LINKING INUIT AND SCIENTIFIC KNOWLEDGE AND OBSERVATIONS
TO BETTER UNDERSTAND
ARCTIC CHAR (SALVELINUS ALPINUS (L.)) COMMUNITY MONITORING
A Dissertation Submitted to the Committee on Graduate Studies
in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy
in the Faculty of Arts and Science
TRENT UNIVERSITY
Peterborough, Ontario, Canada
© Copyright by Jennie A. Knopp 2017
Environmental and Life Sciences Ph.D. Graduate Program
May 2017
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ABSTRACT
Linking Inuit and Scientific Knowledge and Observations to Better Understand
Arctic Char (Salvelinus alpinus (L.)) Community Monitoring
Jennie A. Knopp
Arctic Char (Salvelinus alpinus (L.)) have been, and remain, an important subsistence resource for the Inuvialuit, the Inuit of the western Canadian Arctic. The effects of climate variability and change (CVC) in this region have been noticeably increasing over the past three decades. There are concerns as to how CVC will affect Arctic Char and the
Inuvialuit who rely on this resource as they will have to adapt to changes in the fishery.
Community-based monitoring, is an important tool for managing Arctic Char. Therefore, my dissertation focused on the central question of: Which community-based monitoring factors and parameters would provide the information needed by local resources users and decision-makers to make informed choices for managing Arctic Char populations in light of CVC?
This question is investigated through an exploratory research approach and a mixed method research design, using both scientific and social science methods, and quantitative
(scientific ecological knowledge and observation) and qualitative (Inuvialuit knowledge and observation) information. It is formatted as three journal manuscripts, an introduction, and an integrative discussion. The first manuscript examines potential habitat parameters for monitoring landlocked Arctic Char condition in three lakes on Banks Island in the
Inuvialuit Settlement Region. The second manuscript examines potential local
! ii! ! environmental parameters for monitoring landlocked Arctic Char growth in the same three lakes. The third manuscript investigates aspects of Arctic Char community-based monitoring programs (CBMP) in the Canadian North that have led to the sustained collection of useful data for management of the resource.
This dissertation makes contributions to the field of research by demonstrating the utility of a mixed methods approach. The results demonstrate similarities and differences in char growth and condition within and among Capron, Kuptan and Middle lakes on Banks
Island. This supports both lake-specific and regional climate-driven changes, meaning both lake habitat and local environmental monitoring parameters should be used in char CBMP.
The investigation of char CBMP across northern Canada demonstrates that an adaptive monitoring approach is important for subsistence fisheries, as changing lifestyles and environmental changes impacting a fishery can have direct effects on the successful operation of char CBMP.
Keywords: Arctic, Inuit, Inuvialuit, mixed methods, Arctic Char, Salvelinus alpinus,
Traditional Knowledge, Inuit Knowledge, community-based monitoring, monitoring, freshwater ecology, environment, environmental effects
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ACKNOWLEDGEMENTS
I would like to extend my sincere gratitude to the many people who willingly, and with great enthusiasm, offered their support to ensure the success of my research. I am extremely grateful to the over 100 people who dedicated their time, effort and knowledge.
I hope I have not missed any of the key players below.
First, I would like to dedicate this dissertation to those who passed on during my research. To Nanny (Kathleen Pitman), your endless encouragement, love, support and joie de vivre kept me going. I know you wanted to be there when I walked across the stage to accept my degree, but know you are always with me. To Omi and Opa (John and
Elisabeth Knopp), your strength and determination was a constant source of inspiration.
And to Poppa (Arthur Pitman) who passed too soon, you taught me so much, especially how we can persevere beyond hardships in life. Drew Esau, you left before your time, but your assistance and protection while on your beautiful island stayed with me in all that I do. Geddes Wolki, Martha Kudlak, Roger Kuptana and Andy Carpenter Sr., you adopted me as if I were your own, and taught me more than I could have ever imagined about knowing myself and our natural world. Dr. Rob Roughley, you provided me a home whenever I worked in Winnipeg. You are all deeply missed.
I would like to thank my supervisor Dr. Chris Furgal, who believed in me and guided me through the process of creating and carrying out my own research project, start to finish. Thank you also to my committee members Dr. James (Jim) Reist and Dr. Tom
Whillans, for all that you taught me, and your acceptance and encouragement for using a mixed methods approach to research.
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Quiyanainnyi and quana to the community of Sachs Harbour, who adopted me, and shared your never-ending knowledge, your beautiful land, and your vibrant culture with me. I cannot wait to see you all again soon. Thank you to the Sachs Harbour Hunters and
Trappers Committee, specifically Betty Haogak, for your support and assistance with this research.
To my husband, the incredible Dak de Kerckhove, this is quite the life we have created together! I am eternally grateful for your unwavering support throughout this process, in every form imaginable. I love you with all my heart. To my family and friends, your encouragement of persistence got me through difficult times. I appreciate your understanding of my need to be a recluse for many years while working full time and finishing my PhD during evenings, weekends and holidays. Your love, patience, and support over the past nine years are a part of this dissertation. Thank you to my Dad (John
Knopp), Mom (Susan Pitman), sisteronis (Rebecca Knopp, Emily Pardy, Delia Pitman), brother (Evan Knopp), nieces and nephews (Kristin Bailey, Owen Bailey, Max
Grzegorczyk, Charlie Pardy, Malcolm Pardy and Dexter Pardy), father-in-law (Derrick de
Kerckhove), brother- and sister-in law (Charles and Maiko de Kerckhove), Maria Pia
Rossignaud, the familia (Christiaan Iacoe, Emma Iacoe, Sarah Iaoce, Jake Howe, Ali
Lalani, Yana Lalani), Jaideep and Arlene Narayanan, my godson (Ajay Narayanan), Adam
Phipps, Ella Cooper, Sarah Carr, Saul Davis, Céline Cressman, Evan Richardson, Solomon
Krueger, and Regan and Elsbeth Fielding.
Thank you to my mentors, who taught me so much about various aspects of this research. First and foremost, I would like to thank my community mentors, Lawrence
Amos and Sheila Nasogaluak, for teaching me how to be a respectful Bankslamiut. Dr.
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Burton Alyes, Canada Member of the Canada/Inuvialuit Fisheries Joint Management
Committee and Larry Dow of Fisheries and Oceans Canada, thank you for always being there to answer my questions and share your wisdom. Thank you to Dr. Perce Powles and
Rick Wastle for teaching me the art of otolith analysis. John Babaluk, thank you for sharing the historical Fisheries and Oceans Canada data and your knowledge of the study lakes.
Dr. Evan Richardson, for over 1.5 decades you have continuously inspired me to pursue my passion of Arctic research and have not stopped teaching and encouraging me. Thank you for all you have done.
I am particularly grateful to the local experts and key informants who shared their wealth of knowledge with me. Without your input, I could not have conducted half of this research. Thank you to Andy Carpenter Sr., Geddes Wolki, Roger Kuptana, Martha
Kudlak, Frank Kudlak, Edith Haogak, Lena Wolki, John Keogak, Donna Keogak, Wayne
Gully, Doreen Carpenter, Earl Esau, Lawrence Amos, Larry Carpenter, John Lucas Sr.,
Samantha Lucas, Betty Haogak, Joanne Eldridge, Brian Dempson, Kim Howland, Lois
Harwood, the late Bill Doidge, Barrie Ford, Francois Martin, Larry Ruben, Muffa (John
Max) Kudlak, the late Chris Day, and Kevin Bill.
To my lab and field assistants, you too made this possible. Thank you to my community research assistants Trevor Lucas (field assistant extraordinaire!), the late Drew
Esau, Kyle Wolki, Catherine Kuptana, and Jim Wolki. Thank you to my “southern” field assistants Tracey Loewen, Jonathon Michel, Robert McGowan, and Dak de Kerckhove.
Thank you to my community translators Beverly Amos, Jean Harry, and the late Martha
Kudlak,and to my interview transcribers Kate Tucker, Damien Lee, Simon Cheesman, and
Dakota Brant. James Wilkes, thank you for the inter-coder variability work. Thank you to
! vi! ! all of my lab assistants who worked on the many samples analysed in this research: Mike
Harte, Matt Bond, Allen Brett Campeau, Andrew Eccelstone, Robert McGowan, Marie
Gauteau, Stephen McGovarin, and Brian Wilcox. Matt Toll, thank you for the GIS work.
Thank you also to the HEIC Research Group, especially Kaitlin Breton-Honeyman who was my running mate in this journey, and Kristeen McTavish, Paul McCarney, Eric Lede, and Shirin Nuesslein who helped me sort out items that needed attention at the lab while I was away in the field.
The amount of in-kind support for the research was overwhelming. I am indebted to the Sachs Harbour Royal Canadian Mounted Police (especially Clifton Dunn) as well as the Sachs Harbour and Inuvik Parks Canada staff (David Haogak, John Lucas Jr., Aleta
Esau, Ifan Thomas, and Joe Kudlak) for making sure I had what I needed including places to stay, rides, and the use of equipment. I am also indebted to Gavin Manson of
Environment and Climate Change Canada (ECCC) for the use of their ATV as well as Evan
Richardson from ECCC for my home in Sachs Harbour (the CWS Shack). Thank you
Frank and Martha Kudlak, Geddes and Lena Wolki, John and Donna Keogak, Wayne Gully and Doreen Carpenter, and Larry Carpenter and Yvonne Elias for the use of your cabins out at the lakes. In-kind field and lab equipment was also provided by Rick Wastle at
Fisheries and Oceans Canada, Dr. Chris Wilson and Dr. James (Jim) Schaefer at Trent
University, and Mark Gibson at the Ontario Ministry of Natural Resources.
My research would not have been possible without financial support from ArcticNet
(Network of Centres of Excellence), the Nasivvik Centre for Inuit Health and Changing
Environments (Canadian Institutes of Health Research-Institute for Aboriginal People’s
Health), International Polar Year 2007-2008 (Government of Canada), The W. Garfield
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Weston Foundation, Northwest Territories Cumulative Impacts Monitoring Program, The
Polar Continental Shelf Program (Natural Resources Canada), Canada/Inuvialuit Fisheries
Joint Management Committee, Bruce Hannah (Fisheries and Oceans Canada, Yellowknife
Branch), the Lorraine Allison Memorial Scholarship (Arctic Institute of North America),
Ontario Graduate Scholarship, Northern Scientific Training Programme (Indigenous and
Northern Affairs Canada), and the Canadian National Sportsmen Shows. Thank you also to Trent University, Canada in the Rough, and the Association of Polar Early Career
Scientists for in-kind support.
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POSITIONALITY
“Although philosophical worldviews remain largely hidden in research, they still influence the practice of research and need to be identified.” – Creswell 2008, p. 5
I grew up in small-town southern Ontario where I studied biology throughout high school and during my zoology undergraduate degree at the University of Guelph. The lens through which I understood the natural and biological world was shaped by the western science paradigm I was taught. In my first years as an undergraduate, I experienced a textbook and “dead-grey-things-jars” approach to learning science. This changed when I started field courses. My worldview and approach to learning expanded greatly, and I adopted the belief that ecosystem-based learning and monitoring were important to better understand the natural environment.
My interest in conducting mixed methods ecological research integrating Inuit and scientific knowledge began when I was conducting fieldwork for what is now the Barcode of Life Project. I was in Resolute Nunavut as an undergraduate research assistant collecting invertebrates to examine biodiversity in the area. I met Inuit from the community who shared with me their knowledge about the local environment and ecosystems, and how they gained this knowledge through living their lives “out on the land”. This was my first trip to the north, and to a location where people lived a subsistence-based lifestyle. After this experience, I was determined to pursue a graduate research project examining the linkages between Inuit and scientific knowledge.
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It took nearly five years for my PhD research project to come to fruition. Mixed methods research linking scientific and Inuit knowledge was not as readily accepted at that time (early 2000s). My PhD research was inspired by and built on earlier researchers studying local expert knowledge in Canada and the U.S. such as Fikret Berkes, Lois
Harwood, Milton Freeman, and Henry Huntington.
I have always believed that research should involve the people who would be affected by it, and who have firsthand knowledge to contribute. I also believe it is important to the empowerment of those people to continue the research once the researcher’s role was complete. In my PhD, I chose a mixed methods research design because it made sense for collaboration and conducting social components of my research in a more engaged and trusting place. In addition, it allowed for a scientific approach that empowered the community through the inclusion of their knowledge and participation in the research.
Spending extensive time in the community of Sachs Harbour during my research, and experiencing the use of the subsistence fishery firsthand, as well as the Inuvialuit lifestyle and culture, changed my approach to research. It allowed me to see the importance of a renewable resource from the resource users’ perspective, and learn that collaborative research is important when resource users are directly affected by your study. It also resulted in my worldview being broadened by the worldviews of the Inuvialuit.
This dissertation is reflective of my own integration of knowledge and experience gained during multiple annual visits over an eight-year period to the study lakes and the community of Sachs Harbour, through contemporary scientific data collection and analysis, and through time spent with the people of Sachs Harbour while visiting, traveling, learning, fishing, and living in their community and on their land.
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TERMINOLOGY USED IN THE DISSERTATION
Exploratory research: This dissertation takes an exploratory approach to research.
Exploratory research is conducted when a problem is not clearly defined, there is not a
lot written on the topic, or there is not much information on the population being studied.
The objective of exploratory research is to gather broad-ranging, intentional, systematic
data and information that will help define problems and suggest hypotheses, and to
maximize the discovery of generalizations. (Stebbins 2008, Creswell 2009)
Factor: In this dissertation, the term factor refers to a circumstance, element or influence
that contributes to a particular result, situation or outcome, and is used specifically in
relation to factors that have the potential to influence community-based monitoring
programs.
Local expert: In general, an expert is considered to be a person who has authoritative and
comprehensive knowledge in a particular area, field of interest, or observed
phenomenon. In this dissertation, local experts were determined through a process of
peer-referenced and systematic identification, assuring those considered most
knowledgeable within their local community, social group, or livelihood group were
identified (Davis and Wagner 2003).
Knowledge and observation: To incorporate contemporary observations of local experts,
the term knowledge and observation is used in the dissertation (Furgal and Laing 2012).
In this dissertation, knowledge means an individual or collective understanding
developed through lived experiences and long-term synthesis of data and information,
and sometimes within beliefs or cultural contexts. Observation refers to insights gained
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through monitoring the environment, on a contemporary or short-term timescale, and
having the background knowledge to realize a change has occurred.
