2012).

Concentrations of toxaphene in Lake Trout and Walleye continue to exhibit exponential temporal declines in all of the Great Lakes; however, concentrations appear to level off starting in 2007 (Xia et al. 2012). Continued monitoring of toxaphene in top predator fish in the coming years should confirm whether toxaphene concentrations have reached a steady state in Great Lakes fish.

Polybrominated Diphenyl Ethers (PBDEs)

Basin Wide Status: Fair; Improving

The production and use of three popular commercial formulations of PBDE have or are being voluntarily phased out by industry in North America. The phase out of the more toxic penta- and octa-BDE compounds started in 2004 and by 2012, the use of deca-BDE will likely be reduced as a result of the voluntary withdrawal by industry

(http:/www.bsef.com). In a national survey of PBDE concentrations in top predator fish from lakes across Canada, the highest concentrations were observed in fish from the Great Lakes and >95% of the PBDE compounds in the fish were tetra-, penta-, or hexa-BDEs (Gewurtz et al. 2011). Federal Environmental Quality Guidelines (FEQG) have been developed by Environment Canada for these three homologue groups which are meant to provide targets for acceptable environmental quality, assess the significance of observed concentrations, and to measure the success of risk management activities. The FEQGs to protect wildlife consumers of fish for tetra-, penta- and hexa-BDEs are

88, 1.0, and 420 ng/g ww respectively (Environment Canada 2010). Routine monitoring of PBDEs in whole top predator fish from the Great Lakes combined with retrospective analyses of archived samples by the U.S. EPA (Zhu

& Hites, 2004) and Environment Canada have provided a complete picture of PBDE contamination in Great Lakes fish from 1977 to the present day. Concentrations of PBDEs in Lake Trout and Walleye rose continuously through to the early 2000s then began to decline as shown for penta-BDE in Figure 5

.

Log-linear regression of PBDE concentrations in Lake Trout and Walleye (U.S. EPA; Lake Erie), show significant declining trends of 5.8%/year for tetra-BDEs, 6.4% for penta-BDEs, and 3.4% for hexa-BDEs in Lake Ontario and annual declines of 19% for tetra-

BDEs and 17% for penta-BDEs from Lake Michigan. PBDE concentrations in Lakes Superior, Huron, and Erie also appear to be declining as the slopes of the regressions are all negative; however, the slopes are not significantly different from zero at α = 0.05 with a power of 80%. The majority of tetra-BDE and all hexa-BDE concentrations reported for Lake Trout and Walleye in 2009 from all the Great Lakes are below Environment Canada’s FEQGs; however, all measured penta-BDE concentrations are well above the FEQG of 1.0 ng/g ww (Figure 6).

Other Contaminants of Emerging Interest

Perfluorinated acids

Perfluorooctane sulfonate (PFOS) is a synthetic substance belonging to a larger class of organic fluorochemicals that are either partially or completely saturated with fluorine. PFOS, perfluorocarboxylates and their precursors are used primarily in water, oil, soil, and grease repellents for paper and packaging, carpets, and fabrics, as well as in aqueous

200

film forming foam (AFFF) for fighting fuel fires. PFOS was voluntarily phased-out of production by their primary supplier in 2002. However, PFOS use in Canada and the US continues due to specific use exemptions. Routine monitoring of PFOS in whole Lake Trout from the Great Lakes combined with retrospective analyses of archived samples from EC’s National Aquatic Biological Specimen Bank have provided information on PFOS contamination in Lake Ontario Great Lakes fish from 1979 to 2008 (Figure 7). Concentrations of PFOS in Lake Trout rose continuously at a rate of 5.9%/year through to the late 1980s/early 1990s, after which no consistent change in time was observed. This contradicts trends observed in ringed seals in the Canadian Arctic, where significant PFOS declines were observed within the year following voluntary phase-outs (Butt et al. 2007). This contradiction may be due to continued inputs into Lake Ontario from the continued use of these substances. Perfluorooctanoic acid

(PFOA) is another common fluorochemical and major manufacturers have voluntarily agreed to a 99% phase-out by

2015. However, PFOA is not highly bioaccumulative and time trends were not reliably measured in fish.

Conversely, the concentration of two other fluorochemicals, perfluorodecane sulfonate (PFDS) and Perfluorooctane sulfonamide (PFOSA), have declined consistently in Lake Trout from Lake Ontario since 1992 at rates of 4.4% and

6.2% per year, respectively.

Synthetic Musks

The GLFMSP has begun screening for synthetic musks in fish tissue. These compounds are typically used in perfumes, colognes, shampoos, detergents, disinfectants and enter water through wastewater discharge and atmospheric deposition. The classes of synthetic musks that are of interest include: nitro-musks, polycylic musks, macrocyclic musks, alicyclic musks. To date, analytical results have indicated that two synthetic musks in particular, galoxolide and tonalide, are the most abundant musks found in GLFMSP samples. Concentrations of musks are highest in Lake Ontario followed by Lake Superior, Lake Huron, Lake Michigan, and Lake Erie. There is currently insufficient data to fully explain the spatial pattern in the Lakes; however, this could be evidence of significant atmospheric transport of musks. Detection of these chemicals in the laboratory is extremely difficult due to the high potential for sample contamination since these chemicals are present in numerous products, including laundry detergent, soaps, shampoos, deodorants, body sprays, cleaning supplies, etc. Experimental techniques, such as fragarance-free rooms for analysis may be employed for future analyses. Additional results for musks, and other emerging chemicals, will be reported in subsequent SOLEC indicator reports.

Linkages

Contaminant levels in Lake Trout and Walleye are dependent on complex biological and physiochemical interactions both within and outside of the Great Lakes basin as these apex predators integrate contaminant inputs from water, air, sediment, and their food sources. A changing climate and associated changes to precipitation and wind currents will alter the influx of contaminants from sources outside of the basin and may alter food webs and the contaminant transfer through them. Aquatic invasive species also alter food webs and change energy and contaminant dynamics in the lakes. They also may introduce new pathways by which sediment contaminant pools could be mobilized and transferred to fish. Many new contaminants of concern are components of consumer products, personal care products, or pharmaceuticals, as a result, wastewater treatment effluents are an important source of contamination which is growing along with the human population of the basin.

Management Challenges/Opportunities

Much of the current, basin wide, persistent toxic substance data that is reported focuses on legacy chemicals whose use has been previously restricted through various forms of legislation but that continue to be the source of the highest levels of contaminants detected in fish, eg. PCBs. However, both the U.S. and Canadian programs are making efforts to incorporate the monitoring and surveillance of emerging chemicals into their routine work.

Chemicals of interest are identified through scientific studies (eg. Howard & Muir 2010), general screening of annual samples and also though risk assessments by regulatory bodies. As chemicals are identified through this process, they will be reported out through SOLEC, particularly those chemicals with established criteria.

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Environmental Specimen Banks containing tissue samples are a key component of both the U.S. and Canadian monitoring programs, allowing for retrospective analyses of newly identified chemicals of concern to develop longterm trends in the short-term.

Fostering collaboration between U.S. and Canadian monitoring programs for various media will be beneficial, especially in times of fiscal restraint. In 2009, an ad-hoc binational group was formed to bring together government representatives and researchers working on identifying new chemicals in the Great Lakes ecosystem with the objective to facilitate best management practices and sharing of information and resources. The group provides a forum for agencies and researchers to seek and provide information on emerging contaminant surveillance, monitoring, chemical methods development, and provides a place to collaborate on similar chemicals, or classes of chemicals, in different media. Collaboration among research in differing media also provides an excellent opportunity for cost sharing, an accelerated rate of discovery, and a validation of results among the Great Lakes research and monitoring community.

Comments from author(s)

The authors have made efforts to improve the statistical rigor of this indicator report through the inclusion of error bounds on estimated concentrations and trends through time. The authors have also focused on contaminants with defined environmental targets, guidelines and/or thresholds to put observed concentrations in context with risk to the environment. Other improvements to statistical rigor, such as, better methods to characterize dataset with censored values (i.e. non-detects) should be investigated and incorporated in future reports on this indicator.

Assessing Data Quality

Data Characteristics

1. Data are documented, validated, or quality-assured by a recognized agency or organization

2. Data are traceable to original sources

3. The source of the data is a known, reliable and respected generator of data

4. Geographic coverage and scale of data are appropriate to the Great Lakes basin

5. Data obtained from sources within the

U.S. are comparable to those from

Canada

6. Uncertainty and variability in the data are documented and within acceptable limits for this indicator report

Strongly

Agree

X

X

X

X

X

Agree

X

Neutral or

Unknown

Disagree

Strongly

Disagree

Not

Applicable

Acknowledgments

Authors:

Daryl McGoldrick, Environment Canada

Mandi Clark, Environment Canada

Elizabeth Murphy, United States Environmental Protection Agency

Information Sources

Bhavsar, S.P., D.A. Jackson, A. Hayton, E.J. Reiner, T. Chen, and J. Bodnar. 2007. Are PCB levels in fish from the

Canadian Great Lakes still declining? J. Great Lakes Res. 33: 592-605.

Bhavsar, S.P., S.B. Gewurtz, D.J. McGoldrick, M.J. Keir, and S.M. Backus. 2010. Changes in mercury levels in

Great Lakes fish between 1970s and 2007. Environ. Sci. Technol. 44: 3273-3279.

Butt C.M., D.C.G. Muir, I. Stirling, M. Kwan, and S.A. Mabury. 2007. Rapid response of arctic ringed seals to changes in perfluoroalkyl production. Environ Sci Technol 41:42-49.

202

Carlson, D.L., D.S. De Vault, and D.L. Swackhamer. 2010. On the rate of decline of persistent organic contaminants in lake trout (

Salvelinus namaycush

) from the Great Lakes, 1970-2003. Environ. Sci. Technol. 44: 2004-2010.

Environment Canada. 2010. Risk management strategy for polybrominated diphenyl ethers (PBDEs). Chemicals

Sectors Direcorate, Environmental Stewardship Branch, Environment Canada. Online publication: http://www.ec.gc.ca/Publications/default.asp?lang=En&xml=34DCDBA9-9C86-4EB2-AA93-81B6755321F9

Furdui, V.I., P.A. Helm, P.W. Crozier, C. Lucaciu, E.J. Reiner, C.H. Marvin, D.M. Whittle, S.A. Mabury, and G.T.

Tomy. 2008. Temporal trends of perfluoroalkyl compounds with isomer analysis in lake trout from Lake

Ontario (1979-2004). Environ. Sci. Technol. 42: 4739-4744.

Gewurtz, S.B., D.J. McGoldrick, M.G. Clark, M.J. Keir, M.M. Malecki, M. Gledhill, M. Sekela, J. Syrgiannis, M.S.

Evans, A. Armellin, J. Pomeroy, J. Waltho, and S.M. Backus. 2011. Status and trends of PBDEs in Canadian fish and implications for long-term monitoring. Environ. Toxicol. Chem. 30: 1564-1575.

Howard, P.H. and D.C.G. Muir. 2010. Identifying new persistent and bioaccumulative organics among chemicals in commerce. Environ. Sci. Technol. 44: 2277-2285.

Monson, B. A. 2009. Trend Reversal of Mercury Concentrations in Piscivorous Fish from Minnesota

Lakes: 1982-2006. Environ. Sci. Technol. 43: 1750-1755.

Monson, B.A., D.F. Staples, S.P Bhavsar, T.M. Holsen, C.S. Schrank, S,K. Moses, D.J. McGoldrick, S.M. Backus,

K.A. Williams. 2011. Spatiotemporal trends of mercury in Walleye and Largemouth Bass from the Laurentian

Great Lakes region. Ecotox. 20: 1555-1567.

Pacyna, E. G., J. M. Pacyna, F. Steenhuisen, and S. Wilson. 2006. Global anthropogenic mercury emission inventory for 2000. Atmos. Environ. 40: 4048-4063.

Raymond, B. and R. Rossmann. 2009. Total and methyl mercury accumulation in 1994-1995 Lake Michigan lake trout and forage fish. J. Great Lakes Res. 35: 438-446.

Schmitt, C.J., and W.G. Brumbaugh. 1990. National contaminant biomonitoring program: Concentrations of arsenic, cadmium, copper, lead, mercury, selenium, and zinc in U.S. freshwater fish, 1976-1984. Arch. Environ.

Contam. Toxicol. 19(5): 731-747. Dataset can be found at: http://www.cerc.usgs.gov/data/ncbp/fish.htm

(accessed May 2012).

Xia, X., P.K. Hopke, B.S. Crimmins, J.J. Pagano, M.S. Milligan, and T.M. Holsen. 2012. Toxaphene trends in the

Great Lakes fish. 2011. J. Great Lakes Res. 38(1): 31-38.

Zananski, T.J., T.M. Holsen, P.K. Hopke, and B.S. Crimmins. 2011. Mercury trends in top predator fish of the

Laurentian Great Lakes. Ecotox. 20: 1568-1576.

Zhu, L.Y. and R.A. Hites. 2004. Temporal trends and spatial distribution of brominated flame retardants in archived fishes from the Great Lakes. Environ. Sci. Technol. 38: 2779-2784.

List of Tables

Table 1

. Summary of total PCB concentrations for individual (Env. Canada; Arochlor 1254) and composited (U.S.

EPA; total congeners) whole body Lake Trout or Walleye collected from the each of the Great Lakes measured since the last SOLEC indicator report (2006-2009).

Source: Environment Canada and U.S. Environmental Protection Agency

Table 2

. Summary of the concentrations of opDDT and its metabolites (opDDD and opDDE) in individual (Env.

Canada) and composited (U.S. EPA) whole body Lake Trout or Walleye collected from the each of the Great Lakes measured since the last SOLEC indicator report (2006-2009).

Source: Environment Canada and U.S. Environmental Protection Agency

Table 3

. Summary of total mercury concentrations in individual (Env. Canada; 2006-2009) and composited (U.S.

EPA; 2006-2007) whole body Lake Trout or Walleye collected from the each of the Great Lakes measured since the last Great Lakes/SOLEC indicator report.

Source: Environment Canada and U.S. Environmental Protection Agency

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List of Figures

Figure 1

. Map of Great Lakes showing Environment Canada and U.S. Environmental Protection Agency monitoring stations for fish contaminants.

Source: Environment Canada and U.S. Environmental Protection Agency

Figure 2

. Total PCB concentrations (median & IQR) for individual (Environment Canada) and composited (U.S.

Environmental Protection Agency) whole body Lake Trout or Walleye (Lake Erie) collected from each of the Great

Lakes. Dashed lines show loglinear regression model if annual change is significantly different from zero (α =

0.05).

Source: Environment Canada and U.S. Environmental Protection Agency

Figure 3

. Total mercury concentrations (median & IQR) for individual (Environment Canada) and composited (U.S.

Environmental Protection Agency) whole body Lake Trout or Walleye (Lake Erie) collected from each of the Great

Lakes. Results of 2-segment linear piecewise regression (solid red line) or log-linear regression (solid blue line) models. Mercury concentrations reported by Schmitt and Brumbaugh (1990) in Lake Michigan Lake Trout also provided.

Source: Environment Canada, U.S. Environmental Protection Agency and Schmitt and Brumbaugh

Figure 4

. Median total mercury concentrations in composited Rainbow Smelt collected from the Canadian waters of the Great Lakes by Environment Canada. Lines denote 3 year moving average.

Source: Environment Canada and U.S. Environmental Protection Agency

Figure 5

. Mean (± stdev) penta-BDE concentrations in Great Lakes fish measured by Environment Canada, U.S.

Environmental Protection Agency and Zhu & Hites (2004). Solid lines denote significant log-linear regressions.

Dotted lines denote 3 year moving average when log-linear regression is not significant.

Source: Environment Canada and U.S. Environmental Protection Agency

Figure 6

. Concentrations of the dominant PBDE congeners (ng/g ww) in whole body Lake Trout and Walleye (U.S.

EPA; Lake Erie) in each of the Great Lakes measured in 2009 relative to the Federal Environmental Quality

Guidelines developed by Environment Canada (red dashed line).

Source: Environment Canada and U.S. Environmental Protection Agency

Figure 7

. Temporal trends of PFOS concentrations (geometric mean ± 95% confidence interval) in Lake Ontario

Lake Trout measured by Environment Canada (De Silva, unpublished data) and Ontario Ministry of the

Environment (Furdui et al. 2008).

Source: Environment Canada and U.S. Environmental Protection Agency

Figure 8

. Average synthetic musk concentrations (ng/g ww) in whole body Lake Trout and Walleye (U.S. EPA;

Lake Erie) in each of the Great Lakes measured in 2009.

Source: Environment Canada and U.S. Environmental Protection Agency

Last Updated:

State of the Great Lakes 2011

204

Summary of total PCB concentrations

Lake Superior

*

Env. Canada

Lake Superior

*

U.S. EPA

Lake Michigan

*

Env. Canada

Lake Michigan

*

U.S. EPA

Lake Huron

*

Env. Canada

Lake Huron

*

U.S. EPA

Lake Erie

**

Env. Canada

Lake Erie

**

U.S. EPA

Lake Ontario

*

Env. Canada

Lake Ontario

*

U.S. EPA

*

whole body Lake Trout

**

whole body Walleye

***

0.1 µg/g ww (GLWQA Annex 1)

N

324

35

-

40

101

40

142

40

324

38

Median (IQR)

µg/g ww

0.21 (0.08 – 0.41)

0.37 (0.18 – 0.55)

-

0.92 (0.78 – 0.99)

0.20 (0.16 – 0.26)

0.73 (0.50 – 0.85)

0.77 (0.53 – 1.3)

0.49 (0.38 – 0.79)

0.85 (0.66 – 1.1)

0.87 (0.74 – 1.0)

% measurements above target***

72

100

-

100

89

100

100

100

100

100

Table 1

. Summary of total PCB concentrations for individual (Env. Canada; Arochlor 1254) and composited (U.S.

EPA; total congeners) whole body Lake Trout or Walleye collected from the each of the Great Lakes measured since the last SOLEC indicator report (2006-2009).

Source: Environment Canada and U.S. Environmental Protection Agency

Summary of the concentrations of opDDT and its metabolites

Lake Superior

*

Env. Canada

Lake Superior

*

U.S. EPA

Lake Michigan* Env. Canada

Lake Michigan* U.S. EPA

Lake Huron* Env. Canada

Lake Huron* U.S. EPA

N

255

37

-

41

55

43

Median (IQR)

µg/g ww

0.04 (0.03 – 0.07)

0.09 (0.05 – 0.16)

-

0.27 (0.21 – 0.32)

0.11 (0.07 – 0.14)

0.21 (0.15 – 0.25)

% measurements above target***

0

0

-

0

0

0

Lake Erie** Env. Canada

Lake Erie** U.S. EPA

142

42

0.06 (0.05 – 0.08)

0.05 (0.04 – 0.05)

0

0

Lake Ontario* Env. Canada

Lake Ontario* U.S. EPA

*

whole body Lake Trout

**

whole body Walleye

***

1.0 µg/g ww (GLWQA Annex 1)

200

40

0.21 (0.12 – 0.30)

0.24 (0.19-0.29)

0

0

Table 2

. Summary of the concentrations of opDDT and its metabolites (opDDD and opDDE) in individual (Env.

Canada) and composited (U.S. EPA) whole body Lake Trout or Walleye collected from the each of the Great Lakes measured since the last SOLEC indicator report (2006-2009).

Source: Environment Canada and U.S. Environmental Protection Agency

205

Summary of total mercury concentrations

N

Lake Superior

*

Env. Canada

Lake Superior* U.S. EPA

Lake Michigan* Env. Canada

266

17

-

19

Median (IQR)

µg/g ww

0.18 (0.12 – 0.29)

0.21 (0.14 – 0.33)

-

0.15 (0.13 – 0.18) Lake Michigan* U.S. EPA

Lake Huron

*

Env. Canada

Lake Huron

*

U.S. EPA

Lake Erie

**

Env. Canada

Lake Erie** U.S. EPA

Lake Ontario

**

Env. Canada

101

20

91

20

252

0.10 (0.08 – 0.14)

0.24 (0.20 – 0.28)

0.15 (0.13 – 0.17)

0.11 (0.10 – 0.13)

0.13 (0.11 – 0.15)

% measurements above target***

4

0

-

0

0

0

0

0

0

Lake Ontario** U.S. EPA

*

whole body Lake Trout

**

whole body Walleye

***

0.5 µg/g ww (GLWQA Annex 1)

20 0.10 (0.10 – 0.13) 0

Table 3

. Summary of total mercury concentrations in individual (Env. Canada; 2006-2009) and composited (U.S.

EPA; 2006-2007) whole body Lake Trout or Walleye collected from the each of the Great Lakes measured since the last SOLEC indicator report.

Source: Environment Canada and U.S. Environmental Protection Agency

Figure 1.

Map of Great Lakes showing Environment Canada and U.S. Environmental Protection Agency monitoring stations for fish contaminants.

Source: Environment Canada and U.S. Environmental Protection Agency

206

Figure 2

. Total PCB concentrations (median & IQR) for individual (Environment Canada) and composited (U.S.

Environmental Protection Agency) whole body Lake Trout or Walleye (Lake Erie) collected from each of the Great

Lakes. Dashed lines show loglinear regression model if annual change is significantly different from zero (α =

0.05).

Source: Environment Canada and U.S. Environmental Protection Agency

207

Figure 3

. Total mercury concentrations (median & IQR) for individual (Environment Canada) and composited (U.S.

Environmental Protection Agency) whole body Lake Trout or Walleye (Lake Erie) collected from each of the Great

Lakes. Results of 2-segment linear piecewise regression (solid red line) or log-linear regression (solid blue line) models. Mercury concentrations reported by Schmitt and Brumbaugh (1990) in Lake Michigan Lake Trout also provided.

Source: Environment Canada, U.S. Environmental Protection Agency and Schmitt and Brumbaugh

208

Figure 4

. Median total mercury concentrations in composited Rainbow Smelt collected from the Canadian waters of the Great Lakes by Environment Canada. Lines denote 3 year moving average.

Source: Environment Canada and U.S. Environmental Protection Agency

209

Figure 5

. Mean (± stdev) penta-BDE concentrations in Great Lakes fish measured by Environment Canada, U.S.

Environmental Protection Agency and Zhu & Hites (2004). Solid lines denote significant log-linear regressions.

Dotted lines denote 3 year moving average when log-linear regression is not significant.

Source: Environment Canada and U.S. Environmental Protection Agency

210

Figure 6

. Concentrations of the dominant PBDE congeners (ng/g ww) in whole body Lake Trout and Walleye (U.S.

EPA; Lake Erie) in each of the Great Lakes measured in 2009 relative to the Federal Environmental Quality

Guidelines developed by Environment Canada (red dashed line).

Source: Environment Canada and U.S. Environmental Protection Agency

211

Figure 7

. Temporal trends of PFOS concentrations (geometric mean ± 95% confidence interval) in Lake Ontario

Lake Trout measured by Environment Canada (De Silva, unpublished data) and Ontario Ministry of the

Environment (Furdui et al. 2008).

Source: Environment Canada and U.S. Environmental Protection Agency

Figure 8

. Average synthetic musk concentrations (ng/g ww) in whole body Lake Trout and Walleye (U.S. EPA;

Lake Erie) in each of the Great Lakes measured in 2009.

Source: Environment Canada and U.S. Environmental Protection Agency

212

Contamination in Sediment Cores

Overall Assessment

Status: Fair

Trend: Improving

Rationale: Concentrations of legacy contaminants including PCBs and DDT are generally below guidelines in the

Great Lakes and declining. Other contaminants such as the polybrominated diphenyl ethers (PBDEs) exhibit some exceedances of guidelines, particularly penta-BDE in Lake Ontario; however, temporal trends show recent declines as a result of management actions.

Lake-by-Lake Assessment

Lake Superior

Status: Good

Trend: Unchanging

Rationale: Lake Superior is the largest, coldest and deepest of the Great Lakes; as a result, rates of decreases in concentrations of legacy contaminants are slow. However, typical offshore sediment contaminant concentrations are very low as atmospheric deposition is the primary source. Concentrations of some metals exceed the strictest sediment quality guidelines due to the nature of the watershed (pre-Cambrian shield) and historical regional sources associated with mining and smelting.

Lake Michigan

Status: Not Assessed

Trend: Not Assessed

Rationale: Not Assessed

Lake Huron

Status: Good

Trend: Improving

Rationale: Lake Huron is similar to Lake Superior from a sediment contamination viewpoint, as the lake is large, cold and deep with atmospheric deposition as the primary source of most contaminants. Typical sediment contaminant concentrations are very low. As with Superior, concentrations of some metals exceed the strictest guidelines due to the natural geochemistry of the watershed (pre-Cambrian shield) that results in loadings of compounds such as mercury.

Lake Erie

Status: Fair

Trend: Improving

Rationale: Lake Erie exhibits a definitive spatial gradient in contamination with decreasing concentrations from the western basin to the eastern basin, and from the southern area to the northern area of the central basin.

This spatial distribution in Lake Erie is influenced by industrial activities in the watersheds of major tributaries, including the Detroit River, and areas along the southern shoreline. The shallow nature of the western basin results in resuspended contaminated bottom sediment continuing to influence suspended sediment quality in the water column, while sediment quality in the eastern basin continues to be classified as excellent.

213

Lake Ontario

Status: Fair

Trend: Improving

Rationale: Lake Ontario continues to exhibit the poorest sediment quality of all the Great Lakes. The greatest frequency and magnitude of exceedances of sediment quality guidelines is for polychlorinated dibenzo-

p

-dioxins and dibenzofurans. This legacy contamination issue is the result of historical industrial activities in the Niagara River watershed; however, current levels of dioxin contamination represent a

70 percent decline from peak levels in the 1970s. Trends in most legacy chemicals in Lake Ontario point toward improvement in sediment quality over time.

Purpose

To assess the occurrence, distribution and fate of chemicals in Great Lakes sediments;

To infer potential harm, or pressure, caused by contaminated sediments to Great Lakes aquatic ecosystems;

To assist in identification of sources of chemicals to the Great Lakes.

The Contamination in Sediment Cores indicator is used in the Great Lakes indicator suite as a Pressure indicator in the Pollution and Nutrients top level reporting category.

Ecosystem Objective

The Great Lakes should be free from materials entering the water as a result of human activity that will produce conditions that are toxic or harmful to human health, animal or aquatic life (Great Lakes Water Quality Agreement

(GLWQA) Article IIId, United States and Canada 1987). The GLWQA and the Great Lakes Binational Toxics

Strategy both state the virtual elimination of toxic substances to the Great Lakes as an objective.

Ecological Condition

Bottom sediment contaminant surveys conducted in the Great Lakes from 1968 – 1974, from 1997 – 2002 and more recent surveys provide information on the spatial distribution of contaminants, the impacts of local historical sources and, in concert with sediment cores, the response to management initiatives. Contaminants across several chemical classes are measured in both surface sediment and sediment cores. The measured contaminants with the highest occurrences, causes of degradation of sediment quality and fish consumption restrictions are:

Mercury

PCBs

Dioxins

HCB

Total DDT

Lead

PAHs

Dioxins and Furans

The spatial distribution of mercury contamination in Great Lakes sediments generally represents those of other toxic compounds, both other metals and organics such as PCBs, as accumulation of a broad range of contaminants on a lake-by-lake basis can be the result of common sources, e.g., chlor-alkali production. The highest concentrations of mercury in sediments of lakes Michigan, St. Clair, Erie and Ontario are observed in offshore depositional areas characterized by fine-grained sediments (Figure 1). In the case of lead, the degree of contamination in Lake

Michigan is similar to Lake Ontario. Contaminant concentrations are generally correlated with particle size; hence the distribution of mercury is not only a function of loadings and proximity to sources, but of substrate type and bathymetry. Mercury contamination is generally quite low in lakes Huron, Michigan and Superior and higher in

214

lakes St. Clair, Ontario and the western basin of Lake Erie. There is a gradient in contamination in Lake Erie with decreasing concentrations from the western basin to the eastern basin, and from the southern area to the northern area of the central basin. The spatial distribution in Lake Erie is influenced by industrial activities in the watersheds of major tributaries, including the Detroit River, and areas along the southern shoreline. Sources and loadings of mercury to Lake Huron appear to have been reduced to the point that no apparent spatial pattern exists. Current sediment contamination is substantially lower than peak levels that occurred in the mid – 1950s through the early

1970s. Connecting channels including the Niagara, lower Detroit and upper St. Clair Rivers are associated with historical mercury cell chlor-alkali production; these areas were also intensively industrialized and were primary sources of a variety of persistent toxics to the open lakes, including PCBs. Localized areas of highly contaminated sediment, and/or hazardous waste sites may continue to act as sources of contaminants and influence spatial distributions. Conversely, local sources may no longer be predominant, and spatial patterns may now reflect resuspension, intra-lake mixing and deposition of existing sediment inventories. In this case, further declines would be expected as contaminants are deposited and buried.

Status of Contaminants in Sediment

Sediments in the Great Lakes generally represent a primary sink for contaminants, and can act as a source through resuspension and subsequent redistribution. Conversely, burial in sediments also represents a primary mechanism by which contaminants are sequestered and prevented from re-entering the water column.

Comparisons of surficial sediment contaminant concentrations with sub-surface maximum concentrations indicate that contaminant concentrations have generally decreased by more than 35 per cent, and, in some cases, by as much as 80 per cent over the past four decades (Table 1).

Sediment concentrations can also be assessed against guideline values established for the protection of aquatic biota, e.g., Canadian Sediment Quality Guidelines Probable Effect Level (PEL, CCME, 1999). These guidelines can be applied as screening tools in the assessment of potential risk, and for the determination of relative sediment quality concerns. For metals, PEL guideline exceedances were frequent in Lake Ontario for lead, cadmium and zinc.

Guideline exceedances were rare in all of the other lakes, with the exception of lead in Lake Michigan where the

PEL (91.3

µ g/g) was exceeded at over half of the sites. There were no PEL (277 ng/g total PCBs) guideline exceedances for PCBs in any of the Great Lakes sediments.

The presence of new persistent toxic substances represents a potential threat to the health of the Great Lakes ecosystem. These compounds include perfluoroalklated compounds (PFCs) and brominated flame retardants

(BFRs), the latter of which are heavily used globally in the manufacturing of a wide range of consumer products and building materials. The BFRs have been found to be bioaccumulating in Great Lakes fish and in breast milk of

North American women. While end of the pipe discharges may not be responsible for ongoing contamination, modern urban/industrial centres can act as diffuse sources of current inputs. Sediment core profiles of brominated diphenyl ethers (BDEs) and PFCs in Lake Ontario suggest that accumulation of these chemicals has recently peaked, or continues to increase (Figure 2). The Lake Ontario BDE profile indicates a leveling off of accumulation in the past decade, presumably as a result of voluntary cessation of production of these compounds in North America.

However, the deca-substituted BDE 209 is the predominant congener in sediment, and is still currently used.

Despite these trends, maximum concentrations of many BFRs and PFCs remain well below maximum concentrations of contaminants such as DDT and PCBs observed in past decades.

Assessment of the occurrence and fate of newer compounds has been incorporated into sediment assessment programs. PFCs are a broad range of substances that have attracted much scientific and regulatory interest in recent years as a result of their detection globally in humans and wildlife. PFCs are routinely detected in precipitation and air in urban and rural environments. These compounds have a myriad of applications, but have been primarily used as soil and liquid repellents for papers, textiles and carpeting. Production of PFCs as stain repellents in carpets

215

historically exceeded $1 billion annually. Two classes of PFCs, the perfluoroalkyl sulfonate acids (PFSAs), particularly perfluorooctane sulfonate (PFOS), and the perfluorocarboxylates, particulary perfluorooctanoic acid

(PFOA), are the most commonly measured PFCs; these compounds are highly stable and persistent in the environment, and are potentially toxic. PFCs have been detected in environmental samples far from urban areas, including remote areas such as the Canadian Arctic. The physical and chemical properties of PFCs are different from many other semi-volatile pollutants that can significantly influence their pathways through the environment.

Concentrations of PFCs in sediments of Great Lakes tributaries are highest in urbanized and/or industrialized watersheds. In general levels of perfluoroalkyl sulfonate acids and PFOS in tributaries (Figure 3) and open waters of the Great Lakes are slightly higher than the perfluorocarboxylates with the highest levels of PFCs generally found in areas of Lake Ontario and the western end of Lake Erie and the Detroit River corridor. There is a gradient toward increasing PFC contamination from the upper Great Lakes (Superior and Huron) to the lower Great Lakes (Erie and

Ontario) for both tributary and open-lake sediments (Figures 3 and 4). Concentrations of PFCs in open-lake sediments are driven not only by proximity to sources, but physical processes and bathymetry as well. The highest

PFC concentrations in open-lake sediments were found in Lake Ontario. The spatial distributions of PFCs in Lake

Ontario are fairly consistent across the lake, which is primarily due to lake currents that evenly distribute suspended particles and across the three major depositional basins.

The spatial distributions of PFCs in Great Lakes sediments are heavily influenced by shoreline-based urban and industrial activities, which in some cases stand in contrast to distributions of legacy contaminants such as PCBs.

These results suggest that large urban areas can act as diffuse sources of PFCs associated with modern industrial and consumer products, and therefore management action should focus on prevention of pollutant emissions from consumer and industrial products.

Management Challenges/Opportunities

Management efforts to control inputs of historical contaminants have resulted in decreasing contaminant concentrations in the Great Lakes open-water sediments for the standard list of chemicals. However, chemicals such as BFRs and current-use pesticides may represent emerging issues and potential future stressors to the ecosystem.

These results corroborate observations made globally, which indicate that large urban centers act as diffuse sources of chemicals that are heavily used to support our modern societal lifestyle.

Linkages

Sediment contamination affects both water quality and aquatic dependent life. Sediment is a source of mercury and other toxic chemicals to enter the water column. These chemicals are components of the indicators in the top level categories of Water Quality, Aquatic Dependent Life, Fish & Wildlife, and Restoration & Protection. Relevant indicators include “Toxic chemicals in offshore waters”, water quality as measured by contaminants in whole fish, water birds, and bald eagles, “Fish disease occurrences,” and “Sediment remediation.”

Comments from authors

Long-term research and monitoring programs are valuable tools for demonstrating effectiveness of remedial actions and management initiatives, as well as acting as indicators of emerging issues. Government agencies in both the

United States and Canada are formulating plans for future sediment core work, including the requirements for adequate numbers of samples to enable an accurate assessment of both spatial distributions and temporal trends.

In order to properly assess Lake Michigan, the sediment indicator team needs a consistent U.S. partner. Over the years, U.S. EPA has typically provided a member, however the turnover has been high and in recent years Canadian sediment indicator team had no support. As a result, an assessment of Lake Michigan without the input from the

U.S. perspective was not undertaken.

216

Assessing Data Quality

Data Characteristics

1. Data are documented, validated, or quality-assured by a recognized agency or organization

2. Data are traceable to original sources

3. The source of the data is a known, reliable and respected generator of data

4. Geographic coverage and scale of data are appropriate to the Great Lakes basin

5. Data obtained from sources within the

U.S. are comparable to those from

Canada

6. Uncertainty and variability in the data are documented and within acceptable limits for this indicator report

Strongly

Agree

x x x x

Agree

x x

Acknowledgments

Authors:

Debbie Burniston, Environment Canada, Burlington, ON

Chris Marvin, Environment Canada, Burlington, ON

Neutral or

Unknown

Disagree

Strongly

Disagree

Not

Applicable

Information Sources

Environment Canada Great Lakes Fact Sheet. Polybrominated diphenyl ethers in sediments of tributaries and openwater areas of the Great Lakes. Catalogue No. En84-70/2009E.

Environment Canada Great Lakes Fact Sheet. Perfluoroalkyl compounds in sediments of tributaries and open-water areas of the Great Lakes. ISBN No. 978-1-100-145025-4.

Environment Canada Great Lakes Fact Sheet. Contaminants in sediments of Canadian tributaries and open-water areas of the lower Great Lakes. ISBN No. 978-0-662-46896-7.

List of Tables

Table 1.

Estimated percentage declines in sediment contamination in the Great Lakes (1970 – 2010) based on comparison of surface sediment concentrations with maximum concentrations at depth in sediment cores.

Source: Environment Canada.

List of Figures

Figure 1.

Spatial distribution of mercury contamination in surface sediments in open lake areas and tributaries of the Great Lakes.

Source: Environment Canada and USEPA.

Figure 2.

Core profiles of perfluoroalkyl subtances (PFAS) and brominated diphenyl ethers (BDEs) is sediment cores from the central (Mississauga Basin) basin of Lake Ontario.

Source: Environment Canada and Ontario Ministry of the Environment.

Figure 3

. Total PFSAs perfluoroalkyl sulfonate acids (PFSAs) and perfluorooctane sulfonate (PFOS) concentrations in surficial sediments in tributaries of the Great Lakes.

Source: Environment Canada and the Ontario Ministry of the Environment.

Figure 4.

Total PFSAs perfluoroalkyl sulfonate acids (PFSAs) and perfluorooctane sulfonate (PFOS) concentrations in surficial sediments of open-water areas of the Great Lakes.

Source: Environment Canada and the Ontario Ministry of the Environment.

217

Last Updated

State of the Great Lakes 2011

Estimated percentage declines in sediment contamination

Parameter

Lake Ontario

%Reduction

Lake Erie

%Reduction

Lake St. Clair

%Reduction

Mercury 73 37 89

PCBs 37 40 49

Lake Huron

%Reduction

82

45

Lake Superior

%Reduction

0

15

Dioxins

HCB

Total DDT

Lead

70

38

60

45

NA

72

42

50

NA

49

78

74

NA

NA

93

43

NA

NA

NA

10

Table 1.

Estimated percentage declines in sediment contamination in the Great Lakes (1970 – 2010) based on comparison of surface sediment concentrations with maximum concentrations at depth in sediment cores.

Source: Environment Canada

Figure 1

. Spatial distribution of mercury contamination in surface sediments in open-lake areas and tributaries of the Great Lakes.

Sources: Environment Canada and USEPA.

218

Figure 2.

Core profiles of perfluoroalkyl compounds (PFCs) and polybrominated diphenyl ethers (PBDEs) in sediment cores from the central (Mississauga Basin) basin of Lake Ontario.

Sources: Environment Canada and Ontario Ministry of the Environment.

219

Figure 3.

Total PFSAs perfluoroalkyl sulfonate acids (PFSAs) and perfluorooctane sulfonate (PFOS) concentrations in surficial sediments in tributaries of the Great Lakes.

Source: Environment Canada and the Ontario Ministry of the Environment.

Figure 4.

Total PFSAs perfluoroalkyl sulfonate acids (PFSAs) and perfluorooctane sulfonate (PFOS) concentrations in surficial sediments of open-water areas of the Great Lakes.

Source: Environment Canada and the Ontario Ministry of the Environment.

220

Diporeia

Overall Assessment

Status: Poor

Trend: Deteriorating

Rationale: Abundances of the benthic amphipod Diporeia spp. continue to decline in Lake Michigan, Lake

Huron, and Lake Ontario. Abundances in Lake Superior are variable but overall trends are stable. Diporeia are currently extirpated or very rare in Lake Erie.

