COUPLED HYDROLOGIC AND BIOGEOCHEMICAL RESPONSE TO INSECTINDUCED FOREST DISTURBANCE by Joel A. Biederman A Dissertation Submitted to the Faculty of the DEPARTMENT OF HYDROLOGY AND WATER RESOURCES In Partial Fulfillment of the Requirements For the Degree of DOCTOR OF PHILOSOPHY WITH A MAJOR IN HYDROLOGY In the Graduate College THE UNIVERSITY OF ARIZONA 2013 2 THE UNIVERSITY OF ARIZONA GRADUATE COLLEGE As members of the Dissertation Committee, we certify that we have read the dissertation prepared by Joel A. Biederman entitled “Coupled hydrologic and biogeochemical response to insect-induced forest disturbance” and recommend that it be accepted as fulfilling the dissertation requirement for the Degree of Doctor of Philosophy. _______________________________________________________________________ Date: September 24, 2013 Dr. Paul Brooks _______________________________________________________________________ Date: September 24, 2013 Dr. Shirley Papuga _______________________________________________________________________ Date: September 24, 2013 Dr. Thomas Meixner _______________________________________________________________________ Date: September 24, 2013 Dr. David Gochis Final approval and acceptance of this dissertation is contingent upon the candidate’s submission of the final copies of the dissertation to the Graduate College. I hereby certify that I have read this dissertation prepared under my direction and recommend that it be accepted as fulfilling the dissertation requirement. ________________________________________________ Date: September 24, 2013 Dissertation Director: Dr. Paul Brooks 3 STATEMENT BY AUTHOR This dissertation has been submitted in partial fulfillment of the requirements for an advanced degree at the University of Arizona and is deposited in the University Library to be made available to borrowers under rules of the Library. Brief quotations from this dissertation are allowable without special permission, provided that an accurate acknowledgement of the source is made. Requests for permission for extended quotation from or reproduction of this manuscript in whole or in part may be granted by the head of the major department or the Dean of the Graduate College when in his or her judgment the proposed use of the material is in the interests of scholarship. In all other instances, however, permission must be obtained from the author. SIGNED: Joel A. Biederman 4 ACKNOWLEDGMENTS I would like to thank the students, collaborators and mentors that contributed many hours of effort to this project. In the field Traeger Meyer and Nick Ludolph of Colorado University braved both winter and summer at 10,000 feet to keep the field sites running. Meanwhile Allison Peterson, Gary Gold, Chris Ferlin and Shane Clark of the University of Arizona braved the Tucson summer to analyze many hundreds of water samples. David Reed, Gary Bolton, Scott Peckham and Lisa Philander of the University of Wyoming made it possible to conduct research at a remote mountain site. Thanks to David Gochis and Ethan Gutmann of the National Center for Atmospheric Research for hospitality and training during my summer visits to NCAR. Thank you to Drs. Adrian Harpold, Brent Ewers, Elise Pendall, Peter Troch, James Shuttleworth, Hoshin Gupta and Ty Ferre for academic and research guidance. The following funding sources made it possible for me to complete this work by either providing scholarship and fellowship funds, or funds for field equipment and analytical services: National Science Foundation, Water Sustainability Program Graduate Fellowship, Science Foundation Arizona, Institute of the Environment, the Department of Hydrology and Water Resources, and the Graduate Student and Professional Council. I would like to thank my advisory and technical committee, Dr. Thomas Meixner, Dr. Shirley Papuga, Dr. David Gochis, and of course, my major advisor, Dr. Paul D. Brooks. Thank you for your guidance and friendship. This has been a transformative experience. 5 DEDICATIONS Thank you: Joel Cahoon, my undergraduate advisor, for training me rigorously and supporting me endlessly in all aspects of life. Warren Jones, undergraduate professor, for teaching me about engineering, life, and especially teaching. My parents Chuck and Loraine: Your endless faith motivated me to earn this Ph.D. at last. My wife, Linda: This research would not have been possible without your support, faith, patience and encouragement. My children Axel and Lucie: You gave up snow and sledding to move to Arizona and help me accomplish this dream. 6 TABLE OF CONTENTS ABSTRACT...................................................................................................................... 11 1. 2. INTRODUCTION ................................................................................................... 13 1.1. PROBLEM STATEMENT ........................................................................... 13 1.2. BACKGROUND .......................................................................................... 14 1.3. DISSERTATION FORMAT ........................................................................ 20 PRESENT STUDY ................................................................................................. 22 2.1. APPENDIX A. MULTISCALE OBSERVATIONS OF SNOW ACCUMULATION AND PEAK SNOWPACK FOLLOWING WIDESPREAD, INSECT-INDUCED LODGEPOLE PINE MORTALITY..................................... 22 2.2. 2.1.1. Study Objective .......................................................................... 22 2.1.2. Major Study Findings and Implications ..................................... 22 APPENDIX B. COMPENSATORY VAPOR FLUX REDUCES WATER FOR STREAMFLOW FOLLOWING SEVERE BARK BEETLE-INDUCED FOREST MORTALITY. ........................................................................................ 24 2.3. 2.2.1. Study Objective .......................................................................... 24 2.2.2. Major Study Findings and Implications ..................................... 24 APPENDIX C. CATCHMENT BIOGEOCHEMICAL IMPACTS OF BARK BEETLE INFESTATION ATTENUATED IN THE RIPARIAN ZONE AND HEADWATER STREAMS .................................................................................... 26 2.3.1. Study Objective .......................................................................... 26 2.3.2. Major Study Findings and Implications ..................................... 26 7 TABLE OF CONTENTS - Continued 3. REFERENCES ............................................................................................................. 28 APPENDIX A: MULTISCALE OBSERVATIONS OF SNOW ACCUMULATION AND PEAK SNOWPACK FOLLOWING WIDESPREAD, INSECT-INDUCED LODGEPOLE PINE MORTALITY................................................................................. 33 Abstract ................................................................................................................... 34 1. Introduction .................................................................................................. 36 2. Methods ......................................................................................................... 39 3. 2.1. Study Sites ................................................................................... 40 2.2. Winter Climate............................................................................ 42 2.3. Intensive Study Plots................................................................... 43 2.4. Snow Surveys at peak accumulation........................................... 44 2.5. Isotopic tracers of sublimation:.................................................. 47 Results ........................................................................................................... 48 3.1. Weather....................................................................................... 48 3.2. Snowfall Interception.................................................................. 49 3.3. Spatial distribution of peak snowpack ........................................ 50 3.4. Comparison of peak snowpack between MPB and Unimpacted 51 3.5. Subcanopy environment.............................................................. 52 3.6. Stable isotope tracers of sublimation ......................................... 53 4. Discussion ..................................................................................................... 53 5. Conclusions ................................................................................................... 61 8 TABLE OF CONTENTS - Continued 6. Acknowledgments ......................................................................................... 62 7. References ..................................................................................................... 63 8. Tables ............................................................................................................ 69 9. Figures .......................................................................................................... 72 APPENDIX B: COMPENSATORY VAPOR FLUX REDUCES WATER FOR STREAMFLOW FOLLOWING SEVERE BARK BEETLE-INDUCED FOREST MORTALITY. .................................................................................................................. 79 Abstract ................................................................................................................... 80 1. Introduction .................................................................................................. 81 2. Study sites ...................................................................................................... 84 3. Methods ......................................................................................................... 85 4. 3.1. Quantification of MPB-driven Forest Mortality ........................ 85 3.2. Local Climate and Soil Moisture Measurements ....................... 86 3.3. Eddy Covariance Vapor Flux Measurements............................. 87 3.4. Streamflow and Groundwater Measurements (MPB site only) .. 88 3.5. Water Balance Quantification .................................................... 89 3.6. Stable Isotope Observations ....................................................... 90 3.7. Computational methods and software ........................................ 91 Results ........................................................................................................... 91 4.1. MPB Infestation .......................................................................... 91 4.2. Local Climate and Soil Moisture ................................................ 92 9 TABLE OF CONTENTS - Continued 4.3. Tower Footprint Water Balance ................................................. 93 4.4. Stable Isotope Indicators of Evaporation ................................... 94 4.5. Catchment Water Balance (MPB Site Only) .............................. 95 4.6. Comparison of Sites and Water Balance Approaches ................ 97 5. Discussion ..................................................................................................... 97 6. Conclusions ................................................................................................. 102 7. Acknowledgments ....................................................................................... 103 8. References ................................................................................................... 104 9. Tables .......................................................................................................... 110 10. Figures ........................................................................................................ 115 APPENDIX C: CATCHMENT BIOGEOCHEMICAL IMPACTS OF BARK BEETLE INFESTATION ATTENUATED IN THE RIPARIAN ZONE AND HEADWATER STREAMS. ..................................................................................................................... 126 Abstract: ................................................................................................................ 127 1. Introduction ................................................................................................ 128 2. Study Sites ................................................................................................... 131 3. Methods ....................................................................................................... 132 3.1. Phsyical Hydrology and Weather ............................................. 132 3.2. Biogeochemical Sampling and Analysis ................................... 133 3.3. Catchment Spatial Analysis and Statistics ............................... 135 10 TABLE OF CONTENTS - Continued 4. Results ......................................................................................................... 135 4.1. Weather and Hydrological Response ....................................... 135 4.2. Unimpacted Biogeochemistry From Uplands to RSS ............... 136 4.3. MPB Biogeochemistry From Uplands to RSS .......................... 138 4.4. Spatial Patterns of Chemistry in Nested MPB Streams............ 140 5. Discussion ................................................................................................... 141 6. Implications and Conclusions .................................................................... 147 7. Acknowledgments ....................................................................................... 148 8. References ................................................................................................... 149 9. Tables .......................................................................................................... 157 10. Figures ........................................................................................................ 160 11 ABSTRACT Forest disturbance is expanding in rate and extent and is affecting many montane catchments critical to water resources. Western North America is experiencing an epidemic of mountain pine beetle (MPB) that has affected 20 million hectares of forest in Canada and the United states. This epidemic may have long-lasting consequences for coupled cycles of water, energy, and biogeochemicals. While impacts of forest disturbance by fire and harvest have been studied for more than a half-century, insectdriven mortality differs from these events in the timing and accompanying biophysical impacts. In this work, we quantified catchment hydrologic and hydrochemical response to severe MPB infestation in a lodgepole pine ecosystem. Observations were organized laterally in a nested fashion from soil observations to nested headwater catchments. Vertical observations encompassed what is often termed the critical zone, from atmospheric interactions at the top of the forest through the ground surface and the rooting zone to the interface with groundwater. We quantified responses manifest in snowpack, the primary hydrologic input to this montane ecosystem, in water partitioning between vapor flux and streamflow, and in biogeochemical patterns across the landscape. Key findings of this study include 1) Loss of shelter from the atmosphere caused compensatory sublimation of snowpack to offset decreased interception losses after MPB-driven canopy loss; 2) Vaporization at multiple scales increased over time and in comparison to control forest, reducing water available for streamflow; 3) Nitrogen (N) concentrations were elevated in hillslope groundwater, but attenuation in the riparian zone protected streams from major N influx; and 4) headwater streams rapidly attenuated 12 dissolved carbon (C) and N inputs. Collectively these results demonstrate compensatory negative feedbacks which help explain the lack of strong response to streamflow and stream chemistry observed in the recent MPB epidemic. 13 1. INTRODUCTION 1.1. PROBLEM STATEMENT A rapid, extensive, and ongoing epidemic of mountain pine beetle (MPB) has damaged forests in more than 20 million hectares of western North America since the mid-1990s (Safranyik et al., 2010; USFS, 2012). Although an extensive body of literature documents hydrological and biogeochemical effects of forest disturbance in headwater catchments, there is a paucity of observational evidence related to mortality that is gradual and initially leaves the forest and soils physically intact. Specifically, it is unclear how: 1) tradeoffs between interception losses and sheltering of snowpack will combine to alter net snowpack accumulation, 2) tradeoffs among reduced interception, reduced overstory transpiration, and increased evaporation will influence partitioning of precipitation between vaporization and water available for streamflow, 3) increased litter inputs, changes to microclimates, and physical hydrologic impacts of items 1) and 2) will alter hydrochemical concentrations in soil water and groundwater, and 4) how the above effects will be propagated downstream from the headwaters toward streams of relevance to water resources. These points are addressed in order to improve current conceptual models regarding forest ecosystem function under insect-driven disturbance and to provide 14 relevant information that can aid in the development of forest and water management strategies in affected regions. 1.2. BACKGROUND Forested montane catchments are critical to downstream water resources and the regulation of biogeochemical fluxes. Research from the last half-century in experimental watersheds has demonstrated that forested watersheds are reliable sources of clean water (Brown et al., 2005). In western North America, much of this water derives from snowmelt, and more than 60 million water users rely on snowmelt as a primary supply (Bales et al., 2006). In recent decades, forest die-off has increased due to increased temperature (Williams et al., 2010) drought (Breshears et al., 2009; Adams et al., 2012; Allen et al., 2010 ), fire, and pathogen infestation (Williams et al., 2013; Huber, 2005; Tokuchi et al., 2004). Western North American forests have suffered extensive tree die-off due to mountain pine beetle (MPB; Dendroctonus ponderoseae) and beetle-associated fungal pathogens (Raffa et al., 2008; Kurz et al., 2008; USFS, 2012). Since forests regulate water partitioning and biogeochemical fluxes, the unprecedented MPB epidemic challenges our ability to predict availability of water and limiting nutrients for ecosystems (Edburg et al., 2012) and the amount and quality of downstream resources (Ellison et al., 2012). Understanding response in headwater catchments and their streams is critical for several reasons. First, headwater streams comprise 86% of total stream length and the majority of shoreline in most drainage networks (Leopold, 1964). Second, headwater 15 streams are dominated by inputs from the hillslopes, and therefore they may be more sensitive to hillslope disturbance. Third, headwater streams are relative hot spots for biogeochemical transformation (McLain et al., 2003) due to their low water velocities, turbulent flow, and high ratio of surface area to volume, all of which promote hyporheic exchange (Peterson et al., 2001). Finally, larger-order streams integrate the response of the headwaters. For example, in the snowmelt-dominated Rocky Mountains, Troendle et al. (2001) found similar fractional flow increases in response to harvest in a basin of 17 km2 and in small headwater catchments. Insect-driven forest mortality may affect hydrology differently from other forest disturbances including non-lethal insect infestation (e.g. Swank, 1981; Bormann and Likens, 1979), harvest (e.g. Bosch and Hewlett, 1982; Jones and Post, 2004; Troendle et al., 2001), ice storms (Houlton et al., 2003; Bernhardt et al., 2003) and fire (e.g. DeBano, 2000). MPB may kill a large fraction of available host trees without immediately changing forest structure and soil hydraulic conductivity (Brown et al., 2010). While subsequent needle drop results in decreased snowfall interception loss (Boon, 2012; Pugh and Small, 2012), compensatory increases to winter snowpack sublimation may negate any change to the volume of snowmelt entering the catchment (Boon, 2012; Biederman et al., 2012). Increased energy inputs to spring snowpack increase melt rates (Boon, 2009; Biederman et al., 2012; Pugh and Small, 2012) which could reduce snowmelt infiltration, advance flow timing, and increase the magnitude of peak streamflow (Pugh and Gordon, 2012). While decreased transpiration could be expected to increase soil moisture and streamflow (Pugh and Gordon, 2012), observations indicate that growing season vapor 16 fluxes remain near to or exceed those of control forests (Brown et al., 2013; Reed et al., 2010; Biederman et al., in review) and that streamflow may decline Somor et al. 2010) Direct observations of response to MPB have been grouped into small-scale response (e.g. scale of plots, trees, and stands of trees) and large-scale response (e.g. records at long-term gauged basins of many square km). Reduced snow interception and transpiration are expected to increase streamflow (Pugh and Gordon, 2012), while increased organic matter decay is expected to increase biogeochemical stream fluxes (Morehouse et al., 2008; Griffin et al., 2011). Plot-scale observations have documented expected biophysical and biogeochemical changes, but there has been little significant change to streamflow or water quality at the larger scales relevant to water resources (Clow et al., 2011; Rhoades et al., 2013). A critical gap exists in our understanding of process changes that have prevented small-scale impacts observed in the uplands from propagating to the watershed scales of water resource relevance. Streamflow response to forest disturbance has been the subject of research for more than a half century (Jones and Post, 2004). However, mountain pine beetle-driven mortality differs in its biophysical impacts from the more well-studied cases of fire and harvest. It kills the majority of host trees but does not remove any biomass or disturb the soils as do both harvest and fire (DeBano, 2000). Further, the majority of disturbance studies have occurred in more humid environments as opposed to the boreal and subalpine zones where the MPB epidemic is concentrated (Raffa et al., 2008). A review of disturbance experiments in 14 experimental watersheds showed a median value of mean annual precipitation of 1450 mm, which is nearly twice as large as the mean annual 17 precipitation at the sites used in the present study (Jones and Post, 2004; Biederman et al., 2012). Streamflow in all seasons is dominated by snowmelt in many of the montane catchments of western North America affected by MPB, and various studies have aimed to quantify snowpack response to forest disturbance (e.g. Connaughton, 1935; Troendle and King, 1983; Golding and Swanson, 1986). Plot-based studies of MPB and control stands have shown either increased snowpack beneath killed trees (Pugh and Small, 2012; Boon, 2012) or no response (Boon, 2012). The prevailing expectation has been that decreased interception would lead to larger snowpack accumulation, eventually driving greater streamflow (Pugh and Gordon, 2012). This interpretation is codified in the structures of some land surface models, where simulated vaporization declines with leaf area index under simulated disturbance, increasing streamflow (Bewley et al., 2010, Pomeroy et al., 2012; Mikkelson et al., 2013). Empirical observations of streamflow following MPB are less clear. Bethlahmy (1974) found a small streamflow increase peaking 15 years after infestation, Potts (1984) observed a small increase immediately, and Somor (2010) reported significantly less streamflow in one catchment and no significant change in seven others. Our inability to explain the variable response in streamflow of gauged basins highlights the need for understanding of underlying process responses in the headwaters. While recent work has sought to quantify individual water fluxes after MPB (Boon, 2012; Pugh and Small, 2012; Brown et al., 2013), we are not aware of any previous studies combining 18 observations of vaporization and streamflow to quantify water balance terms in catchments affected by MPB. Changes in the physical hydrology may combine with a rapid increase in dead organic matter to produce biogeochemical response to MPB disturbance. Recent work on biogeochemical response to MPB has provided conceptual frameworks and initial results to guide ongoing research. Kurz et al. (2008) used a land surface model to predict changes to net biome production of carbon (NBP) over a 14-year period in the region of western Canada most affected by the present MPB outbreak. They reported that during the peak of the epidemic and for several years afterward, the impacted forest was converted from a small carbon sink to a large carbon source. Edburg et al., (2012) suggested that NPB would be depressed for 5-10 years or more following mortality, though they discussed variability related to coupling of biogeochemical and biophysical responses (e.g. snowmelt dynamics, understory growth). Edburg et al. (2012) proposed a variety of possible ecosystem responses to additional nitrogen inputs from decaying plant matter. These include short-term retention by microbial biomass and eventual transfer to new plant growth (Brooks et al., 1998) and the possibility that denitrification (Brooks et al, 1997) or export in solution (Brooks and Williams, 1999) might limit plant growth and NBP in the nitrogen-poor ecosystems typically infested by MPB. Mikkelson et al. (2012) reported increased total organic carbon and production of disinfection byproducts at Colorado water treatment plants with source water from MPB-infested catchments. Clow et al. (2011) found increased soil C and N beneath MPB-killed trees but no changes in C or nitrate at the outlets of catchments with areas of 101-102 km2. Rhoades et al. (2013) 19 attribute the surprising lack of stream nitrate response to a combination of low regional atmospheric N deposition in the Rocky Mountains, patchy and time-varying tree mortality, and compensatory uptake by understory and surviving trees. There is therefore a lack of consensus regarding the fate of increased inputs of C and N. The dichotomy of strong response in uplands and weak response in streams highlights our need to address MPB impacts on catchment biogeochemical cycling across spatial scales from uplands to streams. Evaluating response across the landscape will improve our understanding of how MPB impacts propagate through catchment fluxes and pools. Given the variability of responses reported in the literature, a number of questions arise on the response of headwater catchments to MPB-driven insect mortality: 1) How does canopy loss affect net snowpack accumulation in headwater catchments? 