Inuvialuit Knowledge and Observation (IKO): In this dissertation, the term was used
as it was preferred by the Inuvialuit to Traditional Knowledge or Local
Ecological Knowledge. It is the knowledge based on data gathered by Inuvialuit
individually or as a group through learning and living on or using the land,
includes scientific and ecological knowledge, and years or generations of
accumulated knowledge or recent observations on local ecosystems (Community
Corporations 2006, personal communication with local experts in the Inuvialuit
Settlement Region 2008-2015). This knowledge is sometimes represented in
long-term syntheses of that data and information, and sometimes is connected
with cultural beliefs or worldviews. IKO is predominantly presented in a
qualitative form in this dissertation.
Scientific Ecological Knowledge and Observation (SEKO): In this dissertation,
SEKO refers to data and understanding gained through both the reductionist
empirical approach employing the scientific method of inquiry, as well as an
ecological research approach within the belief that a phenomenon of interest
must be “understood in context” (Peterat 2008, p. 237). An ecological research
approach “assumes that the biological and physical features of the system,
including its species [including humans], are central to the health of…fish
stocks” (Harvey and Coon 1997). While ecological research is considered non-
reductionist, it often draws on multiple scientific disciplines that use a
reductionist approach to better understand the system of the phenomenon of
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interest. SEKO is presented in a quantitative form in this dissertation.
Mixed methods research: In this dissertation, mixed methods is a purposeful approach to
research design “in which the inquirer or investigator collects and analyzes data,
integrates the findings, and draws inferences using both qualitative and quantitative
approaches or methods in a single study or a program of study” (Creswell 2008, p.526).
“Mixed methods is an approach to inquiry that combines or associates both qualitative
and quantitative forms…it is more than simply collecting and analyzing both kinds of
data; it also involves the use of both approaches in tandem so that the overall strength
of a study is greater than either qualitative or quantitative research…mixed methods uses
both pre-determined and emerging methods, both open-ended and closed-ended
questions, multiple forms of data drawing on all possibilities, statistical and text
analysis, and interpretation across databases” (Creswell 2009, pp. 4,15).
Parameter: In this dissertation, a parameter is considered to be a measurable component
or characteristic that is a part of a set that defines or classifies a system and determines
its behaviour, specifically in relation to ecological or environmental parameters for
consideration of the community-based monitoring of Arctic Char condition and growth.
Qualitative fish condition: In this dissertation, qualitative fish condition refers to the
overall assessment of the condition of fish as observed by local experts using sight, taste,
and touch. Fish condition is a term used by the Inuvialuit to qualitatively describe
whether or not a fish is acceptable for human consumption and includes a variety of
factors such as “fatness” (girth compared to length) and the general health of the fish
including: flesh and meat texture, flavour and colour, and the absence of diseases, lumps,
cysts, or deformities.
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Quantitative fish condition: In this dissertation, quantitative fish condition refers to the
quantitatively calculated size of fish. Fish condition was calculated using Fulton’s K
(Ricker 1975) which is 100,000 multiplied by the fish weight (in grams) and divided
by the cube of fish length (in millimeters).
Quantitative methods: The definition used in this dissertation is taken from Wolf (2010,
p.145), “[quantitative] methods use mathematical tools to identify patterns in larger
collections of mostly numerical data”.
Qualitative methods: The definition used in this dissertation is taken from Creswell (2009,
p.232), qualitative methods are a “process of research involv[ing] emerging questions
and procedures; collecting data in the participant’s setting; analyzing the data
inductively, building from particulars to general themes; and making interpretations
from the meaning of the data.”
Triangulation: Triangulation refers to the process of integrated analysis of information
originating from quantitative and qualitative methods (Creswell 2007). "The basic idea
underpinning the concept of triangulation is that the phenomena under study can be
understood best when approached with a variety or a combination of research methods.
Triangulation is most commonly used in data collection and analysis techniques, but it
also applies to sources of data” (Rothbauer 2008, pp. 892–894). Extending this further,
triangulation may not always lead to a single point or conclusion. “Rather, [the
researcher] attempts to make sense of what [they] find and that often requires embedding
the empirical data at hand with a holistic understanding of the specific situation and
general background knowledge about [the] phenomena. This conception shifts the focus
on triangulation away from a technological solution for ensuring validity and places the
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responsibility with the researcher for the construction of plausible explanations about
the phenomena being studied” (Mathison 1988, p.17).
References
Community Corporations of Inuuvik, Tuktuuyaqtuuq and Aklarvik. 2006. Inuvialuit
Settlement Region Traditional Knowledge Report. Submitted to Mackenzie Gas Project
Group, Calgary, Alberta. 200 pp.
Creswell, J.W. 2007. Qualitative inquiry and research design: Choosing among five approaches, second edition. Sage Publications Ltd., Thousand Oaks, California.
Creswell, J.W. 2008. Mixed Methods. In: Given, L.M., ed. The Sage Encyclopedia of
Qualitative Research Methods. Sage Publications Ltd., Thousand Oaks, California. 526–
529.
Creswell, J.W. 2009. Research design: Qualitative, quantitative and mixed methods approaches, third edition. Sage Publications Ltd., Thousand Oaks, California. 246 pp.
Davis, A., and Wagner, J.R. 2003. Who knows? On the importance of identifying
“experts” when researching local ecological knowledge. Human Ecology 31(3):463–
489.
Furgal, C., and Laing, R. 2012. A synthesis and critical review of the traditional ecological knowledge literature on narwhal (Monodon monoceros) in the eastern
Canadian Arctic. DFO Can. Sci. Advis. Sec. Sci. Res. Doc. 2011/131.
Harvey, J., and Coon, D. 1997. Beyond Crisis in the Fisheries: A proposal for community-based ecological fisheries management. Conservation Council of New
Brunswick, Fredericton, New Brunswick. 59 pp.
Mathison, S. 1988. Why triangulate? Educational Researcher 17(2):13–17.
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Peterat, L. 2008. Ecological research. In: Given, L.M., ed. The Sage Encyclopedia of
Qualitative Research Methods. Sage Publications Ltd., Thousand Oaks, California.
237–238.
Ricker, W.E. 1975. Computation and interpretation of biological statistics of fish populations. Journal of the Fisheries Research Board of Canada Bulletin No. 191.
Department of the Environment, Fisheries and Marine Service, Ottawa, Ontario.
Rothbauer, P. 2008. Triangulation. In: Given, L.M., ed. The Sage Encyclopedia of
Qualitative Research Methods. Sage Publications Ltd., Thousand Oaks, California.
892–894.
Stebbins, R.A. 2008. Exploratory Research. In: Given, L.M., ed. The Sage Encyclopedia of Qualitative Research Methods. Sage Publications Ltd., Thousand Oaks, California.
327–329.
Wolf, F. 2010. Enlightened eclecticism or hazardous hotchpotch? Mixed methods and triangulation strategies in comparative public policy research. Journal of Mixed Methods
Research 4(2):144–167.
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TABLE OF CONTENTS ! ABSTRACT ...... ii ACKNOWLEDGEMENTS ...... iv POSITIONALITY ...... ix TERMINOLOGY USED IN THE DISSERTATION ...... xi REFERENCES ...... xv CHAPTER 1: INTRODUCTION ...... 1 1.1 IMPORTANCE OF LOCAL FISHERIES TO INUIT COMMUNITIES ...... 1 1.2 CONCERNS REGARDING CLIMATE CHANGE IMPACTS ON ARCTIC CHAR ...... 3 1.3 MONITORING OF ARCTIC CHAR IN THE CANADIAN ARCTIC ...... 5 1.4 ISSUE STATEMENT ...... 6 1.5 RESEARCH CONTEXT ...... 7 1.6 RESEARCH QUESTIONS ...... 10 1.7 RESEARCH APPROACH ...... 11 1.8 RESEARCH DESIGN AND METHODS ...... 13 1.9 ORGANIZATION OF MANUSCRIPT-BASED DISSERTATION ...... 14 1.10 REFERENCES ...... 16 CHAPTER 2: UNDERSTANDING THE EFFECTS OF LAKE HABITAT ON LANDLOCKED ARCTIC CHAR (SALVELINUS ALPINUS (L.)) USING SCIENTIFIC ECOLOGICAL AND INUVIALUIT KNOWLEDGE AND OBSERVATION ...... 30 2.1 INTRODUCTION ...... 30 2.2 METHODS ...... 33 2.2.1 Mixed Methods Research Design ...... 33 2.2.2 Research Location ...... 36 2.2.3 Local Experts and Community Participation ...... 38 2.2.4 In Situ Data Collection ...... 39 2.2.5 Qualitative Analysis of Inuvialuit Knowledge and Observation (IKO) ...... 45 2.2.6 Laboratory Analyses of Scientific Ecological Knowledge and Observation (SEKO) ...... 46 2.2.7 Statistical Analyses of SEKO ...... 47 2.2.8 Triangulation of IKO and SEKO ...... 50 2.3 RESULTS ...... 51 2.3.1 Local Expert Inuvialuit Knowledge and Observation (IKO) ...... 51 2.3.2 Lake Habitat ...... 52 2.3.3 Arctic Char Condition and Diet ...... 63 2.3.4 Triangulation of Knowledge Bases ...... 82 2.4 DISCUSSION ...... 85 2.4.1 Lake Habitat ...... 86 2.4.2 Arctic Char Condition and Diet ...... 88 2.4.3 Triangulation ...... 91 2.4.4 Summary of Lake Habitat Drivers of Arctic Char Condition ...... 92 2.5 CONCLUSION ...... 94
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2.6 REFERENCES ...... 95 CHAPTER 3: UNDERSTANDING GROWTH VARIABILITY IN LANDLOCKED ARCTIC CHAR IN RESPONSE TO LOCAL ENVIRONMENTAL CONDITIONS USING SCIENTIFIC ECOLOGICAL AND INUVIALUIT KNOWLEDGE AND OBSERVATION ...... 107 3.1 INTRODUCTION ...... 107 3.2 METHODS ...... 112 3.2.1 Research Design ...... 112 3.2.2 Research Location ...... 114 3.2.3 Local Experts and Community Participation ...... 117 3.2.4 In Situ Data Collection ...... 118 3.2.5 Analyses of Expert Interviews and Ecological Data ...... 120 3.2.6 Triangulation of SEKO and IKO ...... 127 3.3 RESULTS ...... 128 3.3.1 Literature Review ...... 128 3.3.2 Inuvialuit Knowledge and Observation ...... 129 3.3.3 Local Abiotic and Climatic Conditions...... 130 3.3.4 Arctic Char Growth and Biotic Environmental Conditions ...... 146 3.3.5 Environmental Conditions Affecting Arctic Char Growth ...... 154 3.3.6 Triangulation of Knowledge Bases ...... 159 3.4 DISCUSSION ...... 169 3.4.1 Environmental Conditions Affecting Arctic Char Growth ...... 170 3.4.2 Environmental Conditions with Potential to Affect Arctic Char Growth Identified through IKO ...... 175 3.5 CONCLUSIONS ...... 179 3.6 REFERENCES ...... 180 3.7 APPENDICES ...... 196 APPENDIX 1. MEAN RELATIVE GROWTH OF ARCTIC CHAR OF ALL AGES WITHIN A YEAR FOR EACH STUDY LAKE (CAPRON, KUPTAN AND MIDDLE LAKES ON BANKS ISLAND NT) DETERMINED FROM OTOLITH BACK-CALCULATION...... 196 APPENDIX 2. VON BERTALANFFY GROWTH CURVES (SOLID LINES) WITH 99% CONFIDENCE INTERVALS (DASHED LINES) CALCULATED FROM THE CAPTURED LENGTHS AND AGES OF ARCTIC CHAR SAMPLED FROM CAPRON, KUPTAN AND MIDDLE LAKES ON BANKS ISLAND NT DURING 1992-1994 AND 2008-2012...... 198 CHAPTER 4: FACTORS INFLUENCING THE COMMUNITY MONITORING OF ARCTIC CHAR FISHERIES ...... 201 4.1 INTRODUCTION ...... 201 4.2 METHODS ...... 205 4.2.1 Literature Search ...... 205 4.2.2 Identification of Key Informants for Interviews ...... 206 4.2.3 Interviews with Key Informants across the Canadian Arctic ...... 206 4.2.4 Data Analysis ...... 208 4.3 RESULTS ...... 209 4.3.1 Program Operations ...... 213 4.3.2 Community Perspectives on CBMPs ...... 221 4.3.3 Insights, Considerations, and Recommendations ...... 228
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4.4 DISCUSSION ...... 236 4.4.1 Program Operations ...... 236 4.4.2 Community Perspectives on Char CBMPs ...... 238 4.4.3 Insights, Considerations, and Recommendations from Six Char CBMPs ...... 240 4.4.4 Additional Recommendations and Suggested Future Research ...... 242 4.5 REFERENCES ...... 245 4.6 APPENDICES ...... 257 APPENDIX 1: SEMI-DIRECTED INTERVIEW GUIDE...... 257 APPENDIX 2: GREY AND PEER-REVIEWED LITERATURE USED FOR THE THEMATIC CODING ANALYSIS (N=28)...... 260 APPENDIX 3-1: SUMMARY OF INFORMATION FROM THE THEMATIC CONTENT ANALYSIS ON ARCTIC CHAR AND RELATED SPECIES CBMPS IN THE CANADIAN ARCTIC FOR THE SUBTHEMES FROM THE THEME PROGRAM OPERATIONS ...... 263 APPENDIX 3-2: SUMMARY OF INFORMATION FROM THE THEMATIC CONTENT ANALYSIS ON ARCTIC CHAR AND RELATED SPECIES CBMPS IN THE CANADIAN ARCTIC FOR THE SUBTHEMES FROM THE THEME PROGRAM OPERATIONS ...... 266 APPENDIX 3-3: SUMMARY OF INFORMATION FROM THE THEMATIC CONTENT ANALYSIS ON ARCTIC CHAR AND RELATED SPECIES CBMPS IN THE CANADIAN ARCTIC FOR THE SUBTHEMES FROM THE THEME PROGRAM OPERATIONS ...... 269 CHAPTER 5: INTEGRATED DISCUSSION ...... 272 5.1 SUMMARY AND CONTRIBUTIONS ...... 272 5.2 MIXED METHODS APPROACH TO RESEARCH ...... 278 5.3 ECOLOGICAL COMPLEXITY ...... 280 5.4 MONITORING IMPLICATIONS ...... 282 5.5 RECOMMENDATIONS AND CONSIDERATIONS FOR FUTURE RESEARCH ...... 283 5.6 CONCLUSIONS ...... 286 5.7 REFERENCES ...... 286
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LIST OF TABLES ! CHAPTER 2