Lake-by-Lake Assessment

Lake Superior

Status: Good

Trend: Unchanging

Rationale: Long- term monitoring of populations in deeper regions of the lake indicate that, although substantial interannual variability can occur, there are not directional trends in abundances of

Diporeia

in the lake.

Other studies have shown abundances in shallower regions remain high.

Lake Michigan

Status: Poor

Trend: Deteriorating

Rationale:

Diporeia

abundances continue to decline in Lake Michigan. A lakewide survey in 2010 indicated that

Diporeia

are now rarely found at depths < 90 m (297 ft.) over the entire lake (Fig. 1). At depths > 90 m, abundances in 2010 were lower by 66 % compared to abundances found in 2005. While the trend remains downward at these deeper depths, more intensive temporal surveys (yearly) indicate that the rate of decline has slowed in recent years.

Lake Huron

Status: Poor

Trend: Deteriorating

Rationale:

Diporeia

abundances continue to decline in Lake Huron. The most recent survey lakewide survey occurred in 2007, and abundances were lower by 93 % compared to a similar survey in 2000. Long- term monitoring of abundances on a more limited spatial scale indicated that in 2009

Diporeia

were rarely found at sites < 90 m, and abundances at sites > 90 m were trending downward.

Lake Erie

Status: Poor

Trend: Deteriorating

Rationale: Because of shallow, warm waters,

Diporeia

are naturally not present in the Western and most of the

Central basins.

Diporeia

declined in the Eastern basin beginning in the early 1990s and have not been found since 1998.

Lake Ontario

Status: Poor

Trend: Deteriorating

Rationale:

Diporeia

abundances continue to decline in Lake Ontario. Based on limited sampling in 2009 – 2010, abundances were 97 % lower than abundances found in 1995.

In 2010

, Diporeia

were completely gone from most areas of the lake at depths less than 150 m, and were absent for the first time at a deep midlake site (Fig. 2). It is obvious that the deep, offshore region of Lake Ontario is no longer providing a

221

refuge for

Diporeia

. Limited spatial data indicated a population was still surviving near the Niagara

River at depths between 80 and 110 m.

Purpose

To provide a measure of the biological integrity of the offshore regions of the Great Lakes by assessing the

• abundance of the benthic macroinvertebrate

Diporeia

The

Diporeia

indicator is used in the Great Lakes indicator suite as a State indicator in the Aquatic-dependent life top level reporting category.

Ecosystem Objective

The ecosystem goal is to maintain a healthy, stable population of

Diporeia

in offshore regions of the main basins of the Great Lakes, and to maintain at least a presence in nearshore regions.

Ecological Condition

This glacial-marine relic was once the most abundant benthic organism in cold, offshore regions (greater than 30 m

(98 ft) of each of the lakes. It was present, but less abundant in nearshore regions of the open lake basins, but naturally absent from shallow, warm bays, basins, and river mouths.

Diporeia

occurs in the upper few centimeters of bottom sediment and feeds on algal material that freshly settles to the bottom from the water column (i.e., mostly diatoms). In turn, it is fed upon by most species of Great Lakes fish; in particular by many forage fish species, which themselves serve as prey for the larger piscivores such as trout and salmon. For example, sculpin feed almost exclusively upon

Diporeia

, and sculpin are eaten by lake trout. Also, lake whitefish, an important commercial species, feeds heavily on

Diporeia

. Thus,

Diporeia

was an important pathway by which energy was cycled through the ecosystem, and a key component in the food web of offshore regions. The importance of this organism is recognized in the Great Lakes Water Quality Agreement: Supplement to Annex 1 – Specific Objectives (United

States and Canada 1987).

On a broad scale, abundances are directly related to the amount of food settling to the bottom, and population trends reflect the overall productivity of the ecosystem. Abundances can also vary somewhat relative to shifts in predation pressure from changing fish populations. In nearshore regions, this species is sensitive to local sources of pollution.

Diporeia

populations are currently in a state of dramatic decline in Lake Michigan (Figure 1), Lake Ontario (Figure

2), and Lake Huron, and they are completely gone or very rare in Lake Erie. The population in Lake Superior, although highly variable, remains unchanged. Initial declines were first observed in all lake areas within two to three years after zebra mussels (

Dreissena polymorpha

) or quagga mussel (

Dreissena bugensis

) first became established. These two species were introduced into the Great Lakes in the late 1980s via the ballast water of oceangoing ships. Reasons for the negative response of

Diporeia

to these mussel species are not entirely clear. One hypothesis is that dreissenid mussels are out-competing

Diporeia

for available food. That is, large mussel populations filter food material before it reaches the bottom, thereby decreasing amounts available to

Diporeia

.

However, evidence suggests that the reason for the decline is more complex than a simple decline in food because

Diporeia

have completely disappeared from areas where food is still settling to the bottom and where there are no local populations of mussels. Also, individual

Diporeia

show no signs of starvation before or during population declines. Further,

Diporeia

and

Dreissena

apparently coexist in some lakes outside of the Great Lakes (i.e., Finger

Lakes in New York).

Management Challenges/Opportunities

The continuing decline of

Diporeia

has strong implications to the Great Lakes food web. As noted, many fish species rely on

Diporeia

as a major prey item, and the loss of

Diporeia

will likely have an impact on these species.

Responses may include changes in diet, movement to areas with more food, or a reduction in weight or energy content. Implications to populations include changes in distribution, abundance, growth, recruitment, and condition.

222

Recent evidence suggests that fish are already being affected. For instance, growth and condition of an important commercial species, lake whitefish, has declined significantly in areas where

Diporeia

abundances are low in Lake

Michigan, Lake Huron, and Lake Ontario. Also, studies show that other species such as alewife, slimy sculpin, and bloater have been affected. Management agencies must know the extent and implications of these changes when assessing the current state and future trends of the fishery. Any proposed rehabilitation of native fish species, such as the re-introduction of deepwater ciscoes in Lake Ontario, requires knowledge that adequate food, especially

Diporeia

, is present.

Comments from the author(s)

Because of the rapid rate at which

Diporeia

populations have declined in many areas, and their significance to the food web, agencies committed to documenting trends should report data in a timely manner. The population decline has a defined natural pattern, and studies of food web impacts should be spatially well coordinated. Also, studies to define the cause of the negative response of

Diporeia

to

Dreissena

should continue and build upon existing information. With an understanding of exactly why

Diporeia

populations are declining, we may better predict what additional areas of the lakes are at risk. Also, by better understanding the cause, we may better assess the potential for population recovery if and when dreissenid populations stabilize or decline.

Assessing Data Quality

Data Characteristics

1. Data are documented, validated, or quality-assured by a recognized agency or organization

2. Data are traceable to original sources

3. The source of the data is a known, reliable and respected generator of data

4. Geographic coverage and scale of data are appropriate to the Great Lakes basin

5. Data obtained from sources within the

U.S. are comparable to those from

Canada

6. Uncertainty and variability in the data are documented and within acceptable limits for this indicator report

Strongly

Agree

X

X

X

X

X

X

Agree

Neutral or

Unknown

Disagree

Strongly

Disagree

Not

Applicable

Acknowledgments

Authors:

T. F. Nalepa, Great Lakes Environmental Research Laboratory, National Oceanic and Atmospheric Administration,

Ann Arbor, MI

R. Dermott, Great Lakes Laboratory for Fisheries and Aquatic Sciences, Fisheries and Oceans Canada, Burlington,

ON

List of Figures

Figure 1

. Distribution and density (number per square meter) of the amphipod

Diporeia

spp. in Lake Michigan in

1994/95, 2000, 2005, and 2010. Small crosses indicate location of sampling sites.

Source: Great Lakes Environmental Research Lab, National Oceanic and Atmospheric Administration. USA.

Figure 2

. Distribution and density (number per square meter) of the amphipod

Diporeia

spp. in Lake Ontario in

1995, 2003, 2005, 2007, and 2009/10. Averages derived from all stations sampled that year; small crosses indicate stations not visited.

Source: Great Lakes Lab. for Fisheries & Aquatic Sciences, Fisheries and Oceans, Canada.

223

Last Updated

State of the Great Lakes 2011

Figure 1

. Distribution and density (number per square meter) of the amphipod

Diporeia

spp. in Lake Michigan in

1994/95, 2000, 2005, and 2010. Small crosses indicate location of sampling sites.

Source: Great Lakes Environmental Research Lab, National Oceanic and Atmospheric Administration. USA.

224

Figure 2

. Distribution and density (number per square meter) of the amphipod

Diporeia

spp. in Lake Ontario in

1995, 2003, 2005, 2007, and 2009/10. Averages derived from all stations sampled that year; small crosses indicate stations not visited.

Source: Great Lakes Lab. for Fisheries & Aquatic Sciences, Fisheries and Oceans, Canada.

225

Dreissenid Mussels – Zebra and Quagga mussels

Overall Assessment

Status: Fair

Trend: Deteriorating

Rationale: Over all the Great Lakes, dreissenid mussels are changing at various rates depending on the particular lake, and the particular area within a lake. Currently, quagga mussels (profunda phenotype) are replacing zebra mussels and reaching high abundances in some shallow, nearshore areas, and are also expanding into deep, offshore areas. In other shallow areas, quagga mussel populations (shallow phenotype) are stable and zebra mussels are still present. The offshore region comprises a relatively large proportion of many lakes where quagga mussels are still expanding at a rapid rate (i.e., Lakes

Michigan, Ontario, and Huron). Therefore, the current overall assessment indicates a deteriorating status.

Lake-by-Lake Assessment

Lake Superior

Status: Good

Trend: Unchanging

Rationale: Zebra mussels were first found in Duluth-Superior Harbor in 1989, and quagga mussels were found in the same area in 2005. Since then, spread and population growth of both dreissenid species has been minimal. Both species are most abundant and primarily confined in harbor areas or the nearshore areas of Lake Superior. Some zebra mussels, however, were found in 2009 in a bay of Isle Royale, and were also present in Thunder Bay harbor in 2001. Overall, population growth and spread of both species has been slow. It is believed that calcium concentrations in Lake Superior are too low to support high abundances.

Lake Michigan

Status: Poor

Trend: Deteriorating

Rationale: A recent survey throughout Lake Michigan (2010) indicated that the quagga mussel population expanded greatly since the last survey (2005), and that zebra mussels are now very rare. Based on yearly sampling just in the southern basin, the quagga mussel population at depths < 90 m has apparently stopped increasing and is beginning to decline, but is still increasing at depths > 90 m

(Figure 1). Biomass is presently declining at < 50 m, but still increasing at > 50 m (Figure 2).

Maximum biomass at < 50 m reached 45 g m

-2 in 2008.

Lake Huron

Status: Poor

Trend: Deteriorating

Rationale: The last lake-wide survey of dreissenid populations in Lake Huron occurred in 2007. This survey indicated abundances of quagga mussels increased between 2003 and 2007, but zebra mussels decreased and were rarely found. Between 2003 and 2007, quagga mussels increased 1.6-4.0-fold at depths between 30 and 90 m in the main lake. Similar increases were found in Georgian Bay, but dreissenids were not found in North Channel. Biomass was not determined in any of these regions. Surveys in

Saginaw Bay in 2008-2010 indicated that mean abundance and biomass had decreased 1.6-1.7 fold compared to 1991-1996. In addition, year-to-year variation in 2008-2010 was minimal, indicating that the population had perhaps stabilized at these lower levels. In 2008-2010 the population in Saginaw

Bay consisted of 80% quagga mussels and 20% zebra mussels.

226

Lake Erie

Status: Fair

Trend: Undetermined

Rationale: The last lake wide survey in Lake Erie occurred in 2002. Mean abundances in that year were little changed since 1992 (2,025 m

-2

in 2002 compared to 2,636 m

-2

in 1992), but mean biomass increased 4fold (24.7 g m

-2

in 2002 compared to 6.8 g m

-2

in 1992). Most dreissenid biomass (90%) occurs in the eastern basin. Populations in the central basin are limited because of seasonal hypoxia, and populations in the western basin are limited because of poor food quality (cyanophytes, inorganic particulates).

Recent surveys (2005-2010) in the western basin indicate that dreissenid populations have fluctuated from year-to-year with no clear trends, and that quagga mussels have replaced zebra mussels as the dominant species (Figure 3). Recent trends in the eastern basin are unknown.

Lake Ontario

Status: Fair

Trend: Deteriorating

Rationale: Since 2007,

Dreissena

abundance has been stable or slowly increasing based on data from offshore surveys at depths beyond 30 m (Figure 4). Since 2000, all mussels collected in the offshore portions of Lake Ontario have been quagga mussels. Zebra mussels are restricted to shallow embayments such as the upper Bay of Quinte and inside Hamilton Harbor. Quagga mussels have slowly increased at depths beyond 100 m. Since 2008, they have been present in the deepest part of the lake (224 m), as well as at the middle of the lake. Densities are greatest nearest the south shore, often exceeding 5000 m

-2

, but are as large as 400 m

-2

at 150 m. The population in the east basin of Lake Ontario near Main Duck Island (35 m) has been stable since 2007, and is composed mostly of large individuals greater than 15 mm in length. There, the wet biomass of their soft tissue has ranged between 300 and 450 g m

-2

(shell-free). Assuming dry weight is about

10% of wet weight, this is equivalent to 30-45 g m

-2

dry weight and hence generally similar to the maximum of 45 g m

-2

found at 31-50 m in southern Lake Michigan.

Purpose

To track the status and trends of

Dreissena rostriformis bugensis

(quagga mussel) and

Dreissena polymorpha

(zebra mussel). Instability in dreissenid populations, as measured by abundance and biomass, results in uncertainties in resource management.

The Dreissenid Mussels indicator is used in the Great Lakes indicators suite as a Pressure indicator in the

Invasive Species top level reporting category.

Ecosystem Objective

Dreissenids are actively changing the integrity of Great Lakes ecosystems by altering nutrient and energy cycling, promoting nuisance algal blooms and benthic algae, and negatively impacting native species of invertebrates and fish. Such changes to ecosystem integrity create uncertainty in effective resource management. Thus, the indicator addresses the objective of maintaining healthy and sustainable ecosystems.

Measure

Ideally, specific measures to be reported are dreissenid abundances, biomass, size-frequency distributions, and length-weights. The latter two measures are essential for the most efficient determination of biomass, and also provide a basis for assessing the relative status of populations and individuals, respectively. As a minimum indicator, abundances of both zebra and quagga mussels should be reported. Spatial scales should be each lake, and any particular bay or basin within a lake. Often trends in zebra and quagga mussels can be quite different depending on environmental conditions. The entire suite of measurements listed above will be reported for additional scales.

227

At the minimum, spatially intensive studies of dreissenid abundance should be conducted once every five years in conjunction with other programs associated with the lake wide intensive monitoring program. More frequent sampling (yearly) is recommended in areas that are newly colonized or subjected to new perturbations, such as a new invader.

Status Justification

Good

– no or few mussels with a slow rate of change

Fair

– moderate abundance or now declining from a higher abundance or moderate abundance but slow rate of increase

Poor

– high abundance and/or a fast increase

Endpoint

A quantitative endpoint has not yet been determined. A proposed endpoint of zero dreissenids is unrealistic. A working qualitative endpoint is the point in time and space in which a dreissenid population becomes stable, or varies within a given range. Such an endpoint will allow for the modeling of dreissenid population dynamics and inputs to predictive ecosystem models. Such models are a necessary precursor to effective resource management.

Ecological Condition

Dreissenid populations in the Great Lakes are presently in various stages of change. In many offshore regions, populations are increasing, but in some near shore regions populations seem to be stable or declining. While some year-to-year variability can be expected, a goal of this indicator is to determine at what level of abundance/biomass populations become stable and at equilibrium with the surrounding environment. Such levels, along with associated degrees of uncertainty, can then be used in predictive models to better manage Great Lakes resources.

Many sampling efforts have sought to provide data on population abundances and biomass. While abundances are the most common reporting measure of population status, biomass is more valuable for assessing ecological impacts and for input to predictive models. Biomass is calculated from the soft tissue of these organisms. Some protocols call for separating soft tissue from shell and directly determining soft tissue weight, while others determine the size frequency of the populations (shell length) and infer tissue biomass based upon a predetermined relationship between shell length and soft tissue weight. Data used to obtain biomass with the latter protocol can also be used to assess population dynamics and predict the direction of populations over time. For example, a population with a large number of individuals and a size distribution skewed toward smaller individuals demonstrates high recruitment and possibly low survivability (or if survivability is not compromised then it may illustrate recent colonization). In contrast, population showing a size-frequency distribution skewed towards larger individuals with fewer numbers suggests an aging population with relatively lower recruitment and greater survivability. Traditional population ecology suggests that stable populations move from a size-frequency distribution of low mean biomass towards one of higher mean biomass. As a population colonizes a new area, high resource availability promotes high recruitment. As resources are sequestered into the population, recruitment decreases with decreasing resource availability and mean biomass increases as fewer new (low biomass) individuals are added to the population and surviving members continue to grow.

Management Challenges/Opportunities

The main issue which compromises this indicator is the presence or absence of a commitment by agencies to monitor dreissenids on a regular basis. U.S. EPA Great Lakes National Program Office monitors benthos annually, but the spatial scope emphasizes deeper regions. The regular monitoring of Environment Canada does not include benthos. Sampling by Fisheries and Oceans Canada on Lake Ontario is sporadic. NOAA has supported dreissenid monitoring throughout Lakes Michigan and Huron every five years, and in the southern basin of Lake Michigan every year, but it is uncertain whether this support will continue.

228

Comments from the author(s)

Because of the rapid rate at which

Dreissena

populations have expanded in many areas, and because of the ability of dreissenids to cause ecosystem-wide changes, agencies committed to documenting trends should report data in a timely manner. Besides abundance, biomass should be routinely monitored. This allows comparisons across lakes and other food web components, and is most useful for predictive models. Since dreissenids are found on hard as well as on soft substrates, various sampling methods may be needed to truly assess population mass in a given lake or lake region.

Assessing Data Quality

Data Characteristics

1. Data are documented, validated, or quality-assured by a recognized agency or organization

2. Data are traceable to original sources

3. The source of the data is a known, reliable and respected generator of data

4. Geographic coverage and scale of data are appropriate to the Great Lakes basin

5. Data obtained from sources within the

U.S. are comparable to those from

Canada

6. Uncertainty and variability in the data are documented and within acceptable limits for this indicator report

Strongly

Agree

X

X

X

X

X

Agree

Neutral or

Unknown

X

Disagree

Strongly

Disagree

Not

Applicable

Acknowledgments

Authors:

T. F. Nalepa, Great Lakes Environmental Research Laboratory, National Oceanic and Atmospheric Administration,

Ann Arbor, MI

R. Dermott, Great Lakes Laboratory for Fisheries and Aquatic Sciences, Fisheries and Oceans Canada, Burlington,

ON

C. Madenjian, Great Lakes Science Center, U. S. Geological Survey, Ann Arbor, MI

D. W. Schloesser, Great Lakes Science Center, U. S. Geological Survey, Ann Arbor, MI

Information Sources

Bunnell, D. B., Madenjian, C. P., Holuszko, J. D., Adams, J. V., and French, J. R. P. III. 2009. Expansion of

Dreissena

into offshore waters of Lake Michigan and potential impacts on fish populations. J. Great Lakes

Res. 35: 74-80.

French, J. R. P. III, Schaeffer, J. S., Roseman, E. F., Kiley, C. C., Fouilleroux. 2009. Abundance and distribution of benthic macroinvertebrates in offshore soft sediments in Western Lake Huron, 2001-2007. J. Great Lakes

Res. 35: 120-127.

Grigorovich, I. A., Korniushin, A. V., Gray, D. K., Duggan, J. C., Colautti, R. I., and MacIsaac, H. J. 2003. Lake

Superior: and invasion coldspot? Hydrobiology 499:191-210.

Nalepa. T. F., Fanslow, D. L., Pothoven, S. A., Foley, A. J. III, and Lang, G. A. 2007. Long-term trends in benthic macroinvertebrate populations in Lake Huron over the past four decades. J. Great Lakes Res. 33: 421-436.

Nalepa, T. F., Fanslow, D. Pothoven, S. A. 2011. Recent changes in density, biomass, recruitment, size structure, and nutritional state of

Dreissena

populations in southern Lake Michigan. J. Great Lakes Res. 36 (Suppl.

3): 5-19.

Patterson, M. R., Ciborowski, J. J. H., and Barton, D. R. 2005. The distribution and abundance of

Dreissena

species

(Dreissenidae) in Lake Erie, 2002. J. Great Lakes Res. 31 (Suppl.2): 223-237.

229

Soster, F. M., McCall, P. L., and Herrman, K. A. 2011. Decadal changes in the benthic invertebrate community in western Lake Erie between 1981 and 2004.

List of Figures

Figure 1

. Mean (± SE) abundance (number per square meter) of the

Dreissena

population in each of four depth interval s at 40 stations in the southern basin of Lake Michigan between 1980 and 2010. The number of stations in each depth interval was 16-30 m = 12, 31-50 = 10, 51-90 m = 12, > 90 m = 6. solid circle/solid line = zebra mussel; open circle/dashed line = quagga mussel.

Source: Great Lakes Environmental Research Lab, NOAA

Figure 2

. Mean (± SE) biomass (grams per square meter) of the

Dreissena

population in each of four depth intervals at 40 stations in the southern basin of Lake Michigan between 1980 and 2010. Biomass is given as shellfree dry weight. The number of stations in each depth interval was 16-30 m = 12, 31-50 = 10, 51-90 m = 12, > 90 m

= 6. solid circle/solid line = zebra mussel; open circle/dashed line = quagga mussel.

Source: Great Lakes Environmental Research Lab, NOAA

Figure 3

. Percentage of sites with

Dreissena

(top panel) and mean abundance of

Dreissena

(number per square meter) (bottom panel) in western Lake Erie between 1991 and 2010; n=30. Source: Great Lakes Science Center,

USGS

Figure 4

. Distribution and mean abundance (number per square meter) of the

Dreissena

population (zebra and quagga mussels) in Lake Ontario between 1995 and 2009. Small crosses indicate stations not visited. Ave. = average abundance for all stations sampled that year.

Source: Great Lakes Lab. for Fisheries & Aquatic Sciences, DFO

Last Updated

State of the Great Lakes 2011

230

Figure 1

. Mean (± SE) abundance (number per square meter) of the

Dreissena

population in each of four depth interval s at 40 stations in the southern basin of Lake Michigan between 1980 and 2010. The number of stations in each depth interval was 16-30 m = 12, 31-50 = 10, 51-90 m = 12, > 90 m = 6. solid circle/solid line = zebra mussel; open circle/dashed line = quagga mussel.

Source: Great Lakes Environmental Research Lab, NOAA

231

Figure 2

. Mean (± SE) biomass (grams per square meter) of the

Dreissena

population in each of four depth intervals at 40 stations in the southern basin of Lake Michigan between 1980 and 2010. Biomass is given as shell-free dry weight. The number of stations in each depth interval was 16-30 m = 12, 31-50 = 10, 51-90 m = 12, > 90 m = 6. solid circle/solid line = zebra mussel; open circle/dashed line = quagga mussel.

Source: Great Lakes Environmental Research Lab, NOAA

232

Figure 3

. Percentage of sites with

Dreissena

(top panel) and mean abundance of

Dreissena

(number per square meter) (bottom panel) in western Lake Erie between 1991 and 2010; n=30.

Source: Great Lakes Science Center, USGS

233

Figure 4

. Distribution and mean abundance (number per square meter) of the

Dreissena

population (zebra and quagga mussels) in Lake Ontario between 1995 and 2009. Small crosses indicate stations not visited. Ave. = average abundance for all stations sampled that year.

Source: Great Lakes Lab. for Fisheries & Aquatic Sciences, DFO

234

Drinking Water Quality

Overall Assessment

:

Status: Good

Trend: Unchanging

Rationale: The overall quality of source and finished drinking water in the Great Lakes basin can be considered good. The potential risk of human exposure to the noted chemical and/or microbiological contents, and any associated health effect, is generally low.

Lake-by-Lake Assessment

Each lake was categorized with a not assessed status and an undetermined trend, indicating that assessments were not made on an individual lake basis.

Other Spatial Scales

No other spatial scales were used in this indicator.

Purpose

To evaluate the potential for human exposure to drinking water contaminants and the effectiveness of policies and technologies to ensure safe drinking water throughout the Great Lakes basin

To evaluate the chemical and microbial contaminant levels in source and treated water.

The Drinking Water Quality indicator is used in the Great Lakes indicator suite as an Impacts indicator under the Human Impacts top level reporting category.

Ecosystem Objective

Treated and source drinking water supplies in the Great Lakes basin should be free from harmful chemical and microbiological contaminants and should be safe to drink. This indicator supports the restoration and maintenance of the chemical, physical and biological integrity of the Great Lakes basin (GLWQA Annex 1, 2, 12 and 16).

Ecological Condition

Background

There are several sources of drinking water within the Great Lakes basin, including the Great Lakes themselves, smaller lakes and reservoirs, streams, ponds and groundwater (seeps and wells). These systems are vulnerable to contamination from several sources (chemical, biological, radioactive). Substances that may be present in source water include microbial contaminants (e.g. viruses and bacteria), inorganic contaminants (e.g. salts and metals), pesticides and herbicides, organic chemical contaminants (e.g. synthetic and volatile organic chemicals), and radioactive contaminants. After collection, source water undergoes a detailed treatment process prior to being sent to a distribution system where it is dispersed to consumers. The treatment process involves several basic steps, which are often varied and repeated depending on the condition of the source water. Source water can affect the finished water that is consumed. Good quality source water is an important approach to assuring the safety and quality of drinking water.

The information provided by the United States for this report focuses on finished, or treated, drinking water. There is currently no national drinking water database in the U.S. that includes source water data. In the United States, the

Safe Drinking Water Act Reauthorization of 1996 requires all drinking water utilities to provide yearly water quality information to their consumers. To satisfy this obligation, U.S. WTPs produce an annual Consumer

Confidence/Water Quality Report (CC/WQR). These reports provide information regarding source water type (i.e. surface water, groundwater), the availability of source water assessment and a brief summary of the drinking water systems susceptibility to potential sources of contamination, the water treatment process, contaminants detected in

235

finished drinking water, and violations that occurred, and other relevant information. Records of the number and type of health based violations are also recorded in the nationwide U.S. EPA Safe Drinking Water Information

System (SDWIS). Health based violations in the U.S. include: Maximum Contaminant Level (MCL) which is the highest level of a contaminant that is allowed in drinking water, the Maximum Residual Disinfectant Level (MRDL) which is the highest level of a disinfectant allowed in drinking water, and Treatment Technique (TT) which is a required process intended to reduce the level of contaminants in drinking water.

The data used for the Canadian component of this report was provided by the Ontario Ministry of the Environment

(OMOE) and includes results from two program areas. Source water data is collected as part of the Drinking Water

Surveillance Program (DWSP). The DWSP is a voluntary partnership program with municipalities that monitors source and treated water quality at over 100 systems in Ontario. The Drinking Water Management Division at

OMOE provides information on adverse water quality incidents (AWQI). An AWQI is when a water sample exceeds the Ontario Drinking Water Quality Standards or when an operator observes unsafe water. The Ontario

Drinking Water Quality Standards are described by the Maximum Acceptable Concentration (MAC), which is established for parameters that, when present above a certain concentration, have known or suspected adverse health effects. The Interim Maximum Acceptable Concentration (IMAC) is used for parameters when there is insufficient toxological data or it is not feasible for practical reasons to establish a MAC.

Status of Drinking Water in the Great Lakes Basin

Established drinking water standards were used to assess the quality of source and treated drinking water quality in the Great Lakes basin. Potential health effects may occur from long term exposure above these drinking water standards.

Source (Untreated) Drinking Water Quality

Nine chemical drinking water parameters that frequently result in water quality exceedences and which have potential health effects associated with exposure above the established MAC/IMAC, were selected to provide an assessment of source drinking water quality in Ontario from 2007 to 2009. As stated previously, no source water data was assessed in the U.S. due to the lack of centrally located source. The percentage of drinking water systems monitored through the DWSP where source water is below the MAC/IMAC was used as the metric.

Six of the nine chemical drinking water parameters were never detected above the MAC/IMAC in source waters

(Table 1). These parameters included nitrate, nitrite, atrazine, arsenic, uranium and barium. Fluoride, lead and selenium were the only parameters that had concentrations exceeding the MAC/IMAC in source waters.

Exceedences of these chemical parameters were only found in a few groundwater systems and may be the result of erosion of natural deposits and/or anthropogenic contamination. The percentage of sites and the actual drinking water systems with fluoride and selenium source water exceedences did not change over the time period (Table 1).

Lead was the only parameter the percent of exceedences decreased over time, with none occurring in 2009 (Table

1).

Overall, source water quality is good in Ontario in regards to these selected chemical parameters. There were only four drinking water systems, all sourced from groundwater, where the MAC/IMAC was exceeded and at two of these sites the concentrations in treated and distributed water were below the MAC/IMAC.

Treated Drinking Water Quality

Treated drinking water was assessed for all community drinking water systems in U.S. Great Lakes basin counties and for all municipal residential drinking water systems in Ontario. Metrics were slightly different between countries due to differences in the way data is recorded and stored in their respective databases. In the U.S. the average percentage of drinking water systems and population that did not have any health based violations was used as metrics. In Ontario the percentage of drinking water systems that did not have any health based violations and the percentage of drinking water tests meeting standards were used as metrics.

236

In the U.S. the average percentage of drinking water systems and population that did not have any health based violations has remained mostly unchanged between 2007 and 2010, with the average percentage of community water systems with no exceedences consistently exceeding 90% (Figure 1). The percentage of the population with no violations was a little more variable but, on average, exceeded 90% (Figure 1). These numbers are similar to the national average in the U.S.

In Ontario the average percentage of drinking water systems that did not have any health based violations increased between 2004 and 2010 while the percentage of drinking water systems that met drinking water standards less that

99% of the time decreased (Figure 2). Over the past three years the percentage of drinking water systems with no exceedences has been fairly stable at around 65% and 96% of drinking water systems meet standards greater than

99% of the time. The average percentage of drinking water tests meeting standards in Ontario has increased slightly between 2004 and 2010 but has always exceeded 99.7% (Figure 3).

The proportion of health based exceedences caused by chemical, microbiological, radiological, disinfection byproducts and treatment techniques differs between countries. The majority of exceedences in Ontario are microbiological while in the U.S. microbiological, chemical and disinfection by-product exceedences co-dominate

(Figure 4). Another major difference between countries is that radiological parameters are responsible for 9% of exceedences in the U.S. while there were no radiological exceedences in Ontario (Figure 4). This large difference may be due to the small number of systems in Ontario that submitted results for radiological tests rather than higher concentrations in the U.S. The chemical category was comprised of different parameters for each county with some overlap. In Ontario most chemical exceedences were from fluoride and lead while in the U.S. most were from arsenic. Standards for fluoride and lead are stricter in Ontario which may be why there were more exceedences for these chemical there.

Summary

Based on the information provided from the OMOE DWSP, source water quality in Ontario can be considered good.

It is important to note however that source waters as part of the DSWP are not currently analyzed for microbiological contamination, the largest contributor to health exceedences in Ontario. Treated drinking water quality in the U.S. and Canada can also be considered good. In the U.S. more than 90% of the population was never exposed to a health based violation while in Canada greater than 99.7% of all tests met drinking water standards.

Linkages

Drinking water quality may be negatively impacted by increases in nutrient, pesticide and bacterial loadings from tributaries, contamination in sediment, atmospheric deposition, land conversion, municipal wastewater and industrial loadings and runoff. These pressures result in changes to ground and surface water quality which may act as sources for drinking water. Improved wastewater treatment, sediment remediation and increased protected areas in response to these pressures may improve source drinking water quality.

Management Challenges/Opportunities

A more standardized, updated approach to monitoring contaminants and reporting data for drinking water needs to be established. Even though extensive lists of contaminants and their MCLs have been established in the U.S. and

Ontario, newer parameters of concern might not be listed due to available resources or technology. Additionally, state monitoring requirements may differ, requiring only a portion of this list to be monitored.

Standardized monitoring and reporting, especially of source water in the U.S., would make trend analysis easier and provide a more effective assessment of the state of the ecosystem and the potential for health hazards associated with drinking water. By providing source water data, the origin of contamination at WTPs will be easier to identify as some utilize multiple sources of water. Inclusion of microbiological tests into source water assessments will be important to understand potential impacts to human health.

237

Comments from the author(s)

A concern for future efforts would be the comparability of metrics between countries. Focusing on the population that is impacted by drinking water quality exceedences, rather than the number of exceedences or number of systems with exceedences, will allow us to better evaluate the potential for human exposure to drinking water contaminants.

Source waters may also be examined in the future to better understand where the contaminants are coming from.

Assessing Data Quality

:

Data Characteristics

1. Data are documented, validated, or qualityassured by a recognized agency or organization

2. Data are traceable to original sources

3. The source of the data is a known, reliable and respected generator of data

4. Geographic coverage and scale of data are appropriate to the Great Lakes basin

5. Data obtained from sources within the U.S. are comparable to those from Canada

6. Uncertainty and variability in the data are documented and within acceptable limits for this indicator report

Strongly

Agree

Agree

X

X

X

X

X

X

Neutral or

Unknown

Disagree

Strongly

Disagree

Not

Applicable

Acknowledgments

Author:

Michelle Craddock, Oak Ridge Institute for Science and Education, on assignment to the U.S. Environmental

Protection Agency, Great Lakes National Program Office (GLNPO) 2011

Previous Authors:

Danielle J. Sass, Oak Ridge Institute for Science and Education, on assignment to the U.S. Environmental Protection

Agency, Great Lakes National Program Office (GLNPO) 2008

Jeffrey C. May, Oak Ridge Institute for Science and Education, on assignment to the U.S. Environmental Protection

Agency, Great Lakes National Program Office (GLNPO) 2006

Tracie Greenberg, Environment Canada, Burlington, ON 2006

Information Sources

Ontario Ministry of the Environment. Drinking Water Surveillance Program dataset: http://www.ene.gov.on.ca/environment/en/resources/collection/data_downloads/index.htm#DWSP

Ontario Ministry of the Environment. 2006 (Revised from 2003).

Technical support Document for Ontario Drinking

Water Standards, Objectives and Guidelines

. http://www.ene.gov.on.ca/stdprodconsume/groups/lr/@ene/@resources/documents/resource/std01_079707.pd

f

Ontario Ministry of the Environment. 2011. Annual Report 2009-2010, Chief Drinking Water Inspector. http://www.portal.gov.on.ca/drinkingwater/dw_el_prd_044304.pdf

United States and Canada. 1987.

Great Lakes Water Quality Agreement of 1978, as amended by Protocol signed

November 18, 1987

. Ottawa and Washington.

U.S. Environmental Protection Agency. 2011. Safe Drinking Water Information System database. Select data from this database can be found at: http://water.epa.gov/scitech/datait/databases/drink/pivottables.cfm

238

List of Tables

Table 1.

Percentage of drinking water systems in the Great Lakes Basin (that are part of the DWSP in Ontario) where source water is below the MAC/IMAC for select chemicals.

List of Figures

Figure 1

. Average % community drinking water systems and population that did not have any health based violations in U.S. Great Lakes counties.

Source: U.S. EPA Safe Drinking Water Information System.

Figure 2

.

Percentage of drinking water systems meeting drinking water quality standards (municipal residential drinking water systems) in Ontario.

Source: OMOE. 2011. Chief Drinking Water Inspector Annual Report 2009-2010.

Figure 3

. Percentage of drinking water tests meeting standards (municipal residential drinking water systems) in

Ontario.

Source: OMOE. 2011. Chief Drinking Water Inspector Annual Report 2009-2010.

Figure 4

. Percentage of health based exceedences caused by chemical, microbiological, radiological, disinfection by-products and treatment technique parameters.

Source: U.S. EPA Safe Drinking Water Information System and OMOE. 2011. Chief Drinking Water Inspector

Annual Report 2009-2010

Last Updated

State of the Great Lakes 2011

Percentage of DWSP sites where source water is below the MAC/IMAC.

Nitrate

Nitrite

Atrazine

Arsenic

Uranium

Barium

Fluoride

Lead

Selenium

2007

100.00%

100.00%

100.00%

100.00%

100.00%

100.00%

98.99%

98.99%

98.99%

2008

100.00%

100.00%

100.00%

100.00%

100.00%

100.00%

98.91%

97.83%

98.91%

2009

100.00%

100.00%

100.00%

100.00%

100.00%

100.00%

98.91%

100.00%

98.91%

Table 1.

Percentage of drinking water systems in the Great Lakes Basin (that are part of the DWSP in Ontario) where source water is below the MAC/IMAC for select chemicals.

239

100%

75%

50%

25%

0%

2007 2008 2009 2010

Avg. % systems with no violations Avg. % population with no violations

Figure 1

. Average % community drinking water systems and population that did not have any health based violations in U.S. Great Lakes counties.

Source: U.S. EPA Safe Drinking Water Information System

100%

75%

50%

25%

0%

2004-2005 2005-2006 2006-2007 2007-2008 2008-2009 2009-2010

100% 99%-99.9% <99%

Figure 2

.

Percentage of drinking water systems meeting drinking water quality standards (municipal residential drinking water systems) in Ontario.

Source: OMOE. 2011. Chief Drinking Water Inspector Annual Report 2009-2010

240

100.0%

99.8%

99.6%

99.4%

99.2%

99.0%

2004-2005 2005-2006 2006-2007 2007-2008 2008-2009 2009-2010

Time Period

Figure 3

. Percentage of drinking water tests meeting standards (municipal residential drinking water systems) in

Ontario.

Source: OMOE. 2011. Chief Drinking Water Inspector Annual Report 2009-2010

100%

80%

60%

40%

20%

0%

U.S. (2010) Ontario (2009-2010)

Chemical

Disinfection By-product

Treatment Technique

Microbiologic

Radiologic

Figure 4

. Percentage of health based exceedances caused by chemical, microbiological, radiological, disinfection by-products and treatment technique parameters.

Source: U.S. EPA Safe Drinking Water Information System and OMOE. 2011. Chief Drinking Water Inspector

Annual Report 2009-2010

241

Economic Prosperity (Unemployment)

Overall Assessment

Trend: Undetermined

Rationale: Between 1976 and 2010, the overall unemployment rate fluctuated in response to socio-economic conditions, therefore identifying an expected but “undetermined” long-term trend. The shortterm trend (2005 to 2010) is an increasing unemployment rate. Throughout the thirty-five year bracket, with the exception of 2008-2009 where it experienced a 3.0% increase, the annual rate of change has consistently remained within an approximate 2.0% difference.

Lake-by-Lake Assessment

Trends were not made on an individual lake basis.

Purpose

To provide unemployment trends in the Great Lakes Region, as a representation of economic prosperity in the Great Lakes Region.

The Economic prosperity indicator is used in the Great Lakes Indicator Suite as a driving force indicator under the economic/social category.

Ecosystem Objective

Economic prosperity in the Great Lakes region should be pursued with full regard to the purpose of the Great Lakes

Water Quality Agreement, to restore and maintain the chemical, physical and biological integrity of the Great Lakes

Basin Ecosystem.