2) How does tree mortality affect partitioning of precipitation into vaporization and water available for streamflow? 3) How do hydrological and other biophysical changes propagate across landscape biogeochemistry from the uplands to the riparian-stream system? 4) How do changes in snowpack, vaporization and hydrochemistry propagate downstream from headwater catchments? To quantify hydrological and biogeochemical response to MPB, we observed a site with heavy MPB infestation and compared it to a similar unimpacted site (i.e. control site). Continuous snow depth observations quantified changes to snow inputs, while 20 distributed snow surveys of peak accumulation determined net impacts. Water partitioning response was quantified using streamflow observations in a catchment water balance as well as eddy covariance vaporization observations in a vertical “1dimensional” water balance framework. Stable water isotopes were used to evaluate abiotic vaporization (i.e. the sum of sublimation and evaporation) at multiple scales. Biogeochemical response was quantified using daily to biweekly sampling in a nested design of soil water, groundwater, riparian groundwater and stream water in catchments of four stream orders. 1.3. DISSERTATION FORMAT This dissertation introduction is followed by a section titled “Present Study”, which summarizes the findings of 3 manuscripts drafted for journal submission. The publications drafted for publication follow the “Present Study” as 3 separate appendices, Appendix A, B and C. The titles and my personal contributions to Appendices A, B and C are: Appendix A: “Multiscale observations of snow accumulation and peak snowpack following widespread, insect-induced lodgepole pine mortality.” My personal contribution was the collection and analysis of the data and publication of a scientific article. This work is accepted by the journal Ecohydrology and although not yet included in an issue, it has been made available online by the publisher at DOI: 10.1002/eco.1342 This work is included in this dissertation in accepted manuscript format, for consistency of style with the other appendices. Wiley Science and Ecohydrology do not require any copyright permissions for inclusion of a published article in the dissertation by the same 21 author as described at http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)19360592/homepage/Permissions. Appendix B: “Compensatory vapor flux reduces water for streamflow following severe bark beetle-induced forest mortality.” My personal contribution was the collection of the streamflow and water isotopic data, analysis of these and eddy covariance data, and generation of a manuscript for publication which is under review at the journal Water Resources Research. Appendix C: “Catchment biogeochemical impacts of bark beetle infestation attenuated in the riparian zone and headwater streams.” My personal contribution was the installation of instrumentation, collection of water samples, data analysis and generation of a manuscript for publication. 22 2. 2.1. APPENDIX A. PRESENT STUDY MULTISCALE OBSERVATIONS OF SNOW ACCUMULATION AND PEAK SNOWPACK FOLLOWING WIDESPREAD, INSECT-INDUCED LODGEPOLE PINE MORTALITY. 2.1.1. Study Objective This study addresses the overarching question: How does insect-induced forest die-off affect peak snowpack and the potential snow water inputs to affected catchments? 2.1.2. Major Study Findings and Implications The major findings of this study are: 1) Snowfall interception declined from 20% of annual snowfall in healthy lodgepole pine forest to a number indistinguishable from zero in grey-phase trees 3-4 years following mortality. 2) There was no significant difference in peak snowpack between healthy forest and MPB-infested forest in either red or grey phases of mortality, indicating that reduced interception losses were compensated by winter sublimation of snowpack from the ground. 3) Stable water isotopes confirmed greater kinetic fractionation of snowpack under MPB forest, confirming increased snowpack sublimation. 4) Solar radiation reaching the snowpack was on average 70% greater in the MPB forest as compared to the Unimpacted forest, while subcanopy wind speeds were relatively similar. 23 5) Peak snowpack in MPB forest showed reduction in the spatial variability associated with interception and shading by trees. This work was unique in surveying snowpack across small headwater catchments as compared to prior work that focused mainly on adjacent plots or stands. These results show that reduced snowfall interception losses may be counteracted by increased sublimation of snowpack on the ground. This contrasts with a common perception that interception is the dominant control on peak snowpack accumulation and that snow reaching the snowpack is relatively immune to ablation. Snowmelt water is the dominant annual input to many montane catchments affected by forest disturbance, and our results help explain why expected streamflow increases have not been reported after nearly 15 years of the current MPB epidemic in the central Rocky Mountains. 24 2.2. APPENDIX B. COMPENSATORY VAPOR FLUX REDUCES WATER FOR STREAMFLOW FOLLOWING SEVERE BARK BEETLE-INDUCED FOREST MORTALITY. 2.2.1. Study Objective This study addresses the overarching question: How does insect-induced forest mortality affect the partitioning of precipitation between vapor losses and water available for streamflow? 2.2.2. Major Study Findings and Implications The major findings of this study are: 1) Net vapor losses increased following MPB-induced forest mortality 2) Streamflow declined in headwater catchments with heavy insect-induced forest mortality 3) A large fraction of the vapor losses occurs during snowmelt, suggesting that abiotic evaporation from wet surfaces plays an important role. 4) Stable water isotopes show greater kinetic fractionation in soil and stream water in MPB-infested catchments, indicating increased abiotic evaporation. 5) Solar radiation reaching the forest floor under grey-phase MPB forest was 300-350% larger during the snow-free period as compared to unimpacted forest. In addition to showing that vapor losses may increase and streamflow may decrease following severe forest mortality, these results demonstrate that abiotic evaporation is more important in hydrological response to forest disturbance than previously reported. This study shows that evaporation of snowmelt water, soil water 25 and stream water may increase sufficiently to collectively offset the reduced transpiration resulting from forest die-off. This result is consistent with our previous analysis showing increased snowpack sublimation during winter (Appendix A), as both sublimation and evaporation represent abiotic fluxes from the subcanopy. Model-based studies of MPB impacts on water balance have generally predicted that decreased transpiration would lead to lower vapor losses and greater streamflow until forest regeneration could make a significant difference. Our results suggest that the land surface models commonly used to evaluate and predict water balance following forest disturbance should include improved representation of abiotic vapor fluxes. 26 2.3. APPENDIX C. CATCHMENT BIOGEOCHEMICAL IMPACTS OF BARK BEETLE INFESTATION ATTENUATED IN THE RIPARIAN ZONE AND HEADWATER STREAMS. 2.3.1. Study Objective This study addresses the overarching question: Where on the landscape does attenuation of dissolved carbon and nitrogen occur in MPB-infested catchments? 2.3.2. Major Study Findings and Implications The major findings of this study are: 1) Soil water concentrations of dissolved organic carbon (DOC) and nitrogen (DON) are relatively similar in MPB-infested and unimpacted uplands 3 to 5 years following infestation. 2) Nitrate concentrations are 1 to 2 orders of magnitude greater in MPB- infested uplands. 3) Both DON and nitrate are elevated in MPB upland groundwater, suggesting significant flushing of N from surface soils has already occurred 3 to 5 years following MPB infestation. 4) Most of the elevated N concentrations in MPB groundwater are attenuated in the riparian-stream system (RSS), while DOC concentrations increase upon entering the RSS. 5) DOC and DON are rapidly attenuated downstream in headwater streams, with 55% and 69% lower concentrations, respectively, within 5 km of flow distance in the channel network. 27 These results fill a critical knowledge gap in our understanding of the locations and spatial scales of C and N attenuation following MPB forest mortality. Existing work has documented increased C and N in the top 20 cm of soils as well as very low response in the chemistry of rivers draining MPB-infested mountains, but here we show that 1) within 3-5 years following infestation, the primary impact is observed to be elevated N in groundwater, 2) both organic and inorganic N are attenuated between hillslope groundwater and the RSS and 3) attenuation of DON and DOC occurs rapidly over just a few km in the headwaters, consistent with the lack of response previously reported for large watersheds. 28 3. REFERENCES Adams, H. D., Luce, C. H., Breshears, D. D., Allen, C. D., Weiler, M., Hale, V. C., Huxman, T. E. (2012). Ecohydrological consequences of drought- and infestationtriggered tree die-off: insights and hypotheses. Ecohydrology, 5(2), 145-159. doi: 10.1002/eco.233 Allen, C. D., Macalady, A. K., Chenchouni, H., Bachelet, D., McDowell, N., Vennetier, M., Cobb, N. (2010). 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Proceedings of the National Academy of Sciences of the United States of America, 107(50), 21289-21294. doi: 10.1073/pnas.0914211107 33 APPENDIX A: MULTISCALE OBSERVATIONS OF SNOW ACCUMULATION AND PEAK SNOWPACK FOLLOWING WIDESPREAD, INSECT-INDUCED LODGEPOLE PINE MORTALITY. Manuscript accepted for publication and published online (2012) but not yet included in an issue of the journal Ecohydrology. The publisher (Wiley) does not require copyright permission for inclusion in a dissertation by the same author, as described at http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)1936-0592/homepage/Permission. Title: Multiscale observations of snow accumulation and peak snowpack following widespread, insect-induced lodgepole pine mortality. Running title: Snowpack following insect-induced pine mortality Authors: Joel A. Biederman1*, P. D. Brooks1, A. A. Harpold1, D. J. Gochis3, E. Gutmann3, D. E. Reed4, E. Pendall5 and B. E. Ewers5 1 SAHRA and Department of Hydrology and Water Resources University of Arizona, Tucson AZ 85721 3 4 NCAR, Boulder, CO 80301 Department of Atmospheric Science and Program in Ecology University of Wyoming, Laramie, WY 82071 5 Department of Botany and Program in Ecology University of Wyoming, Laramie, WY 82071 34 Abstract Seasonal snowpack in forested lands is the primary source of fresh water in western North America, where mountain pine beetle (MPB) infestation has resulted in rapid and extensive tree die-off. Forests significantly influence the amount and spatial distribution of peak seasonal snowpack, but the impacts of large-scale tree mortality on the processes controlling peak snowpack are not well understood. We evaluate the effects of widespread tree mortality on winter snow accumulation and peak seasonal snowpack across multiple spatial scales and several levels of MPB impact in the Central Rocky Mountains. Observations for winters 2010 and 2011 include continuous snow depths in 20 plots, distributed snow surveys at peak accumulation, and climate observations above and below canopy including precipitation, temperature, humidity, wind, and shortwave radiation. Stable water isotopes were observed for fresh snowfall and for snowpack. Plot-scale snowfall observations showed 20 % lower interception (p < 0.05) in greyphase stands (needles lost) than Unimpacted stands. However, distributed snow surveys found no differences in peak seasonal snow water equivalent (SWE) between Unimpacted and grey-phase stands. Water isotopes of snowpack from MPB-killed stands indicated kinetic fractionation; enriched values demonstrated higher winter snowpack sublimation than in Unimpacted forest. Following MPB infestation, reduced canopy sublimation of intercepted snow appeared to be compensated by increased snowpack sublimation, consistent with observations of higher snowpack insolation. Consequently, the effects of widespread tree mortality on peak seasonal snowpack, which is crucial for 35 downstream water resources, will be influenced by compensation for lower interception by higher snowpack sublimation. 36 1. Introduction Snow dominates the water cycle inputs to the semi-arid western portions of Canada and the United States (Connaughton, 1935; Troendle, 1983; Bales, 2006) and is the primary control on the fluxes of energy and biogeochemicals. More than 60 million people in the western U.S. rely on mountain snowmelt as a primary source of water (Bales, 2006). Most of this water derives from forested areas, where accumulation and ablation of snow are strongly controlled by vegetation (Troendle and King, 1987; Jost et al., 2007; Veatch et al., 2009; Rinehart et al., 2008; Musselman et al., 2008; Molotch et al., 2009; Varhola et al., 2010). Vegetation influences how montane catchments capture, store, partition and release snow water, yet the impacts of insect-induced tree mortality on snow-vegetation interactions are not well understood, especially against the backdrop of changing or extreme climate (Varhola et al., 2010). Many seasonally snow-covered areas in western North American have recently suffered rapid and extensive tree die-off caused by mountain pine beetle (MPB; Dendroctonus ponderoseae; Raffa et al., 2008; Kurz et al., 2008). Though MPB is endemic to the region, its activity has reached unprecedented levels during the last 15 years. In 2010, MPB infested 2.77 million hectares of forests, accounting for 75% of all U.S. tree mortality related to insects and other pathogens (USFS, 2012). Causes of the present epidemic are thought to include historically high stocks of mature pine trees following a century of fire suppression, increasing beetle survival and reproduction rates due to longer summers and warmer winters (Mitton and Ferrenberg, 2012), and greater tree susceptibility due to water stress from a warmer and dryer climate (Hicke et al., 2006; Ayres and Lombardero 2000; Logan 37 et al. 2003). Understanding the effects of insect-induced changes to canopy structure on snow accumulation and peak seasonal snowpack is critical to effective management of forest and water resources (Troendle, 1983; Troendle and King, 1987) and the prediction of ecosystem response and recovery following MPB (Edburg et al., 2012). Forest canopy controls snowpack through interception, sublimation of snow from the canopy, attenuation of wind speeds, creation of wind eddies and alteration of the radiation balance. A variable fraction of snowfall is retained in the forest canopy (Schmidt and Troendle, 1992; Hedstrom and Pomeroy, 1998; Link and Marks, 1999), and sublimation of this canopy snow may reduce peak seasonal snowpack by 25 – 45 % in mature pine forest (Pomeroy et al., 1998). Studies by Boon (2012) and Pugh and Small (2011) attributed greater peak seasonal snowpack under grey-phase than living lodgepole forest to reduced sublimation of intercepted snow. Modeling studies have predicted increased peak water yield following MPB infestation using model equations that increased snowpack as interception (modeled as a function of canopy density) was decreased (Bewley et al., 2010; Mikkelson et al., 2011, Pomeroy et al., 2012), reinforcing the expectation of reduced interception as a dominant response. Vegetation interacts with wind to affect spatial distribution of snow through development of eddies across the top of forest canopy that may preferentially deposit snow in canopy gaps (Golding and Swanson, 1978) and by altering redistribution of snow on the ground (Troendle, 1983). Canopy also attenuates wind (Bergen et al., 1971), thus offering protection against wind scour (e.g. Winstral et al., 2002) and sublimation (Bernier, 1990). A forest canopy protects snowpack from ablation by attenuating solar radiation and reducing near-surface 38 wind speeds (Link and Marks, 1999; Musselman et al., 2008; Molotch et al., 2009; Veatch et al., 2009; Lopez-Moreno and Stahli, 2008). A significant body of literature indicates the importance of shading from solar radiation in determining snowpack ablation both during winter and spring melt (e.g. Anderson, 1956; Molotch et al., 2009; Veatch et al., 2009; Lopez-Moreno & Stahli, 2008; Musselman et al., 2008, Rinehart et al., 2008). Because canopy can both prevent snowfall from reaching the snowpack and protect the snowpack from ablation (Musselman et al., 2008; Rinehart et al, 2008; Veatch et al., 2009; Molotch et al., 2009, Pugh and Gordon, 2012), reduced canopy density following MPB tree mortality is likely to lead to compensatory process changes (Somor et al., 2010). Prior studies of canopy removal by harvest (e.g. Hoover and Leaf, 1967; Gary, 1974; Troendle, 1983; Golding and Swanson, 1978, 1986; Troendle and King, 1987; Woods et al., 2006) found more snow water equivalent (SWE) in harvested clearings than nearby forest plots for clearing sizes ranging up to about 5-8 times the mean surrounding tree height. However, these studies reported a mix of increased and unchanged SWE at the stand or hillslope scales, leading to the ideas that 1: increases in clearings were supplied by decreases in undisturbed forest (Gary, 1974; Golding and Swanson, 1986) and 2: reduced interception could be compensated by increased sublimation (Troendle, 1983; Golding & Swanson, 1986; Troendle & King, 1987). Differences were observed at plots scales but sometimes not at larger scales, demonstrating the importance of multi-scale observation. Understanding snow process responses (e.g interception reduction) may require observation at the scale of individual 39 trees to plots, but understanding larger-scale snowpack response to canopy reduction calls for observations across multiple stands. Insect-induced mortality may have some similar effects to harvest, but it differs because much of the tree remains intact and may continue to intercept snow, attenuate wind and alter radiation fluxes (Edburg et al., 2012). Prediction of hydrologic response to forest mortality should cover a range of scales allowing process-based understanding to inform the larger-scale impacts on ecosystem function and water resource availability. Studies comparing adjacent stands within a given site are often hampered by lack of stands with similar structure but differing MPB impact (Pugh and Small, 2011), but comparison of multiple sites requires consideration of topography, forest structure, and climate forcing. To address the effect of MPB tree mortality on peak seasonal snowpack, we used nested multi-scale observations of snow depth and SWE, onsite climate data, and isotopic tracers of hydrologic partitioning to answer two questions. 1: How does MPB tree mortality affect the balance of canopy-mediated snow processes influencing peak SWE?, and 2: What is the net effect of MPB tree mortality on peak SWE at the scale of small headwater catchments? 2. Methods Two sites with varying levels and timing of forest mortality from MPB infestation were studied during winters 2010 and 2011, with observations organized in a nested fashion at multiple spatial scales (Figure 1). Each study site comprised a small headwater catchment of approximately 1 square kilometer containing one or more precipitation gauges and a tower for above-canopy climate observation. Within each site, forest stands 40 were categorized by their level of MPB mortality and year of initial major infestation (e.g. Unimpacted, MPB-2007). Stand-scale observations included canopy characteristics, snow depth, SWE, snow chemistry and sub-canopy wind speed. Within three stands chosen for intensive study from the Unimpacted, MPB-2008 and MPB-2007 types, 20 plots were instrumented for continuous observation of snow depth and sub-canopy temperature, humidity, and downward shortwave radiation. 2.1. Study sites Two study sites were identified in late 2009 along the Front Range of the Central Rocky Mountains in northern Colorado and southern Wyoming (Figure 1), a region of the U.S. severely affected by MPB during the present epidemic (since circa 1996). Sites with adjacent uninfested and infested stands of otherwise similar characteristics were not found. The sites at Chimney Park, WY and Niwot, CO offered observations of meteorology and snowpack from prior and concurrent studies. To isolate the effects of vegetation mortality from those of topography, we selected headwater catchments with similar elevation (2750 - 3,000 m) and gentle terrain (Table 1). Both sites have annual mean precipitation of about 800 mm and mean annual air temperatures of 1-3 °C. Forest characteristics and MPB infestation status were obtained from the Niwot Ameriflux project (http://ameriflux.ornl.gov), from H. Barnard (personal communication) and from ground-based vegetation surveys conducted annually since 2008 at Chimney Park. Although of similar species and age, the Chimney Park stands had larger mean tree height and diameter at breast height (DBH) as well as lower stem density than the Niwot stands (Table 1). 41 The Niwot site (Figure 1) is within the University of Colorado’s Long-Term Ecological Research site, 8 km east of the continental divide and 50 km northwest of Denver. It includes an above-canopy Ameriflux tower (Blanken and Monson, 2012) and a Natural Resources Conservation Service (NRCS) SNOTEL station (NRCS, 2012) all within approx. 