Table 1. Summary of Sachs Harbour local expert interviewee attributes including age, years of fishing experience and knowledge of the Capron, Kuptan and Middle lakes on Banks Island NT (n=18)...... 52 Table 2. List of topics from Inuvialuit knowledge and observation on fish habitat features and parameters having the potential to influence Arctic Char condition, with number of Sachs Harbour NT local experts reporting the observation (local experts interviewed n=18)...... 53 Table 3. Trace metal concentrations (mg/L) in water quality samples collected from 2008 to 2011 in Middle, Kuptan and Capron Lakes on Banks Island NT...... 60 Table 4. Lake water nutrients and chemistry data collected in winter 2010 and summer 2011 in Middle, Kuptan and Capron lakes on Banks Island NT...... 62 Table 5. List of topics of Inuvialuit knowledge and observation regarding Arctic Char qualitative condition and diet and number of Sachs Harbor NT local experts reporting observation (local experts interviewed n=18)...... 63 Table 6. The taxonomic identification of invertebrate prey species (excluding zooplankton) found in Arctic Char stomach samples from Middle (n=9), Kuptan (n=12) and Capron (n=38) lakes on Banks Island NT in 2011...... 74 Table 7. Summary of zooplankton average species densities (#/m3) and average weight (µg) in the three study lakes on Banks Island NT from two plankton tows from each of Kuptan and Middle lakes, and one plankton tow from Capron Lake...... 78 Table 8. Summary of average counts of gut and flesh parasite species identified in- laboratory in the three study lakes on Banks Island NT (Capron Lake n=12, Kuptan Lake n=19, Middle Lake n=17)...... 81 Table 9. Matrix triangulating Inuvialuit knowledge and observation and Scientific ecological knowledge and observation results for Arctic Char condition, diet, and lake habitat on Banks Island NT...... 83
CHAPTER 3
Table 1. Summary of Sachs Harbour local expert interviewee attributes including age, number years fishing experience and knowledge of the Capron, Kuptan and Middle lakes on Banks Island NT...... 130 Table 2. List of topics from Inuvialuit knowledge and observation local expert interviews on abiotic environmental conditions and features having the potential to influence Arctic Char growth, with number of Sachs Harbor NT local expert interviewees (n=18) reporting the information...... 131 Table 3. List of topics from Inuvialuit knowledge and observation on Arctic Char size and biotic environmental conditions with the potential to predict changes in Arctic Char growth, with number of Sachs Harbor, Banks Island NT local experts reporting observation (local experts interviewed: n=18)...... 146 Table 4. Number of Arctic Char included in the capture (length and age at time of capture) dataset and the number of Arctic Char used in the back-calculated dataset per year and lake on Banks Island NT...... 149
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Table 5. The best model as determined by pairwise comparisons among the Arctic Char growth curves estimated from lengths and ages from Capron, Kuptan and Middle lakes, Banks Island NT in the 1990s and 2000s survey periods. Asymptotic maximum length (L∞), Brody’s growth co-efficient (K) and the theoretical fork length at an age of 0 years (t0) are given for the best model for each comparison and the standard error of the parameter estimate is in parentheses...... 152 Table 6. Parameter estimates and marginal and conditional R2 from best fitting linear mixed-effects model analysis of back-calculated growth in Arctic Char from Capron, Kuptan and Middle lakes, Banks Island NT...... 156 Table 7. Parameter estimates of Growing Degree Days over 0 °C from a linear mixed- effects model analysis of back-calculated growth in Arctic Char from Capron, Kuptan, and Middle lakes, Banks Island NT. Note: The t-value refers to the parameter, and ΔAIC refers to the comparison among the contrasting models (i.e. GDD0 with length of ice-free period for the all lakes models, and GDD0 with Total Annual Precipitation for the lake-specific models)...... 157 Table 8. Matrix triangulating Inuvialuit knowledge and observation and scientific ecological knowledge and observation relating environmental conditions to Arctic Char growth on southwest Banks Island NT...... 160
CHAPTER 4
Table 1. Five models of community-based monitoring (adapted from Danielsen et al., 2009)...... 209 Table 2. Summary of key informant attributes who provided information on Arctic Char community-based monitoring programs across the four Inuit Land Claim regions in Canada (Inuvialuit Settlement Region, Nunavut, Nunavik, and Nunatsiavut) (n=9)...... 211 Table 3. Themes and subthemes from thematic content analysis on community-based monitoring programs for Arctic Char and related species in the Canadian Arctic. Associated number of interviews (n=9) and documents (n=35) providing information on each subtheme are included...... 212 Table 4. Comparison of information obtained from the thematic content analysis of six Arctic Char community-based monitoring programs across the Canadian Arctic, summarized for several subthemes under the main theme of ‘Program Operations’ (n=9 key informant interviews and n=35 documents)...... 217 Table 5. Model categories (from Table 1) assigned to each of the six Arctic Char CBMPs analysed in this study (n=9 key informant interviews and n=35 documents)...... 220
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LIST OF FIGURES
CHAPTER 1
Figure 1. Map of Inuit Nunangat, homeland of the Inuit in Canada, showing all four Inuit Land Claim regions (Inuvialuit Settlement Region, Nunavut, Nunavik and Nunatsiavut) ...... 2 Figure 2. Overview of the dissertation organization, presenting research questions, the mixed methods approach with qualitative and quantitative methodologies, and knowledge integration techniques for each chapter ...... 16
CHAPTER 2
Figure 1. Diagram illustrating the modified parallel concurrent research design with some sequential steps and final information triangulation followed in this study. Sequential steps occurred in some instances where quantitative analysis dictated further qualitative inquiry (arrow A), or qualitative analysis dictated further quantitative inquiry (arrow B), prior to final information triangulation and interpretation ...... 36 Figure 2. Map of the study location in the Inuvialuit Settlement Region, NT, Canada. Inset map shows locations of Capron, Kuptan, and Middle lakes and the community of Sachs Harbour (marked with a black dot), on the southwest side of Banks Island ...... 38 Figure 3. Bathymetry of Capron, Kuptan and Middle on Banks Island NT lakes measured in 2011 and presented in meters ...... 56 Figure 4. Temperature profiles of Capron (top, black), Kuptan (middle, red) and Middle (bottom, green) lakes on Banks Island NT in summer 2011 (solid line; no ice) and Spring 2012 (dashed line; full ice cover). Temperature loggers were set at the deepest point in each lake (bottom, 2/3 maximum depth, 1/3 maximum depth, and just below the ice surface (spring) or water (summer). Open squares on the profile curves for each temperature logger depth ...... 58 Figure 5. The ten largest fish caught in Middle (green), Kuptan (red) and Capron (black) lakes on Banks Island NT across all survey years (Capron Lake 2008, 2010, 2011; Kuptan Lake 2009, 2011; Middle Lake 2008, 2009, 2011) ...... 68 Figure 6. Condition of Arctic Char in Capron (black; n=62), Kuptan (red; n=89) and Middle (green; n=138) lakes on Banks Island NT calculated using Fulton’s K ...... 68 Figure 7. Gonado-Somatic Indices of running ripe Arctic Char for male (left) and female (right) char in Capron (black; n♂ = 9; n♀ = 1), Kuptan (red; n♂ = 20; n♀ = 7) and Middle (green; n♂ = 14; n♀ = 6) lakes on Banks Island NT ...... 69 Figure 8. Proportions of diet items found in Arctic Char stomachs during 2008-2012 in- field analyses in Capron (n = 57; 9 empty stomachs), Kuptan (n = 88; 1 empty stomach) and Middle (n = 127; 16 empty stomachs) lakes on Banks Island NT ...... 73 Figure 9. Proportion of Arctic Char containing None, Low, Medium and High (dark to light; see Methods for grouping criteria) parasite loads in Capron, Kuptan and Middle lakes on Banks Island NT based on in-field visual-assessment results. The width of the bars represents the relative sample size among lakes (Capron Lake n=62, Kuptan Lake n=90, Middle Lake n=138) ...... 80
! xxii! !
Figure 10. Body condition (i.e. Fulton’s K) of Arctic Char pooled from Capron, Kuptan and Middle lakes on Banks Island NT at None, Low, Medium and High parasite loads ...... 82
CHAPTER 3
Figure 1. Diagram of research design followed in this study showing the modified parallel concurrent design with some sequential steps and final information triangulation. Sequential steps occurred in instances where qualitative analysis dictated further quantitative inquiry (arrow A), prior to final information triangulation and interpretation ...... 114 Figure 2. Map of the Inuvialuit Settlement Region (bottom) situated in the northern portions of the Northwest Territories and Yukon, Canada. The study area is marked with a black star. Inset shows locations of Kuptan, Middle and Capron lakes in relation to Sachs Harbour (marked with a black circle), on the southwest side of Banks Island NT ...... 116 Figure 3. Daily temperatures for the months of July (top) and December (bottom) as recorded by the Sachs Harbour Environment Canada weather station on Banks Island NT between 1970 and 2011 ...... 137 Figure 4. Growing degree days over 0°C (top) and total annual precipitation (bottom) as recorded by the Sachs Harbour Environment Canada weather station on Banks Island NT between 1970 and 2011. The solid lines with points are the observed data, and the dotted lines are fifth degree polynomial regression lines added for illustrative purposes ...... 138 Figure 5. Probability of observed levels of precipitation on Banks Island falling as rain at a mean daily temperature generated from a logistic regression (line) of observations of rain or snow (points) at daily temperature as recorded by the Sachs Harbour Environment Canada weather station on Banks Island NT between 1970 and 2011 ...... 140 Figure 6. Total annual precipitation (top) and total annual days of precipitation (bottom) as predicted to have fallen as rain (dashed line) and snow (solid line) using total precipitation and mean temperature data as recorded by the Sachs Harbour Environment Canada weather station on Banks Island NT between 1970 and 2011 ...... 141 Figure 7. The length of the ice-free period (in days) on Capron, Kuptan and Middle lakes, Banks Island NT calculated from Radarsat and Landsat imagery of ice cover compared with the results from the ice phenology model (Shuter et al., 2013). The black line is the 1:1 line ...... 143 Figure 8. Length of ice-free periods on Capron (blue – solid line), Kuptan (red – dashed line) and Middle (green – dotted line) lakes, Banks Island NT, estimated using the Shuter et al. (2013) empirical forecasting model that predicts freeze and thaw dates on Canadian lakes ...... 144 Figure 9. Von Bertalanffy growth curve 99% confidence intervals for Arctic Char populations in Capron (blue – solid lines), Kuptan (red –dashed lines) and Middle (green – dotted lines) lakes from fish collected in the 1992-1994 (i.e. left panels: A and C) and 2008-2012 (i.e. right panels: B and D) survey periods, and data analyzed
! xxiii! !
using the char lengths and ages at time of capture (i.e. the top panels: A and B) and the lifetime size and ages of a subset of captured char analyzed using otolith back- calculation (i.e. the bottom panels: C and D)...... 150 Figure 10. Probability of Arctic Char reaching maturity at age from a logistic regression fit of a curve (line) of field observations of maturity at age (points) in Capron, Kuptan and Middle lakes, Banks Island NT ...... 153 Figure 11. Natural logarithm of gonad mass at age from Arctic Char caught in Capron, Middle and Kuptan lakes, Banks Island NT ...... 154 Figure 12. Relative growth (annual growth divided by the average annual growth for all fish of that age from the lake population) across all ages per year for Arctic Char populations in Capron (blue –top panel), Kuptan (red – middle panel) and Middle (green –bottom panel) lakes, Banks Island NT ...... 158 ! CHAPTER 4 ! Figure 1. Map of northern Canada showing Inuit Nunangat (homeland of the Inuit of Canada) depicting the four Inuit land claim regions: Inuvialuit Settlement Region (orange), Nunavut (light green), Nunavik (dark green) and Nunatsiavut (purple). Locations of the key informant Arctic Char (and one Dolly Varden Char) community-based monitoring program affiliations are identified with red dots ..... 210!
! xxiv! ! 1!
CHAPTER 1: Introduction
! 1.1 Importance of Local Fisheries to Inuit Communities
In the Canadian Arctic, anadromous and freshwater fisheries remain a strong part of the culture and diet for Inuit communities and are still harvested in large quantities for subsistence and commercial purposes across Inuit Nunangat, the homeland of Inuit in
Canada including all four Inuit land claim regions (Figure 1) (Blanchet and Rochette 2008,
Dempson et al. 2008, Donaldson et al. 2010, Egeland et al. 2010a,b,c, Roux et al. 2011,
Porta and Ayles 2015). Anadromous Arctic Char (Salvelinus alpinus (L.), Ikalupik in
Inuvialuktun, the language of the Inuvialuit) are one of the most important socio-economic species. Arctic Char support mixed commercial-subsistence harvests in Nunavut (Roux et al. 2011) and Nunatsiavut (Dempson et al. 2008). In Nunavik, Arctic Char remain an important subsistence fisheries (Barrie Ford, Nunavik Research Centre, July 2016, pers. comm.). Short-term commercial anadromous char fisheries were attempted in the
Inuvialuit Settlement Region (ISR) in the past but did not persist (Porta and Ayles 2015).
! ! 2!
Figure 1. Map of Inuit Nunangat, homeland of the Inuit in Canada, showing all four Inuit
Land Claim regions (Inuvialuit Settlement Region, Nunavut, Nunavik and Nunatsiavut).
(Map Source: Indigenous and Northern Affairs Canada, Inuit Relations Secretariat, 2009)
Subsistence fisheries continue to play an important role for the Inuvialuit today (Porta and Ayles 2015) as locally-harvested foods are often more nutrient-rich than store-bought foods (Dewailly et al. 2001, Nuttall 2005, Donaldson et al. 2010). Commercial Arctic Char fisheries in Nunavut and Nunatsiavut contribute towards the local wage-earning economy, providing jobs and income for local Inuit both as commercial fishers, as well as in local fish plants (Brian Dempson and Chris Day, Fisheries and Oceans Canada, February 22
2010 and March 28 2010 respectively, pers. comm.). Additionally, subsistence Arctic Char fisheries play an important role in household food security, as many residents still live a subsistence-based lifestyle (Donaldson et al. 2010, Roux et al. 2011, Bell and Harwood
! ! 3!
