The design of a non-lethal fish monitoring program for rivers... by Karma Tenzin

The design of a non-lethal fish monitoring program for rivers... by Karma Tenzin
The design of a non-lethal fish monitoring program for rivers in Bhutan
by
Karma Tenzin
B.Sc. University of Delhi, Sherubtse College (Tashigang, Bhutan), 2000
A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF
THE REQUIREMENTS FOR THE DEGREE OF
Master of Science
In the Graduate Academic Unit of Biology
Supervisor:
Kelly Munkittrick, PhD, Canadian Rivers Institute, UNB
Saint John
Examining Board:
John Johnson, PhD, Biology, UNB Saint John - Chair
Keith Dewar, PhD, Business, UNB Saint John
This thesis is accepted by the
Dean of Graduate Studies
THE UNIVERSITY OF NEW BRUNSWICK
March, 2006
© Karma Tenzin, 2006
ABSTRACT
Bhutan is a small country in the Himalayas that started modernization in the
1960s with a series of five-year plans focused on the sustainable use of
renewable natural resources. The development of large-scale hydroelectric
facilities and the lack of any existing data on fisheries resources have increased
concerns about the river ecosystems. Any monitoring program needs to focus
on non-lethal sampling protocols in keeping with Bhutanese cultural philosophy.
To test the hypothesis that growth in fish can be assessed using non-lethal
sampling, 350 yellow perch (Perca flavescens) were collected from 10 sites on
the Saint John River, NB, Canada. Growth rates were compared within and
among sites using size at age, linear growth profile obtained through backcalculation, increments of growth at age, and size at a standard back-calculated
age. The smallest size, lowest condition, oldest fish and slowest growth were
observed at two reservoir sites (Tobique and Nackawic), and faster growth was
observed at sites with nutrient inputs (Edmundston and Fredericton). The
Nackawic site has previously been identified as a site of concern, but this is the
first study suggesting that the Tobique reservoir is impacted by stress. The
techniques and experiences gained in the Saint John River Study permitted the
designing of a relevant fish monitoring program suited for Bhutan. Data from
Bhutan were reviewed and factors affecting study design were taken into
account with respect to selection of sentinel species, sampling sites, sampling
ii
time and identification and selection of endpoints for assessment of river health
and fish performance in Bhutan. The suggested program will monitor relative
species abundances, growth rates, age distributions, and condition of fish. The
designed framework will strengthen Bhutan’s capability to monitor and manage
their fisheries resources during the next phase of development.
iii
ACKNOWLEDGMENTS
I am very much indebted to great many people who helped me both
professionally and personally in various ways and taught me a lot during the
course of pursuing this degree. I owe much of what I achieved to all these
people who took me through the right direction and helped me when I did not
have the means to get there. I owe special thanks especially to my father Jochu
Dorji and mother Sherub Zangmo for always believing in me.
First and foremost I would like to thank my supervisor Dr. Kelly Munkittrick
for everything he has done for me; I could never thank him enough. Every
meeting with him has been greatly enriching and his support and advice
invaluable. I have in many ways learnt a great deal about life from Kelly and you
are truly my mentor. I am what I am, only due to your untiring push and pull
throughout my uphill struggle. I could always recount on you and your family as
my guardians during my stay in Canada. I found a home away from home in
you and your family and I am very thankful to you and your family for taking care
of me throughout my stay.
I would also like to thank Dr. Allen Curry and Dr. Deborah MacLatchy for
agreeing to be my co-supervisors. I learned a lot as your student and I am
always grateful for everything that was taught to me. I would like to thank Dr.
Deb MacLatchy for helping me with my admission to UNB, finding me a place to
stay and picking me up at the airport when I first came to Canada and especially
iv
for asking Kelly to be my supervisor. I would like to thank Dr. Allen Curry for all
your kind assistance.
Much thanks goes to Dr. Brendan Galloway for taking me to the numerous
field trips, I learned a lot about field research from you. The field trips were great
learning experiences and through these trips I was able to see much of New
Brunswick. I am also grateful to Chad Doherty and Sandra Brasfield for taking
me to field trips and teaching me about sampling on a lot of occasions. I would
like to thank Mark Gautreau for going with me to sample. I gathered much of my
field research experiences through Kelly Munkittrick, Lisa Peters, Brendan
Galloway, Chad Doherty, Sandra Brasfield, Mark Gautreau and Kirk Roach.
In no certain order I would like to thank: Kelly Munkittrick, Deb MacLatchy,
Allen Curry, Lisa Peters, Sandra Brasfield, Brendan Galloway, Steve Currie,
Michelle Gray, Jonathan Freedman, Genevieve Vallieres, Frank, Lottie Vallis,
Jennifer Peddle, Mark Gautreau, Karen Gormley, Eric Chernoff ,Jennifer Shaw,
Kirk Roach, Megan, my family, and many others for being kind and supportive
towards me. If it would not have been you all, I would not have been here today.
Thank you all.
Last but not the least I would like to thank the Royal Government of
Bhutan, Ministry of Agriculture, Bhutan Trust Fund for Environmental
Conservation, and Royal Civil Service Commission for enabling me to pursue
my degree. I am also very indebted to National Environment Commission and
Hydromet Services Division for giving me permission to use their data in this
thesis.
v
TABLE OF CONTENTS
ABSTRACT ........................................................................................................ ii
ACKNOWLEDGMENTS .................................................................................... iv
TABLE OF CONTENTS .................................................................................... vi
LIST OF TABLES............................................................................................ viii
LIST OF FIGURES ............................................................................................. x
CHAPTER 1
1
GENERAL INTRODUCTION .............................................................................. 1
1
Overview ................................................................................. 1
1.1
Bhutan: Background Information ......................................... 2
1.2
Need for an Aquatic Effects Framework for Bhutan ........... 4
1.3
Hydropower in Bhutan........................................................... 5
1.3.1
Impacts of Hydroelectric Dams .............................................. 8
1.3.2
Other Potential Impacts on Rivers of Bhutan...................... 10
1.4
Design of Monitoring Studies ............................................. 12
1.4.1
Focus of Monitoring Studies................................................. 15
1.4.2
Non-lethal Sampling Methodology ....................................... 16
1.4.3
Back-calculating growth ....................................................... 19
1.5
Statement of Problem .......................................................... 20
1.6
Objectives and Outline of Thesis........................................ 21
CHAPTER 2
23
BACK-CALCULATIONS OF GROWTH OF YELLOW PERCH ALONG THE
SAINT JOHN RIVER ........................................................................................ 23
2
Introduction .......................................................................... 23
2.1
The Saint John River, New Brunswick ............................... 24
2.1.1
Recent Studies - Saint John River........................................ 26
2.1.2
Hydroelectric dams on the Saint John River (history and
location) ................................................................................ 30
2.1.3
Objective of this Chapter ...................................................... 32
2.2
Materials and Methods ........................................................ 33
2.2.1
Study Area – the upper Saint John River ............................ 33
2.2.2
Sample Collection.................................................................. 36
2.2.3
Age Reading ........................................................................... 38
2.3
Results .................................................................................. 41
2.3.1
Raw Fish Data ........................................................................ 42
2.3.2
Effects of Sex on Size of Perch ............................................ 46
2.3.3
Size-at-age comparisons....................................................... 46
2.3.4
Length Frequency Data and Ford-Walford Plots................. 50
2.3.5
Back-Calculating Growth ...................................................... 55
2.3.6
Weight Back-Calculation ....................................................... 63
2.4
Discussion ............................................................................ 69
2.4.1
Relevance of the findings to Bhutan.................................... 74
CHAPTER 3
76
A FRAMEWORK FOR MONITORING FISH IN BHUTAN’S RIVERS .............. 76
3
Ecology of Bhutan’s Rivers Systems................................. 76
vi
3.1
Designing the Framework: Ecosystem Definition............. 80
3.1.1
Physiographic Zones of Bhutan ........................................... 82
3.1.2
Climate.................................................................................... 87
3.1.3
Hydrogeology......................................................................... 91
3.1.4
Physical Structure of Rivers ................................................. 97
3.1.5
Water Chemistry of Rivers .................................................... 98
3.1.6
Land Use............................................................................... 102
3.1.7
Dams and Reservoirs .......................................................... 108
3.2
Factors Affecting Sampling Design.................................. 109
3.3
Site Selection...................................................................... 112
3.4
Selection of Sampling Design........................................... 113
3.4.1
Development of Methods and Approach ........................... 117
3.4.2
Baseline Data for Reference Sites...................................... 118
3.4.3
Among River Reference Comparisons .............................. 119
3.4.4
Altitudinal Reference Sites ................................................. 119
3.4.5
Longitudinal Comparisons of Developed Sites................. 120
3.5
Endpoint Selection............................................................ 120
3.6
Selection of Sentinel Species ........................................... 125
3.6.1
Life History Characteristics of Native Species.................. 130
3.6.2
Sample Size Requirements ................................................. 131
3.7
Final Study Design: A Fisheries Assessment Program for
Bhutan
132
3.7.1
Schedule of Sampling ......................................................... 132
3.7.2
Selection of Species ............................................................ 134
3.7.3
Sampling Considerations.................................................... 134
3.7.4
Monitoring Program............................................................. 136
3.8
Conclusion.......................................................................... 137
References..................................................................................................... 139
4
References.......................................................................... 139
5
Appendix A ......................................................................... 153
Curriculum Vitae
vii
LIST OF TABLES
Table 1-1
Table 1-2
Table 1-3
Table 2-1
Table 2-2
Table 2-3
Table 2-4
Table 2-5
Table 2-6
Table 2-7
Table 2-8
Table 2-9
Table 2-10
Table 2-11
Table 2-12
Table 2-13
Table 2-14
Table 2-15
Table 2-16
Table 3-1
Mega hydropower stations power generation............................... 7
A comparison of stressor-based, effects-based and valuesbased approaches to environmental assessment (modified
from Dubé and Munkittrick, 2001)............................................... 13
Endpoints relevant for non-lethal evaluation of fish
performance in an effects-based approach (modified from
Environment Canada, 2005b)..................................................... 19
Fish community study sites, their characteristics and human
impacts (from Curry & Munkittrick 2005) .................................... 25
Summary statistics for all perch captured. Data sharing an
alphabetical letter are not statistically different (within a
column)....................................................................................... 44
Length and weight data for perch used in back-calculation of
length and weight respectively ................................................... 45
Summary statistics for perch captured at St. Hilaire,
Edmundston and Nackawic by sex. Values are mean ± SE
(n), and values sharing an alphabetical superscript are not
significantly different within a site ............................................... 47
Regression table of length at age for all sites, and the rank of
sites based on slope of the regression line................................. 50
Summary table of Ford-Walford plots for fork length (linear
growth) at Edmundston (EDMN) and St. Hilaire (SHIL) by
sex.............................................................................................. 51
Scale width (mm) calculated using Ford-Walford plots (the
plot was limited to age 1-5 fish) .................................................. 53
Distance of annuli (mm) from origin derived from FordWalford plots at individual sites .................................................. 53
Fork length at age increments (cm) derived from FordWalford plots .............................................................................. 54
Summary table of Ford-Walford plots for fork length (linear
growth) ....................................................................................... 54
Scale increments for Edmundston females (mm) ....................... 58
Comparisons of year classes of males and females at St.
Hilaire and Edmundston sites ..................................................... 59
Back-calculated fork length at age (cm) ..................................... 64
Number of fish aged per year class per site for the Saint
John River sites. All fish were collected in 2001, except
Nackawic, which includes fish captured in 2004, and
Edmundston, which were collected in 2003................................ 68
Averages for four-year-olds at all sites ....................................... 68
Summary of rankings of size or growth rates for yellow perch ... 70
Discharge and runoff (source Baillie and Norbu, 2004) .............. 77
viii
Table 3-2
Table 3-3
Table 3-4
Table 3-5
Table 3-6
Table 3-7
Table 3-8
Table 3-9
Table 3-10
Table 3-11
Table 3-12
Table 3-13
Table 3-14
Table 3-15
Table 3-16
Table 3-17
Table 5-1
Table 5-2
Water quality tests for Wang chhu River System (NWWFCC,
2001) .......................................................................................... 79
Summary of fish species recorded in Bhutan (Petr, 1999) ......... 81
List of Introduced fish species (Petr, 1999) ................................ 82
Physiographic zones within the North-South Valleys and
Ridges of Bhutan (recreated from Norbu et al. 2003) ................. 85
Mean annual rainfall in Bhutan (modified from Baille and
Norbu, 2004). ............................................................................. 90
Discharge and specific runoff from rivers during 2003
(source data from Hydrology Section, 2005) .............................. 95
Water quality survey 2003 by NEC (source data provided by
NEC, 2005)............................................................................... 100
Minerals and location of mines in Bhutan (compiled from
USGS, 2006) ............................................................................ 105
Influence of system characteristics on design for fisheries
studies ...................................................................................... 111
Potential sites for development fisheries studies in Bhutan...... 114
Potential stresses associated with hydroelectric development
(created from Greig et al., 1992; CEA, 2001; DFO, 2005)........ 122
Generalized response patterns of fish populations to
changes in populations (from Munkittrick et al., 2000).............. 123
Indicators that should be addressed in the monitoring
program (adapted from Ribey et al., 2002)............................... 126
Sentinel species characteristics for optimizing effects-driven
assessment of aquatic environmental health using fish
populations (modified from Munkittrick et al., 2000) ................. 128
Sample sites and schedule for studies on Bhutan’s rivers
(refer to 2.16 for site locations), ................................................ 133
Recommended fish survey measurements to determine
effects in fish growth, reproduction, condition and survival
(adapted from Ribey et al., 2002) ............................................. 135
Life-history characteristics for fish species of Bhutan: most
information collected from Fishbase– www.fishbase.org and
Petr, 1999 (* valid scientific name from Fishbase).................... 154
Life-history characteristics for introduced fish species of
Bhutan: most information collected from Fishbase–
www.fishbase.org and Petr, 1999 (* valid scientific name
from Fishbase).......................................................................... 157
ix
LIST OF FIGURES
Figure 2-1
Figure 2-2
Figure 2-3
Figure 2-4
Figure 2-5
Figure 2-6
Figure 2-7
Figure 2-8
Figure 2-9
Figure 2-10
Figure 2-11
Figure 2-12
Figure 2-13
Figure 2-14
Figure 2-15
Figure 2-16
Figure 2-17
Figure 2-18
Figure 2-19
Figure 2-20
Figure 2-21
Figure 2-22
Figure 2-23
Map of the Saint John River basin (from Curry and
Munkittrick 2005) ........................................................................ 28
Two year old fish (file: Edm_DS_F_2Yr_864) ............................ 40
Two year old fish scale sample (file: Aroostook_023)................. 40
Fork length-at-age within sites for females and males at: (A)
St. Hilaire (B) Edmundston ......................................................... 48
Fork length-at-age among sites at Edmundston (EDMN) and
St. Hilaire (SHIL): (A) Females (B) Males................................... 48
Weight-at-age within sites for females and males at: (A) St.
Hilaire (B) Edmundston .............................................................. 49
Weight-at-age among sites at Edmundston (EDMN) and St.
Hilaire (SHIL): (A) Females (B) Males ........................................ 49
Ford-Walford plot for fork length for Edmundston female
yellow perch. .............................................................................. 52
Scale length at age comparison within site between males
and females at: (A) Edmundston (B) St. Hilaire ......................... 56
Scale width at age comparison within site between males
and females at: (A) Edmundston (B) St. Hilaire .......................... 56
Scale length at age comparison among sites at Edmundston
(EDMN) and St. Hilaire (SHIL): (A) Females (B) Males .............. 57
Scale width at age comparison among sites at Edmundston
(EDMN) and St. Hilaire (SHIL): (A) Females (B) Males .............. 57
Scale length to width ratio at age for male (A) and female (B)
perch at Edmundston ................................................................. 58
Comparison of average scale increment (Edmundston)
versus Daily Temperature Unit (DTU) >10C for the year of
hatching. Scale increment represents the average increment
for 4-year-old fish for that year; temperature was obtained
from temperature records from Mactaquac Fish Hatchery. ........ 60
Distance of annuli from origin for male (A) and female (B)
perch at Edmundston ................................................................. 61
Percent scale increment to total scale length for male (A)
and female (B) perch at Edmundston ......................................... 61
Scale growth profile for all sites back-calculated from FordWalford plots .............................................................................. 62
Fork length versus scale length for yellow perch from Saint
John River .................................................................................. 65
Back-calculated fork length at age for yellow perch from the
Saint John River ......................................................................... 65
Length increments at age derived from Ford-Walford plots........ 66
Back-calculated weight at scale length for yellow perch............. 66
Back-calculated weight at age for yellow perch .......................... 67
Weight increments at age derived from Ford-Walford plots........ 67
x
Figure 2-24 Relative abundance of yellow perch as compared to other
fish species at sites along the Saint John River (from Curry
and Munkittrick, 2005) ................................................................ 73
Figure 2-25 Fish species richness at sites along the upper Saint John
River from upstream of the Canadian border at Moody
Bridge to Fredericton (from Curry and Munkittrick, 2005)........... 73
Figure 3-1 Major river systems of Bhutan .................................................... 78
Figure 3-2 Provisional physiographic zonation of Bhutan (recreated
from Norbu et al., 2003).............................................................. 84
Figure 3-3 Geological map of Bhutan showing bedrock composition
(sourced from Daniel et al. 2003) ............................................... 88
Figure 3-4 Average temperature and rainfall for the Lingmuteychu
watershed, Bhutan (from RNRRC, 2002) ................................... 89
Figure 3-5 Total annual rainfall in 2004 (source data from Hydrology
Section, 2005) ............................................................................ 91
Figure 3-6 Topography map of Bhutan ........................................................ 93
Figure 3-7 Examples of river gradients and physiographic profiles in
Bhutan (modified from Norbu et al., 2003).................................. 94
Figure 3-8 Location of river flow data collection stations (source data
from Hydrology Section, 2005) ................................................... 96
Figure 3-9 Flow comparisons among the hydrological monitoring
stations (source data from Hydrology Section, 2005). Letters
on x axis refer to the stations in Figure 3-8................................. 96
Figure 3-10 Water quality survey 2003 by NEC (source data provided by
NEC, 2005): (A) Calcium (B) Magnesium (C) Silicon Oxide
(D) Total hardness (Calcium Carbonate).................................. 101
Figure 3-11 Land use of Bhutan (from Karan, 1987) ................................... 102
Figure 3-12 Protected Areas of Bhutan (recreated from DOE, 2004) .......... 104
Figure 3-13 Map of Bhutan with location of industries, mines, sewage
treatment plants, dams, major towns, water sampling
stations, roads and rivers ......................................................... 107
Figure 3-14 River systems of Bhutan with location of large hydropower
development sites (includes existing developed sites and
future planned development to 2023) ....................................... 110
Figure 3-15 Proposed fish sampling sites and location of current and
proposed development ............................................................. 116
xi
CHAPTER 1
GENERAL INTRODUCTION
1
Overview
Bhutan is a small, pristine country with little industrial development, located
in the Himalayan Mountains. Bhutan started modernization in the 1960s with a
series of five-year plans focused on the sustainable use of the natural
resources. Watershed management will provide the foundation for development.
At the same time Bhutan is undertaking a number of large hydropower initiatives
that will impact most of the major river systems in the country. The lack of any
existing monitoring program or any data on existing fish populations have
increased concerns about the fishery resources. There is an increasing interest
in understanding the impacts of development on the river ecosystems, but it has
been difficult due to lack of scientific data available on the fish communities and
the rivers within Bhutan (Rajbanshi and Csavas, 1982).
There have been a few studies on Bhutan’s rivers that have been focused
on the establishment of aquaculture facilities along the southern foothills of
Bhutan near the Indian border. These studies documented 41 fish species in the
warmwater rivers and lakes (Dubey, 1978; Petr, 1999), but there have been no
studies conducted in the cooler water systems where most of the hydroelectric
development will take place. The development of a fish monitoring program for
rivers in Bhutan is further complicated by the lack of available personnel trained
to conduct such studies. There is also the added factor that few people will be
interested to pursue such studies if it involves sacrificing a large number of
1
fishes for research purposes. It is a sentiment among the Bhutanese population
to avoid unnecessary killing of animals.
The main objective of this thesis was to develop a framework for a fish
monitoring program that would be usable in Bhutan. The current scenario in
Bhutan means that the most suitable method would be adapting non-lethal
techniques for field research purposes. Such a program would require the
sacrifice of few, if any, fish to get the required data. Non-lethal techniques have
the added advantage of heeding to conservation principles, which Bhutan holds
very high in its development principles.
Initial field work was conducted on the Saint John River, New Brunswick,
Canada, to develop the techniques to be used for non-lethally assessing the
growth and health of fish populations. The Saint John River study focused on
assessing differences among populations of yellow perch (Perca flavescens)
from upstream and downstream sites near a series of hydroelectric dams along
the Saint John River. A comparison was conducted among a variety of methods
to examine the growth rates of fish, applicable to a monitoring program for the
rivers of Bhutan.
1.1
Bhutan: Background Information
Bhutan is bordered by China in the north and India in the south, east and
west. It has a total surface area of 46,500 km2, a population of 672,425 (OCC,
2005), and an annual growth rate of 2.5% (NSB, 2004). Agriculture is the main
occupation of Bhutanese people, with 69.1% of the population living in rural
2
agricultural areas and 30.9% in urban areas (OCC, 2005). The majority of the
population are followers of Mahayana Buddhism. Buddhism has influenced the
Bhutanese outlook in every aspect of life. Many Buddhist beliefs are proenvironmental in nature. This results in high compliance in implementing the
government’s policy towards environmental conservation.
Bhutan started on the path of modern development with phased five-year
plans, which have a major goal of developing the country through the
sustainable use of natural resources. The plans place particular importance on
the conservation of natural resources and preservation and promotion of cultural
heritage. The development goal of Bhutan has further been refined in the
concept of Gross National Happiness, conceptualised by His Majesty the King
of Bhutan.
In recent years, the government has given much impetus to achieving its
goal of Gross National Happiness. Three policy strategies were identified to
achieve this goal (DOP, 1999): a) the protection and conservation of the
environment through sustainable use of its renewable natural resources, b) the
preservation and promotion of its rich and unique cultural heritage, and c) the
promotion of good governance through efficiency, transparency and
accountability. The three strategies stand out as Bhutan’s pillars of existence
and as an example to the world at large. With these priorities, the government
has framed policies based on principles of the middle path to development
(NEC, 1998), wherein it strives to achieve maximum development without
compromising its natural resources and cultural heritage. These policies have
3
proved to be valuable in bringing Bhutan to the front line in terms of its richness
in biological diversity and cultural heritage and in its efforts for conservation of
these rich resources.
1.2
Need for an Aquatic Effects Framework for Bhutan
Bhutan has an abundant supply of water resources in most parts of the
country and they play an important role in development. Water has been used in
Bhutan for agriculture, drinking, domestic and industrial uses, and for generation
of hydroelectricity. Increased land use and development of industries,
construction and urban settlements, agriculture, forestry and mining results in a
growing number of adverse effects to the existing water bodies. The effects are
in the form of point and non-point sources of pollution, increasing sediment load
due to erosion, and inputs from mining sites.
The development of water resources to harness electricity contributes one of
the most significant impacts. These developments undermine the water quality
and cause impacts on the health of the ecosystem. These effects cannot be
(understood or mitigated if baseline data is not available) if early studies are not
initiated; in time the impacts could lead to degradation of the available water
quality. It is, therefore, necessary to develop proper study designs to assess the
health of these water bodies for management strategies.
Water quality assessments can be conducted in many ways. Some
assessments carried out in the past in Bhutan were based solely on measuring
physical characteristics and water chemistry. These assessments are not able
to detect stress present in the ecological systems and water quality criteria for
4
chemicals have not been defined for Bhutan’s rivers. Furthermore, there can be
ecological consequences of hydroelectric developments without dramatically
altering water chemistry (Greig et al., 1992).