Ecological Condition

The unemployment rates are based on data extracted from Statistics Canada and the United States Department of

Labor (Bureau of Labour Statistics). The unit of analysis in this report is the unemployment percentage rate. This is the number of unemployed persons expressed as a percentage of the labor force. Estimates are in percentages, rounded to the nearest tenth. The data only considers persons in the civilian non-institutional population 15 years of age and over. The unemployment rate is reported for the whole of Ontario and the whole of each of the eight Great

Lakes States, and is not limited specifically to the watershed of the Great Lakes.

As seen in Table 1, the unemployment rate ranges from a low of 4.2% (in 2000) to a peak of 10.6% (in 1983). Since

1976, unemployment in the Great Lakes region has experienced multiple periods of fluctuation in growth and decline (Figure 1). The short-term trend indicates that unemployment has been rising. In particular, from 2008 to

2009, the region experienced its largest fluctuation in growth yet of 3.0%, from 6.1% to 9.1% (Figure 2). Between

1976 and 2010, the Great Lakes Region has had an average unemployment rate of 6.6%. Other than the 2008 to

2009 unemployment change of 3.0%, the annual change in unemployment did not change by more than 2.0% in any other year.

Ontario and the eight U.S. Great Lakes States have experienced similar unemployment rate trends. As seen in Figure

3, the region has experienced wide fluctuations of unemployment. Specifically, in the eight U.S. States, the official unemployment rate in 2010 was 9.5%. These fluctuations mirror the region’s overall pattern, whereby its annual rate of change is within an average of approximately 1.5%.

The United States reached a peak of official unemployment rate of 11.2% in 1982 and experienced its lowest unemployment rate of 4.0% nearly two decades after in 2000. During the Great Lakes region’s highest unemployment year of 1983, the unemployment rate of the eight Great Lakes states was higher than the overall unemployment rate in the United States (Table 2 and Figure 4). However, as seen in Figure 4, the eight States have

242

since managed to keep the official unemployment rate to equal or less than the overall national statistic. In 2000, the unemployment rate of the eight States was the same as the United States. Moreover, in the most recent 2010 unemployment data, the region was 0.1% less than the overall national unemployment figure.

Ontario also experienced wide fluctuations in its unemployment rate over the years. Ranges included a high unemployment rate of 10.9% in 1993, a low unemployment rate of 5.0% in 1988 and 1999, and a total unemployment in 2010 of 8.7%. In a national context, during the Great Lakes region’s highest unemployment year of 1983, Ontario had a slightly lower number than the overall unemployment rate in Canada (Table 3 and Figure 5).

This comparison was similar in the regional lowest unemployment rate year of 2000 wherein Ontario’s unemployment rate was lower than Canada’s overall. In the most recent unemployment data, however, Ontario has a slightly higher unemployment number than all of Canada.

As seen in Table 4 and Figure 6, there is no discernible unemployment rate pattern associated amongst the Great

Lakes province and states. The states which consistently scored a high unemployment rate, particularly in 1983 and

2000, did not have a high unemployment rate in 2010. However, within the Great Lakes Region, Minnesota is consistently within the lower bracket of unemployment rates whereas Illinois frequently remains in the high end of the unemployment range. Michigan experienced the widest range of unemployment rates during low and peak periods contrasting with New York which experienced the smallest range of unemployment rates.

Linkages

The Great Lakes underpin regional economic prosperity and quality of life for the millions of residents in the eight

U.S. States and Ontario. A significant fraction of the U.S. gross domestic product and over $150 billion in goods are generated annually in the Great Lakes region (Gesl 2006). Moreover, the lakes serve as commercial waterways, and supply water for agricultural and municipal uses (Gesl 2006). Unemployment is a key economic indicator when measuring an economy’s strength and sustainability. Economic prosperity is a driving force behind most pressures on the environment, and can be considered as both a positive and negative force.

When the economy is performing well, there tends to be less conflict between economic development and maintaining the integrity of the environment (McGill Redpath Museum). Under a healthy economy where the unemployment rates are low or decreasing, there will be greater economic capabilities to provide research to monitor anthropogenic impacts and to develop and implement new methods for mitigating the associated consequences.

At the same time, when the economy is performing well, there tends to be increased use and development of natural resources. When economic prosperity is high there tends to be higher levels of consumer spending and home buying

(Thorp, Muir and Zegarac 2000). These activities can increase pressures on the ecosystem through household and business waste generation, increased air pollution from transportation sources and accelerated land use changes

(Thorp, Muir and Zegarac 2000). Residential development is the key category of land use change and its environmental impacts are widely recognized. Moreover, the proliferation of international trade treaties in support of increased economic prosperity over the last few decades has led to an increase in the global movement of goods.

Increased transportation, particularly with Great Lakes and oceanic shipping traffic, has placed a strain on natural systems by facilitating the immigration of non-native species to new habitats, introducing pollutants into the aquatic ecosystem and altering and destroying coastal habitats (McGill University Redpath Museum).

Management Challenges/Opportunities

There are many linkages between economic prosperity and stresses to ecosystem health. Decision makers in the

Great Lakes community should aim to maximize the positive and minimize the negative pressures of economic prosperity on the chemical, physical and biological integrity of the Great Lakes ecosystem.

243

Comments from the author(s)

Alternative and/or additional measures of economic prosperity should be examined for use in the SOLEC process.

Unemployment is linked to economic prosperity; however, it may not be sufficient to represent other important aspects of economic prosperity, such as the level and distribution of income and wealth, poverty rates, income volatility and disparity, and economic security (Canadian Index of Well-Being).

Assessing Data Quality

Data Characteristics

Strongly

Agree

Agree

Neutral or

Unknown

Disagree

Strongly

Disagree

Not

Applicable

1. Data are documented, validated, or qualityassured by a recognized agency or organization

2. Data are traceable to original sources

3. The source of the data is a known, reliable and respected generator of data

4. Geographic coverage and scale of data are appropriate to the Great Lakes basin

5. Data obtained from sources within the U.S. are comparable to those from Canada

6. Uncertainty and variability in the data are documented and within acceptable limits for this indicator report

X

X

X

X

X

X

Acknowledgments

Author:

Brenda Yu, Great Lakes Division Intern, Environment Canada.

Contributors:

Krista Verlis, Contractor, Environment Canada, Waterloo, Ontario.

Rob Hyde, Great Lakes Program Officer, Environment Canada.

Erika Washburn, Lakewide Management Plan Coordinator, National Oceanic and Atmospheric Administration

Information Sources

Alden, M., Mortsch, L., Scheraga, J. 2003. “

Climate Change and Water Quality in the Great Lakes Region: Risks,

Opportunities, and Responses.

< www.ijc.org/rel/pdf/climate_change_2003_part3.pdf

>

Canadian Index of Well-Being. 2010.

Special Report: How are Canadians Really Doing?

< http://www.ciw.ca/Libraries/Documents/FirstReportOfTheCIW.sflb.ashx

>

Gesl, D. 2006.

Proposal: Great Lakes Habitat Protection & Restoration Implementation.

<

www.usace.army.mil/CECW/PlanningCOP/.../GrtLakesHIP_10Feb06.pdf

>

Intergovernmental Panel on Climate change (IPCC). 2001.

Climate Change 2001: The Scientific Basis.

Summary for

Policymakers and Technical Summary for the Working Group I Report. WMO and UNEP.

McGill University Redpath Museum. 1999. The Relationship between Human Activities and Impacts on

Biodiversity. < http://redpath-museum.mcgill.ca/Qbp/3.Conservation/impacts.htm

>

Muir, T., Thorp, S., Zegarac M. 2000.

Economic Prosperity

Great Lakes (SOLEC) Indicator.

< http://www.epa.gov/solec/archive/2000/Implementing_Indicators_%28FULL%29.pdf

>

Statistics Canada. 2001. Table 282-0002 –

Labour Force Survey Estimates (LFS), by Sex and Detailed Age Group,

Annual.

< http://www5.statcan.gc.ca/cansim/pickchoisir?lang=eng&id=2820002&pattern=2820002&researchTypeByValue=1 >

Statistics Canada. 2010.

Annual Average Unemployment Rate Canada and Provinces 1976-2010

< http://www.stats.gov.nl.ca/statistics/Labour/PDF/UnempRate.pdf

>

244

United States Department of Labor - Bureau of Labor Statistics. 2011.

Local area unemployment statistics -

Wisconsin, not seasonally adjusted - LAUST55000003,LAUST55000004,LAUST55000005,LAUST55000006 -

(1976 to 2010<

http://data.bls.gov/cgi-bin/surveymost?la+55 >

United States Department of Labor - Bureau of Labor Statistics. 2011.

Local area unemployment statistics -

Pennsylvania, not seasonally adjusted - LAUST42000003,LAUST42000004,LAUST42000005,LAUST42000006

- (1976 to 2010)

. < http://data.bls.gov/cgi-bin/surveymost?la+42 >

United States Department of Labor - Bureau of Labor Statistics. 2011.

Local area unemployment statistics - Ohio, not seasonally adjusted - LAUST39000003,LAUST39000004,LAUST39000005,LAUST39000006 - (1976 to

2010)

. < http://data.bls.gov/cgi-bin/surveymost?la+39 >

United States Department of Labor - Bureau of Labor Statistics. 2011.

Local area unemployment statistics - New

York, not seasonally adjusted - LAUST36000003,LAUST36000004,LAUST36000005,LAUST36000006 - (1976 to 2010)

. < http://data.bls.gov/cgi-bin/surveymost?la+36 >

United States Department of Labor - Bureau of Labor Statistics. 2011. Local area unemployment statistics -

Minnesota, not seasonally adjusted - LAUST27000003,LAUST27000004,LAUST27000005,LAUST27000006

- (1976 to 2010). < http://data.bls.gov/cgi-bin/surveymost?la+27 >

United States Department of Labor - Bureau of Labor Statistics. 2011.

Local area unemployment statistics -

Michigan, not seasonally adjusted - LAUST26000003,LAUST26000004,LAUST26000005,LAUST26000006 -

(1976 to 2010)

. < http://data.bls.gov/cgi-bin/surveymost?la+26 >

United States Department of Labor - Bureau of Labor Statistics. 2011.

Local area unemployment statistics -

Indiana, not seasonally adjusted - LAUST18000003,LAUST18000004,LAUST18000005,LAUST18000006 -

(1976 to 2010)

. < http://data.bls.gov/cgi-bin/surveymost?la+18 >

United States Department of Labor - Bureau of Labor Statistics. 2011.

Local area unemployment statistics - Illinois, not seasonally adjusted - LAUST17000003,LAUST17000004,LAUST17000005,LAUST17000006 - (1976 to

2010)

. < http://data.bls.gov/cgi-bin/surveymost?la+17 >

United States Department of Labor Bureau of Labor Statistics. 2011.

Annual Average Unemployment Rate, Civilian

Labor Force 16 years or Older < http://www.bls.gov/cps/prev_yrs.htm

>

United States Department of Labor - Bureau of Labor Statistics. 2010.

Frequently asked questions

.

< http://www.bls.gov/lau/laufaq.htm#Q03 >

United States Department of Labor - Bureau of Labor Statistics. 2008.

Local area unemployment statistics:

Overview

. < http://stats.bls.gov/lau/lauov.htm

>

List of Tables

Table 1

.

Unemployment Percentage Rate Table in Ontario, Eight Great Lakes States and the Entire Great Lakes

Region

Source: Statistics Canada and United States Department of Labor - Bureau of Labor Statistics

Table 2.

Unemployment Percentage Rate in the United States and the Eight Great Lakes States

Source: United States Department of Labor – Bureau of Labor Statistics

Table 3

. Unemployment Percentage Rate in Canada and the Great Lakes Province (Ontario)

Source: Statistics Canada

List of Figures

Figure 1

. Total Unemployment Rate for the entire Great Lakes Region (Ontario and the eight U.S. Great Lakes

States) from 1976 to 2010

Source: Statistics Canada and United States Department of Labor - Bureau of Labor Statistics

Figure 2

. Short-Term Trend Analysis: Total Unemployment Rate for Great Lakes Region (Ontario and the Eight

Great Lakes States from 2006 to 2010)

Source: Statistics Canada and United States Department of Labor - Bureau of Labor Statistics

Figure 3

. Total Unemployment Rate in the Eight Great Lakes States and Ontario from 1976 – 2010

245

Source: Statistics Canada and United States Department of Labor - Bureau of Labor Statistics

Figure 4

. United States and Eight U.S. Great Lakes States: Low, Peak, and Current Years of Unemployment

Source: United States Department of Labor - Bureau of Labor Statistics

Figure 5

. Canada and the Great Lakes Province (Ontario): Low, Peak, and Current Years of Unemployment

Source: Statistics Canada

Figure 6

. Ontario and the Eight Great Lakes States: Low, Peak, and Current Years of Unemployment

Source: Statistics Canada and United States Department of Labor - Bureau of Labor Statistics

Last Updated

State of the Great Lakes 2011

246

Unemployment Percentage Rate

Year

1976

1977

1978

1979

1980

1981

1982

1983

Unemployment

Percentage Rate in Ontario

6.1

6.9

7.2

6.6

6.9

6.6

9.8

1984

1985

10.4

9.0

7.9

1986

1987

1988

1989

1990

1991

1992

7.0

6.1

5.0

5.0

6.2

9.5

10.8

Average Unemployment

Percentage Rate in the Eight

Great Lakes States

8.0

7.2

6.4

6.4

8.4

9.1

11.2

11.0

8.6

8.0

7.3

6.3

5.5

5.3

5.7

7.0

7.6

Unemployment Percentage Rate in the entire Great Lakes

Region

7.8

7.2

6.5

6.3

8.2

8.8

10.5

10.6

8.5

7.8

5.9

6.9

7.5

6.8

5.8

7.2

6.4

5.5

5.3

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

10.9

9.6

8.7

9.0

8.4

7.2

6.3

5.7

6.3

7.2

6.9

6.8

6.8

5.8

5.2

5.1

4.8

4.4

4.2

4.0

4.8

5.8

6.2

5.8

5.3

5.3

4.9

4.6

4.5

4.2

4.9

5.9

6.1

5.9

2005

2006

6.6

6.3

5.4

5.0

5.6

5.1

2007

2008

2009

6.4

6.5

9.0

5.1

6.0

9.6

5.2

6.1

9.1

2010 8.7 9.5 9.2

Table 1

.

Unemployment Percentage Rate Table in Ontario, Eight Great Lakes States and the Entire Great Lakes

Region. Source: Statistics Canada and United States Department of Labor - Bureau of Labor Statistics

Unemployment Percentage Rate in the U.S. and the Great Lakes Region

Year

1983 (peak unemployment)

2000 (low unemployment)

2010

(current)

United States 9.60 4.0

Eight U.S. Great Lakes States 11.0 4.0

Table 2

.

Unemployment Percentage Rate in the United States and the Eight Great Lakes States

Source: United States Department of Labor – Bureau of Labor Statistics

9.6

9.5

247

Unemployment Percentage Rate in Canada and Ontario

Year

Canada

1983 (peak unemployment)

12.0

2000 (low unemployment)

6.8

Great Lakes Province - Ontario 10.4 5.7

Table 3

. Unemployment Percentage Rate in Canada and the Great Lakes Province (Ontario)

Source:

Statistics Canada

2010

(current)

8.0

8.7

Figure 1

. Total Unemployment Rate for the entire Great Lakes Region (Ontario and the eight U.S. Great Lakes

States) from 1976 to 2010

Source: Statistics Canada and United States Department of Labor - Bureau of Labor Statistics

Figure 2

. Short-Term Trend Analysis: Total Unemployment Rate for Great Lakes Region (Ontario and the Eight

Great Lakes States from 2006 to 2010)

Source: Statistics Canada and United States Department of Labor - Bureau of Labor Statistics

Figure 3

. Total Unemployment Rate in the Eight Great Lakes States and Ontario from 1976 – 2010

Source: United States Department of Labor – Bureau of Labor Statistics

248

Figure 4

. United States and Eight U.S. Great Lakes States: Low, Peak, and Current Years of Unemployment

Source: United States Department of Labor – Bureau of Labor Statistics

Figure 5

. Canada and the Great Lakes Province (Ontario): Low, Peak, and Current Years of Unemployment

Source: Statistics Canada

Figure 6

. Ontario and the Eight Great Lakes States: Low, Peak, and Current Years of Unemployment

Source: Statistics Canada and United States Department of Labor - Bureau of Labor Statistics

249

Energy Consumption

Overall Assessment

Trend: Increasing

Rationale: The trend of total energy consumption in the eight Great Lakes States and Ontario has increased over the eighteen-year examined period. Between 1990 and 2008, energy consumption has increased 10.0%. However, the short term trend assessment of energy consumption from 2005-

2008 illustrates that the total energy usage has decreased (a drop of 3.0% from 2005).

Lake-by-Lake Assessment

Trends were not made on an individual lake basis.

Purpose

To provide energy consumption use trends in the Great Lakes region

The energy consumption indicator is used in the Great Lakes indicator suite as a Driving Force indicator in the Economic/Social category

Ecosystem Objective

Resource conservation and minimizing the unnecessary use of resources are endpoints for ecosystem integrity.

Impacts from energy consumption should be managed so that beneficial uses of the Great Lakes are not impaired, and pollution is controlled as outlined in Annex 2 and Annex 15 of the Great Lakes Water Quality Agreement.

Ecological Condition

In this report, the Great Lakes region is defined as the eight Great Lakes States and the province of Ontario. Energy consumption within the Great Lakes region is examined by data extracted primarily from the Statistics Canada,

Natural Resources Canada, Canadian Industrial Energy End-Use Data and Analysis Centre, and the United States

Information Administration. The unit of analysis for energy consumption is secondary energy use as reflected in

Megawatts Hour (MWh).

Secondary energy is energy used by the final consumer. It includes energy used to heat and cool homes and workplaces, as well as to operate appliances, vehicles and factories. Table 1 lists the total secondary energy use in the Great Lakes States and Ontario from 1990 and 1995-2008. As seen in Table 1, in 2008, the total secondary energy consumption rate in the Great Lakes region is 8,247,276,452 MWh. Secondary energy does not include intermediate uses of energy for transporting energy to market or transforming one energy form to another; this is primary energy (State of the Great Lakes 2009; 294). This report will focus on examining the secondary energy usage in the Great Lakes region.

A) Great Lakes Region as a whole (Ontario + Eight Great Lakes States)

The energy consumption for the entire Great Lakes region has fluctuated over the eighteen-year period (Figure 1).

Comparing the 1990 and 2008 total energy consumption data, the Great Lakes region total energy use grew by 10%.

Within the four specific sectors, the industry sector is the most energy consuming sector in the Great Lakes region

(Figure 2). However, the most recent data available from 2008 indicates that whereas in 1990 the industrial sector consumed 37% of the total energy, it has since decreased to 30.0% (Figure 3 & 4).The remaining three sectors, residence, transportation and commercial have increased their share of energy use by 1%, 3% and 3% respectively since 1990.

In examining the short-term trend analysis, the energy consumption from 2005 to 2008 shows a fluctuation range between a decline of 1.4% to an increase of 3.7%. There was a decrease in energy consumption from 2005 to 2006

(3.7 %); but in the next year (2006 to 2007), the consumption rate experienced an increase of 2.5% (Figure 5).

250

Returning to 2007-2008, the energy usage in the Great Lakes region decreased once again by another 1.0%, leaving the total energy consumption rate in 2008 as 8,247,276,452 MWh.

To obtain a greater understanding of the energy consumption rate within the region, population data from the U.S.

Census and Statistics Canada have been included to examine the average energy use per person within the region

(energy consumption per capita). In 1990, the total population within the Great Lakes region as defined in this report was 86,323,139 (Table 2).The total population’s total energy consumption was 7,429,731,790 MWH/h, and its per capita usage was 87 MWh/per person/per year. It is worth noting that while the energy consumption has increased, per capita usage has dropped slightly. Compared to 1990, although the 2008 population in the Great Lakes region had an increase of 10.6%, its energy usage per capita declined by 3.4% to 84 MWh/per person per year.

B) Comparison between Ontario and the Eight Great Lakes States

The overall trends in energy consumption by sector were quite similar on both sides of the basin. In Ontario, the total secondary energy consumption by the four sectors in 2008 was 763,472,222 MWh (Table 3). The transportation sector accounted for the largest end user percentage of energy consumption at 32%. Energy consumption in the other three sectors was as follows: residence with 21%, commercial/institutional with 18% and industrial with 30% (Figure 6).

Total secondary energy consumption by the four sectors on the eight U.S. Great Lakes States in 2008 was

7,483,804,229 Megawatt hours (MWh) (Table 3). For the U.S Great Lakes States, the industrial sector was the largest consuming sector with 30% in 2008. The remaining three sectors account for 70% of the total, as follows: transportation and residential with 25% each and the commercial/institutional sector with 20% (Figure 6).

Linkages

Both Canada and the United States are among the world’s top per capita electricity and energy consumers; consuming energy can cause a wide range of health and environmental impacts. Environmental impacts are caused by actions required to produce energy, including oil and gas exploration and development, coal mining, hydroelectric dams and reservoirs (Boyd 2001). According to a Stockholm Environment Institute report, current pressure exerted on the ecosystem as a result of energy generation and consumption is unsustainable (Persson and

Noel 2010), As one of the main driving forces, energy consumption is triggering (direct and indirect) pressures on the ecosystem.

Energy consumption is a direct and indirect driving force behind many of the pressures on the Great Lakes.

According to the United Nations Economic and Social Commission for Asia and the Pacifique (UNESCPA), energy consumption has a direct effect on greenhouse gas emissions, emission of air pollutants, acid precipitation and pollution of toxic substance (UNESCAP 2001). Consequently, these effects have a direct impact on biodiversity and the ecosystem.

There is, for example, a direct correlation between energy consumption and the emission of air pollutants. Burning fossil fuels can cause emission of air pollutants into the atmosphere and via atmospheric deposition on to land and water surfaces. Water is a “dangerously effective carrier of pollutants emitted into the air from the combustion of coal and other fossil fuels” (Krantzberg and Bassermann 2010). Rain transports pollutants to watersheds, lakes and rivers, and can therefore compromise water quality. For this reason, initiatives such as the UNEP global Mercury

Partnership are calling for mercury global partnerships between governments and other stakeholders to reduce risks to human health and the environment from the release of mercury and its compounds to the environment from sources such as fossil fuel consumption (UNEP 1).

For other renewable energies such as hydroelectricity, solar power and wind power, the debate surrounding these usages has been controversial. While the use of renewable energy sources is considered more environmentally

251

friendly and fairly economically feasible, it still elicits reactions from local communities and environmental policymakers on their limited benefits, potential tradeoffs and visual pollution.

In the case of hydroelectric power, while its usage is seen as more environmentally friendly, it does come at some environmental cost, particularly on water resources (Krantzberg and Bassermann 2010). Large hydro power can cause disruption in natural river cycles, which in turn affects the aquatic ecosystem, degrades upstream catchment areas and impacts crop productivity (Persson and Noel 2010). In addition, building hydroelectric damns often leads to the loss of forests, wildlife habitat, and species populations.

In the case of solar energy, use of toxic chemicals in the manufacturing of solar energy cells presents a problem both during use and disposal (IUCN 2008).

In the case of wind power, the usage of wind turbines has been controversial. On one hand, recent studies report that wind farms pose no serious environmental threats, and in some cases an off-shore wind-farm may even improve the marine ecosystem (Phadke 2010, and Bergman et al.2011). On the other hand, there are concerns that building wind turbines can result in ecosystem disruption in terms of habitat loss at large wind farms, and with rotors causing mortality of migratory birds (IUCN 2008).

Management Challenges/Opportunities

The linkages between energy use and stress on the Great Lakes health are outlined above. The Great Lakes community and decision makers should continue to support global, national, regional and local energy use conservation initiatives and, seek ways to minimize the stress that energy use and energy production can cause to the

Great Lakes ecosystem.

Comments from the author(s)

In comparison to the Great Lakes region as defined in this report, the total energy use for the Great Lakes watershed would be less. Nonetheless, this data serves the indicator report’s purpose well by illustrating a socio-economic trend that is a driving force behind many of the pressures on the Great Lakes conditions, and the socio-economic context is which decision-makers are working within. The investment required to breakdown energy use trends specifically for the Great lakes watershed boundary and/or on a lake-by-lake level would only be worthwhile should formal energy use conservation reduction targets be set for that defined geographic boundary.

Assessing Data Quality

Data Characteristics

1. Data are documented, validated, or qualityassured by a recognized agency or organization

2. Data are traceable to original sources

3. The source of the data is a known, reliable and respected generator of data

4. Geographic coverage and scale of data are appropriate to the Great Lakes basin

5. Data obtained from sources within the U.S. are comparable to those from Canada

6. Uncertainty and variability in the data are documented and within acceptable limits for this indicator report

Strongly

Agree

X

X

X

X

X

X

Agree

Neutral or

Unknown

Disagree

Strongly

Disagree

Not

Applicable

Acknowledgments

Authors:

Brenda Yu, Great Lakes Division Intern, Environment Canada.

Contributors:

252

Krista Verlis, Contractor, Environment Canada, Waterloo, Ontario.

Rob Hyde, Great Lakes Program Officer, Great Lakes Division, Environment Canada.

Erika Washburn, Lakewide Management Plan Coordinator, National Oceanic and Atmospheric Administration

Information Sources

Bergman, M., Bouma, S., Brasseur, S., Dann, R., Dirksen, S., Fijn, R., Haan., D De., Hal R., Hofstede, R.,

Kouwenhoven, H., Krijgsveld, K., Lambers, R., Lindeboom, H., Leopold, M and Scheidat, M. 2011.

Short

Term Ecological Effects of an Offshore Wind Farm in the Dutch Coastal Zone; A Compilation

.

< http://iopscience.iop.org/1748-9326/6/3/035101 >

Boyd, D. R. 2001.

Canada vs. the OECD: An Environmental Comparison Energy Consumption.

Victoria, British

Columbia: University of Victoria Eco-Research Chair. p.16-17

< http://www.environmentalindicators.com/htdocs/PDF/Pgs21-30.pdf

>

U.S. Census.

US States 1990 & 2008 Population

< http://www.census.gov/ >

Krantzberg, G., and Bassermann R. 2010.

How our Energy Future Affects our Water Future

. The Journal of Policy

Engagement Volume 2(1)

< http://members.peo.on.ca/index.cfm/ci_id/38584.htm

>

International Union for Conservation of Nature. 2008.

Energy, Ecosystems, and Livelihoods: Understanding

Linkages in the Face of Climate Change Impacts.

<www.icun.org/about/work/initiatives/energy_welcome/index.cfm?uNewsID=1646

>

Natural Resource Canada - Office of Energy Efficiency. (2010).

Residential sector Ontario - Table 1: Secondary energy use and GHG Emissions by energy source (1990-2008)

. Retrieved February 14, 2011, from http://oee.nrcan-rncan.gc.ca/corporate/statistics/neud/dpa/tablestrends2/res_on_1_e_1.cfm?attr=0

Natural Resource Canada - Office of Energy Efficiency. (2010).

Commercial/Institutional Sector Ontario - Table 3:

Secondary energy use and GHG emissions by activity type

. Retrieved February 14, 2011, from http://oee.nrcanrncan.gc.ca/corporate/statistics/neud/dpa/tablestrends2/com_on_3_e_1.cfm?attr=0

Natural Resource Canada - Office of Energy Efficiency. (2010).

Industrial sector Ontario - Aggregated industries -

Table 2: Secondary energy use and GHG emssions by industry

. Retrieved February 14, 2011, from http://oee.nrcan-rncan.gc.ca/corporate/statistics/neud/dpa/tablestrends2/agg_on_2_e_1.cfm?attr=0

Natural Resource Canada - Office of Energy Efficiency. (2010).

Transportation sector Ontario - Table 1:

Secondary energy use by energy source.

Retrieved February 14, 2011, from http://oee.nrcan.gc.ca/corporate/statistics/neud/dpa/tablestrends2/tran_on_1_e_4.cfm?attr=0

Persson, L., and Noel, S. 2010.

The Millennium Development Goals in 2010 – threats to Ecosystem Services from

Air Pollution, Energy Generation and Pesticide Use.

Stockholm, Sweden: Stockholm Environment Institute.

< http://sei-international.org/publications?pid=1616 >

Phadke, Roopali. 2010.

Steel Forests or smoke Stacks: The politics of Visualization in the Cape Wind Controversy

.

Environmental Politics Vol 19(1): 1-20

< http://www.hks.harvard.edu/sdn/articles/files/Phadke%20Steel%20Forests.pdf

>

Statistics Canada, 2009.

Report on Energy Supply-Demand in Canada, 1990-2007; Electric Power Generation,

Transmission and Distribution 2007; Rail in Canada 1990-2007; The Canadian passenger Bus and Urban

Transit Industries 2001-2006

< http://www.statcan.gc.ca/start-debut-eng.html

>

Statistics Canada. 2008.

Ontario Population in 2008. <

http://www40.statcan.gc.ca/l01/cst01/demo02a-eng.htm>

Statistics Canada. 1990.

Ontario Population in 1990

< http://www12.statcan.ca/census-recensement/2006/dp-pd/fsfi/index.cfm?LANG=ENG&VIEW=D&PRCODE=35&TOPIC_ID=3&format=flash >

United Nations Economic and Social Commission for Asia and the Pacifique. 2001.

Air Quality

Statistics.

<www.unescap.org/stat/envstat/stwes-mo2-air1.pdf >

United States Energy Information Administration (EIA) 2010.

State Energy Consumption Estimates – 1960 through

2008

. www.eia.gov.emeu/states/sep_use/notes/use_print2008.pdf

253

List of Tables

Table 1

. Energy Consumption in the Great Lake Region from 1990, 1995-2008

Source: United States Energy Information Administration (EIA) 2010. Natural Resource Canada - Office of Energy

Efficiency 2010.

Table 2

. Energy Consumption and Population within the Great Lakes Region (Ontario + 8 States).

Source: United States Energy Information Administration (EIA) 2010. Natural Resource Canada - Office of Energy

Efficiency 2010.

Table 3

. Total Energy Consumption Rate by State/Province in 2008.

Source: United States Energy Information Administration (EIA) 2010. Natural Resource Canada - Office of Energy

Efficiency 2010.

Table 4

. Total Energy Consumption Rate from 2005 – 2008.

Source: United States Energy Information Administration (EIA) 2010. Natural Resource Canada - Office of Energy

Efficiency 2010.

List of Figures

Figure 1

. Total Energy Consumption in all Great Lake locations 1990, 1995-2008.

Source: United States Energy Information Administration (EIA) 2010. Natural Resource Canada - Office of Energy

Efficiency 2010.

Figure 2

. Total Energy Consumption by sector for all Great Lake locations 1990, 1995-2008.

Source: United States Energy Information Administration (EIA) 2010. Natural Resource Canada - Office of Energy

Efficiency 2010.

Figure 3

. The percent contribution of each of the four sectors within the Great Lakes region in 1990.

Source: United States Energy Information Administration (EIA) 2010. Natural Resource Canada - Office of Energy

Efficiency 2010.

Figure 4

. The percent contribution of each of the four sectors within the Great Lakes region in 2008.

Source: United States Energy Information Administration (EIA) 2010. Natural Resource Canada - Office of Energy

Efficiency 2010.

Figure 5

. Total Energy Consumption in the Great Lakes in the Great Lakes States and Ontario, 2005-2008.

Source: United States Energy Information Administration (EIA) 2010. Natural Resource Canada - Office of Energy

Efficiency 2010.

Figure 6

. Comparison of Total Energy Consumption for Ontario and all Great Lakes States in 2008 (MWh).

Source: United States Energy Information Administration (EIA) 2010. Natural Resource Canada - Office of Energy

Efficiency 2010.

Last Updated

State of the Great Lakes 2011

254

Energy Consumption in the Great Lake Region

Year

1990

1995

1996

1997

1998

1999

2000

Total Energy Use (MWh)

7,429,731,790

7,953,728,327

8,193,830,538

8,188,486,379

8,009,460,149

8,296,601,235

8,462,325,567

Residence

1,720,089,146

1,881,985,073

1,965,544,382

1,889,090,097

1,760,838,819

1,878,856,669

1,948,509,147

Commercial

1,266,281,782

1,430,974,398

1,478,911,839

1,494,270,762

1,466,623,015

1,535,890,162

1,615,126,033

Industrial

2,711,060,722

2,791,232,982

2,867,398,314

2,884,634,732

2,816,275,765

2,840,141,925

2,820,664,154

Transportation

1,732,300,141

1,849,535,875

1,881,976,003

1,920,490,789

1,965,722,550

2,041,712,479

2,078,026,233

2001

2002

2003

2004

8,134,622,104

8,244,054,100

8,338,580,794

8,426,769,846

1,899,472,020

1,983,378,737

2,030,464,961

1,987,371,590

1,610,799,287

1,636,049,498

1,639,774,499

1,648,665,008

2,585,355,733

2,561,858,399

2,581,586,950

2,634,747,673

2,038,995,064

2,062,767,466

2,086,754,383

2,155,985,576

2005

2006

8,472,930,380

8,157,785,682

2,052,945,322

1,877,010,541

1,649,586,013

1,585,196,860

2,575,162,448

2,512,107,037

2,195,236,598

2,183,471,244

2007 8,364,775,670 1,998,980,762 1,641,411,359 2,530,691,551 2,193,691,997

2008 8,247,276,452 2,001,826,800 1,664,997,902 2,441,979,930 2,138,471,820

Table 1

. Energy Consumption in the Great Lake Region from 1990, 1995-2008.

Source: United States Energy Information Administration (EIA) 2010. Natural Resource Canada - Office of Energy

Efficiency 2010.

Energy Consumption and Population within the Great Lakes Region

State/Province Total Energy

Ontario

Consumption within the Great Lakes

Region (1990)

653,166,666

Population within the

Great Lakes Region

(1990)

(1991) – 10,085,000

Total Energy

Consumption within the Great Lakes

Region (2008)

763,472,222

Population within the

Great Lakes (2008)

12,932,300

Illinois

Indiana

Michigan

Minnesota

New York

Ohio

Pennsylvania

Wisconsin

1,055,466,152

738,685,632

832,058,075

407,456,708

1,099,309,583

1,125,979,052

1,085,505,936

432,103,986

11,430,602

5,544,159

9,295,297

4,357,099

17,990,455

10,847,115

11,881,643

4,891,769

1,198,279,684

837,421,275

855,269,304

580,016,955

1,168,826,041

1,155,286,158

1,142,889,252

548,815,561

12,842,954

6,388,309

10,002,486

5,230,567

19,467,789

11,528,072

12,566,368

5,627,610

Total: 7,429,731,790 86,323,139 8,250,276,452 96,586,455

Table 2

. Energy Consumption and Population within the Great Lakes Region (Ontario + 8 States).

Source: United States Energy Information Administration (EIA) 2010. Natural Resource Canada - Office of Energy

Efficiency 2010.

255

Total Energy Consumption Rate

State/Province Total Energy Consumption by State/Province(MWh)

Ontario

U.S. Basin Total (2008)

Illinois

Indiana

763,472,222

7,483,804,229

1,198,279,683

837,421,275

Michigan

Minnesota

New York

Ohio

855,269,304

580,016,955

1,168,826,041

1,155,286,158

Pennsylvania 1,142,889,252

Wisconsin 545,815,561

Table 3.

Total Energy Consumption Rate by State/Province in 2008.

Source: United States Energy Information Administration (EIA) 2010. Natural Resource Canada - Office of Energy

Efficiency 2010.

Total Energy Consumption Rate from 2005 – 2008.

Ontario

2005

733,250,000

2006

748,861,111

Illinois

Indiana

Michigan

Minnesota

1,218,794,659

855,591,682

929,504,206

550,709,848

1,169,969,019

836,981,669

879,682,124

543,353,764

New York

Ohio

Pennsylvania

Wisconsin

1,219,820,408

1,189,194,481

1,185,150,100

550,914,997

1,149,160,973

1,143,475,394

1,149,922,957

536,378,672

2007

775,055,556

1,198,836,519

852,455,821

880,971,636

559,003,759

1,190,161,615

1,186,820,605

1,176,475,196

544,994,962

2008

763,472,222

1,198,279,684

837,421,275

855,269,304

580,016,955

1,168,826,041

1,155,286,158

1,142,889,252

548,815,561

Table 4.

Total Energy Consumption Rate from 2005 – 2008.

Source: United States Energy Information Administration (EIA) 2010. Natural Resource Canada - Office of Energy

Efficiency 2010.

Figure 1

. Total Energy Consumption in all Great Lake locations 1990, 1995-2008.

Source: United States Energy Information Administration (EIA) 2010. Natural Resource Canada - Office of Energy

Efficiency 2010.

256

Figure 2

. Total Energy Consumption by sector for all Great Lake locations 1990, 1995-2008.

Source: United States Energy Information Administration (EIA) 2010. Natural Resource Canada - Office of Energy

Efficiency 2010.

Figure 3

. The percent contribution of each of the four sectors within the Great Lakes region in 1990.

Source: United States Energy Information Administration (EIA) 2010. Natural Resource Canada - Office of Energy

Efficiency 2010.

Figure 4

. The percent contribution of each of the four sectors within the Great Lakes region in 2008.

Source: United States Energy Information Administration (EIA) 2010. Natural Resource Canada - Office of Energy

Efficiency 2010.

257

Figure 5

. Total Energy Consumption in the Great Lakes in the Great Lakes States and Ontario, 2005-2008.

Source: United States Energy Information Administration (EIA) 2010. Natural Resource Canada - Office of Energy

Efficiency 2010.

Figure 6

. Comparison of Total Energy Consumption for Ontario and all Great Lakes States in 2008 (MWh).

Source: United States Energy Information Administration (EIA) 2010. Natural Resource Canada - Office of Energy

Efficiency 2010.

258

Extreme Precipitation Events

Overall Assessment

Trend: Increasing

Rationale: Unavailable

Purpose

To assess trends in precipitation and to examine the influence and impact(s) of climate change on the Great

Lakes region.

The Precipitation Events indicator is used in the Great Lakes indicator suite as a Pressure indicator in the

Resource Use and Physical Stressors top level reporting category.

Ecosystem Objective

The ecosystem objective is to maintain the diverse array of Great Lakes coastal wetlands by allowing, as closely as possible, the natural seasonal and long-term fluctuations of Great lakes water levels. The alteration of frequency and magnitude of precipitation events may also affect such beneficial use impairments as ‘Loss of Fish and Wildlife

Habitat,’ ‘Degradation of Phytoplankton and Zooplankton Populations,’ ‘Degradation of Aesthetics,’ ‘Restrictions on Drinking Water Consumption or Taste and Odor Problems,’ ‘Eutrophication or Undesirable Algae,’ ‘Restrictions on Dredging Activities,’ ‘Degradation of Benthos,’ and ‘Degradation of Fish and Wildlife Populations’ under Annex

2 of the Great Lakes Water Quality Agreement.

Ecological Condition

In recent decades the Great Lakes region has seen pattern of above average precipitation in both summer and winter months (Kling, 2003). From 1915 to 2004, total annual precipitation increased by 4.5 inches (Hodgkins et al., 2007).