2012). Arctic Char is one of the most frequently consumed subsistence species in Inuit
Nunangat (Blanchet and Rochette 2008, Egeland et al. 2010a,b,c, Sharma et al. 2010).
1.2 Concerns Regarding Climate Change Impacts on Arctic Char
Temperature is the main parameter driving climate changes in the global system
(Niemi et al. 2016). The increase in global mean surface temperature is projected to rise by 0.3ºC to 1.7ºC by the end of the 21st century, with the Arctic region continuing to warm more rapidly than the global mean (IPCC 2014). Arctic warming is estimated to be approximately eight times faster than the rest of the planet (Cowtana and Way 2014). In
2013, the Canadian national average temperature was 0.8°C above baseline averages, matching global trends (Niemi et al. 2016). The direct effects of climate change observed through scientific studies and projected through modelling in Canada’s Arctic regions include increasing annual temperatures, unprecedented changes in sea ice conditions, melting permafrost and increased bank and shore erosion, changes in precipitation patterns, increasing storm events, and changes to flow regimes (ACIA 2004, AMAP 2011,
Clic/AMAP/IASC 2016).
Regionally-variable responses to climate change in the Arctic have also been observed. For example, from approximately 1959-2009, the western and central Canadian
Arctic experienced a general warming pattern of 2–3°C, while the eastern Canadian Arctic experienced a cooling of approximately 1.5°C (Furgal and Prowse 2009). Another example of a regional difference from the Canadian Arctic includes the strongest increasing trend in increased air temperature in 2013 in all of Canada. An average increase of 2.6°C in 2013 was observed in the northern portion of the Mackenzie River basin in the northern part of the Northwest Territories (Niemi et al. 2016).
! ! 4!
Regional increases in climate variability and change (CVC) outside the range of historical locally-observed conditions, could result in direct effects on local fish habitat including warmer water temperature regimes, early ice breakup and later ice formation, increased UV radiation, increased shoreline erosion, and changes in runoff regimes (Wrona et al. 2006, Prowse et al. 2009). Indirect effects of CVC on fish habitat could include alterations to biogeochemical processes, bank erosion leading to alterations in physical limnology, altered primary and secondary productivity and trophic structure (Reist et al.
2006a and b, Wrona et al. 2006, Niemi et al. 2016). Several studies in Canada have shown the effects of climate on exploited anadromous Arctic Char. For example, precipitation and temperature led to annual variation in stocks abundance; earlier retreat of landfast marine ice was linked to increased annual body condition; and increased summer temperature and precipitation had positive effects on young char mean length and weight
(e.g. Power et al. 2000, Chavarie 2008, Harwood et al. 2015).
Inuit who rely on Arctic Char will have to adapt to changes in the fishery resulting in altered access to healthy fish stocks due to the secondary indirect impacts of CVC. These impacts include changes in fish size and numbers in either a positive or negative direction, changes in the quality of the fish meat which could include changes to texture, appearance, flavour, nutrient value, and parasite or disease loads. Other changes in access to the resource include alterations in physical access to the fishery due to climate change effects on travel routes over land and ice (Berner and Furgal 2005, Wrona et al. 2005, Reist et al.
2006a and b, Wrona et al. 2006, Furgal and Prowse 2008, Niemi et al. 2016). On-going changes in fish and habitat quality as a result of CVC also requires adapting management
! ! 5! strategies (Prowse and Furgal 2009). Thus, there is a need for monitoring to understand the processes and impacts of a rapidly changing environment on Arctic Char resources.
1.3 Monitoring of Arctic Char in the Canadian Arctic
In the Canadian Arctic, monitoring focuses on anadromous Arctic Char populations and is mostly associated with commercial fisheries (e.g. Dempson et al. 1997, Day and de
March 2004, Kristofferson and Berkes 2005, Dempson et al. 2008, Roux et al. 2011, Day and Harris 2013, Fisheries and Oceans Canada 2014). Monitoring of domestic subsistence fisheries is usually undertaken when there is a specific issue identified by a land claim organization (e.g. co-management organizations and local hunters and trappers organizations) (James D. Reist, June 13 2016, pers. comm.) and is usually conducted using community-based monitoring (CBM).
Community-based monitoring supports the inclusion of local knowledge and monitoring approaches, as well as local collection of scientific data and information (Parlee and Łutsël K’é Dene First Nations, 1998; EMAN 2003, Danielsen, 2009; Gofman, 2010).!
Some examples of Arctic Char CBM in northern Canada, driven by local interest (funded through land claims implementation funds) include: CBM of the numbers and condition of
Arctic Char in the ISR (e.g. Paylor et al. 1989, Harwood 2009, Bell and Harwood 2012,
Harwood et al. 2013), Nunavut (e.g. Kristofferson and Berkes 2005), Nunavik (e.g. Power et al. 1989), and CBM of Arctic Char passages during migration in Nunavik (e.g. Mesher
1999, Chum 2009).
Despite these efforts, data and information for freshwater fish and Arctic Char are still sparse (Reist et al. 2006a; Roux et al., 2011, Culp et al. 2012). In order for local fishers and decision-makers to understand the effects of CVC on Arctic Char, rigorous monitoring
! ! 6! programs that provide relevant data are required (Power et al. 1989, Jacquet et al. 2010).
1.4 Issue Statement
A lack of long term scientific data for many freshwater systems and fish in the ISR, including Banks Island, results in a lack of knowledge surrounding the effects climate change on living natural resources such as Arctic Char (Burton Ayles, Inuvialuit-Canada
Fisheries Joint Management Committee and Kevin Bill, Fisheries and Oceans Canada,
November 2007, pers. comm.). The Sachs Harbour Hunters and Trappers Committee
(SHHTC) had concerns about their Arctic Char resource due to a rapidly changing environment and observed declines in char size and numbers in the nearby Middle Lake in the early 2000s (Lawrence Amos and Joanne Eldridge, Sachs Harbour Hunters and
Trappers Committee, March 2008, pers. comm.).
The SHHTC recognized the need for a community-based monitoring plan to monitor their Arctic Char resource, and requested such a program from the Inuvialuit-Canada
Fisheries Joint Management Committee (FJMC). In turn, the FJMC approached their co- management partners at the Freshwater Institute of the Department of Fisheries and Oceans
(DFO) to ask for assistance with this work. The SHHTC also requested that the research incorporate Inuvialuit knowledge alongside scientific data.1
In addition, Bankslamiut (the people of Banks Island) have a history of documenting
CVC effects in their region are considered some of the first Inuit to bring awareness of
!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! 1Note: The only accessible historical scientific data for the study lakes was collected in 1993-94 by Fisheries and Oceans Canada and is presented in an FJMC report that is currently in review (Babaluk, J., J. Knopp and J.D. Reist. 2017. Assessment of Fish Populations in Six Lakes near Sachs Harbour, Banks Island, Northwest Territories, 1993-1994. Canada/Inuvialuit Fisheries Joint Management Committee Technical Report Series, Fisheries Joint Management Committee, viii+100p). Federal biologists collected Arctic Char samples and data from the three study lakes (plus three others) in order to determine if a small-scale commercial fishery was possible for the community (J. Babaluk, Freshwater Institute – Fisheries and Oceans Canada, pers. comm., 2008). This data, and the otoliths collected, were loaned to my research to provide background data.!
! ! 7!
CVC at the international level, and formed collaborations with researchers to document these changes (e.g. Ashford and Castleden 2001, Riedlinger 2001, Riedlinger and Berkes
2001, Jolly et al. 2002, Nichols et al. 2004, Barber et al. 2008, Inuvialuit Communications
Society 2008). The atmosphere of co-management and research collaboration, the long history of a subsistence fishing resulting in a rich local expert knowledge base, and the lack of freshwater fish data from this region, culminated in an appropriate environment to conduct this research.
1.5 Research Context
The ISR covers nearly 1,000,000 km2 and spans the northern part of the Northwest
Territories including the archipelago and Beaufort Sea as well as the northern part of the
Yukon (the Yukon North Slope) (Figure 1). Six ISR community Hunters and Trappers
Committees (HTCs) were created pursuant to the Inuvialuit Final Agreement (IFA), the land claim for the ISR. The HTCs serve the role of advising the Inuvialuit Game Council and wildlife co-management boards on local matters including: hunting and trapping and subsistence use of fish and animals; sub-allocating subsistence quotas; making by-laws governing the exercise of the Inuvialuit rights to harvest; and encouraging and promoting
Inuvialuit involvement in conservation, research, management, enforcement and utilization of wildlife resources (The Western Arctic Claim – Inuvialuit Final Agreement, 1987,
Section 14(76)).
The IFA also states the “Inuvialuit shall have the preferential right within the ISR to harvest fish for subsistence usage including trade, barter, and sale to other Inuvialuit” and
“if subsistence quotas are required to be set out in order to ensure conservation of the resource, they shall be set jointly by the Inuvialuit and the Government” (The Western
! ! 8!
Arctic Claim – Inuvialuit Final Agreement, 1987, Section 14(31)). These fishing rights, as well as fishery monitoring and research, are led by the FJMC, the co-management board responsible for managing fish and marine mammals (Ayles et al. 2007). The FJMC works within an adaptive co-management framework and incorporates the precautionary principle in their approach to the management of freshwater and marine resources in the ISR (Ayles et al. 2007).
The people of the ISR are a fishing people and have been for centuries (Alunik 2003,
Codon et al. 1996, Community Corporations et al. 2006). In the past, fishing was an important part of Inuvialuit culture and survival. Freshwater, anadromous and marine fishes were captured year-round (Government of the Northwest Territories, 1991; Nuttall
2005, Community Corporations et al. 2006). Historically fish were also an important source of food for dog teams, but with the government moving the nomadic Inuvialuit into communities, and with the introduction of snowmobiles in the 1970’s, few dog teams remain in the ISR (Papik et al. 2003).
Arctic Char subsistence fisheries continue to play an important role in the ISR (Bell and Harwood 2012, Porta and Ayles 2015). A survey of 266 Inuvialuit conducted in 2008 reported that 66.9% of people surveyed ate Arctic Char and it was the third most consumed species after caribou and berries (Egeland et al. 2010a). In the same survey, Arctic Char was the country food eaten in the highest quantity with on average 116 grams consumed per day (Egeland et al. 2010a). Between 2000-2006, consumption of locally caught fish increased by three times the previous recorded amounts in the ISR (Donaldson 2010), showing that fish remain an important resource.
! ! 9!
The geographic range of Arctic Char includes the areas surrounding the three northernmost communities in the ISR, (Paulatuk, Ulukhaktok and Sachs Harbour). There are no large-scale commercial Arctic Char fisheries in any of these communities as seen in
Nunavut or Nunatsiavut, however, there are several domestic fishers in Paulatuk and
Ulukhaktok with commercial licences that catch a small number of char to sell to the
Inuvialuit Regional Corporation. Sachs Harbour relies on Arctic Char solely for subsistence purposes. The Sachs Harbour Community Conservation Plan (Community of
Sachs Harbour et al. 2008) listed Arctic Char as a very important traditional food source and a high research priority with interest in knowing more about fishing resources on Banks
Island.
The northernmost ISR community of Sachs Harbour on the southwest of Banks
Island, is a small fly-in community with a population of approximately 100 residents at the time of the study, including 32 individual fishers, representing approximately 18 households. Resident lifestyles include both living off the land and wage-earning employment. The local worldview regarding renewable resource exploitation is summarized well in Sachs Harbour Community Conservation Plan: “if [resources] are used and enjoyed now, they must be left and preserved so that they will be there for the next year and for future years” (Community of Sachs Harbour et al. 2008). Important subsistence species include bears, hares, waterfowl, marine mammals, plants and fish. Harvested fish species include Arctic Char and cod in the marine environment, and Arctic Char, Lake
Trout and Lake Whitefish from freshwater environments (Community of Sachs Harbour et al. 2008).
! ! 10!
1.6 Research Questions
The importance of Arctic Char to Inuvialuit communities (Sachs Harbour local experts, 2008-2015, pers. comm., Egeland 2010), the remote location, and the impending effects of a changing environment necessitate rigourous long-term community-based monitoring for sustainable management of the resource. Landlocked Arctic Char populations were chosen for study due to the lack of research on freshwater-restricted char and community-based monitoring of landlocked fishes in Canada’s north. Also, this allowed for a simplified study system where char were confined to one waterbody throughout their life. The goal of this research was to offer insights into which community-based monitoring parameters and factors would provide the information and knowledge needed by local resource users and decision-makers to make informed choices for managing Arctic Char in light of CVC. As such, I investigated the following research questions:
1.! Does habitat affect the quantitative and qualitative condition of landlocked
Arctic Char, and if so, which habitat and biological parameters show
consistent relationships with fish condition such that they can be used to
monitor char?
2.! Does local environment and climate affect the growth of landlocked Arctic
Char, and if so, which environmental and biological parameters show
consistent relationships such that they can be used to monitor char?
3.! What factors and parameters should be considered for Arctic Char community-
based monitoring?
! ! 11!
1.7 Research Approach
Inuit have attained an intimate and detailed understanding of their surroundings through their own experiences as well as thousands of years of accumulated observations passed on from their ancestors. This intimate understanding of the local environment, known as Traditional Ecological Knowledge, or more specifically Inuit knowledge and observation, can provide expert information to the study of climate change as well as its effects on northern species (Riedlinger and Berkes 2001, Furgal et al. 2006, Laidler 2006,
Haggan et al. 2007). Traditional Ecological Knowledge and is being increasingly recognized by the scientific community as a valuable way to understand our environment
(e.g. Huntington et al. 2004, Furgal et al. 2006, Berkes 2008, Huntington 2011, Fraser et al. 2013).
Fishers’ knowledge has a long-standing history in global fisheries monitoring and management, in both marine and freshwater environments (e.g. Pomeroy 1995, Neiss et al.