The purpose of this document will be to develop guidelines for a framework
for future fish monitoring programs in Bhutan. Bhutan has stated that watershed
management is the single most important strategy to maintain the resource
base needed to support its national economy (Bhutan 2020 document; DOP,
1999). The use of fish has been a common choice for assessment of impacts
on water bodies in many research studies around the world and has been
shown to be effective in indicating the presence of stress in the system. The
current lack of any efficient methods for monitoring the water bodies and lack of
any database on existing fish populations makes a compelling argument to
begin studying the fishery resources in the country. As in most studies, it is
necessary to collect data that can correctly identify the health of the system and
that can be used in monitoring studies. Any fishery monitoring program will
operate out of the Ministry of Agriculture, but will require the cooperation of
various government departments associated with land use, hydrological
monitoring and industrial development.
1.3
Hydropower in Bhutan
The high gradient of the mountain river systems has endowed Bhutan with
enormous potential for hydropower development. Hydroelectricity is the cleanest
source of large-scale energy production in Bhutan and the power sector has
5
been the major revenue earner for the country since the commissioning of the
first hydropower project at Chukha (336 MW) in 1986. The development of
hydropower is guided by the Hydropower Development Master Plan (19902010) and aims to harness 20,000 MW of power by the end of the 10th Five
Year Plan (2012) and 25,000 MW of power by the end of the 11th Five Year
Plan (2017) (DOP, 1999). Currently, four mega hydro projects remain
commissioned: Chukha, Baso chhu Phase I, Kuri chhu and Baso chhu Phase 2,
with a total generation capacity of 460 MW (Table 1-1).
Though the current development represents only 1.5% of the estimated
30,000 MW potential (DOP, 2002), power generation remains the major
contributor to the country’s external revenue earnings. The soon to be
commissioned Tala Hydro Power Station (2006) has a generation capacity
(1020 MW) that exceeds the combined power output of the four previous mega
projects. It is expected to boost the country’s development with unprecedented
economic earnings and accelerate development projects in Bhutan.
The construction of power projects not only produces electricity for export,
but also enhances other avenues of development, and provides Bhutan with the
much needed cheap source of power for industrialization. The Kuri chhu power
station was constructed to allow the establishment of two other mega projects,
the Dungsam Cement Project in Nganglam and the Ferro Silicon Project in
Matanga. These projects are expected to consume 25 MW and 20 MW,
respectively, of the 60 MW generated. The remaining 15 MW will be distributed
for supply to the six eastern Dzongkhags (Districts) and will also supplement the
6
Table 1-1
Mega hydropower stations power generation
Hydro Power
Stations
7
*Chukha
*Baso chhu Phase I
*Baso chhu Phase
II
*Kuri chhu
Tala
Puna Tsang chhu
Mangde chhu
Puna Tsang chhu II
Chamkhar chhu
Chamkhar chhu
Kholong chhu
Amo chhu
Chukha II
Sunkosh
Multipurpose
Project
Digala
Shingkhar
Khoma chhu
Nika chhu
Rothpashong
Bunagu
Power
Output
(MW)
336
24
40
60
1020
1002
670
992
671
568
486
499
500
4060
670
570
326
210
401
180
River
Project State
Other details
Wang chhu
Baso chhu
Tailrace from Baso
chhu I + Ruri chhu
Kuri chhu
Wang chhu
Puna Tsang chhu
Mangde chhu
Puna Tsang chhu
Chamkhar chhu
Chamkhar chhu
Kholong chhu
Amo chhu
Wang chhu
Puna Tsang Chhu at
Sarbang
*Commissioned 1986
*Commissioned 2002
*Commissioned 2004
First Mega Hydro Project
Run-of-the-river
73,000 m3 water storage
*Commissioned 2002
Completion in 2006
**Planned Completion 2011
**Planned Completion 2013
**Planned completion 2015
**Planned Completion 2019
**Planned Completion 2022
**Planned Completion 2023
**Planned Feasibility Study 2010
15.7 million m3 water storage
Study completed
Proposed study during 9th Plan
Kuri chhu
Proposed study during 9th Plan
(* Currently Operational, ** Power System Master Plan –Bhutan 2003-2022)
4.9 million m3 water storage
1.1 million m3 water storage
5.2 million m3 water storage
1.8 million m3 water storage
1.6 million m3 water storage
1.4 million m3 water storage
2.4 million m3 water storage
Dam 1: power generation
Dam 2: 141 KM Irrigation
Canal
Shemgang
western power grid. In view of the value of the power projects, additional
projects have been identified as the main avenue for future development.
Furthermore, the potential for development of aquaculture at the dam sites is
currently being examined.
The development of hydropower proves beneficial to the South Asian region
as a whole. The current projects export almost 90% of the generated power to
India, thus reducing the immediate need for India to finance coal and nuclear
generating plants. This way it effectively checks the release of large amounts of
greenhouse gases, which might otherwise have resulted from such power
plants. The building of dams is further seen as an effective means of flood
control downstream of the dams and the Indian plains during the monsoons. It is
also anticipated that the development will lead to the development of irrigation
systems by using canals from the dams.
1.3.1 Impacts of Hydroelectric Dams
Hydroelectric dams can impact a river system in a number of ways. There
are two main types of hydroelectric facilities, the run-of-the-river station type and
the peaking station. The run-of-the-river station generates electricity by letting
water pass through turbines without blocking the flow of the river, so the river
continuum is maintained. The peaking station blocks the river and stores a large
amount of water above the dam to release water regularly to generate
electricity. The different types of operation impact river systems differently. The
peaking stations tend to have more impact than do the run-of-the-river stations
8
which have localised impact (Greig et al., 1992). Most dams in Bhutan are a
combination of both types.
The initial effects on river ecosystems would invariably be caused during the
construction of the dam. The effects during construction would include a large
amount of erosion and sedimentation due to the clearing of forests, the
movement of large amounts of earth and construction materials, the paving of
access roads, and the diversion of water flow for construction downstream
(Greig et al., 1992). A peaking station progressively starts flooding a large
amount of land upstream, changing the ecosystem from terrestrial to aquatic.
The flooding of land upriver with increasing depth causes associated changes in
thermal regime (Greig et al., 1992). In comparison, decreasing and fluctuating
water levels would be observed downstream with associated changes in thermal
regimes (Greig et al., 1992). The sediment-free water released from peaking
stations also causes higher erosion downstream, potentially resulting in
destruction of fish habitat (Greig et al., 1992). The sporadic release of water
from peaking stations also results in high mortality of fish eggs and younglings
downstream (Greig et al., 1992). The regulation of water flow also results in
more turbulence causing destruction of habitat and food sources downstream.
There have been specific cases where poor management and operational
strategies of dams have led to extinction of particular fish species from a river
system (Penczak et al., 1998). The existence of a dam on a river results in the
modification of the river’s physical, chemical and biological attributes (Duthie
and Ostrofsky, 1975; Kanehl and Lyons, 1997; Penczak et al., 1998;
9
Schmetterling and McEvoy, 2000; Gido et al., 2002; Greig et al., 1992) and this
causes wide changes in the response of fish and an overall change in
community structure of fish (Munkittrick et al., 2000; Jager et al., 2001; Gido et
al., 2002). The construction of dams breaks the continuity of the river and blocks
the migratory route of fishes to their spawning habitats (Penczack et al., 1998;
Schmetterling and McEvoy, 2000), and also affects the spawning sites
downstream due to their operations (Panczack et al., 1998; Hanna et al., 1999).
Fish blocked off from their spawning habitat by dams were reported to be
reabsorbing their eggs (Schmetterling and McEvoy, 2000), raising concerns
about the persistence of the species concerned.
In a peaking station the response to a dam can be seen in the fish
community changing from a river-based environment to an ecosystem that
resembles a lake (lacustrine) (Greig et al., 1992). The study of impacts of
hydroelectric dams is important in evaluating the extent of their effects on fishes,
other than those effects caused by discharge of effluents (Munkittrick et al.,
2000). There is a need to achieve greater understanding of the impacts of dams
on the river ecosystem to come up with proper mitigation measures (Efford,
1975; Schmetterling and McEvoy, 2000).
1.3.2 Other Potential Impacts on Rivers of Bhutan
Bhutan is a mountainous country with few flatlands available for settlement,
putting lots of pressure on the narrow river valleys for urban settlement and
agricultural farmlands. The population growth in these river valleys has led to
10
the loss of riparian zones for the adjacent water bodies. This trend is most
noticeable in Thimphu, the capital city of Bhutan, located at the headwaters of
Wang chhu (river). The location of industrial estates within the municipal
boundary further compounds the problem as the industrial runoff ends up in the
river along with non-point sources of pollution. The government does have
regulations which prohibit the input of industrial inputs into rivers and streams.
However, this regulation has seen little success in implementation due to
constraints in the number of personnel available for enforcement (NWFCC,
2001).
There are two large wastewater sewage treatment plants in Bhutan. The
treatment plant at Thimphu (population of 27,000) discharges its effluent into
Wang chhu and has a fecal coliform count of 1500FC/100ml (Charlton, 1997).
The other plant discharges into Amo chhu at Pheuntsholing (population of
12,000) and the effluent is calculated to contain 55FC/100ml (Charlton, 1997).
These are two visible point sources of effluent in Bhutan and with the
development of other townships there will be the development of more sewage
plants.
The establishment of large manufacturing industries, quarrying of stones and
sand, mining and construction has also added stress to the rivers through
various types of effluents. Although the effects of these point and non-point
sources of effluents on the biota of affected rivers have been studied and known
in many developed countries, effects have not been studied in Bhutan. It is vital
that studies be conducted to establish baseline data of changes that might be
11
stressing the river systems at this early stage of development. Specific
management plans to mitigate the causes of these effects can then be
implemented.
1.4
Design of Monitoring Studies
Although there have been concerns about the environmental consequences
of development for several decades, the assessment methodologies for
predicting, mitigating, and assessing impacts have varied considerably (SCS,
2000). There are three main strategies to assessing or monitoring
environmental impacts: stressor-based, values-based, and effects-based (Table
1-2). In a stressor-based monitoring program, the stressors (such as
sedimentation, thermal change or altered flow) are defined based on the
development and linked to probable impacts on identified Valued Ecosystem
Components (VEC) through the construction of theoretical stress-response
pathways (Dubé and Munkittrick, 2001). The probable impacts are evaluated
and used to identify potentially significant stressors to develop potential
mitigation measures. For a hydroelectric development, a stressor-based
assessment would focus (for example) on identifying the impacts of changes in
flow on spawning migrations of fish (Grieg et al., 1992).
This approach may prove to be successful in systems exposed to a single
stressor but proves difficult when examining a complex system with multiple
stressors (Munkittrick et al., 2000). Stressor-based monitoring fails to detect
12
effects of subtle stressors which might already be present in the system before
any development has taken place.
Table 1-2
A comparison of stressor-based, effects-based and values-based
approaches to environmental assessment (modified from Dubé
and Munkittrick, 2001)
Focus
Boundaries
Stressor
Stressor-response
pathways and
valued ecosystem
components
Related to
development
Use of existing data
Library searches
Follow-up
requirements
Traditionally very little
Advantages
Are often based on
previous
assessments and
experience
Ignores unidentified
interactions and
cumulative effects
Disadvantages
Question
How do I mitigate
potentially important
impacts?
Effects
Performance
indicators of
ecosystem status
Values
Ecosystem uses or
benefits
Related to
biological
components
Field studies
Related to human
uses
Ongoing monitoring
and adaptive
management
Site-specific focus
Time and expense
of baseline
monitoring
What are the
factors that are
limiting energy
flow?
Use and opinion
surveys
Opinion surveys
Focused on user
Not based on
ecosystem
properties or
responses
How do I protect
the uses that are
important?
A values-based assessment involves active participation of community
stakeholders in an assessment of the value of potential development, or of a
potential resource worth protecting. This approach is the main approach that
has been used to date in Bhutan. The value of the hydroelectric power
13
development has been the main focus, in terms of export potential, and in terms
of driving other potential developments. A values-based approach does not
usually focus on determining ecosystem-level impacts. Since the fishery value
in Bhutanese rivers is low, and the value of the electricity has been high, the
focus has been on the development of the hydroelectric potential.
In an effects-based monitoring program, the performance of the system is
identified as the unit for protection. In the absence of a hydroelectric
development, there are environmental constraints on the performance of the
system. The effects-based approach seeks to focus on the limiting factors, and
utilize them to drive the risk assessment process (Munkittrick et al., 2000; Dubé
and Munkittrick, 2001). There no current understanding of the health of Bhutan’s
rivers, or an adequate understanding of their ecology that can be used to drive
an effects-based assessment. The main advantage of an effects-based
approach, within the context of developing a monitoring program for Bhutan, is
that it allows an iterative development of baseline information on the ecology of
the system.
Several critical data gaps (Munkittrick et al., 2000) will challenge the
development of an effects-based approach in Bhutan, including an inadequate
understanding of the natural variability of performance indicators and concerns
about reference sites. A standardized and easy to apply assessment framework
is needed that will determine whether future development will adversely affect a
system (Dubé and Munkittrick, 2001). In Canada, the effects-based approach
has been used to develop the Environmental Effects Monitoring (EEM)
14
requirements for pulp and paper mills (Walker et al., 2002), metal mines (Ribey
et al., 2002) and sewage treatment outfalls (Kilgour et al., 2005). It is applicable
to situations with hydroelectric development (Munkittrick et al., 2000), and can
be adapted to help develop an assessment framework for Bhutan’s river
systems.
The sequential steps in the effects-based approach are to define the
geographical limitations of the study, develop the key performance indicators of
the system, develop the performance assessment, and identify the impaired
aspects, the limiting factors and the critical stressors (Munkittrick et al., 2000).
Effects-driven approaches will drive the collection of focused baseline data prior
to the construction of new facilities, and more widespread adoption of postdevelopment monitoring programs (Dubé and Munkittrick, 2001). The existence
of baseline data providing information on the growth, reproductive performance
and survival of organisms, and on stressors limiting the performance of the
system will make prediction and risk assessments more accurate.
1.4.1 Focus of Monitoring Studies
It is possible to define indicators at multiple levels of organization
(physiological, individual, population and community) and at multiple ecological
levels (bacterial, algal, invertebrate, fish, etc). The monitoring program of
interest to Bhutan is related to a fisheries assessment, so it is not necessary at
this time to deal further with other taxonomic levels. However, it is important to
15
remember that other levels of organization can provide valuable information
(Munkittrick et al., 2000).
As far as the level of organization is concerned, there are compromises
between measures with a rapid response time (physiological) and those with
ecological relevance (population, community); between responses that are easy
to reverse (physiological) and those that are difficult (community); and between
those that are easy to link to the cause of changes (physiological, chemical) and
those that are relevant to stakeholders (population) (Munkittrick et al., 2000).
The Canadian EEM program operates at the individual/population level as a
compromise to these trade-offs, and this is probably most relevant to the
situation in Bhutan. Physiological measurements will be difficult due to the
isolation of many field areas and equipment limitations. Community measures
will be difficult in large, high gradient rivers, especially when there is no baseline
of data against which to judge. The most promising approach is an iterative,
sentinel-species driven approach to develop the baseline data, focusing on the
individual/population level endpoints.
1.4.2 Non-lethal Sampling Methodology
Study designs for fish surveys have been evolving over the past few years,
and there has been increased emphasis on the use of small-bodied fish species
(Munkittrick et al., 2000). Fish resident in a system can be naturally stressed
before any additional changes, which result in additional stress, are made to the
system. This requires any assessment to take into consideration the initial
16
performance of fish populations in the system (Munkittrick et al., 2000).
Changes in performance of fish populations can be assessed by measuring
endpoints such as maturity, lifespan, age-specific mortality rates, recruitment,
growth rates and abundance (Ruemper, 1998). Endpoints which are critical to
assessing the impacts of stressors include estimates of age distributions and
indicators of energy use and energy storage (Munkittrick et al., 2000). Recent
attention has focused on developing non-lethal approaches for collecting these
types of data for environmental assessments (Gray et al., 2002, Environment
Canada, 2005b). These kinds of data will be critical for developing baseline data
on fish populations in Bhutan’s river systems. As opposed to large lethal
sampling applied in traditional assessment methods (Munkittrick et al., 2000),
the application of non-lethal assessment of populations (as in Gray et al., 2002;
Environment Canada, 2005b) can be seen as a better alternative in light of its
adherence to Bhutan’s conservation principles and cultural sensitivity to lethal
sampling.
The most important endpoints are those reflecting information on growth,
reproduction, energy storage and survival (Environment Canada, 2005a) (Table
1-3). Non-lethal information on condition and length frequencies are relatively
straightforward, and are a function of the number of individuals sampled.
Reproductive information, in terms of non-lethal data, will be dependent on the
collection method and timing, and will vary with the species being examined. In
many cases, these methods will need to be developed site-specifically once
more information is available on the life history of Bhutanese fishes. Once this
17
information has been developed, a standardized approach to estimate
abundance or density will be possible. The initial information needed to
evaluate species suitability will be related to relative abundance, life history and
longevity. Obviously, there will be significant differences in sampling programs
to evaluate fish that live for a single year, for three years, or for several
decades.
The initial information that needs to be developed is associated with relative
abundance, distribution, age distributions, and growth rates of fishes in the
rivers of Bhutan. Comparing the distributions of ages of fish in a population can
be conducted through direct measurement of the ages of fish by enumerating
growth zones in calcified tissues, or indirectly by assessing size-frequency plots
(Gray et al., 2002). The most commonly used method is the analysis of the
growth zones found in otoliths (inner ear bones), external scales, fin rays,
vertebrae, or cheek bones such as the cleithrum or operculum (Bagenal and
Tesch, 1978). With the exception of fin rays and scales, the removal of aging
structures is lethal.
Scales can be read relatively accurately during the early years in most
species, however, reliability diminishes near maturity in the majority of species
(Beamish and McFarlane, 1987). The accuracy of aging based on these
structures depends on a variety of factors including the presence of distinct
growth seasons (as experienced by most northern and temperate species),
proper storage and preparation of tissues and structures, and validation of the
particular method. In most species, internal bony tissues are the most accurate
18
aging tissue, though methods can be age- and species-specific (Beamish and
McFarlane, 1987).
Table 1-3
Endpoints relevant for non-lethal evaluation of fish performance in
an effects-based approach (modified from Environment Canada,
2005b).
Endpoint
Growth
Reproduction
Condition
Survival
Non-destructive
Size (length and weight) of young-of year (Age 0)
at end of growth period
Size of 1+ fish
Size at age (if possible)
Relative abundance of young-of-the year (%
composition of young of year)
Young-of-year survival
Body weight relative to length (k)x
Length:frequency distribution
Age frequency distribution (if possible)
Growth can be measured through a variety of methods, including size
distributions and incremental analysis, size-at-age, tracking of a cohort over
time, biochemical methods, and back-calculation. The focus of this study is to
evaluate methodologies for back-calculating growth, within the context of
developing a fisheries monitoring program for rivers in Bhutan.
1.4.3 Back-calculating growth
Back-calculation of fish growth with the use of scales or bony structures is
seen to have wide potential in its application to ecological studies. Fish scales
19
give important information regarding fish size at different ages by backcalculation (Johal et al., 2001). In general, the annuli on an aging structurse are
marked, and the distances between annuli are proportional indicators of the
relative growth of a fish during different periods of its life history.
Horppila et al. (1999) examined three hypotheses regarding back-calculation
of fish growth. They concluded that the body proportional hypothesis gives the
most reliable estimate for back-calculated age for roach as compared with the
scale proportional hypothesis and the Fraser-Lee method. It is anticipated that
the use of any method, if used consistently to back-calculate age, will not affect
the results (i.e., detection of differences in performance of fish between
reference and exposed sites).
Major variations in environmental conditions influence the formation of annuli
on scales of fish and consequently scales are shown to be accurate in
predicting life history characteristics (Fabré et al., 1998; Machias et al., 1998).
Information on growth rates obtained can be used to detect differences between
upstream and downstream sites of dams.
1.5
Statement of Problem
The lack of any information regarding the extent of stress on a river system
undermines understanding the impacts of continued development on the health
of the river ecosystem. The recognition of the carrying capacity due to existing
natural stressors of a river system is important in assessing the extent of stress
that can be incurred due to development activities (Munkittrick et al., 2000).
20
Information that can help establish the amount of development that can take
place without significantly degrading the river system can support good
management strategies for the river system.
Information on the health and growth of existing populations of fish in a
system can yield important information regarding carrying capacity of the
system. Since no background information on fish exists for rivers of Bhutan
regarding the carrying capacity of its rivers, it is important to begin such studies
before more development takes place. Immediate attention must be given to
gathering information regarding existing fish populations. The present study on
the Saint John River is to specifically design a non-lethal sampling protocol
suitable to the Bhutanese scenario in order to develop information for a fisheries
assessment.
1.6
Objectives and Outline of Thesis
The primary objective of the thesis is to develop a framework for a fish
monitoring program for Bhutan that can be used to evaluate potential impacts of
hydroelectric development on Bhutan’s river systems. This objective will be
developed by determining a protocol for back-calculating fish growth rates using
fishes of the Saint John River that can be applied to help manage Bhutan’s
fisheries and maintain river quality.
The specific objectives are:
21
1. Define the factors that need to be considered in developing a speciesspecific growth profile, and develop a sampling strategy for yellow
perch (Perca flavescens) in the Saint John River.
2. Determine the performance of fish upstream and downstream of dams
along the Saint John River system.
3. Develop a protocol that could be transferred to monitor the status of
fish populations in Bhutan (based on Munkittrick et al., 2000).
The thesis is arranged into three chapters. After this introductory chapter,
Chapter 2 describes the development of the data, and evaluation of growth of
yellow perch in the Saint John River, Chapter 3 examines the relevant data
available for Bhutan, and describes a framework for initiating a fisheries
assessment project for Bhutan’s rivers. A final discussion makes some
recommendations about the best path forward.
22
CHAPTER 2
BACK-CALCULATIONS OF GROWTH OF YELLOW PERCH ALONG THE
SAINT JOHN RIVER
2
Introduction
There is a need to evaluate different methodologies for non-lethally
determining growth in fish to focus the monitoring program and framework for
Bhutan. Therefore, evaluation was undertaken using fish collected from the
Saint John River, New Brunswick, Canada, along a continuum of development
that includes a series of hydroelectric dams. As mentioned in earlier chapters, it
is expected that hydroelectric dams will influence fish distributions, abundance
and performance. The growth of fish is an output related to factors including the
availability, quality and quantity of food, and can be influenced by other energy
outputs, including reproductive development and movement (Munkittrick et al.,
2000).
There are a number of ways to examine size of fish that will be important to
evaluate for a non-lethal sampling program: the size of fish captured, the size-at
age, the length-frequency and age-frequency distributions, Ford-Walford plots to
estimate maximum length, back-calculations of the rates of fish growth, and the
average back-calculated size of fish at a pre-determined age. Each of these will
be examined to determine the differences in information that can be obtained
and to evaluate the relative strengths and weaknesses of different approaches.
This is important for understanding the relative strengths of information that will
23
be obtained through a non-lethal sampling program. The focus of this part of
the thesis is to describe a protocol which will minimize variability while
increasing the power by using back-calculation methods for assessment.
2.1
The Saint John River, New Brunswick
The Saint John River is a 7th order river (river order reflects the relative size
and complexity of a river basin) and runs a length of 700 km from its head
waters to the Bay of Fundy and has a mean annual discharge of 1110 m3/s
(Curry and Munkittrick, 2005; Munkittrick et al., 2005). It has a vertical descent
of 481 m from head waters to the mouth at the Bay of Fundy (Munkittrick et al.,
2005). The Saint John River Basin covers 55,000 km2 (Curry and Munkittrick,
2005; Munkittrick et al., 2005). It runs approximately 50 km through Northern
Maine in the United States and then flows through the province of Quebec and
New Brunswick in Canada to drain into the Bay of Fundy at Reversing Falls,
Saint John (Munkittrick et al., 2005).
It is a highly impacted river with numerous stressors along major part of its
length (Table 2-1) (Curry and Munkittrick, 2005). The Saint John River is
impacted due to effluents from pulp mills, wastewater sewage treatment plants,
and other industrial discharges. These effluents were shown to have adverse
effects on fish populations in other river systems (Munkittrick et al., 2000). Many
studies have been either completed or undertaken recently to understand the
river’s assimilative capacity (capacity to absorb wastes) in view of the
developments taking place. By understanding the extent to which the river can
24
Table 2-1
Fish community study sites, their characteristics and human impacts (from Curry & Munkittrick 2005)
Location
(km upstream)
>475 – 625
Elevation
(m a.s.l.)