400 m distance and 30 m elevation of the forest stands studied. Forest cover is natural re-growth following logging a century ago, dominated by 97 % lodgepole pine (Pinus contorta) with a few individuals of Engelmann spruce (Picea engelmannii) and subalpine fir (Abies lasiocarpa). MPB activity was not observed within the forest stands studied, and these were labeled Unimpacted. The Chimney Park site (Figure 1) is in the Medicine Bow National Forest 110 km north of the Niwot site and 50 km southwest of Laramie, WY. It includes a tower with above-canopy observations of wind velocity, temperature, humidity and shortwave radiation, which began collecting data in January 2009. The site is primarily an evenaged forest of lodgepole pine (82 %) with small amounts of aspen (Populus tremuloides, 11 %), Douglas fir (Pseudotsuga menziesii, 5 %) and Engelmann spruce (1 %), (Reed et al., in preparation), with the last stand-replacing fire 135 years ago (Knight et al, 1985). Chimney Park experienced extensive MPB infestation beginning in 2007, with approximately 75 % of mature lodgepole pine killed by 2011. MPB travel to new host trees during summer, where they introduce a blue-stain fungus that inhibits sap flow and usually kills the tree within several weeks to months (Yamaoka et al., 1990). Dead trees retain their needles for 1-3 years (Wulder et al., 2006), termed the red phase of mortality. Once the needles are lost, trees are said to be in the grey phase of mortality, which lasts 42 5-20 years or more, until the stems fall. Study stands at Chimney Park were categorized by their year of initial MPB infestation including MPB-2007, MPB-2008, and MPB2009. The MPB-2007 and 2008 stands experienced approximately 75 % mortality, nearly all in the first year of infestation. Most dead trees (75 % of total) in the MPB2007 stand were in the grey phase during the entire study. Most dead trees in the MPB2008 stand (75 % of total) were in the red phase during the first winter of the study (2010) but lost their needles and progressed to the grey phase in the second winter (2011). The MPB-2009 stand experienced 10 % mortality before winter 2010 and an additional 15 % by winter 2011. 2.2. Winter Climate We defined the winter snow accumulation season as lasting from the first day of persistent snow cover on the Niwot SNOTEL station 663 (NRCS, 2012) in mid-October to our April 7-9 peak accumulation surveys, conducted approximately one week prior to the snowpack becoming isothermal and commencing to melt. We will refer to this snow accumulation period as “winter” hereafter. We characterized winter climate at each site with above-canopy observations of temperature, vapor pressure deficit, wind, and incident shortwave radiation (Table 2). Wind speed at the Niwot site was corrected to the same height above canopy as the Chimney Park observations (3.7 m above canopy) using a neutral atmosphere logarithmic profile with zero-plane displacement height of twothirds the mean tree height and a roughness length of 1.1 m. Open-area winter precipitation observations were made at the Niwot SNOTEL supplemented with data from a nearby (~200 m) NOAA Climate Reference Network site when necessary. 43 Chimney Park precipitation was observed by a cluster of weighing-type gauges located 250 m west of the site meteorological tower in a small forest clearing similar in dimension to the clearing at the Niwot SNOTEL. These different instruments within the cluster were bias-corrected to a Geonor T-200B reference weighing precipitation gauge at the site. 2.3. Intensive study plots During February and March 2010, digital Judd ultrasonic snow depth sensors (Judd Communications, Salt Lake City, Utah) were installed at 20 plots. Eight sensors were located in an Unimpacted stand, six in an MPB-2008 stand and six in an MPB-2007 stand. In each stand type, half of the depth sensors were located under tree canopy, while the others were located in canopy gaps. Gaps were defined by open areas with widths approximately 1/4 to 1/2 of the mean surrounding tree height. Although the timing of precipitation at the two sites was correlated at better than 99 % (p < 0.0001), Chimney Park received 10-14 % more precipitation. Depth records were therefore normalized to the mean snow depth in gaps from each stand at peak accumulation to account for this difference; this approach treats gap sensors as experimental controls for analysis of new snowfall. Sensor power was lost for portions of the winter in the MPB-2007 and MPB2008 plots (Figure 2), and manual snow depth observations were made to supplement the record at the MPB-2007 plots on the days bracketing the 2011 snow survey. New snowfall inputs during each storm (mean value in gaps) were quantified for each stand, with storms defined as periods of precipitation rate ≥ 1.0 mm/hr (water equivalent) and total precipitation ≥ 5 mm (water equivalent). 44 Sub-canopy climate observations included temperature, humidity, incoming shortwave radiation and wind speeds. Silicon cell pyranometers (model SP, Apogee Instruments, Logan, Utah) measured downward shortwave radiation below the canopy at a height of 2 m in all 20 plots (half under canopy and half in gaps) beginning in April, 2010. These sensors directly sample wavelengths from 300 – 1100 nm, the spectral range containing 80-90% of solar radiation reaching the land surface, and estimate the remaining 10-20% of radiation in wavelengths of 1100 - 2800 nm. Vegetation or high humidity can bias incoming shortwave radiation towards shorter wavelengths, reducing the accuracy. Power loss issues disrupted observation in the MPB-2007 plots, but comparisons were made between the Unimpacted and MPB-2008 plots for winter 2011. Temperature and relative humidity sensors (model EM50, Decagon Devices, Pullman, Washington), were installed in all 20 plots at 2 m height in April 2010. These were gillshielded and aspirated with solar-powered fans. Two sub-canopy (3 m) sonic anemometers (model CSAT3, Campbell Scientific, North Logan, UT) were deployed from April 16 to July 29, 2011 in the MPB-2009 stand near the Chimney Park met tower and another two were deployed in Unimpacted study plots to investigate the effects of MPB mortality on wind attenuation. Above-canopy winds were on average 13 % lower at each site during this spring/summer season than during the two winters of the study. 2.4. Snow surveys at peak accumulation Snow surveys were conducted April 7-9 2010 and 2011 (Figure 1) over small headwater catchments including 5-6 stands at each site (somewhat less area was surveyed at Niwot during the 2nd year due to overall lower variability in canopy cover and snow 45 distribution). In recognition of the potentially important roles of slope and aspect on snow accumulation and ablation, we focused on areas of low slope at both sites. Chimney Park snow surveys had slopes ranging from 1.9 – 17 % with mean (standard deviation) of 4.3 % (1.8 %) and a relatively uniform mixture of all aspects. The Niwot surveys were made on gentle opposing hillslopes with northeast (15 % of survey) and southeast (85 % of survey) aspect and slopes ranging from 3.7 – 18 % with mean (standard deviation) of 9.0 % (2.3 %). Surveys were made along orthogonal transects (e.g. Anderton et al, 2004) aligned with cardinal magnetic directions. Depth measurements were made at 5-m centers as well as one meter to the front, back, left and right for a total of 100 depth observations along each 100 linear meters of survey. An observation of canopy density was made at each 5-m center point using the categories none, sparse, medium and dense. Transects were selected to characterize Unimpacted, MPB-2009, MPB-2008 and MPB-2007 stand types but extended beyond these to broadly characterize small headwater catchments of ~1 km2 at each site (Figure 1) with over 8,000 total observations. The present analysis focused on MPB mortality in mature forests and used the 4,634 observations in mature lodgepole pine stands, excluding those closer to a stand edge than twice the mean tree height to minimize edge effects (Woods et al., 2006). Determination of differences among mean SWE of stand types and canopy densities was performed by one-way ANOVA followed by a t-test-based comparison of multiple means (Matlab R2012a). 46 Patterns of spatial correlation were studied within each stand type using experimental and modeled semivariograms (e.g. Schabenberger & Gotway, 2004). The experimental semivariogram : 1 N h zxi zxi h 2 N h i 1 2 is half the average squared difference in depth observation pairs z at locations x, separated by a lag distance h. N(h) is the number of such depth observation pairs in the given dataset. Snow depth variability may be anisotropic, so semivariograms were calculated separately for 200-m South-North and West-East transect portions using the 120 depth observations falling along the centerline of each survey at positions of 0, 1, 2, 5, 6, 7, . . . 199, 200, 201 m. Experimental semivariograms were fitted with exponential models (Matlab R2012a) to allow calculation of the sill, or variance approached at large lag distances, and the range, calculated as the lag distance at which the model semivariogram reaches 95 % of the sill variance. Observations closer to one another than the range are considered autocorrelated, while those farther apart than the range are considered independent. With each peak seasonal snow survey, densities were determined from 2-4 snow pits at each site using the method described by Cline et al. (2001) in a variety of forest stands and both under canopy and in gaps. Pits were excavated to the ground surface, taking snow density, grain type and size, and temperature measurements at 10-cm vertical increments. Fewer snow density measurements were required than snow depths because density varies in space much less than depth (Elder et al., 1998; Anderton et al., 2004). Densities did not vary significantly in space within either site, so mean density values 47 (range: 261 to 342 kg/m3) for each site and date were applied in calculation of SWE (Anderton et al., 2002; Jost et al., 2007). 2.5. Isotopic tracers of sublimation Stable water isotopes of snowpack were compared to the isotopic content of fresh snowfall. Snowfall samples were collected within 24-36 hours of storms in forest clearings, which minimized potential contamination by previously intercepted snow sloughed from the canopy, where it would be more likely to have partially sublimated. Fresh snowfall determined the local meteoric water line (LMWL) at each site, which was considered the starting point for any snowpack isotopic enrichment. Snowpack isotope samples were collected from snow pits dug approximately monthly at paired undercanopy and gap locations. Samples were collected from each 10-cm vertical layer, with composite values volume-weighted using the snow density measurements. The samples were analyzed for stable water isotope ratios (δ2H and δ18O) at the University of Arizona using a DLT-100 liquid water isotope analyzer (Los Gatos Research (LGR), Inc., model 908-000). Further analytical details are described in Lyon et al. (2009). The isotopic enrichment of snow is similar to that of evaporating water, with mass exchange between snow and vapor (Moser and Stichler, 1975). The sublimated fraction of snowpack, f, was estimated via the method given by Clark and Fritz (1997) and demonstrated in a recent field study by Gustafson et al. (2010) using both δ18O and δ2H (deuterium) values. Equation 2 dictates the equilibrium fractionation enrichment factor expressed as per mil (‰) due to the transition of water from the solid to vapor phase: 18Ol s (1 ) 103 (2) 48 where Ol s is the per mil (‰) fractionation and is the fractionation factor ( = 18 1.015) (O’Neil, 1968, cited in Clark and Fritz, 1997) Kinetic fractionation is governed by equation 3, where h is the humidity at the snow-atmosphere boundary. 18 Ol s 14.2 (1 h) (3) Deuterium excess of snow pit isotopic values, relative to the LMWL, showed a humidity of approximately 80-90% at the snow-atmosphere boundary. The total fractionation of 18 O O due to sublimation is the sum of equilibrium and kinetic fractionation, 18 T expressed as: 18 OT 18 Ol s 18 Ol s (4) The fractional water loss f from the snowpack due to sublimation enrichment then was calculated according to Rayleigh distillation: 18OObs. 18OSnowfall 18OT ln( f ) (5) 18 where OObs was the maximum snowpack value and OSnowfall was the intercept of the 18 least-squares linear regression of snowpack samples with the LMWL (Matlab R2012a). The sublimation estimates were not sensitive to temperature and relative humidity, which were assumed based on conservative conditions to be -2 °C and 90 %. 3. Results 3.1. Weather Cold temperatures and frequent storms (mean interstorm interval of 4.2 days) prevailed throughout the winter snow accumulation seasons (winters) of 2010 and 2011, resulting in the development of continuous snow cover across the study sites. Snowpack temperatures and crystal stratigraphy excluded melt during the winters. 2010 winter 49 precipitation was climatologically average (379 mm at Niwot and 422 mm at Chimney Park) while 2011 winter precipitation was 113 % (calculated from 30-year Niwot SNOTEL history) of average (422 m at Niwot and 466 mm at Chimney Park). The Niwot and Chimney Park sites received comparable climate forcing as characterized by temperature, vapor pressure deficit, wind speed, and downward shortwave radiation (Table 2) and largely experienced the same regional-scale winter storms, evidenced by similar timing and magnitude of snow depth increases in plots (Figure 2). Cumulative daily winter precipitation plots (Chimney Park vs. Niwot, plots not shown) had slopes of 1.10 and 1.14 for winters 2010 and 2011, reflecting the 10-14% greater winter precipitation at Chimney Park (see methods). However, these plots showed linear correlation greater than 99 % (p < 0.0001), meaning the precipitation timing was quite similar. 3.2. Snowfall interception To address this study’s first question about the balance of canopy-mediated snow process responses (see Introduction), continuous snow depth records were used to compare new snowfall under canopy and gaps in the Unimpacted, MPB-2008 and MPB2007 plots. In the Unimpacted plots, locations under gaps accumulated deeper snow than under adjacent canopy throughout the winter (Figure 2). Differences between canopy and gaps were smaller in the MPB-2008 plots and slightly reversed in the MPB-2007 plots, where the under-canopy mean depth was slightly larger than in gaps. At the end of the winter, differences in mean snow depth under canopy as compared to gaps were 11%, 4% and -7% for the Unimpacted, MPB-2008 and MPB-2007 plots. Taking one minus 50 the ratio of new snowfall during storms under canopy to that in gaps (Figure 3) as an estimate of interception, we calculated interception of 20 %, 14 % and 0 % in the Unimpacted, MPB-2008 and MPB-2007 plots, respectively. Assuming 60 % of intercepted snow sublimates and the remaining 40 % is unloaded to the snowpack (Pomeroy et al., 1998), these correspond to reductions in peak seasonal snowpack of 12.0 %, 8.4% and 0.0%. 3.3. Spatial distribution of peak snowpack Marked contrasts in spatial distribution of peak snow depth across the different stages of MPB infestation were used to make further inferences about the balance of canopy-mediated snow process responses. Representative South-to-North transects (Figure 4) show least depth under denser canopy and greatest depth under canopy observed to be “sparse” or “none”, but the overall variability decreased with increasing time since MPB infestation. Standard deviations of depth were 21.9, 10.6 and 6.4 cm for Unimpacted, MPB-2008 and MPB-2007 transects (Figure 4), respectively. Numerous field observations indicated that gaps larger than half the surrounding tree height had deepest snow at their southern edges and least snow at their northern edges (e.g. Figure 4a Unimpacted transect near 0 m and +70 m); the phenomenon was weaker in grey stands that had lost their needles than in healthy or red-phase stands as illustrated in Figure 4b (MPB-2008) near 0 m and +75 m and in Figure 4c (MPB-2007) just south of 0 m. Semivariograms (Figure 5) had clear sills, indicating that snow surveys were of sufficient extent to characterize the mean and variability (Figure 6) of each stand type (Cressie, 1993; Legendre & Legendre, 1998; Jost et al., 2007). Semivariograms of normalized 51 2010 peak snow depth were anisotropic (Isaaks & Srivastava, 1989), showing an order of magnitude lower sill variance along South-North transects in an MPB-2007 stand (grey phase, sill = 0.015) than an Unimpacted stand (sill = 0.120) with an MPB-2008 stand (red phase, sill = 0.053) of intermediate variability (Figure 5). In the Unimpacted forest (Figure 5a), the sill variance along a South-North transect (0.120) was double the sill variance along a West-East transect. The semivariogram ranges, which represent the distance beyond which depths were independent, decreased from 12.2 m in an Unimpacted stand to 7.4 in an MPB-2008 stand (red phase) to 3.3 m in an MPB-2007 stand (grey phase) along South-North transects. 3.4. Comparison of peak snowpack between MPB and Unimpacted Amounts and spatial distribution of SWE were used to compare mean effects of MPB infestation on peak seasonal SWE as well as the role of canopy within each stand type. SWE at the snow surveys ranged from 23.0 to 29.3 cm over the two years (Table 3). SWE values were normalized by onsite observations of winter precipitation for each site and year, with the ratio SWE:P indicating the fraction of snowfall remaining in the snowpack at peak seasonal accumulation. Consistent with expectations based on low slope, there was no significant relationship between peak SWE:P and slope at either site. At Niwot the small portion (15 %) of the dataset with Northeast aspect had higher SWE:P than the points with Southeast aspect (SWE:P of 0.658 and 0.625, respectively). Mean normalized peak seasonal snowpack (SWE:P) was used to address this study’s second question regarding the net impact of forest mortality on SWE. Unimpacted, MPB-2008 and MPB-2007 stand types were statistically indistinguishable with a mean SWE:P of 52 0.62 (Figure 5), while the MPB-2009 stand had 2 % greater SWE:P (p < 0.05). Total winter season ablation was therefore 36 - 38 % of snowfall. When SWE:P values were categorized by canopy density (i.e. none, sparse, medium and dense), the number of unique (p < 0.05) canopy groups was highest in the Unimpacted stand type (4 groups) and lowest in the MPB-2007 stand type (2 groups). With increased time since infestation, areas of medium to dense canopy tended to higher SWE:P, while areas of sparse or no canopy showed monotonically decreasing SWE:P (i.e. gap areas retained a smaller fraction of winter snowfall at peak seasonal accumulation). 3.5. Subcanopy environment The balance of canopy-mediated snow process responses (study question 1) was further informed by sub-canopy climate observations during the second winter (2011, Table 2). Sub-canopy mean temperatures and vapor pressure deficits for the winter season were similar among all plots, with temperature ranging from -1.9 °C (Unimpacted) to -0.9 °C (MPB-2008) and vapor pressure deficit ranging from a winter mean of 0.20 kPa (MPB-2007) to 0.23 kPa (Unimpacted). Incoming shortwave radiation averaged 14 W/m2 in the Unimpacted plots as compared to 25 W/m2 in the MPB-2008 plots (in grey phase in 2011), equating to 70 % greater insolation of the MPB-2008 snowpack than Unimpacted snowpack during the winter. During the April-July 2011 assessment of subcanopy (3-m height) wind speeds, above- and below-canopy wind speeds were 2.73 m/s and 0.36 m/s in the Unimpacted stand and 3.00 m/s and 0.43 m/s in the MPB-2009 stand. 53 3.6. Stable isotope indicators of sublimation The enrichment of stable water isotopes in snowpack differed between Unimpacted and MPB-impacted stands. Unimpacted stand snowpack plotted along the LMWL, indicating no kinetic fractionation. This does not exclude equilibrium fractionation (saturated conditions at the snow-air interface) which is not detectable with this method. MPB-impacted stand snowpack plotted on a line below (Figure 7) and statistically different from the LMWL (p < 0.05) with a slope of 6.2, indicating kinetic sublimation at an average relative humidity of 90 %. We calculated δ 18Oreact - δ 18O0-react as 3.6 and δ 2Hreact - δ 2H0-react as 22.2. The fraction of SWE lost from the combined MPB-impacted stand snowpack via kinetic sublimation is estimated at 24 % using 18 O and 18 % using 2H. These estimates of snowpack kinetic sublimation loss would include neither sublimation of intercepted snow completely sublimated from the MPB canopy, nor sublimation of snowpack under equilibrium (saturated) conditions. The estimate may be further reduced by condensation back into the snowpack, which may bring the isotopic signature of snowpack back towards the LMWL and obscure the sublimation signal. These 18-24 % snowpack loss estimates are therefore lower bounds of total winter snowpack sublimation in the MPB stands, consistent with estimates of an additional 0-8.4 % lost by canopy sublimation and snow surveys showing a total of 36-38 % winter season ablation of snowfall. 