1999, Johannes et al. 2000, Pitcher 2001, Le Diréach et al. 2004, Stead et al. 2006,
UNESCO 2007, Schafer and Reis 2008, Carvalho et al. 2009, van Zwieten 2011, Cooke
2013), and is gaining recognition in the circumpolar north (e.g. Berkes and Fast 2007,
Knotsch et al. 2010, Eythórsson and Brattland 2012). In Canada, incorporating Indigenous or local expert knowledge and observations in fisheries monitoring and management has been an on-going trend (e.g. Harvey and Coon 1997, Pellerin and Grondin 1998, Neiss et al. 1999, Berkes et al. 2001, Gallagher 2002, Morris et al. 2002, Howland et al. 2004,
Kristofferson and Berkes 2005, Fraser et al. 2013, Bell and Harwood 2012, Lapointe 2014).
There is a great opportunity for increasing our understanding of the potential effects of climate change on Arctic species through integrating the knowledge of the Inuit with the
! ! 12! knowledge gained through scientific methods (Huntington et al. 2004, Carmack et al.
2008). Using both bodies of knowledge produces a more robust suite of information that incorporates local expertise and understanding of the resource (Huntington et al. 2004,
Furgal et al. 2006, Berkes et al. 2007). This type of research design, referred to as mixed methods, is an approach to research combining quantitative and qualitative methods, with the analysis focusing on integration of the two forms of data (Creswell 2009).
I chose a mixed methods research design to integrate social sciences (qualitative) methods and Inuvialuit knowledge and observation (IKO) with scientific (quantitative) methods and scientific ecological knowledge and observation (SEKO). I took steps within my research that allowed the knowledge of the Inuvialuit local experts to be incorporated with the openness and respect it deserved. My research design incorporated the intersection of a pragmatic philosophical approach with ethnographic strategies of inquiry (Creswell
2007, 2009). Pragmatism is a philosophical approach to research that assesses the meaning of theories in terms of the success of their real-world practice, and considers multiple methods, different worldviews, and different forms of data collection and analysis
(Creswell 2009). Ethnography is a qualitative strategy of inquiry in which the “researcher studies an intact cultural group in a natural setting over a prolonged period time by collecting, primarily, observational and interview data…the research process is flexible and typically evolves contextually in response to the lived realities encountered in the field setting” (Creswell 2009, p. 13).
My learning about the Inuvialuit worldview, culture and fishing practices was achieved using an Inuvialuit pedagogy where people are active learners, absorbing by watching and doing in a land-based environment where skills needed for this lifestyle are
! ! 13! acquired through observation and practice (Lyons 2010). A minimum of two months cumulative time, per year, were spent in the community interacting and collaborating with local experts over the course of the five-year research phase (January 2008 – December
2012), and several weeks per year during the phase of transferring the monitoring program developed using study results to the community (January 2013–2014).
To ensure the study met the needs of the community and to ensure the equal inclusion of both IKO and SEKO, local expert fishers from the community were directly involved in determining study locations and had on-going input into the research design, study parameters and interpretation of results. Local assistants who worked on the project in the field determined intra-lake sampling locations and sampling methods based on local fishing practices. Local assistants were also trained in scientific sampling methods and worked with me throughout the project to sample all fish habitat parameters and to collect data from fish caught in scientific nets and local subsistence catches. This research approach led to an environment of reciprocal learning between myself and the local experts.
1.8 Research Design and Methods
An exploratory research approach (Creswell 2009) was used, with a modified mixed methods parallel concurrent design with some sequential steps (adapted from Creswell
2009). The mixed methods design organized and directed the collection and analysis of qualitative (IKO) and quantitative (SEKO) in Chapters 2 and 3. Contemporary biological and ecological sampling methods were used to gather SEKO on Arctic Char condition and growth, fish habitat, and local climate conditions. Concurrently, contemporary social science research methods were used to gather IKO on the same parameters. Reiterating sequential steps determined new parameters or questions for study required to explain
! ! 14! phenomena observed in a previous step. An ecological question would be asked, SEKO and IKO collected, and analyses carried out from both knowledge bases, producing answers, or sometimes more questions to be addressed through further data collection and analyses. Once all available data, information and knowledge were analysed, a process of triangulation (Creswell 2009) compared qualitative and quantitative information gathered at the same scale (conceptual, spatial, or temporal) to determine convergence or divergence between the two knowledge bases (Gagnon and Berteaux, 2009; Furgal and Laing, 2012).
Chapter 4 used qualitative methods, information, and analyses exclusively to analyse grey and peer-reviewed literature and interviews with key informants from Arctic Char community-based monitoring programs across the Canadian Arctic.
1.9 Organization of Manuscript-Based Dissertation
My dissertation is organized into five chapters, with three chapters (2-4) written as stand-alone manuscripts to be submitted for peer-review publication, and as such are presented in third person. This chapter (1) serves as the introduction to the dissertation providing relevant background and context to this study. Chapters 2, 3 and 4 specifically address the main objective of my research. Chapter 5 is an integrated discussion and conclusion of Chapters 2-4. Figure 2 provides a visual overview of how the dissertation is structured.
Chapter 2: Understanding the Effects of Lake Habitat on Landlocked Arctic Char
(Salvelinus alpinus (L.)) using Scientific Ecological and Inuvialuit Knowledge and
Observation, presents a mixed methods approach examining if lake habitat affect lake- resident Arctic Char quantitative and qualitative condition, and if so, which biological and habitat parameters can be used to monitor Arctic Char.
! ! 15!
Chapter 3: Understanding Growth Variability in Landlocked Arctic Char in
Response to Local Environmental Conditions Using Scientific Ecological and Inuvialuit
Knowledge and Observation presents a mixed methods approach used to examine if local climate and environment affect landlocked Arctic Char growth, and if so, what environmental and biological parameters can be used to monitor Arctic Char.
Chapter 4: Factors Influencing the Community Monitoring of Arctic Char Fisheries, presents a qualitative approach to examine which factors and parameters should be considered for Arctic Char community-based monitoring as determined by key informants and literature from six established and recognized programs across Canada’s Arctic regions.
Chapter 5: the conclusion of the dissertation, is an integrative discussion of Chapters
2–4 including an overview of what was learned through using the mixed methods approach to this research.
! ! 16!
!
Figure 2. Overview of the dissertation organization, presenting research questions, the mixed methods approach with qualitative and quantitative methodologies, and knowledge integration techniques for each chapter.
1.10 References
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CHAPTER 2:
Understanding the Effects of Lake Habitat on Landlocked Arctic Char
(Salvelinus alpinus (L.)) using Scientific Ecological and Inuvialuit
Knowledge and Observation
2.1 Introduction
Freshwater and anadromous fisheries, including those for Arctic Char (Salvelinus alpinus (L.)), are important commercial and subsistence resources across the Canadian
Arctic. Anadromous Arctic Char are an important socio-economic species that have mixed commercial-subsistence harvests in Nunavut (Roux et al. 2011) and Nunatsiavut (Dempson et al. 2008) (see Chapter 1, Figure 1). Commercial-subsistence anadromous char fisheries also existed in the Inuvialuit Settlement Region (ISR) in the past and subsistence fisheries continue to play an important role for the Inuvialuit (Porta and Ayles 2015). The non- commercial harvest of country foods, including freshwater and anadromous fishes, is an important part of Inuit life, culture, and human health (Nuttall 2005, Furgal and Seguin
2006, Donaldson et al. 2010, Porta and Ayles 2015). Subsistence fisheries in the Canadian north contribute toward the need for healthy foods in local communities (Berkes 1990,
Donaldson et al. 2010) and provide essential nutrients, proteins and fats resulting in protection against diseases and illnesses (Dewailly et al. 2001, Donaldson et al. 2010,
Egeland 2010).!!Small-scale domestic Arctic Char fisheries play an important role in household food security, as many residents still live a subsistence-based lifestyle
(Donaldson et al. 2010, Roux et al. 2011, Bell and Harwood 2012).
! ! 31!
Regional increases in climate variability and change in combination with the resulting effects on the local environment, flora, and fauna, have the potential to influence in northern fish habitats (Wrona et al. 2006). Projected alterations to freshwater habitat include changes in biogeochemical processes, allochthonous inputs, ice-free conditions, water temperature regimes, bank erosion, primary and secondary productivity, and trophic structure (Wrona et al. 2006, Vincent et al. 2013, Poesch et al. 2016). These habitat alterations will lead to indirect climate change effects on char, projected to result in changes to size and numbers, body condition and condition of meat for consumption (Reist et al.
2006a and b). Local Inuit populations harvesting fish resources will have to adapt to these effects, which have the potential to alter or lessen the potential use of the resource, change the quality of the fish meat, and change access to healthy fish stocks (Berner and Furgal
2005, Wrona et al. 2005, Reist et al. 2006a, Furgal and Prowse 2008). Thus, there is a need to understand the processes and effects of a rapidly changing environment on Arctic fisheries.
Sustainable fisheries management requires the prediction of biological and ecological responses to a variety of mechanisms and perturbations. However, “owing to a dearth of basic knowledge regarding fish biology and habitat interactions in the north, complicated by scaling issues and uncertainty in future climate projections, only qualitative scenarios can be developed in most cases. This limits preparedness to meet the challenges of climate change in the Arctic with respect to fish and fisheries” (Reist et al. 2006a, p.370).
While a number of long-term Arctic Char monitoring programs exist in the Canadian
Arctic, they are mostly focused on mixed commercial-subsistence fisheries and focus only on anadromous Arctic Char populations. Even within these monitoring programs, Roux et
! ! 32! al. (2011) stated that “Salvelinus alpinus fisheries in Nunavut are currently managed in data-poor situations”. Further to this, there is limited monitoring data for Arctic freshwater fisheries and ecosystems (Culp et al., 2012, Cooke and Murchie 2013) and limited understanding, in the Arctic in particular, regarding ecological connections between climate parameters and freshwater biological systems. According to Niemi et al. (2016, p.9), “Mechanistic understanding of many of the [Arctic] freshwater…systems is limited, basic biotic inventories and the structural and functional characteristics of…the ecosystems are lacking for many areas, and understanding of tolerances and preferences of key biota are similarly limited”.
To understand the effects of climate change on freshwater Arctic Char, managers and resource users require rigourous monitoring plans that provide appropriate data from rigorously chosen indicators (Power et al. 1989, Jacquet et al. 2010). Monitoring ecosystems can provide understanding and insights to baseline conditions, information about patterns over time, and provide information toward forecasting changes in a resource
(Busch and Trexler 2003). The best available information should be used to improve understanding of fundamental ecological principles and baseline states for freshwater
Arctic Char fisheries. Fisheries data and information can be generated from many sources including stakeholders and local ecological knowledge (Lapointe et al. 2014). Local expert ecological knowledge and observations are important sources of information being used more frequently in research to provide additional information to that generated through scientific studies (e.g. Furgal et al. 2006, Martinez-Levasseur et al. 2016), including towards the study of remote fisheries in Canada (e.g. Fraser et al. 2013). In recognition that multiple methods and sources of information could increase confidence in the
! ! 33! interpretation of results (Gagnon and Berteaux 2009) and provide a more thorough understanding of parameters being studied (Furgal et al. 2006, Fraser et al. 2013), a mixed methods approach combining both quantitative (scientific) and qualitative (local expert) approaches and information was used in this study.
The intent of this exploratory mixed methods research was to better understand the effects of lake habitat parameters on Arctic Char condition in three landlocked lakes fished by Inuvialuit on Banks Island in the Inuvialuit Settlement Region, and to determine if certain habitat parameters could be used as potential monitoring indicators of char condition. In this study, contemporary scientific sampling methods and analysis of quantitative data were used to measure the relationship between habitat parameters and
Arctic Char condition. At the same time, the effects of habitat parameters on char condition were also explored using social science methods and analysis of qualitative information from interviews, scoping sessions and meetings with local Inuvialuit fish experts from
Sachs Harbour in the Inuvialuit Settlement Region in Canada’s Western Arctic.
2.2 Methods
2.2.1 Mixed Methods Research Design
Two literature reviews were conducted to initiate this research. The first was conducted to determine existing indicators used in scientific ecological research to measure
Arctic Char condition and habitat parameters, as well as to provide understanding of the complex range of life histories seen in this species. A second literature review was also conducted of documented Inuvialuit knowledge and observation on char and lake habitat in the study area. Literature searches used online databases of both grey and peer-reviewed papers on char, and additional documented Inuvialuit knowledge was accessed through a
! ! 34! review of resources contained in ISR libraries.
In this paper, the term Inuvialuit knowledge and observation (IKO) is used as it was preferred by the Inuvialuit involved in the study to Local Ecological Knowledge or
Traditional Knowledge, commonly used in this literature. IKO is the ecological knowledge held by Inuvialuit, based on information obtained individually or as a group through living on or using the land within their lifetime (Community Corporations 2006, personal communication with local experts in the Inuvialuit Settlement Region 2008-2015). This knowledge is sometimes represented in long-term syntheses of that data and information, and sometimes is connected with cultural beliefs or worldviews. In this paper, scientific ecological knowledge and observation (SEKO) refers to data and information gained through scientific inquiry within the belief that a phenomenon of interest must be
“understood in context” (Peterat 2008, p. 237).
Qualitative condition of char is used to refer to how the Inuvialuit qualitatively describe whether or not a fish is acceptable for human consumption and includes a variety of factors such as “fatness” (girth compared to length) and the general health of the fish including flesh and meat texture, flavour, colour, and the absence of diseases, lumps, cysts, or deformities. Quantitative condition of char refers to the numerically calculated size of fish using Fulton’s K (Ricker 1975) which is 100,000 multiplied by the fish weight (in grams) and divided by the cube of fish length (in millimeters).
In this study, a modified mixed methods parallel concurrent design with some sequential steps and final knowledge and observation triangulation was used (adapted from
Creswell, 2009; Figure 1). This research design facilitated the linking of quantitative ecological and qualitative social science methods and information. In some instances,
! ! 35! analysis of qualitative information (IKO) led to further quantitative inquiry, and in others, analysis of quantitative data (SEKO) led to further qualitative inquiry (sequential steps) prior to the final step of triangulation (comparative and integrative analyses) and interpretation of both knowledge bases. Triangulation (Creswell 2007, Rothbauer 2008) involved comparing the quantitative (SEKO) and qualitative (IKO) knowledge bases when they were comparable at the same scales (temporal, spatial, conceptual) to determine convergence or divergence between the two knowledge bases (Gagnon and Berteaux 2009,
Furgal and Laing 2012).
! ! 36!
Figure 1. Diagram illustrating the modified parallel concurrent research design with some sequential steps and final information triangulation followed in this study. Sequential steps occurred in some instances where quantitative analysis dictated further qualitative inquiry
(arrow A), or qualitative analysis dictated further quantitative inquiry (arrow B), prior to final information triangulation and interpretation (adapted from Creswell 2009).