338
Sewage, poultry processing
447
295
Main stem
Pulp mill, paper mill, sewage treatment plants, piggeries
420
136
Grand Falls
Main stem
(reservoir)
Potato agriculture, potato processing
Hydroelectric dam, no
fish passage
360
135
Tobique
Tribut ary
(reservoir)
Forestry
Hydroelectric dam,
with fish passage
325
100
Aroostook
Main stem
Potato farming and processing, sewage treatment
facilities, de -commissioned air force base.
Hydroelectric dam no
fish passage
329
80
Florenceville
Main stem
Two food processing plants, potato farming, and sewage
treatment facilities
Hydroelectric dam
275
55
Hartland
Main stem
Presque Isle tributary has starch production industries
and potato production fields
255
50
Woodstock
Main stem
Large municipal sewage tre atment facility, intense potato
production, Meduxnekeag River drains urban and potato
production
233
48
Nackawic
Main stem
(reservoir)
Pulp mill
185
45
Fredericton
Main stem
135
9
Site
Priestly,
Moody Bridge
Baker Brook
Type
Main stem
Stressors
Forestry, recreation
Main stem
Edmundston
25
*m. a. s. l. – meters above sea level
Comments
The head of the
flooded reservoir
created by the
Mactaquac
Hydroelectric Dam
Downstream of the
Mactaquac Dam, no
fish passage
withstand development (assimilative capacity), we can maintain its water quality
and protect the aquatic ecosystem (Munkittrick et al., 2005).
2.1.1 Recent Studies - Saint John River
There have been a variety of recent studies taking place on the Saint John
River, including the upper (Culp et al., 2003; Galloway et al., 2003; Flanagan
2003; Gray et al., 2005; Curry and Munkittrick, 2005) and middle basins
(Doherty et al., 2004; Luiker et al., 2004, 2005), and at the river mouth (Dubé
and MacLatchy, 2000, 2001; Vallis et al., 2006; Vallieres et al., 2006). There
are concerns about the continuing impacts of nutrients from industry and
municipal outfalls, and the impacts of agriculture and food processing plants in
the upper basin, although the situation is improving (Cunjak and Newbury,
2004).
Studies on the Saint John River included the investigation of effects of pulp
and paper mill effluents (Galloway et al., 2003), agricultural inputs (Gray et al.,
2002), and sewage effluents (Doherty et al., 2004) on fish communities. The
studies involved use of both lethal (Doherty et al., 2004; Galloway et al., 2003)
and non-lethal (Gray et al., 2002) techniques to access the effects of effluents
on fish populations (Munkittrick et al., 2005) and communities (Curry and
Munkittrick, 2005). There are a variety of changes in the fish community in the
middle reaches of the river associated with the presence of large hydroelectric
dams (Curry and Munkittrick, 2005). These dams offer no fish passage
upstream.
26
Curry and Munkittrick (2005) compared the fish community at 12 sites across
300 km of the upper basin, and found that relatively few fish species were
sufficiently widespread; only 3/21 species were found at 10 or more sites along
the river – white sucker (Catostomus commersoni), common shiner (Luxilus
cornutus) and yellow perch (Perca flavescens).
Galloway et al. (2003, 2004) evaluated the performance of fish in the
Edmundston reach of the river, sampling fish from the Canadian border
downstream to Riviere Vert (approximately 40 km upstream of Grand Falls)
(Figure 2-1). Several fish species were used in this part of the river, including
white sucker, yellow perch, slimy sculpin (Cottus cognatus) and blacknose dace
(Rhinichthys atratulus). The study focused on the potential impacts near
Edmundston, where there is a pulp mill, a paper mill, multiple sewage outfalls
and inputs from farming and a food processing plant. Additional studies
examine the relative inputs of the sewage and pulp mill effluents on
invertebrates (Culp et al., 2003), and potential responses of fathead minnow
(Pimephales promelas) to concentrations of effluent higher than those found in
the river.
Among the field studies using fish, white sucker were not found to be
sensitive to point source shoreline discharges in this section of the river,
probably because water column mixing is relatively poor and they stay towards
the middle of the river. This species has been widely used in other studies on
other rivers (Munkittrick et al., 2002). Slimy sculpin have been shown to have a
27
aw
re n
ce
Ri
ve
r
N
Edmundston
Tobique River
St.
L
Baker
Brook
Grand Falls
EB
EC
Aroostook
Caribou
Q
U
Priestly
Moody
Bridge
Aroostook
Dam
Tobique
Presque
Isle
Aroostook
River
Beechwood Dam
Florenceville
Hartland
Nackawic
MAINE
SAINT JOHN RIVER
DRAINAGE BASIN
Dam
Figure 2-1
Fredericton
Woodstock
Mactaquac
Dam
Watershed boundary
Sample site
Large Urban
NEW BRUNSWICK
Saint
John
100 km
BAY
Bay
of of
FUNDY
Fundy
Map of the Saint John River basin (from Curry and Munkittrick
2005)
very small home range (Gray et al., 2002; Cunjak et al., 2005) and respond
strongly to effluent inputs (Galloway et al., 2003, 2004). However, this species
was only found in large numbers in the upper river basin (above Grand Falls;
Curry and Munkittrick, 2005) and in tributaries (Gray et al., 2005). The yellow
perch did show some responses (Galloway et al., 2004) and has previously
28
been used as an indicator species in this part of the river (BAR, 1996) and
elsewhere (McMaster et al., 2002).
Further downstream, Doherty et al. (2005) evaluated white sucker in the
vicinity of Florenceville and Woodstock. This study was initiated because the
fish community surveys (Curry and Munkittrick, 2005) had identified lesions on
white sucker in the upper portion of this reach of the river. Radiotracking of the
white sucker showed that outside of the spawning season, the home range was
relatively small for this species in this part of the river (Doherty et al., submitted).
The fish showed the largest size and condition near the upstream part of this
reach at Florenceville (Doherty et al., 2005). This area is immediately
downstream of the Beechwood hydroelectric dam. Daily water level fluctuations
resulting from upstream dam discharge may change habitat availability and/or
diversity, thereby altering the fish community (Doherty et al., 2005). The area is
also adjacent to a large potato processing plant that has been associated with
significant nutrient inputs to the river (Luiker et al., 2004, 2005).
Freedman (2005) evaluated the fish community in the Nackawic reach of the
river to determine mobility and potential suitability of species as sentinels over
small distances. His study was associated with the pulp mill and sewage
discharges of the town of Nackawic, and his analyses of stable isotopes of
carbon and nitrogen suggested that yellow perch showed high home-range
fidelity. He also showed that significant differences in body size and organ sizes
could be seen over a small range (<1 km) (Freedman, 2005), as had been
previously reported with yellow perch in the Ottawa River (McMaster et al.,
29
2002). While the abundance of yellow perch did not appear to be affected by
pulp mill effluent near Nackawic, changes in their trophic positions and carbon
sources suggest there is an impact (Freedman, 2005). The utility of the species
does depend on sampling seasons, and similar to white sucker (Doherty et al.,
2005), yellow perch do show more mobility at spawning times.
Except for the upper 200 km of the river basin, yellow perch are widely
distributed all along the length of the Saint John River, (Curry and Munkittrick,
2005). This, as well as their high site fidelity, and the relative ease of aging of
their scales, makes them a good species to select to examine the size
distributions and growth rates to evaluate non-lethal sampling methods to
examine the impacts of hydroelectric dams on fish performance in the Saint
John River.
2.1.2 Hydroelectric dams on the Saint John River (history and location)
Hydroelectric facilities continue to impose significant obstacles to upstream
passage and no opportunity for safe downstream passage. Much of the earlier
knowledge about the health of the Saint John River ecosystem came from
assessments of the dramatic decline in populations of Atlantic salmon (Salmo
salar) that have occurred over the past 50 years (Cunjak and Newbury, 2004).
Their declining numbers, from tens of thousands to a few thousand in recent
years, are strongly correlated with the construction of dams, particularly the
farthest downstream dam which allows no free passage of fishes. A major
study of the biology and socioeconomics of the river occurred in the late 1960s
30
and early 1970s (Meth, 1972). High summer water temperatures, especially in
the impoundments, stress the fish and restrict growth for many species. Altered
flow regimes may affect in-river movements and the abundance of non-native
piscivorous species (e.g., smallmouth bass (Micropterus dolomieu), chain
pickerel (Esox niger), muskellunge (Esox masquinongy)), provides additional
constraints to juvenile salmon production in the river (Cunjak and Newbury,
2004).
There are in total 11 dams in existence on the river system (Cunjak and
Newbury, 2004; Munkittrick et al. 2006). The current study involves the
investigation of effects of five major dams located on the mainstem (Grand
Falls, Beechwood and Mactaquac) or on major tributaries near the mainstem
(Tobique, Aroostook).
The Grand Falls hydroelectric facility (66 MW) is the first facility as you go
down river from the head waters. It is located at a 23 m natural barrier, and was
first operated in 1928-1931. The next two major hydroelectric dams on the river
are located on major tributaries. The Tinker dam is located on the Aroostook
River, just upstream of the US-Canada border. The 34 MW station is described
as a run-of-the-river facility with five generators that began operation at various
times between 1925 and 1965 (WPS Power Development, 2000). Although it is
constructed as a run-of-the-river facility, there are large variations in
downstream flow in the Aroostook River (unpubl. observations). The Aroostook
River enters the Saint John about 30 km below Grand Falls, and about 4 km
upstream of the Tobique River.
31
The Tobique Narrows Dam (20 MW) was built in 1953 on the Tobique River
near the confluence of the main Saint John River about 35 km upriver from
Beechwood Dam and 39 km downstream of Grand Falls. The Beechwood Dam
(113 MW), built in 1957, has a head of 17 m and is located 130 km upriver of
Mactaquac Dam. It has a fish collection gallery and a mechanical skip-hoist
which lifts fish over the dam into the headpond.
Mactaquac dam, built in 1967, has a head of up to 35 m. Fish passage is
provided through a fish collection facility situated in the base of the dam, which
is comprised of a collection gallery, holding pool, crowder and hopper. The
hopper lifts upstream migrants into tank trucks for upriver distribution. All adult
salmon captured in the migration channel at the Mactaquac Main Salmon
Hatchery are sorted for broodstock and for transportation upriver where they are
released for natural spawning and angling. The Mactaquac reservoir is 100 km
in length and covers an area of approximately 87 km2. It is operated as a
peaking station with a daily cycle throughout the entire year (low discharge
overnight and high during the day). Both the Beechwood and Mactaquac
facilities have limited and selective active fish passage (only Atlantic salmon and
alewife (Alosa pseudoharengus involving upstream transport by truck, and act
as barriers to upstream movement for other fishes.
2.1.3 Objective of this Chapter
The objective of this chapter is to develop a protocol for back-calculating fish
growth rates in the Saint John River in the vicinity of five hydroelectric dams that
32
can be applied to help manage Bhutan’s fisheries and maintain river quality. The
specific hypothesis tested is that there are no differences in the growth
performance of yellow perch at various sites along the Saint John River.
The specific objectives are listed below:
1. Define the factors that need to be considered in developing a speciesspecific growth profile, and develop a sampling strategy for yellow
perch in the Saint John River.
2. Determine the performance of fish upstream and downstream of dams
along the Saint John River system.
3. The second part of this chapter will test the hypothesis that similar
information about the effects of dams on life history characteristics of
fish can be obtained using non-lethal and lethal sampling techniques
2.2
Materials and Methods
Yellow perch were collected and measured from 10 sites in the upper Saint
John River near the hydroelectric dams to examine their growth and condition.
2.2.1 Study Area – the upper Saint John River
In the headwater reaches (>km 400), where river width and depth average
50 m and 2 m, respectively, summer and winter low discharge averages 135
m3/s. At Fredericton (135 km), low water discharge averages 250 m3/s
(average width = 750 m and depth = 3 m) (Curry and Munkittrick, 2005).
33
Yellow perch were collected using a standardized protocol of gillnetting and
electrofishing at 10 sites by Curry and Munkittrick (2005) during late July and
August, 2000 and 2001 (Table 2-1). Additional detailed samples were collected
at St. Hilaire and Edmundston by angling during the summer of 2002 (Galloway
et al., 2004) and by Tenzin in the summer of 2004 by angling. Further detailed
sampling was undertaken by angling in the Mactaquac headpond (Tenzin in
summer of 2004) and by Freedman (2005) by electrofishing near Nackawic.
The main study sites along the main stem (Table 2-1) spanned a variety of
human-impacted reaches, and included areas with reservoirs, forestry
operations, dam/flow regulation, potato farming, pulp mills, paper mill, urban
sewage treatment discharge, food processing, and pig/poultry production. The
sites at Florenceville, Hartland, and Fredericton experience substantial
fluctuations in water levels owing to the hydroelectric facilities. There is no fish
passage at the Mactaquac Dam and thus it is the upstream limit for at least 10
anadromous species of fishes (Curry and Munkittrick, 2005).
Existing samples for aging and comparison exist from previous studies
conducted at a number of sites on the river. These include
a)
St. Hilaire – the furthest site upstream with significant perch populations.
Although there are some sewage and food processing effluents upstream,
the inputs are relatively minor. The upper 200 km of the basin lies within
the Maine Northwoods – an industrial forest area where there are few
people or inputs outside of forestry operations.
34
b)
Edmundston – this area of the river receives significant input of sewage
from an area including approximately 20,000 people. Inputs also include
a large pulp mill, a paper mill, and some local agricultural activity. Both
the pulp mill and the paper mill have secondary waste treatment facilities.
The town sewage input includes both treated and untreated sewage.
c)
Grand Falls – in addition to a natural 23 m waterfall that is now blocked by
a hydroelectric facility, the Grand Falls area (population approximately
6000) is the start of the potato growing area of New Brunswick, and the
site of a large potato processing plant than employs more than 250
people.
d)
Aroostook – this area has fewer than 500 people, but is the site of a
hydroelectric facility on the Aroostook River at the US-Canada border.
Upstream of the dam, there are historical issues with agricultural activities
and PCB contamination from a closed US air force base.
e)
Tobique – The Tobique area is home to about 2500 people, and the
Tobique River drains an area of active forestry. The tributary is blocked
by a hydroelectric facility near its confluence with the Saint John River.
f)
Florenceville – is located a few km below a large hydroelectric facility that
blocks the Saint John River. It is home to <1000 people, but is the site of
a very large potato processing facility that is a major contributor of
nutrients to the Saint John River (Luiker et al., 2004, 2005). The river
fluctuates approximately 2 m several times a day, as the peaking
hydroelectric facility alters flow with the hydroelectric demand. The food
35
processing plant produces primarily frozen french fries and has been in
operation since 1957. The processing plant built a tertiary treatment plant
involving an aerobic digester in 1996 (Jacques Whitford Environment
Limited, 1996).
g)
Hartland – is a town of <1000 people located 20 km downstream of
Florenceville. The Presque Isle tributary to the river drains agricultural
and food processing activities.
h)
Woodstock – is a town of over 5000 people located near the southern end
of the potato growing belt for New Brunswick. Treated sewage is
released into the Saint John River, and the Meduxneakeag River also
drains some potato growing areas.
i)
Nackawic – is the site of a large pulp mill that was closed for parts of 2004
and 2005. The city’s population is approximately 1000 people at the
upper end of the Mactaquac headpond. The headpond was not cleared
at the time of the construction of the dam, and the deeper water areas
near Nackawic have some issues with hypoxia during the summer.
j)
Fredericton – is the lowermost site sampled as part of this project. It is 20
km below Mactaquac dam, has a population of about 80,000 people, and
the main discharges to the river are related to secondary-treated sewage
inputs.
2.2.2 Sample Collection
To evaluate the performance of sampled fish upstream and downstream of
dams, the fish collected were examined for external lesions, and sex was
36
determined. Scales were collected for aging. Fish were measured for weight (±
0.1 g) and fork length (±0.1 cm), and lateral scales were collected, dried in
paper envelopes, and examined for the measurement of annuli. Scale samples
were collected for aging. More than 350 perch were collected from 10 sites on
the Saint John River, from Saint Hilaire to Fredericton. All fish were aged, but
some fish were removed from the data set for back-calculating growth. In total,
318 fish were retained for back-calculations.
Fish were removed in some cases because the Ford-Walford plots (see
below) suggested that the fit of the data with the ages was not consistent, and
the differences were not easily resolved. In other cases, some data were
missing from individual fish and these were removed. Most fish that were
removed (>60%) were from Nackawic and other sites had few fish that were
confusing.
2.2.2.1 Scale Cleaning and Mounting
Scales were removed from the scale envelopes and soaked in distilled water
in a Petri dish. With aid of a binocular microscope, five scales were selected and
initially cleaned with forceps. Care was taken not to subject the scales to
corrosive pressure to preserve the rings. In the later stages, forceps were used
only to hold the scales and paint brushes with clipped tips were used to scrape
dirt off the scales. The paint brushes performed comparatively better at cleaning
without damaging the rings on the scales. The scales were then rinsed again
and put on paper towels for drying. Five dry scales were mounted between two
microscope slides with the ends secured together by paper tape. All the scales
37
were mounted with the curved side facing up and with the same alignment. The
sample identity was written with markers on the paper tapes, which also helped
in identifying which side faced up.
2.2.2.2 Scale Digitization
Scales were digitized with the use of an Olympus BX40 (UNB ID 05927)
microscope equipped with Sony Ex Wave HAD digital color video camera,
Model No. SSC-DC54A (Serial No. 101266). Media Cybernetics Optimas 6 (S/N
30N65000-11391) imaging software was used to capture images to the
computer. The images were captured at 2X and 4X magnification and all the
images were saved according to their site and the magnification at which the
images were captured. The imaging software was calibrated with the aid of an
image micrometer taken at 2X and 4X magnifications. This allowed for two
configurations to be loaded to measure the scale images, which were also
captured under 2X and 4X magnifications.
From the five scales mounted on each slide, only the best one was used to
capture images. The use of five scales during mounting also allowed rejection of
regenerated scales observed at higher magnification without diminishing the
actual number of samples.
2.2.3 Age Reading
Age determination using scales formed the most important aspect of this
thesis. Jearld (1983) indicates errors in age determination include missing the
first annulus, the crowding of rings and reabsorption in old scales, and over-
38
estimation of age due to anomalous rings. A detailed list of criteria was
developed by Jearld (1983) to correctly identify fish ages. Refinement of the
criteria over iterative readings reduced variability among consecutive readings.
The scales of yellow perch show distinct growth rings due to a higher rate of
growth in the warmer months and slow growth during the winter. The differences
in rate of growth are reflected in the formation of rings on the scales with
summer growth rings spaced widely apart and the winter growth rings
concentrated closely together, resulting in distinct formation of alternating light
and dark bands when observed under the microscope (Figure 2-2 and Figure
2-3).
The edge of the dark band shows the end of winter season for that growth
year and each dark band was counted as an annulus. The absence of distinct
focus was treated as regenerated scales and these regenerated scales were
filtered out from the samples. The centers of regenerated scales tend to be
without any distinct circuli and are clear. New growth rings crossing over or
cutting winter growth rings were determined to be the start of new summer
growth. Many false rings or anomalous rings could be eliminated using such
observations in the ring formation, preventing overestimation of age.
39
Radial Line
2nd Annulus
Cutting over
(new growth)
No Cutting over
1st Annulus
Cutting over
(new growth)
Origin
Figure 2-2
Two year old fish (file: Edm_DS_F_2Yr_864)
2nd Annulus
1st Annulus
Figure 2-3
Two year old fish scale sample (file: Aroostook_023)
40
2.2.3.1 Ford- Walford plots
The ages were examined by plotting size at age of one year L(t+1) against
size at age of the previous year ( Lt) (with the t values pertaining to constant
time intervals, e.g., a year). Two values derived from this exponential function
are important in characterising growth in fish populations: maximum possible
size (L∞) and rate of growth to maximum possible size (K). Ford-Walford plots
are typically used to derive L∞ and K.
2.2.3.2 Back-Calculation
Back-calculation was used to estimate fish length at the time of each
annulus formation. It used the relative distance between annuli to approximate
the growth of the fish over time by an assumed relationship between the current
size of the structure and the current overall size of the fish. It requires that the
growth of the aging structure be compared to a consistent landmark and to the
size of the fish. The successive measurements on the same fish are not
independent and the number of animals represents the replication, not the
measurements.
2.3
Results
More than 350 perch were collected from 10 sites on the Saint John River,
from Saint Hilaire to Fredericton. The largest perch were captured at the two
most upstream sites (St. Hilaire and Edmundston), and were smallest at the
Tobique site (Table 2-2). Among sites, there was no significant relationship
41
between weight of fish and average age (r2=0.02), and the Tobique and
Nackawic fish were among the oldest and smallest fish. Condition factor also
varied significantly between sites, and Nackawic and Tobique also had the
skinniest fish (Table 2-2).
2.3.1 Raw Fish Data
Scales were examined from 355 fish. All fish were aged, but some fish were
removed from the data set for back-calculating growth. In total, 318 fish were
retained for back-calculations. Fish were removed in some cases because the
Ford-Walford plots suggested that the fit of the data with the ages was not
consistent, and the differences were not easily resolved. In other cases, some
data were missing from individual. Most fish that were removed (>60%) were
from Nackawic and other sites had few fish that were confusing; Nackawic fish
were the oldest and thinnest fish suggesting some stress was present. The fish
retained for analysis were significantly shorter (p=0.009), lighter (p=0.008), and
older (p<0.001) than the entire data set for Nackawic, but there was no
difference in condition factor (p=0.38).
Five scales per fish were cleaned and mounted on slides for digitizing.
During digitization the scale which showed the best detail under the microscope
was used to capture the image, resulting in 354 images. Thirty-one scales were
not used due to difficulty in aging caused either by fish being too old or the
scales being very unclear. Eleven scale images were not used due to them
being from regenerated scales. In the second round of measurement, five
42
additional scales were used which were not used in the first round of
measurement. Data were collected and analysed for only 307 scale samples in
the first part of measurement and 312 scale samples were used in the second
part resulting in 80% to 88% useable samples from the total collected. Over
44% of the bad scales turned out to be from Nackawic. Hartland and
Fredericton each accounted for 16% of the bad scales; 26% of the bad scales
were regenerated, of which 82% turned out to be from Nackawic samples. The
rest of the bad scales were either too old or were very unclear samples. The
site differences in size of perch were consistent with the reduced data set (Table
2-3).
Perch collected from St. Hilaire were observed with the highest growth in
length and weight and condition (Table 2-3). The lowest growth in length and
weight was observed in perch collected from Tobique, and the lowest condition
was observed in perch collected from Nackawic. The results for mean age
changed here as compared to the ones reported in Table 2-2 because of the
removal of fish. The highest and lowest mean age were reported from
Florenceville and Woodstock, respectively (Table 2-3).