Although trends indicate increases in total precipitation, precipitation has not increased uniformly over the last one hundred years. For example, over the last 90, 70, and 50 years respectively, precipitation in March and February declined. Conversely, precipitation in April, May and July through December, over the same time periods, increased

(Hodgkins et al., 2007). These finding highlight the seasonal shift in precipitation patterns.

The following figure showcases trends in average annual precipitation, in inches, over the Great Lakes providing support of an overall pattern of increasing total annual precipitation.

Looking forward, in low- and high- emission climate models scenarios, average annual total precipitation is expected to be slightly above long-term averages. It is also expected that annual average precipitation will increase by 10 to 20 percent by the end of century. In terms of temporal shifts in seasonal patterns of precipitations, winter and spring rains are expected to increase and summer rains decrease by up to 50 percent.

Over the course of the last five decades, the frequency of 24-hour and 7-day intense rainfall events have been high relative to the long-term average. Furthermore, findings based on models suggest an increase in both 24-hour and multiday heavy rain events over the next century. It is predicted that the frequency of such events may double by

2100 (Kling et al., 2003).

Data Source

Data from this report was generated using climate data from the National Oceanic and Atmospheric Administration

(NOAA) climate divisions found in Table 1. These divisions were chosen based on an approximation of the boundaries of the Great Lakes basin.

259

Linkages

The impact of changes in the temporal distribution and magnitude of precipitation in the Great Lakes region will likely have an effect on the hydrologic system of the basin. As temperatures increase, evaporation as well is expected to increase. Additionally, an increase in surface water runoff will likely accompany an increase in total precipitation resulting in both positive and negative impacts on ecosystems. For ecosystems that rely on water level recharge during the winter season, the increase in winter precipitation may result in favorable impacts. Conversely, ecosystems that rely on summer recharge, such as some wetland ecosystems, may experience significant stress with decreases in summer precipitation (Wuebbles et al., 2004). Changes in runoff will also affect soil moisture. When compared to the long-term average from 1961-1990, soil moisture is expected to increase upwards of eighty percent during winter in some areas in the region and decrease regionally by upwards of thirty percent in the summer and fall. A shift in soil moisture may also promote the preference of crops and ecosystems that are reliant on recharge during the winter months (Kling et al., 2003). Groundwater recharge is also expected to increase as more rain falls when plants are dormant, leading to increased base flow in spring-fed streams and lakes, and surface flooding of areas with hydric soils.

Additional consequences of altered precipitation patterns include:

Increased occurrence of flooding events

Increased erosion and distribution of pollutants from upland sources

Increased runoff during heavy rain events

Increased groundwater recharge in winter and spring

Decreases in fish and invertebrate production

Disturbance of food web interactions and fish and insect life histories (Kling et al., 2003)

Increased lake effect snow resulting in warmer surface waters and decreased ice cover (Burnett et al.,

2003).

Management Challenges/Opportunities

The realm of response options to address climate change is classified into two categories, the first of which is adaptation, or “initiatives and measures designed to reduce the vulnerability of natural and human systems against actual or expected climate change effects” (Koslow, 2010). Although a wide range of adaptation strategies exist, there are significant financial, technological, cognitive, behavioral, political, social, institutional, and cultural constraints resulting in limited implementation and effectiveness of adaptive strategies (Bernstein et al., 2007).

Adaptation is one way to deal with the knowledge gaps and uncertainty of climate change science (Patino, 2010).

The Wisconsin Initiative on Climate Change Impacts (WCCI) recommends a risk management approach to impacts and adaptation. With confidence in seasonal changes, there is concern for spring high water events which will increase the threat of flooding from rivers, streams, and groundwater, and promote sanitary sewer overflows into waterways. Understanding the forecasted impacts and vulnerabilities is a first step toward implementing adaptation strategies (Liebl, 2011)

In the Great Lakes basin there has been significant progress in defining what adaptation means for conservation and restoration efforts in the region. For example, tools to help managers incorporate adaptation strategies into planning efforts have been developed by such organizations as the National Wildlife Federation, the Climate Adaptation

Knowledge Exchange, regional Sea Grant offices, NOAA, and Natural Resources Canada to name a few (Koslow,

2010 and Natural Resources Canada). A few examples of projects or programs which have integrated adaptive strategies into management processes relevant to increased precipitation and altered distribution of precipitation events include the following:

Wisconsin Imitative on Climate Change Impacts: The Wisconsin Imitative on Climate Change Impacts partnered with the Milwaukee Sewage Department on a project designed to provide estimates of the effects of altered precipitation patterns on sewage overflows to allow for better stormwater management.

260

City of Chicago: The city currently utilizes green roofs as a means of reducing the amount of impervious surface and thus reducing stormwater runoff.

City of Detroit: The City of Detroit uses green alleys, or concrete alleyways fitted with permeable pavement and open-bottom catch basins, to reduce stormwater runoff. Although only one alleyway has been built thus far, it is capable of holding up to a 10-year storm without water going into the storm drain

(Koslow, 2010).

Updating flood profiles to locate at risk areas (e.g., hazardous materials, wells and septic, roadways) can assist in prioritizing resource spending. Mapping hydric soils, regulating development of these lands, and restoring or enhancing existing ecological buffer zones can improve stormwater storage capacity and reduce downstream flood magnitudes. Collectively, enhancement of stormwater storage capacity and the disconnection of stormwater inputs to sanitary systems will reduce the frequency and magnitude of sanitary overflows in combined stormwater and sanitation systems (Liebl, 2011).

Adaptation is not explicit to infrastructure, but also to programs and policy. Adaptation in programs and policy calls for ongoing and permanent monitoring for re-assessment and adjustment (Policy Horizons Canada 2010). At minimum, programs and policy should embed mechanisms for adjustments informed by monitoring. Flood management and the protection of ground water resources will benefit from the restoration and enhancement of surrounding wetlands and open space (Adapting to Climate Change, NOAA 2010 & Liebl, 2011). However, areas of functional conservation will likely migrate or perish. To provide continued protection to these areas as they migrate with climate change requires particular mechanisms. Rolling easements, for example, are designed to promote the natural migration of shorelines. Defined by physical characteristics such as the line of vegetation, the delineation of the easement is adapted to change in accordance with changing water levels (Adapting to Climate

Change, NOAA 2010).

The other way in which climate change can be addressed is through mitigation, or technological change and substitution that reduce resource inputs and emissions per unit of output (Koslow, 2010).

Assessing Data Quality

Strongly

Agree Agree

Neutral or

Unknown Disagree

Strongly

Disagree Data Characteristics

1. Data are documented, validate or qualityassured by a recognized agency or organization

2. Data are traceable to original sources

3. The source of the data is a known, reliable and respectable generator of data

4. Geographic coverage and scale of data are appropriate to the Great Lakes basin

5. Data obtained from sources within the

U.S. are comparable to those from Canada

6. Uncertainty and variability in the data are documented and within acceptable limits for this indicator report

X

X

X

X

X

Not

Applicable

X

Acknowledgments

Author:

Sarah Neville, ORISE Research Fellow Appointed to the U.S. Environmental Protection Agency Great Lakes

National Program Office

Robert Liva, ORISE Research Fellow Appointed to the U.S. Environmental Protection Agency Great Lakes

National Program Office

261

Contributor:

Deke Arndt, Chief, Climate Monitoring Branch, National Oceanic and Atmospheric Administration

Information Sources

Burnett, a., Kirby, K., Norton, D. 2003. Increasing Great Lakes lake-effect snowfall during the twentieth century: a regional response to global warming? Journal of Climate 16, 3535-3542.

Hodgkins, G.A., Dudley, R.W., and Aichele, S.S.. 2007. Historical changes in precipitation and streamflow in the

U.S. Great Lakes Basin, 1915–2004: U.S. Geological Survey Scientific Investigations Report 2007–5118, 31 p.

Kling, G.W., Hayhow, K., Johnson, L.B., Magnuson, J.J., Polasky, S., Robinson, S.K., Shuter, B.J., Wander, M.M.,

Wuebbles, D.J., and Zak, D.R. 2003. Confronting Climate Change in the Great Lakes Region: Impacts on Our

Communities and Ecosystems. Union of Concerned Scientists and The Ecological Society of America.

Koslow, M. (2010). Improving the Odds: using Climate-Readiness Planning to Reduce the Impacts of Climate

Change on the Great Lakes Ecosystem. National Wildlife Federation.

Liebl, David S. Stormwater Management and Climate Change: Implications for the Great Lakes Region. A Global

Change-Local Impact presentation with Ohio State University. 2011. Date accessed 14 October 2011.

<http://www.wicci.wisc.edu/uploads/Liebl_2-15-11_OSUWebinar.pdf>

National Oceanic and Atmospheric Administration (NOAA). 2010. Adapting to Climate Change: A Planning Guide for State Coastal Managers. NOAA Office of Ocean and Coastal Resource Management. Date Accessed 14

October 2010 <http://coastalmanagement.noaa.gov/climate/adaptation.html>

Patino, Lorena. Government of Canada. 2010. Understanding Climate Change Adaptation and Adaptive Capacity

Synthesis Report. Date Accessed 12 October 2010 <www.pri-prp.gc.ca>

Understanding Climate Change Adaptation and Adaptive Capacity. Policy Horizons Canada. 2010. Date Accessed

14 October 2010. <http://www.horizons.gc.ca/page.asp?pagenm=2010-0041_>

Wuebbles, D.J., and Hayhoe, K. 2004. Climate Change Predictions for the United States Midwest. Mitigation and

Adaptation Strategies for Global Change 9:335-363.

List of Tables

Table 1

. Climate Divisions

Source: NOAA

List of Figures

Figure 1

. Trends in Precipitation in the Great Lakes

Source: NOAA

Last Updated

State of the Great Lakes 2011

262

Climate Divisions

State

Minnesota

Wisconsin

Illinois

Indiana

Michigan

Ohio

Pennsylvania

New York

Climate Division

3,6

1,2,3,6,9

2

1,2,3

1,2,3,4,5,6,7,8,9,10

1,2,3,4

10

1,9,10

Table 1

. Climate Divisions

Source: NOAA

Figure 1

. Trends in Precipitation in the Great Lakes

Source: NOAA

263

Fish Consumption Restrictions Advisory Rating Scale

Overall Assessment

Status: Fair

Trend: Undetermined

Rationale: U.S. Overall Average Score – 4.02, Ontario MOE Overall Average Score – 3.74. The Fish

Consumption Advisory Rating Scale Indicator was created to categorize the different levels of risk to sensitive populations (children under 15 and women of child bearing age) from consuming certain fish species in each of the Great Lakes. The Indicator involves a five-level, Consumption

Advisory Rating Scale that corresponds to the current contaminant levels in Great Lakes fish.

Protective measures associated with each consumption advisory rating scale allows a flexible, graduated and appropriate response to the level of risk from consumption. The information used to conduct this analysis demonstrates that there are consumption advisories in all of the Great

Lakes for a variety of species of fish that are driven by PCBs, mercury, dioxin, chlordane, mirex and toxaphene (Table 1). The level of the advisory varies according to the species, size and location of the fish. The average score for Lake Trout and Walleye (Lake Erie) (Figure 1 & 2) in the Great Lakes basin falls into the one meal per month to six meals per year category (Tables 2

& 3). Some locations and size classes allow for unlimited or 1 meal per week consumption of these fish while others are under do not eat advisories. Contaminant trends cannot be identified through this type of assessment.

Lake-by-Lake Assessment

Lake Superior

Status: Fair

Trend: Undetermined

Rationale:

U.S. Lake Average Score - 2.67, Ontario MOE Lake Average Score - 2.81.

The U.S. States of

Minnesota, Wisconsin, and Michigan and the Province of Ontario issue consumption advice for fish from the waters of Lake Superior. Advisories in Lake Superior are driven by PCBs, dioxin, mercury, chlordane, and toxaphene with PCBs continuing to be the largest contributor (Table 1). Lake Superior fish consumption advisories for Lake Trout range between unrestricted or 1 meal per week for some small fish to do not eat for some large fish (Tables 2 & 3).

Lake Michigan

Status: Fair

Trend: Undetermined

Rationale:

U.S. Lake Average Score – 3.95.

The U.S. States of Michigan, Wisconsin, Illinois, and Indiana issue consumption advice for fish consumed from the waters of Lake Michigan. Advisories in Lake

Michigan are driven by PCBs and chlordane with PCBs continuing to be the largest contributor (Table

1). Lake Michigan fish consumption advisories for Lake Trout range from 1 meal per month to do not eat (Tables 2 & 3).

Lake Huron

Status: Poor to Fair

Trend: Undetermined

Rationale:

U.S. Lake Average Score – 5, Ontario MOE Lake Average Score - 3.70.

The U.S. State of

Michigan and the Province of Ontario issue consumption advice for fish consumed from the waters of

Lake Huron. Advisories in Lake Huron are driven by PCBs, dioxin, and mercury with PCBs continuing to be the largest contributor (Table 1). Lake Huron fish consumption advisories for Lake Trout range

264

between unrestricted or 1 meal per week in small fish to do not eat in large fish (Tables 2 & 3). Please note that a far less diverse data set was used in the creation of a lake average, for the U.S., due to the fact that only the state of Michigan borders Lake Huron.

Lake Erie

Status: Fair

Trend: Undetermined

Rationale:

U.S. Lake Average Score - 3.5, Ontario MOE Lake Average Score – 3.74 (Lake Trout) 1.86

(Walleye).

The U.S. States of Michigan, Ohio, and Pennsylvania and the Province of Ontario issue consumption advice for fish consumed from the waters of Lake Erie. Advisories in Lake Erie are driven by PCBs, dioxin, and mercury with PCBs continuing to be the largest contributor (Table 1). Lake Erie fish consumption advisories for Lake Trout in both the U.S. and Canada range between the 1 meal per month advice category to 6 meals per year (Tables 2 & 3).

Lake Ontario

Status: Poor

Trend: Undetermined

Rationale:

U.S. Lake Average Score – 5, Ontario MOE Lake Average Score 4.54.

The U.S. State of New

York and the Province of Ontario issue consumption advice for fish consumed from the waters of Lake

Ontario. Advisories in Lake Ontario are driven by PCBs, dioxin, mercury and mirex with PCBs continuing to be the largest contributor (Table 1). Lake Ontario fish consumption advisories for Lake

Trout range between unrestricted or 1 meal per week for some small fish in Ontario to do not eat

(Tables 2 & 3). Please note that a far less diverse data set was used in the creation of a lake average, for the U.S., due to the fact that only the state of New York borders Lake Ontario.

For more information on the fish consumption advice for species not included in this assessment, please visit: http://water.epa.gov/scitech/swguidance/fishshellfish/fishadvisories/states.cfm

or www.ontario.ca/fishguide

Purpose

To assess the restrictive nature of fish consumption advisories issued in the Great Lakes.

To determine what contaminants are driving consumption advisories in the Great Lakes.

To infer potential effects to human health through consumption of contaminated fish.

The Fish Consumption Restrictions indicator is used in the Great Lakes indicators suite as an Impact indicator in the Human Impacts top level reporting category.

Ecosystem Objective

Fish in the Great Lakes ecosystem should be safe to eat and consumption should not be limited by contaminants of human origin. Reductions in the number and severity of fish consumption restrictions will reflect an improvement in environmental quality and the potential for reduced exposure to contaminants from consumption of Great Lakes fish. This indicator supports Annexes 1, 2 and 12 of the GLWQA.

Ecological Condition

History and Background

Since the 1970s, there have been declines in the levels of many PBT chemicals in the Great Lakes basin due to bans on the use and/or production of harmful substances and restrictions on emissions. However, because of their ability to bioaccumulate and persist in the environment, PBT chemicals continue to be a significant concern. Historically,

PCBs have been the contaminant that most frequently limited the consumption of Great Lakes sport fish. In some

265

areas, dioxins/furans, mercury, and toxaphene (Lake Superior) do contribute to restrictive fish consumption advisories.

Annex 2 of the Great Lakes Water Quality Agreement (United States and Canada 1987) requires Lakewide

Management Plans (LaMPs) to define “…the threat to human health posed by critical pollutants… including their contribution to the impairment of beneficial uses.” Both the Protocol for a Uniform Great Lakes Sport Fish

Consumption Advisory (Great Lakes Sport Fish Advisory Task Force, 1993) and the Guide to Eating Ontario Sport

Fish (OMOE 2007) are used to assess the status of the ecosystem by comparing contaminant concentrations in fish to levels that result in consumption advice. Contaminants upon which consumption advisories are based in Canada and the U.S. include PCBs, dioxin/furans, mercury, toxaphene, chlordane and mirex (Tables 2 & 3).

Contaminant concentrations in sport fish from both the OMOE program and the U.S. Great Lakes State programs determine the advised maximum consumption frequency of fish meals. Both countries calculate and issue their own advice (Tables 2 & 3). In 2009, the Great Lakes National Program Office’s Great Lakes Fish Monitoring and

Surveillance Program eliminated the sport fish analysis portion of its program and refocused its efforts on identifying emerging chemicals in whole fish. In lieu of trend monitoring data, both countries are presenting information on the number and level of Fish Consumption Advisories. The tracking of the number of advisories for common species, Lake Trout and Walleye, and chemicals over time will allow for sufficient identification of the status of the environment over time.

Measure

To numerically quantify fish consumption advisories in the Great Lakes, a metric was created that scores the level of advisories. Scores on a scale of 1 to 5 were given based on the level of consumption advisories for the sensitive population (women of child-bearing age and children under 15) across all size classes of Lake Trout in each state and province (Table 4). Lake Trout was chosen because it is a top predator fish and represents a ‘worst case scenario’ for fish consumption advisories. The average score across all states and provinces for a lake was used as the measure.

To increase uniformity between advisories issued by the states and Canada, advisories were broken down by fish length and scored in increments of 2”. For states that do not specify a minimum or maximum class size in their advice, information was broken out into sizes according to that state’s fish regulations between 6 and 30 inches.

The status of each lake was determined based on the average lakewide score. Good is a lakewide score of <2. Fair is a lakewide score of 2 to 4. Poor is a lakewide score >4. The target for this indicator is a lakewide score of 1 for each lake and for the entire Great Lakes basin, indicating that there are no fish consumption advisories.

Fish Consumption Restrictions in the Great Lakes

Fish consumption advisories for Lake Trout and Walleye in the Great Lakes range from unrestricted consumption to do not eat advisories. Although U.S. and Canadian data cannot be directly compared due to differences in the way consumption advisories are issued, they do follow similar patterns in terms of the levels of consumption restrictions in the individual Great Lakes. Consumption advisories for Lake Trout are most restrictive in Lakes Ontario and

Huron and least restrictive in Lake Superior (Figures 1 & 2). All lakes have do not eat advisories for at least some size classes of Lake Trout.

Differences in advisories within and between lakes reflect different levels of contaminant concentration in the air and sediment as well as differences in sampling regimes and locations between the states and Ontario. PCBs continue to drive most fish advisories despite the fact that they were banned in the U.S. and Canada in the 1970s.

This is likely due to large amounts of PCBs still persisting in the environment and being released from old electrical equipment. However, it is noteworthy that the PCB levels in Great Lakes fish have declined substantially since the

1970s (Figure 3).

266

Linkages

Fish consumption restrictions may be the result of pressures such as contamination in sediment, atmospheric deposition, pesticides in tributaries and industrial loadings. Contaminants from these sources bioaccumulate in fish and can result in restrictive fish consumption advisories. The number and level of restrictive fish consumption advisories may decrease over time as the result of sediment remediation and industrial efficiencies or may increase as a result of, for example, higher contaminant levels and/or changes in methods of calculating advisories (e.g., incorporation of new science on toxicity of contaminants).

Management Challenges/Opportunities

Health risk communication is a crucial component to the protection and promotion of human health in the Great

Lakes. Enhanced partnerships between states and tribes involved in the issuing of fish consumption advice and U.S.

EPA headquarters will improve U.S. commercial and non-commercial fish advisory coordination. In Canada, acceptable partnerships exist between the federal and provincial agencies responsible for providing fish consumption advice to the public.

At present, PCBs, mercury, and chlordane are the only PBT chemicals that have uniform fish advisory protocols across the U.S. Great Lakes basin. The Great Lakes Sport Fish Advisory Task Force is currently drafting additional uniform PBT advisories in order to limit confusion of the public that results from issuing varying advisories for the same species of sport fish across the basin.

In order to best protect human health, increased monitoring and reduction of PBT chemicals need to be made a priority. In particular, monitoring of contaminant levels in environmental media and biomonitoring of human tissues need to be addressed, as well as assessments of frequency and type of fish consumed. In addition, improved understanding of the potential negative health effects from exposure to PBT chemicals is needed.

Comments from the author(s)

Differences in the way consumption advisories are developed in the U.S. and Canada means that data cannot be directly compared between the two countries. Differences exist in terms of the contaminant concentrations used to determine consumption restrictions, the number of sample sites, frequency of sampling, and years of data that advisories are based on. For example, sample collection and release of advice for the Ontario MOE and the Great

Lakes States may be on different schedules. Lake Trout were selected for this indicator as they are top predator fish and therefore reflect a ‘worst case scenario’ for fish consumption restrictions and are not representative of all fish.

Collection and analysis, for both countries, are subject to availability of funds and change with time.

An increased focus on emerging chemicals is occurring in monitoring programs in the United States and Canada.

While the Great Lakes National Program Office no longer collects or analyzes sport fish fillets, the Office has instituted an Emerging Chemicals Surveillance Program in whole fish that looks to identify the presence or absence of emerging chemicals of interest and will inform State monitoring and advisory programs. 2011 will be the first year of this program and results will be shared through various outlets, including SOLEC, as they are received.

The Ontario Ministry of the Environment continues to monitor contaminants of long term concern such as PCBs, dioxins/furans, mercury and organochlorine pesticides. Recently, the ministry has started analyzing some chemicals of emerging concern for the Great Lakes environment such as polybrominated diphenylethers (PBDEs), perfluorinated compounds (PFCs) and polychlorinated naphthalene (PCNs) in selected fish samples.

Assessing Data Quality

Data Characteristics

1. Data are documented, validated, or quality-assured by a recognized agency or organization

Strongly

Agree

Agree

x

Neutral or

Unknown

Disagree

Strongly

Disagree

Not

Applicable

267

Data Characteristics

2. Data are traceable to original sources

3. The source of the data is a known, reliable and respected generator of data

4. Geographic coverage and scale of data are appropriate to the Great Lakes basin

5. Data obtained from sources within the

U.S. are comparable to those from

Canada

6. Uncertainty and variability in the data are documented and within acceptable limits for this indicator report

Strongly

Agree

Agree

x x x x

Neutral or

Unknown

Disagree

Strongly

Disagree

Not

Applicable

x

Acknowledgments

Authors:

Elizabeth Murphy, U.S. Environmental Protection Agency GLNPO (312-353-4227 or [email protected]

)

Michelle Craddock, Oak Ridge Institute for Science and Education (ORISE) Research Fellow, Appointed to U.S.

Environmental Protection Agency, GLNPO

Satyendra Bhavsar, Sport Fish Contaminant Monitoring Program, Ontario Ministry of Environment, Etobicoke, ON

Contributor:

Jackie Fisher

Information Sources

Sport Fish Consumption Advisory Programs

Minnesota Department of Health - http://www.health.state.mn.us/divs/eh/fish/index.html

Wisconsin Department of Natural Resources - http://dnr.wi.gov/fish/consumption/

Illinois Department of Public Health - http://www.idph.state.il.us/envhealth/factsheets/fishadv.htm

Indiana Department of Health - http://www.idph.state.il.us/envhealth/factsheets/fishadv.htm

Michigan Department of Community Health - http://www.michigan.gov/mdch/0,1607,7-132-54783_54784_54785--

-,00.html

Ohio Environmental Protection Agency - http://www.epa.state.oh.us/dsw/fishadvisory/index.aspx

Pennsylvania Department of Environmental Protection - http://www.portal.state.pa.us/portal/server.pt/community/fish_consumption/10560

New York Department of Environmental Conservation - http://www.dec.ny.gov/outdoor/7736.html

Ontario Ministry of the Environment - www.ontario.ca/fishguide

Great Lakes Sport Fish Advisory Task Force. 1993. Protocol for a uniform Great Lakes sport fish consumption advisory. http://fn.cfs.purdue.edu/anglingindiana/HealthRisks/TaskForce.pdf, last accessed July 22, 2005.

United States and Canada. 1987. Great Lakes Water Quality Agreement of 1978, as amended by Protocol signed

November 18, 1987. Ottawa and Washington. http://www.ec.gc.ca/glwqa/

Bhavsar, S.P., D.A. Jackson, A. Hayton, E.J. Reiner, T. Chen, and J. Bodnar. 2007. Are PCB levels in fish from the

Canadian Great Lakes still declining? Journal of Great Lakes Research 33(3): 592-605.

Stow, C.A., E.C. Lamon, S.S. Qian, and C.S. Schrank. 2004. Will Lake Michigan lake trout meet the Great lakes strategy 2002 PCB reduction goal? Environmental Science & Technology 38(2): 359-363.

List of Tables

Table 1.

Contaminants on which the fish advisories are based on by lake for Canada and the United States.

Source: Compiled by U.S. EPA, Great Lakes National Program Office

Table 2.

Consumption limits set by the Guide to Eating Ontario Sport Fish (based on Health Canada TDIs).

* Women of childbearing age and children under 15

268

Source: Ontario Ministry of the Environment (2011)

Table 3.

Consumption limits set by the Great Lakes Sport Fish Advisory Task force. *Women of childbearing age and children under 15

Source: Great Lakes Sport Fish Advisory Task Force (PCB Protocol 1993, Mercury Protocol 2007, Chlordane

Discussion Paper)

Table 4.

Consumption advisory scores used to calculate metric for the Fish Consumption Restrictions Indicator

Source: U.S. Environmental Protection Agency and Ontario Ministry of the Environment

List of Figures

Figure 1

. U. S. Fish Consumption Advisory Rating Scale

Source: U.S. State Consumption Advisory Programs. Compiled by U.S. EPA, Great Lakes National Program

Office

Figure 2

. Canada Fish Consumption Advisory Rating Scale

Source: Ontario Ministry of the Environment. Compiled by U.S. EPA, Great Lakes National Program Office

Figure 3

. Long-term trends of total-PCB in Great Lakes lake trout.

Source: Data were adopted for skin-on lake trout fillets samples from Lake Michigan from Stow et al. 2004 and for skin-off lake trout fillet samples from the other lakes from Bhavsar et al. 2007.

Last Updated

Some content was updated for the 2011 document.

Last complete updated was for the

State of the Great Lakes 2009

report

Contaminants Responsible for Advisories*

Lake/ State or Province

Superior/Michigan

Superior/Wisconsin

Superior/Minnesota

Superior/Ontario

Huron/Michigan

Huron/Ontario

Erie/New York

Erie/Ohio

Erie/Pennsylvania x x x x x

PCB

x x x x

Dioxin

x x x x

Mercury

x x x x x x x

Chlordane

x

Mirex Toxaphene

x

Erie/Michigan

Erie/Ontario

Ontario/New York

Ontario/Ontario

Michigan/Illinois

Michigan/Michigan

Michigan/Indiana x x x x x x x x x x x

x x x x x x x x x

Michigan/Wisconsin x x

Table 1.

Contaminants listed in state/provincial fish consumption advisories. *Not all states/provinces issue advisories for all of the listed contaminants.

Source: Great Lakes states and Ontario Ministry of the Environment

269

Advised meals per month

8

4

2

1

Do not eat

Table 2a Advised meals per month for general population

PCBs (ppm)

<0.105

0.105-0.211

0.211-0.422

0.422-0.844

>0.844

Mercury

(ppm)

<0.61

0.61-1.23

1.23-1.84

-

>1.84

Chlordane

(ppm)

<0.059

0.059 - 0.117

0.117 - 0.235

0.235 - 0.469

>0.469

Mirex (ppm)

<0.082

0.082-0.164

0.164-0.329

0.329-0.657

>0.657

Photomirex

(ppm)

<0.015

0.015-0.031

0.031-0.061

0.061-0.122

>0.122

Toxaphene

(ppm)

<0.235

0.235-0.469

0.469-0.939

0.939-1.877

>1.877

PFOS (ppm)

<0.080

0.080 - 0.160

0.160 - 0.320

0.320 - 0.640

>0.640

Dioxin/DL-

PCBs (ppt)

<2.7

2.7 - 5.4

5.4 - 10.8

10.8 - 21.6

>21.6

Table 2b Advised meals per month for sensitive* population

Advised meals per month

8

4

Do not eat

Do not eat

PCBs (ppm)

<0.105

0.105 - 0.211

>0.211

>0.211

Mercury

(ppm)

<0.26

0.26-0.52

>0.52

-

Chlordane

(ppm)

<0.059

0.059 - 0.117

>0.117

>0.117

Mirex (ppm)

<0.082

0.082 - 0.164

>0.164

>0.164

Photomirex

(ppm)

<0.015

0.015 - 0.031

>0.031

>0.031

Toxaphene

(ppm)

<0.235

0.235 - 0.469

>0.469

>0.469

PFOS (ppm)

<0.080

0.080 - 0.160

>0.160

>0.160

Do not eat >0.211 >0.52 >0.117

*Women of child-bearing age and children under 15.

>0.164 >0.031 >0.469 >0.160

Table 2.

Consumption limits set by the Guide to Eating Ontario Sport Fish (based on Health Canada TDIs).

Source: Ontario Ministry of the Environment (2011)

Consumption limits

Consumption

Advice Groups*

Concentration of

PCBs (ppm)

0 – 0.05 Unrestricted

Consumption

2 meals/ week

1 meal/ week

1 meal/ month

6 meals/ year

Do not eat

0.06 – 0.2

0.21 – 1.0

1.1 – 1.9

>1.9

Concentration of Hg

(ppm)

0 <= 0.05

> 0.05 <= 0.11

>0.11 <= 0.22

>.22 <= 0.95

Concentration of Chlordane

0 - 0.15

0.16 - 0.65

0.66 - 2.82

2.82 - 5.62

>5.62

(ppm)

>0.95

* Women of childbearing age and children under 15

Table 3.

Consumption limits set by the Great Lakes Sport Fish Advisory Task force.

Source: Great Lakes Sport Fish Advisory Task Force (PCB Protocol 1993, Mercury Protocol 2007, Chlordane

Discussion Paper)

Consumption advisory scores

Consumption Advisory

Unrestricted (8 meals / month)

1 meal/week (4 meals / month)

1 meal/month

6 meals/year

Score

1

2

3

4

Do not eat 5

Table 4.

Consumption advisory scores used to calculate metric for the Fish Consumption Restrictions Indicator

Source: U.S. Environmental Protection Agency and Ontario Ministry of the Environment

Dioxin/DL-

PCBs (ppt)

<2.7

2.7 - 5.4

>5.4

>5.4

>5.4

270

Figure 1

. U. S. Fish Consumption Advisory Rating Scale

Source: U.S. State Consumption Advisory Programs. Compiled by U.S. EPA, Great Lakes National Program

Office

Figure 2

. Canada Fish Consumption Advisory Rating Scale

Source: Ontario Ministry of the Environment. Compiled by U.S. EPA, Great Lakes National Program Office

271

Figure 3

. Long-term trends of total-PCB in Great Lakes lake trout.

Source: Data were adopted for skin-on lake trout fillets samples from Lake Michigan from Stow et al. 2004 and for skin-off lake trout fillet samples from the other lakes from Bhavsar et al. 2007.

272

Forest Cover

Overall Assessment

Component 1: Percent of forested lands within a watershed

Status:

Trend:

Fair

Improving

Rationale: Forested lands are a large percentage of land area within the Lake Superior basin (85%), a moderate amount in the Lake Michigan, Huron and Ontario basins (49% - 61%) and low in the

Lake Erie basin (20%) based on satellite imagery. Trends in forest cover, based on forest inventory data or remote sensing, suggest that forest cover is only changing slowly in all basins.

However, it is important to note that the forest cover trends being seen in the Great Lakes basin are quite small. Changes in forest types, composition and localized decreases in forest cover remain a concern.

Component 2: Percent of forested lands within riparian zones

Status: Fair

Trend: Undetermined

Rationale: Similar to total forest cover, forested cover types in the riparian zone of water bodies is high in the

Lake Superior basin, moderate in the Lake Michigan, Huron and Ontario basins and low in the

Lake Erie basins. Adequate, consistent long-term data is not available to assess trends.

Lake-by-Lake Assessment

Lake Superior

Component 1: Percent of forested lands within a watershed

Status: Good

Trend: Improving

Rationale: The Lake Superior basin has a high forest cover (85%) and low rates of agriculture and development

(3.2%). These data suggest that there is unlikely to be long-term impairment of water quality.

Component 2: Percent of forested lands within riparian zones

Status: Good

Trend: Undetermined

Rationale: With 96% of the riparian zones of water bodies in the Lake Superior basin having forest cover, these waters are likely to be well protected. Insufficient data is available to assess trends.

Lake Michigan

Component 1: Percent of forested lands within a watershed

Status: Fair

Trend: Improving

Rationale: There is considerable variation in the watersheds draining into Lake Michigan, Generally there is high forest cover in the northern watersheds, while southern watersheds have low forest cover.

Component 2: Percent of forested lands within riparian zones

Status: Fair

Trend: Undetermined

Rationale: Northerly watersheds have high forest cover in riparian zones, while southern watersheds have significant agricultural activity in riparian zones that may decrease water quality and ecosystem integrity. Insufficient data is available to assess trends.

273

Lake Huron

Component 1: Percent of forested lands within a watershed

Status: Good

Trend: Improving

Rationale: Most northerly watersheds have a high level of forest cover with the watersheds, while more southerly ones have low forest cover. There is some potential in southerly watersheds to have impairments in water quality and ecosystem integrity.

Component 2: Percent of forested lands within riparian zones

Status: Fair

Trend: Undetermined

Rationale: Watersheds in the southern portion of the basin have moderate levels of agriculture and forests in the riparian zones which could lead to impairments in water quality and ecosystem integrity.

Lake Erie

Component 1: Percent of forested lands within a watershed

Status: Poor

Trend: Deteriorating

Rationale: Lake Erie has the lowest coverage by forests in the lake basin and the highest percentage of agricultural and developed lands. There is a large potential for water quality problems and risks to ecological integrity.

Component 2: Percent of forested lands within riparian zones

Status: Poor

Trend: Undetermined

Rationale: A high level of agricultural activities and a low proportion of forest cover in riparian zones suggests heightened threat to water quality and ecosystem integrity

Lake Ontario

Component 1: Percent of forested lands within a watershed

Status: Fair

Trend: Deteriorating

Rationale: Most watersheds in the Lake Ontario basin have low forest covers and significant proportions of the land area in agricultural activities with the associated risks to water quality.

Component 2: Percent of forested lands within riparian zones

Status: Fair

Trend: Undetermined

Rationale: Moderate levels of forest and agricultural covers in riparian zones in the Lake Ontario basin suggest there is moderate risk to water quality and ecosystem integrity.

Purpose

This indicator describes the forest cover that is required to perform the hydrologic functions and host the organisms and essential processes that are necessary for supplying high quality water and protecting the physical integrity of the watershed.

The Forest Cover indicator is used in the Great Lakes indicator suite as a State indicator in the Landscape and

Natural Processes top level reporting category.

274

Ecosystem Objective

To have a forest composition and structure that most efficiently conserves the natural ecological diversity of the region.

Ecological Condition

This indicator includes two components:

Percent of forested lands within watershed by lake basin, over time.

Percent of forested lands within riparian zones by watershed, over time.

Component 1 summarizes the percent of forested lands by watershed within each lake basin. Decades of research and monitoring have shown that water draining forested watersheds is of high quality, as measured by sediment yields, nutrient loadings, contaminant concentrations and temperatures. Forest cover also contributes to many other ecosystem services, including controlling soil erosion, increasing groundwater infiltration, stabilizing shorelines and mitigating storm run-off. Leaf litter and woody debris provide critical food and habitat for fish and other aquatic wildlife.

In general, an increase in forest cover improves water quality. Ernst (2004) in a small survey of municipal water systems, showed that water treatment costs can be directly related to the degree of forest cover in the source watershed. The function she developed suggests that treatment costs are lowest at levels of forest cover above ~60%.

Other studies have been less successful in discovering empirical relationships between forest cover and the economics of municipal water supplies. For the purposes of this report, and subject to further discussion, we have used the following end-points in assessing the status and trends of Great Lakes watersheds: Good = >60% forest cover by lake basin; Fair = 30 – 60% forest cover by lake basin: and Poor = <30% forest cover by lake basin.

Figure 1 shows the tertiary watersheds draining into the Great Lakes and their level of forest cover. There is a strong

N-S gradient evident in the degree of forest cover as would be expected given a similar gradient in population and agricultural activity. In the Lake Superior basin, 85% of the land area is forested (Table 1), with only minor amounts of development and agriculture. In all the other basins, forests have been replaced by development and agriculture, comprising 29% in the Lake Huron basin, ~45% in the Lake Michigan and Ontario basin and 78% in the Lake Erie basin (Table 1). However, it must be noted that within any given basin, there are watersheds with adequate to good forest cover.

Assessing trends in the forest cover indicator has proven difficult. Whereas the status of forest cover can be readily assessed through analysis of carefully checked and referenced satellite data, these data are usually available for single points in time. For this report, we have employed data for the US portions of the lake basins from forest inventory programs that can provide a time series up to 30 years and for the Canadian portions of the basins from satellite imagery for 2009 and 2011. Table 3 shows that in the US portion of all lake basins, there is a trend towards increasing forest cover, whereas there are mostly weak trends towards decreasing forest cover in the Canadian portion of the basins.

Component 2 summarizes the area of riparian zones (30 metre buffer around all surface waters) that is forested within each lake basin. Where watersheds have experience large land-use changes due to agricultural activities or urban and suburban development, increased forest coverage within a riparian zone can mitigate many of the potentially harmful impacts on water bodies. Forested riparian zones can decrease the amount of surface runoff to water bodies (reducing erosion), mitigate nutrient loadings from fertilizer application and other non-point source pollutants and increases the capacity of the ecosystem to store water. Riparian zones can also important sources of energy and material to aquatic systems and help regulate water temperatures.

275

The end-points for this component have been defined as: Good = >80% forest cover in riparian zones; Fair = 50 –

80% forest cover in riparian zones; and Poor = <50% forest cover in riparian zones.

This component was assessed by creating a 30 m buffer around all waterbodies in the National Hydrology Dataset

(US) and using it as a mask on the NLDC or Landcover 2008 data layers. On a lake basin level, the proportion of forest cover in riparian zones parallels that of the forest cover in the watersheds (Table 2). The Lake Superior basin has 96% of its riparian zones identified as forested, while only 31% of riparian zones in the Lake Erie basin are forested, with Lakes Michigan, Huron and Ontario being intermediate. Also similar to the forest cover component, agriculture and development are the competing land uses. There is also substantial variation at the tertiary watershed level with each of the lake basins (Figure 2). The northern watersheds have much higher rates of forested riparian zones than watersheds in the south, where there is much greater development and agriculture.

Trend analysis is not presently possible for this component. What is required is a time series of properly classified satellite imagery over a long enough time period (>20 years) in order to identify trends with any degree of reliability.