4. Discussion In this study we observed shifts in two canopy-mediated snow processes following MPB forest mortality: decreased interception (Figure 3) and increased 54 snowpack sublimation (Figure 7). Ultimately these compensated for one another, resulting in no difference to peak normalized SWE (Figure 6), in contrast with the few previous direct observations of snow accumulation following insect-induced mortality (Boon 2007, 2012; Pugh and Small, 2011). Sublimation of intercepted snow from the canopy is often considered the dominant flux representing differences between snowfall and peak SWE (Schmidt and Troendle, 1992; Hedstrom and Pomeroy, 1998), leading to an expectation of increased peak SWE following forest mortality. Sublimation requires available energy for the change of phase between ice and water vapor and the turbulence to transport vapor away from the ice surface, both of which are high in the forest canopy and much lower at the level of the snowpack on the forest floor. Given sufficient energy and turbulence however, snowpack sublimation may represent a large fraction of winter snowfall (Hood et al, 1999; Molotch et al., 2009). Molotch et al. (2009) reported winter snowpack sublimation rates averaging 0.41 mm d-1 and a mean contribution by snowpack to total sublimation of 45 % for healthy forest at the Niwot site used in this study. Our results indicate that the sum of winter sublimation losses from the canopy and snowpack remained constant (Figure 6). Snowpack sublimation increased (Figure 7), compensating for lower sublimation of snow from the canopy. These results were similar to studies in which canopy removal treatments altered spatial distribution of snow with little to no effect on peak SWE at larger scales (e.g. Woods, 2006; Troendle and King, 1987; Gary, 1974). A recently developed method (Gustafson et al., 2010) of comparing stable water isotopes in fresh snowfall to those in snowpack confirmed greater sublimation of snowpack in insect-killed forest (Figure 7), and season-long observations of temperature, 55 vapor pressure deficit, solar radiation and wind speed (Table 2) provide inferences to explain why snowpack sublimation increased, compensating for reduced canopy snow sublimation. Continuous snow depth sensors identified the expected pattern of lower interception in the high mortality forests (Figure 3), presumably in response to reduced canopy density (Hedstrom and Pomeroy, 1998; Pomeroy et al., 2002). Interception is a function of canopy area, temperature, humidity, and snowfall characteristics (e.g. Stroebel, 1978; Hedstrom and Pomeroy, 1998; McNay et al., 1988; Pomeroy et al., 2002), and has been implicitly accepted as a driver of increased snowpack in modeled response to MPB (Bewley et al., 2010; Mikkelson et al., 2011, Pomeroy et al., 2012). Interception rates observed in healthy forest (Figure 3) were similar to recent regional observations (Musselman et al., 2008; Molotch et al., 2009), suggesting that differences in new snowfall under canopy and in gaps are due primarily to interception and not influenced by redistribution of canopy snowfall preferentially deposited in gaps (Golding and Swanson, 1978). Although unloading of intercepted snow from the canopy may also influence estimates of interception (Clark et al., 2011) low new snow densities result in an immediate depression of snow depth following unloading (Mussleman et al., 2008, Molotch et al., 2009) which allowed us to exclude these events from the analysis summarized in Figure 3. It is possible that higher subcanopy wind speeds (Table 2) during storm events reduced the observed interception below impacted stands, and that both lower stem density and taller trees (Table 1) could enhance this effect. However, the 20 % difference in interception between the Unimpacted and MPB-2007 plots (Figure 56 3) is of similar magnitude to findings by Pugh and Small (2011) in lodgepole pine forests in Colorado and by Boon (2012) in British Columbia. In spite of reduced interception, peak SWE was unchanged by widespread (~75 %) MPB tree mortality (Figure 6), indicating that lower interception (Figure 3) was compensated by higher winter snowpack sublimation. Differences in topography between the Niwot and Chimney Park sites could have influenced the SWE comparison. The Unimpacted stands at Niwot showed slightly higher (~ 5 %) peak normalized SWE in an area with 9 % slope and Northeast aspect as compared to an area with 9 % slope and Southeast aspect. Because 85 % of the dataset was collected on the Southeast aspect, this may have led us to underestimate SWE:P in the Unimpacted stands, meaning that net snow accumulation at the larger scale might actually be lower in MPB impacted stands than the Unimpacted stands. Melt was excluded during the winter because profiles of cold content and crystal structure indicated a continuously cold snowpack. Wind scour was excluded by more than 8,000 snow depth observations collected over areas of approximately one square kilometer at the two sites in two years, which showed no major areas of net deposition. Minimal wind redistribution is consistent with our observations of low subcanopy wind speeds (Table 2). With melt and wind excluded as important process of winter snowpack ablation at these sites, we infer that reduced canopy sublimation in MPB-impacted stands was compensated by increased snowpack sublimation. Snowpack sublimation is difficult to observe, especially when concurrent with canopy sublimation, which confounds standscale vapor flux observations (Molotch et al., 2009). Increases in concentrations of 57 snowpack solute ions have been used successfully in open areas (Gustafson et al., 2010), but ion contamination from throughfall and needle litter in MPB-impacted stands made stable isotopes preferable in this study (Gustafson et al., 2010; Sommerfeld et al., 1987; Sommerfeld et al., 1991; Stichler, 1986). Comparison of stable water isotopes in snowpack with those in fresh snowfall offered evidence that snowpack sublimation was indeed higher in MPB-impacted stands (Figure 7). Although this method (Eq. 2-5) allows quantification of just the kinetic portion of sublimation, the significant difference in kinetic fractionation (i.e. snowpack sublimation loss under subsaturated conditions) between Unimpacted (no loss) and MPB-impacted (20-25 % loss) stand types confirms a major increase in sublimation from the snowpack below the canopy following MPB mortality. Such a difference could have been caused by enhancement of vapor transport away from the surface (i.e. increased vapor pressure deficits and/or turbulent transport) or by increased available energy from solar radiation (Veatch et al., 2009, Gustafson et al., 2010, Rinehart et al., 2008). Isotopic contents of fresh snowfall inputs to the snowpack could be influenced by partial sublimation of snow initially retained in the canopy and then sloughed to the ground. The collection of samples in open areas immediately after storms was intended to minimize such effects. Given the lower wind speeds and higher density of canopy available for interception, we would expect any such effect to be larger in Unimpacted stands. Since canopy sublimation would likely exhibit kinetic fractionation, the consistency with which snowfall and snowpack samples remained near the Global Meteoric Water Line in the Unimpacted stands (Figure 7a) suggests that partial canopy snow sublimation was of minimal influence on the isotope results. 58 Larger snowpack sublimation beneath MPB-impacted forest canopy could have been controlled by higher wind speeds (Stegman, 1996) and turbulence (Molotch et al., 2007) or by greater transmission of solar radiation (Boon, 2009; Pugh and Small, 2011), consistent with the major role that radiation plays in the energy balance of forested snowpacks (Link and Marks, 1999). Our observation of similar wind speeds in the Unimpacted and MPB-2009 stand types (Table 2) makes it unlikely that wind controlled differences in snowpack sublimation. 71 % more solar radiation reached the snowpack in the MPB-2008 plots than in the Unimpacted plots (Table 2). Although the type of pyranometer used might lead to over-estimation of below-canopy shortwave by 10-20 % (see Methods), any bias should be larger for Unimpacted stands, suggesting that the true difference could be larger. The 71 % difference we observed is much larger than the 1113 % shortwave difference calculated by Pugh and Gordon (2012) for grey-phase stands using a modified Beer-Lambert model (Hellstrom, 2000). More detailed canopy radiation transmission models could be more informative (e.g. Hellstrom, 2000; Hardy et al., 2004); caution is warranted in using spatially lumped models, becuase winter season sublimation can vary among forest stands with similar average canopy density but different geometry (i.e. spatial arrangement of trees and gaps, Woods et al., 2006; Veatch et al., 2009) and/or topography (slope, aspect, elevation e.g. Rinehart et al., 2009). Although vegetation is the most important control of SWE in forested terrain, even in complex topography (Varhola et al., 2010), solar interactions with slope and aspect may be of increased importance following canopy density reduction (Troendle and King, 1987; Somor et al., 2010). Net shortwave inputs to the snowpack may be further 59 increased by litter-fall beneath killed trees and associated albedo reductions (Winkler et al., 2010; Pugh and Small, 2011). If the observed 11 W/m2 (Table 2) were the only difference in available energy from December 1 to April 1, it would be sufficient to sublimate an additional 4.1 cm of SWE, or 14 % of the mean peak SWE observed in this study, more than compensating for the estimated 12 % reduction in canopy sublimation between the Unimpacted and grey phase MPB-2007 (Figure 3). Spatial observations from our distributed snow surveys supported the importance of solar radiation in controlling snowpack sublimation and net annual snow water input. First, the observation of greater snow depth at the shaded southern edges of forest gaps and less depth near the less-shaded northern edges (Figure 4) indicated the importance of solar shading (Veatch et al., 2009; Molotch et al., 2009, Musselman et al., 2008; Golding and Swanson, 1986). Second, snow surveys showed decreased snowpack (SWE:P) in gaps (Figure 6) of MPB-killed forest, which may be attributed to reduced shading by adjacent canopy. Third, the importance of solar shading was demonstrated by higher semivariogram sill variance along the South-North transect than the West-East transect of Unimpacted forest (Figure 5). A South-North transect in healthy forest crosses the deep, shaded southern portion and shallower, unshaded northern portion of snow in each gap traversed, whereas a West-East transect crosses each gap parallel to its snow depth contours, resulting in lower variability. This directional difference was not observed in MPB-killed forest, consistent with a reduction in canopy shading. Compensatory process changes affect peak SWE following insect-induced tree mortality, with a potentially variable balance between lower interception and increased 60 higher snowpack sublimation. Reduced sublimation of intercepted snow with reduced canopy density is intuitive, and our estimates of 8.4 – 12.0 % more snowfall reaching the snowpack in grey-phase stands (Figure 3) are consistent with both empirical observations (Boon, 2012; Pugh and Small, 2011) and modeled results (Bewley et al., 2010; Pugh and Gordon, 2012) ranging from 7 - 19 %. Much less is known about the effects of insectinduced tree mortality on winter snowpack sublimation. The present study’s conclusion of no change in peak seasonal SWE (Figure 6) contrasts with increased SWE observed following MPB in Colorado by Pugh and Small (2011) and for one of two winters in British Columbia by Boon (2012). We suggest that such contrast may arise because the observations in this study are nested across a larger range of spatial scales (tree, plot, stand, hillslope) than previous studies. Earlier studies of harvest effects on snowpack reported forest-to-clearing snowpack differences but no net change averaged over larger scales (Hoover and Leaf, 1967; Gary 1974; Troendle, 1983; Golding and Swanson, 1986; Troendle and King, 1987), highlighting the importance of large-scale snowpack characterization. Peak SWE is a primary indicator of long-term water availability in forested mountain catchments, and this study has implications for ecosystem function and downstream water resources. The conventional wisdom is that widespread tree mortality results in increased water yield based on harvest studies (see review by Pugh and Gordon, 2012), but the few empirical studies of water yield response to insect-induced mortality are inconclusive in this regard. Bethalmy (1974) reported a small water yield increase that did not peak until 15 years following major infestation, while Potts (1984) found a 61 small increase immediately, and Somor et al. (2010) found less runoff in one catchment and no change in seven others following widespread MPB forest mortality. These mixed responses in runoff likely reflect variable SWE response (i.e. changes to interception and winter sublimation), time-varying changes to transpiration (Edburg et al., 2012), and mediation of impacts due to complex hydrologic flow paths and the patchy, transient nature of insect infestation. Our results showed that increased winter sublimation compensated for reduced interception and demonstrated that insect-induced forest mortality will not necessarily result in increased water availability. 5. Conclusions This study provided extensive empirical evidence from two winters that snow process responses to insect-induced forest mortality can compensate for one another, resulting in no change to peak SWE. Observations of reduced interception were consistent with expectations from prior studies, but surprisingly, there was no difference in peak SWE between healthy and grey-phase forest. Higher rates of snowpack sublimation were confirmed by the recently developed method of comparing stable water isotopes in fresh snowfall to those in snowpack. Several lines of evidence suggested that vegetation shading of snowpack from solar radiation was a primary control on winter sublimation of snow at the study sites and that shading was reduced in insect-killed forest. The plot-scale observations of new snowfall and accumulated depth showed a decreased association between canopy density and snow depth, consistent with the decreased spatial variability of depth, the decreased spatial scale of variability, and the lower importance of canopy density in controlling SWE: P at peak accumulation. The 62 contrast between our results and those of two prior studies emphasizes the importance of winter snowpack sublimation as well as the need for large-scale observation when characterizing peak SWE. The significance of peak SWE as an indicator of hydrologic response to forest disturbance highlights the need for improved understanding of the balance between greater net snow inputs and increased snowpack sublimation; factors needing further investigation include forest geometry, topographic exposure to radiation and wind, and the dynamics of a given disturbance. 6. Acknowledgements The National Science Foundation EAR-0910831, United States Geological Service, Wyoming Agricultural Research Station through McIntire-Stennis and Wyoming Water Development Commission supported this research. Science Foundation Arizona and the Arizona Water Sustainability Program provided additional support. The National Science Foundation Niwot Ridge Long-Term Ecological Research project and the University of Colorado Mountain Research Station provided logistical support and data. Snowfall isotope data for Niwot were provided by Rory Cowie and Dr. Mark Williams of INSTAAR. The National Center for Atmospheric Research is supported through a cooperative agreement from the National Science Foundation. We gratefully acknowledge the work of two anonymous reviewers whose comments helped clarify and strengthen the key contributions of this work. 63 7. References Anderson, H.W. 1956. Forest-cover effects on snowpack accumulation and melt. Central Sierra Snow Laboratory. 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Canadian Journal of Forest Research-Revue Canadienne De Recherche Forestiere, 20(1), 31-36. doi: 10.1139/x90-005 69 8. Tables Table 1. Mean characteristics of the two sites and four stand types Site Stand Elevation (m) Latitude Longitude Age (yr) Stem Density (per ha) Tree Ht. (m) DBH (cm) Niwot, CO Unimpacted 3000 40° 02′ -105° 33′ 100 3900 11.4 12.1 2750 41° 04′ -106° 07′ 90-110 2250 1160 1310 14.0 17.6 17.0 14.2 20.1 19.9 Chimney Park, WY MPB-2009 MPB-2008 MPB-2007 70 Table 2. Total precipitation and above- and below-canopy climate by site for winters 2010 and 2011. NWT = Niwot, CO and CP = Chimney Park, WY. Standard deviations are shown to reflect the variability in daily climate variables. *All data are for the winter snow accumulation season except sub-canopy wind speeds, which were observed April 16 – July 29, 2011, during which the mean of daily above-canopy wind speeds were: NWT = 2.7 (1.3) m/s and CP = 3.0 (0.9) m/s. Year Site 2010 NWT Above Canopy Winter Precip. (mm) Mean Daily (Standard Deviation) Wind Temp. Speed VPD (°C) (m/s) (kPa) Rsw (W/m2) 379 -3.0 (4.8) 3.3 (1.7) 0.26 (0.19) 158 (80) CP Above Canopy 433 -3.0 (4.5) 3.2 (1.1) 0.24 (0.17) 165 (80) 2011 NWT Above Canopy Unimpacted Sub-canopy 422 -2.1 (6.8) -1.9 (5.1) 4.1 (2.4) *0.38 (0.15) 0.28 (0.22) 0.23 (0.17) 131 (65) 14 (9) 466 -2.0 (7.1) -1.8 (5.3) -0.9 (2.4) - 3.6 (1.3) *0.43 (0.30) 0.27 (0.25) 0.20 (0.21) 0.21 (0.14) - 126 (65) 25 (15) - CP Above Canopy MPB-2007 Sub-canopy MPB-2008 Sub-canopy MPB-2009 Sub-canopy 71 Table 3. Distributed snow depth and SWE values from surveys conducted in headwater catchments (~1km2) near peak accumulation for winters 2010 and 2011. MPB-2007 and MPB 2008 stand types experienced 75 % mortality in their initial infestation year; The MPB-2009 stand type experienced 15 % mortality by winter 2010 and a total of 25 % by winter 2011. The sample mean and standard error of the mean are shown to reflect the uncertainty associated with estimating the population mean. Sample sizes of depth observations are Unimpacted = 1766, MPB-2009 = 746, MPB-2008 = 923 and MPB2007 = 1199. Year Stand 2010 Unimpacted MPB-2009 MPB-2008 MPB-2007 Depth (cm) SWE (cm) SWE:P 88.3 (0.6) 92.9 (0.3) 96.4 (0.8) 94.0 (0.3) 23.0 (0.2) 28.2 (0.1) 29.3 (0.2) 28.6 (0.1) 0.61 0.65 0.68 0.66 2011 Unimpacted MPB-2009 MPB-2008 MPB-2007 87.8 (0.7) 82.6 (0.5) 83.2 (1.5) 79.0 (1.6) 27.0 (0.2) 28.2 (0.2) 28.5 (0.5) 27.0 (0.5) 0.64 0.61 0.61 0.58 72 9. Figures Figure 1. Site maps of a. Chimney Park, Wyoming and b. Niwot, Colorado sites showing canopy taller than 2 m (shaded area). Chimney Park includes lodgepole pine stands with ongoing low-level infestation (MPB-2009) as well as stands with greater than 75% mortality from infestations in 2007 (MPB-2007) and 2008 (MPB-2008). The Niwot site was Unimpacted by MPB through 2011 73 Figure 2. Mean normalized depths under canopy (solid) and gaps (dashed) for a. Unimpacted b. MPB-2008 and c. MPB-2007 plots (n = 4 each for Unimpacted gap and Unimpacted canopy and n = 3 for all other categories). Depths were normalized to the mean gap value at the snow survey date of April 9 (day of water year 191, indicated with vertical dotted line) to account for the small differences in seasonal precipitation between sites (Table 2). Mean depth values on Apr. 9 for gap and canopy plots in each stand type are also shown. 74 Figure 3. Ratios of snowfall under canopy to snowfall in gaps for all snowstorms of more than 5 cm between March 10, 2010 and April 9, 2011. Sample sizes were n = 56, 36 and 38 for the Unimpacted, MPB-2008 and MPB-2007 plots, where each sample is one storm observed at one plot. Bars show mean values, and error bars show standard error of the mean. The MPB-2007 plots mean ratio was higher than those of the Unimpacted and MPB-2008 plots (p < 0.05). 75 Figure 4. Snow survey depths (line and markers) and canopy densities (shaded bars) April 7-8, 2010 for sample transects in the a. Unimpacted (mean, sd: 85.3, 21.9 cm), b. MPB-2008 (95.6, 10.6 cm), and c. MPB-2007 (95.9, 6.4 cm), stands. The MPB-2008 and MPB-2007 stands were 21 and 33 months post-infestation, respectively. The MPB stands (panels b and c) had received 14 % more snowfall than the Unimpacted stands at this date (Table 2). Each point represents the mean and standard deviation (bars) of 5 observations made within a 1-m radius on 5-m centers. 76 Figure 5. Experimental semivariograms (markers) of peak seasonal snow depth normalized to the mean depth of sample transects in a. Unimpacted, b. MPB-2008 and c. MPB-2007 stands (same as in Fig 4) April 8-9, 2010, with best-fit exponential model semivariograms (curves). All semivariograms reached clear sills, indicating surveys were of sufficient spatial extent to characterize mean and variability of snow depth. Larger sill variance along the South-North than East-West Unimpacted transect illustrated solar shading. Sill variance and the range of spatial autocorrelation were lower in stands with ~75 % MPB-induced tree mortality. 77 Figure 6. Peak SWE normalized to winter precipitation for both the 2010 and 2011 surveys in a. Unimpacted, b. MPB-2009, c. MPB-2008 and d. MPB-2007 stand types. All points were in mature lodgepole stands, and canopy density was recorded using the categories None, Sparse, Medium and Dense. Dashed lines are means of each forest cover type, bars are means of each canopy type, and error bars are standard error of the mean. The means were equal for Unimpacted, MPB-2008 and MPB-2007 stand types but slightly higher (p < 0.05) for the MPB2009 stand type. Letters indicate unique canopy density means within each stand type (p < 0.05). 78 Figure 7. Water isotopic contents of fresh snowfall and evolved snowpack for a. Unimpacted stands and b. combined MPB stands. “+” symbols denote fresh snowfall and “Δ” denote snowpack. The MPB stands snowpack slope was significantly less than that of the Local Meteoric Water Line or LMWL (p < 0.05). 79 APPENDIX B: COMPENSATORY VAPOR FLUX REDUCES WATER FOR STREAMFLOW FOLLOWING SEVERE BARK BEETLE-INDUCED FOREST MORTALITY Manuscript in review by the journal Water Resources Research. Title Compensatory vapor flux reduces water for streamflow following severe bark beetleinduced forest mortality Running title: Reduced streamflow following bark beetle disturbance Joel A. Biederman1*, P. D. Brooks1, A. A. Harpold2, D. Gochis, B.E. Ewers4, D. E. Reed4,5 1 Department of Hydrology and Water Resources University of Arizona, Tucson AZ 85721 2 INSTAAR, Boulder, CO 80309 3 NCAR, Boulder, CO 80301 4 Department of Botany and Program in Ecology University of Wyoming, Laramie, WY 82071 5 Department of Atmospheric Science and Program in Ecology University of Wyoming, Laramie, WY 82071 80 Abstract A North American epidemic of mountain pine beetle (MPB) has disturbed over 5 million hectares of forest already under stress from shifts in climate and related disturbances and containing headwater catchments crucial to water resources. There is limited empirical evidence of how MPB infestation affects partitioning of precipitation between vapor flux and streamflow, and to our knowledge these fluxes have not been observed simultaneously following forest disturbance. We combined eddy covariance tower footprint water balance, catchment water balance, and stable isotope indicators of evaporation to quantify hydrologic partitioning over three years in MPB-impacted and Unimpacted forests. Annual vapor flux V at the Unimpacted site was conservative, varying only from 573 to 623 mm, while MPB site V varied over a larger range from 569 to 700 mm. Stable isotope fractionation of stream and soil water showed no kinetic evaporation at the Unimpacted site. Annual evaporation line slopes at the MPB site declined monotonically from 5.9 to 4.9 from 2010 – 2012, indicating abiotic evaporation contributed significantly to V. Increased evaporation was likely driven by greater subcanopy shortwave radiation, which averaged 21 Wm-2 during summer in the Unimpacted forest as compared to 66 Wm-2 in MPB-impacted forest. Runoff coefficients at the Unimpacted site varied from 14% to 40%, following the pattern of annual precipitation. MPB site runoff coefficients varied from 0% to 37% but declined monotonically each year. Collectively, these results show that compensatory vapor flux, including evaporation, may offset reduced interception and transpiration, thereby decreasing water available for streamflow. Key Words: Forest disturbance, evaporation, evapotranspiration, streamflow, insect, beetle 81 1. Introduction Forested watersheds are among the most reliable sources of clean water [Brown et al., 2005]. Montane forests world-wide are undergoing unprecedented die-off due to combined effects of increased temperature, drought, fire, and pathogen infestation [Williams et al., 2010, 2013; Breshears et al., 2009; Adams et al., 2012; Westerling et al., 2006; Huber, 2005; Tokuchi et al., 2004]. Of particular interest in Western North American forests is tree mortality due to endemic mountain pine beetle (MPB; Dendroctonus ponderoseae) [Raffa et al., 2008; Hicke et al., 2012]. Recent MPB activity is unprecedented, affecting more than 5 million hectares in the western US and British Columbia [Meddens et al., 2012]. MPB introduce blue-stain fungi that inhibit sap flow and usually kill host trees within several weeks to months [Hubbard et al., 2013]. Dead trees may retain their red-brown needles for one to three years, termed a red phase [Wulder et al., 2006]. Once needles have fallen, the killed MPB hosts are said to be in a grey phase, which may last years to decades. This progressive change in canopy structure over several years without immediate soil disturbance is different than harvest or fire, challenging our ability to predict MPB effects on water resources [Clow et al., 2011; Mikkelson et al., 2012]. A large body of literature provides initial context for hydrologic response to MPB disturbance. Studies of forest disturbance impacts on streamflow have established that streamflow usually increases in proportion to forest area removed, with lesser response in dry regions [see Stednick, 1996; Brown et al., 2005]. However, only a small portion of studies has been conducted within interior mountain conifer forests with annual precipitation of 600 to 1200 mm [Bosch and Hewlett, 1982], which describes much of the North American forest impacted by MPB. Disturbance effects in interior mountains are the weakest and most variable (r2 = 0.01) of all eco-regions in the United States [Stednick, 1996]. Even streamflow response to 100% forest 82 removal can be highly variable in interior mountains, with increases ranging from 0 to 350 mm [Stednick, 1996]. Variable streamflow response reflects variability in vapor flux due to snow sublimation [Troendle, 1983] and summer evapotranspiration [Brown et al., 2013; Hubbart et al., 2007], which remain poorly understood. Because the change in forest canopy following MPB is gradual, recent work has examined how progressive hydrologic partitioning response may affect water resources and forest succession [Edburg et al., 2012]. Forests regulate partitioning through interception, transpiration, and sheltering the land surface [Troendle and King, 1987; Molotch