43
Table 2-2
44
Site*
SHIL
EDMN
GRFA
ARST
TOBQ
FLOR
HART
WOOD
NACK
FRED
A A
Summary statistics for all perch captured. Data sharing an alphabetical letter are not statistically
different (within a column)
Length (cm)
20.7 ± 0.8 (25) abcde
20.4 ± 0.4 (101) abd
15.2 ± 0.9 (18) defgh
17.6 ± 0.7 (26) acdefg
13.5 ± 0.8 (15) efgh
17.3 ± 1.7 (11) acdefgh
17.7 ± 0.6 (25) abcdefg
15.7 ± 0.7 (22) cdefgh
18.0 ± 0.4 (68) acdef
18.3 ± 0.4 (44) abcde
highest value
Weight (g)
146.4 ± 15.7 (25) bcdg
135.7 ± 8.2 (101) bcdg
59.6 ± 12.6 (18) acefh
85.5 ± 12.1 (26) acdef
32.6 ± 7.1 (15) eh
101.3 ± 26.0 (10) abcdefg
81.8 ± 7.9 (25) acdef
57.6 ± 8.0 (22) acefh
67.9 ± 4.7 (68) acef
103.4 ± 10.1 (38) abcdg
Age (years)
4.4 ± 0.3 (25) abce
5.2 ± 0.2 (101) abe
2.8 ± 0.4 (18) ace
3.8 ± 0.3 (26) abce
4.9 ± 0.5 (15) abcde
3.8 ± 0.7 (11) abce
4.2 ± 0.3 (25) abce
3.5 ± 0.3 (22) ace
6.3 ± 0.3 (68) de
4.4 ± 0.3 (42) abce
Condition
1.52 ± 0.03 (25) ab
1.44 ± 0.02 (101) ab
1.39 ± 0.04 (18) abd
1.39 ± 0.04 (26) abd
1.18 ± 0.04 (15) acd
1.33 ± 0.05 (10) abd
1.39 ± 0.04 (25) abd
1.34 ± 0.03 (22) abd
1.08 ± 0.03 (68) cd
1.49 ± 0.06 (38) ab
AAAA lowest value
*SHIL = St. Hilaire, EDMN = Edmundston, GRFA = Grand Falls, ARST = Aroostook, TOBQ = Tobique
FLOR = Florenceville, HART = Hartland, WOOD = Woodstock, NACK = Nackawic, FRED = Fredericton
Table 2-3
45
Site
SHIL
EDMN
GRFA
ARST
TOBQ
FLOR
HART
WOOD
NACK
FRED
AAA
Length and weight data for perch used in back-calculation of length and weight respectively
Length (cm)
21.0 ± 0.7 (23)
20.2 ± 0.4 (98)
15.2 ± 0.9 (18)
17.3 ± 0.7 (25)
12.8 ± 0.5 (14)
18.0 ± 1.7 (10)
17.0 ± 0.5 (18)
15.2 ± 0.6 (21)
17.1 ± 0.4 (45)
17.4 ± 0.3 (37)
highest value
Weight (g)
147.9 ± 15.6 (23)
133.7 ± 8.2 (98)
59.6 ± 12.6 (18)
77.7 ± 9.7 (25)
26.2 ± 3.4 (14)
101.3 ± 26.0 (10)
68.0 ± 5.8 (18)
51.5 ± 5.4 (21)
56.7 ± 3.6 (45)
83.8 ± 4.7 (31)
AAAA lowest value
Age (years)
4.5 ± 0.3 (23)
5.2 ± 0.2 (98)
4.8 ± 0.8 (18)
4.3 ± 0.4 (25)
4.9 ± 0.5 (14)
8.5 ± 1.5 (10)
6.1 ± 0.6 (18)
3.2 ± 0.2 (21)
6.8 ± 0.3 (45)
4.3 ± 0.3 (31)
Condition
1.51 ± 0.04 (23)
1.45 ± 0.02 (98)
1.39 ± 0.04 (18)
1.38 ± 0.04 (25)
1.19 ± 0.04 (14)
1.33 ± 0.05 (10)
1.37 ± 0.05 (18)
1.33 ± 0.03 (21)
1.05 ± 0.02 (45)
1.46 ± 0.04 (31)
2.3.2 Effects of Sex on Size of Perch
Sex was only identified in fish collected by angling at St. Hilaire and
Edmundston (Tenzin, unpubl. data), and those collected at Nackawic (Freedman,
2005) because these were lethally sampled. Female perch were always longer
and heavier than male fish (Table 2-4), but were not significantly different in age or
condition. For the purposes of this thesis, the detailed data analyses will first be
presented by sex for the furthest upstream sites because of sample size and the
availability of information on sex of fish. The following set of analyses is presented
for combined analyses of fish non-lethally sampled for which sex was not known.
Comparisons among sites will subsequently be conducted and compared.
2.3.3 Size-at-age comparisons
The size of fish was examined based on size-at-age data, which show
differences between females and males at both Edmundston and St. Hilaire for
both length (Figure 2-4) and weight (Figure 2-6). In a site-by-site comparison, both
length (Figure 2-5) and weight (Figure 2-7) give similar results, and interpretation
was similar to the interpretation of data based on weight; females at S. Hilaire
showed a faster increase in size-at-age than females at Edmundston, but males
were similar.
In an examination of all sites on the river, pooled sexes were compared for
length-at-age (Table 2-5). Tobique fish had the slowest growth, followed by
46
Nackawic, and the slope of the line was highest at Grand Fall and Florenceville,
followed by St. Hilaire.
Table 2-4
Site
SHIL
Summary statistics for perch captured at St. Hilaire, Edmundston and
Nackawic by sex. Values are mean ± SE (n), and values sharing an
alphabetical superscript are not significantly different within a site
Sex
F
M
EDMN
F
M
NACK
F
M
AAA
Length (cm)
22.1 ± 0.9 (17)
a
18.8 ± 0.5 (7)
b
21.4 ± 0.5 (60)
a
18.9 ± 0.6 (41)
b
18.5 ± 0.4 (54)
a
16.2 ± 0.6 (13)
b
highest value
Weight (g)
172.1 ± 19.4 (17)
a
101.9 ± 9.1 (7)
b
155.0 ± 10.8 (60)
a
107.5 ± 11.3 (41)
b
72.8 ± 5.5 (54)
a
51.0 ± 6.1 (13)
b
AAAA lowest value
47
Age (years)
4.3 ± 0.3 (17)
a
5.0 ± 0.5 (17)
a
5.4 ± 0.3 (60)
a
4.8 ± 0.3 (41)
a
6.6 ± 0.3 (54)
a
5.3 ± 0.4 (13)
b
Condition
1.51 ± 0.04 (17)
a
1.52 ± 0.04 (7)
a
1.46 ± 0.02 (60)
b
1.42 ± 0.03 (41)
b
1.07 ± 0.04 (54)
a
1.13 ± 0.03 (13)
a
A
35
B
35
n=23
n=98
y = 2.7233x + 10.181
R2 = 0.9022
30
25
25
20
Females
Males
y = x + 13.757
R2 = 0.9727
15
Fork Length (cm)
Fork Length (cm)
y = 1.3079x + 14.351
R2 = 0.8366
30
20
10
10
5
5
0
0
0
2
4
6
8
10
12
0
2
4
Age
6
8
10
12
Age
Fork length-at-age within sites for females and males at: (A) St. Hilaire (B) Edmundston
A
35
B
35
y = 2.7233x + 10.181
R2 = 0.9022
30
y = 1.5785x + 10.782
2
R = 0.9482
30
25
25
20
EDMN
SHIL
y = 1.3079x + 14.351
R2 = 0.8366
15
Fork Length (cm)
48
Figure 2-4
Fork Length (cm)
Females
Males
y = 1.5785x + 10.782
R2 = 0.9482
15
20
10
10
5
5
0
EDMN
SHIL
y = x + 13.757
2
R = 0.9727
15
0
0
2
4
6
Age
Figure 2-5
8
10
12
0
2
4
6
8
10
12
Age
Fork length-at-age among sites at Edmundston (EDMN) and St. Hilaire (SHIL): (A) Females (B)
Males
A
400
n=98
n=23
350
350
y = 60.371x - 92.287
R2 = 0.9447
y = 28.762x - 0.3462
R2 = 0.7912
300
250
Females
Males
200
Weight (gm)
Weight (gm)
300
B
400
150
250
Females
Males
200
150
100
100
y = 28.258x - 35.899
R2 = 0.8423
50
y = 16.667x + 18.524
R2 = 0.9671
50
0
0
0
2
4
6
8
10
0
12
2
4
Age
A
10
12
B
400
y = 60.371x - 92.287
R2 = 0.9447
350
8
Weight-at-age within sites for females and males at: (A) St. Hilaire (B) Edmundston
400
350
300
300
250
250
EDMN
SHIL
200
150
Weight (gm)
Weight (gm)
49
Figure 2-6
6
Age
y = 28.258x - 35.899
R2 = 0.8423
EDMN
SHIL
200
150
100
100
y = 28.762x - 0.3462
R2 = 0.7912
50
y = 16.667x + 18.524
R2 = 0.9671
50
0
0
0
2
4
6
Age
Figure 2-7
8
10
12
0
2
4
6
8
10
12
Age
Weight-at-age among sites at Edmundston (EDMN) and St. Hilaire (SHIL): (A) Females (B) Males
Table 2-5
Regression table of length at age for all sites, and the rank of sites
based on slope of the regression line
SITES
R2
Slope
Intercept
Correlation
n
SHIL
EDMN
GRFA
ARST
TOBQ
FLOR
HART
WOOD
NACK
FRED
0.4649
0.8116
0.9171
0.9079
0.9318
0.9477
0.9077
0.9043
0.9139
0.9063
1.7783
1.4411
2.3787
2.0978
0.9482
2.2434
1.5294
1.7847
0.9789
1.2458
12.9200
12.7830
8.5759
9.5431
8.2192
8.8120
11.3120
9.4127
10.4400
12.4210
0.6818
0.9009
0.9576
0.9528
0.9653
0.9735
0.9527
0.9510
0.9560
0.9520
23
98
18
26
14
10
25
23
45
37
Slope
Rank
5
7
1
3
10
2
6
4
9
8
Intercept
Rank
1
3
9
6
10
8
4
7
5
2
2.3.4 Length Frequency Data and Ford-Walford Plots
Ford-Walford plots were used to generate back-calculated length, weight,
scale length, and scale width for comparison among sites and within sites. The
Ford-Walford plot was chosen due to its easy applicability to generate a linear
growth profile (Ruemper, 1998; Sparre, 1998) and the rationale that the use of
one method of back-calculation consistently for all the data collected would
generate growth profiles that would be comparable among and within sites.
The measured growth parameters (fork length 1, weight, scale length and
scale width) for aged fish were averaged into a single reading per year for each
age group. It was possible to generate tables for each of these averaged values
in t (year the data were collected) and t+1 (the next year, using the value for fish
a year older than the current one) (Sparre, 1998). These two values, t and t+1,
1
Fork length is the length from the most anterior part of the fish to the tip of the median
caudal fin rays (Anderson et al., 1983).
50
were plotted to generate the regression line (Figure 2-8). Another line was
generated at 45º from the origin. The intercept of the regression line generated
from the plots and the 45º line was taken as the maximum growth for that
parameter (Sparre, 1998) (Figure 2-8). The intercept of the regression line on
the Y-axis is taken as the value of the parameter at age-1 (Figure 2-8). This
method was used consistently for all the parameters among and within sites to
generate linear growth profile for the parameters investigated (Table 2-7, Table
2-8, Table 2-9). The equation of the line (linear growth profile) was used to
back-calculate all the values for each growth parameter linearly and could be
used to compare the parameters by site and by sex.
For the Ford-Walford plots, the largest intercepts (fork length at age 1) were
found at St. Hilaire, followed by Grand Falls and Woodstock. The smallest was
Tobique, followed by Florenceville, and Fredericton (Table 2-10).
Table 2-6
Sites
SHIL
SHIL
EDMN
EDMN
Summary table of Ford-Walford plots for fork length (linear growth)
at Edmundston (EDMN) and St. Hilaire (SHIL) by sex
Sex
R2
F
M
F
M
0.9227
0.9602
0.9537
0.9361
Intercept (size at
age-1)
5.3306
4.7794
3.6106
3.2065
51
Slope
0.8708
0.7970
0.8942
0.9071
n Two line intercept
(max growth)
16
41.26
7
23.54
60
34.13
38
34.52
40
y = 0.8942x + 3.6106
35
R2 = 0.9537
n = 60
Length at (t+1 )
(cm)
30
25
fork-length at age-1
20
Intercept = 3.6106
15
Max growth (two line
intercept) = 34.13
10
5
0
0
Figure 2-8
5
10
15
20
Length at t
(cm)
25
30
35
Ford-Walford plot for fork length for Edmundston female yellow
perch.
52
40
Table 2-7
Sites
SHIL
EDMN
GRFA
ARST
TOBQ*
FLOR*
HART
WOOD
NACK*
FRED
53
Table 2-8
Sites
SHIL
EDMN
GRFA
ARST
TOBQ
FLOR
HART
WOOD
NACK
FRED
Scale width (mm) calculated using Ford-Walford plots (the plot was limited to age 1-5 fish)
Age 1
Age 2
Age 3
Age 4
Age 5
Age 6
Age 7
Age 8
Age 9
Age 10
Max.
1.1729
0.2046
0.8907
0.8299
1.8690
-0.8181
1.3001
0.8193
3.4792
1.2989
1.5393
0.3981
1.2532
1.3233
1.1016
-2.5112
1.6795
1.3639
0.4085
1.7925
1.6538
0.5810
1.4008
1.6166
1.4167
-6.0154
1.7902
1.7259
3.1187
1.9800
1.6895
0.7540
1.4608
1.7910
1.2873
-13.2675
1.8225
1.9665
0.7266
2.0513
1.7007
0.9176
1.4852
1.8946
1.3404
-28.2765
1.8319
2.1264
2.8379
2.0784
1.7042
1.0723
1.4952
1.9563
1.3186
-59.3392
1.8346
2.2327
0.9745
2.0887
1.7053
1.2185
1.4992
1.9929
1.3276
1.7056
1.3569
1.5009
2.0147
1.3239
1.7057
1.4876
1.5016
2.0276
1.3254
1.7058
1.6113
1.5018
2.0353
1.3248
1.8355
2.3034
2.6191
2.0926
1.8357
2.3504
1.1676
2.0941
1.8358
2.3816
2.4487
2.0947
1.8358
2.4023
1.3180
2.0949
1.7058
3.7610
1.5020
2.0466
1.3250
0.7649
1.8358
2.4435
1.8481
2.0950
Distance of annuli (mm) from origin derived from Ford-Walford plots at individual sites
Annulus
1
0.5685
0.5264
0.6998
0.4683
0.3366
0.5487
0.5862
0.9661
0.4592
0.8335
Annulus
2
1.0872
0.9792
1.2621
0.8943
0.6505
1.0032
1.0785
1.6696
0.8450
1.5249
Annulus
3
1.5605
1.3686
1.7139
1.2819
0.9432
1.3798
1.4919
2.1819
1.1691
2.0984
* indicates problems obtaining good plot
Annulus
4
1.9923
1.7035
2.0769
1.6344
1.2161
1.6917
1.8391
2.5550
1.4413
2.5741
Annulus
5
2.3862
1.9916
2.3686
1.9551
1.4706
1.9501
2.1307
2.8266
1.6701
2.9687
Annulus
6
2.7457
2.2394
2.6030
2.2469
1.7080
2.1642
2.3755
3.0245
1.8622
3.2961
Annulus
7
3.0737
2.4525
2.7913
2.5123
1.9293
2.3415
2.5812
3.1685
2.0236
3.5676
Annulus
8
3.3729
2.6358
2.9426
2.7537
2.1356
2.4884
2.7539
3.2734
2.1593
3.7928
Annulus
9
3.6460
2.7934
3.0642
2.9734
2.3281
2.6101
2.8989
3.3498
2.2732
3.9796
Annulus
10
3.8951
2.9290
3.1619
3.1732
2.5075
2.7109
3.0207
3.4054
2.3689
4.1346
Table 2-9
Sites
SHIL
EDMN
GRFA
ARST
TOBQ
FLOR
HART
WOOD
NACK
FRED
Table 2-10
Fork length at age increments (cm) derived from Ford-Walford
plots
Age
1
9.95
8.68
7.08
7.50
6.19
4.41
8.47
0.86
4.98
9.42
Age
2
2.70
3.18
2.80
2.75
1.71
3.11
2.17
6.35
2.88
2.69
Age
3
2.46
2.73
2.25
2.50
1.60
2.58
1.82
4.62
2.42
2.23
Age
4
2.24
2.35
1.81
2.27
1.49
2.14
1.53
3.37
2.03
1.85
Age
5
2.05
2.02
1.45
2.07
1.39
1.77
1.28
2.45
1.71
1.54
Age
6
1.87
1.74
1.17
1.88
1.29
1.47
1.08
1.78
1.43
1.27
Age
7
1.71
1.50
0.94
1.71
1.21
1.21
0.91
1.30
1.21
1.06
Age
8
1.56
1.29
0.75
1.56
1.13
1.01
0.76
0.95
1.01
0.88
Age
9
1.42
1.11
0.61
1.42
1.05
0.83
0.64
0.69
0.85
0.73
Age
10
1.30
0.95
0.49
1.29
0.98
0.69
0.54
0.50
0.71
0.60
Summary table of Ford-Walford plots for fork length (linear growth)
Sites
R2
SHIL
Intercept
(length of age1 fish in cm)
Slope
n
Slope
Rank
Intercept
Rank
0.1968
12.5120
0.4554
23
10
7
Two line
intercept
(max
growth
in cm)
22.97
EDMN
0.9580
2.8606
0.9300
98
5
2
40.87
GRFA
0.9953
10.6740
1.9899
18
1
9
-10.78
ARST
0.8470
4.1272
0.8876
26
7
3
36.72
TOBQ
0.9034
-0.4501
1.1212
14
2
8
3.71
FLOR
0.8401
2.6122
1.0052
10
4
10
-502.35
HART
0.9409
2.3427
0.9569
25
3
1
54.35
WOOD
0.9915
5.2808
0.7941
23
9
5
25.65
NACK
0.9762
2.9673
0.8802
45
8
6
24.77
FRED
0.9882
2.7698
0.9152
37
6
4
32.66
54
2.3.5 Back-Calculating Growth
There are a variety of techniques that can be used for back-calculating
growth rates. The simplest technique is measuring the length and width of the
scales, but it is also possible to examine the size of growth increments (the
growth rate of fish back-calculated from the information in the increments) and
to also examine growth by back-calculating the size of fish at a specific age.
2.3.5.1 Scale Width and Length by Age
It is also possible to compare growth by examining changes in the length
and width of scales by ages (Table 2-8, Table 2-7). The relationships between
scale length and scale width are similar to size versus age for both male and
female perch (Figure 2-9, Figure 2-10, Figure 2-11, Figure 2-12), and the ratio
between scale length and width is independent of age (Figure 2-13).
2.3.5.2 Scale Increments
The annular increments on the scales provide a history of growth, with the
differences in distances between annuli proportional to the growth obtained in
different years. The scale increment data for Edmundston females (Table 2-11)
included fish that were captured from 10 year classes from 1991 to 2001 (Table
2-12).
55
A
5
4.5
4.5
y = 0.1548x + 1.6731
2
R = 0.5975
y = 0.4425x + 0.8807
R2 = 0.6021
4
3.5
3
Females
Males
2.5
2
1.5
Scale Length (mm)
4
Scale Length (mm)
B
5
y = 0.1924x + 1.271
2
R = 0.7707
1
3.5
3
Females
Males
2.5
2
y = 0.1498x + 1.3848
R2 = 0.6973
1.5
1
0.5
0.5
0
0
0
2
4
6
8
10
12
0
2
4
Age
Figure 2-9
8
10
12
56
Scale length at age comparison within site between males and females at: (A) Edmundston (B) St.
Hilaire
A
5
B
5
4.5
4.5
4
4
3.5
3.5
y = 0.2007x + 0.9
2
R = 0.5911
3
Females
Males
2.5
2
Scale Width (mm)
Scale Width (mm)
6
Age
y = 0.3294x + 0.3957
R2 = 0.6672
3
Females
Males
2.5
2
1.5
1.5
1
1
y = 0.1108x + 1.0522
2
R = 0.6502
0.5
y = 0.1262x + 0.8553
R2 = 0.6517
0.5
0
0
0
2
4
6
Age
8
10
12
0
2
4
6
8
10
12
Age
Figure 2-10 Scale width at age comparison within site between males and females at: (A) Edmundston (B) St.
Hilaire
A
5
y = 0.4425x + 0.8807
R2 = 0.6021
4.5
4
4
3.5
3.5
3
EDMN
SHIL
2.5
2
y = 0.1548x + 1.6731
2
R = 0.5975
1.5
Scale Length (mm)
Scale Length (mm)
4.5
B
5
y = 0.1924x + 1.271
R2 = 0.7707
3
EDMN
SHIL
2.5
2
y = 0.1498x + 1.3848
R2 = 0.6973
1.5
1
1
0.5
0.5
0
0
0
2
4
6
8
10
0
12
2
4
6
8
10
12
Age
Age
A
5
4.5
4
4
EDMN
SHIL
2.5
2
Scale Width (mm)
3.5
y = 0.3294x + 0.3957
R2 = 0.6672
3
B
5
4.5
3.5
Scale Width (mm)
57
Figure 2-11 Scale length at age comparison among sites at Edmundston (EDMN) and St. Hilaire (SHIL): (A)
Females (B) Males
3
EDMN
SHIL
y = 0.1262x + 0.8553
R2 = 0.6517
2.5
2
1.5
1.5
1
1
y = 0.1108x + 1.0522
R2 = 0.6502
0.5
y = 0.1364x + 0.7844
R2 = 0.7859
0.5
0
0
0
2
4
6
Age
8
10
12
0
2
4
6
8
10
12
Age
Figure 2-12 Scale width at age comparison among sites at Edmundston (EDMN) and St. Hilaire (SHIL): (A)
Females (B) Males
A
1.8
1.8
1.6
1.6
1.4
1.4
1.2
1.2
1
0.8
0.6
0.2
1
0.8
0.6
y = -0.0061x + 1.5644
R2 = 0.0091
0.4
B
2
L/W Ratio
L/W Ratio
2
y = -0.0062x + 1.5603
R2 = 0.0155
0.4
0.2
0
0
2
4
6
8
10
0
12
0
Age
2
4
6
8
10
Age
Figure 2-13 Scale length to width ratio at age for male (A) and female (B) perch at Edmundston
58
Table 2-11
Scale increments for Edmundston females (mm)
Age
st
2
3
4
5
6
7
8
9
10
11
1
0.5185
0.5578
0.5202
0.4542
0.4491
0.4561
0.3581
0.3915
0.3781
0.5107
nd
2
0.8683
0.5395
0.5919
0.4279
0.3644
0.2618
0.3165
0.2872
0.2296
0.1725
3
rd
0.5868
0.4890
0.4745
0.4158
0.4662
0.3499
0.4254
0.2754
0.3486
4
th
0.5160
0.4910
0.4902
0.3798
0.2679
0.3395
0.2645
0.3452
5
th
0.3804
0.5423
0.3528
0.3626
0.3038
0.2491
0.2884
Increments
6th
0.4693
0.3232
0.3349
0.4135
0.2749
0.2388
7th
8th
9th
10th
11th
0.2915
0.2646
0.3749
0.2394
0.2495
0.3037
0.3095
0.3061
0.2579
0.2060
0.3170
0.2414
0.2029
0.2064
0.2018
12
Table 2-12
Site
Comparisons of year classes of males and females at St. Hilaire
and Edmundston sites
Sex
Year Class
1993
SHIL
EDMN
1994
1995
Total
Per
Site
1996
1997
1998
1999
2000
2001
M
1
2
1
2
1
F
2
3
8
2
1
16
7
M
1
2
2
2
6
7
5
8
5
38
F
1
5
2
7
5
8
13
8
7
60
One of the challenges with increment data is that the growth per year is not
equal in all years, and the amount of growth will also vary with water
temperature for that year. A significant relationship between water temperature
and scale increment exists (Figure 2-14). This data can also be used to
examine relative growth rates between sexes and sites (Figure 2-15, Figure 216).
For comparisons among sites, measurements of distance of annuli obtained
from image analysis were pooled for each site irrespective of the age of the fish
in the group to obtain a single value of growth for each annulus at each site. The
resulting data were used on a Ford-Walford plot to obtain a linear growth profile
for scale growth for the particular site. The growth profiles obtained were
compared among sites (Table 2-8; Figure 2-17). Maximum scale growth was
obtained from fish collected at Fredericton and St. Hilaire and was lowest
among the fish collected from Tobique and Nackawic (Figure 2-17).
59
0.4
y = -0.0004x + 1.5278
2
R = 0.8145
0.35
Scale Increment (mm)
0.3
0.25
Females
Males
0.2
0.15
0.1
y = -0.0001x + 0.6955
2
R = 0.4556
0.05
0
2700
2800
2900
3000
3100
3200
Yearly DTU Contribution (C)
Figure 2-14 Comparison of average scale increment (Edmundston) versus
Daily Temperature Unit (DTU) >10C for the year of hatching.
Scale increment represents the average increment for 4-year-old
fish for that year; temperature was obtained from temperature
records from Mactaquac Fish Hatchery.