Linkages

The well-documented ability of forested lands to produce high quality water and for forested riparian areas to protect water resources has linkages to many other indicators. In particular, forest cover and forested riparian areas contribute directly to reducing nutrient, and other non-point source pollutant, loadings to the tributaries and lakes and ameliorate the effects of atmospheric deposition. Indirectly, the high quality water emanating for forested areas supports diverse aquatic communities. Climate change, through its effects on forest composition and function and on local hydrological processes is likely to affect the ability of forests to produce high quality water, although the magnitude and direction of these affects are not well known. For example, the decline to total annual runoff in many

Great Lakes basins may lead to increased concentrations of nutrients and contaminants in tributary waters. Also, changes in forest composition, due human activities (eg. forest management) or natural agents (eg. emerald ash borer), may affect water quality and/or quantity.

Management Challenges/Opportunities

The increasing recognition of the benefits of forest cover in general and forested riparian areas in particular is leading to changes in regional planning that preserve forest cover. The increasing adoption of forest management certification standards (eg. Forest Stewardship Council) is increasing the deployment of best practices to protect water resources in managed forests. However, there remain many opportunities for improvement. The application of

Integrated Watershed Management is not widely practiced and governance structures to support IWM are only slowly developing.

Comments from the author(s)

Estimating forest cover by remote sensing is widely used and generally reliable. However, many of the available datasets do not contain the long time series needed to adequately assess trends. Regular assembly of cross-border data sets are needed to measure changes in forest cover and to understand the drivers of change. Forest inventory data (eg. USFS FIADB) is also useful but Canada lacks an equivalent system. There also remains the challenge of integrating both forest inventory systems and remote sensing data across jurisdictions due to differences in goals and methodologies.

Assessing Data Quality

Data Characteristics

1. Data are documented, validated, or quality-assured by a recognized agency or organization

Strongly

Agree

Agree

X

Neutral or

Unknown

Disagree

Strongly

Disagree

Not

Applicable

276

Data Characteristics

2. Data are traceable to original sources

3. The source of the data is a known, reliable and respected generator of data

4. Geographic coverage and scale of data are appropriate to the Great Lakes basin

5. Data obtained from sources within the

U.S. are comparable to those from Canada

6. Uncertainty and variability in the data are documented and within acceptable limits for this indicator report

Strongly

Agree

Agree

X

X

X

Neutral or

Unknown

X

Disagree

Strongly

Disagree

X

Not

Applicable

Acknowledgments

Authors:

Fred Beall, Natural Resources Canada, Canadian Forest Service, Great Lakes Forestry Centre, 1219 Queen St E,

Sault Ste. Marie, ON, P6A 2E5; email: [email protected]

; phone 705 541-5553

Contributors:

Charles Perry and Dale Gormanson, USDA Forest Service, 1992 Folwell Avenue, St. Paul, MN 55108; Bill Dalton and Larry Watkins, Ontario Ministry of Natural Resources, 70 Foster Dr., Suite 400, Sault Ste. Marie, ON, P6A 6V5

List of Tables

Table 1

. Percentage of land cover types by lake basin. Cover types were identified from Landsat satellite imagery for 2006 (US) and 2008 (Ontario), forest includes areas classisfied forest and treed wetlands.

Sources: National Land Classification Database (US) and Landcover 2008 (MNR, Forest Evaluations and Standards

Sections)

Table 2

. Percent of forest cover in riparian zones. Data based of summing cover types in a 30 m buffer around all water bodies.

Sources: National Land Classification Database (US) and Landcover 2008 (MNR, Forest Evaluations and Standards

Sections)

Table 3

. Change in forest cover within Great Lake Basins.

Notes: For US estimates of Superior Huron and Michigan the change was based of 2005 and 2009 data and for Erie and Huron 2005 and 2010 data

Sources: US basins based on analysis of USFS FIA plots and for Canada a comparison of 2009 and 2011 satellite images.

List of Figures

Figure 1

. Percent forest cover in tertiary watersheds (HUC8 in US and 4 digit in Ontario) of the Great Lakes. Forest cover was estimated from satellite imagery and includes a variety of forest types (i.e. deciduous, conifer, mixed) and treed wetlands.

Source: U.S. National Land Cover Database NLCD 2006 and Ontario Landcover 2008

Sources: US NLCD 2006 and Ontario Landcover 2008)

Figure 2

. Percentage of riparian zones with tertiary watersheds identified as forested.

Source: U.S. National Land Cover Database 2006 and Ontario Landcover 2008

Last Updated

State of the Great Lakes 2011

277

Percentage of land cover types by lake basin

Superior Michigan

Forest

Agriculture

85.0

1.7

49.1

35.1

Developed

Water

Wetland

1.5

10.4

1.0

10.3

3.0

2.3

Huron

61.0

24.6

4.4

7.4

0.9

Erie

19.6

61.0

17.3

1.0

0.8

Ontario

49.1

35.5

8.3

4.6

1.9

Table 1

. Percentage of land cover types by lake basin. Cover types were identified from Landsat satellite imagery for 2006 (US) and 2008 (Ontario), forest includes areas classified forest and treed wetlands.

Source: National Land Classification Database (US) and Landcover 2008 (MNR, Forest Evaluations and Standards

Sections)

Percent of forest cover in riparian zones

Forest

Agriculture

Urban

Superior

96.0

0.8

0.9

Michigan

63.4

23.4

7.7

Huron

72.7

19.9

3.0

Erie

30.9

54.5

11.7

Ontario

63.0

25.6

5.7

Wetland 1.6 5.0 2.0 2.7 5.1

Table 2

. Percent of forest cover in riparian zones. Data based on summing cover types in a 30 m buffer around all water bodies.

Source: National Land Classification Database (US) and Landcover 2008 (MNR, Forest Evaluations and Standards

Sections)

Percent change in forest cover within Great Lake Basins

Basin USA

Superior

Michigan

0.43

1.26

Canada

-0.01

Huron

Erie

Ontario

0.47

0.92

0.39

-0.3

-3.52

-1.96

Table 3.

Percent change in forest cover within Great Lake Basins.

Notes: For US estimates of Superior Huron and Michigan the change was based of 2005 and 2009 data and for Erie and Huron 2005 and 2010 data

Source: US basins based on analysis of USFS FIA plots and for Canada a comparison of 2009 and 2011 satellite images.

278

Figure 1

. Percent forest cover in tertiary watersheds (HUC8 in US and 4 digit in Ontario) of the Great Lakes. Forest cover was estimated from satellite imagery and includes a variety of forest types (i.e. deciduous, conifer, mixed) and treed wetlands.

Source: U.S. National Land Cover Database 2006 and Ontario Landcover 2008

Figure 2

. Percentage of riparian zones with tertiary watersheds identified as forested.

Source: U.S. National Land Cover Database 2006 and Ontario Landcover 2008

279

Greenhouse Gas Emissions

Overall Assessment

Trend: Undetermined

Rationale: Between 1990 and 2008, the long-term trend of greenhouse gas emissions in the Great Lakes region was increasing. In 2009, however, the region experienced its largest annual drop in emissions, resulting in the region’s lowest greenhouse gas emission in nineteen years.

Lake-by-Lake Assessment

Trends were not made on an individual lake basis.

Purpose

To provide greenhouse gas emissions trends in the Great Lakes region

The greenhouse gas emissions indicator is used in the Great Lake indicator suite as a driving force indicator in the Economic/Social category

Ecosystem Objective

A reduction in greenhouse gas emissions will contribute to achieving and maintaining environmental benefits, such as beneficial uses of the Great Lakes, as outlined in Annex 2 of the Great Lakes Water Quality Agreement.

Ecological Condition

The greenhouse gas emissions presented are reflective of the emissions for the Great Lake region as defined in this report (the whole Ontario as well as the whole of the eight Great Lakes States). Greenhouse gas emissions estimates are extracted from Environment Canada (National Inventory Report) and the United States Environmental

Protection Agency. In this report, the unit of analysis is million metric ton of carbon dioxide (CO2). The data only considers emissions from carbon dioxide (CO2) within the energy sector and the burning of fossil fuels, and not

CO2 emissions from other sources or from other greenhouse gases such as methane and nitrous oxide. While these sources are important and significant in calculating the total greenhouse gas emissions, they are not included in this report due to a lack of consistent data availability in the United States. Nonetheless, the measure in this report accurately illustrates the trends of greenhouse gas emissions in the Great Lakes region.

A) Great Lakes Region as a whole (Ontario and Eight Great Lakes States)

The total greenhouse gas emissions for the entire Great Lakes region (Ontario and the eight States) have fluctuated over the nineteen-year period (Table 1 and Figure 1). The long-term trend of the region is undetermined after the significant drop in greenhouse gas emission in 2009. Currently, when comparing the emission data from 1990 to

2009, the overall region has decreased by 1.7%. Despite the overall decrease in emission from 1990 to 2009, the region’s long-term emissions trend has always been increasing. In fact, when comparing the 1990 emissions with

2008, the region increased by 6.8%. It was not until 2009 where emissions experienced the biggest decline of 8.3%, likely in response to difficult overall economic conditions. In examining the short-term trend, the region experienced fluctuation. More specifically, as seen in Figure 2, greenhouse gas emissions decreased by 4.0% from

2005 to 2006. While the region experienced a growth of 2.2% in its subsequent year, greenhouse gas emissions rate decreased again by 2.8% in 2008. In 2009, the region continued to decrease and had the biggest decline of 8.3%, resulting in the region’s lowest greenhouse gas emission in nineteen years. Given the continuous fluctuation in the region, the short-term trend is undetermined.

B) Comparison between Ontario and Eight Great Lakes States

In Ontario, the total emission in 2009 was approximately 124.5 MMTCO2 (Table 1). Since 1990, Ontario’s emission has decreased by 0.6% with a yearly fluctuation rate range from a decline of 12.5% to a growth of 6.5%

280

(Table 1 & Figure 4). In a national context, Ontario’s greenhouse gas emission in 2009 represents 25.3% of the total emissions in Canada, a decrease of 5.0% from Ontario’s 1990 national share (Environment Canada: Canada

National Inventory Report) (Table 2). In the United States, the total emissions in the eight Great Lakes States in

2009 were 1441.7 MMTCO2 (Table 1). This has increased by 1.8 % since 1990. The annual fluctuation rate over the years has ranged from a decline of 8.0% to a decline of 3.7% (Figure 3 and Figure 4). In a national context, the eight great lakes states represent 26.2% of the total emissions in the United States in 2009, a decrease of 2.6% from the region’s 1990 national share (U.S. Environmental Protection Agency) (Table 3).

To obtain a greater understanding of greenhouse gas emissions within the region, the population data in 2009 have been included to examine the average greenhouse gas emissions per person. As gathered from the U.S. Census and

Statistics Canada, the total population in 2009 within the Great Lakes region was 96,978,002 and total greenhouse gas emissions were 1566.1 MMTCO2(Table 4). That year, emissions usage per capita was 16.2 MMTCO2 (Table

4). From 1990 to 2009, the Great Lakes region has experienced a 2.3% decrease in its overall greenhouse gas emissions per capita (Table 4 and 5).

Linkages

Emissions of greenhouse gases from human activities are causing climate change on a global scale. Most greenhouse gas emissions are caused by the burning of fossil fuels for energy and by industrial processes such as petroleum refining and cement manufacturing (Boyd 2001). While the dominant greenhouse gas is carbon dioxide (CO2), other principal greenhouse gases that enter the atmosphere and are derived from human activities include methane released from landfills and agriculture, nitrous oxide from fertilizers, and fluorinated gases from industrial processes

(EPA 2011.

Climate change is a major threat to the ecosystem with both direct and indirect effects on biological systems. Direct effects include increased temperature and increased CO2 levels associated with global climate change (Clark and

Sullivan 2007). These direct effects cause other indirect effects, such as changes to hydrologic cycles (precipitation and evaporation), changes in precipitation patterns, floods, and water shortages (Clark and Sullivan 2007).

Other examples include lower water levels and an impact on the areal extent and diversity of shoreline wetlands

(Alden and Mortsch 2004). Fluctuations in water levels within wetlands will likely cause changes in nutrient levels and may also enable the release of toxic metals such as mercury (Clark and Sullivan 2007).

The Great Lakes region has already started experiencing this warming effect and as additional warming occurs, a range of ecological changes and effects on wildlife are expected, with the most significant effects on aquatic and other species dependent on water bodies for breeding and feeding (Clark and Sullivan 2007). Changes in water temperature, water levels and flows, precipitation, air temperature, timing and duration of ice break up and disturbance hazards have all placed additional stress in the basin (Alden and Mortsch 2004). Higher air temperatures change the distribution and health of aquatic and terrestrial plants and animal species (Alden and Mortsch 2004).

The geographic distribution of numerous fish species is likely to be altered. Under a climatic warming, both northern and southern boundaries of species’ ranges in the Great Lakes region will shift northward. As a result, the fish communities of the Great Lakes will be altered due to invasion of warm water species and local extirpation of cool water and coldwater species (Mandrak 1989). The rise in water temperature will also enhance the growth of undesirable species (such as algal blooms). In many lakes, including Lake Michigan, changes in speciation are likely as water temperatures increase and water levels decline. Cold-water species such as salmonids (e.g. coho salmon and lake trout) will be under increased stress. Temperature increases also lowers oxygen levels in the summer, creating

“dead zones” which cannot support life and if dead zones persist, they can give rise to toxic algal blooms, damaging fisheries and create risks to human health (Clark and Sullivan 2007).

281

Management Challenges/Opportunities

There are many linkages between greenhouse gas emissions and stresses to ecosystem health. Great lakes community and decision makers should continue to support global, national, regional and local efforts to reduce greenhouse gas emissions.

Comments from the author(s)

In Canada, the Canadian National Inventory Report uses CO2 equivalent (CO2eq) as its official metric measure to examine greenhouse gases. The CO2eq value is calculated by multiplying the amount of the gas by its associated global warming potential. CO2eq is a more accurate way of displaying and understanding the emissions from various greenhouse gases and from various sectors. For more information on the official Canadian GHG data, table

6 outlines the CO2 emissions used in this report and the official GHG data (CO2eq) extracted from the National

Inventory Report and utilized by the Canadian Environmental Sustainability Indicators.

In comparison to the Great Lakes region, the total greenhouse gas emissions for the Great Lakes watershed would be less. Nonetheless, this data serves the indicator report’s purpose well by illustrating a trend that is a driving force behind many of the pressures on Great Lakes conditions. The investment required to break-down greenhouse gas emission trends specifically for the Great Lakes watershed boundary and/or on a lake-by-lake level would only be worthwhile if formal emission reduction targets are set for that defined geographic boundary.

Assessing Data Quality

Data Characteristics

1. Data are documented, validated, or qualityassured by a recognized agency or organization

2. Data are traceable to original sources

3. The source of the data is a known, reliable and respected generator of data

4. Geographic coverage and scale of data are appropriate to the Great Lakes basin

5. Data obtained from sources within the U.S. are comparable to those from Canada

6. Uncertainty and variability in the data are documented and within acceptable limits for this indicator report

Strongly

Agree

X

X

X

X

X

X

Agree

Neutral or

Unknown

Disagree

Strongly

Disagree

Not

Applicable

Acknowledgments

Author:

Brenda Yu, Great Lakes Division Intern, Environment Canada.

Contributors:

Dennis O’Farrell, Manager, Inforrmation and Indicators Division, Environment Canada.

Anton van Heusden, Project Officer, Greenhouse Gas Reporting Section, Environment Canada.

Rob Hyde, Great Lakes Program Officer, Great Lakes Division, Environment Canada.

Krista Verlis, Contractor, Environment Canada, Waterloo, Ontario.

Christian Vézina, Scientific and Technical Analyst, Information and Indicators Division, Environment Canada

Information Sources

Alden, M., Mortsch, L. 2004.

Impacts of Climate Change on the Great Lakes Impaired Beneficial Uses.

Meteorological & Geoastrophysical Abstracts.

< http://search.proquest.com/docview/20205193?accountid=32874 >

282

Boyd, D. R. 2001.

Canada vs. the OECD: An Environmental Comparison – Climate Change Greenhouse Gas

Emissions.

Victoria, British Columbia: University of Victoria Eco-Research Chair. p.16-17

< http://www.environmentalindicators.com/htdocs/PDF/Pgs21-30.pdf

>

Center of Excellence for Great Lakes and Human Health. 2011.

Harmful Algal Blooms in the Great Lakes: What they are and How they can Affect your Health”

< http://www.glerl.noaa.gov/res/Centers/HABS/habs.html

>

Clark, M. and Sullivan, R. 2007.

Can Biodiversity Survive Global Warming?

Chicago Wilderness Journal. Accessed August 4 2011

<www.chicagowilderness.org/.../CW%20Journal/CWJournalVol5No1.pdf>

Environment Canada. 2010.

About Canada’s Greenhouse Gas Inventory

< http://www.ec.gc.ca/gesghg/default.asp?lang=En&n=3E38F6D3-1 >

Environment Canada. 2010.

Canada’s Greenhouse Gas Inventory. National/Provincial/Territorial Tables: Table 7:

Ontario GHG Emissions Summary

< http://www.ec.gc.ca/ges-ghg/default.asp?lang=En&n=83A34A7A-1 >

Environment Canada. 2010.

Definitions and Glossary.

< http://www.ec.gc.ca/gesghg/default.asp?lang=En&n=B710AE51-1 >

Environment Canada. 2011.

Publications – National Inventory Report 1990 – 2009: Greenhouse Gas Sources Part 3

< http://www.ec.gc.ca/Publications/default.asp?lang=En&xml=A07097EF-8EE1-4FF0-9AFB-

6C392078D1A9 >

Mandrak, N.E. 1989.

Potential Invasion of the Great Lakes by Fish Species Associated with Climatic Warming

.

Journal of Great Lakes Research Volume 15(2): 306-316

United States Environmental Protection Agency (EPA). 2011.

State CO2 Emissions from Fossil Fuel Combustion

1990-2009

. < http://www.epa.gov/statelocalclimate/resources/state_energyco2inv.html#ref >

United States Environmental Agency (EPA). 2009.

CO2 Emissions from Fossil Fuel Combustion – Million metric

Tons 203 (MMTco2)

<http://www.epa.gov/statelocalclimate/documents/pdf/CO2FFC_2007.pdf>

United States Environmental Agency (EPA). 2011.

Inventory of U.S. Greenhouse Gas Emissions and Sinks 1990-

2009.

< http://www.epa.gov/climatechange/emissions/usinventoryreport.html

>

United States Environmental Agency (EPA). 2011.

Greenhouse Gas Emissions

< http://www.epa.gov/climatechange/emissions/index.html

>

List of Tables

Table 1

. Annual Greenhouse Gas Emissions in the Great Lakes Region’s Energy Sector, 1990-2009

Source: Environment Canada. 2011.

National Inventory Report

, and United States Environmental Protection

Agency. 2011.

State CO2 Emissions from Fossil Fuel Combustion 1990-2009.

Table 2

.

Ontario’s Percent of National Greenhouse Gas Emissions – 1990 and 2009

Source: Environment Canada. 2011.

National Inventory Report

Table 3

. Great Lakes State’s percent of national greenhouse gas emissions (energy sector) - 1990 and 2009

Source: United States Environmental Protection Agency. 2011.

State CO2 Emissions from Fossil Fuel Combustion

1990-2009.

Table 4

. 1990 Per Capita Greenhouse Gas Emissions (energy sector)

Source: Environment Canada. 2011.

National Inventory Report

, and United States Environmental Protection

Agency. 2011.

State CO2 Emissions from Fossil Fuel Combustion 1990-2009.

Environment Canada and United

States Environmental Protection Agency,

State of the Great Lakes 2011, Human Population

Table 5

. 2009 Per Capita Greenhouse Gas Emissions (energy sector)

Source: Environment Canada. 2011.

National Inventory Report

, and United States Environmental Protection

Agency. 2011.

State CO2 Emissions from Fossil Fuel Combustion 1990-2009,

and Environment Canada and United

States Environmental Protection Agency,

State of the Great Lakes 2011, Human Population

.

Table 6

. Ontario’s CO2 emissions compared to GHG emissions from 1990 to 2009

Source: Environment Canada. 2011.

National Inventory Report

283

List of Figures

Figure1

. Total Greenhouse Gas Emissions in the Great Lakes Region’s Energy Sector, 1990-2009.

Source: Environment Canada. 2011.

National Inventory Report

, and United States Environmental Protection

Agency. 2011.

State CO2 Emissions from Fossil Fuel Combustion 1990-2009.

Figure 2

. Short-term Trend: Total Greenhouse Gas Emissions in the Great Lakes Region’s Energy Sector, 2005-

2009.

Source: Environment Canada. 2011.

National Inventory Report

, and United States Environmental Protection

Agency. 2011.

State CO2 Emissions from Fossil Fuel Combustion 1990-2009.

Figure 3

. Comparison of Greenhouse Gas Emissions in the Energy Sector in the Great Lakes States and Ontario,

1990-2009.

Source: Environment Canada. 2011.

National Inventory Report

, and United States Environmental Protection

Agency. 2011.

State CO2 Emissions from Fossil Fuel Combustion 1990-2009.

Figure 4

.

Total Greenhouse Gas Emissions from 1990-2007 (Energy Sector in Ontario and 8 U.S. Great Lakes

States).

Source: Environment Canada. 2011.

National Inventory Report

, and United States Environmental Protection Agency

(EPA). 2011.

State CO2 Emissions from Fossil Fuel Combustion 1990-2009.

Last Updated

State of the Great Lakes 2011

Annual Greenhouse Gas Emissions

Year

1990

1991

1992

1993

1994

1995

1996

Ontario's Total

Emissions (MMTCO2)

125.2

123.8

127.2

119.9

120.2

123.4

130.3

U.S. Great Lakes States

Total Emissions

(MMTCO2)

1467.6

1450.1

1456.1

1485.8

1489.6

1516.4

1573.9

Entire Great Lakes

Region Total Emissions

(MMTCO2)

1592.8

1573.9

1583.2

1605.7

1609.8

1639.8

1997

1998

1999

2000

2001

2002

2003

2004

137.1

140.1

147.3

157.6

151.7

156.0

160.1

151.1

1588.7

1550.6

1577.9

1624.3

1563.9

1579.8

1604.8

1622.9

1704.3

1725.9

1690.8

1725.2

1781.8

1715.6

1735.8

1764.9

2005

2006

2007

153.6

144.9

152.0

1638.3

1574.8

1605.8

1774.0

1791.8

1719.6

1757.8

2008 142.2 1566.3 1708.4

2009 124.5 1441.7 1566.1

Table 1

. Annual Greenhouse Gas Emissions in the Great Lakes Region’s Energy Sector, 1990-2009

Source: Environment Canada. 2011.

National Inventory Report

, and United States Environmental Protection

Agency. 2011.

State CO2 Emissions from Fossil Fuel Combustion 1990-2009.

284

Ontario’s percent of National greenhouse gas emissions

State/Province Ontario’s

Greenhouse Gas

Emissions (MMTCO2)

Total Greenhouse Gas

Emissions in Canada

(MMTCO2)

Ontario (1990)

Ontario (2009)

125.2

124.5

412.5

490.1

Greenhouse Gas

Emissions in National

Context

30.3%

25.3%

Table 2

.

Ontario’s percent of National greenhouse gas emissions – 1990 and 2009

Source: Environment Canada. 2011.

National Inventory Report

Great Lakes States’ percent of National greenhouse gas emissions

State/Province Eight Great Lakes States

Greenhouse Gas

Emissions (MMTCO2)

Total Greenhouse Gas

Emissions in US

(MMTCO2)

5099.7 Eight Great Lakes

States (1990)

Eight Great Lakes

States (2009)

1467.6

1441.7 5505.2

Greenhouse Gas

Emissions in National

Context

28.8%

26.2%

Table 3

. Great Lakes States’ percent of National greenhouse gas emissions (energy sector) - 1990 and 2009

Source: United States Environmental Protection Agency. 2011.

State CO2 Emissions from Fossil Fuel Combustion

1990-2009.

1990 Per Capita Greenhouse Gas Emissions

State/Province Total Greenhouse Gas

Ontario

Emissions in the Great Lakes

Region (1990) – MMTCO2

125.2

Population within the Great Lakes

Region (1990)

10,085,000

Per Capita 1990

12.4

Illinois

Indiana

Michigan

Minnesota

New York

Ohio

Pennsylvania

194.9

205.3

180.4

79.6

208.8

246.8

265.5

11,430,602

5,544,159

9,295,297

4,357,099

17,990,455

10,847,115

11,881,643

17.1

37.0

19.4

18.3

11.6

22.8

22.4

Wisconsin

Total:

86.2

1592.8

4,891,769

86,323,139

17.6

18.5

Table 4

. 1990 Per Capita Greenhouse Gas Emissions (energy sector)

Source: Environment Canada. 2011.

National Inventory Report

, and United States Environmental Protection

Agency. 2011.

State CO2 Emissions from Fossil Fuel Combustion 1990-2009.

Environment Canada and United

States Environmental Protection Agency,

State of the Great Lakes 2011, Human Population

285

2009 Per Capita Greenhouse Gas Emissions

State/Province Total Greenhouse Gas

Emissions in the Great Lakes

Region (2009) MMTCO

Ontario

Illinois

124.5

226.4

Indiana

205.5

Michigan

164.2

Minnesota

92.2

New York

176.9

Ohio

236.8

Pennsylvania

243.4

Wisconsin

Total:

96.3

1566.1

Population within the Great Lakes

(2009)

13,064,900

12,910,409

6,423,113

9,969,727

5,266,214

19,541,453

11,542,645

12,604,767

5,654,774

96,978,002

Per Capita 2009

9.5

17.5

32.0

16.5

17.5

9.1

20.5

19.3

17.0

16.2

Table 5

. 2009 Per Capita Greenhouse Gas Emissions (energy sector)

Source: Environment Canada. 2011.

National Inventory Report

, and United States Environmental Protection

Agency. 2011.

State CO2 Emissions from Fossil Fuel Combustion 1990-2009,

and Environment Canada and United

States Environmental Protection Agency,

State of the Great Lakes 2011, Human Population

.

Ontario’s CO2 emissions compared to GHG

Year CO2 Emissions in

Ontario (MMTCO2)

1997

1998

1999

2000

2001

2002

2003

2004

1990

1991

1992

1993

1994

1995

1996

2005

2006

2007

2008

2009

137.1

140.1

147.3

157.6

151.7

156.0

160.1

151.1

125.2

123.8

127.2

119.9

120.2

123.4

130.3

153.6

144.9

152.0

142.2

124.5

Official GHG Emissions in Ontario (MMTCO2eq)

190.3

189.6

194.4

204.2

196.7

202.9

206.8

200.8

176.5

176.2

180.1

170.7

172.6

177.3

184.7

202.1

193.7

199.6

189.6

165.1

Table 6

. Ontario’s CO2 emissions compared to GHG emissions from 1990 to 2009

Source: Environment Canada. 2011.

National Inventory Report

286

Figure1

. Total Greenhouse Gas Emissions in the Great Lakes Region’s Energy Sector, 1990-2009.

Source: Environment Canada. 2011.

National Inventory Report

, and United States Environmental Protection

Agency. 2011.

State CO2 Emissions from Fossil Fuel Combustion 1990-2009.

Figure 2

. Short-term Trend: Total Greenhouse Gas Emissions in the Great Lakes Region’s Energy Sector, 2005-

2009.

Source: Environment Canada. 2011.

National Inventory Report

, and United States Environmental Protection

Agency. 2011.

State CO2 Emissions from Fossil Fuel Combustion 1990-2009.

Figure 3

. Comparison of Greenhouse Gas Emissions in the Energy Sector in the Great Lakes States and Ontario in

1990 and 2009.

Source: Environment Canada. 2011.

National Inventory Report

, and United States Environmental Protection

Agency. 2011.

State CO2 Emissions from Fossil Fuel Combustion 1990-2009.

287

Figure 4

.

Total Greenhouse Gas Emissions from 1990-2009 (Energy Sector in Ontario and 8 U.S. Great Lakes

States).

Source: Environment Canada. 2011.

National Inventory Report

, and United States Environmental Protection Agency

(EPA). 2011.

State CO2 Emissions from Fossil Fuel Combustion 1990-2009.

288

Hardened Shorelines

Overall Assessment

Status:

Trend:

Undetermined

Undetermined

Rationale: An overall assessment is not possible as information allowing a direct comparison to previous hardened shoreline indicator status is only available for the Lake Ontario shoreline.

Lake-by-Lake Assessment

Lake Superior

Status: Undetermined

Trend: Undetermined

Rationale: Available information does not allow a direct comparison to previous hardened shoreline indicator status.

Lake Michigan

Status: Undetermined

Trend: Undetermined

Rationale: Available information does not allow a direct comparison to previous hardened shoreline indicator status.

Lake Huron

Status: Undetermined

Trend: Undetermined

Rationale: Available information does not allow a direct comparison to previous hardened shoreline indicator status.

Lake Erie

Status: Undetermined

Trend: Undetermined

Rationale: Available information does not allow a direct comparison to previous hardened shoreline indicator status.

Lake Ontario

Status: Poor

Trend: Deteriorating

Rationale: Updated (2001-2002) shoreline classification datasets for Lake Ontario indicate that approximately 63.0% of the shoreline has less than 40% hardening which is below the poor threshold of 70%. While the percent of shoreline in the “no protection” category was comparable to the previous SOLEC update (NOAA, 1997), reductions in the “minor protection” category were offset by increases in the “moderate protection” and “major protection” categories suggesting a potential trend towards increased overall shoreline hardening in some areas. There is uncertainty in the trend analysis due to variations in input datasets as discussed further below

.

Purpose

To assess the amount of shoreline altered by the construction of shore protections, such as sheet piling, rip

• rap and other erosion control shore protection structures.

To infer the potential harm to aquatic-dependent life, water quality and natural processes from conditions created by shore protections.

289

The Hardened Shoreline indicator is used in the Great Lakes indicator suite as a Pressure indicator in the

Resource Use and Physical Stressors top level reporting category.

Ecosystem Objective

Impacts from hardened shorelines should not impair the physical, biological or chemical integrity of the Great Lakes as reflected in Annex 2 of the Great Lakes Water Quality Agreement – restoration and protection of beneficial uses.

Ecological Condition

Measure

The amount (kilometres/miles) of shoreline that has been hardened through construction of sheet piling, rip rap and other erosion control shore protection structures. Shoreline reaches are categorized using descriptions from the baseline shoreline classification dataset and include highly protected (70-100%), moderately protected (40-70%), minor protection (15-40%), no protection (< 15%), non-structural protection, and unclassified.

Note: measure does not include artificial coastal structures that are extend out into the waters, such as jetties, groynes, breakwalls, piers, etc.

Endpoint

The reference values for basinwide and lakewide scales are as follows.

Good = >80% of the shoreline has minor to no protection (i.e. 0-40% hardened shoreline measure categories).

Fair = 70-80% of the shoreline has minor to no protection (i.e. 0-40% hardened shoreline measure categories).

Poor = < 70% of the shoreline has minor to no protection (i.e. 0-40% hardened shoreline measure categories).

Trend determination will be based on no net increase in the percent of shoreline in the highly protected and moderately protected categories. The defined endpoint is intended to support an assessment of relative change over time and represents an initial suggestion for establishing preferred conditions. However, further discussion and refinement of the endpoint categories is required to reflect improved understanding of shoreline hardening and ecosystem impacts. The Status Justification section below outlines some of the challenges with attempting to define reference conditions for hardened shorelines.

Status Justification

There is limited documentation on specific shoreline hardening objectives, particularly at the basinwide and lakewide scales. The proposed end-point values for a hardened shoreline status assessment provide a descriptive point of reference using the baseline SOLEC estimates of the extent and intensity of shoreline hardening. Various environmental services can be impacted by shoreline hardening including changes or reductions in aquatic habitat, alterations in sediment transport, and changes in nearshore groundwater-lake interactions (see Province of Ontario,

2001). There are a variety of challenges in defining appropriate end-point values regarding shoreline hardening. In particular, a refined end-point assessment should reflect the differing quality and quantity of environmental services being provided (or not provided) by differing shoreline locations (e.g. pollution filtration, fish habitat, etc.) and weight the necessity and amount of the shoreline services required to achieve established ecosystem goals relative to the extent and impact of various shoreline hardening activities. However, the ecological services provided by natural shorelines and the impacts of hardened shorelines are difficult to measure as they often relate to many complex, long-term, and interdependent ecological processes (such as pollution filtration and sediment transport), in addition to more immediate and observable effects such as habitat and habitat loss. There are also variations in the extent to which certain types of shoreline hardening activities actually impact various ecological services based on the age, quality, and design characteristics of the shoreline structures. The current end-point categories only provide a general estimate of the extent and intensity of shoreline hardening and do not reflect an assessment of the relative sensitivity to shoreline hardening on each lake. The selected endpoints account for the fact that some shoreline

290

hardening already exists on the Great Lakes and is likely to be maintained into the future. The trend assessment captures the relative change in the percent of shoreline with >40% hardening.

For the purpose of this report, an overall undetermined reference value has been selected for the basinwide assessment due to the lack of a standardized dataset on many of the lakes that can be directly compared to the baseline conditions established for the Great Lakes/SOLEC hardened shoreline indicator. Where updated datasets do exist, they tend to be limited in geographic scope (i.e. they do not cover a full lake basin) or there are issues in matching the existing hardened shoreline indicator categories. The baseline conditions, as represented in the 2009

Great Lakes/SOLEC hardened shoreline indicator report, are provided in Table 1 for reference.

Lake Ontario does have a full dataset that can be compared with the baseline conditions indentified in previous

SOLEC reporting based on NOAA 1997 data. The updated dataset was developed in 2001 and 2002 to support the

International Joint Commission’s (IJC’s) International Lake Ontario – St. Lawrence River Regulation Study. A similar methodology was utilized to classify the full U.S. and Canadian Lake Ontario shoreline based on the type and extent of shoreline hardening (see Stewart, 2002) with the results summarized in the Flood and Erosion

Prediction System (FEPS) database (see Baird, 2005). The dataset was used to model water level impacts on shoreline structure lifespan and as a result, there are small gaps where direct comparisons to the baseline data set are difficult. In particular, there were some instances where the percent of very low quality shoreline structures was not identified as they were not included in the water level impact modeling. In the case of the SOLEC comparison, these areas were identified within the unclassified category, even though there was likely some shoreline hardening occurring. It should also be noted that the updated Lake Ontario classification dataset utilized a higher resolution shoreline delineation than was used in the baseline conditions unidentified in previous Great Lakes/SOLEC reporting. As a result, the classified shoreline extent is greater for the updated dataset. Finally, the updated dataset estimates the percent hardened shoreline using standard 1 km reaches along the full shoreline whereas the baseline dataset categorized reaches of variable (and generally greater) length.

Table 2 provides the length of shoreline in the baseline and updated (2001-2002) datasets along with the percent of shoreline within the various percent hardening categories for Lake Ontario. The percent of shoreline within the moderately (40 to 70% hardened) and major (>70% hardened) categories increased by 9.8 and 1.7 %, respectively while the percent of the shoreline within the minor (15 to 40% hardened) and no protection categories (<15% hardened) was reduced by 12.8%. The extent of shoreline in the minor and low protection categories is below the poor threshold established in the endpoint discussion and resulted in the poor status classification. The results suggest that there has been an increase in the amount of shoreline hardening since the baseline dataset was established in the late 1980s and a deteriorating trend was identified. However, since the overall length of categorized shoreline increased due to the refined shoreline delineation, there is uncertainty as to whether the identified change represents a true increase or a difference in dataset methodologies. Figure 1 provides maps of both the baseline Lake Ontario shoreline hardening categorization and the updated Lake Ontario data.

Linkages

Hardening shorelines can result in the loss of habitat, further erosion of unprotected properties adjacent to the structure, water quality degradation and the interruption of natural shoreline processes including reduced downdrift sediment transport.

Management Challenges/Opportunities

Shoreline hardening is generally implemented to stabilize shorelines and/or protect existing or planned infrastructure from erosion and flooding. Past high water conditions resulted in increased demand for shoreline hardening activities, although projects were often undertaken on a case-by-case basis without considering potential ecological consequences or impacts to adjacent property owners. The ecological impacts are not only difficult to quantify as a monetary equivalent, but difficult to perceive without an understanding of sediment transport along the lakeshores.

291

The importance of the ecological process of sediment transport needs to be better understood as an incentive to reduce new shoreline hardening. An educated public is critical to ensuring wise decisions about the stewardship of the Great Lakes basin ecosystem, and better platforms for getting understandable information to the public are needed.

Opportunities exist to identify particular shoreline functions that need to be maintained and where shoreline hardening is deemed necessary, to implement structures that are compatible with the ongoing ecosystem and sediment transport functions. There are also opportunities to modify existing shoreline hardening features to enhance identified ecosystem functions or even to remove certain shoreline hardening features altogether where other methods exist to reduce vulnerabilities (e.g. moving vulnerable infrastructure away from eroding shorelines).

Comments from the author(s)

There is uncertainty in undertaking direct comparison between the original hardened shorelines dataset previously reported and the more recent Lake Ontario dataset. In particular, the categorization is based on shoreline reaches which are defined differently in both datasets. The original dataset uses shoreline reaches of variable length whereas the more recent Lake Ontario data uses fixed 1 km shoreline reaches. It is possible that the large increase in highly hardened shorelines between the two datasets reflects a general reduction in reach length and not an overall increase in shoreline hardening. In addition, the overall shoreline lengths vary between the two datasets due to the base shoreline mapping used in the classifications. The recent Lake Ontario dataset uses a higher resolution shoreline delineation and includes certain features such as embayments that may not have been included in the original medium resolution shoreline delineation from the baseline hardened shoreline dataset. Since the indicator is based on a relative difference in the percent of shoreline within various categories, it is still possible to make some comparisons. However, it should be recognized that direct comparisons between data sets will be highly uncertain without using a common baseline shoreline delineation and comparable reach lengths. Finally, the baseline dataset is not clear on the transition between percent protected categories. For example, a shoreline reach that is 70% hardened could fall within either the 40% to 70% category or the 70% to 100% category. More explicit transitions were used for the categorization of the updated dataset.

There are opportunities for future updates to the hardened shorelines SOLEC indicator. Updated high resolution aerial imagery exists for much of the Great Lakes shoreline and oblique imagery has been recently collected or is planned to be collected for much of the U.S shoreline of the Great Lakes. With the information, it will be possible to use existing reach delineations and update the percent of shoreline hardening. Any efforts to update existing datasets should ensure that classification methodologies are similar to past efforts (e.g. as used for the updated Lake Ontario shoreline classification) and standardized reach delineations are utilized .

Assessing Data Quality

Data Characteristics

1. Data are documented, validated, or quality-assured by a recognized agency or organization

2. Data are traceable to original sources

3. The source of the data is a known, reliable and respected generator of data

4. Geographic coverage and scale of data are appropriate to the Great Lakes basin

5. Data obtained from sources within the U.S. are comparable to those from

Canada

Strongly

Agree

Agree

X

X

X

X

Neutral or

Unknown

X

Disagree

Strongly

Disagree

Not

Applicable

292

Data Characteristics

Strongly

Agree

Agree

Neutral or

Unknown

Disagree

Strongly

Disagree

Not

Applicable

6. Uncertainty and variability in the data are documented and within acceptable limits for this indicator report

Clarifying Notes:

1.