2.2.2 Research Location
The northernmost ISR community of Sachs Harbour (71°59'6.52"N,
125°14'47.71"W) is a small fly-in community that had a population of 112 residents in 2011
(http://www12.statcan.gc.ca/census-recensement/index-eng.cfm, accessed December 3
2016) including 32 individual fishers representing approximately 18 households. This study location was chosen due to the community’s reliance on country foods, including
! ! 37!
Arctic Char (Egeland 2010), and the dearth of freshwater fish research in the area. Five lakes near the community of Sachs Harbour were identified by the Sachs Harbour Hunters and Trappers Committee (SHHTC) as important char fishing locations (Capron, Fish,
Kuptan, Middle and Raddi lakes). The study was restricted to landlocked char, as they are isolated in the same location throughout their life and therefore present the opportunity to examine the effects of local environmental factors on growth over time in one location
(Kristensen et al. 2006).
Three of the lakes identified by the SHHTC were essentially landlocked and therefore included in this study: Capron, Kuptan, and Middle lakes (Figure 2). The three lakes act as closed systems with only rare opportunities for Arctic Char to migrate elsewhere. Kuptan and Capron lakes have narrow, shallow and ephemeral spring streams, one to the ocean and one to the watershed, respectively. However, these ephemeral streams only allow outward spring migration and only occur under extreme spring precipitation events. Middle Lake is closed. This paper will discuss the limnology and ecology of the lakes in further detail, however, as a brief introduction, all three of the lakes fall within the
Low-Arctic Ecoclimatic Zone (Lim et al. 2005) and therefore are typical of waterbodies on the southern coastal rim of Banks Island, but not necessarily of those of the Mid- or High-
Arctic Zones further north and inland. As such, these lakes fall within a zone of relatively richer biological diversity, higher annual air temperatures, and longer growing seasons than other areas of Banks Island (Lim et al. 2005).!!!!!
! ! 38!
Figure 2. Map of the study location in the Inuvialuit Settlement Region, NT, Canada. Inset map shows locations of Capron, Kuptan, and Middle lakes and the community of Sachs
Harbour (marked with a black dot), on the southwest side of Banks Island. (Both maps adapted from files courtesy of J. Babaluk, Fisheries and Oceans Canada).
2.2.3 Local Experts and Community Participation
Local fishing experts (local experts defined by Davis and Wagner 2003) in the community were determined through a specific process which involved asking two community organizations to independently create lists of people who fit the criteria of being individuals who: fished in all fishing seasons; fished several times per month during the fishing seasons; and had fished locally for at least ten years. Individuals whose names appeared on both lists were approached for interviews. Prior to interviews, the final list
! ! 39! was reviewed with the two organizations to ensure it collectively included individuals with experience from all three study lakes.
While some local experts were also members of the SHHTC, only identified local experts were involved in the qualitative information collection through participation in scoping sessions, semi-directed IKO interviews and validation workshops. Members of the
SHHTC were consulted regarding initial study design, including the selection of study locations and appropriateness of some methods. The SHHTC was included due to their elected role as the fish and wildlife management representatives for the community. Other community members, including local fishers and SHHTC members, participated in community meetings and workshops at various stages of the project as well, but were not involved in the scoping sessions, semi-directed IKO interviews or validation workshops, as they were not identified as local fishing experts (or did not live in the community at the time of the interviews).
2.2.4 In Situ Data Collection
2.2.4.1 Collection of Inuvialuit Knowledge and Observation (IKO)
Exploratory semi-directed interviews (Creswell 2009) were conducted with local experts in spring 2010. Interviews were digitally recorded. Community residents fluent in
Siglitun or Inuinnaqtun (local Inuvialuktun dialects) were used as translators and present at an interview whenever required or requested by the interviewee. Interviews focused on
IKO of: historical and current conditions of freshwater fish habitat; potential changes to fish habitat; historical and current char size and condition; and, potential changes in char.
Information on interviewee attributes, human use of the resource; perspectives on monitoring of char; and, other related topics of interest to the participant were also
! ! 40! discussed and recorded. The interviews provided background information on participants and context to the issues of focus in the study.
Ethnographic fieldwork (Nadasdy 2003), prolonged engagement (Lundy 2008), and a community-collaborative research approach (Tondu et al. 2014) built trust with the fishing community and created an environment of open and reciprocal learning between the researchers and the local experts. Ethnography is a qualitative methodology in which the researcher studies a cultural group in situ over a prolonged time, primarily through observation and interviews, and where the research process is flexible in order to respond to the lived field setting (Creswell 2009). Prolonged engagement is a qualitative methodology referring to spending extended time with study participants in their native culture and everyday world, resulting in the immersion of the researcher in the culture, and allowing the study to go farther in investigating phenomena that cannot be adequately explored with short-term studies (Lundy 2008). A minimum of two months cumulative time per year was spent in the community interacting and collaborating with local experts over the course of the five-year research phase (January 2008 – December 2012).
Additional participant observation activities (McKechnie 2008) done in an ethnographic format included: attending community gatherings and SHHTC meetings, home visits with local experts, and trips on the land accompanying, assisting and learning from fishers in their travels and fishing activities. Participant observation is a qualitative method of “data collection in which the researcher takes part in everyday activities related to an area of social life in order to study an aspect of that life through the observation of events in their natural context…to gain a deep understanding of a particular topic or situation through the meanings ascribed to it by the individuals who live and experience it”
! ! 41!
(McKechnie 2008, p. 598). The information obtained through participant observation complemented the semi-directed interviews by providing additional insight and explanation of the information collected through the interviews.
Local research assistants (RAs) were chosen by the SHHTC based on who they felt had a good knowledge of being out on the land and a keen interest in research. The local
RAs were trained to aid with the collection of all quantitative data. Trained RA from outside of the community also assisted with the collection of the in situ IKO and SEKO.
At the study sites, local experts and local assistants determined specific intra-lake sampling locations. For example, intra-lake areas known for good fishing were chosen as the locations to conduct plankton tows, as field logistics did not allow for the opportunity for a random sampling protocol across the entire lake. The ethnographic, prolonged engagement, and participant observation components of the research were conducted at times deemed important by the community for fishing efforts and times of community gatherings. Research involving IKO was carried out under Trent University Research
Ethics Board Approval (#21069) with approval from the SHHTC and local expert participants.
2.2.4.2 Field Sampling Techniques for Lake Habitat
The bathymetry of each lake was estimated using spatially referenced depth measurements taken every 100 m, or more frequently if the depth changed more than 3 m, along a set of transects that covered the main littoral and pelagic zones. Depth was recorded using a depth sounder (541 Sonar – 409700-1, Hummingbird USA) and spatial positions were recorded with a handheld GPS unit (Garmin GPSMap76, Garmin Ltd. Switzerland).
Lake surface area, volume and bathymetric maps were generated in ArcMap (ArcGIS
! ! 42! v10.2, ESRI, USA) using the lake boundaries and the recorded depth, and the Krieg function using the Spatial Analysis Toolbox.
Temperature profiles of Capron, Middle and Kuptan lakes were carried out in summer in 2011 (August 4, 8 and 11, respectively) when the water was ice-free, and in spring 2012 (May 16 for all lakes) when the lakes were still fully covered with ice.
Temperature loggers (HOBO Water Temperature Pro v2 Data Logger – U22-001, Onset
Computer Corp. USA) were set on a vertical rope anchored at the bottom with a float at the surface. The loggers were set at the deepest point of the lake at four depths: just below the surface, 1/3 max depth, 2/3 max depth and just above bottom. In spring, temperature loggers were placed in the same fashion except that the float was allowed to freeze into the ice through the hole drilled, with the surface logger just below the bottom of the ice.
Water chemistry analyses were conducted between 2008 to 2011 to characterize the suitability of the lakes for providing fish habitat for salmonids and to observe possible differences among them. Trace metals were analysed in water samples collected in the summer season for 2008, 2009 and 2011 in Middle and Kuptan lakes, and 2008 and 2011 in Capron Lake, as well as during winter in all lakes in 2010. Nutrients, ions and solids were analysed from water samples collected from all lakes in winter 2010, and nitrogen ions, calcium carbonates, chlorophyll a, pH and total dissolved solids were collected in all lakes in summer 2011. Water samples were collected in glass and plastic bottles, using the preservatives nitric acid for metals samples, and sent to Taiga Labs in Yellowknife NT within 72 hours. All analyses were conducted following industry standards (see ALS
Laboratories, ALS Global, Edmonton AB, www.alsglobal.com).
! ! 43!
2.2.4.3 Field Sampling Techniques for Arctic Char Condition and Diet
To measure condition, Arctic Char from the three study lakes were captured from
2008-2012 using floating and sinking multimesh gillnets with a total length of 120 m and
20 m bar mesh sizes: 10 mm (110/2 twine), 19 mm (110/3), 33 mm (110/3), 45 mm (210/2),
55 mm (210/3) and 60 mm (210/3); net depth = 1.8 m. Nets were set randomly from shore extending into the littoral zone (water depth range: 0-8 m) and were checked regularly.
Three nets were continuously set in each lake for 3-6 days until a target maximum of 75 char (as dictated as per the Fisheries and Oceans Canada Scientific Fishing Licence) were dead sampled each year from Capron (2008, 2010, 2011), Kuptan (2009, 2011), and Middle
(2008, 2009, 2011) lakes. In one year, more than 75 fish were caught in Middle Lake due to an unexpected large capture in one net set duration. In addition to summer net sets, subsistence catch was also sampled whenever possible. All fish sampling was in accordance with the Guide to the Care and Use of Experimental Animals (www.ccac.ca) and following the Trent University Animal Care Committee Approvals #08052, #09032 and #10018 as well as the Department of Fisheries and Oceans Canada Animal Use
Protocol approvals.
Total and fork length were measured in centimetres using a fish measuring board.
Wet mass of the whole fish and gonads were measured in grams using an electronic scale.
Fish were examined internally for maturity, parasites, and stomach contents as well as externally for parasites. Whenever possible, the sex of the fish was identified including whether the gonads were in an immature, or mature (running ripe or resting) state. Both sagittal otoliths were collected. The presence of diet items from the stomachs were recorded using simplified diet categories including: plant, zooplankton, worm, amphipod,
! ! 44! insect (larvae and adult), fish eggs, and fish. Empty stomachs were also recorded. If possible, insect diet items were identified at least to Order in the field. A subsample of guts were frozen and shipped to the laboratory for further analyses. All fish meat, flesh and heads were returned to community members who wanted them for human consumption as requested by the SHHTC.
In addition to stomach contents, zooplankton biomass and diversity were estimated for two samples per lake and were collected with a metered conical, 0.5 m diameter
(D:L=2:7), 200-µm mesh net fitted with a Rigosha meter. The samples were taken in summer 2011 in different areas within each lake over the pelagic zone dictated by locations of good fishing by local experts. The net was towed behind the research vessel at a speed of 2.8 km/hr and depth between 2–5 m below the surface for 250–400 m (spanning 5-9 minutes for each tow). Zooplankton were stored in 95% ethanol for shipping.
An in-field visual assessment of the surface of scales, gills, gut cavity (without cutting into guts), and flesh (meat) was carried out for macro-parasites and parasitic cysts depicted in Common Parasites of Freshwater Fishes in the Northwest Territories and
Nunavut (Stewart and Bernier 1999). Types present and loads were recorded using a scale created in collaboration with local RAs based on visual observations that could easily and accurately be conducted by fishers or community-based monitors. The visual-assessment parasite load scale used was:
A.! None: no parasites present
B.! Low: < 30 individuals, ≤ 2 genera of parasites, and < 25% coverage of
gut/flesh/gills/scales
! ! 45!
C.! Medium: > 30 individuals, > 2 genera of parasites, and 25-75% coverage
of gut/flesh/gills/scales
D.! High: > 30 individuals, > 2 genera of parasites, and > 75% coverage of
gut/flesh/gills/scales.
2.2.5 Qualitative Analysis of Inuvialuit Knowledge and Observation (IKO)
Audio recordings of local expert semi-directed interviews and scoping sessions were transcribed verbatim. Individual transcripts were returned to participants for the opportunity to verify their transcript prior to IKO analysis. All transcripts were entered into the qualitative analytical software NVivo (QSR International Pty Ltd. 1999-2014 v.
10). A two-pass thematic coding process was used in NVivo (Saldana 2009). First, descriptive coding examined patterns of responses to the interview questions. The second pass examined the transcripts for common thematic patterns that were not explicitly asked in the interviews but emerged from the interview discussion. If these text units emerged, they were coded as categories of emergent themes.
Inter-coder variability was checked on two interviews with the assistance of a trained qualitative analyst not involved in the research. This was done to increase reliability in the development and application of the coding scheme to the qualitative information.
Comparisons between coders were done and areas of disagreement were discussed until consensus was reached in terms of the application of the codes to text. Member checks by local experts were used to validate coding and IKO interpretation during follow-up visits and validation meetings in the community. Member checks is a qualitative methodology whereby study participants are consulted on the accuracy and validity of the results (Jensen
2008). Additional external validation of researcher interpretation of results was achieved
! ! 46! through a series of local expert meetings and multiple local expert home visits (Creswell
2009). The results of IKO analysis were used to identify key local expert observations of changes in Arctic Char condition and to identify key indicators or cues of direct and indirect associations between lake habitat and char condition.
2.2.6 Laboratory Analyses of Scientific Ecological Knowledge and Observation
(SEKO)
Prey items were removed from the stomachs of a subset of captured char and all invertebrates (except parasites) were sent to Dr. R. Quinlan’s Aquatic Ecology, Limnology, and Paleoecology lab at York University (Toronto, Ontario) for expert identification to lowest possible taxonomic level. Parasites were removed from the body cavity (including muscle and internal organs), gut surface, and inside dissected stomachs. As
Echinorhynchus mainly occurs in the intestines, this parasite may be under-represented in the lab samples as only the stomachs and beginning of the intestines were dissected as this was the most cost-effective method. Gill parasites were not collected, preserved or identified in the lab. Parasites from all gut samples were sent to the Canadian Cooperative
Wildlife Health Centre (Edmonton, Alberta) for expert identification. All specimens were identified to lowest taxonomic level possible. Several parasite specimens could only be identified by molecular diagnosis. These specimens were subjected to DNA extraction using an Epicentre DNA extraction kit (Epicentre USA) by the Canadian Cooperative
Wildlife Health Centre. Extracted DNA from each specimen was used as a template to amplify a part of a mitochondrial gene, COX-1. The amplified gene was then submitted for Sanger sequencing. The sequence obtained was then blasted to find the closest match in the NCBI-nucleotide database.