et al., 2009; Varhola et al., 2010]. Disturbance-driven changes in hydrologic partitioning may affect downstream water resources, including the amount and timing of streamflow [Pugh and Gordon, 2013; Brown et al., 2005; Ellison et al., 2012] and water availability for forest successional vegetation [Edburg et al., 2012]. Succession is likely to depend on both partitioning between streamflow and vapor flux as well as how vapor flux comprises sublimation, evaporation, and transpiration for plant growth [Edburg et al., 2012; Brown et al., 2013; Romme et al., 1986]. The expectations for response to MPB include an initial, large decline in transpiration followed by more gradual increases in sublimation, compensatory transpiration, and evaporation [Biederman et al., 2012; Edburg et al., 2012, Romme et al., 1986]. The timing and relative magnitudes of these changes are unknown, but the prevailing expectation is for greater streamflow [Pugh and Gordon, 2013]. There is limited and conflicting empirical evidence of streamflow response to MPB in support of these expectations. Increased streamflow was reported by Potts [1984] and Bethlahmy [1974], though an increase reported by Bethlahmy [1974] peaking 15 years post-MPB contrasts with the view that disturbance impacts are usually immediate and decline over years to decades 83 [Bosch and Hewlett, 1982; Stednick, 1996; Brown et al., 2005]. A recent study of eight MPBimpacted basins found both increases and decreases, attributed in part to variable interactions among topography and canopy loss in controlling vapor flux [Brooks et al., 2012; Somor, 2010]. Snowpack observations have shown either that winter vapor flux declined or that increased snowpack sublimation compensated for reduced canopy sublimation, resulting in no net change [Biederman et al., 2012; Boon, 2012; Pugh and Small, 2012]. In summer, total vapor flux has been observed to remain relatively constant several years following MPB infestation [Brown et al., 2013]. Conversely, land surface models predict reduced vapor flux with declining leaf area index (LAI) under simulated disturbance, leading to increased water availability for streamflow [Bewley et al., 2010, Pomeroy et al., 2012; Mikkelson et al., 2013b]. Similarly, remote-sensing products such as MODIS that use plant-mediated algorithms [Mu et al., 2011] predict reduced vapor flux [Bright et al., 2013; Maness et al., 2013]. The variable streamflow response to MPB [Bethlahmy, 1974; Potts, 1984; Brooks et al., 2012] and lack of consistency between observations and models demonstrates our limited ability to predict water resources following insect-driven disturbance. There is therefore a need to quantify hydrologic partitioning in insect-disturbed headwater catchments by observation of the dominant fluxes. Snow surveys quantify winter vapor flux over a range of spatial scales [Anderton et al., 2004; Musselman et al., 2008; Veatch et al., 2009]. Eddy covariance vapor flux observations above canopy [Baldocchi et al., 1988] allow computation of a tower footprint water balance for a footprint similar in magnitude to a headwater catchment (~101 ha) [Wilson et al., 2001]. Alternatively, using a traditional catchment water balance approach, the difference between precipitation and observed streamflow can be used to estimate catchment-scale vapor flux. Both water balance approaches usually assume that storage changes are small compared to 84 hydrologic fluxes and are therefore suited to seasonal to annual time scales [Brutsaert, 2005]. Finally, stable water isotope fractionation can be used to quantify both average humidity and the cumulative kinetic evaporation at any desired scale [Jasechko et al., 2013; Clark and Fritz, 1997]. Kinetic evaporation is a lower estimate of vapor flux because it does not include plant transpiration or the equilibrium component of evaporation. We present three years of observations following MPB infestation at a site with 52-77% MPB-driven overstory mortality and at a paired unimpacted site to answer the question: How does MPB tree mortality affect partitioning of precipitation between vapor flux and streamflow? To our knowledge, the present work is the first effort combining snow surveys, eddy covariance water balance, catchment water balance, and stable isotope indicators of evaporation to quantify hydrologic partitioning following forest disturbance. 2. Study sites An MPB-impacted site “MPB” and a control site “Unimpacted” were identified in 2009 along the eastern edge of the Central Rocky Mountains, a region severely impacted by MPB over the last 15 years (Figure 1). Due to extensive tree mortality, adjacent MPB-impacted and unimpacted stands having otherwise similar climate and biophysical characteristics could not be located. However, biophysical and meteorological observations at these sites over several prior decades and including our study period showed them to be well-paired in both pre-MPB condition and climate forcing. The MPB site (Figure 1) at Chimney Park WY is 100 km west of Cheyenne in the Medicine Bow National Forest and the headwaters of the Laramie River. The site experienced overstory mortality of 52-77% between 2007 and 2010. 85 The Unimpacted site (Figure 1) is located 125 km SSE of MPB and 50 km NW of Denver, CO within the Niwot Ridge Long-Term Ecological Research (LTER) observatory in the headwaters of Boulder Creek. The study area, known as “C1,” contains an above-canopy eddy covariance and meteorological tower and the Niwot SNOTEL station. MPB activity above background levels was not observed at this site through 2012 (< 5% of trees). To isolate MPB effects, we selected sites with gentle slopes (5 to 8%) and similar elevation of 2750 to 3000 m (Table 1). The sites are characterized by long, cold winters with continuous snow cover from October until May or June, and mean annual air temperatures of 1-3 °C. The Unimpacted site receives an average of 800 mm annual precipitation, with 400 mm as snow (Niwot SNOTEL 1981-2012). The MPB site similarly receives an average of 400 mm snowfall, but drier summers result in lower annual precipitation of 600 - 650 mm [Fahey et al., 1985]. Soils at both sites are of sandy loam texture. Overstory trees at the two sites are dominated by lodgepole pine (Pinus contorta) with most stands aged 110-140 years since the prior stand-replacing event [Knight et al., 1985; http://ameriflux.lbl.gov]. The eddy covariance tower footprints had trees of similar height (11 m). Mean diameters at breast height were 12.1 cm and 14.0 cm at the Unimpacted and MPB tower footprints, respectively, while stem densities were 3900 and 2500 stems ha-1. Further site details are given in Biederman et al., [2012] and by University of Colorado Mountain Research Station (http://culter.colorado.edu/NWT/index.html). 3. Methods 3.1. Quantification of MPB-driven Forest Mortality Forest characteristics and die-off status were obtained for the Unimpacted tower footprint using the AmeriFlux database [http://ameriflux.lbl.gov] and for the MPB tower footprint using annual ground-based surveys. Tree mortality across the MPB site was mapped by classifying 86 Quickbird imagery acquired on August 25, 2011. Live, red-phase, and grey-phase tree pixels, along with pixels of other land cover types, were identified on true-color imagery, and used to train and evaluate a maximum likelihood classifier that separated classes using green band, Normalized Difference Vegetation Index, and Red-Green Index variables [Coops et al., 2006]. Classification accuracy was 96.8% with a kappa of 0.962. 3.2. Local Climate and Soil Moisture Measurements The study period comprised hydrologic years 2010 to 2012 divided into two seasons termed winter and summer (all further reference to years indicates the hydrologic year, from October 1 to September 30). Winter was October 1 until the onset of snowmelt runoff, marked by five consecutive days of normalized streamflow increase of at least 0.05 mm d-2 in at least one catchment, with summer lasting from this onset of snowmelt until September 30. Observations were collected every 30 minutes of above-canopy temperature, vapor pressure deficit VPD, wind speed, and incident solar (shortwave) radiation Rsw. For the Unimpacted site, these data were obtained as an AmeriFlux Level 1 product (quality checked, calibrations applied and gaps filled) [http://ameriflux.lbl.gov], while gaps at the MPB site (~5% annually after the solar power system upgrade in 2011) were filled using linear regressions against the hourly NLDAS forcing data product (http://ldas.gsfc.nasa.gov/nldas/). Daily means were calculated for days with at least 20 hours of data, with remaining days rejected. Wind speeds were corrected to the same height above canopy at each site using a logarithmic profile [Shuttleworth, 2012]. Precipitation at the MPB site was observed by a cluster of weighing-type gauges located 250 m west of the eddy covariance tower (Figure 1) and bias-corrected to an onsite Geonor T200B reference weighing precipitation gauge. A wind correction for snowfall was applied to raw 87 measurements. Precipitation observations for the Unimpacted site were obtained from an onsite NOAA Climate Reference Network (CRN) site, gap filled with data from the SNOTEL station in winter (<5%) and a tipping bucket (<5%) in summer. In 20 plots (12 MPB and 8 Unimpacted), snow depths were observed using ultrasonic sensors (Judd Communications), while subcanopy solar radiation was measured using silicon cell pyranometers (model SP, Apogee Instruments, Logan, UT). Peak snow water equivalent SWE for 2010 and 2011 was determined by distributed depth surveys (n ≈ 2,000 site-1 year-1) and snow-pit based densities [Biederman et al., 2012]. In 2012, snowmelt commenced one month in advance of normal (March 9, 2012) before peak snowpack surveys could be performed. Volumetric soil moisture was observed in 2011 and 2012 using Decagon EC-5 and 5-TE sensors (Decagon Corp. Pullman, WA) at depths of 10 cm (+2 cm), 30 cm (+ 5 cm) and 60 cm (+ 10 cm) in each of six plots per site (n = 18 per site). 3.3. Eddy Covariance Vapor Flux Measurements An above-canopy eddy covariance flux tower was instrumented in 2009 at the MPB site with an open path infrared gas analyzer (IRGA) (LI-7500; Li-Cor Inc., USA) and a sonic anemometer (CSAT3; Campbell Scientific Inc., USA). 10 hz data were processed to 30-minute water vapor fluxes following Lee et al. [2004]. An unbiased statistical friction velocity filter [Gu, 2005] was used to remove periods with insufficient turbulence. Daily means were calculated for days with at least 20 hours of data. MPB site gaps in daily vapor flux (25%) resulted from solar power failure, lightning strikes and animal activity. To estimate cumulative seasonal vapor flux, we compared using the mean daily flux within the same year and season (e.g. summer 2011) against using linear interpolation of a 5-day running mean. These approaches produced cumulative seasonal fluxes that differed by < 5%, and the first approach 88 was selected. 30-minute vapor flux values for the Unimpacted site were provided as a Level 1 product by P. Blanken and S.P. Burns from [ftp://cdiac.ornl.gov//pub/ameriflux/data/Level1/ Sites_ByName//Niwot_Ridge/Fluxes/] and processed to daily fluxes. Energy balance closure at each site averaged about 80%, which is typical for tall-canopy eddy covariance systems, and corrections to force energy closure were not applied. Observations and data processing at both sites were consistent with AmeriFlux guidelines, reducing potential bias, and cumulative error at each site should be at or below 20% [Wilson 2002]. For winters 2010 and 2011, prior to MPB site winter flux measurements, cumulative winter vapor flux at both sites was determined by the difference of winter precipitation and peak snow water equivalent [Biederman et al., 2012]. The MPB site solar power system was upgraded in 2011, enabling winter eddy covariance observations thereafter. 3.4. Streamflow and Groundwater Measurements (MPB site only) Streamflow was gaged in nested catchments of first, second and third order at the MPB site (Figure 1) with respective drainage areas of 15, 136 and 725 ha using Hobo pressure sensors (Onset Corporation). Stream stage stations were added progressively such that the first-order catchment was observed in 2010 to 2012, the second-order catchment in 2011 and 2012, and the third-order catchment only in 2012, and stage records were compared for consistency across scales. The first-order catchment was gauged at a culvert that flowed partially full (tranquil flow throughout), and a rating curve was developed using outlet stage (Type 4 culvert flow) [Chow, 1959]. In the other catchments, empirical power function rating curves were developed using standard US Geological Survey streamflow methods [http://ga.water.usgs.gov/edu/streamflow2], and these remained consistent from year to year. The second-order catchment stage exceeded the observational rating curve for one week during 2011 snowmelt, during which Manning’s 89 equation [Chow, 1959] was applied using a cross-section survey. Daily streamflow for the 1100 km2 Laramie River above Woods Landing was obtained from USGS gauge 6659500 (http://waterdata.usgs.gov). We divided annual streamflow into that which occurred during snowmelt and the remainder, which was defined as base flow. Groundwater level was observed at the MPB site in a piezometer 114 cm deep placed 55 m east of and 3 m above the main channel of the second-order catchment in a topographically convergent “zero-order” channel observed to flow during snowmelt and for two to four weeks thereafter. 3.5. Water Balance Quantification At the Unimpacted and MPB eddy covariance towers, the tower footprint water balance was quantified as (1) where P is precipitation, V above-canopy eddy covariance vapor flux, ΔS the change in water storage, and Q* is residual water available for streamflow (Wilson et al., 2001). Annual changes in catchment water storage ΔS were assumed to be negligible in comparison to the other fluxes [Wilson et al., 2001]. While observed fluxes (P, V) were reported seasonally, the calculated water balance component Q* as only determined annually due to large intra-annual changes in water storage. Annual tower footprint partitioning coefficients were calculated for runoff and vapor flux . Precipitation and peak SWE were assumed to be uniform in space at each site based on the small site dimensions (< 8 km2), gentle terrain (maximum elevation difference of 120 m in the third-order catchment), and prior observations indicating no effect of MPB mortality on stand-scale peak SWE [Biederman et al., 2012]. 90 At the MPB site, catchment water balance was quantified for the first-, second- and thirdorder catchments as: (2) where Q is observed streamflow, V* the total catchment vapor flux estimated as the residual of the other terms [Brutsaert, 2005], and P and ΔS are as in Eq. 1. Annual catchment partitioning coefficients were calculated for runoff and vapor flux . 3.6. Stable Isotope Observations Rainfall was collected biweekly in amber glass bottles and protected from evaporation with mineral oil. Soil water was collected from using porous tension cup lysimeters (Prenart Corp.) at depths of 10 cm (+2 cm), 30 cm (+ 5 cm) and 60 cm (+ 10 cm) during and after snowmelt until the soils became too dry to produce samples under tension of 70 kPa. Twelve lysimeters were located in forested hillslopes at the MPB site with another eight at the Unimpacted site. Stream water samples were collected from the outlets of the zero-, first-, second- and third-order MPB catchments and an Unimpacted site zero-order catchment draining the study hillslope (Figure 1). Stream samples were collected daily at 15:00 by autosampler (ISCO Corp.) during snowmelt and by grab samples every one to two weeks during base flow. Isotopic signatures were not altered by up to 7 days storage inside the autosampler. Stable isotope ratios (δ2H and δ18O) were determined at the University of Arizona using a DLT-100 liquid water isotope analyzer (Los Gatos Research (LGR), Inc., model 908-000). Further analytical details are described in Lyon et al. [2009]. Isotopic enrichments of δ18O and δ2H (deuterium) values were used to evaluate kinetic, abiotic evaporation following the method given by Clark and Fritz [1997) and demonstrated 91 recently in field studies and regional- to global-scale analyses of evaporation, [Gustafson et al., 2010; Biederman et al., 2012; Jasechko et al., 2013]. Stream evaporation lines were used to quantify the catchment average humidity at the evaporating surface using the relationship of Gonfiantini [1986] as adapted by Clark and Fritz [1997]. The total fractionations of both δ18O and δ2H in the most enriched sample per site and year were used to quantify the maximum observed kinetic evaporation according to Rayleigh distillation [Clark and Fritz, 1997]. 3.7. Computational Methods and Software Catchment delineation was performed in ARC-GIS 10.1 with the TauDEM toolkit [http://hydrology.uwrl.usu.edu/taudem/taudem5.0/ accessed Feb. 2013] using a 1-m airborne laser swath map (ALSM). The percentage northerly aspect in each MPB catchment was defined as cells with slope greater than 5% and terrain aspect with a north component. Quickbird imagery was classified using Environment for Visualizing Images (ENVI) software. Statistical analyses were performed in MATLAB R2012a. Least squares regression with ANOVA was used to test whether mean daily shortwave radiation, wind speed and vapor pressure deficit were significant linear predictors of daily summer vapor flux, with ANCOVA used to evaluate MPB effects. The same approach was used to determine the local meteoric water line (LMWL) for each site from δ18O and δ2H in precipitation and to identify evaporation lines significantly different from the LWML. 4. Results 4.1. MPB Infestation The MPB site infestation began in 2007, and by August 2011, overstory mortality was 77% in the eddy covariance tower footprint and 62%, 61% and 52% in the first-, second-, and third-order catchments, respectively. Most of the killed trees in the tower footprint had lost their 92 needles and progressed to grey phase by winter 2011. Understory appeared to respond rapidly to the release of resources, with understory cover reaching 28% to 37% by summer 2011 in greyphase stands as compared to 3% in uninfested stands at the MPB site [Borkhuu et al., submitted to Soil Biology and Biochemistry, 2013]. 4.2. Local Climate and Soil Moisture In the three years of this study (2010-12), precipitation at the Unimpacted site was 100%, 128% and 90% of average (onsite SNOTEL 1981-2012), while the Cinnabar Park SNOTEL 20 km distant from the MPB site indicated precipitation for 2010-12 was 121%, 127% and 74% of the 2004-12 average. Winter precipitation ranged from 295 to 459 mm and accounted for 40% to 52% of annual precipitation at the Unimpacted site and 55% to 72% of annual precipitation at the MPB site. Winter precipitation was similar at the two sites, varying between sites in any year by 5 to 9% (Table 2). Summer precipitation ranged from 125 to 566 mm and was more variable among years and between sites than winter precipitation. The Unimpacted site experienced more summer precipitation, with the largest seasonal difference between sites in summer 2012 (125 mm at MPB and 428 mm at Unimpacted). Patterns of snow accumulation and ablation were similar at the two sites (Figure 2). Peak SWE ranged from 212 to 287 mm and differed between the two sites in any year by 3% to 24% (Table 2). Spring snowmelt commenced at the same time at each site and ended about one week earlier at the MPB site each year. Above-canopy observations of T, VPD, wind speed and Rsw showed similar seasonal means (Table 2) and temporal patterns (Figure 2) at the two sites. Mean T ranged from -4.0 to 5.3 ˚C in winter and 7.5 to 10.5 ˚C in summer. Mean VPD averaged 0.13 to 0.27 kPa in winter and 0.58 to 0.90 kPa in summer. Mean winter VPD was lower by 0.05 to 0.11 kPa at the MPB 93 site, while in summer, MPB site mean VPD was greater by 0.17 to 0.21 kPa. Mean daily wind speeds in all seasons ranged from 2.9 to 6.1 m s-1 and were greater at the Unimpacted site by 0.6 to 2.0 m s-1. Above-canopy Rsw was similar at the two sites, but mean subcanopy Rsw under MPB forest was greater by three times or more, averaging 61 to 70 W m-2 in summer as compared to 20 to 21 W m-2 under Unimpacted forest (Table 2). Volumetric soil moisture averaged 28 % at the MPB site and 19 % at the Unimpacted site. Peak soil moistures of 36% for MPB and 39% for Unimpacted were reached each year during late snowmelt. Snowmelt was the dominant input to soil moisture, which usually decreased monotonically each summer, reaching minima of 20% and 15% on average at the MPB and Unimpacted sites, respectively. A few small responses of soil moisture (3 to 5% increase) to summer rains were observed only at the Unimpacted site and shallowest (10 cm) depth. 4.3. Tower Footprint Water Balance Vapor flux time series showed similar patterns at each site both seasonally and daily (Figure 3), consistent with the similar seasonal means (Table 2) and daily variability (Figure 2) of likely environmental drivers of vapor flux: wind speed, T, VPD, and Rsw. Annual V at the two sites was equal to one another in 2010, when P was very similar. In 2011, the year with greatest P (Figure 4), the MPB tower V (Figure 3) averaged 50% to 100% greater than Unimpacted V during snowmelt, and V remained greater at the MPB site throughout most of the relatively wet summer in spite of greater precipitation at the Unimpacted site (Figure 4). Similarly, in 2012 a pattern of greater V at the MPB site was observed up until June. The MPB site subsequently received only 29% as much summer P as the Unimpacted site, and by August and September 2012, V was 30% to 50% lower at the MPB site. Continuous eddy covariance 94 tower operation in winter 2012 showed similar V to the Unimpacted tower, consistent with prior snow surveys showing similar winter V at each site in 2010 and 2011 [Biederman et al., 2012]. Annual eddy covariance tower V ranged from 569 to 691 mm (Table 3) and varied among years by only 9% at the Unimpacted tower as compared to 21% variability among years at the MPB tower. In 2010, when many of the recently-killed MPB trees remained in the red phase, annual V differed by <1% between the two towers, leading to similar residual streamflow Q* of 220 mm for Unimpacted and 182 mm for MPB. In 2011, when most MPB trees had lost their needles and progressed to the grey phase, annual V was 13% (79 mm) greater at the MPB tower compared to Unimpacted in spite of 30% (239 mm) lower precipitation, leading to MPB Q* of only 95 mm as compared to 413 mm for Unimpacted. In the dry year 2012, the Unimpacted tower footprint received 10% less precipitation than average but recorded its highest annual V of the three years, resulting in its lowest annual Q* (99 mm). Meanwhile 2012 MPB V exceeded P, leaving no water available for Q*. Expected climate drivers VPD, Rsw and wind speed were tested for prediction of summer V at each tower. VPD was a significant predictor of daily vapor flux (p < 0.001, Figure 5), and the linear regression slope was nearly four times greater (p < 0.001) at the Unimpacted tower (slope = 1.04 mm kPa-1) than the MPB tower (slope = 0.27 mm kPa-1). Interestingly, the intercept of this regression was larger at the MPB tower (2.1 mm) than the Unimpacted tower (1.5 mm), resulting in greater predicted V at the MPB tower when VPD < 0.8 kPa. Mean daily Rsw and wind speed were not significantly predictors of summer daily V at either site. 4.4. Stable Isotope Indicators of Evaporation Isotopes suggested that snowmelt was the primary water source to both soil moisture and streams. At both sites, isotope values in stream and soil water were much closer to those of 95 snowpack (mean δ18O of -21‰) than of summer rain (mean δ18O of -10 ‰). However, at the Unimpacted site, six samples of 10-cm soil water and two stream samples had δ18O > -12‰ (Figure 6), suggesting occasional small increases in shallow soil moisture from summer precipitation. Soil water and stream samples at the MPB site followed evaporation lines beginning with the isotopic signature of snowpack. All stream water isotopes plotted along these evaporation lines, indicating snowmelt as the primary water source and consistent with the observed lack of deep soil moisture response to summer rainfall. Isotopes showed more kinetic evaporation at the MPB site, with evaporation line slopes falling below the LMWL (p< 0.05) in both soil water and stream water at four spatial scales (Figure 6). The lack of evaporation line at the Unimpacted site indicates no significant kinetic fractionation. Equilibrium evaporation (humidity of 100%) is not excluded, but net evaporation into a saturated transition layer would be less due to simultaneous condensation [Clark and Fritz, 1997]. Evaporation lines were not different (p > 0.05) within a given year between MPB soil and stream water, so these were combined to determine one MPB site evaporation line per year (Figure 6). The resulting slopes decreased from 5.9 to 5.7 to 4.9 for 2010 to 2012, respectively. These correspond to average humidity of 87%, 84%, and 66% (Table 4). At the MPB site in 2010, the most enriched stream water showed greater evaporation than the most enriched soil water (32% evaporative fraction from stream water and 25% from soil water). In 2011 and 2012, however, the most enriched MPB soil water showed greater evaporation than the most enriched MPB stream water, with stream evaporative fraction reaching 42% in 2011 and 38% in 2012. 