X

There is documentation prepared as part of the IJCs International Lake Ontario – St. Lawrence River Study (see

Stewart, 2002). The classification itself was undertaken by private contractors with considerable experience in shoreline classification procedures. However, there is no formal validation methodology for undertaking this type of shoreline classification

2.

3.

The data can be traced to original sources

The classification itself was undertaken by private contractors with considerable experience in shoreline classification procedures

4.

5.

6.

The geographic scale for the updated information only covers Lake Ontario and cannot be used for Great Lakes Basin wide assessments

The procedure for identifying hardened shorelines was applied consistently on both the Canadian and U.S. shorelines of

Lake Ontario. However, the identification and interpretation of hardened shorelines was influenced by the imagery and input datasets which varied around the shoreline in terms of age and resolution (see Stewart, 2002). The specific age and quality of input imagery used for individual shoreline reaches are not identified.

The identification and interpretation of hardened shorelines was influenced by the imagery and input datasets which varied around the shoreline in terms of age and resolution. As mentioned previously, the variation in reach length and detail of shoreline delineation between the baseline dataset and the updated Lake Ontario data result in uncertainty in the overall status and trends analysis regarding hardened shorelines

Acknowledgments

Authors:

Mike Shantz, Environment Canada, Burlington, ON. (2011)

Information Sources

Baird. 2005.

Final Flood and Erosion Prediction System Database (MS Access Database)

. Prepared for the Coastal

Zone Technical Working Group of the International Joint Commissions International Lake Ontario – St.

Lawrence River Study.

National Oceanic and Atmospheric Administration (NOAA). 1997.

Great Lakes and St. Lawrence River Medium

Resolution Vector Shoreline Data

. (GIS dataset)

Province of Ontario. 2001.

Understanding Natural Hazards.

Ministry of Natural Resources. Queen's Printer for

Ontario.

Stewart, C.J. 2002.

Task Summary Report: A Revised Geomorphic, Shore Protection, and Nearshore Classification of the Canadian and United States Shoreline of Lake Ontario and the St. Lawrence River

. Prepared for the

Coastal Zone Technical Working Group of the International Joint Commissions International Lake Ontario – St.

Lawrence River Study.

List of Tables

Table 1

. Baseline SOLEC hardened shoreline classification used for 2012 assessment based on information provided in 2009 Great Lakes/SOLEC indicator report

Source: National Oceanic and Atmospheric Administration (1997)

Table 2

. Comparison of baseline SOLEC hardened shoreline classification and updated (2001-2002) hardened shoreline classification for Lake Ontario

Source: Baseline SOLEC data from National Oceanic and Atmospheric Administration (1997) and updated Lake

Ontario data from Stewart (2002) and Baird (2005)

293

List of Figures

Figure 1

. Maps of baseline SOLEC hardened shoreline classification and updated (2001-2002) hardened shoreline classification for Lake Ontario

Source: Baseline SOLEC data from National Oceanic and Atmospheric Administration (1997) and updated Lake

Ontario data from Stewart (2002) and Baird (2005)

Last Updated

State of the Great Lakes 2011

Baseline Great Lakes/SOLEC hardened shoreline classification

Lake/

Connecting

Channel

Heavily

Protected

(%) (>70% protected)

Moderately

Protected (%)

(40-70% protected)

Minor

Protection (%)

(15-40% protected)

No

Protection

(%) (<15% protected)

Lake Superior

St. Marys River

Lake Michigan

Lake Huron

St. Clair River

Lake St. Clair

Detroit River

Lake Erie

Niagara River

Lake Ontario

St. Lawrence

River

3.1

2.9

8.6

1.5

69.3

11.3

47.2

20.4

44.3

10.2

12.6

1.1

1.6

2.9

1.0

24.9

25.8

22.6

11.3

8.8

6.3

9.3

3

7.5

30.3

4.5

2.1

11.8

8.0

16.9

16.7

18.6

17.2

89.4

81.3

57.5

91.6

3.6

50.7

22.2

49.1

29.3

57.2

54.7

Nonstructural

Protection

(%)

0.03

1.6

0.1

1.1

0.0

0.2

0.0

1.9

0.0

0.0

0.0

Unclassified

(%)

3.4

5.1

0.5

0.3

0.0

0.1

0.0

0.4

0.9

6.2

6.2

Total

Shoreline

(km)

Table 1

. Baseline Great Lakes/SOLEC hardened shoreline classification used for 2011 assessment based on

2571

5080

707

2713

6366

100

629

244

1608

184

1772 information provided in 2009 SOLEC indicator report

Source: National Oceanic and Atmospheric Administration (1997)

Comparison of baseline Great Lakes/SOLEC hardened shoreline classification and updated classification

Baseline SOLEC

Classification

Updated Lake Ontario

Classification

Length of Shoreline Categorized (km)

1. Heavily Protected (%)(>70% protected)

2. Moderately Protected (%)(40-70% protected)

3. Minor Protection (%) (15-40% protected

4. No Protection (%) (<15% protected)

5. Non-structural Protection (%)

6. Unclassified (%)

1772.0

10.2

6.3

18.6

57.2

0.0

6.2

2444.3

20.0

8.0

5.7

57.3

0.1

8.8

Table 2

. Comparison of baseline Great Lakes/SOLEC hardened shoreline classification and updated (2001-2002) hardened shoreline classification for Lake Ontario

Source: Baseline SOLEC data from National Oceanic and Atmospheric Administration (1997) and updated Lake

Ontario data from Stewart (2002) and Baird (2005)

294

Figure 1

. Maps of baseline Great Lakes/SOLEC hardened shoreline classification and updated (2001-2002) hardened shoreline classification for Lake Ontario

Source: Baseline Great Lakes/SOLEC data from National Oceanic and Atmospheric Administration (1997) and updated Lake Ontario data from Stewart (2002) and Baird (2005)

295

Harmful Algal Blooms (HABs)

Overall Assessment

Status: Fair to Poor

Trend: Unchanging or Deteriorating

Rationale: Overall, there are too few data and no systematic monitoring programs to enable a rigorous quantitative evaluation of the conditions and trends for HABs in the Great Lakes. However, the existing data and anecdotal evidence suggest that nearshore and offshore zones are disparate, and should be assessed separately. The status of the Upper Great Lakes is generally good in the deeper offshore waters. The status is either unchanged or deteriorating in the shallower basins and/or nearshore areas, particularly in the lower lakes (Erie, Ontario) which are experiencing frequent outbreaks of HABs and nuisance algal blooms (NABs) as both planktonic and attached algae.

Lake-by-Lake Assessment

Lake Superior

Status: Good

Trend: Unchanging or Undetermined

Rationale: There is very little quantitative current information on HABs in Lake Superior. Severe HABs outbreaks have not been documented recently in this lake and cyanobacterial biomass remains mostly at low levels in those cases where it has been evaluated. An occasional local impairment may occur near shoreline development.

Lake Michigan

Status: Fair

Trend: Unchanging/Deteriorating

Rationale: Offshore waters are generally good but cyanobacteria blooms are reported in some coastal regions in eutrophic embayments such as Green Bay, Muskegon Bay and in many of the river mouths along the eastern shore. Shoreline and beach fouling by

Cladophora

represent a source of bacteria for beaches and groundwater. Trapped bacterial flora during their growth provides substrate for further bacterial activity during decay.

Lake Huron

Status: Fair

Trend: Unchanging (offshore), Deteriorating (some nearshore regions)

Rationale: Lake Huron is generally oligotrophic in most areas, but experiences potentially toxic HABs occur in some nearshore areas, notably Saginaw and Sturgeon Bay which develop toxic summer outbreaks of planktonic

Anabaena

and

Microcystis aeruginosa

.

Lake Erie

Status: Fair to Poor

Trend: Deteriorating

Rationale: Lake Erie is the most heavily impaired by planktonic HABs, particularly in the last two years where satellite images of extensive surface blooms of

Microcystis

and other HABs have been posted on many websites (e.g. NOAA). Toxic and nuisance planktonic (

Microcystis; also Anabaena, Planktothrix and

Aphanizomenon

) HABs are a particular concern in the western basin, often originating in the southwest

(Maumee Bay and Sandusky Bay) and it is argued that October 2011 saw one of most severe planktonic HABs on record in the Great Lakes, covering most of west and central basins. Areas of the west basin also experience significant benthic NABs of the cyanobacteria

Lyngbya wollei

. The Central

296

basin of Lake Erie has large outbreaks of planktonic HABs; notably near Cleveland, where they may extend significant distances alongshore or in a northern direction into the offshore waters, and recently reported during the past few years along the northern shoreline between Point Pelee and Port Stanley or further eastward. Offshore water in the Eastern basin is high in quality and experiences very few planktonic blooms, but erratic but significant planktonic outbreaks have been reported in nearshore areas of this basin, notably near Erie and Long Point. However, many nearshore areas of the East Basin have significant impairment from attached

Cladophora

beds, despite low ambient nutrient levels

Lake Ontario

Status: Fair

Trend: Deteriorating (some nearshore areas); improving/unchanging (offshore areas)

Rationale: Offshore waters are generally good however blooms of cyanobacteria and related impairments (toxins, taste-odour compounds) occur on an annual basis in some nearshore areas, notably the Bay of Quinte,

Sodus Bay, Rochester embayment, Hamilton Harbour and the Greater Toronto region, causing advisories and beach closures in some of these areas. In many nearshore areas, dense beds of attached

Cladophora

have led to extensive beach closures, fouling and other issues

Purpose

To assess the potential harm to human, other organisms or ecosystems from planktonic or benthic/attached algal blooms.

Ecosystem Objective

Waters should be safe for drinking (>25 million people rely on the Great Lakes for drinking water), and for recreational use, and substantially free from toxic and/or high abundances of noxious cyanobacteria or algae that may harm human, animals or ecosystem health or have other harmful effects. While cyanobacteria produce a wide variety of toxins, hepatotoxic microcystins (MCs) are the most persistent and common cyanotoxins currently reported across the Great Lakes, and are generally produced by one of several species of

Microcystis, Anabaena

or

Planktothrix

. Other cyanobacterial toxins such as anatoxin-a have been found in embayments but are rare in occurrence thus this indicator focuses on a single class of MC toxins. Nontoxic bloom events are also of concern, however. Recently, winter blooms of the diatom

Aulacoseira

have been reported, which may contribute to the severity of the summer anoxia in the central basin. Benthic/littoral cyanobacteria such as

Lyngbya

or eukaryotic algae - particularly

Cladophora

and

Spirogyra

- show widespread occurrence in the nearshore zone and represent a different type of threat to the ecosystem. However some of the root causes of benthic HABs (elevated nutrients) are similar to the root cause of pelagic HABs. A combined metric enables monitoring for changes in both general types of blooms.

Ecological Condition

Background

Harmful cyanobacterial and/or algal* blooms (HABs) are a global issue in eutrophic waters with high anthropogenic

(and/or natural) nutrient loading (e.g. Hallegraeff 1993). HABs are differentiated from ‘non-harmful’ blooms by their qualitative impacts on, or threats to: i) water quality, biota or physico-chemical characteristics; ii) health risks from toxins or heightened microbial activity; iii) aesthetics or recreation (Pearl 1988). Prior to remediation in the late 1970s, HABs were a major problem in many offshore and nearshore areas in the Great Lakes (e.g. Watson and

Boyer 2008) where concerns focused on reduced aesthetics, taste-odour (T&O), foodweb structure, beach/intake/net fouling and economic impacts. Lake-wide remediation efforts initiated in the 1980s were mainly directed towards the reduction of point-source nutrient loading, and successfully mitigated many HAB impairments with progress largely gauged against the management reduction targets for Total Phosphorus (TP) and chlorophyll a (chl-a).

Recently there has been a resurgence in algal blooms in the Lakes, with an additional new concern being their

297

potential for the production of toxins*. Current management continues to target planktonic (subsurface) chl-a as a measure of total algal biomass and productivity, which is often a poor metric for these events.

(Notes - * algae here can be used to denote both eukaryotic algal taxa and cyanobacteria; ** Toxins were not recognized as a threat to the Great Lakes in the 1970s, but there is little historical data on their occurrence prior to their report in Lake Erie in the mid 1990s (Brittain et al., 2000). This perception of increased toxicity is based more on anecdotal evidence and reports may be biased by increasing public awareness, advances in analytical techniques, and increased monitoring.)

Most efforts are focused on visible HABs caused by planktonic toxic cyanobacteria, but HABs also can be caused by blooms of

Cladophora

and other benthic/littoral macroalgal proliferation. These benthic mats, along with planktonic outbreaks, have shown an apparent resurgence particularly in the lower Great Lakes. Because these events are often episodic, and vary seasonally and interannually in severity and spatial coverage, it is difficult to implement appropriate research, monitoring and management programs, particularly in large and complex waterbodies such as the Great Lakes where sampling is often subject to weather and vessel access. Blooms may not be restricted to the lakes themselves and have been reported in major embayments, tributaries and connecting channels.

Most algal blooms in the Great Lakes are reported in the nearshore areas, which are most prone to shoreline development issues, greater influx of nutrients and to some extent, increased public vigilance. The size of nearshore zones varies from ~1-10% in Superior to 60-90% in Erie, as does the influence of physical and climatic factors

(runoff, erosion, thermal bar formation, upwelling/downwelling, alongshore/nearshore/offshore currents, circulation patterns, surface/ground water inputs, lake level regulation, ice formation, etc.). As a result, the nearshore zones are highly dynamic, and there is significant spatial-temporal variance in the areas supporting littoral and planktonic communities and offshore-nearshore material exchange.

HABs in the Great Lakes are caused by a variety of species. Major impairments to ecosystem services include: i) noxious/toxic metabolites (odour, toxins); ii) fouling (beaches, nets, intakes); iii) aesthetics and economic impacts including beach closures; vi) modified nutrient turnover and sequestration or translocation (via cell bound fractions) of nutrients; vii) increased bacterial activity; viii) adverse effects on food web integrity. Importantly their appearance is often associated with nearshore regions and this is poorly captured by the current LaMP targets – i.e. offshore nutrient and chl-a levels.

Key aspects of HABs

These are summarized in detail in Watson and Boyer 2008, but some key points are summarized below:

HABs cause significant economic harm. Annual estimates vary, but range up to annual costs of $4.6 billion/yr

(USA) in response monitoring, fisheries, tourism, public health & advisory, lost revenue & property value.

Not all HABs are caused by cyanobacteria or resemble green paint or pea soup. They are caused by many species and vary in colour from green to red and brown.

Algal blooms do not always show up as surface scums and can be hard to identify or anticipate. Some blooms are mixed through the water column, grow in deep water layers, under ice or as benthic/attached mats.

Cyanobacteria produce many toxins which fall into three major categories, based on their activity: liver toxins

(hepatotoxins), neurotoxins & dermal irritants. These toxins vary greatly in their chemical properties, stability and toxicity. Microcystins (hepatoxins; also carcinogens) are the most stable and prevalent across the Great

Lakes. These toxins can persist in the water column after a bloom has died and disappeared.

Toxins, taste and odour issues, visible blooms, cyanobacteria and algal biomass, and the abundance of chl-a may or may not be related. Toxins are odourless & colourless and there is often a very poor relationship between occurrence of toxins and T&O compounds. The two classes of compounds are derived from separate biochemical pathways. These compounds are produced by a number of different genera and cell and species-

298

• specific variation in their production is common.

Blooms are difficult to define, measure and predict.

Blooms can show rapid changes in their spatial location and abundance.

With calm conditions (or overnight), buoyancy-regulating cyanobacteria can float to the surface and be carried large distances by wind/waves. These may wash onshore, creating patches of very high toxin levels along beaches.

Variations in analytical and sampling methods can lead to inconsistencies in the reported levels of these compounds.

Fluorescence-based, cell counts and other abundance measures (e.g. molecular, biochemical) are often poorly correlated with each other and actual cell biomass due to wide variance in pigment content, photo-acclimation and cell composition. Taxonomic identification of many of the responsible species may be complex, leading to differences between analysts.

Additional Information

The term ‘algal bloom’ is a non quantitative descriptor for visible increases in free-floating or attached algal/cyanobacterial density, often manifested as scums, mats or water colour. Harmful algal blooms are differentiated as having harmful socioeconomic or ecological effects and may be caused by algal/cyanobacteria species belonging to many major taxonomic groups. The most concern is with HABs caused by cyanobacteria

(CHABs), which include toxic blooms, caused by a subset of cyanobacterial species with the capacity to produce one or more toxins (neurotoxins, hepatotoxins or dermatotoxins) and currently are the only known sources of algal toxins in inland waters that directly affect humans. Detrimental health effects from benthic algal accumulations on the shore are more difficult to quantify but may result in socioeconomic and ecological damage (Table 1).

Great Lakes: current status of HABS

Toxins: The most commonly reported toxins in the Great Lakes and other waters are microcystins (MCs) produced by numerous cyanobacteria species; some of which (e.g.

Microcystis Anabaena

and

Planktothrix

spp.) bloom in the

Lakes (e.g. Boyer 2007). In lakes Ontario and Erie, anatoxin-a and saxitoxins have been detected at high and low levels, respectively (Boyer 2007). While

Cylindrospermopsis

is present in Great Lakes and its surrounding watersheds, the toxin cylindrospermopsin previously associated with this genus has not been confirmed for these waterbodies. Analysis of numerous samples acros s the Great Lakes has shown no detectable levels of βmethylamino-l-alanine (BMAA), a toxin of emerging concern in some areas. The question of BMAAs and the link to Alzheimer’s continues to be debated. There are no data on the occurrence of lipopolysaccharides (LPS), produced by all cyanobacteria and widely believed to cause gastroenteritis, skin/eye irritations, hay fever, asthma and blistering (although this is debated; e.g. Stewart

et al

. 2006).

Taste and odour (T&O) impairment is widespread in the Great Lakes. T&O is most commonly caused by volatile organic compounds (geosmin, 2-methyisoborneol,

β

-cyclocitral and biogenic sulphides) released during the growth and decay of planktonic and benthic cyanobacteria, bacteria and algae. These compounds have no known human health effects, but can impart significant consumer alarm and treatment/economic costs and function in foodwebs as powerful chemical signals (e.g. Watson et al 2008a; Watson 2003).

Other issues i.e. benthic HABs (

Cladophora

,

Lyngbya, Chara

). Despite a significant reduction in these impairments in the 1980s-90s, there has been a significant resurgence in this problem which is now widespread in the lower lakes, notably in areas affected by a combination of diffuse shoreline or tributary influx of nutrients and colonised by dressenid mussels. The link among these factors to growth and biomass is, however, obscured by the dynamic physical nature of the nearshore zone, sloughing off and difficulties with sampling.

299

Great Lakes: current status of HABS in individual lakes

As noted above, there are no long term data or rigorous monitoring programs in place across most of the lakes, and only a qualitative assessment of the current status in each lake can be made.

Lake Superior:

There is very little quantitative current information on HABs in Lake Superior. To our knowledge, severe HABs outbreaks have not been documented recently in this Lake. Algal biomass, especially for potentially toxic cyanobacterial species remains mostly at low levels, although there may be some local impairment near shoreline development. Localized, low toxicity blooms have been observed in the connecting channels across the

Keweenaw Peninsula.

Lake Michigan:

Cyanobacteria blooms are reported in some coastal regions in eutrophic embayments such as

Green Bay, Muskegon Bay and in many of the river mouths along the eastern shore of Lake Michigan. Shoreline and beach fouling by

Cladophora

represent a source of bacteria for beaches and groundwater, trapping bacterial flora during their growth and providing substrate for further bacterial activity during decay.

Lake Huron:

Lake Huron is generally oligotrophic in most areas, but experiences potentially toxic HABs occur in some nearshore areas, notably Saginaw Bay develops toxic summer outbreaks of

Microcystis aeruginosa

. These blooms appear to be genetically distinct with a greater MC production capacity than HABs populations of

M. aeruginosa

in western Lake Erie (Dyble

et al

2008). Highest toxin levels occur in shallow regions with high TP concentrations. Blooms have been reported from Sturgeon Bay in 2006-07, but no recent data is available (Diep

et al

. 2006). Recently, complaints of fish-net fouling by attached chlorophytes have increased (

Spirogyra cf circumlineata

,

Stigeoclonium

; Watson and Milne, unpublished). Rotting mats of beached green macroalgae are increasingly impacting aesthetics, recreation and tourism along some shorelines, notably Saginaw and more recently, the S.E., largely caused by

Cladophora

and

Chara

, respectively, with the detection of human fecal indicators (

E. coli

,

Enterococcus

) and evidence of differential survival in the beached mats and in situ beds of the macroalgae (Lake Huron Binational Partnership 2008-2010 Action Plan 2008).

Cladophora

is more clearly associated with suspected nutrient discharge while

Chara

is more widespread and not clearly linked to local inputs

(Howell

et al

. 2005).

Lake St Clair (LSC):

St. Clair River/Lake St. Clair/Detroit River’s status is Fair. Recent reports and surveys do not identify algal blooms as a problem across most of LSC, as also indicated by generally low chla levels (~3-5ug/L;

Lake St. Clair Canadian Watershed Technical Report; Watson unpublished). However, recent satellite images and anecdotal reports indicate blooms in the SE region of Lake St. Clair near the mouth of the Thames River.

Lyngbya

mats have also been found in the western shoreline areas associated with macrophyte stands; also in the Detroit

River (Trenton Channel) (Watson unpublished).

Lake Erie

: Lake Erie is the most heavily impaired by planktonic HABs, particularly in the last two years where satellite images of extensive surface blooms of

Microcystis

and other HABs have been posted on many websites

(e.g. NOAA). Toxic HABs and their causes are a particular concern and the focus of several recent studies (e.g.

MERHAB-LGL, Stumpf et al. 2012).

General trends: Overall, the data indicate an apparent deterioration, and shifts in external/internal physical/ chemical/ biological regimes - notably in the western basin of Lake Erie. These are not easily assessed using current monitoring methods and measures, particularly where basin-wide averages and/or surface (1m) chl-a are considered

(Ghadouani & Smith 2005). Studies suggest an increase in the severity of blooms in the western basin and some nearshore areas of the north shore (Point Pelee, Rondeau Bay, Long Point), and a decline in overall chl-a and total and/or eutrophic species biomass in the offshore regions of the central and eastern basins. Pre-remedial cyanobacteria populations were predominated by Nitrogen-fixers (

Aphanizomenon, Anabaena

), while many of the recent blooms have been dominated by non nitrogen-fixers, notably

Microcystis

and

Planktothrix

spp., suggesting

300

changes in nutrient supply or dreissenid activity. Nevertheless, significant blooms of nitrogen-fixing populations of

Anabaena

(cf

lemmermanni

) occur in both western and eastern basins (Watson, unpublished).

Immense surface blooms (>20 km

2

) have been recorded in the western basin of Lake Erie near the Maumee and

Sandusky Rivers (e.g. Rinto-Kanto

et al

. 2005; Stumpf et al 2012). Microcystins (MCs) are the most common cyanobacterial toxins measured in Lake Erie. Data from 2000–2004 measured a wide range in MC levels from detection limits (in 2002) to >20μg/L (in 2003). Toxicity is not restricted to the western basin: in 2003, highest MC concentrations were measured from Maumee, Long Point Bay and Sandusky Harbour. Neurotoxins (anatoxin–a, saxitoxin, neosaxitoxin) occurred at or near detection limits in the open lake waters. Samples collected across the lake between 2003 & 2008 showed the greatest proportion of samples (72-77%) with detectable MC levels from the western basin (Figure 1), although only ~5% had levels above 1µg/L.

Toxins are not always produced by the same species, by the dominant taxa, or on a consistent basis.

Microcystis

blooms from Maumee have shown 5-100% variance in genetic potential for MC production. Recent molecular work has shown that blooms upstream in the Maumee R. are not a source of toxic

Microcystis

spp. to western basin of

Lake Erie, but the two populations arise independently (Kutovaya

et al

2010). In fact

Planktothrix

can be the major source of MC toxins in Maumee Bay and Sandusky Harbor where cyanobacteria populations are dominated by nontoxin producers (e.g.

Aphanizomenon, Anabaena

; Rinto-Kanto

et al

. 2005; Boyer 2007). Most impairment occurs at shorelines and beaches and can be manifested as fish/bird kills. Lyngbyatoxins (inflammatory/vesicatory and tumour-promoting) were not detected in the mats of

Lyngbya wollei

proliferating in the Maumee and Detroit Rivers.

Cylindrospermopsis raciborskii

, first identified in Sandusky Bay 2005, may develop localized biomass but to date, cylindrospermopsin or deoxycylindrospermopsin has been detected in these areas. The highly variable morphology of this and other species may lead to misidentification as an

Aphanizomenon issatchenkoi

or

Rhaphidiopsis curvata

.

Geosmin and 2-methylisoborneol (MIB) are likely the cause of annual musty-muddy odour problems in drinking water in supplies in the western basin (e.g. Toledo). Significant odour is produced by extensive rotting mats of shoreline attached algae. The planktonic cyanobacterial taxa which are currently problematic in Lake Erie

(

Microcystis*

and the local strain of

Planktothrix

) do not produce these or other T&O compounds which commonly impair drinking water supplies. (*Note –

Microcystis

produces ß-cyclocitral; however, this is rapidly removed by most water treatment methods.)

Severe impairments by thick mats of the cyanobacterium

Lyngbya wollei

reported in the mouth of the Maumee

River (western basin) at sites with high ambient P in the overlying water between 2006-09 appear to have abated this past year (Watson

et al

. 2008b; Western Lake Erie Waterkeeper Association unpublished). Extensive mats of attached green algae, notably

Cladophora

are showing an increase in abundance along some northern shorelines, although there are no recent data (post 2008) available on distribution.

Lake Ontario:

Blooms of cyanobacteria and related impairments (toxins, taste-odour compounds) occur on an annual basis in some nearshore areas, notably Areas of Concerns (AOCs) of Lake Ontario. Sporadic outbreaks of high MC levels and cyanobacteria blooms have been recorded in Hamilton Harbour, Bay of Quinte, Oswego Harbor and most recently, Sodus Bay (Watson and Boyer 2008, Watson

et al

. 2010a,b; Boyer unpublished). Spatial and temporal levels of MCs in the Bay of Quinte, Hamilton Harbour, Oswego Harbor (now delisted) and the Rochester

Embayments indicate periods of severe impairment of nearshore sites by windblown accumulations of toxic material, where MC levels can reach levels in excess of 500 µg/L. Microcystins and toxigenic

Microcystis

are also commonly found in many of the nearshore regions and embayments that span the northern Coast of New York State

(Hotto

et al

, 2007). While microcystins are certainly the toxin of most concern in Lake Ontario, recent surveys indicate the widespread occurrence of low concentrations of anatoxin-a in nearshore embayments (Boyer 2007;

Yang 2007, Boyer unpublished). The organism responsible for anatoxin-a production is currently unidentified.

Other toxins (saxitoxins and cylindrospermopsin) are rare.

301

Studies have identified three T&O patterns over the past 5 years which are caused by geosmin and/or 2-MIB.

Recently, there have been no severe T&O impairments to drinking water in intakes from Lake Ontario, although there have been anecdotal reports of T&O from the St Lawrence River (J. Ridal, personal communication) . Benthic algal impairment continues to be major problem in many areas, with issues of plant intake and beach fouling

(Higgins

et al

. 2008). Severe impairment is also manifested by benthic mats of the cyanobacteria

Lyngbya

cf.

wollei

and epiphytic

Gloeotrichia

recently identified in the St. Lawrence River near the confluence of nutrient-rich tributaries (Vis

et al

. 2008). As with the Maumee populations, these mats of

Lyngbya

are non-toxic but show high geosmin production, likely the source of extensive drinking water T&O impairment in the Montreal area.

Linkages

Increasing nutrient inputs from diffuse and point sources, climate change (severe storm events, differences in insulation/harmful irradiation, ice-cover and mixing), and invasive species (e.g.

dreissenid mussels) in the Great

Lakes may lead to increased frequency, distribution and severity of both nearshore (attached/benthic) and offshore algal blooms and favour the predominance of cyanobacteria.

Management Challenges/Opportunities

There are a number of issues that relate to the effectiveness of monitoring and applying this indicator:

There is a critical need for a coordinated, interagency monitoring program, which employs standard methods; different sampling regimes and analytical protocols employed by individual studies affect data comparability and interpretation of long-term trends.

Basin-wide seasonal means, used widely to gauge trophic levels, do not resolve temporal/spatial differences in biomass and taxa, and thus cannot identify problem areas and/or potential drivers.

Littoral/benthic, epiphytic and meroplanktic algal populations are not addressed by most sampling programs, yet can account for a high proportion of algal productivity, or represent seed beds where surface blooms originate.

Alternative measures of algal abundance and productivity are often poorly correlated, as are measures of light regime. Chl-a continues to be a target measure for management, yet there are often poor correlations among chl-a, total algal biomass and levels of impairment. Secchi depth estimates visible light attenuation, which can differ significantly (seasonally and spatially) from PAR extinction.

Toxins should be systematically investigated, particularly in high risk source-waters, using regular monitoring at recreational areas and intake zones, mid-late summer spatial surveys during high risk periods and an alert level framework such as developed by the World Health Organization (Watzin

et al

. 2006). More effective criteria for

T&O would include regular measures of the most problematic compounds (e.g. geosmin, MIB) in source waters and municipal supplies, and comparison against their odour threshold levels.

Nutrient levels may, or may not predict toxin or odour outbreaks. Blooms are often local and inshore in origin and can spread over considerable areas as surface scum.

Incidental reports, media releases and websites may inflate or misrepresent these issues. Most attention is focused on surface scum, which inevitably bias samples and perceived severity.

Comments from the authors

There are few long term data collected on HABs and more specifically, toxins, in the Great Lakes, making trend analysis difficult. Differences in sampling regimes and analytical protocols (e.g. surface or integrated sampling; taxa enumeration; toxin analyses) utilized in past studies affects the ability to compare data and determine long term trends in toxins and bloom occurrences. Attention is most often focused on shoreline scums or algal material visible

302

at the surface, particularly for inland waters where many reported blooms are caused by attached macroalgae

(

Cladophora, Lyngbya

) or large, buoyancy-regulating cyanobacteria. These buoyancy-regulating taxa can produce rapid surface accumulations from populations through the mixed layer or deep living/benthic populations.

Concentrated surface scums appear, disappear and migrate rapidly with changes in vertical mixing, currents and wind activity. These can produce rapid changes in toxin levels along a waterfront or cover extensive areas in large lakes, and are difficult to sample, quantify or predict. Beach and shoreline sampling programs require multiple subsites to capture this envelope of spatial/temporal variance in risk and impairment, which are poorly represented by basin-wide seasonal means. Sampling regimes in the Great Lakes are often sparse (both temporally and spatially) and are likely to miss spatial and temporal peaks in cyanobacterial/algal abundance.

Assessing Data Quality

Data Characteristics

Strongly

Agree

Agree

Neutral or

Unknown

Disagree

Strongly

Disagree

Not

Applicable

1. Data are documented, validated, or qualityassured by a recognized agency or organization

2. Data are traceable to original sources

3. The source of the data is a known, reliable and respected generator of data

4. Geographic coverage and scale of data are appropriate to the Great Lakes basin x x x x

5. Data obtained from sources within the U.S. are comparable to those from Canada

6. Uncertainty and variability in the data are documented and within acceptable limits for x x this indicator report

Clarifying Notes: See notes under ‘

Management Challenges/Opportunities’ and ‘Comments from the authors’.

The sources of data are varied and in many cases, use different sampling and analytical methods. Monitoring in the lower lakes is generally good but monitoring in the upper lakes Michigan, Huron and Superior is sparse and largely reactive

Acknowledgments

Authors:

Susan Watson, Environment Canada, Burlington, ON ([email protected])

Greg Boyer, State University of New York ( [email protected]

)

Information Sources

Boyer, G. L. 2007. Cyanobacterial toxins in New York and the lower Great Lakes Ecosystems. Adv. Exp.Med. Biol.

619: 151-163

Brittain S. M., Wang, J., Babcock-Jackson, L., Carmichael, W. W., Rinehart, K. L., and Culver, D. A. 2000

Isolation and characterization of microcystins, cyclic heptapeptide hepatotoxins from a Lake Erie strain of

Microcystis aeruginosa.

J. Great Lakes Res. 26(3):241–249.

Diep, N., Benoit, N., Howell, T. & Boyd, D. 2006. Spatial and temporal variability in the trophic status of nearshore waters across a spectrum of environments along the Georgian Bay coastline. Presented at Second International

Symposium on the Lake Huron Ecosystem: The State of Lake Huron: Ecosystem Change, Habitat,

Contaminants, and Management, Honey Harbour, ON

Dyble J., Fahnenstiel G.L., Litaker R.W., Millie D.F., & Tester P. 2008. Microcystin concentrations and genetic diversity of

Microcystis

in the lower great lakes. Environ.l Toxicol.. 23:507-516

Fahnenstiel G.L., Millie D.F., Dyble J., Litaker R.W., Tester P.A., McCormick M.J., Rediske R., & Klarer D. 2008.

Microcystin concentrations and cell quotas in Saginaw Bay, Lake Huron. AEHM. 11:190-195.

Ghadouani A., & Smith R.E.H. 2005. Phytoplankton distribution in Lake Erie as assessed by a new in situ spectrofluorometric technique. J. Gt Lakes Res.

303

Higgins, S.N., Malkin, S.Y., Howell, E.T., Guildford, S.J., Campbell, L., Hiriart-Baer, V. & Hecky, R.E. 2008. An ecological review of

Cladophora glomerata

(Chlorophyta) in the Laurentian Great Lakes. In Press. J. Phycol.

Hotto, A.M., Satchwell, M.F., & Boyer, G.L. 2007. Molecular characterization of potential microcystin-producing cyanobacteria in Lake Ontario embayments and nearshore waters. Appl. Environ. Microbiol.73: 4570-4578.

Howell, T., S. Abernathy, A.S. Crowe, T. Edge, H. House, J. Milne, M. Charlton, P. Scharfe, S. Sweeny, S..B.

Watson, S. Weir, A.M. Weselan & M. Veliz. 2005. Sources and mechanisms of delivery of

E. coli

(bacteria) pollution to the Lake Huron shoreline of Huron County, Ontario. Interim Report: Science Committee to

Investigate sources of Bacterial Pollution of the Lake Huron Shoreline of Huron County

Lake Huron Binational Partnership 2008-2010 Action Plan 2008 http://www.epa.gov/greatlakes/lamp/lh_2008/lh_2008_7.pdf

Paerl, H. W. 1988. Nuisance phytoplankton blooms in coastal, estuarine and inland waters. Limnol. Oceanogr. 33:

823–847.

Rinta-Kanto J.M., & Wilhelm S.W. 2006. Diversity of microcystin-producing cyanobacteria in spatially isolated regions of Lake Erie. Appl. Environ. Microbiol.72:5083-5085.

Rinta-Kanto, J. M., Ouellette, A.J.A., Twiss, M.R., Boyer, G.L., T. Bridgeman, T. & Wilhelm, S.W. 2005.

Quantification of toxic

Microcystis

spp. during the 2003 and 2004 blooms in western Lake Erie using quantitative real-time PCR. Environ. Sci. Technol. 39: 4198-4205.

Stumpf RP, Wynne TT, Baker DB, Fahnenstiel GL (2012) Interannual Variability of Cyanobacterial Blooms in

Lake Erie. PLoS ONE 7(8): e42444.

Vis C., Cattaneo A., & Hudon C. 2008. Shift from chlorophytes to cyanobacteria in benthic macroalgae along a gradient of nitrate depletion. J. Phycol. 44:38-44

Watson, S.B. 2007. Cyanobacterial Blooms in Hamilton Harbour: Risk, Causes and Consequences. Hamilton

Harbour Watershed Monitoring and Research Report, 2006 season

Watson, S.B & Boyer, G.L. Harmful Algal Blooms (HABS) in the Great Lakes: current status and concerns. SOLEC

2008

Watson, S.B., Boyer, G.L & Ridal J. 2008a. Taste and odour and cyanobacterial toxins: impairment, prediction and management in the Great Lakes. Can. J. Fish. Aquat. Sci. 65(8): 1779-1796

Watson, S.B, Hudon, C. & Cattaneo, A. 2008b Cyanobacterial impairments in the Great Lakes-St. Lawrence River: benthic fingerprints of anthropogenic activity. 43rd CAWQ Symposium, Burlington ON

Watson, S.B. & T. Howell. 2007 Sturgeon Bay: Cyanobacteria Blooms in a Northeast Embayment of Lake

Huron/Georgian Bay. 30th Congress, International Association of Theoretical and Applied Limnology.

Montréal, Que

Watson SB, Yang, R, Newbold, B. 2011 Algal Bloom Response and risk management: on-site response tools.

NWRI internal report in press

Watzin, M.C., Brines Miller, E., Shambaugh, A.D., and Kreider, M.A. 2006. Application of the WHO alert level framework to cyanobacteria monitoring on Lake Champlain, Vermont. Environ. Toxicol. 21(3): 278-288

Wilhelm S.W.

et al

. 2003. Effect of phosphorus amendments on present day plankton communities in pelagic Lake

Erie. Aquatic Microb. Ecol. 32:275-285.

Yang, X. 2007. Occurrence of a cyanobacterial neurotoxin, anatoxin-a, in New York State waters. Ph.D. thesis,

State University of New York – ESF, Syracuse NY, 244p.

List of Tables

Table 1.

HABs Impairments - Socioeconomic and Ecological

List of Figures

Figure 1

. Lake Erie: percent of all samples collected between 2003-2009 with detectable levels of MC toxins.

Source: Greg Boyer, SUNY; unpublished

304

Last Updated

State of the Great Lakes 2011

report

HABs Impairments

Impairment

Drinking/recreational water integrity

Source water quality and function

Fouling

Mechanisms

Taste and odour, poor aesthetics

Anoxia from decaying material

Reduced water transparency etc.

Industrial intakes

Fish nets

Beaches/shorelines

Entrain/facilitate growth of pathogenic microbiota

Affected agents

Drinking/recreational water

Multiple ecosystem (fish and wildlife; internal nutrient loading etc); Tourism/ recreational; property value

Drinking/hydro/other industries; aquaculture/tourism/ recreational; waterfront and property value

Tourism/ recreational; property value

Elevated shoreline and beach bacterial/ pathogen levels

Biomagnification (toxins, taste)

Ecological

Tainted fish /shellfish State of the

Great Lakes 2011

report

sh/other

Multiple; include cell/tissue damage, growth inhibition, teratogenic, toxigenic (toxins, irritants, shading, allelopathic interactions, inadequate food quality, etc)

Recreational/food/aquaculture; ecological (foodweb transfer)

Multiple foodweb levels

Table 1

. HABs Impairments - Socioeconomic and Ecological

Qualitative assessment only at this point; could be developed into more quantitative measures.