! ! 47!
All zooplankton samples from the plankton tows were sent to Aquatic Bio-Services
(Waterloo, Ontario) for expert identification to species level using Dumont and Negrea
(2002) and Dussart and Defaye (2001), as well as determining average species body size, density and biomass. One of the two Capron Lake samples had not been preserved completely and could not be used in the Aquatic Bio-Services analyses. One zooplankton sample from each lake had been analysed in the laboratory for bulk wet weight prior to
Aquatic Bio-Services analyses to determine total biomass estimates. This allowed for the verification that the bulk wet weights from the whole sample were similar to the aggregated biomass measurements from the Aquatic Bio-Services results. Therefore, the bulk wet weight, for the Capron Lake sample that could not be analyzed by Aquatic Bio-Services, was used for total biomass for that sample.
2.2.7 Statistical Analyses of SEKO
Statistical comparisons of water quality were not possible for all parameters. Either samples were below detection limits or were collected only once in winter or summer.
Where comparisons were possible among the three lakes, a one-way analysis of variance
(ANOVA) with post-hoc Tukey test was used. Assumptions of the ANOVA were verified for this analysis by examining water quality parameters taken from other ponds and lakes on Banks Island (Lim et al. 2005).
Maximum lengths of fish caught were calculated using Pauly’s (1984) method of the average of the largest 10 fish per lake sample. Fish condition was calculated using
Fulton’s K (Ricker 1975) which is 100,000 multiplied by the fish weight (in grams) and divided by the cube of fish length (in millimeters). When comparing fish condition across populations it is important to determine whether the relationships between length and
! ! 48! weight are stable throughout development (Froese 2006). If not, the condition of younger and older fish should not be pooled together. To do so, a general additive model was run to test for the interaction of the categorical variable (lake) on the length-weight relationship
(i.e. a cubic power law) of the three populations. If the interaction was significant, log- transformed linear regressions between length and weight were conducted for each lake to determine if the exponent was greater than 3. If so, it suggested that the char grow relatively fatter as they age, and are different across lakes. If so, the relationship between fish condition and length was examined through ordinary linear least squares regresssion, and if there continued to be a significant change with length in at least one of the lakes, an age- subset of the population was used for inter-lake comparisons.
In this study, the adult subset of the population was used for inter-lake comparisons of fish condition, for fish length greater than 250 mm (to match the minimum size of char observed by the Inuvialuit, see Results). This value was also approximately the size of
Arctic Char at 50% maturity (see Chapter 3) and therefore an appropriate lower limit. Inter- lake comparisons of Pauly’s maximum length and fish condition were conducted using a one-way analysis of variance (ANOVA) with post-hoc Tukey comparisons (Sokal and
Rohlf 1981).
Gonado-Somatic Index (GSI) was calculated for each char by dividing the weight of the gonads by total fish weight, and multiplying the result by 100. The GSI was compared among lakes for running ripe fish only using a two-way ANOVA including both lake and sex with post-hoc Tukey comparisons (Sokal and Rohlf 1981).
Diet overlap among lakes was estimated using Schoener’s Index on the field-based diet categories using the following equation (from Yang and Livingston 1985):
! ! 49!
Cx,y = 1.0 - 0.5 | px,i - py,i |! where px,i and py,i are the proportions of prey i in the diets of Arctic Char in lakes x and y.
An index of 0 or 1 represents none or complete diet overlap, respectively, and although 0.6 is typically used as a threshold to represent significant levels of overlap, a jackknife procedure can also be used to determine a more statistical grounded threshold (Smith 1985).
The stomachs were sampled with replacement within each lake 1000 times and random samples were selected for each set of lake pairs without replacement to create a frequency distribution of Schoener’s Indices. For each lake pair the observed Schoener’s Index was deemed significant if it was larger than the 95% quantile of the random distribution. The detailed in-laboratory expert identifications of prey items were used to report species and life stages associated with invertebrate-based char diets. The abundance of prey items found within a subsample of char stomachs analysed in-laboratory were compared among lakes using non-parametric Wilcoxon Rank-Sum Tests in pairwise comparisons with a
Bonferroni correction for a critical p-value of p<0.01 (Sokal and Rohlf 1981).
Zooplankton biomass was compared among lakes using an one-way ANOVA with a post-hoc Tukey test of comparisons (Sokal and Rohlf 1981). There was not enough data to verify the assumptions of the ANOVA, however, there was no a priori reason to suspect the data was inherently non-normal.
The parasite loads of the fish within each lake and the effect of parasites on fish condition (i.e. Fulton’s K) was examined using a variety of tests. First, the in-laboratory parasite counts per fish were used to evaluate the accuracy of the in-field visually-assessed parasite loads for the same set of fish using a one-way ANOVA. A pairwise Chi-squared test with a Bonferroni adjusted p-value for multiple comparisons was conducted among all
! ! 50! three lake pairs to determine if the in-field parasite loads differed. A pairwise t-test was then conducted on pooled data across all lakes to determine whether the presence or absence of parasites within a fish gut influenced quantitative fish condition. Lastly, a two-factor
ANOVA with Tukey post-hoc comparisons were conducted to examine the effect of parasite load and lake on fish condition (K).
2.2.8 Triangulation of IKO and SEKO
Upon the completion of all IKO and SEKO analysis, interpretation, and validation, a process of triangulation was conducted by creating a matrix of results (Leech and
Onwuegbuzie 2008) of study parameters for information gathered at the same spatial, temporal or conceptual scales (Gagnon and Berteaux 2009, Furgal and Laing 2012). The matrix compared the SEKO results to the IKO results (e.g. Huntington et al. 2004, Gilchrist et al. 2005, Furgal and Laing 2012). This led to the determination of whether the results of the knowledge bases enriched, corroborated, contradicted or were inconsistent with one another with respect to the same phenomenon being explored (adapted from Mathison 1988 and Furgal and Laing 2012). One knowledge base was seen to enrich the other when it provided additional information where the other was lacking. They corroborated when similar information and explanations of observed phenomenon were found. Knowledge bases contradicted one another when information from the two sources diverged or disagreed. Knowledge bases were inconsistent when they did not corroborate, nor did they contradict. In instances where the knowledge bases contradicted or were inconsistent, further investigations were conducted, when possible, to better understand the differences in the observed phenomenon, or follow up studies are recommended when further investigations were not possible.
! ! 51!
2.3 Results
2.3.1 Local Expert Inuvialuit Knowledge and Observation (IKO)
A total of 18 local experts were interviewed. Disclosed ages ranged from 44-80 and interviewees had a combined 795 years of knowledge and observations about fish and fish habitat on Banks Island. Table 1 provides a summary of the interviewee attributes including the number of years of IKO for each of the three study lakes. Qualitative information identified possible relationships that may apply to any of the study lakes by pooling the information, except in instances where interviewees described a unique phenomenon in a specific study lake. As different family units fished at different lakes, knowledge and observations were distributed among the three lakes (Table 1). Middle and
Kuptan lakes were popular fishing locations, so the majority of local experts (89%, Table
1) interviewed had knowledge about these two lakes (combined 707 years of knowledge and observations, Table 1). Capron Lake was further away from the community with a rougher travel route, and was a less common fishing location. Therefore, fewer interviewed local experts (50%, Table 1) had knowledge of this lake (combined 437 years of knowledge and observations, Table 1).
!
! ! 52!
Table 1. Summary of Sachs Harbour local expert interviewee attributes including age, years of fishing experience and knowledge of the Capron, Kuptan and Middle lakes on
Banks Island NT (n=18).
Attributes Female Male (n=8) (n=10) Span Ages 44-79 43-80 Median Age 68 58 Mean Age 63.2 60.2 Span N Years Fishing Experience 22-58 24-71 Median N Years Fishing Experience 42.5 46 Mean N Years Fishing Experience 43 45.1 Knowledge of Capron Lake 50% 50% Knowledge of Kuptan Lake 88% 90% Knowledge of Middle Lake 88% 90%
2.3.2 Lake Habitat
The thematic content analysis of the IKO revealed information about fish habitat that stemmed predominantly from fishing activities. A list of the number of respondents reporting specific fish and lake habitat characteristics, in addition to habitat parameters that are potentially important to char condition, is provided in Table 2. Further descriptions of habitat parameters perceived or understood as important to char condition and examples of participant explanations are provided below.
! ! 53!
Table 2. List of topics from Inuvialuit knowledge and observation on fish habitat features and parameters having the potential to influence Arctic Char condition, with number of
Sachs Harbour NT local experts reporting the observation (local experts interviewed n=18).
Thematic codes of List of topics of IKO of lake habitat features having the Number of lake habitat potential to influence Arctic Char condition interviewees characteristics reporting (n = total number of observation interviewees who provided IKO for thematic code)
ALLOCHTHONOUS •! In spring, when lake ice is melting, fish in lakes feed in 4 INPUT front of ephemeral snowmelt creeks flowing from the (n=5) land •! Less snowfall and thicker active layer absorbing snow 2 melt over time has resulted in less overland flow running into the lakes •! Many muskox on hills around Capron Lake [and 1 therefore muskox droppings as potential nutrients into lakes] FISH SPECIES IN •! Middle, Kuptan and Capron lakes have Arctic Char* 2 LAKES and Lake Trout* (n=12) •! Kuptan Lake is mainly a trout lake, Middle Lake 3 important for Arctic Char ice fishing •! Lakes near study lakes, connected to the ocean via 7 Sachs River (Fish and Raddi lakes), have Arctic Char, Lake Trout and “crooked backs” [Lake Whitefish*] •! Fish smaller than ~20-25cm in length were lumped into 6 category of “minnow” (presence of Least Cisco* or Ninepsine Stickleback* mostly unknown) •! Ninespine Sticklebacks* in the puddles that form on the 1 ice in Middle Lake [identified from a photo during IKO interview] GOOD FISHING •! Good fishing location = many plump fish 9 LOCATIONS •! Mouth of creek (including spring freshets) entering 4 WITHIN LAKES lake (n=13) •! Every lake that has “shrimps” (amphipods) has the 1 healthiest fish •! Fish travel along cut banks 1 LAKE BOTTOM •! Middle Lake has mossy plants on bottom in shallow 3 (n=5) areas, deeper areas do not have moss •! Some areas of lakes have sand, gravel, rocks, or 2 boulders or a combination of these substrates LAKE DEPTH •! Middle Lake is extremely deep in parts 2 (n=4) •! Capron Lake is shallow throughout 2 •! Kuptan Lake depth is in between Capron and Middle 2 lakes
! ! 54!
WATER QUALITY •! Have not noticed changes to water quality (based on 18 (n=18) taste and clarity) •! All lake water clear in summer, Capron Lake has very 2 clear water WATER •! Water warmer now, noticeable change since ~1999- 6 TEMPERATURE 2001, kids started swimming in Middle Lake and ocean (n=7) in recent years •! Water temperature in the lakes has stayed the same 1 * Arctic Char (Salvelinus alpinus), Lake Trout (Salvelinus namaycush), Lake Whitefish (Coregonus clupeaformis), Least Cisco (Coregonus sardinella), Ninespine Stickleback (Pungitius pungitius).
2.3.2.1 Allochthonous Input
Five local experts (Table 2) pointed out observations of a fish habitat parameter not directly addressed in the semi-directed interview questions: the potential importance of allochthonous input to char feeding. As local experts Donna and John Keogak shared,
“there’s not enough snow, the creeks are not as high as they used to be, and that’s what [Arctic
Char] used to feed off is the run off in the creeks...when there is candle ice [in spring]…where the water is coming in from the land from snow melt, they’re all feeding at the run-off”. “In the summertime, [Arctic Char] are always in front of little creeks flowing out…try to feed on the bugs that go out from the little creeks” (Elder, Geddes Wolki). No SEKO was collected or available pertaining to allochthonous input in the three study lakes.
2.3.2.2 Lake Bottom
Less than half of the local experts (n=5/18, Table 2) provided knowledge about the habitat at the bottom of the lakes. These observations were made through direct observation, seeing both substrate and macrophytes through clear water in shallow areas.
Substrates observed included sand, gravel and rocks. Elder John Lucas Sr. shared “…that’s where we catch most of our fish, where there’s a lot of gravel on the bottom.” Elder Roger
Kuptana knew that “most of the lakes…are pretty sandy-like”. Betty Haogak observed in the shallow areas where she could see through the water column that “Middle Lake has
! ! 55! always had mossy plants on the bottom”. No SEKO was obtained or available for lake substrate in the three study lakes.
2.3.2.3 Lake Depth
Some local experts (n=4/18, Table 2) were able to estimate the deepest part of each lake within a few feet (information collected through on-the-land conversations). This was a result of their traditional ice fishing technique referred to as “jiggling”. Near the bottom of the lake and just under the ice were considered the best locations within the water column to catch char while ice fishing. Therefore, it was customary when starting to fish at a newly augered hole, to lower the line and lure until it touched the bottom and then wind it up 2–5 ft (0.61-1.52m) before jiggling the stick to move the hook and attract fish. Middle and
Kuptan lakes were reported to be much deeper than Capron Lake (n=4/18, Table 2). Local experts also reported that Middle Lake was so deep in some parts that it was difficult to reach the bottom with a fishing line. Measurements showed that Middle Lake had a surface area of 12.29 km2, a volume of 4.4 X 108 m3, and a maximum depth of 81 m. Kuptan Lake had a surface area of 5.43 km2, a volume of 1.3 X 108 m3, and a maximum depth of 66 m.
Capron Lake had a surface area of 5.77 km2, a volume of 1.9 X 107 m3, and a maximum depth of 13 m. Capron Lake is approximately half the surface area but 1/20th the volume of
Middle Lake (Figure 3).
! ! 56!
Figure 3. Bathymetry of Capron, Kuptan and Middle on Banks Island NT lakes measured in 2011 and presented in meters.