60
A
3.5
3
3
Age 2
Age 3
Age 4
Age 5
Age 6
Age 7
Age 8
Age 9
Age 10
2
1.5
1
0.5
Age 2
Age 3
Age 4
Age 5
Age 6
Age 7
Age 8
Age 9
Age 10
Age 11
2.5
Distance
(mm)
A
2.5
Distance (mm)
B
3.5
2
1.5
1
0.5
0
0
0
2
4
6
8
10
12
0
2
4
6
Age
8
10
12
Age
A
45
B
50
45
40
40
Age
Age
Age
Age
Age
Age
Age
Age
Age
30
25
20
15
10
2
3
4
5
6
7
8
9
10
Age 2
Age 3
Age 4
Age 5
Age 6
Age 7
Age 8
Age 9
Age 10
Age 11
35
% Increment
35
% Increment
61
Figure 2-15 Distance of annuli from origin for male (A) and female (B) perch at Edmundston
30
25
20
15
10
5
5
0
0
0
2
4
6
Age
8
10
12
0
2
4
6
8
10
12
Age
Figure 2-16 Percent scale increment to total scale length for male (A) and female (B) perch at Edmundston
4.5
4.0
Distance (mm)
3.5
SHIL
EDMN
GRFA
ARST
TOBQ
FLOR
HART
WOOD
NACK
FRED
3.0
2.5
2.0
1.5
1.0
0.5
0.0
0
1
2
3
4
5
6
7
8
9
10
11
Annuli
Figure 2-17 Scale growth profile for all sites back-calculated from Ford-Walford
plots
2.3.5.3 Back-Calculating Sizes at a Standard Age
A different approach to back-calculate length and weight was taken here as
compared to the previous one. The average fork length for each age group was
correlated with the distance of annuli obtained from Ford-Walford plot (Table
2-8). The data were used to linearly derive the back-calculated length of fish at
age for each site (Table 2-13).
The fork length at scale length was compared among sites (Figure 2-18).
The ratio of fork length to scale length decreased in the order: Edmundston,
62
Aroostook, Woodstock, St. Hilaire, Florenceville, Nackawic, Tobique, Grand
Falls, Hartland and Fredericton.
The back-calculated fork length was also compared among sites by age
(Figure 2-19). Perch collected at St. Hilaire and Edmundston and Aroostook
were found to have the highest growth and the lowest growth was seen among
the fish at Tobique, Nackawic, Florenceville, Hartland and Grand Falls. The
fork-length increments at age were also obtained from back-calculated fork
lengths (Table 2-13) and were plotted to observe comparative differences
among sites (Figure 2-20).
2.3.6 Weight Back-Calculation
The scale growth profile (Table 2-8) was used again to correlate with the
average weight of each age group of fish by site to obtain weight-of-fish-at-age.
The resulting data were used to back-calculate weight. The data obtained were
used to plot the weight-at-scale-length for each site (Figure 2-21). The weight
gained to scale growth was highest for fish collected at Edmundston and the
lowest among fish collected at Fredericton, Tobique, Hartland and Grand Falls
(Figure 2-22). The back-calculated weight at age was also compared among
sites (Figure 2-23). The fish collected at St. Hilaire and Edmundston gained the
most weight and the fish at Tobique, Nackawic, Hartland, Florenceville and
Grand Falls gained the lowest (Figure 2-24).
63
Table 2-13
Back-calculated fork length at age (cm)
64
Sites
Age 1
Age 2
Age 3
Age 4
Age 5
Age 6
Age 7
Age 8
Age 9
Age 10
SHIL
9.9500
12.6500
15.1100
17.3500
19.4000
21.2700
22.9800
24.5300
25.9500
27.2500
EDMN
8.6800
11.8600
14.5900
16.9400
18.9600
20.7000
22.2000
23.4800
24.5900
25.5400
GRFA
7.0800
9.8800
12.1300
13.9300
15.3900
16.5500
17.4900
18.2500
18.8500
19.3400
ARST
7.5000
10.2400
12.7400
15.0100
17.0800
18.9600
20.6700
22.2300
23.6400
24.9300
TOBQ
6.1900
7.9000
9.4900
10.9800
12.3700
13.6700
14.8700
16.0000
17.0500
18.0300
FLOR
4.4100
7.5200
10.1000
12.2400
14.0100
15.4700
16.6900
17.6900
18.5200
19.2100
HART
8.4700
10.6400
12.4600
13.9900
15.2700
16.3500
17.2500
18.0100
18.6500
19.1900
WOOD
0.8600
7.2000
11.8300
15.1900
17.6400
19.4300
20.7300
21.6700
22.3600
22.8700
NACK
4.9800
7.8600
10.2800
12.3100
14.0200
15.4500
16.6600
17.6700
18.5200
19.2300
FRED
9.4200
12.1100
14.3400
16.1900
17.7300
19.0000
20.0600
20.9300
21.6600
22.2600
50
Fork Length (cm)
40
SHIL
EDMN
GRFA
ARST
TOBQ
FLOR
HART
WOOD
NACK
FRED
30
20
10
0
0
1
2
3
4
5
6
7
-10
Scale Length (mm)
Figure 2-18 Fork length versus scale length for yellow perch from Saint John
River
30
Fork Length (cm)
25
SHIL
EDMN
GRFA
ARST
TOBQ
FLOR
HART
WOOD
NACK
FRED
20
15
10
5
0
0
1
2
3
4
5
6
7
8
9
10
11
Age
Figure 2-19 Back-calculated fork length at age for yellow perch from the Saint
John River
65
11
10
9
SHIL
EDMN
GRFA
ARST
TOBQ
FLOR
HART
WOOD
NACK
FRED
Length (cm)
8
7
6
5
4
3
2
1
0
0
1
2
3
4
5
6
7
8
9
10
11
Age
Figure 2-20 Length increments at age derived from Ford-Walford plots
800
700
600
SHIL
EDMN
GRFA
ARST
TOBQ
FLOR
HART
WOOD
NACK
FRED
Weight (g)
500
400
300
200
100
0
-100 0
1
2
3
4
5
6
7
-200
Scale Length (mm)
Figure 2-21 Back-calculated weight at scale length for yellow perch
66
350
300
250
Weight (g)
200
150
100
50
0
-50 0
1
2
3
4
5
6
7
8
9
10
11
SHIL
EDMN
GRFA
ARST
TOBQ
FLOR
HART
WOOD
NACK
FRED
-100
-150
-200
Age
Figure 2-22 Back-calculated weight at age for yellow perch
100
Weight Increments (g)
90
80
SHIL
EDMN
GRFA
ARST
TOBQ
FLOR
HART
WOOD
NACK
FRED
70
60
50
40
30
20
10
0
0
1
2
3
4
5
6
7
8
9
10
11
Age
Figure 2-23 Weight increments at age derived from Ford-Walford plots
67
Table 2-14
Year
Class
1991
SHIL
EDMN
GRFA
ARST
TOBQ
FLOR
HART
WOOD
NACK
FRED
TOTAL
Number of fish aged per year class per site for the Saint John
River sites. All fish were collected in 2001, except Nackawic,
which includes fish captured in 2004, and Edmundston, which
were collected in 2003
1992
1993
1994
1995
4
2
7
1
2
1
1
1
4
2
2
2
1
1
1
1
3
2
1
Table 2-15
5
5
4
4
1997
1998
1999
2000
2001
3
9
2
11
3
7
5
1
7
6
9
12
4
15
3
7
3
1
10
5
8
8
10
18
7
6
3
16
3
1
12
1
1
7
6
6
2
1
2
3
2
3
3
4
Averages for four-year-olds at all sites
Site
Weight
SHIL
EDMN
GRFA
ARST
TOBQ
FLOR
HART
WOOD
NACK
FRED
171.00
155.86
81.50
72.63
23.44
68.00
79.17
69.14
75.22
85.00
AAA
3
1996
highest value
Length
Annuli
Distance
2.30
2.40
2.87
2.51
1.57
2.62
2.24
2.55
2.08
2.63
22.20
21.77
17.55
16.98
12.39
18.20
17.75
17.14
18.70
17.73
AAAA lowest value
68
3
4
Total
Per
Site
23
98
18
26
14
10
25
22
45
42
323
2.4
Discussion
The size and growth of yellow perch were evaluated at 10 sites along the
Saint John River. The largest fish were captured at the site furthest upstream
(St. Hilaire), and were four times as heavy as those collected at the site with
smallest fish (Tobique). The condition factor was almost 50% higher at St.
Hilaire than it was at Nackawic and 30% higher than at Tobique. Data from the
Canadian EEM program have suggested that changes in sizes and growth rates
in excess of 30% are ecologically relevant (Munkittrick et al., 2002; Lowell et al.,
2004; Munkittrick et al., 2006). For condition factor, differences in excess of
10% are thought to be important (Munkittrick et al., 2002).
In general, growth was consistently fastest at St. Hilaire, Edmundston and
Fredericton, and slowest at Tobique, Nackawic and Woodstock (Table 2-16).
Condition factor is an indicator of energy reserves and commonly correlates with
growth rate (Lowell et al., 2003). St. Hilaire, Edmundston and Fredericton also
had the highest condition factors, and Tobique and Nackawic had the lowest
condition factors.
69
Table 2-16
Site
SHIL
EDMN
GRFA
70
ARST
TOBQ
FLOR
HART
WOOD
NACK
FRED
Summary of rankings of size or growth rates for yellow perch
Raw data
Weight
K
1
1
2
3
8
4
5
10
4
6
9
7
3
4
9
8
4
7
10
2
Adjusted Data
Weight
k
1
1
2
3
7
4
5
10
3
6
9
8
4
5
9
7
6
7
10
2
Length-at-age
Slope
Intercept
5
1
7
3
1
9
3
10
2
6
4
9
8
6
10
8
4
7
5
2
Ford-Walford
Slope
10
5
1
Intercept
7
2
9
7
2
4
3
9
8
6
3
8
10
1
5
6
4
Back-calculated Size
Final Size
Age 4
4
2
6
7
3
5
8
10
7
5
2
9
1
4
9
8
6
3
10
1
The lowest slope for size-at-age was also evident at Nackawic and Tobique,
and were less than half of that seen at the fastest growing sites; the steepest
slopes were at Florenceville and Grand Falls. Both of these sites are reservoirs
upstream of hydroelectric facilities. However, the slope of the regression lines
for length or weight-at-age did not correlate as strongly with fish size or
condition as did intercept for the regressions. It is possible to estimate growth
performance a number of ways, and there was good agreement in rankings
between the body weight and condition of fish, and the length-at-age intercept,
and estimated sizes at age 4 and age 10 using back-calculation (Table 2-16).
There was poor agreement of the slopes of length-at-age, or Ford-Walford
slopes or intercepts with the other rankings. There was also not good
agreement within the slopes of length-at-age or Ford-Walford plots. The size-atage and body size at capture give good information on an integrated response
of the fish over its life span. But, the back-calculated information provides a
complete picture of the growth history, and enables an analysis of the growth
performance of younger fish.
In terms of impacts, enrichment is mild near Edmundston (Culp et al., 2003;
Galloway et al., 2003), and nitrogen and phosphorus are elevated near
Florenceville associated with a potato processing plant discharge (Luiker et al.,
2004, 2005). A similar potato processing plant discharges effluent upstream of
Grand Falls, but elevated levels of nutrients further downstream are associated
with agricultural inputs near Hartland and Woodstock. Increased size and
condition have been reported in white sucker near the Florenceville area
71
(Doherty et al., 2005), and faster growth has been seen in slimy sculpin
downstream of Edmundston (Galloway et al., 2003). We would expect that
elevated nutrients would be associated with improved performance near
Edmundston and Florenceville, and yellow perch were larger here with higher
condition factors than at many other sites. Grand Falls, Florenceville and
Aroostook also had the largest slopes for length-at-age and had higher than
average condition factors.
The abundance of perch has been shown to increase in the Saint John River
with distance downstream (Figure 2-24; Curry and Munkittrick, 2005). Diversity
also increases (Figure 2-25), especially after the dam at Mactaquac, upstream
of Fredericton. This dam acts as a barrier to 10 anadromous fish species in the
river (Curry and Munkittrick, 2005).
The poorest performance of yellow perch occurred near Tobique and
Nackawic. Nackawic has been the subject of previous studies (Freedman,
2005). The river reach near Nackawic, receives effluent from a large pulp mill,
and is influenced to varying degrees by both upstream and downstream
hydroelectric facilities. In the first cycle of EEM studies at the St. AnneNackawic Pulp Mill (in 1995) yellow perch and white sucker were used as the
sentinel species (BEAK, 1996), while the Cycle 2 study (in 1999) assessed only
yellow perch (BEAK, 2000). These earlier studies found decreased body size,
condition and liver size in fish near Nackawic. Freedman (2005) showed that
the yellow perch showed relatively high site fidelity, and that both pulp mill- and
72
2.5
Relative Abundance
2
1.5
All fishes
Yellow perch
1
0.5
M
oo
dy
Br
id
B a P ri ge
k es
E d e r B tly
m ro
u o
G nd k
ra st
n d on
A r Fa
oo l ls
st
o
F l T o ok
o r biq
en u
ce e
Ha ville
W rt
o o la n
ds d
Na toc
k
F r ck a
ed w
er ic
ic
to
n
0
Site
Figure 2-24 Relative abundance of yellow perch as compared to other fish
species at sites along the Saint John River (from Curry and
Munkittrick, 2005)
25
Species richness (n)
20
15
10
5
F
A r al l s
oo
st
oo
k
To
bi
Fl
qu
or
e
en
ce
vil
Ha le
rt l
a
W
o o nd
ds
to
Na c k
ck
aw
Fr
ic
ed
er
ic
to
n
n
d
ds
to
G
ra
n
ok
un
Br
o
Ed
m
st
ly
ke
r
Pr
ie
Ba
M
oo
dy
Br
id
ge
0
Site
Figure 2-25 Fish species richness at sites along the upper Saint John River
from upstream of the Canadian border at Moody Bridge to
Fredericton (from Curry and Munkittrick, 2005)
73
sewage effluent-exposed sites in this reach had lower species richness,
abundance, and diversity. Fishes that are present show marked differences in
trophic position and dietary sources than those at non-exposed reference sites
(Freedman, 2005).
The poor performance at Tobique was not expected. While Luiker et al.
(2004) found elevated chlorophyll a near Tobique, nutrients were not elevated.
The yellow perch were sampled from the headpond and, therefore, this is an
area of the river where further study is required.
2.4.1 Relevance of the findings to Bhutan
This study on the Saint John River identified methodology that can be used
in non-lethal sampling programs to assess the effects of hydroelectric activities
on fish health. There are a number of advantages of using fish age in
monitoring studies. The accurate interpretation of fish age can allow for backcalculation of fish growth to describe the period years before any monitoring
was ever initiated at the site of interest and indicate if a history of effects is
present. These methodologies are of particular value in a country such as
Bhutan, in which little monitoring has been initiated to date and in which
development of non-lethal sampling methods are imperative.
There are also a number of limitations in using fish age in monitoring studies
as the precision and accuracy of the age interpretation can have considerable
influence on the results. Accuracy and precision in age interpretation can be
increased by increasing the number of samples and also by validating by
74
different age interpreters repeatedly until consistency among readers can be
reached. Older fish can be harder to age due to slow growth in their latter years.
It is important during the baseline studies to evaluate variability; this
information will be needed to determine appropriate sample sizes. The impacts
of temperature and age on growth rate in most species means that power will be
increased with a sampling design that focuses the sampling strategy on fish of a
similar age at comparable sites. It is probable that the suitability of different
indicators will need to be evaluated for each species in initial monitoring
programs in Bhutan. It is also difficult to generalize which indicators are most
accurate estimates of growth.
The sampling program for Bhutan must evaluate the impacts of sex on
growth rates. If there is an effect due to sex, it is possible with some species to
separate the sexes non-lethally by secondary sex characteristics or by condition
factor (when there are large differences between male and female gonad sizes)
when the fish can not be easily sexes externally.
The various measures of growth need to be evaluated for Bhutanese
species to determine the most sensitive and culturally-appropriate sampling
design. Calculations similar to those in this chapter need to be undertaken. It is
also important that the sampling design include other endpoints. Information on
abundance, fish community structure, and stable isotopes will all play an
important role in understanding impacts.
75
CHAPTER 3
A FRAMEWORK FOR MONITORING FISH IN BHUTAN’S RIVERS
3
Ecology of Bhutan’s Rivers Systems
Bhutan has has five major glacial-fed perennial river systems, Amo chhu 2,
Wang chhu 3, Puna Tsang chhu 4, Manas and the Nyere Ama chhu flowing from
north to south (Table 3-1; Figure 3-1). The total length of the rivers and
tributaries are estimated to be 7200 km (Petr, 1999). All the rivers drain into the
Brahmaputra River Basin in the Indian Plains, and most of the rivers originate
within Bhutan with a few exceptions. The headwaters of the Amo chhu and two
tributaries of the Manas River System, the Kuri chhu and the Gongri-Twang
chhu (which continues as Dangme chhu) originate on the Tibetan plateau. All
the rivers differ greatly due to extreme altitudinal gradients among flow beds
(Baillie and Norbu, 2004). The rivers have a very high gradient, resulting in very
high water velocities; the Wang chhu descends from almost 3600 meters at
Thimphu to 500 meters at the Southern Himalayan, within a span of
approximately 200 km.
The rivers have maximum flow during the monsoons, with the flow rate
increasing up to 20-50 times during the monsoons (Charlton, 1997). This results
in intermittent flooding of the foothills; flooding has become more frequent in the
2
Toorsa in India
3
Raidak in India
4
Sankosh in India
76
recent years, possibly due to climate change. The flooding is more severe as
one proceeds north to south due to heavier rainfall experienced in the south and
the funnelling effect of the converging rivers. The effect of flooding has also
become more noticeable in the recent years, which might be due to expanding
and new settlements in flood- prone areas.
The water temperatures for Wang chhu river system ranged from 11-18°C in
the upper reaches (NWWFCC, 2001). Shrestha (1991) conducted water quality
tests for the winter of 1990-1991 and a similar study was conducted in summer
by NWWFCC in 2001. The findings of the two studies are shown in Table 3-2.
Table 3-1
Discharge and runoff (source Baillie and Norbu, 2004)
3550
Mean
annual
discharge
(m3/s)
102
Mean
specific
runoff (mm
p.a.)
906
8050
384
1504
3200
149
1469
Kuri chhu
8600
291
1067
Gongri chhu
8560
262
965
Manas chhu
20925
784
1182
River
Catchment
area (km2)
Wang chhu
Puna Tsang
chhu
Mangde chhu
77
China
Bhutan
Key
hu
Ch
Chhu
Ama
Da
ngm
e
Ch
hu
Da
ng
Tsang Chhu
s
na
Ma
Pu
na
u
Major river systems of Bhutan
hu
Ch
h
Ch
Chh
u
50 km
S
Figure 3-1
Wang
hu
Ch
E
e
gd
an
o
Am
W
M
u
hh
C
Ha
N
o
r
ka
am
Ch
u
hh
78
Baso
u
Chh
Chhu
Chhu
DoChhu
C
Pa
Bangladesh
ri
Ku
im
Th
India
Ph
Mo
Ch
hu
Nepal
Ch
hu
Rivers
e
er
Ny
Table 3-2
Parameters
Water quality tests for Wang chhu River System (NWWFCC, 2001)
Alkalinity
CO2
DO
Total Hardness
pH
(mg/L)
(mg/L)
(mg/L)
(mg/L)
(mg/L)
Tributaries
1991
2001
1991
2001
1991
2001
1991
2001
1991
2001
Thim chhu
45-66
86-120
1.0-5.8
5.0-6.0
9.1-13.5
7.5-8.0
43-66
51-120
8.0-9.4
7.7-8.0
Paro chhu
48-65
51-103
4.5-8.9
3.0-6.0
7.5-11.5
7.0-8.7
53-66
51-68
8.0-8.3
7.8-8.3
Ha chhu
13-57
34.20
2.2-5.5
2.0-4.0
7.5-11.2
7.5-8.4
12-63
17-34
7.0-8.5
7.2-7.3
79
There have been 41 species of fish documented in rivers and lakes of
Bhutan (Table 3-3 and Table 3-4) (Day, 1873; Dubey, 1978; Dhendup and
Boyd, 1994; Petr, 1999). The snow trout or asla (Schizothorax progastus) and
Himalayan trout (Barilus spp.) are common in all rivers (Petr, 1999). Brown trout
(Salmo trutta) were introduced in 1930 (Petr, 1999), and are also very abundant
in most rivers. Other species of interest are katle (Acrossocheilus
hexagonolepis) and mahseer (Tor tor and T. puititora) (Petr, 1999). Specific
details on the population, density and distribution of species remain unknown at
this time due to lack of studies.
With the exception of snow trout and brown trout (NWWFCC, 2001), all other
species have only been recorded in warmer waters on the southern plains (Petr,
1999). There is no information on the distribution of other species within the
area of Bhutan influenced by existing and potential hydropower development.
3.1
Designing the Framework: Ecosystem Definition
Munkittrick et al. (2000) outlined a framework for an effects-based approach
for monitoring impacts of hydroelectric development. The effects-based
approach uses the performance of fish to provide an integrated signal about the
status of the system, and follow-up studies can be used to identify factors
limiting performance in the system (Hewitt et al., 2005). The characteristics of
the system are important for defining the most sensitive study design for
detecting impacts. For the purpose of this discussion, the relevant
characteristics will be described in terms of the physical environment and
80
Table 3-3
Summary of fish species recorded in Bhutan (Petr, 1999)
Family
Cyprinidae
Cobitidae
Siluridae
Sisoridae
Belonidae
Channidae
Nandidae
Mastacembelidae
Species
Common name
River/stream (pond)
1
Schizothorax progastus
Dinnawah
snowtrout/asla
2
3
Schizothorax
molesworthii
Acrossocheilus
hexagonolepis
Sankosh; Chamkhar; Kuru; Manas; Ha;
Mangdi
Manas
Copper mahseer
4
5
6
Crossocheilus latius
Tor putitora
Tor tor
7
Barilius barna
8
9
10
11
12
13
14
15
16
17
18
19
20
Barilius bendelisis
Barilius bola
Puntius macropogon
Puntius sophore
Puntius ticto
Puntius titius
Cirrhinus lata
Barbus spp.
Labeo dero
Labeo dyocheilus
Labeo pangusia
Garra annandalei
Garra gotyla
21
22
23
24
25
26
27
28
29
30
Danio aequipinnatus
Danio dangila
Brachydanio rerio
Botia Dario
Semiplotus semiplotus
Rasbora daniconius
Noemacheilus botia
Batasio batasio
Mystus bleekeri
Mystus vittatus
Manas; Mangdi; Phepso; Gaylegphug;
Sarbhang Khola; Kuru; Chanchi;
Phuntsholing
Manas; Sarbhang Khola; Gaylegphug
Manas; Sarbhang Khola; Gaylegphug
Manas; Sarbhang Khola; Gaylegphug;
Phepsu
Manas; Sarbhang Khola; Gaylegphug;
Phepsu; Sankosh; Khalikhola;
Phuntsholing; Magdi
Sarbhang Khola; Gaylegphug
Phepsu
Gaylegphug
Gaylegphug
Gaylegphug; Sarbhang Khola
Sankosh; Sarbhang Khola
Sankosh
Gaylegphug
Manas
Manas; Phepsu
Sankosh
Gaylegphug; Sarbhang Khola; Phepsu
Sankosh; Sarbhang Khola; Phepsu;
Magdi
Manas; Sarbhang Khola
Manas; Sarbhang Khola
Sarbhang Khola
Gaylegphug
Phepsu
Gaylegphug
Sarbhang Khola
Gaylegphug
Gaylegphug
Gaylegphug
31
32
Ompok pabda
Bagarius bagarius
33
34
35
36
37
38
39
Nangra punctata
Xenentodon cancila
Channa gachua
Channa striatus
Badis badis
Nandus nandus
Mastacembelus
armatus
Mahseer
Mahseer; jantura
Ticto barb
Swamp barb
Giant danio
Zebra danio
Bengal loach
Assamese kingfish
Slender rasbora
Mottled loach
Day’s mystus
Striped dwarf
catfish
Pabdah catfish
Dwarf goonch/
Bagarid catfish
Freshwater garfish
Snakehead murrel
Badis
Gangetic leaffish
Zig-zag eel
81
Gaylegphug
Manas
Manas
Phepsu
Phepsu
Gaylegphug
Manas
Gaylegphug
Sarbhang Khola; Kalikhola
Table 3-4
List of Introduced fish species (Petr, 1999)
Family/Species
Salmonidae
1 Salmo trutta fario
2 Salmo trutta trutta
Cyprinidae
3 Cyprinus carpio
4 Catla catla
5 Cirrhinus mrigala
6 Labeo rohita
7 Aristichthys nobilis
8 Ctenopharyngodon idella
9 Hypophthalmichthys molitrix
Common Name
River/stream (pond)
Brown trout
Sea trout
Ha; Paro; Thimphu
Ha; Paro; Thimphu
Common carp
Catla
Mrigal
Rohu
Bighead carp
Grass carp
Silver carp
Gaylegphug – ponds
Gaylegphug – ponds
Gaylegphug – ponds
Gaylegphug – ponds
Gaylegphug – ponds
Gaylegphug – ponds
Gaylegphug – ponds
stresses, factors affecting the selection of sampling sites, and characteristics of
the biota that can increase the sensitivity of monitoring programs.