Variation

 

by

 

Basin

 

of

 

samples

 

with

 

detectable

 

Microcystins

 

(2003

2008)

Distribution   by   Basin

25%   Central   basin

72% ‐ 77%  

Western  

Basin

Western;   n=234

Central;   n=218

Eastern;   n=83

Percentages   change   very   little   if   the   detection   limit   is   set   at   >0.1

  or   >   1.0

  ug/L.

Figure 1

.

Lake Erie: percent of all samples collected between 2003 & 2009 with detectable levels of MC toxins.

Source: Greg Boyer, SUNY; unpublished

305

Human Population

Overall Assessment

Trend

:

Increasing

Rationale: The long-term trend (1971 to 2006) of the total population in the Great Lakes region is increasing. Compared to 1971, the population increased by 14.0% in 2006. The short-term trend from 2001 to 2006 indicates that the total population in the Great Lakes region has increased by

1.8%.

Lake-by-Lake Assessment

Lake Superior

Trend: Decreasing

Rationale: Human population around Lake Superior has decreased by 5.0% over the long-term. The short-term trend indicates a continued decline; more specifically, from 2001 to 2006, Lake Superior’s population decreased by 1.3%.

Lake Michigan

Trend: Increasing

Rationale: Human population around Lake Michigan has been increasing over the years. The long-term trend indicates a growth of 11.3%, and a short-term trend from 2001 to 2006 shows continued growth of

0.7%.

Lake Huron

Trend: Increasing

Rationale: From 1971 to 2006, human population around Lake Huron has consistently been increasing. Since

1971, the long-term trend indicates a substantial growth of 24.1%. Likewise, the short-term trend shows a continual increase of 2.7% from 2001 to 2006.

Lake Erie

Trend: Increasing

Rationale: Both long-term and short-term trends in Lake Erie indicate that human population is increasing. From

1971 to 2006, human population increased by 3.1% From 2001 to 2006, human population increased by

0.4%.

Lake Ontario

Trend: Increasing

Rationale: Human population around Lake Ontario has consistently been increasing. The long-term trend since

1971 indicates that population has increased by 29.8%. Similarly, the short-term trend from 2001 to

2006 indicates a continued increase of 5.0%.

Purpose

To assess the current human population trend in the Great Lakes region

The Human Population indicator is used in the Great Lakes indicator suite as a Driving Force indicator in the Economic/Social category

Ecosystem Objective

The human population should be living and working with full regard to the purpose of the Great Lakes Water

Quality Agreement, to restore and maintain the chemical, physical and biological integrity of the Great Lakes Basin

Ecosystem.

306

Ecological Condition

In this report, the Great Lakes basin is defined as the watershed of the Great Lakes.

Measures

There are different approaches to determine the human population of the Great Lakes basin. A range of population estimates for the Great Lakes basin are often cited by different organizations and reports (Table 1). In this report, it was initially a challenge to properly compare the Canadian and American population datasets because the U.S. population numbers in the Great Lakes are not available by watershed. In addressing the issue, one potential approach was to identify and include every county that falls fully or partially in the Great Lakes basin. However, the problem with this approach was that whether the county was 1.0% or 100% in the Great Lakes basin, the entire population number would be included in the estimate. Consequently, this resulted in an overestimate of the U.S. population in the Great Lakes region. Another challenge in this approach was the fact that there are many counties that fall in more than one lake basin; in which case, the analysis required to accurately portray the lake-by-lake estimates is difficult.

A ratio approach uses GIS analysis to calculate that if only 1.0% of a county’s boundary falls in the Great Lakes

Basin, then only 1.0% of the county’s population would be included. This ratio approach does have a number of limitations. For example it assumes that each county has an evenly distributed population. That is not always the case and the ratio approach can underestimate human population where a county falls only partially in the Great

Lakes basin but has a population centre(s) within the basin. This approach also does not accurately reflect the significant population in Illinois that resides outside the Great Lakes basin but is serviced by Lake Michigan’s drinking water.

The adjusted-ratio approach, used in this report, reflects a review of the population identified for each U.S. county.

Every county with a population over 100,000 people (and 40,000 people for the Lake Superior Basin) was examined to ensure the population calculated in the ratio approach accurately reflected the distribution of the county’s population. In the end, the population ratio of eight counties were adjusted to accurately reflect the population centers and in the Chicago area four counties were selected and adjusted to represent the total population of Illinois serviced with drinking water.(Table 2).

Total Populations in the Great Lakes Region (Ontario and Eight Great Lakes States)

The total population in the Great Lake basin in 2006 has increased to 38,968,987 (Table 3). As seen in Figure 1, the population growth from 1971 to 1986 was small. From 1986 to 1991, however, the region experienced its largest population growth of 5.7%. Since then, the region’s population numbers continued to grow steadily and from 1996 to 2001, the region had its second largest population growth of 4.3%. In examining the long-term trend, the region’s population increased 14.2% since 1971 (Figure 2). In the short-term trend, from 2001 to 2006, the Great Lakes region experienced a small increase of 1.8% (Figure 3).

In 2006, 33.2% of Canadians lived in the Great Lakes Basin, and 9.4% of Americans lived in the Great Lakes Basin.

Within the entire Great Lakes region, Ontario experienced the largest population increase. From 1971 to 2006,

Ontario’s population increased by 37.4% (Figure 4). The short-term trend from 2001 to 2006 indicated Ontario’s population had grown by 6.5% (Figure 5, Table 3). Five U.S. Great Lakes States also experienced population growth, although their growth was not as evident as Ontario’s. Indiana had the highest population growth amongst the eight states with 17.4%, following by Wisconsin with 11.7%, Michigan with 11.0%, Pennsylvania with 4.0% and Illinois with 3.3% (Figure 4). Minnesota, New York and Ohio, on the other hand, experienced decreases in their population. In particular, Minnesota decreased the most with an 8.2% decline, followed by Ohio with a decline of

4.8% and New York with 4.0% decline (Figure 4).

307

Each of the Great Lakes

The total population around each Great Lake and associated watersheds between 1971to 2006 has fluctuated over time (Table 4).

Around Lake Superior, the human population has decreased by 5.0% from 1971 to 2006 (Figure 6). With the exception of 1971-1976 and 1991-1996 where the population increased slightly, Lake Superior has consistently experienced a declining population. In 1981 to 1986, Lake Superior had its largest population decline of 5.6%

(Figure 6). The short-term trend from 2001 to 2006 indicates that the population continues to decline; the population has decreased by 1.3%. In proportion to the entire Great Lake Basin, only 1.5% of the total human population in the Great Lakes Basin lives around the Lake Superior basin, and this percentage has decreased by

0.4% since 1971 (Figure 7 & 8).

Around Lake Michigan, the human population has increased by 11.3% from 1971 to 2006 (Figure 6). With the exception of 1991-1996, Lake Michigan has consistently had an increasing population. In particular, from 1996 to

2001, the population growth was 6.0% (Figure 8). The short-term trend from 2001 to 2006 indicates an increase of

0.7% (Figure 8). In proportion to the entire Great Lake basin, 34.7% of the total human population lived around

Lake Michigan in 1971 (Figure 7). As of 2006, Lake Michigan’s total population portion in the basin dropped slightly to 33.6% (Figure 8). In both 1971 and 2006, Lake Michigan had the largest population percentage in the basin.

Around Lake Huron, the human population has consistently been growing. The long-term trend indicates that Lake

Huron’s human population has increased by 24.1% since 1971 (Figure 6). From 1986 to 1991, Lake Huron had its largest population increase of 8.5% (Figure 6). The short-term trend shows a continued growth and .from 2001 to

2006, the population increased by 2.7%. Lake Huron basin’s human population was 7.3% of the total population in the Great Lake Basin in 1971 (Figure 7). As of 2006, Lake Huron contained 8.0% of the total population in the basin

(Figure 8).

Around Lake Erie, the human population has increased by 3.1% over the long term (Figure 6). However, unlike other Great Lakes where their human population has either been increasing or decreasing relatively consistently,

Lake Erie’s population trend has fluctuated greatly. From 1971 to 1986, the population decreased steadily. From

1986 to 1991, the population increased significantly by 3.6%. In 1996the population decreased once again and since then, the population has grown again. The short-term trend in Lake Erie indicates an increase of 0.4% from 1996 to

2000. In proportion to the entire Great Lake region, Lake Erie and Lake Michigan used to have the greatest share of population within the basin. In 1971, Lake Erie held 35.4% of the entire population for the Great Lake Basin (Figure

7). In 2006, however, the population had declined by 4.1% to 31.4% of the Great Lake Basin population (Figure 8).

Around Lake Ontario, human population has consistently increased. The long-term trend of indicates an increase of

29.8% since 1971, the largest long-term population growth among the Great Lake basins. Lake Ontario experienced its largest population increase from 1986 to 1991 with 7.7% (Figure 6). The short-term trend, from 2001 to 2006, indicates continued growth of 5.0% (Figure 6). In proportion to the entire Great Lake basin, as of 2006, 25.2% of the total human population fell within Lake Ontario’s basin. In comparison to its 1971 proportion to the other Great

Lake basins, human population in Lake Ontario’s basin increased by 4.6% (Figure 7 and 8).

Linkages

Humans are a key driving force in the overall impact on the environment. Emphasis should be placed on ensuring humans are working, playing and living sustainably. Further analysis in population trends, consumption rate and population density are areas that can help understand and calculate the different impacts humans have on the environment.

308

Assessing Data Quality

Data Characteristics

1. Data are documented, validated, or qualityassured by a recognized agency or organization

2. Data are traceable to original sources

3. The source of the data is a known, reliable and respected generator of data

4. Geographic coverage and scale of data are appropriate to the Great Lakes basin

5. Data obtained from sources within the U.S. are comparable to those from Canada

6. Uncertainty and variability in the data are documented and within acceptable limits for this indicator report

Strongly

Agree

X

X

X

X

X

Agree

X

Acknowledgments

Authors:

Brenda Yu, Great Lakes Division Intern, Environment Canada.

Neutral or

Unknown

Disagree

Strongly

Disagree

Not

Applicable

Contributors:

Krista Verlis, Contractor, Environment Canada, Waterloo, Ontario.

Rob Hyde, Great Lakes Program Officer, Great Lakes Division, Environment Canada.

Susan Holland-Hibbert, Business Analysis and Data Management Division, Information Management Directorate,

Environment Canada

Erika Washburn, Lakewide Management Plan Coordinator, National Oceanic and Atmospheric Administration

Information Sources

National Inventory Report.

National Inventory Report 1990-2008: Greenhouse Gas Sources

. http://www.ec.gc.ca/Publications/default.asp?lang=En&xml=492D914C-2EAB-47AB-A045-C62B2CDACC29

Population Division, United States Census Bureau. (2009).

Table 1: Annual Estimates of the Resident Population for

Counties of Minnesota: April 1, 2000 to July 1, 2008 (CO-EST2008-01-27)

[excel]. Retrieved February, 15,

2011, from http://quickfacts.census.gov/qfd/states/27000lk.html

Population Division, United States Census Bureau. (2009).

Table 1: Annual Estimates of the Resident Population for

Counties of Wisconsin: April 1, 2000 to July 1, 2008 (CO-EST2008-01-55)

[excel]. Retrieved February 16,

2011, from http://quickfacts.census.gov/qfd/states/55000lk.html

Population Division, United States Census Bureau. (2009).

Table 1: Annual Estimates of the Resident Population for

Counties of Illinois: April 1, 2000 to July 1, 2008 (CO-EST2008-01-17)

[excel]. Retrieved February 16, 2011, from http://quickfacts.census.gov/qfd/states/17000lk.html

Population Division, United States Census Bureau. (2009).

Table 1: Annual Estimates of the Resident Population for

Counties of Indiana: April 1, 2000 to July 1, 2008 (CO-EST2008-01-18)

[excel]. Retrieved February 16, 2011, from http://quickfacts.census.gov/qfd/states/18000lk.html

Population Division, United States Census Bureau. (2009).

Table 1: Annual Estimates of the Resident Population for

Counties of Michigan: April 1, 2000 to July 1, 2008 (CO-EST2008-01-26)

[excel]. Retrieved February 16,

2011, from http://quickfacts.census.gov/qfd/states/26000lk.html

Population Division, United States Census Bureau. (2009).

Table 1: Annual Estimates of the Resident Population for

Counties of Ohio: April 1, 2000 to July 1, 2008 (CO-EST2008-01-39)

[excel]. Retrieved February 16, 2011, from http://quickfacts.census.gov/qfd/states/39000lk.html

309

Population Division, United States Census Bureau. (2009).

Table 1: Annual Estimates of the Resident Population for

Counties of Pennsylvania: April 1, 2000 to July 1, 2008 (CO-EST2008-01-42)

[excel]. Retrieved February, 16,

2011, from http://quickfacts.census.gov/qfd/states/42000lk.html

Population Division, United States Census Bureau. (2009).

Table 1: Annual Estimates of the Resident Population for

Counties of New York: April 1, 2000 to July 1, 2008 (CO-EST2008-01-36)

[excel]. Retrieved February 16,

2011, from http://quickfacts.census.gov/qfd/states/36000lk.html

Population Estimates Program, Population Division, United States Census Bureau. (2000).

County population estimates and demographic components of population change: Annual time series, July 1, 1990 to July 1, 1999

.

Retrieved February 17, 2010, from http://www.census.gov/popest/archives/1990s/CO-99-08.html

Statistics Canada. (2010).

Table 153-0036 - Selected population characteristics, Canada, major drainage areas and sub-drainage areas, every 5 years (number unless otherwise noted).

Retrieved February 14, 2011,

< http://estat.statcan.gc.ca/cgiwin/cnsmcgi.pgm?regtkt=&C2Sub=&ARRAYID=1530036&C2DB=EST&VEC=&LANG=E&SrchVer=2&Ch unkSize=50&SDDSLOC=&ROOTDIR=ESTAT/&RESULTTEMPLATE=ESTAT/CII_PICK&ARRAY_PICK

=1&SDDSID=&SDDSDESC>

United States Bureau of the Census - Population Estimates and Population Distribution Branches. (1982).

Preliminary estimates of the intercensal population of counties, 1970-1979

. Retrieved February 15, 2011, from http://www.census.gov/popest/archives/pre-1980/e7079co.txt

United States Bureau of the Census - Population Estimates and Population Distribution Branches. (1992).

Intercensal estimates of the resident population of States and counties, 1980-1989

. Retrieved February 15,

2011, from http://www.census.gov/popest/archives/1980s/e8089co.txt

List of Tables

Table 1

. Population Estimate Approaches (Year: 2006).

Source: United Status Census Bureau and Statistics Canada

Table 2.

Counties Adjustment

.

Source: United Status Census Bureau and Statistics Canada

Table 3.

Total Population in the Great Lakes States and Ontario from 1971 to 2006.

Source: United Status Census Bureau and Statistics Canada

Table 4.

Total Population around each Great Lake and associated watersheds from both Ontario and Great Lake

States from 1971 to 2006.

Source: United Status Census Bureau and Statistics Canada

List of Figures

Figure 1.

Total Population in the Great Lakes Region from 1971 to 2006.

Source: United Status Census Bureau and Statistics Canada

Figure 2.

Long-Term Trend Comparison of the Great Lakes Region between 1971 and 2006.

Source: United Status Census Bureau and Statistics Canada

Figure 3.

Short-Term Trend Comparison of the Great Lakes Region from 2001 to 2006.

Source: United Status Census Bureau and Statistics Canada

Figure 4.

Comparison of the Population in each of the Great Lakes States and Ontario in 1971 to 2006.

Source: United Status Census Bureau and Statistics Canada

Figure 5.

Comparison of the Population in the Great Lakes States and Ontario in 2001 and 2006.

Source: United Status Census Bureau and Statistics Canada

Figure 6.

Total Population around each Great Lake and Associated Watersheds from both Ontario and the Great

Lakes States in 1971 to 2006.

Source: United Status Census Bureau and Statistics Canada

Figure 7.

Percentage of the Human Population Found in Each Great Lake and Associated Watershed in the Great

310

Lakes Region in 1971.

Source: United Status Census Bureau and Statistics Canada

Figure 8.

Percentage of the Human Population Found in Each Great Lake and Associated Watershed in the United

States in 2006.

Source: United Status Census Bureau and Statistics Canada

Last Updated

State of the Great Lakes 2011

Population Estimate Approaches

Approach

Great Lakes and St. Lawrence River Region. (Whole of

Ontario, Quebec and Eight Great Lakes States)

Great Lakes Region (Whole of Ontario and Eight Great

Lakes States)

Great Lakes Basin (All U.S. counties that are fully or partially located in the basin - overestimate approach)

Great Lakes Basin (Ratio of U.S. county within the basin

= ratio of population attributed to the basin - underestimate approach, especially due to Chicago area)

Estimates

Total: 103,359,687

Ontario: 12,665,330

Quebec: 7,631,600

Eight Great Lakes States: 83,062,787

Total: 95,718,087

Ontario:12,665,330

Eight Great Lakes States: 83,062,787

Total: 42 868 987

Ontario: 10,879,768

Eight Great Lakes States: 31,989,219

Total: 32 629 828

Ontario: 10,879,768

Eight Great Lakes States: 21,750,060

Great Lakes Basin (U.S. county adjusted ratio approach used in this report)

Table 1

. Population Estimate Approaches (Year: 2006).

Source:

United Status Census Bureau and Statistics Canada

Total: 38,968,987

Ontario: 10,879,768

Eight Great Lakes States: 28,089,219

Counties Adjustment

County

Cook County, DuPage County, Will

County and Lake County, Illinois

Adjustment Rationale

These ratios were adjusted to account for the approximate 6.4 million people in Illinois that receive drinking water from Lake

Michigan in 2010, according to the Chicago Metropolitan

Agency for Planning

La Porte County, Indiana

St. Joseph County, Indiana

Marquette County Michigan

St. Louis County, Minnesota

Accounting for Michigan City

Accounting for South Bend and surrounding area

Accounting for Marquette

Erie County, Pennsylvania

Douglas County, Wisconsin

Kenosha County, Wisconsin

Accounting for Duluth, and some iron-range communities (e.g.

Hoyt Lakes)

Accounting for City of Erie, and coastal townships from

Springfield to Northeast

Accounting for City of Superior and surrounding area

Accounting for City of Kenosha

Racine County, Wisconsin

Table 2

. Counties Adjustment.

Accounting for City of Racine and surrounding area

Source:

United Status Census Bureau and Statistics Canada

311

Illinois

Indiana

Michigan

Total Population in the Great Lakes States and Ontario

1971

6,021,260

1976

5,938,855

1981

5,829,213

1986

5,831,514

945,833

8,988,758

961,748

9,135,800

975,880

9,228,640

981,281

9,146,124

Minnesota

New York

Ohio

Pennsylvania

Wisconsin

222,844

3,570,221

4,242,702

224,262

2,396,147

223,376

3,541,288

4,160,853

234,963

2,408,192

223,587

3,457,816

4,105,531

234,483

2,410,832

204,558

3,420,398

4,036,441

231,536

2,418,094

1991

6,014,380

1,071,477

9,844,548

200,190

3,444,814

4,069,454

232,468

2,562,540

1996

5,917,302

1,033,124

9,547,821

203,282

3,511,654

4,066,331

233,111

2,529,981

Ontario

Total

Population

6,813,337

33,425,364

7,317,524

33,922,599

7,650,414

34,116,395

8,064,667

34,334,613

8,950,267

36,390,138

Table 3.

Total Population in the Great Lakes States and Ontario from 1971 to 2006.

9,555,896

36,598,502

Source:

United Status Census Bureau and Statistics Canada

2001

6,268,708

1,116,641

10,019,923

207,846

3,476,534

4,101,553

235,324

2,658,063

10,168,222

38,252,815

2006

6,226,965

1,145,015

10,100,700

204,577

3,428,569

4,037,445

233,669

2,712,278

10,879,768

38,968,987

Superior

Michigan

Huron

Erie

Ontario

Total Population around each Great Lake

1971 1976 1981

621,342

11,612,395

2,454,075

11,836,856

6,900,696

636,166

11,704,666

2,616,270

11,743,266

7,222,230

634,723

11,747,052

2,711,185

11,592,423

7,431,013

1986

599,218

11,780,684

2,721,926

11,465,682

7,767,104

1991

597,198

12,509,795

2,973,575

11,894,835

8,414,735

1996

604,314

12,220,287

2,998,756

11,879,720

8,895,424

2001

597,908

12,999,125

3,147,612

12,169,921

9,338,248

2006

590,295

13,095,085

3,233,157

12,217,235

9,833,214

Total for All 33,425,364 33,922,599 34,116,395 34,334,613 36,390,138 36,598,502 38,252,815

Table 4.

Total Population around each Great Lake and associated watersheds from both Ontario and Great Lake

States from 1971 to 2006.

Source:

United Status Census Bureau and Statistics Canada

38,968,987

Figure 1.

Total Population in the Great Lakes Region from 1971 to 2006.

Source: United Status Census Bureau and Statistics Canada

312

Figure 2.

Long-Term Trend Comparison of the Great Lakes Region between 1971 and 2006.

Source: United Status Census Bureau and Statistics Canada

Figure 3.

Short-Term Trend Comparison of the Great Lakes Region from 2001 to 2006.

Source: United Status Census Bureau and Statistics Canada

313

Figure 4.

Comparison of the population around each of the Great Lakes and associated watershed in both the eight of the Great Lakes states and Ontario in 1971 to 2006.

Source: United Status Census Bureau and Statistics Canada

Figure 5.

Comparison of the Population in the Great Lakes States and Ontario in 2001 and 2006.

Source: United Status Census Bureau and Statistics Canada

314

Figure 6.

Total Population around each Great Lake and Associated Watersheds from both Ontario and the Great

Lakes States in 1971 to 2006.

Source: United Status Census Bureau and Statistics Canada

Figure 7.

Percentage of the Human Population Found in Each Great Lake and Associated Watershed in the Great

Lakes Region in 1971.

Source: United Status Census Bureau and Statistics Canada

315

Figure 8.

Percentage of the Human Population Found in Each Great Lake and Associated Watershed in the United

States in 2006.

Source: United Status Census Bureau and Statistics Canada

316

Ice Duration on the Great Lakes

Editor’s Note (2009)

This indicator was last updated in 2007. Since that time, re-evaluation of the information presented suggests that the trend would be better represented as Unchanging rather than Deteriorating. Also, this report represents only one indicator relevant to the analysis of climate change in the Great Lakes basin, and extrapolation to generalized conclusions about climate change is not warranted.

Much additional information about climate change and links to supporting web pages are available through:

Environment Canada: http://www.ec.gc.ca/climat-climate/default.asp?lang=En&n=E584B5CF-1 or http://www.ec.gc.ca/climat-climate/default.asp?Lang=Fr&n=E584B5CF-1

U.S. Environmental Protection Agency: http://www.epa.gov/climatechange/

Great Lakes Information Network: http://www.great-lakes.net/envt/refs/cchange.html

Overall Assessment

Status: Mixed (Fair)

Trend: Deteriorating (with respect to climate change)

Lake-by-Lake Assessment

Individual lake basin assessments were not prepared for this report.

Purpose

To assess the ice duration, and thereby the temperature and accompanying physical changes to each lake

• over time, in order to infer the potential impact of climate change.

The Ice Duration indicator is used in the Great Lakes indicator suite as a State indicator in the Landscape and Natural Processes top level reporting category.

Ecosystem Objective

This indicator is used as a potential assessment of climate change, particularly within the Great Lakes basin.

Changes in water and air temperatures will influence ice development on the Lakes and, in turn, affect coastal wetlands, nearshore aquatic environments, and inland environments.

Ecological Condition

Background

Air temperatures over a lake are one of the few factors that control the formation of ice on that surface. Colder winter temperatures increase the rate of heat released by the lake, thereby increasing the freezing rate of the water.

Milder winter temperatures have a similar controlling effect, only the rate of heat released is slowed and the ice forms more slowly. Globally, some inland lakes appear to be freezing up at later dates, and breaking-up earlier, than the historical average, based on a study of 150 years of data (Magnuson et al. 2000). These trends add to the evidence that the earth has been in a period of global warming for at least the last 150 years.

The freezing and thawing of lakes is a very important aspect to many aquatic and terrestrial ecosystems. Many fish species rely on the ice to give their eggs protection against predators during the late part of the ice season. Nearshore ice has the ability to change the shoreline as it can encroach upon the land during winter freeze-up times. Even inland systems are affected by the amount of ice that forms, especially within the Great Lakes basin. Less ice on the

Great Lakes allows for more water to evaporate and be spread across the basin in the form of snow. This can have an effect on the foraging animals (such as deer) that need to dig through snow during the winter in order to obtain food.

Status of Ice Duration on the Great Lakes

Observations of the Great Lakes data showed no real conclusive trends with respect to the date of freeze-up or break-up. A reason for this could be that due to the sheer size of the Great Lakes, it wasn’t possible to observe the

317

whole lake during the winter season (at least before satellite imagery), and therefore only regional observations were made (inner bays and ports). However, there were enough data collected from ice charts to make a statement concerning the overall ice cover during the season. There appears to be a decrease in the maximum ice cover per season over the last thirty years (Fig. 1).

The trends on each of the five Great Lakes show that during this time span the maximum amount of ice forming each year has been decreasing, which correlated to the average ice cover per season observed for the same time duration (Table 1). Between the 1970s and the 1990s there was at least a 10% decline in the maximum ice cover on each lake, nearly 18% in some cases, with the greatest decline occurring during the 1990s. Since a complete freezeup did not occur on all the Great Lakes, a series of inland lakes (known to freeze every winter) in Ontario were examined to see if there was any similarity to the results in the previous studies. Data from Lake Nipissing and Lake

Ramsey were plotted (Fig. 2) based on the complete freeze-over date (ice-on date) and the break-up date (ice-off date). The freeze-up date for Lake Nipissing appears to have the same trend as the other global inland lakes: freezing over later in the year. Lake Ramsey however, seems to be freezing over earlier in the season. The ice-off date for both however, appear to be increasing, or occurring at later dates in the year. These results contradict what is said to be occurring with other such lakes in the northern hemisphere (Magnuson et al. 2000).

The satellite data used in this analysis can be supplemented by on-the-ground citizen-collected data. The IceWatch program of Environment Canada’s Ecological Monitoring and Assessment Network and Nature Canada have citizen scientists collecting ice-on and ice-off dates of lakes throughout the Ontario portion of the Great Lakes basin. These volunteers use the same criteria for ice-on and ice-off as does the satellite data, although the volunteers only collect data for the portion of the lake that is visible from a single vantage point on the shore. The IceWatch program began in 2000 as a continuation of a program run by the Meteorological Service of Canada. Data from this program date back to the 1850s. An analysis of data from this database and the Canadian Ice Database (Canadian Ice

Services/Meteorological Service of Canada) showed that ice break-up dates were occurring approximately one day earlier every seven years between 1950 and 2004 for 341 lakes across Canada (Futter, unpublished data). The data from IceWatch are not as comprehensive as the satellite-collected data, but they do show some trends in the Great

Lakes basin. From two sites with almost 100 years of data, Lake Nipissing is shown to be thawing later in the season

(Fig. 3). IceWatch data from near Lake Ramsey indicate that lakes have been freezing later over the past 30 years.

Pressures

Based on the results of Figure 1 and Table 1, it seems that ice formation on the Great Lakes should continue to decrease in total cover if the predictions on global atmospheric warming are true. Milder winters will have a drastic effect on how much of the lakes are covered in ice, which in turn, will have an effect on many aquatic and terrestrial ecosystems that rely on lake ice for protection and food acquisition.

Management Implications

Only a small number of data sets were collected and analyzed for this study, so this report is not conclusive. To reach a level of significance that would be considered acceptable, more data on lake ice formation would have to be gathered. While the data for the Great Lakes is easily obtained from 1972 through the present, smaller inland lakes, which may be affected by climate change at a faster rate, should be examined. As much historical information as is available should be obtained. This data could come from IceWatch observers and the IceWatch database from throughout the Great Lakes basin. The more data that are received will increase the statistical significance of the results.

Comments from the author(s)

Increased winter and summer air temperatures appear to be the greatest influence on ice formation. Currently there are global protocols, which are being introduced in order to reduce the emission of greenhouse gases.

It would be convenient for the results to be reported every four to five years (at least for the Great Lakes), and quite

318

possibly a shorter time span for any new inland lake information. It may also be feasible to subdivide the Great

Lakes into bays and inlets, etc., in order to get an understanding of what is occurring in nearshore environments.

Acknowledgments

Author:

Gregg Ferris, Environment Canada Intern, Downsview, ON.

Updated by:

Heather Andrachuk, Environment Canada, Ecological Monitoring and Assessment Network (EMAN);

[email protected]

All data analyzed and charts created by the author.

Information Sources

Magnuson, J.J., Robertson, D.M., Benson, B.J., Wynne, R.H., Livingston, D.M., Arai, T., Assel, R.A., Barry, R.G.,

Carad, V., Kuusisto, E., Granin, N.G., Prowse, T.D., Stewart, K.M., and Vuglinski, V.S. 2000. Historical trends in lake and river ice covering the Northern Hemisphere. Science 289(9):1743-1746.

Ice charts obtained from the National Oceanic and Atmospheric Administration (NOAA) and the Canadian Ice

Service (CIS).

Data for Lake Nipissing and Lake Ramsey obtained from Walter Skinner, Climate and Atmospheric Research,

Environment Canada-Ontario Region.

List of Tables

Table 1

. Mean ice coverage, in percent, during the corresponding decade.

Source: National Oceanic and Atmospheric Administration.

List of Figures

Figure 1

. Trends of maximum ice cover and the corresponding date on the Great Lakes, 1972-2000.

The red line represents the percentage of maximum ice cover and the blue line represents the date of maximum ice cover.

Source: National Oceanic and Atmospheric Administration.

Figure 2

. Ice-on and ice-off dates for Lake Nipissing (red line) and Lake Ramsey (blue line).

Data were smoothed using a 5-year moving average.

Source: Climate and Atmospheric Research and Environment Canada.

Figure 3

. Ice-off dates and trend line from 1900-2000 on Lake Nipissing.

Source: Ecological and Monitoring Assessment Network (EMAN).

Last Updated

State of the Great Lakes 2007

The “Mixed” status term used in the 2009 report were replaced with the “Fair” status term to be consistent with definitions used for the 2011 reporting cycle.

319

Mean ice coverage

Lake

Erie

Huron

Michigan

Ontario

Superior

1970-1979

94.5

71.3

50.2

39.8

74.5

1980-1989

90.8

71.7

45.6

29.7

73.9

Table 1

. Mean ice coverage, in percent, during the corresponding decade.

Source: National Oceanic and Atmospheric Administration.

1990-1999

77.3

61.3

32.4

28.1

62.0

1970s to 1990s

-17.2

-10.0

-17.8

-11.7

-12.6

Figure 1

. Trends of maximum ice cover and the corresponding date on the Great Lakes, 1972-2000.

The red line represents the percentage of maximum ice cover and the blue line represents the date of maximum ice cover.

Source: National Oceanic and Atmospheric Administration.

320

Figure 2

. Ice-on and ice-off dates for Lake Nipissing (red line) and Lake Ramsey (blue line).

Data were smoothed using a 5-year moving average.

Source: Climate and Atmospheric Research and Environment Canada.

Figure 3

. Ice-off dates and trend line from 1900-2000 on Lake Nipissing.

Source: Ecological and Monitoring Assessment Network (EMAN).

321

Inland Water Quality Index

Overall Assessment

Status: Fair

Trend: Undetermined

Rationale: The average Water Quality Index (WQI) value for 95 Canadian tributaries to the Great Lakes was 70/100.

Lake-by-Lake Assessment

Lake Superior

Status: Good

Trend: Undetermined

Rationale: Average WQI value for 9 tributaries was 80/100.

Lake Michigan

Status: Undetermined

Trend: Undetermined

Lake Huron

Status: Good

Trend: Undetermined

Rationale: Average WQI value for 29 tributaries was 83/100.

Lake Erie

Status: Fair

Trend: Undetermined

Rationale: Average WQI value for 18 tributaries was 45/100.

Lake Ontario

Status: Fair

Trend: Undetermined

Rationale: Average WQI value for 33 tributaries was 66/100.

Other Spatial Scales

St. Lawrence River

Status: Good

Trend: Undetermined

Rationale: Average WQI value for 6 tributaries was 81/100.

Purpose

To communicate the overall water quality status of Great Lakes tributaries with the Canadian Council of

Ministers of the Environment (CCME) Water Quality Index (WQI).

To infer the influence of land use activities on the surface water quality of streams in the Great Lakes basin.

To provide context for the effects of tributary water quality on Great Lakes aquatic ecosystems, particularly the nearshore.

The Inland Water Quality Index indicator report is used in the Great Lakes indicator suite as a Pressure indicator in the Pollution and Nutrients top level reporting category.

322

Ecosystem Objective

This indicator supports the objective of ensuring that surface waters in the Great Lakes basin are of a quality that is protective of aquatic life.

Ecological Condition

Measure

The WQI (CCME 2011

b

) provides a mathematical framework for synthesizing water quality monitoring results for multiple samples and parameters into a single value representing overall water quality conditions at a given site. The

WQI is based on three measures (factors) of compliance with water quality criteria (guidelines and objectives) for the protection of aquatic life. The first factor (scope) measures the percentage of the number of parameters that comply with water quality criteria. The second factor (frequency) measures the percentage of individual water quality tests that comply with criteria. The third factor (magnitude) measures by how much criteria are exceeded.

The three factors are combined into a single unitless value between 0 and 100 where higher numbers indicate better water quality. Computation of the WQI is described in detail in CCME (2001

a

,

b

). The sensitivity of the WQI to user-driven variations in formulation and application has been studied by Khan et al. (2004), Davies (2006), Gartner

Lee Limited (2006), Statistics Canada (2007), de Rosemond et al. (2009), and Kilgour and Associates Limited

(2009).

For this SOLEC indicator, WQI values were calculated using measurements of total concentrations of eight water quality parameters: ammonia (unionized), chloride, copper, iron, nitrate, nitrite, phosphorus and zinc (Table 1).

Water quality data (2002-2009) were acquired from the Ontario Provincial Water Quality Monitoring Network

(OMOE 2011). The most downstream monitoring site on each stream draining to the Great Lakes was selected, including tributaries to the Great Lake connecting channels and the St. Lawrence River. The most recent four years of results were used for the index calculations. For most (83/95) sites the 2006-2009 data were used. The 2002-2005 data were used for some (12/95) sites that were monitored infrequently (< 10 samples) between 2006 and 2009.

Sources of the water quality criteria include CCME water quality guidelines for the protection of aquatic life

(CCME 2011

a

) and the Ontario interim provincial water quality objective for total phosphorus (OMOE 1994).

Endpoint

The WQI calculates a value between 0 and 100 for each monitoring site. The developers of the WQI recommended fitting the calculated values into five categories that describe water quality conditions: Excellent (95-100); Good

(80-94); Fair (65-79); Marginal (45-64); and Poor (0-44). The category range describes sites where the water quality complies with water quality criteria virtually all of the time (Excellent) or hardly any of the time (Poor).

For this SOLEC indicator, the five original categories developed by CCME were dissolved into three descriptive categories: Good (80-100), Fair (45-79) and Poor (0-44).

Background

The Provincial Water Quality Monitoring Network (PWQMN) collects stream water quality information from hundreds of sites across Ontario in partnership with Ontario’s Conservation Authorities. Most of these sites are located in the Great Lakes basin, and many are located at or near the outlets of tributaries to the Great Lakes. Stream water samples from each site are collected approximately monthly and delivered to the Ontario Ministry of the

Environment’s laboratory where they are tested using consistent analytical methods for a consistent set of water quality parameters. Parameters are selected to indicate the influence of land used activities on stream water quality.

For example, chloride is measured as an indicator of the influence of salt loading from winter de-icing. Field measurements including water temperature and pH are also taken at the time of sample collection using portable water quality meters. A complete set of water quality data (2002-2009) for all stream monitoring sites is available on the Ontario Ministry of the Environment public website (OMOE 2011).

323

Status of Water Quality in Great Lakes Tributaries

The overall water quality status of tributaries to the Great Lakes can be described as Fair (WQI avg

=70, n=95). 39%,

48% and 13% were categorized as having Good, Fair and Poor water quality, respectively (Figures 1 and 2).

Good water quality was found in certain tributaries to Lakes Superior, Huron and Ontario and the St. Lawrence

River. Poor water quality was found in certain tributaries to Lakes Erie and Ontario. The WQI values at individual sites ranged from 7.6 (Sturgeon River, Lake Erie) to 100 (Montreal and Michipicoten Rivers, Lake Superior;

Mississagi and Serpent Rivers, Lake Huron).

On a lake-by-lake basis (Figure 2), tributaries to Lake Superior (WQI avg

=80, n=9), Lake Huron (WQI avg

=83, n=29) and the St. Lawrence River (WQI avg

=81, n=6) can be described as having Good water quality. Tributaries to Lake

Erie (WQI avg

=45, n=18) and Lake Ontario (WQI avg

=66, n=33) had Fair water quality.

Linkages

Calculated WQI values show a statistically significant negative association with two measures of watershed development: percent watershed area occupied by human land uses and road density (Figure 3). This suggests that overall water quality in Great Lakes tributaries, as represented by WQI values, is influenced by human land uses where minimally developed watersheds have the highest WQI values.

The WQI values indicate the potential for substances in stream water to impact aquatic life based on compliance with water quality criteria. However, the values are not a direct measure of impacts to aquatic communities, such as changes in fish and benthic invertebrate communities. The WQI values also infer the potential for discharge from tributaries to impact the Great Lakes, particularly at the tributary mouths and nearby nearshore areas.

Management Challenges/Opportunities

The WQI was developed to communicate water quality information to general audiences. It is not intended to replace rigorous technical analysis of water quality data for water resources management.

The water quality of many Great Lakes tributaries has been monitored since the 1960s. Calculation of WQI values for historical monitoring data is possible and could support an assessment of trends in the WQI over time. However, some of the anticipated challenges include: inconsistent laboratory methods and detection limits over time and incomplete datasets (missing parameters, missing years).

The WQI could be applied to water quality results from U.S. tributaries to the Great Lakes depending on the availability of the data. An anticipated challenge is that WQI results are not directly comparable between jurisdictions where different water quality parameters and criteria are used. This will be the case for any index.

Comments from the author(s)

The CCME WQI is used extensively in Canada, most notably for the annual Canadian Environmental Sustainability

Indicators report (Environment Canada 2011). The WQI has also been used and adapted by some of Ontario’s

Conservation Authorities for their watershed report cards. OMOE currently does not use the WQI for reporting; however, given its widespread use, the author accepts that it is a logical starting point for developing an indicator of

Great Lakes tributary water quality for SOLEC.

The strengths and weaknesses of the WQI have been, and continue to be, discussed. A few reports on the sensitivity of the WQI are posted on the CCME website. The Gartner Lee Limited (2006) report is particularly helpful in understanding the nuances of the WQI.

Most of the monitoring sites in the Ontario PWQMN are purposefully located in populated areas and areas where water quality impacts from varying land uses are known or expected. Minimally-impacted reference watersheds are

324

likely under-represented in this SOLEC indicator.

The sites selected for this SOLEC indicator likely under-represent the upper Great Lakes, especially Lake Superior.