4.5. Catchment Water Balance (MPB Site Only) The onset of snowmelt runoff at the MPB site occurred April 9, March 25 and March 9 in the years 2010 to 2012, respectively (Figure 7). Groundwater at the MPB site responded to 96 snowmelt, with the water table reaching the ground surface during snowmelt in 2010 and 2011 and rising to within 20 cm of the ground surface in 2012 (not shown). Summer groundwater recession did not have observable responses to rain, consistent with the observed lack of response in soil moisture and water isotopes. Minimum groundwater elevation at the end of the hydrologic year was 10 cm greater in 2011 than in 2012. Other than snowmelt, the only hydrologic inputs producing observable response in groundwater and streamflow were during the first few weeks of October 2010 and 2011 (Figure 7). Precipitation during this period of low evaporative demand and before the establishment of permanent snowpack produced 1 to 4 cm rise in groundwater and a discernible streamflow response (> 0.2 mm d-1) in the second- and third-order catchments. In the first-order MPB catchment, which overlapped the MPB tower footprint, annual streamflow Q (Table 5) declined monotonically from 2010 to 2012 despite the greatest precipitation in 2011. Two-thirds of the first-order catchment Q reduction (-167 mm) between 2010 and 2011 occurred during snowmelt (Figure 7; Table 5). Only 11 mm of annual Q were measured in the dry year 2012, consistent with tower V exceeding annual precipitation (Table 3). First-order catchment V* was greatest in 2011 and lowest in the dry year 2012 (Table 5), reflecting the same inter-annual pattern as the observed eddy covariance V (Table 3). The MPB second-order catchment and Laramie River hydrographs were broader and peaked later than the first-order catchment hydrograph in 2010 and 2011, while streamflow was very small at all spatial scales in 2012 (Figure 7). The 1100 km2 Laramie River produced 200 mm of area-normalized streamflow Q in 2010 and 280 mm in 2011, consistent with greater P in 2011 than 2010 (SNOTEL) but in contrast to the reduced Q in the first-order catchment. The second- and third-order catchments produced greater Q than the first-order catchment, resulting 97 in lower V* (Table 5). The second-order catchment RC was 36% and 19% in 2011 and 2012, while the third-order catchment RC was 17% in 2012, the only year it was observed. 4.6. Comparison of Sites and Water Balance Approaches Annual hydrologic partitioning was summarized by the vapor flux coefficient VC and runoff coefficient RC (Figure 8). Similar VC and RC* at each tower footprint indicated similar partitioning in 2010, when many of the MPB site trees remained in the red phase. Unimpacted RC* followed the pattern of annual P, with the highest partitioning to streamflow (40%) in the wet year 2011 and the lowest percentage (14%) in the dry year 2012, while the MPB RC* declined each year of the study, from 24% to 12% to zero. Similarly in the first-order MPB catchment, which overlapped the tower footprint, RC declined from 37% to 16% to 2% over the period 2010 – 12. Both tower footprint and catchment water balance approaches consistently indicated an increased percentage of precipitation consumed by vapor flux (increasing VC or VC*) and reduced availability of water for streamflow (decreasing RC or RC*) at the MPB site. 5. Discussion Both eddy covariance observations of vapor flux and catchment surface discharge consistently showed increased vapor flux and reduced streamflow following severe MPB infestation in the central Rocky Mountains. Strong evidence of kinetic fractionation of stream and soil water isotopes indicated that part of this response was due to an increase in evaporation due to the canopy opening up following tree mortality. Results from this comprehensive approach differ from prior studies based on streamflow [Potts, 1984; Bethlahmy, 1974], model simulations [Bewley et al., 2010; Mikkelson et al., 2013b; Pomeroy et al., 2012] and remote sensing [Bright et al., 2013; Maness et al., 2013], that suggest a hydrologic partitioning shift towards reduced vapor flux and increased streamflow following beetle-induced disturbance. 98 Given that the sign of observed response is opposite of expectations, it is necessary to examine the evidence from each water balance approach. Next, we evaluate evidence regarding mechanisms and drivers of increased vapor flux. Finally, we discuss the impact of vapor flux increases on our understanding of hydrologic partitioning response to forest disturbance. Catchment and tower footprint water balances were consistent in showing reduced streamflow at the MPB site in comparison to the Unimpacted tower water balance. Consistent year-to-year reductions in MPB site Q* and first-order catchment Q (Table 3; Table 5), which had the longest observational record and overlapped with the MPB tower footprint during prevailing west winds, increased our confidence in interpreting the observed hydrologic response. The first-order catchment residual between Q and Q* ranged from 11 to 95 mm (2 – 13% of annual P), similar to a mean annual residual of 60 mm (5% of mean annual P) over five years reported by Wilson et al. [2001]. Lower annual vapor loss from the MPB catchments than the MPB tower (Table 3; Table 5) suggest that lower mortality in the first-, second- and thirdorder catchments (62%, 61% and 52%, respectively) could have resulted in lower vapor loss than in the tower footprint (mortality 77%). Alternatively, lower vapor losses could be related to the greater percentages of land surface with northerly aspect in the larger catchments, which we would expect to reduce available energy for vapor flux. Our assumptions of negligible annual changes in storage ΔS and lateral advection did not appear to affect our conclusions [Wilson et al., 2001; Hubbart et al., 2007; Scott, 2010]. Base flows reached similar low values each year (Figure 7), and stream water isotopes reflected only the signature of snowmelt progressively enriched by kinetic fractionation, suggesting no shift from near-surface to deeper streamflow sources (Figure 6). MPB V exceeded P in the dry year 2012 (Table 3). Since inter-annual variability in MPB water table elevations was small, on the 99 order of 3-5 cm, it is possible that there was lateral subsidy into the tower footprint [Mackay et al., 2002; Thompson et al., 2011], although we observed no corresponding increase in streamflow. Stand scale evaluations of the effects of forest disturbance often focus on precipitation, particularly snow, that is intercepted by vegetation and subsequently lost back to the atmosphere [Troendle et al., 1983; Pugh and Small, 2012]. However, our results show that evaporation can remove a significant fraction of precipitation reaching the ground. Process-based research has shown that intermediate forest density can minimize winter vapor loss [Veatch et al., 2009; Gustaffson et al., 2010] and enhance summer soil moisture [Gray et al., 2002] due to effective shading from solar radiation. Accordingly, it is not surprising that severe canopy loss can drive increases in snowpack sublimation canceling or outweighing reduced canopy sublimation (Biederman et al., 2012; Harpold et al., 2013] and that winter vapor flux was similar at MPB and Unimpacted sites (Figures 3 & 4, winter 2012). Still, the larger MPB site V as compared to Unimpacted during snowmelt 2011 and 2012 (Figure 3) showed that evaporation or sublimation of the melting snowpack was important (Table 5) [Schelker et al., 2013]. Stable isotope fractionation, which is not affected by transpiration, indicated greater kinetic evaporation at the MPB site (Figure 6), with stream and soil water samples showing maximum kinetic evaporation as large as 25 to 42%. Increases in evaporation are in addition to the well documented increase in transpiration of surviving vegetation stimulated by increased availability of water, light and nutrients [Kozlowski et al., 2002; McMillin et al., 2003; Van Pelt et al., 1999; Rhoades et al., 2013; Romme et al., 1986]. In light of the existing expectations for more streamflow, our observations of higher V (Figure 3) due in part to greater evaporation (Figure 6) are somewhat surprising. Higher MPB V 100 as compared to Unimpacted V was observed after most trees lost their needles (2011 and 2012) and during periods when water was plentiful at the ground surface, namely during snowmelt 2011 and 2012 and the relatively wet summer of 2011. Increased abiotic evaporation from a wet land surface suggests alterations to the subcanopy environment, though any differences in abovecanopy climate should be considered first when comparing different sites. Larger summer VPD at the MPB site could have contributed to larger V. However, the weaker response of summer V to VPD at the MPB site as compared to Unimpacted (Figure 5) suggests VPD differences did not exert a strong effect at the MPB site. The MPB site daily V was on average greater than the Unimpacted site when VPD was below average (0.8 kPa), suggesting that other drivers, such as wind or available energy, at least partially controlled MPB site vapor flux. The wind speed was lower at the MPB site, which would tend to reduce the evaporative demand of the atmosphere and therefore does not explain increased V. Despite similar above-canopy Rsw at the two sites, the more than 300% increase in subcanopy Rsw (Table 2) was the most likely driver of increased evaporation. Increases in remotely-sensed winter albedo following MPB infestation suggest higher shortwave radiation may drive increased evaporation across the landscape for years to a decade or more post-disturbance [Bright et al. 2013; Vanderhoof et al., 2013, O’Halloran et al., 2012]. Reduced partitioning to streamflow shown by declining RC and RC* (Figure 8) is in direct contrast to prevailing expectations and modeled results for hydrologic response to MPB [Pugh and Gordon, 2013; Bewley et al., 2010; Bright et al., 2013, Maness et al., 2013]. On closer examination however, our results are not inconsistent with the empirical record in response to forest disturbance. Bosch and Hewlett [1982] established that streamflow increase following disturbance was lower in dry regions, such as the semi-arid interior mountains which 101 are host to much of the present MPB epidemic. Stednick [1996] found that in the Rocky Mountains, streamflow response to disturbance was both the weakest and most variable of all regions in North America and documented examples of zero response when up to 100% of the forest was removed. Bethlahmy [1974] did not detect streamflow response in the first decade following MPB infestation in the Rocky Mountains, while a more recent study found a mixture of increases and decreases, with reduced streamflow in one catchment being the only significant change [Brooks et al., 2012; Somor, 2010]. Recently Brown et al. [2013] showed that total vapor flux was conserved for several years following MPB, but there remains uncertainty in the degree to which a tower footprint represents spatially heterogeneous catchments [Wilson et al., 2001; Foken, 2008; Scott, 2010]. Our results clarify that following severe MPB disturbance 1) vapor flux may increase, particularly during periods when water is abundant at the land surface, including snowmelt and rainy periods, 2) abiotic evaporation contributes a significant fraction of the total vapor flux, and 3) increased penetration of solar radiation beneath MPB-killed canopy is a likely driver of this compensatory evaporation. These results agree reasonably well with the hydrologic response expected by Edburg et al. [2012] but demonstrate that compensatory vapor fluxes may be as large as or larger than reductions in interception and transpiration, reducing water for streamflow. Our results highlight several priorities for future research. First, our study evaluated MPB disturbance in the central Rocky Mountains, and it is necessary to determine the applicability of our results across the range of latitude and climate within the present MPB epidemic from Canada [e.g. Rex and Dube, 2006] to Arizona [e.g. Morehouse et al., 2008] as well as to disturbance to other species of trees and by other beetle species [Raffa et al., 2008; 102 Hicke et al., 2012]. Second, complex topography has been shown to influence hydrologic partitioning [Scott, 2010; Flerchinger and Cooley, 2000; Flerchinger et al., 2010], yet it is unclear how forest disturbance might interact with topographic effects. We hypothesize that forest hillslopes with greater exposure to incident solar radiation may produce greater compensatory vapor flux following disturbance, as suggested by Rinehart et al. [2008]. Third, our observations of compensatory vapor flux contrast with land surface models [Bewley et al., 2010; Mikkelson et al., 2013b; Pomeroy et al., 2012] and remote sensing products [Bright et al., 2013; Maness et al., 2013], demonstrating a need to improve vapor flux representation in models. Fourth, resources managers remain uncertain about how interactions among climate change, forest disturbance, and forest management will affect water for forests [Grant et al., 2013] and downstream water resources [Clow, 2010; Harpold et al., 2012]. Our observations of increased subcanopy solar radiation and greater vapor fluxes during periods of wet land surface suggest that forest disturbance may increase the sensitivity of hydrological processes to climate. Finally, there is the possibility that increased abiotic evaporation may limit water availability for forests, with feedbacks to progression of mortality and forest succession [Kaiser et al., 2012; Grant et al., 2013]. 6. Conclusions Numerous forest disturbance studies [see Brown et al., 2005] suggest that any streamflow increase will be largest initially and decline back to baseline over a period of 10-15 years or more as regrowth occurs. Surprisingly, we are unaware of any studies demonstrating increased streamflow in response to the present MPB epidemic (post-1994) using long-term gauge records or paired catchments. While it remains possible that ongoing mortality will continue to alter hydrologic partitioning, eddy covariance tower footprint and catchment water balances 103 consistently yielded a similar inference of increased vapor flux, while stable isotope fractionation suggested a portion of the increase was due to abiotic evaporation. The resulting availability of water for streamflow was lower, in contrast to expectations. Future work should evaluate the ongoing progression of hydrologic response and the transferability of these results to other areas, but the observations presented here help clarify the lack of streamflow response observed at the larger scales relevant to water resources. 7. Acknowledgments This work was supported by funding from the National Science Foundation EAR0910831, United States Geological Service, Wyoming Agricultural Research Station through McIntire-Stennis and the Wyoming Water Development Commission. Science Foundation Arizona and the Arizona Water Sustainability Program provided additional support. LiDAR mapping of the MPB site was supported by an NCALM Seed grant. We thank B. Bright and J. Hicke of the University of Idaho for sharing QuickBird land cover classification of the MPB site. The National Science Foundation Niwot Ridge Long-Term Ecological Research project and the University of Colorado Mountain Research Station provided logistical support and data. The Niwot Ridge AmeriFlux tower data was provided by P. Blanken and S. Burns. The AmeriFlux tower has been supported by the US Department of Energy (DOE), the National Institute for Climate Change Research (NICCR) and Terrestrial Carbon Processes Program (TCP) and the National Science Foundation (NSF) Long-Term Research in Environmental Biology (LTREB). Supplementary snow pit data for Niwot were provided by J. Knowles. Additional regional atmospheric reference data were provided by J. Frank and the Glacier Lakes Ecosystem Experiments Site. The National Center for Atmospheric Research is supported through a 104 cooperative agreement from the National Science Foundation. The authors thank T. Meixnier, B. Bright and Z. Guido for useful comments. 8. References Adams, H. D., Luce, C. H., Breshears, D. D., Allen, C. 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(m) DBH (cm) 3000 40° 02′ -105° 33′ 100 3900 11.4 12.1 Cryochrepts Sandy Loam 2750 41° 04′ -106° 07′ 90-110 2500 11.1 14.0 Cryochrepts Sandy Loam The sites had similar elevation, soil texture, stand age and average tree sizes in lodgepole pinedominated overstory. Location and elevation are for the eddy covariance (EC) towers. The Unimpacted site had greater stem density in the eddy covariance tower footprint. bScott-Denton et al., 2003; cKnight et al., 1985. 111 Table 2. Local climate for the Unimpacted and MPB sitesa Year SWE (mm) YR P (mm) W S T (˚C) YR W VPD (kPa) S W Wind Speed (m s-1) S W S Rsw Above Canopy (W m-2) W S Rsw Below Canopy (W m-2) W S ---------- Unimpacted --------2010 2011 2012 230 (2) 270 (2) 222 (6) 420 459 295 381 801 566 1025 428 722 -4.8 (5.9) -4.0 (7.1) -4.0 (5.9) 9.0 (6.2) 7.5 (7.3) 9.0 (6.0) 0.24 (0.19) 0.24 (0.20) 0.27 (0.19) 0.64 (0.40) 0.58 (0.40) 0.69 (0.41) 5.2 (2.9) 6.1 (3.2) 6.0 (3.4) 3.5 (1.5) 137 (63) 251 (79) 4.1 (2.1) 129 (59) 250 (81) 14 (9) 3.6 (1.4) 131 (50) 240 (79) - 21 (12) 20 (12) - 3.2 (1.0) 3.8 (1.2) 4.1 (1.3) 2.9 (0.8) 131 (62) 275 (74) 3.1 (1.0) 123 (55) 261 (85) 25 (15) 2.9 (0.9) 124 (45) 270 (74) - 61 (39) 70 (40) ---------- MPB --------2010 2011 2012 a 286 (1) 270 (3) 266 (10) 440 430 323 311 751 356 786 125 448 -5.1 (5.5) 10.2 (6.2) -4.0 (7.0) 9.1 (7.6) -5.3 (5.9) 10.5 (6.2) 0.13 (0.15) 0.19 (0.22) 0.20 (0.16) 0.82 (0.45) 0.75 (0.51) 0.90 (0.47) YR, yearly; W, winter; S, Summer; SWE, peak snow water equivalent; P, precipitation; T, temperature; VPD, vapor pressure deficit; Rsw shortwave (solar) radiation. For SWE, the mean and one standard error of spatially distributed observations are shown. Precipitation values are period totals. All other values shown are mean (std. dev.) of daily values. The sites received similar winter precipitation and peak SWE, but the Unimpacted site received more summer P. T was similar at both sites. WS was lower at the MPB site. MPB site VPD and Rsw were slightly lower in winter and higher in summer than at the Unimpacted site. Below-canopy Rsw averaged 70% greater in winter and 300-350% greater in summer at the MPB site as compared to Unimpacted. In 2012 the sites received the lowest P and had the greatest mean VPD of the study period. 112 Table 3. Eddy covariance tower footprint water balance at the Unimpacted and MPB sitesa Year W P (mm) S Year W V (mm) S Year Q* (mm) Year RC* = Q* ÷ P (%) Year 220 413 99 27 40 14 182 86 0b 24 11 0b ---------- Unimpacted ---------2010 2011 2012 420 459 295 381 566 428 801 1025 722 190 189 194 383 423 429 573 612 623 -------------- MPB --------------2010 2011 2012 a 440 430 323 311 356 125 751 786 448 154 160 207 416 540 384 569 700 591 P, precipitation; V, vapor flux, Q*, residual streamflow; RC* eddy covariance water balance runoff coefficient Q* P-1; W, winter, S, summer; MPB, mountain pine beetle site. Annual vapor flux varied by 9% at the Unimpacted site and 21% at the MPB site. RC* coefficient declined each year at the MPB site, while at the Unimpacted site, the runoff coefficient showed a similar pattern to annual precipitation, with the highest value in 2011 and lowest in 2012. bTotal vapor flux for 2012 exceeded precipitation. 113 Table 4. MPB site annual stable isotope fractionationa Year Evaporation Line Slope (-) Transition Layer Humidity (%) Soil Water Δ18O-max (‰) Stream Water Δ18O-max (‰) Soil Water fkin-max (%) Stream Water fkinmax (%) 2010 5.9 87 4.3 5.6 25 32 2011 5.7 84 9.3 5.0 42 28 2012 4.9 66 9.8 6.3 38 26 Δ O-max, enrichment of the most isotopically enriched sample with respect to the local meteoric water line; fkin-max, fraction of precipitation evaporated kinetically in the most enriched sample with respect to the local meteoric water line. a 18 114 Table 5. Annual catchment water balance fluxes at the MPB sitea Water Year P (mm) V* (mm) Snowmelt Q (mm) Base Flow Q (mm) Total Q (mm) RC = Q ÷ P (%) ------------ first-order catchment 15 ha; 11% northerly aspect, 62% mortality----------2010 2011 2012 751 786 448 474 657 437 250 83 5 27 52 6 277 129 11 37 16 2 ---------- second-order catchment 136 ha; 20% northerly aspect, 61% mortality ---------2011 2012 786 448 506 362 150 78 130 8 280 86 36 19 --------- third-order catchment 725 ha; 39% northerly aspect, 52% mortality -------2012 a 448 374 45 31 76 17 P, annual precipitation; V*, annual catchment-based residual vapor flow; Q, annual observed streamflow. Q in the first-order catchment declined by 53% from 2010 to 2011 in spite of 5% greater precipitation, indicating increased V*. The decline in Q was due primarily to a 67% reduction in snowmelt Q, highlighting the importance of this brief period for annual hydrologic partitioning. Forest mortality was quantified August, 2011, when most dead trees were in grey phase. 115 10. Figures Figure 1. Site maps (upper panels) and detail maps (lower panels). Both sites include precipitation gauges, eddy covariance and meteorological towers. At each site, stable water isotopes were sampled from soil lysimeters, and zero-order streams. Streamflow and stable water isotopes were observed at the outlets of three nested catchments at the MPB site. 116 117 Figure 2. Precipitation at the a. Unimpacted and b. MPB sites, c. snow depth, d. temperature, e. vapor pressure deficit VPD and f. incoming shortwave radiation Rsw divided by winter W and summer S. Patterns of winter precipitation were very similar at the two sites, but the Unimpacted site received more summer precipitation. Snow depth time series show similar patterns of accumulation and peak amounts, with the MPB site snowmelt 1 to 2 weeks earlier than at the Unimapcted site. Temporal patterns of T, VPD and Rsw were very similar between the two sites for most of the year. The Unimpacted site tended to have lower T, VPD and Rsw in late summer, consistent with more summer precipitation. Shown are 5-day running means of 30-minute observations. indicates winter (W) and summer (S). Shading 118 119 Figure 3. Above-canopy eddy covariance vapor flux V divided into winter W, and summer S, which begins with snowmelt SM. Values shown are 5-day running means of 30-minute observations. The MPB site showed larger vapor flux than the Unimpacted site during snowmelt 2011 and 2012. MPB site vapor flux was lower than at the Unimpacted site in late summer 2012, consistent with dier and warmer conditions (Figure 2). 