It is necessary to consider background information to tailor a study design for
the specific region of interest. The basic requirements of the background
information include understanding the geology, hydrogeology, local climate,
industrial development, physical structure, water chemistry and resident biota
(Munkittrick et al., 2000). This information will help define the scope and
magnitude, and limitations, of the study design.
3.1.1 Physiographic Zones of Bhutan
Norbu et al. (2003) have proposed a classification of physiographic zones for
Bhutan based on altitude, climate, bedrock geology, surface drift, landforms,
hydrology, soils and natural vegetation. Norbu et al. (2003) have divided
82
Bhutan into three main zones: High Himalaya, North-South Valleys and Ranges,
and Southern (Figure 3-2). Each of these main zones is further subdivided into
multiple zones. The High Himalayas will not be considered within the context of
a fisheries monitoring program as they are outside proposed development sites.
Furthermore, much of the water in this zone is presently in glaciers and lakes,
and there is limited surface runoff that would support fish.
Most of the settlements and industrial development in the Southern Region
are near the border with India, and downstream reaches would be outside
Bhutan’s boundaries. Studies in the Southern Region will be limited in range
towards the downstream sites. The high occurrence of landslides and high
sediment loads in the Southern Region might prompt the study of sediment
loads on fish populations, and there are some opportunities for examining
industrial impacts that will be considered. But future hydroelectric development
is the major concern, and it will primarily occur in the North-South Valleys and
Ranges.
According to Norbu et al. (2003), the North-South Valleys can be further
classified as: Northern Valleys, Inner Valleys and Passes, Southern Mountains
and Gorges, Deep Eastern Valleys, and the Merak-Sakten-Block (Table 3-5).
The Northern Valleys include much of the protected areas and have seen
little development. There will be little opportunity to sample within these
protected areas, and most of the monitoring designs will consider areas outside
of the Nature Reserves.
83
Key
N
Region: High Himalaya
Zone 1: Trans-Himalayan Plateau
Mo
Zone 3: High Himalayan Plateau
Ch
hu
E
Ph
oC
hh
u
W
Zone 2: High Himalayan Peaks
S
Region: North-South valleys
e
Da
ngm
Ch
hu
s
na
Ma
Pu
na
Tsang Chhu
Da
ng
hu
Ch
Chh
u
hu
Ch
Zone 9: Front hills
Wang
hu
Ch
Region: South
de
o
Am
Zone 8: Merak-Sakten block
g
an
Zone 7: Deep Eastern valleys
M
Ha
u
hh
C
84
Baso
u
Chh
& gorges
Zone 10: Southeastern Bhutan
Zone 11: Piedmont (Duars)
Figure 3-2
50 km
Physiographic Region
Provisional physiographic zonation of Bhutan (recreated from Norbu et al., 2003)
A
hu
Ch
u
Chh
Ama
r
ka
am
Ch
hu
Ch
Zone 6: Southern Mountains
Chhu
Chhu
DoChhu
Pa
Zone 5: Inner valleys & passes
i
ur
K
im
Th
Zone 4: Northern valleys
e
er
Ny
Table 3-5
Physiographic zones within the North-South Valleys and Ridges of Bhutan (recreated from Norbu et
al. 2003)
Zone
Northern valleys
& ranges in W &
C*
Inner valleys &
passes in W & C
Altitude range
(m a.s.l.)
2000 – 4500
1100 – 4000
Bedrock
Landforms
Hydrology
Gneiss, schist,
quartzite &
limestone with
intrusions; some
Tethyan
High N–S* ranges; deep U- valleys
upstream, more V- downstream
Moderate runoff
High N–S ranges; wide alleys with river
terraces & large side valley fans
Moderate runoff from mid
& upper slopes but low
from valley floor & lower
slopes.
85
Eastern valleys &
ranges
500 – 4000
Gneiss, schist,
quartzite &
limestone with
intrusions; some
Lesser Himalayan
Rocks
High N–S ranges; deep, narrow V –
valleys; few terraces or fans
Moderate runoff from mid
& upper slopes but low
from valley floor & lower
slopes.
Southern
mountains &
gorges
400 – 5100
Gneiss, schist,
quartzite &
limestone with
intrusions
High N–S ranges, with plateau
remnants; deep, narrow & steep valleys
& gorges
High runoff from lower
slopes; moderate from
higher altitudes
Merak-Sakten
block
1500 – 4500
Tethyan
metasediments
High E-W* block; upstream valleys wide
with terraces & fans; valleys
downstream deeper & steeper
Moderate runoff
* N-S is North-South, W & C is West and Central, E-W is East-West
The Inner Valleys and Passes include most of the major cities of Bhutan and
also have lots of agricultural development. Most of the agricultural development
consists of small farms with limited mechanization. This area also has
considerable industrial and mining development in some small regions.
The Southern Mountains and Gorges include one of the most developed
sites for hydroelectricity in the west, as well as the area for potential
hydroelectric development sites. They have also seen development of
settlements due to hydroelectricity, and these can be considered to be sites with
multiple constructions in new settlements. As well, there has been considerable
road development for these settlements.
The Deep Eastern Valleys are the location of major towns in Eastern Bhutan.
Most of the towns tend to be small and are located away from rivers due to the
absence of flatlands in the valleys, and the population tends to be sparsely
distributed as compared to western Bhutan. One of the biggest hydroelectric
projects in terms of water storage lies here on the Kuri chhu. The Merak-Sakten
Block can also be excluded from immediate assessments due to the absence of
major development in terms or settlements, agriculture or industries.
As mentioned above, Norbu et al.’s (2003) classification of regions was
based on similarity of altitude, climate, bedrock geology, surface drift, landforms,
hydrology, soils and natural vegetation. Background geology, soils and surface
drift contributes to baseline water chemistry and limitations on the resident fish
biota. Altitude, climate and hydrology all affect the quantity and quality of water
in the system, and these will be described in the following sections.
86
The basic understanding of bedrock geology is a requirement for
assessment in terms of its influence on water chemistry and related changes in
resident fish (Munkittrick et al., 2000). Each of the zones proposed by Norbu et
al. (2003) can be identified with a particular type of bedrock geology. According
to Baille and Norbu (2004), much of Bhutan is underlain by high-grade
metamorphic rocks and gneiss forms the dominant portion (Figure 3-3). The
bedrock is composed mostly of thick sheets of metamorphosed geneisses,
quartzites, schists and marbles (Daniel et al., 2003; Baillie et al., 2004). Tethyan
metasediments dominate in the higher altitudes in the northern mountains and
southern hills and gradually shift towards being dominated by gneiss, schist,
quartzite and limestone towards the lower valleys (Table 3-5, Figure 3-3). Baillie
et al. (2004) notes that almost 70% of the country is dominated by gneisses.
3.1.2 Climate
The country can be classified into mainly three distinct climatic zones. The
southern foothills and the plains, with an altitude of less than 2000 m, have a hot
humid climate with temperatures ranging from 15 to 30ºC throughout the year
and annual rainfall ranging from 2500 to 5000 mm. The central inner Himalayas,
with altitudes ranging from 2000 to 3000 m, have a comparatively cooler
temperate climate with an annual average rainfall of about 1000 mm. The
Greater Himalayas, with altitudes ranging from 3000 to 7500 m, have an alpine
climate with an annual rainfall of around 400 mm.
87
N
W
A
88
Figure 3-3
Geological map of Bhutan showing bedrock composition (sourced from Daniel et al. 2003)
The rainfall is heaviest at the onset of the monsoon in the summer during the
months of June, July and August (Figure 3-4). This is mainly due to Bhutan
being in the Eastern Himalayas, which is among the first to receive the monsoon
winds. The south-western and south-central parts receive the highest amount of
rainfall in the country with mean annual rainfall well over 4000 mm, sometimes
reaching 5000 mm as in the case of Pheuntsholing (Table 3-6). The 2004
rainfall data show the highest rainfall occurring in Sarpang in the south-central
part of Bhutan, with total annual recorded rainfall of over 7000 mm (Figure 3-5).
Eastern Bhutan comparatively receives lesser rainfall than western Bhutan due
to it lying in the rain shadow of Meghalaya plateau in India (Baille and Norbu,
2004). All of these factors culminate in the presence of various ecological niches
within the country, resulting in its rich biodiversity.
Figure 3-4
Average temperature and rainfall for the Lingmuteychu watershed,
Bhutan (from RNRRC, 2002)
89
Table 3-6
Mean annual rainfall in Bhutan (modified from Baille and Norbu,
2004).
Station
Chengmari
Samtse
Pugli
Phuntsholing
Gedu
Darla
Lhamoizingkha
Sarpang
Bhur
Panbhang
Dechenling
Nanglam
Deothang
Bakuli
Daifam
Ha
Paro
Wang
Thim
Puna Tsang
Mangde
Chamkhar
Kuri
Kholong
Gongri
Longitude (°E)
89°03'
89°06'
89°14'
89°23'
89°31'
89°34'
89°51'
90°16'
90°26'
90°58'
91°13'
91°14'
91°29'
91°42'
92°05'
89°17'
89°20'
89°33'
89°34'
89°52'
90°31'
90°45'
91°10'
91°30'
91°33'
Altitude
(meters
above sea
level)
430
430
300
420
1980
1750
170
330
375
220
1000
550
800
240
280
2620
2410
2450
2210
1250
2120
2590
700
1830
830
90
n (years)
6
14
6
15
17
12
17
14
7
13
14
11
6
7
10
8
16
10
17
11
14
11
13
12
10
Mean
annual
rainfall
(mm)
4160
4200
4270
4940
3450
3380
4570
4480
4070
4150
3250
3280
3310
3270
2830
910
660
740
610
762
1321
719
944
1176
890
8000
Total Annual Rainfall (mm)
7000
6000
5000
4000
3000
2000
1000
a
as
G
C
ha
m
kh
a
Kh r
at
a
Ph Lh y
eu un
t
n
se
Pe tsho
li n
m
ag
g
at
sh
e
Tr
on l
g
M sa
on
Pu gar
na
K a kha
ng
lu
D ng
ag
Sa
a
m
dr W na
up an
Jo gd
ng i
kh
a
Ts r
ira
ng
Pa
Sa ro
rp
an
Si g
p
Zh so
em o
g
Si ang
m
to
kh
a
Ta
sh
H
iY a
an a
gt
se
0
Rain Guageing Stations
Figure 3-5
Total annual rainfall in 2004 (source data from Hydrology Section 5,
2005)
3.1.3 Hydrogeology
Hydrogeology has a major influence on local fish habitat. All the rivers of
Bhutan flow from north to south and are mainly 4th or 5th order rivers. There are
five major river systems, with a total length of 7200 km (Petr, 1999). All the
rivers originate within Bhutan with exception of the Kuri chhu and the Gongri
Twang chhu (Baille and Norbu, 2004).
Baille and Norbu (2004) concluded the river profiles to be effectively different
even among the tributaries of the same river system and it is not possible to
5
Hydrology Section: Hydromet Services Division, Department of Energy, Ministry of Trade
and Industries,Royal Government of Bhutan, Thimphu, Bhutan
91
generate a single generalised profile even within the same river system. The
mountainous terrain (Figure 3-6) offers variation in the altitudinal profile of river
beds even along the same latitude (Figure 3-7). The terrain also results in very
steep descents with multiple waterfalls for some of the rivers offering vast
potential for hydropower development. The Kholong chhu in eastern Bhutan is
among the steepest, rising at 5000 m and joining Gongri at 1000 m (Baille and
Norbu, 2004). The differences among the river profiles demonstrate the need to
develop unique assessments on all the rivers.
The Wang chhu receives discharge from the Thim chhu, Paro chhu, Do chhu
and Ha chhu and has a mean discharge of 60 m3/s (Table 3-7). The Mo chhu
and Pho chhu together form the Puna Tsang chhu with a mean discharge of
over 300 m3/s. Discharge rates for other rivers have been similarly collected and
maintained by the Hydromet Services Division, Department of Energy (Figure
3-8) and have been shown in Table 3-7. Figure 3-9 shows the river flow at the
main gauging stations previously set up by the Hydromet Services Division. The
increasing discharge with high current and unstable soil conditions towards
southern Bhutan result in a high amount of sediment load in the rivers when
reaching the southern foothills. The sediment load is further compounded by
heavier rainfall in the south with associated sediment-laden runoff and flooding.
92
N
W
E
93
Figure 3-6
6
Topography map of Bhutan 6
Map source from http://www.southasianfloods.org/graphic/maps/bhutan/topo.html (Accessed March 15, 2006)
Stepped high valley & low pass in W & C Bhutan
6000
Altitude (m.a.s.l)
Kang Bum
Dagala
4000
Dochula
Thim chhu
2000
Wang chhu
28 N
27 N
Deep valley & high ridge in E Bhutan
Altitude (m.a.s.l)
6000
4000
Thrumsingla
2000
Kuri chhu
Manas
27 N
Figure 3-7
28 N
Examples of river gradients and physiographic profiles in Bhutan
(modified from Norbu et al., 2003).
94
Table 3-7
Discharge and specific runoff from rivers during 2003 (source data from Hydrology Section, 2005)
River
95
Thimphu chhu
Wang chhu
Mo chhu
Puna Tsang chhu
Mangde chhu
Mangde chhu
Mangde chhu
Chamkhar chhu
Kuri chhu
Gongri chhu
Kholong chhu
Guageing
Stations
Lungtenphug
Tamchu
Yebesa
Wangdi
Dobani
Bjizam
Tingtibi
Kurjey
Kurizampa
Uzorong
Muktirap
Elevation
(ft)
7473
6994
4130
3996
1056
6356
1786
8598
1997
2103
5530
Mean
(m3/s)
22.99
60.95
126.83
303.91
361.27
72.43
135.84
52.95
466.57
353.09
78.29
Maximum
(m3/s)
37.21
102.20
196.70
483.80
571.21
119.45
194.00
87.80
976.86
554.65
144.65
Minimum
(m3/s)
15.55
41.37
84.10
203.93
251.03
45.65
99.63
33.60
309.42
236.31
39.29
Runoff
(mm)
91.61
63.87
144.35
127.98
111.00
137.59
112.18
103.53
143.56
108.84
228.35
Key
N
Hydromet Water Sampling
Stations
W
Ch
hu
S
Chhu
hu
Ch
Pu
na
I
G
E
Chhu
J
er
Ny
e
s
na
Ma
Chh
u
e
e
gd
an
Wang
u
hh
oC
Am
B
hu
Ch
Ama
M
u
hh
C
Ha
hu
Ch
D
Baso
u
Chh
K
Da
ngm
A
Da
ng
u
r
ka
am
Ch
h
Ch
DoChhu
Pa
F
Tsang Chhu
m
i
ur
K
i
Th
H
C
Chhu
Ch
hu
Mo
Ph
o
Rivers
E
Ch
hu
Roads
50 km
Figure 3-8
Location of river flow data collection stations (source data from
Hydrology Section, 2005)
1000
900
800
River Flow (m3/s)
700
600
Mean Flow
Maximum
Minimum
500
400
300
200
100
0
A
B
C
D
E
F
G
H
I
J
K
Data Collection Stations
Figure 3-9
Flow comparisons among the hydrological monitoring stations
(source data from Hydrology Section, 2005). Letters on x axis
refer to the stations in Figure 3-8
96
The timing of sampling will be affected by flows, and fish will be most
concentrated and easiest to capture during the periods of lower flow. The
difference between maximum and minimum river flow in monsoon and dry
months is as much as 50 times (Charlton, 1997). It will be important to avoid
sampling during the monsoons from June to August, as 90 - 97% of the
sediment transport occurs during this season (Sharma, 2002), and flow will be
very high. Sediment transport issues are huge, over 4800 t km-2 in some areas
(in Sharma, 2002)
3.1.4 Physical Structure of Rivers
All the rivers (excepting the Manas and Lhobhrak) flow from the Himalayas
to the Brahmaputra River. The rivers have a confined channel in narrow valleys
and are not navigable (Dubey, 1978). The Amo chhu, Wang chhu and Mo chhu
drain western Bhutan and the Manas and its tributaries to the east. The Amo
chhu is one of the principal rivers in western Bhutan and begins in Tibet. The
river flows rapidly and follows a confined valley between steep mountains, with
an average depth of at least 1 m. As it leaves the foothills and enters the Duar
plain, it widens into a braided channel. The minimum annual flow of the river is
11.75 m3/s and the river and its tributaries measure a total of 310 km (Dubey,
1978).
The Wang chhu and its tributaries cover a total length of nearly 610 km in
Bhutan (Dubey, 1978). The main river is a rapid stream, running over a bed of
large boulders. Between Thimphu and the confluence with the Paro chhu, the
97
course of the river is not severely confined but, after leaving the confluence, it
runs through a narrow defile between very steep cliffs (Dubey, 1978).
The Paro chhu flows southeast through a comparatively open valley with
large boulders. It is joined by several small tributaries flowing from nearby
mountains. The Ta chhu, which flows in just above Paro Dzong, joins it from the
left. To the west, the Ha chhu drains into the Wang chhu. At Tashichho Dzong
the bed of the river is about 2,121 m above sea level and at the point of its exit
in the Duar its elevation is only 90 m (Dubey, 1978).
The Mo chhu drains a basin of 9,900 km2, has a total length of 1,810 km,
including all its tributaries, and has a minimum annual flow of 53.8 m3/s (Dubey,
1978). At Punakha, it is joined by the Pho chhu and 20 km further downstream
at Wangdi Phodrang, by the Tang chhu.
The Manas is the largest river system in Bhutan, with a total length of 3,200
km (Dubey, 1978). Just before reaching Tashigang, the Manas is joined by the
Kulong chhu. At Tashigang the Manas is about 50 m wide, and its waters flow
rapidly over a bed of boulders. The river bed near Tashigang is about 606 m
above sea level; it is only about 121 m above sea level where it joins the
Tongsa chhu.
3.1.5 Water Chemistry of Rivers
Water quality is determined by the geological conditions the river flows
through and by inputs of various effluents from human activities (Munkittrick et
al., 2000). Sharma et al. (2005) have classified Nepalese rivers into seven
98
classes of river quality based on ecological integrity and water quality. The
collection of water quality data is essential in identifying the associated stresses
if any were detected during the assessment. The available data from the
National Environment Commission water quality survey of 2003 are reflected in
Table 3-8.
Thim chhu, Amo chhu and Paro chhu showed the highest amounts of E.coli
as these rivers flow through the most populated towns and receive inputs from
water and sewage treatment plants (Thim chhu and Amo chhu). Highest
turbidity was seen in Thim chhu, Paro chhu and Kuri chhu. Dissolved oxygen
and pH ranged from 8.3-11.0 (mg/l) and 7.7 to 8.4, respectively. Dissolved
ammonium, phosphates and nitrates did not show much variation among the
surveyed rivers. Comparative charts for dissolved calcium, magnesium, silicon
oxide and total hardness are shown in Figure 3-10 (A, B, C, D). In terms of
water quality, hydroelectric development would be expected to have impacts on
sediments, nutrients, physical parameters and inorganic contaminants (Greig et
al., 1992). Impacts on major ions would be expected to be relatively low, with
some influence on biological oxygen demand (BOD), and organic parameters.
99
100
Table 3-8
Water quality survey 2003 by NEC (source data provided by NEC 7, 2005)
River
Alt
m
Pressure
hPa
Flow
m3/s
Turbidity
NTU
pH
Dissolved
Oxygen
mg/l
165.0
994.0
52.0
5.5
7.8
2340.9
785.2
72.0
28.5
1740.0
847.8
167.3
2370.0
775.0
3020.0
1033.3
742.0
935.9
1790.0
Amo
chhu
Thim
chhu
Wang
chhu
Paro
chhu
Ha chhu
Puna
Tsang
chhu
Mangde
chhu
Kholong
chhu +
Gongri
chhu
Kuri chhu
Chamkar
chhu
7
E.Coli
count
org/ml
9.5
Electrical
Conductivity
at
25˚C µS/cm
144.5
8.2
9.4
16.3
8.3
12.0
2.0
178.0
865.0
1013.3
857.0
2575.0
Ammonia
mg/l
Nitrate
mg/l
Phosphorus
mg/l
22.5
Chemical
Oxygen
Demand
mg/l
2.5
0.2
0.2
0.0
200.7
53.9
7.2
0.2
0.2
0.0
9.5
158.7
15.5
4.3
0.2
0.2
8.4
9.0
142.0
26.0
6.0
0.2
0.2
0.0
1.7
9.3
8.3
7.9
8.3
9.5
64.7
104.4
0.0
3.0
2.7
4.0
0.2
0.3
0.2
0.2
0.0
1.3
16.0
7.0
7.8
11.0
128.0
0.0
1.0
0.2
0.2
0.0
951.3
56.5
8.7
7.7
10.3
114.7
0.0
1.0
0.2
0.2
0.0
960.0
772.5
46.5
16.0
22.0
3.0
8.1
8.0
11.0
9.5
277.0
108.0
2.0
1.0
1.0
1.5
0.2
0.2
0.2
0.2
0.0
0.0
NEC: National Environment Commission, Royal Government of Bhutan, Thimphu, Bhutan
A
30.0
B
10.0
9.0
25.0
8.0
7.0
Magnesium (mg/l)
Calcium (mg/l)
20.0
15.0
6.0
5.0
4.0
10.0
3.0
2.0
5.0
1.0
0.0
Amo Chhu Thim Chhu
Wang
Chhu
Paro Chhu Haa Chhu Punatsang
Chhu
Mangde
Chhu
Kholong
Gongri
Chhu
Kuri Chhu
0.0
Chamkar
Chhu
Amo Chhu Thim Chhu
Wang
Chhu
Rivers
101
Mangde
Chhu
Kholong
Gongri
Chhu
Kuri Chhu
Chamkar
Chhu
Mangde
Chhu
Kholong
Gongri
Chhu
Kuri Chhu
Chamkar
Chhu
Rivers
C
8.0
Paro Chhu Haa Chhu Punatsang
Chhu
D
120.0
7.0
100.0
Calcium Carbonate (mg/l)
Silicon Oxide (mg/l)
6.0
5.0
4.0
3.0
80.0
60.0
40.0
2.0
20.0
1.0
0.0
0.0
Amo Chhu Thim Chhu
Wang
Chhu
Paro Chhu Haa Chhu Punatsang
Chhu
Rivers
Mangde
Chhu
Kholong
Gongri
Chhu
Kuri Chhu
Chamkar
Chhu
Amo Chhu Thim Chhu
Wang
Chhu
Paro Chhu Haa Chhu Punatsang
Chhu
Rivers
Figure 3-10 Water quality survey 2003 by NEC (source data provided by NEC, 2005): (A) Calcium (B)
Magnesium (C) Silicon Oxide (D) Total hardness (Calcium Carbonate)
3.1.6 Land Use
Agricultural activities make up about 5% of land use, and almost all of it
occurs within the North-South Valleys (Figure 3-11). Forested land constitutes
almost 75% of the surveyed land and 46% of the surface area (Karan, 1987).
This forest cover is the highest among South Asian countries (Sharma, 2002).
Deforestation and mismanagement of forest resources near road areas and
overgrazing have resulted in significant soil erosion in numerous areas, and in
general sedimentation in rivers is a significant issue.
N
W
E
S
Figure 3-11 Land use of Bhutan (from Karan, 1987)
102
3.1.6.1 Protected Areas and Parks
Bhutan has currently set aside 26.23% of its land as protected areas (Figure
3-12). It has four national parks, four wildlife sanctuaries and one nature
reserve. All are connected by biological corridors to enable migration or
movement of fauna among these protected areas. All the river basins run along
one or more protected areas along the course of their flow.