A redundancy analysis or similar approach could be considered for future iterations of this indicator to omit some sites from the lower Great Lakes such that each of the Lakes is more equally represented.

Human influence is not the only cause of exceedances of water quality criteria. Parameters can exceed their respective criteria in areas that are naturally rich in a given nutrient or metal. No considerations for naturallyoccurring elevated concentrations of some parameters were made in the WQI calculations.

Assessing Data Quality

Data Characteristics

Strongly

Agree

Agree

Neutral or

Unknown

Disagree

Strongly

Disagree

1. Data are documented, validated, or qualityassured by a recognized agency or organization

2. Data are traceable to original sources

3. The source of the data is a known, reliable and respected generator of data

4. Geographic coverage and scale of data are appropriate to the Great Lakes basin

5. Data obtained from sources within the U.S. are comparable to those from Canada

X

X

X

X

6. Uncertainty and variability in the data are documented and within acceptable limits for X this indicator report

Clarifying Notes: Water quality data for U.S. tributaries to the Great Lakes were unavailable for WQI calculations.

Not

Applicable

X

Acknowledgments

Authors:

Aaron Todd, Environmental Monitoring and Reporting Branch, Ontario Ministry of the Environment, Toronto, ON

Contributors:

Shenaz Sunderani, Carline Rocks and Georgina Kaltenecker, Environmental Monitoring and Reporting Branch,

Ontario Ministry of the Environment, Toronto, ON

Information Sources

Canadian Council of Ministers of the Environment (CCME). 2001

a

. CCME Water Quality Index 1.0, Technical

Report. http://www.ccme.ca/assets/pdf/wqi_techrprtfctsht_e.pdf

Canadian Council of Ministers of the Environment (CCME). 2001

b

. CCME Water Quality Index 1.0, User’s

Manual. http://www.ccme.ca/assets/pdf/wqi_usermanualfctsht_e.pdf

Canadian Council of Ministers of the Environment (CCME). 2011

a

. Canadian water quality guidelines for the protection of aquatic life: Summary table. Updated 2011. http://st-ts.ccme.ca/?chems=all&chapters=1&pdf=1

Canadian Council of Ministers of the Environment (CCME). 2011

b

. CCME Water Quality Index 1.1. http://www.ccme.ca/assets/xls/ccmewqi_calculator_1.1_en.xls

Davies, J.M. 2006. Application and tests of the Canadian Water Quality Index for assessing changes in lakes and rivers of central North America. Lake and Reservoir Management 22(4):308-320.

http://dx.doi.org/10.1080/07438140609354365 de Rosemond, S., Duro, D.C., and Dubé, M. 2009. Comparative analysis of regional water quality in Canada using the Water Quality Index. Environmental Monitoring and Assessment 156(1-4):223-240. http://dx.doi.org/10.1007/s10661-008-0480-6

Environment Canada. 2011. Canadian Environmental Sustainability Indicators. http://ec.gc.ca/indicateurs-

325

indicators/default.asp?lang=En&n=13307B2E-1

Gartner Lee Limited. 2006. A sensitivity analysis of the Canadian Water Quality Index. http://www.ccme.ca/assets/pdf/wqi_sensitivity_analysis_rpt_web.pdf

Khan, A.A., Paterson, R., and Khan H. 2004. Modification and application of the Canadian Council of Ministers of the Environment Water Quality Index (CCME WQI) for the communication of drinking water quality data in

Newfoundland and Labrador. Water Quality Research Journal of Canada 39(3):285-293.

Kilgour and Associates Limited. 2009. Reducing the sensitivity of the Water Quality Index to episodic events. http://www.ccme.ca/assets/pdf/wqi_sensitivity_1435.pdf

Ontario Ministry of the Environment (OMOE). 1994. Water management, policies, guidelines and provincial water quality objectives of the Ministry of the Environment. http://www.ene.gov.on.ca/stdprodconsume/groups/lr/@ene/@resources/documents/resource/std01_079681.pdf

Ontario Ministry of the Environment (OMOE). 2011. Provincial Water Quality Monitoring Network data (2002-

2009). http://www.ene.gov.on.ca/environment/en/resources/collection/data_downloads/index.htm#PWQMN

Statistics Canada. 2007. Behaviour study on the Water Quality Index of the Canadian Council of Ministers of the

Environment. http://www.statcan.gc.ca/pub/16-001-m/16-001-m2007003-eng.htm

Information on the Ontario Provincial Water Quality Monitoring Network (PWQMN) – including a map of monitoring sites can be found here: http://www.ene.gov.on.ca/environment/en/monitoring_and_reporting/provincial_water_quality_monitoring_netw ork/index.htm

.

PWQMN monitoring sites (ESRI ArcGIS shapefile), 2002-2009 results (Microsoft Access and Excel) and metadata are posted on the MOE public website here: http://www.ene.gov.on.ca/environment/en/resources/collection/data_downloads/index.htm

.

The WQI Calculator (Microsoft Excel, v1.1, 2011), user’s manual and technical report can be downloaded here: http://www.ccme.ca/ourwork/water.html?category_id=102 .

List of Tables

Table 1

. Water quality criteria for the eight indicators used in the CCME Water Quality Index (WQI) calculations.

Source: Ontario Ministry of the Environment

List of Figures

Figure 1

. CCME Water Quality Index (WQI) values for 95 Canadian tributaries to the Great Lakes.

Source: Ontario Ministry of the Environment

Figure 2

. CCME Water Quality Index (WQI) values for Canadian Great Lakes tributaries by lake basin.

Source: Ontario Ministry of the Environment

Figure 3

. CCME Water Quality Index (WQI) values for Canadian Great Lakes tributaries (n=95) versus (a) percent watershed occupied by human land uses and (b) road density.

Source: Ontario Ministry of the Environment

Last Updated

State of the Great Lakes 2011

326

Water quality criteria

Indicator

Ammonia (unionized)

Chloride

Copper

Iron

Nitrate

Nitrite

Phosphorus

Zinc

Criterion

0.0152 mg L

-1

-N

110 mg L

-1

2

µ g L

-1

at water hardness of 0-120 mg L

-1

-CaCO

3

3

µ g L

-1

at water hardness of 120-180 mg L

-1

-CaCO

3

4

µ g L

-1

at water hardness of >180 mg L

-1

-CaCO

3

300

µ g L

-1

2.9 mg L

-1

-N

0.06 mg L

-1

-N

0.03 mg L

-1

30

µ g L

-1

Source

CCME

CCME (draft)

CCME

CCME

CCME

CCME

OMOE

CCME

Sources: CCME = Water quality guidelines for the protection of aquatic life (CCME 2011

a

); OMOE = Interim provincial water quality objective (OMOE 1994).

Table 1

. Water quality criteria for the eight indicators used in the CCME Water Quality Index (WQI) calculations.

Source: Ontario Ministry of the Environment

Figure 1

. CCME Water Quality Index (WQI) values for 95 Canadian tributaries to the Great Lakes.

Source: Ontario Ministry of the Environment

327

Figure 2

. CCME Water Quality Index (WQI) values for Canadian Great Lakes tributaries by lake basin.

Source: Ontario Ministry of the Environment

328

Figure 3

. CCME Water Quality Index (WQI) values for Canadian Great Lakes tributaries (n=95) versus (a) percent watershed occupied by human land uses and (b) road density.

Source: Ontario Ministry of the Environment

329

Land Cover

Overall Assessment:

Status: Mixed

Trend: Undetermined

Rationale: Low-intensity development increased 33.5%, road area increased 7.5%, and forest decreased

2.3% from 1992 to 2001. Agriculture lost 210,000 ha (520,000 acres) of land to development.

Approximately 50% of forest losses were due to management and 50% to development

Lake-by-Lake Assessment:

Lake Superior

Status: Good

Trend: Undetermined

Rationale: Lowest conversion rate of non-developed land to developed and highest conversion rate of non-forest to forest. Of the 4.2 million ha (10.4 million acre) watershed area in the U.S. basin, 1,676 ha (4141 acres) of wetland, 6,241 ha (15,422 acres) of agricultural land, and 14,300 ha (35,336 acres) of forest land were developed between 1992 and 2001.

Lake Michigan

Status: Mixed

Trend: Undetermined

Rationale: Intermediate to high rate of land development conversions. Of the 1.2 million ha (3.0 million acre) watershed area, 9,724 ha (24,028 acres) of wetland, 78,537 ha (193,624 acres) of agricultural land, and

57,529 ha (142,157 acres) of forest land were developed between 1992 and 2001.

Lake Huron

Status: Fair

Trend: Undetermined

Rationale: Second lowest rate of conversion of land to developed. Of the 4.1 million ha (10.1 million acre) watershed area in the U.S. basin, 4,314 ha (10,660 acres) of wetland, 17,881 ha (44,185 acres) of agricultural land, and 17,730 ha (43,812 acres) of forest land were developed between 1992 and 2001.

Lake Erie

Status: Poor

Trend: Undetermined

Rationale: Highest conversion rate of non-developed to developed area. Of the 5.0 million ha (12.4 million acre) watershed area in the U.S. basin, 3,352 ha (8,283 acres) of wetland, 52,502 ha (129,735 acres) of agricultural land, and 27,869 ha (68,866 acres) of forest land were developed between 1992 and 2001.

Lake Ontario

Status: Mixed

Trend: Undetermined

Rationale: Intermediate to high conversion rate of non-developed to developed land use coupled with the lowest rates of wetland development. Of the 3.4 million ha (8.4 million acre) watershed area in the U.S. basin,

458 ha (1,132 acres) of wetland, 24,883 ha (61,487 acres) of agricultural land, and 20,670 ha (51,076 acres) of forest land were developed between 1992 and 2001.

Other Spatial Scales

This indicator pertains primarily to risk of degradation of the coastal margins and nearshore waters. The importance

330

of land use condition (especially as a source of nutrients and contaminants) declines with increasing distance away from the coastal margin since substances are typically transported by the water contributed by tributaries.

Purpose

Assess the status of land cover within the Great Lakes basin

Infer the potential impact (risk of degradation) of land cover and land cover change on Great Lakes

• ecosystem health

The Land Cover indicator is used in the Great Lakes indicator suite as a State indicator in the Landscapes &

Natural Processes category.

Ecosystem Objective

Sustainable development is a generally accepted land use goal for the Great Lakes basin. This indicator supports

Annex 13 of the 1987 Great Lakes Water Quality Agreement (GLWQA).

Ecological Condition

A common land cover classification was developed to allow an integrated comparison of land use in both Canada and the U.S. between 1990 and 2001. This involved integrating the detailed but distinct classifications of the US system (24 land use classes as delineated by Wolter 2006) with the Canadian system (The Ontario Ministry of

Natural Resources’ Ontario Provincial Land Cover, consisting of 27 (in 1990) or 28 (in 2000) classes). The resulting unified assessment was comprised of 6 land classes (Developed, Agriculture, Grassland/ Shrubland, Forest,

Wetland, Water (Ciborowski et al. 2011)). Using this common land cover classification for the year 2000, we calculated the total and proportional amounts of each land cover class by lake and across the Great Lakes Basin

(Table 1).

There were large variations in proportional distribution of each type of land cover among lakes, with the Lake

Superior basin being predominately forested (Fig. 1) and Lake Erie predominantly agricultural (Fig 2). Forest and

Agricultural land uses were more evenly distributed in lakes Michigan (Fig. 3) and Ontario (Fig. 4). The relative amount of developed land ranged from a low of 2.1% in the Lake Superior basin to 13.4% in the Lake Erie basin.

The large variation in land use among lakes reflects the underlying climatic and soil gradients across the Great

Lakes Basin that have historically constrained the conversion of the native vegetation (forest or grassland) to agricultural land use.

Between two nominal time periods (1992 and 2001), the U.S. portion of the Great Lakes watershed has undergone substantial change in many key land use/land cover (LU/LC) categories. Of the total change that occurred (798,755 ha, 2.5% of watershed area), salient transition categories included a 33.5% increase in area of low-intensity development, 7.5% increase in road area, and a decrease of forest area by over 2.3%, the largest LU/LC category and area of change within the watershed. More than half of the forest losses involved transitions into early successional vegetation (ESV), and hence, will likely remain in forest production of some sort. However, nearly as much forest area was, for all practical purposes, permanently converted to developed land. Likewise, agriculture lost over 50,000 more hectares (125,000 acres) of land to development than forestland, much of which involved transitions into urban/suburban sprawl. Approximately 210,068 ha (81%) of agricultural lands were converted to development, and 16.3% of that occurred within 10 km of the Great Lakes shoreline.

LU/LC transitions between 1992 and 2001 within near-shore zones of the Great Lakes (0-1, 1-5, 5-10 km) largely paralleled those of the overall watershed. While the same transition categories dominated, their proportions varied by buffered distance from the lakes. Within the 0-1 km zone from the Great Lakes shoreline, conversions of forest to both ESV (9,087 ha, 5.0% of total category change (TCC)) and developed land (8,657 ha, 5.6% of TCC) were the largest transitions, followed by conversion of 3,935 ha (1.9% of TCC) of agricultural land to developed. For the 1-5 km zone inland from the shore, forest to developed conversion was the largest of the three transitions (17,049 ha,

331

11.0% of TCC), followed by agricultural to developed (14,279 ha, 6.8% of TCC) and forest to ESV (13,116 ha,

7.3% of TCC). Within the 5-10 km zone from shoreline, transition category dominance was most similar to the trend for the whole watershed, with 16,113 ha (7.7% of TCC) of agriculture converted to developed, 14,516 ha (8.0% of

TCC) of forest converted to ESV, and 14,390 ha (9.3% of TCC) of forestland being developed by 2001. When all buffers from shoreline out to 10 km are combined, the forest to developed transition category was the largest

(40,099 ha, 25.9% of TCC), followed by forest to ESV (36,726 ha, 20.3% of TCC), and agricultural to developed

(34,328 ha, 16.3% of TCC).

Contrary to previous decadal estimates showing an increasing forest area trend from the early 1980s to the early

1990s, due to agricultural abandonment and transitions of forest land away from active management, there was an overall decrease (~2.3%) in forest area between 1992 and 2001. Explanation of this trend is largely unclear.

However, increased forest harvesting practices in parts of the region coupled with forest clearing for new developments may be overshadowing gains from the agricultural sources observed in previous decades.

The distribution of land use classes for each Great Lake is shown in Figures 1-5. When analyzed on a lake-by-lake basis, Lake Michigan’s watershed naturally has shown the greatest area of change from 1992 to 2001 (286,587 ha,

~2.5%), because its watershed is entirely within the U.S., and hence, the largest analyzed. Lake Michigan’s watershed leads in all LU/LC transition categories but two: 1) miscellaneous vegetation to flooded and 2) ESV to forest (Fig. 3). When normalized by area, however, Lake Michigan’s proportion of LU/LC change is intermediate when compared to the other Great Lakes watersheds on the U.S. side of the border. Although Lake St. Clair is not a

Great Lake, and the U.S. part of its watershed is largely metropolitan (Fig. 2), Lake St. Clair’s watershed shows the highest rates of change into development from wetland, ESV, agriculture, and forest sources.

Of the Great Lakes, Lake Erie’s watershed (Fig. 2) shows the greatest proportion of land conversion to development

(87,077 ha, 1.74%), while Lake Superior’s watershed (Fig. 1) had the lowest proportion (20,351 ha, 0.48%). For example, Lake Erie’s watershed had the highest proportion of agricultural land conversion to development.

However, Lake Ontario’s watershed (Fig. 4) showed the greatest proportion of forest conversion to development.

Lake Superior’s watershed reflects a high proportion of lands under forest management in that it has both the highest proportion of forest conversion to ESV and vice-versa. Lastly, Lake Huron’s watershed (Fig. 5) had the highest proportion of wetlands being converted to development, followed closely by watersheds for Lake Michigan and

Lake Erie.

Linkages

The importance of land use condition (especially as a source of nutrients and contaminants) is greatest at shorelines and coastal margins, and declines with increasing distance away from the shore since substances are typically transported by the water contributed by tributaries. Natural land cover is an indicator of good conditions because it incorporates nutrients into biomass and slows the rate of water runoff into the lakes, together with materials

(sediments, pollutants) that the water transports.

Management Challenges/Opportunities

Rates of land use change provide an important integrated indicator of the degree and location of both loss and gain of natural lands, representing increases and reductions in the risks of degradation.

Comments from the author(s)

Land use changes estimated for the combined US-Canada data set between 1990 and 2000 are much more pronounced in the Canadian data set compared with the US data, with up to 10% change observed in certain categories. These changes are much greater than changes reported in the literature, and lead us to evaluate possible explanations for these differences. There are two sources of error. The first is registration error – maps not properly aligned in a common coordinate system (discussed in detail by Ciborowski et al. 2011). This can lead to

332

displacement of images found on both maps. For example, a road running through a forest whose apparent position is offset between images is interpreted as a conversion from road to forest in on one part of the map, and a conversion from forest to road on another part. Since numerous map tiles are used to create the composite map for

Canada, and the error across the map tiles appears to be non-uniform, each source image would have to be reviewed and corrected to remove the overall bias. The second, and likely more pronounced error, is the result of a change in criteria used to classify land use/land cover between 1990 and 2000. Ciborowski et al. (2011) document examples of where extensive areas mapped as ‘settlement/developed’ in 1990 are not present in the Yr 2000 map; those same areas in 2000 are mapped as forest depletion’. In other cases, roads mapped as ‘developed’ in 1990 are mapped as

‘open land’ in 2000. Yet another final example, shows an extensive area near Sudbury classified as ‘developed’ in

1990 but mapped as ‘early successional’ in 2001. The errors due to differences in classification criteria and registration between images preclude a meaningful assessment of land use change. To make such an assessment, we would recommend a reclassification of the source images from 1990, using the same criteria for the 2000 assessment

(and that common criteria be developed and used for all successive interpretations of satellite data). This, coupled with the accurate georectification of the 1990 imagery, would allow an assessment of land use change compatible with the US land use change assessment conducted by Wolter, and ultimately integration across the Great Lakes

Basin.

Assessing Data Quality:

Data Characteristics

1. Data are documented, validated, or qualityassured by a recognized agency or organization

2. Data are traceable to original sources

3. The source of the data is a known, reliable and respected generator of data

4. Geographic coverage and scale of data are appropriate to the Great Lakes basin

5. Data obtained from sources within the U.S. are comparable to those from Canada

6. Uncertainty and variability in the data are documented and within acceptable limits for this indicator report

Strongly

Agree

X

X

X

X

X

X

Agree

Neutral or

Unknown

Disagree

Strongly

Disagree

Not

Applicable

Acknowledgments:

Authors:

Jan J.H. Ciborowski, Department of Biological Sciences, University of Windsor, 401 Sunset Avenue, Windsor, ON,

Canada. N9B 3P4

Terry A. Brown, George E. Host, Paul Meysembourg, and Lucinda B. Johnson, Natural Resources Research

Institute, University of Minnesota Duluth, 5013 Miller Trunk Highway, Duluth, MN, 55811

Peter Wolter, Department of Forest Ecology and Management, University of Wisconsin-Madison.

Contributors:

Members of the Great Lakes Environmental Indicators project - Gerald L. Niemi (Senior PI; NRRI, University of

Minnesota Duluth), Nicholas P. Danz (University of Wisconsin – Superior), and Thomas Hollenhorst (US EPA,

Mid-Continent Ecology Division National Health and Environmental Effects Research Laboratory, Duluth, MN

55804) contributed to formation of the research group that identified the need for this database. Scudder D. Mackey

(Habitat Solutions NA) and Li Wang (University of Windsor) contributed to the cross-walking and amalgamation of

Canadian and US-based information into a common dataset. Sandra E. George (Environment Canada, Burlington) and Mike Robertson (Ontario Ministry of Natural Resources, Peterborough, ON) were especially helpful in facilitating the licensing and acquisition of Canadian map data. The SOLEC coordinators Rob Hyde, Nancy Stadler-

333

Salt, Stacey Cherwaty-Pergentile (Environment Canada, Burlington, ON), and Paul Horvatin and Karen Rodriguez

(US EPA GLNPO, Chicago, IL) provided the impetus for developing the concept paper on land cover that allowed us to assess the status of land cover within the Great Lakes basin, and to ultimately infer the potential impact (risk of degradation) of land cover and land cover change on Great Lakes ecosystem health.

The project on which these data were based was originally funded by the U.S. Environmental Protection Agency

Science to Achieve Results (STAR) Estuarine and Great Lakes (EaGLe) program through funding to the Great

Lakes Environmental Indicators (GLEI) and Reference Condition projects (U.S. EPA Agreements EPA/R-8286750 and EPA/R-82877701, respectively), and funding from the National Space and Aeronautics Administration (NAG5-

11262). We additionally acknowledge funding from Environment Canada (Agreements KW405-09-1987-O and

KW405-10-1831R-O) to update and expand the stress data across the entire Great Lakes Basin.

Information Sources

:

Canadian LULC was derived from the Provincial Land Cover data sets:

(http://www.lib.uoguelph.ca/resources/data_resource_centre/geospatial_data_resources/ ontario_provincial_land_cover_database.cfm).

From 1990 and 2000; for 2000, the eastern portion of the basin south of the Canadian Shield was completed using the National Land and Water Information Service (NLWIS) coverage: http://www4.agr.gc.ca/AAFC-AAC/display-afficher.do?id=1226330737632&lang=eng

U.S. LULC was based on Wolter and colleagues’ work from the Great Lakes Environmental Indicators (GLEI) project (Wolter et al. 2006), which in turn were derived from the National Land Cover Dataset (NLCD).

Land cover classes and the crosswalking procedures necessary to integrate the US and Canadian databases into a common classification system are documented in Ciborowsi et al. (2011).

Ciborowski, J.J.H., G.E. Host, T.A. Brown, P. Meysembourg and L.B. Johnson. 2011. Linking Land to the Lakes: the linkages between land-based stresses and conditions of the Great Lakes. Background Technical Paper prepared for Environment Canada in support of the 2011 State of the Lakes Ecosystem Conference (SOLEC),

Erie, PA. 47 p + Appendices.

Wolter, P., C.A. Johnston and G.J. Niemi. 2006. Land use land cover change in the Great Lakes basin 1992–2001.

Journal of Great Lakes Research 32:607–628.

List of Tables:

Table 1

. Total and relative area of land in the watershed of each Great Lake in each of six land cover classes in 2000

(Canada) and 2001 (US), and the entire Great Lakes Basin.

Source: Ciborowski et al. (2011).

List of Figures:

Figure 1.

Distribution of land use across the Lake Superior basin in 2000 (Canada) and 2001 (US) colour-coded according to six land use classes.

Source: Ciborowski et al. (2011).

Figure 2

. Distribution of land use across the Lake Erie basin in 2000 (Canada) and 2001 (US) colour-coded according to six land use classes.

Source: Ciborowski et al. (2011)

Figure 3

. Distribution of land use across the Lake Michigan in 2000 (Canada) and 2001 (US) colour-coded according to six land use classes.

Source: Ciborowski et al. (2011)

Figure 4

. Distribution of land use across the Lake Ontario basin in 2000 (Canada) and 2001 (US) colour-coded according to six land use classes.

Source: Ciborowski et al. (2011).

334

Figure 5

. Distribution of land use across the Lake Huron basin in 2000 (Canada) and 2001 (US) colour-coded according to six land use classes.

Source: Ciborowski et al. (2011).

Last Updated:

State of the Great Lakes 2011

Permissions and Links:

Permission to put graphics online: Yes.

Permission to link from SOLEC web site to other Agency site(s): N/A

Lake

Ontario

Area

(km

2

) %

Lake Erie

Area

(km

2

) %

Lake Huron

Area

(km

2

) %

Lake

Michigan

Area

(km

2

) %

Developed

Agriculture

Grassland/

Shrubland

Forest

Wetland

Water

5,828

22,099

2,023

27,280

2,317

3,116

9.3

35.3

3.2

43.5

3.7

5.0

10,732

52,844

696

13,032

1,974

965

13.4

65.9

0.9

16.2

2.5

1.2

6,926

33,702

2,452

76,640

10,163

11,107

4.9

23.9

1.7

54.4

7.2

7.9

11,799

42,364

3,193

38,516

17,423

3,627

10.1

36.2

2.7

32.9

14.9

3.1

Lake

Superior

Area

(km

2

)

2,660

1,733

1,242

95,818

10,483

13,060

%

2.1

1.4

1.0

76.7

8.4

10.4

Glreat Lakes

Area

(km

2

)

37,948

15,274

9,608

251,285

42,360

31,874

%

7.2

29.0

1.8

47.8

8.1

6.1

Total 62,663 100.0 80,242 100.0 140,994 100.0 116,922 100.0 124,996 100.0 525,817 100.0

Table 1.

Total and relative area of land in the watershed of each Great Lake in each of six land cover classes in 2000

(Canada) and 2001 (US), and the entire Great Lakes Basin.

Source: Ciborowski et al. (2011).

335

Figure 1.

Distribution of land use across the Lake Superior basin in 2000 (Canada) and 2001 (US) colour-coded according to six land use classes. Source: Ciborowski et al. (2011).

Figure 2

. Distribution of land use across the Lake Erie basin in 2000 (Canada) and 2001 (US) colour-coded according to six land use classes. Source: Ciborowski et al. (2011)

336

Figure 3

. Distribution of land use across the Lake Michigan in 2000 (Canada) and 2001 (US) colour-coded according to six land use classes. Source: Ciborowski et al. (2011)

Figure 4

. Distribution of land use across the Lake Ontario basin in 2000 (Canada) and 2001 (US) colour-coded according to six land use classes. Source: Ciborowski et al. (2011).

337

Figure 5

. Distribution of land use across the Lake Huron basin in 2000 (Canada) and 2001 (US) colour-coded according to six land use classes.

Source: Ciborowski et al. (2011).

338

Lake Sturgeon

Overall Assessment

Status: Fair

Trend: Improving

Rationale: There are remnant populations in each basin of the Great Lakes, but few of these populations are large. Progress continues as agencies learn more about population status in many tributaries and the Great Lakes proper. Confirmed observations and captures of lake sturgeon continue to increase in all lakes. Stocking is contributing to increased abundance in some areas. There remains a need for information on some remnant spawning populations. Researchers are learning more about the juvenile life stage. In many areas habitat restoration is needed because spawning and rearing habitat has been destroyed or altered, or access to it has been blocked.

Lake-by-Lake Assessment

Lake Superior

Status: Fair

Trend: Improving

Rationale: Lake sturgeon abundance shows an increasing trend in a few remnant populations and in two rivers where stocked. Twenty-one Lake Superior tributaries historically supported lake sturgeon populations.

Recent evidence of successful reproduction has been documented in ten tributaries.

Lake Michigan

Status: Fair

Trend: Improving

Rationale: Remnant populations persist in at least nine tributaries having unimpeded connections to Lake

Michigan. Successful reproduction has been documented in eight of these rivers, and abundance has increased in a few in recent years. Active rehabilitation has been initiated through rearing assistance in two remnant populations, and reintroductions have been initiated in four rivers.

Lake Huron

Status: Fair

Trend: Improving

Rationale: Current lake sturgeon spawning activity is limited to five tributaries, four in Georgian Bay and the

North Channel and one in Saginaw Bay. Abundant stocks of mixed sizes are consistently captured in the North Channel, Georgian Bay, southern Lake Huron and Saginaw Bay.

Lake Erie

Status: Fair

Trend: Improving

Rationale: Lakewide incidental catches since 1992 indicate a possible improvement in their status in lake Erie.

Spawning occurs in four known locations in the basin, all located in the connecting waters between lakes Huron and Erie. The Huron Erie Corridor supports a robust population of all age classes. The western basin of Lake Erie, the Detroit River East of Fighting Island, the North Channel of the St. Clair

River and Anchor Bay in Lake St. Clair appear to be nursery areas for juveniles and foraging areas for adults.

Lake Ontario/St. Lawrence River

Status: Fair

Trend: Improving

339

Rationale: Lakewide incidental catches since 1995 indicate a possible improvement in their status. Spawning occurs in the Niagara River, Trent River, and possibly the Black River. There are sizeable populations within the Ottawa and St. Lawrence River systems. Stocking for restoration began in 1995 in New

York.

Purpose

To assess the presence and abundance of lake sturgeon in the Great Lakes and their connecting waterways and

• tributaries

To infer the health and status of the nearshore benthivore fish community that does, could or should include lake sturgeon

Ecosystem Objective

Conserve, enhance or rehabilitate self-sustaining populations of lake sturgeon where the species historically occurred and at a level that will permit all state, provincial and federal delistings of classifications that derive from degraded or impaired populations, e.g., threatened, endangered or at risk species. Lake sturgeon is identified as an important species in the Fish Community Goals and Objectives for each of the Great Lakes. Lake Superior has a lake sturgeon rehabilitation plan, and many of the Great Lakes States have lake sturgeon recovery or rehabilitation plans which call for increasing numbers of lake sturgeon beyond current levels.

Ecological Condition

Background

Lake sturgeon (

Acipenser fulvescens

) were historically abundant in the Great Lakes with spawning populations using many of the major tributaries, connecting waters, and shoal areas across the basin. Prior to European settlement of the region, they were a dominant component of the nearshore benthivore fish community, with populations estimated in the millions in each of the Great Lakes (Baldwin

et al

. 1979). In the mid- to late 1800s, they contributed significantly as a commercial species ranking among the five most abundant species in the commercial catch (Baldwin

et al

. 1979, Figure 1).

The decline of lake sturgeon populations in the Great Lakes was rapid and commensurate with habitat destruction, degraded water quality, and intensive fishing associated with settlement and development of the region. Sturgeon were initially considered a nuisance species of little value by European settlers, but by the mid-1800s, their value as a commercial species began to be recognized and a lucrative fishery developed. In less than 50 years, their abundance had declined sharply, and since 1900, they have remained a highly depleted species of little consequence to the commercial fishery. Sturgeon is now extirpated from many tributaries and waters where they once spawned and flourished (Figures 2 and 3). They are considered rare, endangered, threatened, or of watch or special concern status by the various Great Lakes fisheries management agencies. Their harvest is currently prohibited or highly regulated in most waters of the Great Lakes.

Status of Lake Sturgeon

Efforts continue by many agencies and organizations to gather information on remnant spawning populations in the

Great Lakes. Most sturgeon populations continue to sustain themselves at a small fraction of their historical abundance. In many systems, access to spawning habitat has been blocked, and other habitats have been altered.

However, there are remnant populations in each basin of the Great Lakes, and some of these populations are large in number (tens of thousands of fish, Figures 3-7). Genetic analysis has shown that Great Lakes populations are regionally structured and show significant diversity within and among lakes (DeHaan et al. 2006, Welsh et al. 2008).

Lake Superior

The fish community of Lake Superior remains relatively intact in comparison to the other Great Lakes (Bronte

et al

.

2003). Historic and current information indicate that at least 21 Lake Superior tributaries supported spawning lake

340

sturgeon populations (Harkness and Dymond 1961; Auer 2003; Quinlan 2007). Successful reproduction was confirmed in the St. Louis River in spring 2011 through capture of larval fish. Lake sturgeons currently reproduce in 10 Lake Superior tributaries. The Lake Sturgeon Rehabilitation Plan for Lake Superior (Auer 2003) serves as the guiding document for agency activities. Populations in the Sturgeon River, Michigan, and Bad River, Wisconsin, meet rehabilitation plan criteria for self-sustaining populations (Auer 2003, Auer and Baker 2007, GLIFWC unpublished data, Quinlan 2007, Quinlan et al. 2010). Improvements in assessment techniques have provided better estimates of lakewide abundance (Auer and Baker 2007, Schram 2007, and GLIFWC unpublished data). The estimated combined spawning run population size in the Bad and White rivers, Wisconsin, was 844 individuals, 666 in the Bad River and 178 in the White River (Schloesser and Quinlan 2011). The estimated number of lake sturgeon in annual spawning run in the Sturgeon River, MI range from 350 to 400 adults (Auer and Baker 2007) ,

Stocking in the St. Louis (MN) and Ontonagon (MI) rivers have resulted in increases in abundance in localized areas. Genetic analysis has shown that lake sturgeon populations in Lake Superior are distinct from one another and significantly different from those in the other Great Lakes (Welsh et al. 2008).

Studies and assessments continue in key tributaries, embayments and nearshore waters including the Kaministiquia

River, Ontario, Chequamegon Bay, Wisconsin, Batchawana and Goulais bays, Ontario, Pigeon Bay,

Minnesota/Ontario in Keweenaw Bay and in nearshore waters off the Ontonagon River, Michigan (Quinlan et al.

2010). A key study on the Kaministiquia River, Ontario, examined the effect of conrolled flow regimes at Kakabeka

Falls on the migratory behavior and reproductive response of lake sturgeon from 2002-2009 (Friday 2009). Habitat

(substrate type and water depth) for adult and juvenile fish was geo-referenced and quantified using hydroacoustics in the Kaministiquia River, Ontario (Biberhofer and Prokopec 2005) and Bad River (Cholwek

et al

. 2005). Habitat preference of stocked sturgeon is being studied in the Ontonagon and St. Louis rivers using radio telemetry

(Fillmore 2003, 1854 Authority unpublished data). Due to potential for overexploitation, sport fishing regulations in

Ontario waters have been changed to eliminate harvest. There remains a prohibition of commercial harvest of lake sturgeon in Lake Superior. Regulation of recreational and subsistence/home use harvest in Lake Superior varies by agency.

In 2011, fishery agencies conducted a coordinated lakewide juvenile lake sturgeon index survey that will provide the most comprehensive data set to date for Lake Superior lake sturgeon. This effort targeted eighteen locations associated with all known current and historic lake sturgeon populations. Despite limited progress, challenges remain. Spawning runs are absent in 11 of 21 historic spawning tributaries, and only two populations meet targets identified in the 2003 Rehabilitation Plan. Overall, lake sturgeon abundance remains a small fraction of historical abundance, estimated at 870,000 (Hay-Chmielewski and Whelan 1997) and basic abundance and biological data is unavailable for a few stocks.

Lake Michigan

Sturgeon populations in Lake Michigan continue to sustain themselves at a small fraction of their historical abundance. An optimistic estimate of the lakewide adult abundance is less than 10,000 fish, well below 1% of the most conservative estimates of historic abundance (Hay-Chmielewski and Whelan 1997). Remnant populations currently are known to spawn in waters of at least nine tributaries having unimpeded connections to Lake Michigan

(Schneeberger

et al.

2005, Elliott 2008, Clapp

et al.

2012 ). Two rivers, the Menominee and Peshtigo, appear to support annual spawning runs of 200 or more adults, six rivers, the Manistee, Muskegon, Grand, Kalamazoo, Fox and Oconto, appear to support annual spawning runs of between 20 and 100 adults, and smaller numbers of sturgeon in spawning condition have been captured or observed in the lower Mansitique and St. Joseph Rivers (Baker 2006;

Elliott and Gunderman 2008; K. Smith, unpublished data). Successful reproduction has been documented in eight of these rivers, and age 0 juveniles can be captured regularly in many of these rivers. Recent recruitment estimates have been made from research efforts in the Peshtigo River indicating that in some years, several hundred fall recruits are produced from that system (Caroffino et al. 2007), and research and assessment efforts in the Manistee and Muskegon rivers indicate significant recruitment from those systems as well (K. Smith, MDNR, personal

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communication). In addition, abundance of spawners in some rivers appears to have increased in the last decade, indicating that increased recruitment may have been occurring for several years in some rivers. Some lake sturgeon have been observed during spawning times in a few other Lake Michigan tributaries such as the Cedar, Millecoquins and Boardman Rivers, and near some shoal areas where sturgeon are thought to have spawned historically, but it is not known if spawning occurs in these systems,. A large self-sustaining population exists in the Lake Winnebago system upstream of the lower Fox River. This population spawns in the Wolf and Upper Fox Rivers and supports an active winter recreational spear fishery. The upper Menominee River also supports two self-sustaining populations which are separated from each other and from the lower Menominee River population by several dams. These populations also support a very limited hook and line fishery in the fall of each year.

Active management in the form of reintroduction stocking and rearing assistance has been implemented in 7 Lake

Michigan basin tributaries. Commencing in 2005, Lake sturgeon are being reared from eggs using streamside rearing facilities and stocked as fingerlings into the Milwaukee, Kewaunee, Cedar and Whitefish rivers where sturgeon have been considered extirpated for some time. Over the next 20 years, these reintroductions are intended to rebuild self-sustaining populations that use these rivers to spawn. Streamside rearing facilities are also being used to increase the survival of naturally produced eggs and larvae in the Manistee River (since 2003,Holtgren et al 2007) and in the Kalamazoo river since 2011. Stocking also has been conducted in the upper Menominee River for many years and in portions of the Winnebago system. Though limited recreational harvest is allowed in both the upper

Menominee River and the Winnebago system, no harvest is allowed from other Lake Michigan tributaries or from

Lake Michigan. Habitat evaluations have been conducted in many sturgeon tributaries within the Lake Michigan basin (Daugherty et al. 2008), and improvements in flow conditions and improved fish passage via dam removal of installation of fish passage is ongoing.

Lake Huron

Lake sturgeon populations continue to be well below historical levels. Spawning has been identified in the Garden,

Mississaugi and Spanish rivers in the North Channel, in the Nottawasaga River in Georgian Bay and in the Rifle

River in Saginaw Bay. Adult spawning populations for each of these river systems are estimated to be in the 10s and are well below rehabilitation targets (Hay-Chmielewski and Whelan 1997; Holey

et al

. 2000). Research in the

Saginaw River Watershed in 2005 – 2007 indicated that lake sturgeon are no longer spawning in that watereshed, although sufficient spawning habitat does exist below the Dow Dam (Midland, MI) on the Tittabawassee River, and below Hamilton Dam (Flint, MI) on the Flint River. Also, creation of a rock ramp at the Chesaning Dam

(Chesaning, MI) on the Cass river in 2010 now allows lake sturgeon passage and provides access to approximately

40 miles of high gradient quality spawning habitat above the former dam site. Research since 2007 on the St.

Mary’s River system has yet to determine a spawning stock of Lake Sturgeon. Barriers in Michigan’s tributaries to

Lake Huron continue to be a major impediment to successful rehabilitation in Lake Huron.

Stocks of lake sturgeon in Lake Huron are monitored primarily through the volunteer efforts of commercial fishers cooperating with the various resource management agencies. To date the combined efforts of researchers in U.S. and

Canadian waters has resulted in over 7,000 sturgeon tagged in Saginaw Bay, southern Lake Huron, Georgian Bay and the North Channel, with relatively large stocks of mixed sizes being captured at each of these general locations.

Tag recoveries, telemetry studies, and genetic collections indicate that lake sturgeon are moving within and between jurisdictional boundaries and between lake basins, supporting the need for more cooperative management between the states and between the U.S. and Canada. In October 2009 Ontario closed both commercial and recreational harvest of Lake Sturgeon. Regulation of recreational and subsistence/home use harvest in Lake Huron varies by agency and is largely unknown.

Lake Erie

Lake sturgeon populations continue to be well below historical levels with the exception of the stocks located in the

Huron Erie Corridor which are close to historic levels. Spawning has been identified at four locations in the

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connecting waters between Lak