2012 winter vapor flux patterns were similar for the two sites, consistent with snow surveys showing equal amounts of total winter sublimation in 2010 and 2011. -1 Vapor Flux (mm d ) W S W SM S W SM S SM 4 3 Unimpacted MPB 2 1 0 1-Oct-09 1-Apr-10 1-Oct-10 1-Apr-11 1-Oct-11 1-Apr-12 1-Oct-12 120 Figure 4. Cumulative annual (a.) precipitation P and (b.) eddy covariance vapor flux V divided into winter W, and summer S, which begins with snowmelt SM. When precipitation was very similar at each site in 2010, annual V was equal at each site. In 2011, the year with greatest P, MPB tower V (slope of cumulative flux) was greater than Unimpacted V during snowmelt and throughout the summer. In 2012, a similar pattern of larger flux at the MPB site was observed during snowmelt, but the summer was much drier at the MPB site (P = 125 mm) than the Unimpacted site (P = 428 mm), and MPB Vapor Flux (mm) Precipitation (mm) site V slowed during late summer of this dry year. 1000 a. W S W SM S W SM S SM 750 500 250 0 Unimpacted MPB 700 b. 500 300 100 0 1-Oct-09 1-Apr-10 1-Oct-10 1-Apr-11 1-Oct-11 1-Apr-12 1-Oct-12 121 Figure 5. Summer daily vapor flux as a function of vapor pressure deficit (VPD) at the Unimpacted and MPB eddy covariance towers. VPD was a significant predictor of summer vaporization at both sites (p < 0.01), but the MPB site vapor flux was less sensitive to VPD. The intercept was significantly greater at the MPB site, while the slope was lower (p < 0.01). When daily VPD was less than 0.8 kpa, the vapor flux was greater on average at the MPB site. Unimpacted Daily Vapor Flux (mm) 6 V = 1.04*VPD+1.5 MPB p < 0.001 V = 0.27*VPD+2.1 2 p < 0.001 2 R = 0.18 R = 0.01 4 2 0 0.5 1 1.5 2 0 0.5 Daily Mean VPD (kPa) 1 1.5 2 122 Figure 6. Stable water isotopes in soil water and stream water and the local meteoric water line (LMWL) for the (a.) Unimpacted and (b.) MPB sites. Stream water was not distinguishable from the LMWL at the Unimpacted site (p > 0.05). At the MPB site, evaporation line slopes less than the LMWL (p< 0.05) demonstrate kinetic fractionation, suggesting compensatory vapor flux due to abiotic evaporation. 123 Figure 7. MPB site area-normalized streamflow for nested first, second and third-order study catchments in the headwaters of the Laramie River, divided into winter W, and summer S, which begins with snowmelt SM. Greater vapor flux (Figure 3), especially during snowmelt, contributed to decreasing annual streamflow in the first-order study catchment. Time series shown are five-day running means. W -1 Streamflow (mm d ) 12 S W Peak = 23 SM S W SM S SM 10 1st-order 2nd-order 3rd-order Laramie Riv. 8 6 4 2 0 1-Oct-09 1-Apr-10 1-Oct-10 1-Apr-11 1-Oct-11 1-Apr-12 1-Oct-12 124 Figure 8. Annual vapor flux coefficients VC = V÷P and runoff coefficients RC = Q÷P for the (a.) Unimpacted tower footprint, (b.) MPB tower footprint and (c.) MPB firstorder catchment. Water balance calculated ratios are denoted by “ * ”. The MPB site tower footprint partitioning was similar to Unimpacted in 2010, but in 2011 the MPB tower V increased in spite of greater P, reducing RC*. In the dry year 2012, MPB tower footprint V (panel b.) exceeded annual precipitation, leaving no water available for streamflow and RC* of zero. MPB tower footprint VC were greater than catchment VC*, possibly because higher mortality in the tower footprint (77%) than across the firstorder catchment (62%) led to greater compensatory vapor flux. 125 126 APPENDIX C: CATCHMENT BIOGEOCHEMICAL IMPACTS OF BARK BEETLE INFESTATION ATTENUATED IN THE RIPARIAN ZONE AND HEADWATER STREAMS Manuscript for submission to the Journal of Geophysical Research-Biogeosciences Title: Catchment biogeochemical impacts of bark beetle infestation attenuated in the riparian zone and headwater streams Running title: Attenuation of bark beetle biogeochemical impacts Authors: Joel A. Biederman1*, P. D. Brooks1, T. Meixner1, A. A. Harpold2, , D. E. Reed4,5, E. Gutmann3 1 Department of Hydrology and Water Resources University of Arizona, Tucson AZ 85721 2 INSTAAR, Boulder, CO 80309 3 NCAR, Boulder, CO 80301 4 Department of Atmospheric Science and Program in Ecology University of Wyoming, Laramie, WY 82071 5 Department of Botany and Program in Ecology University of Wyoming, Laramie, WY 82071 Keywords: carbon, nitrogen, forest disturbance, groundwater, soil, insect, beetle 127 Abstract Forest disturbance is expanding in rate and extent and is affecting many montane catchments critical to water resources. Western North America is experiencing a bark beetle epidemic that has affected an estimated 20 million hectares of forest in Canada and the United states. Consequences for biogeochemical cycling may include loss of limiting nutrients critical to forest succession and contamination of ground and surface waters. We followed biogeochemical response to severe MPB forest mortality along a putative hydrological flowpath from the uplands to the riparian-stream system including soil water, upland and riparian groundwater, and nested streams of zero- to third-order, encompassing spatial scales of 10-1 to 103 m. Soil water and upland groundwater showed NO3 elevated by two orders of magnitude as compared to an unimpacted site, while upland groundwater also showed about five times greater DON. Nearly 100% of the NO3 impacts and most of the DON were attenuated in the riparian zone en route to the stream. DOC and DON in the impacted site channel network were attenuated by 46% and 65%, respectively, within 4.5 km downstream of channel initiation. These results indicate that groundwater was contaminated with organic and inorganic nitrogen, riparian zones protected streams from elevated groundwater N, and rapid attenuation of DOC and DON in headwater streams is partly responsible for the lack of biogeochemical impacts observed at the watershed scale. 128 1. Introduction Montane forests are among the world’s cleanest and most reliable water sources [Brown et al., 2005], but forests are changing rapidly due to combined effects of increased temperature, drought, fire, and pathogen infestation [Williams et al., 2010, 2013; Breshears et al., 2009; Adams et al., 2012; Westerling et al., 2006; Huber, 2005; Tokuchi et al., 2004]. Western North America has experienced rapid and extensive forest mortality due to endemic mountain pine beetle (Dendroctonus ponderoseae), and climate change is expected to enhance infestation dynamics [Ayres and Lombardero, 2000; Mitton and Ferrenberg, 2012]. Over the last two decades, bark beetles including mountain pine beetle (MPB) have affected approximately 20 million ha in western North America [Meddens et al., 2012], an area similar in extent to that impacted by wildfire. Mountain pine beetles introduce fungi, inhibiting sap flow and killing host trees within weeks to months [Hubbard et al., 2013]. Dead trees retaining red needles are said to be in a red phase for one to two years as needles are lost [Wulder et al., 2006]. During the subsequent grey phase, snags, branches and boles fall to the ground over years to decades. This progressive change in canopy structure and gradual input of organic matter to soils differentiates beetle mortality from more well-studied disturbances by harvest, extreme weather, or nonlethal pathogens, challenging our ability to predict biogeochemical impacts for ecosystem succession and water resources [Edburg et al., 2012; Adams et al., 2012; Mikkelson et al., 2013]. A significant body of literature provides context for expected biogeochemical response to forest disturbance by diverse agents including nonlethal insects [Swank, 129 1981; Bormann and Likens, 1979), harvest [Bormann et al., 1968; Schelker et al., 2012; Jones and Post, 2004] extreme weather [Houlton et al., 2003; Bernhardt et al.., 2005] and fire [Mast and Clow, 2008]. These disturbance studies have led to expected increases in aqueous loss of inorganic N, particularly NO3, which is of concern for both human health and ecosystem impacts [Galloway et al., 2003]. Higher NO3 loss has been reported for regions with high atmospheric N deposition, such as the northeastern United States [Bormann et al., 1968] or Europe [Huber, 2005] as compared to regions with lower N deposition, such as the western United states [Sollins et al., 1981; Rhoades et al., 2013]. While forest disturbance impacts for aqueous C fluxes are less well-studied than for N, streamwater DOC may increase following harvest [Schelker et al., 2012]. Unlike fire or harvest, mountain pine beetle disturbance does not initially disturb soils or remove biomass [Adams et al., 2012], so biogeochemical responses may differ. There is emerging evidence that strong upland biogeochemical response to mountain pine beetle translates poorly to the watershed scales relevant to water resources [Rhoades et al., 2013; Mikkelson et al., 2013]. Upland response includes increased needle litter with higher N concentrations [Griffin and Turner, 2012; Morehouse et al., 2008] and increased soil concentrations of NO3 and NH4 [Griffin and Turner, 2012; Morehouse et al., 2008; Clow et al., 2011; Huber, 2005]. Similar patterns were reported by Tokuchi et al. [2004] following pine wilt disease, which has comparable biophysical impacts to mountain pine beetle. Two studies of mountain pine beetle response in soil DOC have shown one increase [Kana et al., 2013] and one decrease [Xiong et al., 2011]. While increased streamwater NO3 has been reported in response to pine wilt in Japan 130 [Tokuchi et al., 2004] and bark beetle in Bavaria [Zimmermann et al., 2000], stream response to mountain pine beetle in North America has been weak for DOC [Mikkelson et al., 2012] and NO3 [Clow et al., 2011; Rhoades et al., 2013]. Hypotheses for the lack of apparent connection between upland and watershed-scale stream responses include spatial and temporal variability of infestation [Clow et al., 2011; Edburg et al., 2011], delayed response due to shifts in water fluxes and flowpaths [Mikkelson et al., 2012, 2013], dilution [Zimmermann et al., 2000] and N uptake by surviving vegetation [Rhoades et al., 2013; Zimmermann et al., 2000]. However, there is a critical lack of biogeochemical observation along hydrological flowpaths connecting the uplands and riparian-stream system against which to evaluate these hypotheses. Here we evaluate biogeochemical solution concentrations at an unimpacted site and a site with > 50% forest mortality along a putative flowpath [Lohse et al., 2009] including soil water, hillslope groundwater, riparian groundwater, and nested streams up to third-order. Our goals are to: (1) evaluate how biogeochemical impacts vary as putative flowpath length increases from upland soils to the stream network; and (2) identify flowpath elements critical to regulation of biogeochemical response (i.e. “hot spots” [Mclain et al., 2003]) to bark beetle-driven forest mortality. The present work forms part of a larger project quantifying coupled hydrological and biogeochemical response to mountain pine beetle, and we evaluate results of the present work in the context of observed physical hydrology [Biederman et al., 2012; Biederman et al., in review]. To our knowledge, this work represents the most comprehensive effort to observe biogeochemical impacts of the North American bark beetle epidemic on aqueous 131 biogeochemistry over such a spatial continuum from the uplands to the riparian-stream system over scales of 10-1 to >103 m. 2. Study sites An MPB-impacted site “MPB” and an unimpacted control site “UN” were identified in 2009 along the eastern edge of the Central Rocky Mountains, a region severely impacted by mountain pine beetle (Figure 1). Due to extensive tree mortality, adjacent impacted and unimpacted stands having otherwise similar climate forcing and biophysical traits were not found. However, biophysical and meteorological observations from prior and present work showed the MPB and UN sites to be well paired. To isolate MPB effects, we selected sites with gentle slopes (5 to 8%) and similar elevations of 2750 to 3000 m. Both sites had overstory dominated by lodgepole pine (Pinus contorta) aged 110-140 years since the previous stand-replacing disturbance [Knight et al., 1985; http://ameriflux.lbl.gov]. Soils at both sites are sandy loam cryochrepts and show depositional layering, although soils at MPB are of schist parent material, while UN soils are granitic (Table 1) [Knight et al., 1985; Scott-Denton et al., 2003]. Both sites contain onsite precipitation gauges and above-canopy meteorological towers. The sites are characterized by long, cold winters with continuous snow cover from October until May or June and mean annual air temperatures of 1-4 °C (Table 2). These sites were previously compared in studies evaluating changes to snowpack [Biederman et al., 2012] and water partitioning [Biederman et al., in review] in response to mountain pine beetle. UN (Figure 1) is located 50 km NW of Denver, CO within the Niwot Ridge LongTerm Ecological Research (LTER) observatory. MPB activity above background levels 132 was not observed at this site through 2012 (< 5% of trees). The site contains the Niwot SNOTEL station [www.wcc.nrcs.usda.gov] and Niwot Ridge AmeriFlux tower [http://ameriflux.lbl.gov]. Numerous prior studies have been conducted at this site [e.g. Brooks et al., 1998; Monson et al., 2002; Hood et al., 2005]. The MPB site (Figure 1) at Chimney Park, WY is located 125 km NNW of UN in the Medicine Bow National Forest. From 2007 to 2010, the site experienced overstory mortality of 50-80% [Biederman et al., in review]. The stream-riparian zone is dominated by phreatophytes not directly affected by mountain pine beetles. Previous research at MPB has addressed the effects of forest gaps on snow accumulation [Gary, 1974], nitrogen cycling [Fahey et al., 1985; Knight et al., 1985], and impacts of simulated bark beetle infestation on water and nutrient fluxes [Knight et al., 1991]. 3. Methods 3.1. Physical Hydrology and Weather At both sites, observations of soil water and groundwater were nested within upland hillslopes drained by zero-order streams, defined as the convergent portions of hillslopes where surface flow channels were observed to initiate (Figure 1). Additionally at MPB, the upland hillslopes were nested within larger study catchments of first and second order (Table 2). To investigate spatial patterns in MPB stream chemistry that emerged from preliminary results, a third-order catchment was added to routine sampling in 2012. Volumetric soil water content was observed using Decagon EC-5 and 5-TE sensors (Decagon Corp.) at depths of 10 cm (+2 cm), 30 cm (+ 5 cm) and 60 cm (+ 10 133 cm) in each of six plots per site (n = 18 per site). Water stages in all streams and one groundwater piezometer at each site were recorded using Hobo pressure transducers (Onset Corp.). Periods of missing data at the UN piezometer (~ 5% of all data) were gapfilled using linear regression (r2 = 0.98) to a 7-m deep well located 50 m away. Observations of meteorology and snowpack were made within 300 m of the hillslope and zero-order stream observations at each site (Figure 1) as described in Biederman et al., [2012]. 3.2. Biogeochemical Sampling and Analysis At each site, routine sampling included soil water, hillslope groundwater, riparian groundwater and streams (Figure 1) lasting from snowmelt onset until the source dried out or the start of the subsequent winter. Twelve porous cup tension lysimeters (Prenart Corp.) were located in forested MPB upland plots and another eight were located at UN at depths of 10 (+2) cm, 30 (+ 5) cm) and 60 (+ 10) cm. Soil water samples were collected every 1-2 weeks under tension of 70 kPa. Upland groundwater at depths of 110 (+ 20) cm, was sampled from 3-4 piezometers at each site every 1-2 weeks. Riparian groundwater at depths of 90 cm (+ 20 cm) was sampled from 2-4 piezometers every 1-2 weeks. During snowmelt, stream samples were collected daily by automated sampler at the outlets of the MPB and UN zero-order catchments of both sites as well as outlets of the first- and second-order MPB catchments. Additional grab samples were collected very 1-3 weeks at all catchment outlets and several intermediate stream locations. Water samples were transported to the lab on ice and filtered within 24 hours using 0.45-micron glass fiber filters. Filtered aliquots for analysis of dissolved organic 134 carbon (DOC) and total dissolved nitrogen (TDN) were stored at 4 ̊C and analyzed within 2-3 weeks on a TOC/TN analyzer (Shimadzu Corp.) with a method detection limit (DL) of 0.05 mg l-1 for DOC and 0.05 mg l-1 for TDN. Filtered aliquots for analysis of dissolved inorganic nitrogen (DIN), NO3 and NH4 were stored at 4 ̊C and analyzed within 1-2 weeks on a SmartChem Discrete Analyzer (Westco Scientific) with DL of 0.005 and 0.002 for NO3-N and NH4-N, respectively. Dissolved organic nitrogen (DON) was determined by subtraction of DIN from TDN. 3.3. Catchment Spatial Analysis and Statistics Contributing area, average hillslope slope, stream network, stream order [Strahler, 1952], and length and average slope of the main channel were determined for each MPB catchment using the TauDEM toolkit [http://hydrology.uwrl.usu.edu/taudem/taudem5.0] and a 1-m airborne laser swath map (ALSM) in ARC-GIS 10.1 software. Statistical analyses were performed using MATLAB 2012a (MathWorks Corp.) Standard errors of the means were used to quantify how well sample means estimated population means, while standard deviations were used to represent sample variability. To evaluate how concentrations of DON and DOC were predicted by distance from the channel head, we evaluated exponential models of concentration as a function of distance. Each solute was additionally evaluated using an exponential model with a putative nonzero asymptote. DOC was observed to remain relatively constant between the second-order and third-order streams, so the mean value from these two streams of 16 mg l-1 DOC was used as the asymptote. DON declined from the second-order to third-order stream, so the third-order mean value of 0.26 mg l-1 135 was used as the asymptote. Overall significance of channel distance as a predictor of concentration was determined from the p value of the F statistic versus a constant model. 4. Results The presentation of results begins with weather and physical hydrologic response at the UN and MPB sites. Biogeochemical concentrations are then presented along a putative flowpath beginning with UN, which provides context for the subsequent evaluation of biogeochemistry at MPB. The putative flowpath begins with shallow soil water, proceeds through deeper soil water into hillslope groundwater, continues across riparian groundwater into zero-order streams, and follows the channel network to streams of progressively higher order. 4.1. Weather and Hydrological Response The two years of this study were characterized by precipitation that was above average in 2011 and below average in 2012. For 2011 and 2012, precipitation at UN was 1025 mm and 722 mm, or 128% and 90% of average (onsite SNOTEL 1981-2012). At MPB, the 2011 and 2012 precipitation totals were 786 mm and 448 mm. No long-term record exists for MPB, but the Cinnabar Park SNOTEL 20 km distant indicated precipitation for 2011 and 2012 was 127% and 74% of average (2004-2012). Winter precipitation and snowpack accumulation were similar at the two sites (Figure 2), but MPB received less summer precipitation than UN, particularly in 2012 (Figure 2). In 2011 the mean annual temperatures were 2.8 and 1.9 ̊C at MPB and UN, while 2012 was warmer with mean temperatures of 3.4 and 3.2 C ̊ . In both years the snowmelt began synchronously at the two sites but proceeded more rapidly at MPB and finished 5 days 136 earlier at MPB than at UN. Below-canopy solar radiation averaged 74% greater during winter and 300-350% greater during summer at MPB as compared to UN. Volumetric soil moisture averaged 29% at MPB and 20% at UN in 2011, while in 2012 the means were 27% and 18%. The sites reached similar peak soil moistures of 36% at MPB and 39% at UN each year at the end of snowmelt. Soil moisture decreased throughout each summer, with the only response to summer rains observed being increases of 3 – 5% at the 10-cm depth at UN (data not shown). Stream and groundwater stage rose rapidly during snowmelt each year, with groundwater reaching the surface for several weeks at each site in the wet year 2011 and rising to within 10 to 20 cm of the surface in the dry year 2012 (Figure 3). Snowmelt was the dominant driver of stage in groundwater and streams, consistent with prior observations of stream water isotopes at both sites [Biederman et al., in review] and of soil moisture and streamflow dynamics at MPB [Knight et al., 1985]. However, groundwater and the zero-order stream stage at UN responded to a period of several weeks with persistent rainfall in July and August 2012 (Figure 2, Figure 3). In the wetter year 2011, annual runoff coefficients ranged from 11 to 36% at MPB as compared to 40% at UN, while in the drier year 2012, runoff coefficients ranged from 0-19% at MPB as compared to 14% at UN [Biederman et al., in review]. 4.2. Unimpacted Biogeochemistry From Uplands to RSS At the unimpacted site, mean chemistry in shallow soil water (nominal depth 10 cm) was highly variable, with DOC mean (standard deviation) of 34.4 (25.7) mg l-1 and DON of 1.32 (0.81) mg l-1, giving a ratio of mean DOC:DON of 26. (Table 3). Deeper 137 soil water (30-60 cm) showed 60-76 % lower concentrations and lower variability than shallow soil water, with DOC of 13.7 (3.6) mg l-1 and DON of 0.32 (0.07). DIN (both NO3 and NH4) remained near detection limits in soil water. While mean chemistry of hillslope groundwater was similar to deeper soil water, riparian groundwater and zeroorder stream water showed progressive reductions in DOC and DON. Ratios of mean DOC:DON for all locations except shallow soil water were relatively invariant, ranging from 40 to 48. Time series showed rising DOC in UN hillslope groundwater as the water table rose during snowmelt (Figure 3), with peak values of 26 mg l-1 in the wet year 2011 and 20 mg l-1 in the dry year 2012. DOC in UN riparian groundwater and zero-order stream water was comparatively constant through time. DON was consistently low in UN groundwater, with only one sample greater than 0.5 mg l-1 (Figure 4). UN zero-order stream water DON was likewise relatively constant in time, with 90% of samples in the wet year 2011 falling between 0.2 and 0.4 mg l-1. Zero-order DON was lower in the dry year 2012, with all samples below 0.1 mg l-1. NO3-N remained below 0.12 mg l-1 in the UN groundwater and zero-order stream, with most stream samples below detection limit (Figure 5). Along the putative hydrological flowpath at UN, the largest change in mean chemistry occurred between shallow and deep soil water (Figure 6). Unimpacted groundwater and zero-order stream had similar DOC, DON and DOC:DON ratio to deep soil water, and no large transitions in dissolved chemistry were observed between the uplands and the riparian-stream system. 138 4.3. MPB Biogeochemistry From Uplands to RSS At the MPB site, mean chemistry in shallow soil water was not significantly different from the UN site in DOC or DON (Table 3), and the ratio of mean DOC:DON was 42. NO3-N was much larger in shallow soil water at MPB (p< 0.001), with mean (standard deviation) of 1.21 (2.22) mg l-1, although NH4 was near detection limits, similar to soil water at UN. In deeper soil water, mean DOC and DON were reduced by 50% and 60%, respectively, as compared to shallow soil water, similar to the pattern observed at UN, while NO3 remained similarly high in deep and shallow soil water. Upland groundwater at MPB showed a further reduction of 36% in mean DOC as compared to deep soil water, but mean DON and NO3 in upland groundwater were the highest observed for any landscape unit in the study at 1.65 (1.2) mg l-1 and 3.68 (3.47) mg l-1, indicating a large accumulation of N in groundwater. MPB riparian groundwater and zero-order stream water showed mean DOC increases of 62% and 79% as compared to upland groundwater. Mean DON declined from the hillslope to riparian groundwater and the zero-order stream, with reductions of 80% and 65%, respectively. Nearly all the NO3 was attenuated upon entering the riparian zone, and both riparian groundwater and streams at all scales showed NO3 <= 0.05 mg l-1. Both DOC and DON were greater in the MPB zero-order stream as compared to the UN zero-order stream (p < 0.01). DOC in the higher-order streams (second- and third-order) was attenuated by 32% to 39% as compared to the lower-order streams (zero- and first-order), while DON was attenuated by 42% to 59%. 