3.1.6.2 Industrial Development
Industries in Bhutan can be classified into forest- or wood-based, agrobased, mineral-based and service-based. The development of forest-based
industries at the expense of exploiting the forests has been reduced with the
government restricting the export of timber. This is due to the government’s
realization that forests offer vital ecological benefits and the forestry act states
that Bhutan will maintain 60% forest coverage for all time. The restriction on
timber exports has seen substantial reduction in deforestation with aggressive
reforestation; forest coverage is thought to be increasing. There still exist
cottage industries for wooden products such as wooden masks, traditional
bowls and cups. The making of traditional paper (daysho), bamboo products,
and traditional herbs for medicine also exist as cottage industries for non-wood
products. Large non-wood based industries include particle board industries.
Softwood-based industries export broom and tool handles to European
countries and tea boxes and wooden shoe heels to India.
103
Key
Protected Areas
N
Biological Corridors
Forest Management Units
Jigme Dorji
Wangchuk
National Park
u
Ch
h
Rivers
o
Bumdeling
Wildlife
Sanctuary
r
Ku
i
Chhu
Ch
hu
g
an
h
Ch
u
Jigme Singye
Wangchuk
National Park
e
de
Da
ng
hu
Ch
Thrumshingla
National Park
M
u
hh
C
o
Am
s
na
Ma
Wang
hu
Ch
Chh
u
Tsang Chhu
u
Ha
Royal Manas
National Park
Phibsoo Wildlife
Sanctuary
Chhu
r
ka
am
Ch
DoChhu
h
Ch
Baso
u
Chh
Da
ngm
im
Th
Pa
104
Toorsa
Strict
Nature
Reserve
Ch
hu
Ph
Mo
S
Roads
50 km
Figure 3-12 Protected Areas of Bhutan (recreated from DOE, 2004)
Sakteng
Wildlife
Sanctuary
Chhu
hu
Ch
Ama
E
Pu
na
W
e
er
Ny
Khaling National
Wildlife Sanctuary
The Department of Geology and Mines provides mapping, resource
exploration and technical services in Bhutan and also regulates the mines so
that their functioning is environmentally friendly (DGM, 2005). Bhutan’s mined
mineral resources consist of gypsum, limestone, marble quartzite, coal, slate
and talc (Table 3-9) (USGS, 2006). Almost all of the mining is carried out in
southern Bhutan, except that of marble slate and dolomite (Figure 3-13). Marble
is mined in Gidakom near Thimphu and slate is mined in Wangdiphodrang.
Dolomite, gypsum and limestone are used in the cement and calcium carbide
factories; most of the manufactured product is exported to India. Quartzite is
used in the manufacture of ferrosilicon, which is exported to India and Japan.
Table 3-9
Minerals and location of mines in Bhutan (compiled from USGS,
2006)
Minerals
Mine Location
Gypsum
Khotakpa, Pemagatsel
Coal
Bhangtar, Chenangri, Deothang
Dolomite
Samtse, Mongar, Samdrupjongkhar, Shemgang
Marble
Gidakom
Slate
Wangdiphodrang
Talc
Kalapani
Limestone
Haurie Khola and Rongri, Pugli, Duarpani, Kalesore and Titi
Quartzite
Tintali, Suktikhola and at Kamji
105
The by-product of manufacturing ferrosilicon, microsilica, is also exported.
Quarrying of boulders and sand is carried out in river beds during the dry
season in some parts, mainly for construction. The existing mining industries
and mineral-based industries are strictly required to conduct proper
environmental impact assessments both before initiation of a project and on a
periodic basis afterwards, to prevent any detrimental effects on the surrounding
environment.
Agricultural industries such as food processing plants (fruit juices, fruit jams,
pickles, dairy, and distillery) exist mainly in southern Bhutan (Figure 3-13). The
progress of the agro-based industries inherently depends on the performance of
the agriculture sector. Though there has not been much expansion in
agricultural lands due to limited availability of agricultural land, intensification
programs initiated by the government in the existing agricultural lands (by
educating the farmers and providing subsidies for agricultural tools, such as
machinery and quality seeds) have resulted in sustaining agro-industries fairly
well within the regional market.
A recent boost in service industries such as construction and tourism has
helped Bhutan to mitigate unemployment. The increase in employment has
been due to initiation of construction of mega-projects such as the Tala and Kuri
chhu hydropower plants as well as increases in tourism. Though the
construction of hydropower plants is perceived as being a benefit to Bhutan’s
economy in the coming decades, environmental damages during construction
106
Key
Large Hydropower Sites (2006)
Mines (Gypsum, coal,
dolomite, marble, slate,
limestone, talc, quartzite)
Large Hydropower Sites (1012)
Large Hydropower Sites (2017)
Cement Factories
Food Processing
industries (Fruit
products, distilleries,
dairies, beverages,
etc)
Water and Sewage
Treatment Plants
Large Hydropower Sites (2023)
Ch
hu
Chemical Industries
(Calcium Carbide,
Ferrosilicon, candle,
plastic, polythene,
etc)
o
Roads
ri
Ku
Ch
hu
Pu
na
Tsang Chhu
e
Da
ng
hu
Ch
hu
Ch
Chhu
er
Ny
e
s
na
Ma
u
u
Chh
h
Ch
Wang
E
de
u
hh
hu
Ch
W
g
an
C
o
Am
N
M
107
Baso
u
Chh
Ha
Chhu
r
ka
am
Ch
hu
Ch
DoChhu
Pa
Chhu
Da
ngm
im
Th
Rivers
Ama
Mo
Ph
Hydromet Water Sampling
Stations
Ch
h
u
Major towns with road access
50 km
S
Figure 3-13 Map of Bhutan with location of industries, mines, sewage treatment plants, dams, major towns, water
sampling stations, roads and rivers
and during operation are unavoidable. These types of projects will call for more
environmental vigilance; other similar projects are likely to be launched in the
future.
3.1.7 Dams and Reservoirs
Many of the rivers of Bhutan have seen fast development of run-of-the-river
stations, peaking stations, or hybrids of both in the past two decades. The
power sector aims to generate 20,000 MW of power by the end of the 10th Five
Year Plan (2012) and add another 5,000 MW by the end of the 11th Five Year
Plan (2017) (DOP 1999). The first major dam, Chukha (336 MW), was
commissioned in 1986 and currently the major hydropower dams include Baso
chhu Phase I, Kuri chhu and Baso chhu Phase 2 with total generation capacity
of 460 MW (Figure 3-14). The newest mega hydropower station at Tala will be
commissioned in June 2006. Additionally, smaller dams affecting rivers and
streams have been constructed since the 1960s.
The most impacted river, by number of dams, is the Wang chhu. The Wang
chhu already has two major dams at Chukha (336 MW) and at Tala (1020 MW).
Another dam, Chukha II (500 MW), is also planned (DOP, 1999). In the east, the
Kuri chhu has seen the development of a major dam with a high-capacity
peaking facility generating 60 MW. The Baso chhu (24 MW) is a run-of-the-river
type station on the Baso chhu, a tributary of Puna Tsang chhu. The Baso chhu I
(40 MW) located further downstream has water flow from the tailrace of Baso
chhu and Ruri chhu.
108
3.2
Factors Affecting Sampling Design
The previous overview has examined the basic background information to
tailor a study design for the specific region of interest. This information will help
define the scope and magnitude, and limitations, of the study design. The main
focus of the monitoring program for Bhutan, based on the geographic
information, will be related to monitoring of the North-South valleys where the
hydroelectric development will take place (Figure 3-14). The geology, physical
structure, local climate, hydrogeology, industrial development, and water
chemistry place restrictions and offer opportunities to optimize study designs
(Table 3-10).
There will not be many confounding factors in the North-South Valleys
because of low population densities and low development of agriculture, and
most of the industry and mining take place in the southern plains. However, the
systems will be largely forested, prone to high sediment inputs, and road access
will be limited. The inability to travel the rivers in boats will largely restrict
sampling to areas with road access. Consequently, sampling in some future
areas of development will need to wait for road access to the areas.
Sampling should avoid the monsoon season in June-August because of high
flows and high sediment transport during these periods. Sampling should not
use fish that spawn in the fall after these periods, as impacts of water flow
regulation and fluctuations will probably be largest prior to the monsoon season.
Therefore, it will probably be best to sample between March and May.
109
Key
Large Hydropower Sites (2006)
N
W
Large Hydropower Sites (2012)
Large Hydropower Sites (2017)
E
Ch
hu
Rivers
Roads
i
ur
K
Ch
hu
g
an
u
o
Am
hu
Ch
Chhu
er
Ny
e
s
na
Ma
u
Wang
h
Ch
Pu
na
Tsang Chhu
h
Ch
e
de
Da
ng
hu
Ch
M
u
hh
C
110
Chh
u
Chhu
r
ka
am
Ch
DoChhu
hu
Ch
Baso
u
Chh
Ha
Da
ngm
im
Th
Pa
Chhu
Ama
Mo
Ph
o
S
Ch
hu
Large Hydropower Sites (2023)
50 km
Figure 3-14 River systems of Bhutan with location of large hydropower development sites 8 (includes existing
developed sites and future planned development to 2023)
8
Location of Hydropower sites taken from “The 2003-2022 Power System Master Plan Final Report – Executive Summary” (DOE
2004)
Table 3-10
Influence of system characteristics on design for fisheries studies
111
Characteristic
Physiographic zones
Restriction
Restrict studies primarily to North-South central
valleys
Rationale or Consequences
Location for hydroelectric
development
Climate
Avoid monsoon season in June-August
Avoid high flow, high sediment
deposition
Hydrogeology
Probably sample March-May
Physical Structure of
Rivers
Not navigable, high flow
Will restrict sampling gear types
Land Use
Largely forested, small agriculture, road system
poorly developed
Restricted access
Protected Areas and
Parks
Not available for sampling
Industrial
Development
Industrial development and mining towards
southern plain
Not a lot of confounding factors in
North-South Valleys
Dams and reservoirs
Series of existing, proposed and planned
developments
Allows development of tiered, and
sequential sampling
The fish species that offer the most sensitivity will be ones that are spawning
or preparing to spawn in the time periods leading up to the monsoon season. At
least two species should be examined, one that spawns in the nearshore area
prior to or at the start of the monsoon season, and a second that is preparing to
spawn during this time period.
The fish capture techniques will have to consider the fast current, in systems
that are not navigable; these factors will restrict sampling gear types. The most
suitable sampling options will include angling, long-lining and cast-netting.
Back-pack electroshocking should be used to examine potential small-bodied
species, and to examine growth rates and size-distributions of juveniles. The
most sensitive designs will include species in which the juvenile stages are
spent in the mainstream of the river systems.
Considering these limitations on the sampling design, the next phases of the
sampling design are to select the study sites, design the sampling schedule,
select the relevant endpoints, and select the sentinel species.
3.3
Site Selection
Proper sample site selection is very important for monitoring studies. In the
case of Bhutan, most of the rivers are experiencing very fast development,
either through hydropower construction on the river or growth of urban and
industrial areas near the rivers. Therefore, it becomes necessary to prioritize
sampling schedules for specific sites to keep pace with development and to
112
identify specific effects associated with these developments, or the nature of
questions asked during assessments (Munkittrick et al., 2000).
Greig et al. (1992) examined study design needs for hydroelectric
development, and recommended that researchers:
1. Study existing sites on regulated rivers with upstream (reference), reservoir
and downstream sites,
2. Study reference sites on a) unregulated rivers, b) sites during different
periods of operation to understand how changes in operation affect habitat,
and c) future development areas before, during and after development, and
3. Establish experimental sites to conduct detailed studies.
Relevant sites are available in Bhutan for all of these options (Table 3-11).
3.4
Selection of Sampling Design
Bhutan presents a complex system, whereby rivers differ even along the
same latitude due to the changing altitude and difference in river sizes. It is
important in this case for reference sites to be selected for river size and
altitude; until more is known about the distribution of fishes in the study area it is
not possible to have a final study site selection.
However, some preliminary designs can be stated. It is important to have
study sites on as many rivers as possible, and study designs sometimes use
both local reference sites that have closely matched conditions, and regional
reference sites to provide information about regional changes. The regional,
113
Table 3-11
Potential sites for development fisheries studies in Bhutan
Focus
Potential Rivers
Priority
Establish
experimental sites
to conduct detailed
studies
Development of methods, baseline
information of fish biology
Upper tributaries of
Wang chuu
1
Background Data
Available
NWWFCC, 2001
Monitoring Studies
Existing sites on regulated rivers with
upstream (reference), reservoir and
downstream sites
Wang chhu
Kuri chhu
2
Flow data only
Study sites on unregulated rivers
Dangme chhu*
4
Flow data only
Study sites during difference periods
of operation to understand how
changes in operation affect habitat
Wang chhu
2
Flow data only
Study future sites before, during and
after development
Puna Tsang chhu
Mangde chhu
Chamkar chhu
3
Flow data only
Examine potential future confounding
factors
Thim chhu
(sewage)
3
Charlton, 1997 for
sewage (Thim chhu and
Amo chhu)
114
Goal
Examine potential
industrial or
sewage impacts
Pa chhu
(agriculture)
Amo chhu (urban)
None for agriculture input
Petr, 1999 for Amo chhu
* Additional sampling on future development sites will contribute to understanding variability in unregulated rivers
long-term study site should be selected at an area with good accessibility, and
the upper tributaries of the Wang chhu make the most sense.
It is also necessary to examine sites that are exposed to sewage and
industrial waste, so that an understanding can be developed about potential
future impacts associated with expanding stresses (Table 3-11).
It may also be necessary to take into consideration the wide changes in
water temperatures between north and south or rivers at higher and lower
altitudes. This may be a factor that results in different fish communities even
along the same river. A provisional line depicting warm and cold water has been
shown (Figure 3-15), but the line does not take into consideration the low rivers
which are also warm above the line. Identification of divisions among fish
communities due to water temperature or altitude may be refined during
subsequent sampling.
Baseline fish community surveys are important for Bhutanese rivers as the
community structure of fish in these rivers remains unstudied. These baseline
studies can be used to identify the types of fish present in the system (seasonal
or non-seasonal), the types suitable for monitoring studies (sentinel species),
and the selection of reference sites. Community studies may involve using
various means to catch fish and techniques for monitoring studies may be
refined during these studies for different rivers.
In monitoring studies, it is important to study the residency of the fish to
make sure they are not moving between affected and reference sites
(Munkittrick et al., 2000). In the case of Thim chhu (Figure 3-15), monitoring
115
Key
Proposed Fish
Sampling Sites
Large Hydropower Sites (2012)
Mines (Gypsum, coal,
dolomite, marble, slate,
limestone, talc, quartzite)
Large Hydropower Sites (2017)
Cement Factories
Food Processing
industries (Fruit
products, distilleries,
dairies, beverages,
etc)
Water and Sewage
Treatment Plants
Large Hydropower Sites (2023)
Major towns with road access
Ch
hu
Mo
Roads
Chemical Industries
(Calcium Carbide,
Ferrosilicon, candle,
plastic, polythene,
etc)
Ch
hu
Ph
o
Hydromet Water Sampling
Stations
Rivers
e
Ch
hu
Da
ng
G
hu
Ch
G1
Pu
na
Tsang Chhu
H
na
Ma
s
C
Chhu
hu
Ch
u
Wang
h
Ch
C1
E
D
F
F
hu
Ch
o
Am
Chh
u
B1
D
e
gd
an
u
hh
C
A1
B
Warm Water
E
Baso
u
Chh
M
A
E
r
ka
am
Ch
DoChhu
A2
Ha
Cold Water
D
F
Da
ng m
m
A
E
S
hu
Ch
116
W
A
ri
Ku
i
Th
Pa
N
Chhu
50 km
Figure 3-15 Proposed fish sampling sites and location of current and proposed development
H
Chhu
Ama
Large Hydropower Sites (2006)
e
er
Ny
studies between site A1 (effected by urban and sewage effluent) and site A
(reference site above settlement) may yield inconclusive results if fish moved
between the sites due to absence of barriers. In this case it may be necessary
to study the residency of fish through techniques such as mark and recapture
techniques or by using stable isotope analysis to identify residency issues.
3.4.1 Development of Methods and Approach
The top priority for sampling will be conducted on the Wang chhu river
system. The Wang chhu is probably one of the most developed rivers and is
undergoing further development at the present time. The Wang chhu river
system is made up of three main tributaries, the Thim chhu, Pa chhu and the Ha
chhu. All the tributaries and the main river are in turn fed by many smaller rivers
and streams offering good fish spawning habitat. A detailed study was
conducted to survey the water quality and status of fish populations in these
rivers in 2001 (NWWFCC, 2001). Although observations were made by the
study team regarding water quality and the occurrence of illegal fishing, the
team conducted sampling entirely with throw/cast nets, which isn’t suitable for
fishing in these types of rivers. Therefore, the population survey of fish would be
inconclusive.
Initial sampling would involve refining fish sampling techniques in these
rivers with the use of various methods such as long-lines, angling, electrofishing and gill netting in some parts of the rivers for community surveys. Angler
117
surveys should also be considered for increasing sample sizes, as information
on length, weight and age could be easily obtained.
3.4.2 Baseline Data for Reference Sites
Multiple sites can be selected on the Wang chhu river system. Munkittrick et
al. (2001) notes that selecting multiple reference sites can strengthen the study
by improving the understanding of differences among reference sites outside
the influence of stress. Multiple reference sites on the Wang chhu river will be
selected upstream of development and urban settlements (Figure 3-15, Site A)
based on prior knowledge of developments on the rivers. As there are no
barriers restricting fish movement, it may be necessary to understand how far
fish move within the system by mark-recapture methods and stable isotope
methods. Use of various types of fishing methods will be necessary to
understand the community composition and structure in these rivers. The
NWWFCC (2001) survey was able to confirm only two types of fish, the brown
trout (Salmo trutta) and the snow trout (Schizothorax progastus). Iterative
sampling during all seasons have to be initiated to understand the life-history
pattern of these fish and to know if there are occurrences of other fish in the
system, as well as their life history.
The comparison of reference sites on Thim chhu, Pa chhu and Ha chhu will
yield important information on differences among sites and rivers on the same
system.
118
3.4.3 Among River Reference Comparisons
There is the possibility to sample upstream areas of all major river systems,
upstream from existing and potential developments, to collect comparative
information. Sites that are comparable to the Wang chhu (Sites A) could be
selected in the upper reaches of the Mo chhu, Mangde chhu, Changku chhu
and Dangme chhu (sites D, E, F and H; Figure 3-15) to assess inter-river
differences in fish community composition among the systems. It may be
possible to detect differences between Wang chhu, which experienced repeated
brown trout introductions, and some of the other rivers, which may have native
fish populations.
3.4.4 Altitudinal Reference Sites
Altitudinal comparisons can be made among rivers on the same latitude
using GPS navigation. The most powerful sampling designs are designs that
can sample the same sites before and after developments occur (Environment
Canada, 2005a), and future hydroelectric developments will occur on the Amo
chhu (planned feasibility study 2010), Puna Tsang chhu (Site D; 2011, 2015),
Mangde chhu (Site E; 2013), Chamkhar chhu (Site F; 2019, 2022), and Kholong
chhu (Site G; 2023) (Figure 3-15). Sites should be selected upstream and
downstream of the proposed developments. Baseline data collected prior to
development will be useful in understanding species distribution patterns, and in
helping develop mitigation plans to reduce the impacts of potential
119
developments. Continued monitoring after development at these sites will be
required.
In some cases, road access would currently limit sampling, but sampling
should be initiated as soon as access becomes possible.
3.4.5 Longitudinal Comparisons of Developed Sites
There are existing sites with hydroelectric development on the Wang chhu
(sites A1, B1), Amo chhu (C1) and Kuri chhu (G1). As soon as methods are
developed and refined, sampling should be initiated at upstream and
downstream sites in these locations (Figure 3-15).
3.5
Endpoint Selection
There has been considerable in Canada over the last decade related to
endpoint selection as the environmental effects monitoring (EEM) programs
have developed. EEM programs exist for point source effluents associated with
pulp and paper mills (Walker et al., 2002), metal mining operations (Ribey et al.,
2002), and sewage treatment plants (Kilgour et al., 2005). There has been some
discussion of developing similar monitoring programs for hydroelectric facilities
(Munkittrick et al., 2000), and recent recommendations for monitoring
techniques for species abundance and species composition near hydroelectric
facilities (DFO, 2005).
120
The river systems available in Bhutan offer opportunities for the development
of tiered, and sequential sampling programs. The focus of this study design will
be specifically to understand the impacts of hydroelectric development on
fisheries resources, because hydroelectric development is the biggest potential
impact facing Bhutan’s rivers.
The focus of the study designs for Bhutan need to focus on the specific
stresses associated with development and operation of hydroelectric facilities.
The main impacts of hydroelectric development include changes in quantity,
quality and distribution of fish habitat, shifts in species composition, spawning
failures in shorelines, spawning species affected by drawdowns, initial increases
in productivity, changes in harvesting and use of fish, physical damage to
fisheries resources, confinement and restriction of fish, and changes in
migration patterns and access to habitat, with a fragmentation of populations
(Table 3-12).
Fish populations can show a variety of responses to these kinds of stresses,
and these have been analyzed and summarized by Munkittrick et al. (2000).
The responses associated with a hydroelectric development would usually be
confined to impacts on food and habitat, and would be analogous (depending
on the species) to exploitation responses (increased food), recruitment failure
(disruption of spawning habitat) and food limitations (loss of food resources)
(Table 3-13).
121
Table 3-12
Potential stresses associated with hydroelectric development (created from Greig et al., 1992; CEA,
2001; DFO, 2005)
Potential
Development
Action
Reservoir
clearing
Reservoir
flooding
Potential Stress
122
Deforestation, erosion, decomposition of waste
plant material, exposing soils
Change in depth, morphometry, erosion and
sedimentation, potential mobilization of mercury,
changes in ground water reserves, changes in
primary production and energy flow
Transmission Deforestation, road access
line
construction
Road
Deforestation, road access
construction
Construction Changes in access, water use and recreational
camps
fishing
Extraction of Erosion, sedimentation
construction
materials
Dam
Redistribution of energy, change in flow, change
operation
in temperature, nutrients and sediments
Turbines,
Changes in water velocity, oxygenation
spillways
Diversions
Changes in water depths, velocities,
Fish
passage
Potential Impact
Changes in habitat
Changes in habitat, shifts in species
composition, shoreline spawning affected by
drawdowns, initial increase in productivity
Changes in habitat and harvesting of fish
Changes in habitat and harvesting of fish
Potential impacts on fish populations
Impacts on habitat, feeding
Changes in quantity, quality and distribution
of fish habitat,
Physical damage to fisheries resources,
confinement and restriction of fish
Changes to habitat
Changes in migration patterns and access to
habitat, fragmentation of populations
Table 3-13
Generalized
Pattern
Generalized response patterns of fish populations to changes in populations (from Munkittrick et al.,
2000)
Cause of Changes
Follow-up study
Age
Distribution
Energy
Utilization
Energy
Storage
123
Exploitation
Decreased competition between
adults associated with mortality or
eutrophication
Examine food resource
availability and population density
Shift to
younger
Increased
Increased
Recruitment
Failure
Shift to older age classes associated
with decreased reproductive success
Detailed examination of spawning
habitat, utilization and
reproductive development
Shift to older
No change
No change
Multiple
Stressors
Simultaneous impacts on food
availability and reproductive success
Detailed studies of reproductive
development and food resources
Shift to older
Decreased
Decreased
Food
Limitation
Increased competition associated with
increased reproductive success or
decreased food availability
Examine food resource
availability and population density
No change
Decreased
Decreased
Niche Shift
Modest increase in competition for
forage base
Examine food base and
competition aspects
No change
Decreased
No change
Metabolic
Redistribution
Inability to maximally utilize available
food resources
Detailed physiological studies of
energetics
Shift to
younger
Mixed
Mixed
Chronic
Recruitment
Failure
Shift to small population of older
individuals
Detailed study of reproductive
performance
Shift to older
Increased
Increased
or
decreased
Null response
No obvious changes
Check population size data to see No change
No change No change
if carrying capacity of the system
has changed
A shift in age distribution can be indicated by mean age or larger samples for ages of the population. Energy utilization can be reflected in
growth rate, reproductive rates or age at maturity. Energy storage can be reflected in condition factors, liver size or in lipid storage levels.