139 Time series of MPB upland groundwater showed similar DOC dynamics to the UN site, with rising concentrations as the groundwater table increased and peak values of 24 mg l-1 and 25 mg l-1 in the wet year 2011 and dry year 2012, respectively (Figure 3). DOC in MPB riparian groundwater was comparatively constant in time but with mean concentration (21 mg l-1) approaching the upland groundwater peak DOC concentrations. In the wet year 2011, MPB lower-order streams showed peak DOC near peak stage, followed by falling concentration with falling stage and then a gradual return to concentrations near those of riparian groundwater. Lower-order stream DOC was less dynamic in the dry year 2012, remaining similar to DOC in riparian groundwater. Higher-order stream DOC was comparatively constant in time through both years. Time series of DON showed high variability in MPB upland groundwater, with peak concentrations of 4.6 mg l-1 and 3.5 mg l-1 reached at peak stage in 2011 and 2012, respectively (Figure 4). While upland groundwater DON fell below 0.5 mg l-1 in 2011 as groundwater stage declined, 2012 concentrations remained above 0.5 mg l-1 during the entire period when samples could be obtained. Riparian groundwater DON was relatively constant, similar to the UN site, remaining below 0.7 mg l-1. DON is greater and more variable in lower-order than higher-order streams, similar to DOC, but the inter-annual differences are larger for stream DON than stream DOC, with lower concentrations in 2012. Along the putative flowpath at MPB, mean biogeochemical concentrations showed different patterns from those at UN (Figure 6). In the uplands, DOC and DON patterns with soil depth were similar at the two sites, declining sharply from shallow soils 140 to deep soils. DOC increased across the transition from uplands to the riparian-stream system at MPB, in contrast to UN, where no change was observed. Both NO3 and DON were elevated in MPB upland groundwater as compared to UN, indicating substantial groundwater N contamination, but most of this was attenuated across the transition from uplands to riparian-stream system. 4.4. Spatial Patterns of Chemistry in Nested MPB Streams Exponential decay regression models of DOC showed distance from the channel head to be a significant (p< 0.05) predictor of stream DOC across nine sampling locations at the MPB site ranging from 23 to 4580 meters (Figure 7). A simple exponential model overestimated DOC over the channel distance 1-3 km and underestimated DOC at larger distances, while an exponential with putative nonzero asymptote had greater curvature and more accurately reflected the stable DOC concentration at flow distances larger than 1 km. Distance from channel head was also a significant (p < 0.05) predictor of stream DON (Figure 8). A simple exponential model with lower curvature than the model with nonzero asymptote better predicted continued attenuation of DON across the two largest scales. 5. Discussion Observations of biogeochemistry along a putative hydrological flowpath [Lohse et al., 2009] showed expected patterns at an unimpacted site, while a site with severe mountain pine beetle infestation showed elevated soil water NO3, large increases of DON and NO3 in upland groundwater, and attenuation of DOC and DON in headwater streams. Our observations of increased N storage in upland groundwater and attenuation of C and 141 N in headwater streams improve current understanding of the weak response to bark beetle infestation observed at the watershed scale [Clow et al., 2011; Rhoades et al., 2013; Mikkelson et al., 2012]. In the following discussion, we evaluate plausible mechanisms for observed responses in the uplands and riparian-stream system (RSS) and draw inferences about whether these mechanisms occur gradually along hydrological flowpaths or locally at biogeochemical hot spots [McLain et al., 2003; Lohse et al., 2009]. We conclude with discussion of how this work improves understanding of biogeochemical response to bark beetle infestation and an outline of key priorities for future study. An unimpacted site (UN) provided context for expected hydrological and biogeochemical patterns in a subalpine, lodgepole pine-dominated catchment. Snowmelt was the dominant hydrological input to soil moisture and streams, which were supplied primarily by groundwater (i.e. all water moving through the subsurface) [Biederman et al., in review; Jensco et al., 2009; Frisbee et al., 2011]. Annual evapotranspiration (ET) averaged 618 mm and varied by only 2% between years, so runoff available for transporting biogeochemical solutes was determined by precipitation in excess of this relatively constant ET [Biederman et al., in review]. Biogeochemical concentrations at UN agreed reasonably with prior subalpine observations of DOC [Hood et al., 2003], DON, and NO3 [Hood et al., 2003b]. Soil water DOC and DON indicated decreasing organic matter (OM) with depth (Figure 6). Upland groundwater had similar mean DOC and DON concentrations to deep soil water with peaks during snowmelt suggesting OM flushing from shallower soils as groundwater approached the surface (Figure 3, Figure 4) 142 [Hornberger et al., 1994; Boyer et al., 1997]. Stream water DOC and DON reflected similar concentrations to the relatively stable concentrations of riparian groundwater, with small snowmelt peaks suggesting activation of OM-rich shallow flowpaths (Figure 3, Figure 4) [Bishop et al., 2004; Jencso et al., 2009; Lyon et al., 2011]. Low DIN at UN is consistent with fierce competition for N among plants and microbes in N-limited lodgepole pine ecosystems of western North America ([Fahey et al., 1985] as well as limited NH4 mobility. MPB received similar meteorological forcing to UN (Figure 2) and produced similar physical hydrological response in contrast to expected increases in snowpack and runoff outlined in recent reviews [Edburg et al., 2012; Pugh and Gordon, 2013; Mikkelson et al., 2013]. Mountain pine beetle infestation did not affect peak snowpack accumulation [Biederman et al., 2012], and ET was not reduced despite overstory mortality [Biederman at al., in review], meaning that runoff water for transport of biogeochemical solutes did not increase as expected [Mikkelson et al., 2013]. In the uplands, MPB soil water DOC and DON showed similar concentrations and reduction with depth as at UN (Figure 6) suggesting that increased litter inputs [Borhkhu et al., in review; Morehouse et al., 2008; Griffin et al., 2011] did not greatly increase soluble OM in soils. While our observations of 48% greater mean DOC in deep soil water at MPB than UN (Table 3, Figure 6) contribute to very limited observations of soil water DOC following bark beetle infestation [Mikkelson et al., 2013], the soil water DOC difference did not appear to have affected upland groundwater (Figure 6). The greatest impacts observed at MPB were elevated NO3 in soil water, consistent with prior 143 studies [Huber, 2005; Morehouse et al., 2008; Griffin et al., 2011; Clow et al., 2011] and elevated DON and NO3 in upland groundwater (Table 3; Figure 6). Research at MPB pre-dating the infestation showed only trace N [Fahey et al., 1985], so it is likely that bark beetle infestation caused groundwater N accumulation as has been observed in more humid climates [Zimmermann et al., 2000; Hobara et al., 2001]. When viewed along a putative vertical hydrological flowpath through surface soils, elevated N over a relatively small scale (~ 1 m), classifying this as a hot spot impact. Increased production of mobile NO3 was likely stimulated by higher litter N inputs [Morehouse et al., 2008; Griffin et al., 2011] and more rapid mineralization and nitrification [Hobara et al., 2001;] possibly related to higher soil moisture and incoming solar radiation favoring N mineralization and nitrification [Griffin et al. 2011; Zimmermann et al., 2000]. Increased NO3 leaching to groundwater was probably facilitated both by temporal asynchrony between periods of high soil water NO3 during snowmelt and uptake by short (i.e. snow covered) regenerating vegetation [Meixner et al., 2001] and by the mortality of more deeply rooted overstory trees [Romme et al., 1986]. Brooks et al. [1998] showed that microbial uptake of NO3 during snowmelt could store N for later use by plants, dampening NO3 flushing to streams, but this mechanism did not appear to prevent significant accumulation in groundwater. While upland piezometers were arrayed at variable distance from the stream-riparian zone (Figure 1), no compelling spatial patterns in chemistry were detected along the putative flowpath, suggesting upland groundwater behaved as a relatively well-mixed biogeochemical reservoir. 144 At the transition from the MPB uplands to the RSS, removal of nearly 100% of NO3 and the majority of DON (Table 3, Figure 6) classified this transition as a biogeochemical hot spot, consistent with extensive examples in the literature [e.g. Vidon et al., 2010; Dahm et al., 1998; Mulholland and Hill, 1997]. Such hot spots occur due to the mixing of limiting reactants, adjacency of different redox zones, and prevalence of plants and microorganisms [Lohse et al., 2009]. Possible mechanisms of NO3 removal include denitrification [Oelsner et al., 2009; Brooks and Lemmon, 2007; Meixner et al., 2007; Peters et al., 2011] and uptake by phreatophytes [Cirmo and McDonnell, 1997; Dosskey et al., 2010]. Riparian groundwater DOC concentration in excess of 20 mg C l-1 (Figure 3) is consistent with adequate substrate for denitrification [Baker and Vervier, 2004]. In a parallel study at MPB, Borkhu et al. [in review] observed higher fluxes of N2O from soils in wetter landscape positions, suggesting significant denitrification. While we did not quantify N stores or fluxes in riparian vegetation, it is likely that increased concentrations in water delivered from the uplands also resulted in greater plant uptake. An increase in mean DOC between MPB upland groundwater and the RSS (Figure 3, Figure 6) suggests the riparian zone as a source of DOC production [Bishop et al., 2004] which could support both greater microbial immobilization and the development of reduced redox conditions facilitating denitrification [Lohse et al., 2009] The attenuation of DOC and DON with increasing downstream distance improves our understanding of the responses to bark beetle infestation observed at the watershed scale. While the zero-order stream departed from the overall pattern of higher concentrations at lower flow lengths, steeper terrain (Table 2) may have reduced the 145 residence time of upland groundwater in the riparian zone and the resulting addition of DOM to water entering the stream. While DOC was attenuated by an average of 35% between the first-order (channel distance 600 m) and second-order streams (channel distance 3200 m), and an additional 11% at the third-order stream (Figure 7), and the residual concentration of 16 mg l-1 was well above stream DOC for the UN site (Table 3) and similar unimpacted subalpine streams [Hood et al., 2003]. Since the observed DOC response at larger watershed scales varies from weak [Mikkelson et al., 2012] to none [Clow et al., 2011], it appears likely that some combination of further downstream processing and dilution has muted the watershed-scale DOC response. In contrast, DON declined with channel distance over the range of observations and was reduced by 65% between the first-order and third-order streams, reaching the same concentration as the UN stream after ~ 5 km (Table 3, Figure 8). It therefore appears that a lack of N response to bark beetle infestation at the watershed scale [Clow et al., 2011; Rhoades et al., 2013] may be partly due to processing in headwater streams. While biogeochemical inputs related to bark beetle infestation could have varied among catchments at MPB, the relatively uniform and synchronous mortality across the study catchments (Table 2) suggests that mixing of different inputs does not likely explain declining DOC and DON with channel distance. Rapid attenuation of C and N in headwater streams can occur by both physical and biological immobilization [Covino et al., 2010; Bernal et al., 2012] and is facilitated by shallow, turbulent flow and high ratio of channel bed width to cross-sectional area, which foster movement of water between the stream and hyporheic sediments [Peterson et al., 2001; Wollheim et al., 146 2001]. Dissolved C and N may be permanently removed by respiration and denitrification or processed into other forms. These various removal mechanisms may be viewed as occurring either continuously along flowpaths [Meixner et al., 2001; Berhnardt et al., 2003] or in a sequence of biogeochemical hot spots in the stream-hyporheic system created by spatial and temporal variability in physical hydrology [Brooks and Lemmon., 2007]. Although the results of this study are consistent with the weak response to North American bark beetles in watershed-scale biogeochemistry, they contrast with expectations of greater impacts, particularly for N, from other disturbance studies. One likely explanation is that bark beetle disturbance has mainly occurred in the western part of the continent, where lower atmospheric deposition rates and greater N limitation often result in lower export following forest disturbance [e.g. Sollins et al., 1981; Fahey et al., 1985; Mast and Clow, 2008] as compared to disturbances from regions of higher N deposition in eastern North America [Vidon et al., 2010; Bernhardt et al., 2003] or Europe [Zimmermann et al., 2000; Huber, 2005]. An important corollary is that loss of N from soils to upland groundwater could put this limiting nutrient beyond the reach of regenerating vegetation, possibly impacting forest succession. A second factor limiting N loss is the semi-arid nature of much of the interior mountains affected by North American bark beetles. While N mineralization and nitrification have been observed in this and other studies, low annual runoff ranging from zero to a few hundred mm in this region [e.g. Flerchinger and Cooley, 2000] and low water flux may limit N loss [Vitousek 147 et al., 1979], consistent wtih lower stream DON in the dry year 2012 as compared to 2011 (Figure 4). 6. Implications and Conclusions The complete removal of NO3 and significant addition of DOC by the MPB riparian zone illustrates the importance of riparian hot spots. Efforts to evaluate or model biogeochemical response to forest disturbance should occur in the context of a system including both upland (catchment) and riparian-stream system (RSS) components (Figure 9) [Seidl et al., 2011], and efforts to manage disturbed forest should preserve riparian zones. Site differences in riparian zone vegetation or organic matter production could cause different biogeochemical responses, and future work should include similar observations to this study at sites with contrasting riparian environments. Hydrological differences would also be expected to alter outcomes if they affected residence times or flowpaths through the riparian zone [Lohse et al., 2009; Peters et al., 2011] including upland topography and soils and the amount, timing and partitioning of precipitation [Stednick et al., 1996; Biederman et al., in review]. Since MPB upland groundwater NO3 concentrations approached USEPA drinking water limits, this raises concern for how widespread bark beetle infestation may impact regional groundwater quality. Recharge to deeper aquifers is largely unquantified, but it is reasonable to additional N inputs will be attenuated within several years to decades as litter is processed [Borhkuu et al., in review] and vegetation takes up N more rapidly and from deeper rooting soil layers [Romme et al., 1986]. Future breakthrough of N from 148 upland groundwater to streams could occur [Hobara et al., 2001], raising concerns for increased aquatic productivity. Prior to this study, the weak stream response to bark beetle infestation has been attributed mainly to variability of impacts in time and space (i.e. dilution) [Zimmermann et al., 2000; Clow et al., 2011; Mikkelson et al., 2012] and compensatory uptake by surviving upland vegetation [Rhoades et al., 2013]. Significantly, this study illustrates that biogeochemical mechanisms at riparian hot spots and along flow paths in soils and streams can collectively attenuate some or all of the dissolved fluxes within small headwater catchments (Figure 9). 7. Acknowledgements This work was supported by funding from the National Science Foundation EAR0910831, United States Geological Service, Wyoming Agricultural Research Station through McIntire-Stennis and the Wyoming Water Development Commission. Science Foundation Arizona and the Arizona Water Sustainability Program provided additional support. LiDAR mapping of the MPB site was supported by an NCALM Seed grant. We thank B. Bright and J. Hicke of the University of Idaho for sharing QuickBird land cover classification of the MPB site. The National Science Foundation Niwot Ridge Long-Term Ecological Research project and the University of Colorado Mountain Research Station provided logistical support and data. M. Williams and M. 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(m) DBH (cm) Soils UN mortality < 5% 3000 40° 02′ -105° 33′ 100 3900 11.4 12.1 Cryochrepts Sandy Loam c MPB mortality 52-77% 2750 41° 04′ -106° 07′ 90-110 2500 11.1 14.0 Cryochrepts Sandy Loam b a Elevation Latitude (m) Longitude The sites had similar elevation, soil texture, stand age and average tree sizes in lodgepole pine-dominated overstory. The Unimpacted site had greater stem density and lower mean diameter at breast height (DBH). bScott-Denton et al., 2003; cKnight et al., 1985. 158 Table 2. Characteristics of the MPB study catchments. Main Channel Length (m) Main Channel Avg. Slope (%) Avg. Hillslope Slope (stdev) (%) MPB Catchment Area (ha) Overstory Mortality (%) Zero-Order 6 50 96 9.4 7.6 (5.5) First-Order 15 62 725 1.3 5.3 (4.3) Second-Order 136 61 3257 1.8 7.9 (6.5) Third-Order 725 52 4581 2.5 8.3 (6.5) 159 Table 3. Solute concentrations by landscape position at the Unimpacted (UN) and MPB sites. Landscape Position DOC (mg C l-1) DON (mg N l-1) NO3-N (mg N l-1) NH4-N (mg N l-1) ---------- UN ---------Soil Water 10 cm 34.4 (25.7) 1.32 (0.81) BDL 0.03 (0.01) Soil Water 30-60 cm 13.7 (3.6) 0.32 (0.07) 0.02 (0.02) ND Upland Groundwater 15.6 (5.4) 0.37 (0.14) 0.03 (0.03) 0.05 (0.02) Riparian Groundwater 12.6 (9.6) 0.26 (0.14) 0.01 (0.01) 0.10 (0.14) Zero-Order Stream 9.4 (1.8) 0.23 (0.10) 0.01 (0.01) 0.15 (0.17) ---------- MPB ---------- a Soil Water 10 cm 40.5 (15.3) 0.97 (0.34) 1.21 (2.22) 0.05 (0.02) Soil Water 30-60 cm 20.4 (12.9) 0.39 (0.22) 0.94 (1.60) ND Upland Groundwater 13.1 (5.9) 1.65 (1.2) 3.68 (3.47) 0.09 (0.04) Riparian Groundwater 21.2 (10.8) 0.33 (0.21) 0.05 (0.06) 0.09 (0.12) Zero-Order Stream 23.5 (4.7) 0.57 (0.24) 0.01 (0.01) 0.15 (0.16) First-Order Stream 26.4 (4.0) 0.63 (0.31) 0.02 (0.04) 0.09 (0.14) Second-Order Stream 16.0 (2.9) 0.33 (0.10) 0.03 (0.10) 0.10 (0.14) Third-Order Stream 16.9 (2.2) 0.26 (0.13) 0.02 (0.01) ND Shown are mean (standard deviation). Soil water showed much higher NO3 at the MPB site. DON and NO3 were elevated in MPB upland groundwater but mostly attenuated in riparian groundwater. Both DON and DOC decreased from the MPB zero-order stream to larger-scale streams. BDL = Below NO3-N detection limit of 0.005 mg l-1. ND = no data. 160 10. Figures Figure 1. Site maps (upper panels) and detail maps (lower panels). Both sites include precipitation gauges and meteorological towers. At each site, solution chemistry was sampled from tension lysimeters, upland groundwater (GW), riparian groundwater, and zero-order (0-ord.) streams. Additionally, stream chemistry was observed at the outlets of three nested catchments (1st through 3rd-order) at the MPB site. 161 Figure 2. Precipitation at the a. Unimpacted and b. MPB sites, c. snow depth, d. temperature. Precipitation patterns were similar at the two sites, but the Unimpacted site received more summer precipitation. Snow depth time series show similar patterns of accumulation and peak amounts, with the MPB site snowmelt finishing five to seven days earlier. Temperature was similar between the two sites, although the Unimpacted site tended to lower temp late summer, consistent with more summer precipitation. Shown are 5-day running means of 30-minute observations. 162 Figure 3. Time series of dissolved organic carbon (DOC) concentration and hydrologic stage for the mountain pine beetle (MPB) and Unimpacted (UN) sites showing (a) upland and riparian groundwater and (b) zero-order streams. The bottom panel (c) shows MPB nested streams of first through third order. Groundwater DOC from each source was relatively constant in time. UN groundwater decreased in DOC from hillslope to riparian, while MPB groundwater increased in DOC. The MPB zero-order stream had greater DOC than the UN zero-order stream. in the first-order stream than the larger streams. In the MPB streams (c), DOC was greater 163 164 Figure 4. Time series of dissolved organic nitrogen (DON). All other descriptions are as for Figure 3. Note the different vertical scale for panel a, where MPB upland groundwater was elevated in DON as compared to all other water sources. Riparian groundwater DON was similar at MPB and UN. Zero-order steam DON mirrored the riparian groundwater concentration at UN, while at MPB, zero-order stream DON was higher than in the riparian groundwater. In the MPB streams (c), DON was greater in the first-order stream than the larger streams. 165 Figure 5. Time series of dissolved nitrate (NO3) concentration. Note the logarithmic scale for NO3. All other descriptions are as for Figure 3. MPB upland groundwater had one to two orders of magnitude more NO3 than UN groundwater, but most of this difference was attenuated in riparian groundwater. Zero-order steams at both sites consistently showed only trace NO3, and NO3 remained low in higher-order MPB streams. 166 Figure 6. Solution concentrations of (a) DOC, (b) DON, and (c) NO3 across landscape units from the uplands to riparian-stream system at the MPB and Unimpacted (UN) sites. Shown are mean values and one standard error. Landscape positions are: SW 10 = soil water at 10 cm depth; SW 30-60 = soil water at 30-60 cm depth; HS-GW = hillslope groundwater; R-GW = riparian groundwater; Stream = zero-order streams. DOC was similar in SW 10 at both MPB and UN, but greater at the MPB site in SW 30-60. HSGW at each site had similar DOC, but MPB R-GW and stream water showed increases in DOC as compared to HS-GW. MPB soil water had one to two orders of magnitude more NO3 than UN soil water, and MPB HS-GW had much greater DON and NO3 than UN HS-GW. The MPB stream had higher DON than the UN stream, but only trace NO3 was observed in either stream. Only one sample of SW 10 was analyzed for NO3 at UN. BDL = Below NO3-N detection limit of 0.005 mg l-1. 167 168 Figure 7. Stream DOC concentration as a function of distance from the channel head at all MPB site sampling locations. Distance was taken via the longest upstream channel. Boxes shown represent the 25th to 75th percentile of all observations, while black markers show the median and whiskers show the remaining quartiles. The dashed curve is an exponential decay function fit by nonlinear least squares. The solid curve is a similar function decaying to an asymptote equal to the mean value of the 2nd-order and 3rd-order streams. Channel distance was a significant predictor of DOC using either model (p<0.05). Exponential Decay Exponential With Asymptote 50 DOC (ppm) 40 DOC = 14e-0.9D+16 DOC = 28e-0.16D 30 20 10 0 0 1 2 3 4 Channel Distance (km) 5 169 Figure 8. As for Figure 5, for DON. Channel distance was a significant predictor of DON using either model (p<0.05). 1.4 Exponential Decay Exponential With Asymptote 1.2 DON (ppm) 1 DON = 0.73e-0.21D 0.8 DON = 0.47e-0.36D+0.26 0.6 0.4 0.2 0 0 1 2 3 4 Channel Distance (km) 5 170 Figure 9. Conceptual model of biogeochemical solution concentrations across landscape positions from the hillslope to the stream-hyporheic zone and several orders of nested streams.
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