The type of recruitment failure associated with hydroelectric development
would either be because of dewatering of nearshore spawned eggs, or blockage
of migratory routes and access to spawning sites. Both recruitment failure and
increased productivity and habitat result in the same kinds of changes in fish –
there are fewer fish and more resources so the fish grow faster, reproduce
more, are fatter (higher condition) and mature younger (Munkittrick et al., 2000).
The patterns can be differentiated by an increase in the abundance of younger
fish for increased habitat, and a decrease in terms of recruitment failures. Food
limitation reduces the growth rates of fish, and the fish have lower condition.
The expected stresses affect the abundance, diversity of fish species, age
distributions and growth. The impacts will be associated with habitat alterations,
changes in productivity and in sedimentation. So the main types of responses
that should be associated with hydroelectric development would be relatively
easy to detect during standardized monitoring by measuring relative species
abundances, growth rates, age distributions and condition (a function of length
and weight of fish).
Greig et al. (1992) summarized the specific information needs related to
hydroelectric development as: a) understanding distributions and abundance of
fish species in the region, b) determining baseline fish habitat needs, including
information on temperature, substrate composition, depth, cover, oxygen, pH,
suspended solids and food availability, c) predicting changes in habitats
associated with development – information on flow, water quality, and sediment
124
transport, and d) developing models that predict impacts of habitat change on
changes in fisheries resources.
The sampling program should also include information on water quality,
temperature, sediment load, and mercury, which would all be expected to be
affected by hydroelectric development. Baseline surveys of other heavy metals
should also be investigated in water samples. A key issue will also be the flow
of energy, and the mobility of fish, which can both be tracked using stable
isotopes (Gray et al., 2004; Cunjak et al., 2005). The fish issues of importance
will be parameters that will respond to habitat, movements and spawning and
abundance (Table 3-14).
The key aspect of information that will need to be developed once sampling
begins in Bhutan will be the measurements that will be used to document
growth and energy use in fish. The next chapter will examine these issues
using fish collected from the Saint John River near hydroelectric developments.
3.6
Selection of Sentinel Species
The life-history characteristics and biology of fish species can dramatically
affect their suitability as sentinel species for monitoring programs (Munkittrick et
al., 2000). A long-lived species that does not mature sexually until they are 15
to 20 years old, and spawns only every 2 to 3 years, would not be as sensitive
to impacts associated with reproductive toxicity as one that matures rapidly, has
a high fecundity, and spawns regularly. The main factors for selecting any
125
sentinel species are that they are present in abundance, they are exposed to
the stressors of interest, and the endpoints that are desired can be acquired
(Environment Canada, 1997). For instance, in a non-lethal sampling program, a
fish that can be easily aged (e.g., by scales or length-frequency analysis) is
more desirable than one that is difficult to age.
Table 3-14
Indicators that should be addressed in the monitoring program
(adapted from Ribey et al., 2002)
Concern
Endpoints
Community
Community
composition
Population
Abundance
Exposure/
Residency
Fish
usability
Indicators
(historical data)
Presence/absence
Abundance of
species
Rare/endangered
species
Abundance
Growth
Reproduction
Initial
Monitoring
Relative
abundance
CPUE* of
species
Periodic
Monitoring
Size vs. Age
Average age
Relative year
class strength
Size vs. Age
Average age
Relative year
class strength
Health
Condition
Physical
abnormalities
Condition
Factor
Physical
abnormalities
Stable isotopes
Contaminant
levels
Metals levels in
tissues
Tissue
concentrations
of mercury
Condition
Factor
Physical
abnormalities
Stable
isotopes
Tissue
concentration
s of mercury
* CPUE: Catch Per Unit Effort
126
For fish that are abundant, can be measured, and are exposed, there are a
variety of other life-history characteristics that are important for sensitivity.
These include longevity, food preference, reproductive investments and growth
rates, and spawning time (Table 3-15). The factors need to be examined sitespecifically for study designs. For Bhutan, and for a non-lethal sampling
program, response time and sensitivity will be shorter for a short- to mediumlived species. In very old fish, aging from non-lethal structures becomes more
difficult as growth slows in older fish.
Capture success for non-lethal sampling may be higher for piscivorous fish,
as angling success will be higher, although these species commonly have a
larger home range. It will be useful to examine multiple species; the Canadian
Environmental Effects Monitoring (EEM) program recommends at least two
species (Environment Canada, 2005).
Fish with a high reproductive rate and early maturity will respond more
quickly to changes in energy use. With concerns about dewatering associated
with fluctuating flows, it will be useful to use a fish that spawns nearshore as at
least one species. Fish with a fast growth rate will be easier to age, so fish with
a larger size and a lifespan of <10-15 years would be preferred for at least one
sentinel species.
127
Table 3-15
Characteristics
Sentinel species characteristics for optimizing effects-driven assessment of aquatic environmental
health using fish populations (modified from Munkittrick et al., 2000)
Fisheries Health
Point
Non-point
Human
Health
Comments
128
Source
Source
Residency (in
absence of
barriers)
Local
Wide
ranging
Issuespecific
For non-point source impacts, need a species that will integrate the signals from
the area.
Abundance
High
High
Issuespecific
For human health, there may be local concerns associated with food preferences
and consumption that outweigh all other factors.
Longevity
Shortmedium
Shortmedium
Long
For fisheries health issues, long-lived species will decrease the likelihood of
detecting changes. For human health, long-lived species increase the body
burdens and possible consequences of exposure.
Food
preference
Benthic
Issuespecific
Piscivorous
For human health, want a species that is at the top of the food chain. For other
issues, this would be associated with (usually) increased mobility.
Fecundity and
growth rate
High
High
Low
High energetic requirements are preferred, so that changes in food availability or
quality will be detected quickest. For human health, retaining body burdens
by slow growth and reproduction would be preferred.
Age to
maturation
Short
Short
Long
For impacts on fisheries health, species that need energy for initiation of spawning,
while retaining needs for fast growth will show impacts sooner; for human
health, delayed maturity reduces the clearance of contaminants in females
associated with spawning.
Spawning time
Sitespecific
Sitespecific
Sitespecific
The relationship between exposure and spawning time will vary with the issue. In
prairie systems, spring spawning fish develop eggs over-winter, during
maximum exposure from point-sources. In other systems, maximum
exposure occurs during the late summer or fall.
Food chain
involvement
Yes
Yes
Yes
Always want a species with an aquatic-based diet, and not one depending
predominantly on terrestrial-based foods.
Spawning time is a site-specific and issue-specific criterion. As mentioned
above, a fish that spawns near-shore would be preferred in at least one species.
The preferred sampling time is March to May (Table 3-15), so selecting a fish
species that is in the process of investing energy in reproductive development
would be sampled. It is easiest to detect disruptions of food availability during
this time period. An exception would be species for which young-of-the-year
could be easily sampled prior to the onset of the monsoon season’s high
turbidity and flows.
As there is very little baseline data available on Bhutan’s fish species, the
sentinel species for monitoring studies should be selected through initial
community surveys. This is similar to the pre-design sampling component of the
EEM programs in Canada, where the focus of the community data is the
determination of potential sentinel species and relative abundances. Data on
abundance from catch is highly variable (see Munkittrick et al., 2000), and are
difficult to use for decision-making.
The usefulness of small-bodied fish in monitoring assessments has been
shown in studies conducted on the Saint John River in Canada (Gray et al.,
2002). There is a lack of knowledge on occurrence of small-bodied fish in
Bhutanese rivers. Community surveys using different techniques could yield
information on existence of such small bodied fish and their life history could be
looked at for monitoring purposes.
129
3.6.1 Life History Characteristics of Native Species
Bhutan currently lacks any detailed survey and baseline information on the
distribution and abundance of its aquatic fauna. The current knowledge of fish of
Bhutan is a documented list of 41 species found in rivers and lakes of southern
Bhutan (Day, 1873; Dubey, 1978; Dhendup and Boyd, 1994; Shrestha, 1998;
Petr, 1999). This survey used chemical sampling (Petr, 1999), which is not
suitable in the fast-moving rivers in the North-South Valleys. Most of the
species found in Petr’s (1999) survey are warm-water species which may not be
present in the hydroelectric development area.
There are no background data on fish in the North-South Valleys other than
the survey conducted by NWWFCC (2001). They found snow trout and brown
trout in the Wang chhu system. From that study, snow trout have a ventral
mouth, a long digestive tract (2.5 X body length) and stomach contents of algae
and some aquatic insects. Brown trout stomach contents included aquatic
insects, small crustaceans and small fish (NWWFCC, 2001). The current
importance of the aesthetic value placed on snow trout by the government and
communities (NWWFC, 2001) may make it a possible candidate for sentinel
species after its abundance, mobility and response to stressors are known.
A detailed survey is needed to identify species which may be suitable as
sentinels. Snow trout may not be an ideal candidate species. They spawn in
September or October, and migrate to small tributaries. Although the migration
means that they may be captured in higher numbers at spawning time, their
growth and reproductive characteristics will be a function of the location where
130
they are resident. Detailed studies would need to be conducted on the home
range and behaviour of the species to understand its suitability as an indicator.
However, because of its high aesthetic value, it should be part of the monitoring
program. It is assumed that the information integrated by the trout would
encompass a relatively large geographic area, but they would be sensitive to
issues surrounding mobility and access to limited habitats.
Local community and government concerns also sometimes play a role in
indicator selection. However, stakeholders may not always select the species
that are the most sensitive or responsive to changes. One criterion that is
important is the presence of rare, threatened or endangered species. The
Bhutanese government has shown concern about the decreasing population of
snow trout (NWWFCC, 2001). It also stopped stocking brown trout in Wang
chhu based on its possible effect on the snow trout population. Evaluation of
performance and recruitment data of specific fish species on each river will be
necessary to determine the state of the population. Community surveys on
selected sites can give a clear picture of the status of fish populations in rivers
of Bhutan and it may be possible to identify any endangered species.
3.6.2 Sample Size Requirements
The Canadian EEM program uses a minimum sample size of 20 adult males
and 20 adult females for monitoring (Environment Canada, 2005a) and a
sample size of 100 for non-lethal estimates of size distributions (Environment
Canada, 2005b). If back-calculations of growth are used, sample sizes need to
131
focus on relatively large numbers of fish (n=12) of a single cohort to increase
the power of comparisons between sites (Ruemper, 1998).
Sampling designs are better if they are based on local information, but there
are no baseline data available for any species in Bhutan other than for the
ranges of length of snow trout and brown trout captured by cast-netting
(NWWFCC, 2001). Sampling size calculations require information on variability,
power (1-β), levels for statistical significance (α) and effect size. Variability
information is not available for Bhutanese species. The Canadian EEM program
recommends that β and α levels be set equally (0.05 or 0.10) (Environment
Canada, 2005a), and recent advice for effect sizes recommends goals of
detecting a difference of 25% for growth and 10% for condition (Munkittrick et
al., 2006).
3.7
Final Study Design: A Fisheries Assessment Program for Bhutan
The lack of any existing monitoring program and lack of any data on existing
fish populations have increased concerns about fishery resources in Bhutan.
The following study design meets the criteria set out in this thesis.
3.7.1 Schedule of Sampling
A preliminary sampling schedule has been framed depending on the
importance placed on the phase of development on the rivers (Table 3-16). The
schedule takes into consideration current developments and known potential
132
Table 3-16
Sample sites and schedule for studies on Bhutan’s rivers (refer to
2.16 for site locations),
lethal sampling
Site
A
River
Thim chhu,
Pa chhu, Ha
chhu
Site Type
Reference sites,
(upstream of
settlements and
development)
A1
Thim chhu
Sewage effluent &
below urban area
A2
Pa chhu
Below agricultural
area
B
Wang chhu
Reference site
B1
Wang chhu
Below dam site
C
Amo chhu
Reference site
C1
Amo chhu
Sewage effluent &
below urban area
D
Puna Tsang
chhu
Baseline community
survey, future
development
E
Mangde chhu
Baseline community
survey, future
development
F
Chamkhar
chhu
Baseline community
survey, future
development
G
Kuri chhu
Reference site
G1
Kuri chhu
Below dam site
H
Dangme chhu
Baseline community
survey
monitoring studies
2007
133
2008
2009
2010
future developments affecting the river systems of Bhutan. The schedule may
be altered and refined as and when necessary based on urgency due to
unforeseen development during the designing process or during the study
period. In monitoring studies, iterative follow-up studies can be conducted to
verify conclusions from earlier studies.
3.7.2 Selection of Species
Much of the validity of monitoring results is based on the choice of sentinel
species. The potential sentinel species for monitoring purpose must be selected
correctly during the initial community baseline studies. The evaluation of the
requirements of its responsiveness to stress, site fidelity and other life-history
characteristics may be further refined during iterative follow-up studies. To get
detailed and complete performance data on the fish it is necessary to lethally
sample the fish on the selected sites until baseline data have been collected
(Table 3-17).
3.7.3 Sampling Considerations
The initial surveys should be focused on studying the structure of the fish
communities in Bhutan. The studies for building a baseline performance
database would include collecting important information regarding: body weight,
fork length or total length, liver weight and gonad weight. The community
database would include information on distribution and abundance of fish
134
Table 3-17
Recommended fish survey measurements to determine effects in
fish growth, reproduction, condition and survival (adapted from
Ribey et al., 2002)
Measurements
Expected
Precision
Length (fork or total or standard)* +/- 1mm
Total body weight (fresh)
+/- 1.0%
Age
+/- 1 year (10% to be
independently
confirmed)
NA
External condition
Recommended Reporting
Individual measurements, mean,
standard deviation
Individual measurements, mean,
standard deviation
Individual measurements, mean,
standard deviation
Obvious abnormalities, prevalence
of lesions, tumours, parasites, etc.
Sex
NA
Male, female, immature
* If caudal fin forked, use fork length. Otherwise, use total length. In cases where fin erosion is prevalent,
standard length should be used
species in the studied sites. Aging structures (scales, opercula, spines,
vertebrae, and otoliths) may also be collected lethally and non-lethally for basic
understanding of the potential for applying aging techniques for monitoring
studies in Bhutan.
The use of scales in back-calculating growth of yellow perch along the Saint
John River has shown that site differences in performance of fish can be
detected non-lethally. Aging and back-calculating growth of fish can give
important information on effects of development on fish population on a
chronological basis. The effectiveness of aging techniques of fish selected for
monitoring should be considered for detecting effects of developments on fish
populations in the rivers of Bhutan. The available non-lethal aging techniques
for monitoring fish performance have significant value as they comply with the
conservation principles of the government. Other non-lethal methods such as
135
site comparison of body size can also yield important information on
performance of fish in a system (Table 3-17).
3.7.4 Monitoring Program
The underlying significance of this research lies in its contribution toward
development of non-lethal techniques for ecological studies. Non-lethal
techniques are increasingly gaining importance in ecological field studies due to
their adherence to conservation policies. This research will promote
understanding of important aspects of fish growth characteristics upstream and
downstream of dams. The knowledge of detailed life-history characteristics of
fish in affected systems is vital for identification of effective mitigation measures.
In addition, the project will assist in delimiting the impacts of hydroelectric dams
from those of other stressors caused mainly by discharge of various effluents in
the Saint John River system.
There are a number of ways to examine size of fish that will be important to
evaluate effectiveness of a non-lethal sampling program: size of fish captured,
size-at age, length-frequency, and back-calculations of the rates of fish growth.
The sampling program will strengthen Bhutan’s capability to monitor and
manage its fisheries resources during the next phase of development.
It will be important to coordinate essential information on water flows, water
chemistry, temperature, flow data and the fisheries assessments. Many of
these functions currently rest in different government departments, and
136
discussions will need to take place regarding the best mechanism to coordinate
this information.
3.8
Conclusion
The primary objective of the thesis was to develop a framework for a fish
monitoring program for Bhutan that could be used to evaluate potential impacts
of hydroelectric development on Bhutan’s river systems. The study reviewed
different growth measurements using yellow perch collected on the Saint John
River, in New Brunswick, Canada. Obvious differences in performance of fish
were detected, and were consistent with other ongoing studies in the areas
using other fish species and other parameters.
The comparisons of growth measurements will need to be repeated using
Bhutanese fish species, as the optimal measurement for growth may be
different for different species. Bhutan’s geology, physical structure, local
climate, hydrogeology, industrial development, and water chemistry were
reviewed as they place restrictions on potential study designs. Potential study
sites were selected, the sampling schedule was evaluated and a review of
impacts examined potential endpoints for a monitoring program.
There is not very much information on fish species distributions, abundances
and biology in Bhutan’s North-South Valleys, where most of the hydroelectric
development will take place. A priority has been placed on developing some of
the background information, and on conducting comparative sampling projects
137
within developed rivers, on undeveloped rivers, and during the development
phases at proposed sites.
138
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5
Appendix A
Summary of background information on species found in Bhutan
153
Table 5-1
Life-history characteristics for fish species of Bhutan: most information collected from Fishbase–
www.fishbase.org and Petr, 1999 (* valid scientific name from Fishbase)
Species
Food
Schizothorax progastus
Zoobenthos, algae, aquatic
plants, fish eggs/larvae
Schizothorax molesworthi
Schizothorax richardsonii
154
Acrossocheilus
hexagonolepis
*Neolissochilus
hexagonolepis
Algae, aquatic plants and
detritus
Zoobenthos, phytoplankton,
plants, insects, crustaceans
Tor tor
Barilius barna
Barilius bendelisis
20.5 (SL)
60.0
120.0
Spawning
Temperature
preference
Present in study
areas
September
to October
Cold
Subtropical
Cold
Breeds upstream,
benthopelagic,
potamodromous
Benthopelagic
Spawns upstream
Warm,
Tropical
Migrates upstream
during spawning
Warm,
Tropical
Warm
Benthopelagic,
potamodromous
Benthopelagic,
potamodromous
Warm
Moves upstream
during rainy
season,
Benthopelagic,
potamodromous
Benthopelagic
March to
May and
September
to October
April to
October
(peak
August to
September)
12.4 (SL)
Crossocheilus latius
Tor putitora
Tail
Length
(cm)
50.0
Fish, zooplankton, dipteran
larvae, plant matter
Juveniles – plankton
Plankton, chironomid
larvae, water beetles,
crustaceans
275.0
Nekton, insects, fish
15.0
52.0
(150 cm
reported)
22.7
March to
September
Warm,
Tropical
Warm
Benthopelagic,
potamodromous
Barilius bola
*Raiamas bola
Puntius macropogon
(Misspelling for Puntius
micropogon)
*Hypselobarbus
periyarensis
Puntius sophore
Puntius ticto
155
Puntius titius
*Puntius chola
Cirrhinus lata ??
Barbus spp. ??
Labeo dero
*Sinilabeo dero
Crustaceans, insects,
plankton
Worms, crustaceans,
insects, plant matter
Detritus
Labeo dyocheilus
Labeo pangusia
Garra annandalei
Garra gotyla gotyla
Danio aequipinnatus
Danio dangila
Brachydanio rerio
*Danio rerio
Botia Dario
Semiplotus semiplotus
*Cypribion semiplotum
Algae, diatoms
Algae, plants, detritus
Exogenous insects, worms,
crustaceans
Worms, small crustaceans,
insect larvae
35.0
Warm
50.0
Warm
18.0
10.0
Warm,
Tropical
Warm
15.0
Warm
75.0
May to June
Warm
Warm
Warm,
tropical
Dermersal,
potamotromous
Benthopelagic
Benthopelagic,
amphidromous
Benthopelagicm
potamordomous
Benthopelagic,
potamodromous
90.0
Warm
90.0
Warm
23.0
14.5
15.0
Warm
Warm
Warm
Hill streams,
migrates to warmer
waters, shallow
Benthopelagic,
potamodromous
Benthopelagic,
potamodromous
Benthopelagic
Benthopelagic
Pelagic
8.3 (SL)
3.8
Warm
Warm
Benthopelagic
Benthopelagic
15.1
60.0
Warm
Warm
Demersal
Benthopelagic
Rasbora daniconius
Noemacheilus botia
*Acanthocobitis botia
Nekton, zoobenthos,
zooplankton, fish,
crustaceans, insects
Zoobenthos, insects
Batasio batasio
Mystus bleekeri
Mystus vittatus
Nekton, zoobenthos, fish,
crustaceans, insects
Ompok pabda
Bagarius bagarius
156
Nangra punctata
*Gogangra viridescens
Xenentodon cancila
Channa gachua
Channa striatus
*Channa striata
Badis badis
Nandus nandus
Mastacembelus armatus
Nekton, zoobenthos, fish,
crustaceans, insects
Nekton, zoobenthos, fish,
crustaceans, insects
Nekton, fish, insects
Detritus, nekton,
zoobenthos, zooplankton,
herps, crustaceans, insects,
worms,
Zoobenthos, crustaceans,
insects, worms
Nekton, zoobenthos, fish,
insects
Nekton, plants, zoobenthos,
zooplankton, fish,
crustaceans, insects,
worms
15.0
Warm
Benthopelagic,
potamodromous
Warm
Dermersal
10.0
15.5
Warm
Warm
21.0
Warm
Demersal
Demersal,
potamodromous
Demersal
30.0
Warm
11.0
200.0
May to June
100-150
eggs
Before flood
Warm
8.5
Warm
40.0
Warm
20.0 (SL)
100.0
March to
August
June to July
8.0
Warm
Warm
Demersal,
potamodromous
Benthopelagic,
potamodromous
Demersal,
potamodromous
Pelagic,
amphidromous
Benthopelagic,
potamodromous
Benthopelagic,
potamodromous
Warm
Benthopelagic
20.0
300 eggs
Warm
Benthopelagic
90.0
April to June
Warm
Demersal,
potamodromous
Table 5-2
Life-history characteristics for introduced fish species of Bhutan: most information collected from
Fishbase– www.fishbase.org and Petr, 1999 (* valid scientific name from Fishbase)
Species
Salmo trutta fario
???
Salmo trutta trutta
157
Cyprinus carpio
carpio
Catla catla
Cirrhinus mrigala
*Cirrhinus cirrhosus
Labeo rohita
Aristichthys nobilis
Ctenopharyngodon
idella
Hypophthalmichthys
molitrix
Food
Spawning time
Nekton, zoobenthos, fish, herps,
insects, mollusks, benthic
invertebrates
Nekton, zoobenthos,
zooplankton, fish, insects,
terrestrial invertebrates,
crustaceans, mollusks, worms
Detritus, nekton, plants,
zoobenthos, zooplankton, fish,
insects, worms
Plants, zoobenthos,
phytoplankton, insects
Detritus, phytoplankton,
zooplankton, crustaceans
Detritus, plants, zooplankton,
invertebrates
Zooplankton
January to May and
October to December
Higher aquatic plants,
submerged grass, detritus,
insects, invertebrates
Plants, phytoplankton
Tail Length
(male/
unsexed)
(cm)
100
Other
information
Demersal, nonmigratory
April to July and July
to November
140
Pelagic,
anadromous
Spring and summer
120
Benthopelagic,
potamodromous
May to September
182
Benthopelagic,
potamodromous
Benthopelagic,
potamodromous
Benthopelagic,
potamodromous
Benthopelagic,
potamodromous
Demersal,
potamodromous
100
April to August
200
April to June
112
April to September
150
April to September
105
Benthopelagic,
potamodromous
CURRICULUM VITAE
Candidate’s Full Name: Karma Tenzin
Universities Attended
1997- 2000 Sherubtse College, University of Delhi, Tashigang, Bhutan (B. Sc.,
2000)
Publications
Tenzin K, Dorji L, 2000. A Study of Butterfly and Moth Species in Eastern
Bhutan. Sherubtse College, Tashigang, Bhutan
NWWFCC. 2001. Survey on water quality and status of fish in the rivers of
Thimphu, Paro and Haa Dzongkhags. Report. National Warm Water Fish
Culture Centre, Ministry of Agriculture, Royal Government of Bhutan.
Gelephu. 35p
Conference Presentations
Tenzin K, 2006, Potential developmental challenges in rivers of Bhutan. Linking
Watersheds Workshop: February 26- March 1, Fredericton, New
Brunswick
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