2.3.2.4 Water Temperature
Local experts commented on changes in lake surface water temperature. While one local expert had not noticed changes in average summer surface water temperatures within approximately the last 10-15 years, others (n=6/18, Table 2) observed that in one of the more frequently fished lakes (Middle Lake) water was noticeably warmer since approximately 1999-2001. No historical temperature data from the three study lakes were available to determine quantitative changes over time (i.e. no benthic core or long-term temperature profile studies have been done on these lakes nor was this observed through
IKO other than surface water temperatures). However, short-term temperature profiles for the three lakes obtained through temperature loggers indicated a temperature range throughout the water column of 0°C to 2°C in spring and a range of 4°C to 13°C in the summer (Figure 4). For all three lakes the surface and top half of the lake remained close to 0°C and warmed near the bottom in spring. In summer, surface temperatures ranged between 10°C and 13°C, and in the deeper lakes (i.e. Middle and Kuptan), decreased to a minimum of 4°C with depth. In Capron Lake, summer profiles indicated a well-mixed
! ! 57! water column at 13°C which is warmer than the upper limits in both Middle and Kuptan at
10°C and 11°C, respectively. Not enough data loggers were deployed to accurately determine if a thermocline was present. However, high Arctic lakes of these depths do not usually hard-stratify due to long period of ice cover and high winds causing continuous mixing.
! ! 58!
Figure 4. Temperature profiles of Capron (top, black), Kuptan (middle, red) and Middle
(bottom, green) lakes on Banks Island NT in summer 2011 (solid line; no ice) and Spring
2012 (dashed line; full ice cover). Temperature loggers were set at the deepest point in each lake (bottom, 2/3 maximum depth, 1/3 maximum depth, and just below the ice surface
(spring) or water (summer). Open squares on the profile curves for each temperature logger depth.
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2.3.2.5 Water Quality
All local experts (n=18, Table 2) shared their perspectives that lake water quality in all seasons had not changed within the study lakes over their lifetimes based on their observations of clarity and taste. Andy Carpenter summarized this knowledge well, “I don’t notice a difference in the water, it is hard to tell, [because] in the summer it is always pretty clear”. Laboratory analyses of water quality (see Table 3 for trace metals; Table 4 for nutrients and chemistry) found that Capron Lake differed from Middle and Kuptan lakes with generally lower concentrations of common ions (i.e. Ca, Cl, Mg, Na, K, S, Sr) leading to lower hardness, conductivity and TDS. Chlorophyll a was below detection limits. Trace metals were generally below or near detection limits. For example, mercury if present, was not detectable. Nutrients (i.e. various forms of nitrogen and phosphorus) were also below detection limits in all lakes. Statistical comparisons among at least two of the three lakes was possible for Ba, Ca, Fe, Mg, K, Na, and Sr. One-way ANOVAs (F2,5) with post-hoc
Tukey tests (adjusted p-values reported here) revealed several significant differences:
Capron Lake exhibited a significant difference from Middle and Kuptan lakes for Barium
(p<0.0005), Calcium (p<0.0005), Magnesium (p<0.0001), Potassium (p<0.005) and
Strontium (p<0.001); and Sodium was significantly different among all three lakes
(p<0.005 for all three).
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Table 3. Trace metal concentrations (mg/L) in water quality samples collected from 2008 to 2011 in Middle, Kuptan and Capron
Lakes on Banks Island NT. (Note: “<” denotes that the concentration is below the detection limit of the analysis.)
Parameters Middle Lake Kuptan Lake Capron Lake
Season of Summer Summer Winter Summer Summer Summer Winter Summer Summer Winter Summer Collection Date of Aug. 10, Jul. 16, Mar. 21, Aug. 8, Aug. 27, Jul. 26, Mar. 17, Aug. 12, Aug. 17, Mar. 23, Aug. 4, Collection 2008 2009 2010 2011 2008 2009 2010 2011 2008 2010 2011 Aluminum <0.005 <0.005 <0.005 <0.01 <0.005 0.0063 <0.005 <0.01 <0.005 <0.005 <0.01 Antimony <0.002 <0.0004 0.00047 <0.0004 0.0003 <0.0004 <0.0004 <0.0004 <0.0002 <0.0004 <0.0004 Arsenic 0.006 0.00044 0.00077 <0.0004 0.0007 0.00049 0.00143 <0.0004 0.0002 0.0007 <0.0004 Barium 0.052 0.0479 0.0716 0.0483 0.064 0.0578 0.072 0.0598 0.011 0.0156 0.0154 Beryllium <0.0001 <0.001 <0.001 <0.001 <0.0001 <0.001 <0.001 <0.001 <0.0001 <0.001 <0.001 Bismuth <0.0005 - - - <0.0005 - - - <0.0005 - - Boron 0.022 <0.05 <0.05 <0.05 0.021 <0.05 <0.05 <0.05 0.006 <0.05 <0.05 Cadmium <0.00001 <0.00005 <0.0001 <0.00005 <0.00001 0.00001 <0.00006 <0.00005 <0.00001 <0.00001 <0.00005 Calcium 36.2 35.9 55.1 34.0 36.1 38.5 42.8 33.6 15.2 20.9 15.8 Chromium <0.005 - 0.0017 <0.005 <0.0005 <0.005 0.0011 <0.005 <0.0005 <0.001 <0.005 Cobalt <0.0001 <0.002 <0.002 <0.002 <0.0001 <0.002 <0.002 <0.002 <0.0001 <0.002 <0.002 Copper <0.001 <0.001 0.0086 <0.001 <0.001 <0.001 0.0222 <0.001 <0.001 <0.001 <0.001 Iron <0.05 <0.03 <0.03 0.025 <0.05 <0.03 <0.03 0.013 <0.05 <0.03 0.013 Lead 0.0001 <0.0001 0.00049 0.00028 0.0001 <0.0001 0.00148 0.00012 <0.0001 0.00054 0.00013 Lithium 0.004 <0.01 <0.01 <0.01 0.004 <0.01 <0.01 <0.01 0.002 <0.01 <0.01 Magnesium 18.2 18.7 28.4 17.5 17.1 16.5 21.2 17.0 8.1 11.4 8.59 Manganese <0.005 <0.005 <0.005 <0.002 <0.005 <0.005 <0.005 <0.002 0.006 <0.005 0.0062 Mercury - <0.00002 <0.00002 <0.0001 - <0.00002 <0.00002 <0.0001 - <0.00002 <0.0001 Molybdenum 0.003 <0.005 <0.005 <0.005 0.002 <0.005 <0.005 <0.005 <0.001 <0.005 <0.005 Nickel 0.0006 <0.002 <0.002 <0.002 <0.0005 <0.002 <0.002 <0.002 <0.0005 <0.002 <0.002 Phosphorus - - 0.02 <0.02 - - <0.02 <0.02 - <0.02 <0.02 Potassium 1.2 1.32 1.74 1.16 1.2 1.14 1.18 1.16 0.6 0.7 0.78 Selenium <0.0002 0.00099 0.00053 <0.0004 0.0003 <0.0004 <0.0004 <0.0004 <0.0002 <0.0004 <0.0004 Silicon 0.8 - - - 0.73 - - - 0.5 - - Silver <0.00001 <0.0001 <0.0001 <0.0001 <0.00001 <0.0001 <0.0001 <0.0001 <0.00001 <0.0001 <0.0001 Sodium 26.9 26.3 39.2 26.5 24.7 23.8 28.7 24.3 2.4 2.9 2.3 Strontium 0.097 - 0.131 0.0904 0.093 - 0.105 0.0866 0.025 0.0294 0.0242
! ! 61!
Parameters Middle Lake Kuptan Lake Capron Lake
Season of Summer Summer Winter Summer Summer Summer Winter Summer Summer Winter Summer Collection Date of Aug. 10, Jul. 16, Mar. 21, Aug. 8, Aug. 27, Jul. 26, Mar. 17, Aug. 12, Aug. 17, Mar. 23, Aug. 4, Collection 2008 2009 2010 2011 2008 2009 2010 2011 2008 2010 2011 Sulphur 9 - - - 6.4 - - - 2.9 - - Thallium <0.00005 <0.0001 <0.0001 <0.0001 <0.00005 <0.0001 <0.0001 <0.0001 <0.00005 <0.0001 <0.0001 Tin <0.001 <0.05 <0.05 <0.05 <0.001 <0.05 <0.05 <0.05 <0.001 <0.05 <0.05 Titanium 0.001 <0.001 <0.001 <0.001 0.0008 <0.001 <0.001 <0.001 0.0005 <0.001 <0.001 Uranium 0.0016 0.00106 0.00172 0.00111 0.001 0.00075 0.00103 0.00077 <0.0005 <0.0001 <0.0001 Vanadium 0.0002 <0.001 <0.001 <0.001 0.0002 <0.001 0.001 <0.001 0.0001 <0.001 <0.001 Zinc 0.002 <0.004 0.0144 <0.004 0.003 <0.004 0.007 <0.004 0.003 <0.004 <0.004 Zirconium <0.001 - - - <0.001 - - - <0.001 - -
!
! ! 62!
Table 4. Lake water nutrients and chemistry data collected in winter 2010 and summer 2011 in Middle, Kuptan and Capron lakes on Banks Island NT. (Note: “<” denotes that the concentration is below the detection limit of the analysis.)
Parameter Measured Middle Lake Kuptan Lake Capron Lake Season of Collection Units Winter Summer Winter Summer Winter Summer Date of Collection Mar. 21, 2010 Aug. 8, 2011 Mar. 17, 2010 Aug. 12, 2011 Mar. 23, 2010 Aug. 4, 2011 Alkalinity (Total as CaCO3) mg/L 178 125 144 129 85 62.6 Ammonia-N mg/L <0.005 <0.050 0.0062 <0.050 <0.005 <0.050 Bicarbonate mg/L 217 - 174 - 104 - Carbonate mg/L <5 - <5 - <5 - Chloride mg/L 71.9 - 53.4 - 5.73 - Chlorophyll a µg/L - <0.010 - <0.010 - <0.010 Conductivity µS/cm 643 - 494 - 211 - Dissolved Calcium mg/L 52.5 - 43.8 - 21.6 - Dissolved Magnesium mg/L 26.8 - 21.1 - 11.9 - Dissolved Potassium mg/L 1.86 - 1.47 - 0.8 - Dissolved Sodium mg/L 38.2 - 29.2 - 3.3 - Fluoride mg/L 0.09 - 0.067 - <0.05 - Hardness (as CaCO3) mg/L 241 - 196 - 103 - Hardness total Ca and Mg mg/L 255 - 194 - 99.1 - Hydroxide mg/L <5 - <5 - <5 - Ion Balance % 102 - 109 - 105 - Nitrate mg/L <0.05 <0.050 <0.05 - <0.05 <0.050 Nitrate + Nitrite mg/L <0.071 <0.071 <0.071 - <0.071 <0.071 Nitrite mg/L <0.05 <0.050 <0.05 - <0.05 <0.050 pH pH 8.2 - 8.29 - 8.02 - SAR SAR 1.07 - 0.9 - 0.12 - Sulfate (SO4) mg/L 38.1 - 21.7 - 12.2 - TDS (Calculated) mg/L 336 - 257 - 107 - Total Dissolved Solids mg/L 350 241 238 237 110 77 (TDS) Total Kjeldahl Nitrogen mg/L <0.2 <0.2 <0.2 - <0.2 <0.2 Total Nitrogen mg/L <0.20 <0.21 <0.20 0.28 <0.20 <0.21 Total Solids mg/L - 252 - - - - Total Suspended Solids mg/L - <3.0 - - - -
! ! 63!
2.3.3 Arctic Char Condition and Diet
Local experts provided IKO on char condition and diet (Table 5), focused on fish over a specific minimum size required for consumption (>~25 cm in total length).
Table 5. List of topics of Inuvialuit knowledge and observation regarding Arctic Char qualitative condition and diet and number of Sachs Harbor NT local experts reporting observation (local experts interviewed n=18).
Thematic codes List of topics of Inuvialuit knowledge and observation of Number of of Arctic Char Arctic Char qualitative condition and diet interviewees condition and reporting diet observation (n = total number of interviewees who provided IKO for thematic code)
CONDITION •! “Healthy” fish = plump, free of abnormalities, firm flesh 18 (QUALITATIVE) “Unhealthy” fish = thin for their length, and/or (n=18) abnormalities, and/or soft flesh •! On average Arctic Char condition did not drastically 14 change over time and char generally healthy in all study lakes •! Fish are skinnier in some years, depends on weather, 3 warm summer = more bugs for them to feed on •! Fish in some lakes are healthier than others, Middle Lake 2 fish are less healthy •! Middle Lake Arctic Char are becoming less plump since 4 ~1999 and even thinner leading up to ~2006-2009 including fish captured in spring summer and fall, however no thin Arctic Char harvested in Middle Lake in 2014; Lake Trout longer in 2008 (linked to warmer weather) •! Big “healthy” char in Capron Lake (fat for their length) 2 FLESH (MEAT) •! Spring/early summer (July) fish flesh is pale 1 COLOUR (n=9) •! Fish from different lakes have different colours, some are 4 orange or red, others pale •! Prey items and quantity can affect colour of char meat, 5 lakes with lots of “shrimp” (amphipods) have fish with red meat •! Char and trout that feed on zooplankton have red flesh 3 DEFORMITIES •! Past several years deformities have been increasing in 3 (n=4) Middle and Kuptan lakes, in addition to non-study lakes •! Fish develop deformities (e.g. crooked spine) when lake 1 is not fished for a while due to over-crowding, once lake is fished fish go back to normal
! ! 64!
DISEASES •! Have not observed fish diseases, lake fish are healthy 5 (n=7) •! Started observing sores on surface of char, started 2 ~1980’s LUMPS OR •! Started observing fish with cysts (fluid-filled sacs or 3 CYSTS bumps) near backbone and in meat ~2003, fishers throw (n=3) these fish back into lake because they don’t want to consume them •! Observed increase in small lumps (made of tissue) in 1 char starting in early to mid 2000s
PARASITES •! No increase in parasites (all fished lakes) 1 (n=6) •! Increased parasites in char, did not see any when younger 3 (30 years ago or longer), seeing more since 2000-2003 (all lakes fished) •! Fish in Middle Lake have increased numbers of “white 3 balls” [encapsulated tapeworm] than in other lakes, however few seen in 2014 •! Fish in lakes connected to the ocean are “cleaner” (less 1 parasites) TASTE •! Fish from different lakes taste different 5 (n=6) •! Fish in Capron Lake taste better because they are “fattier” 2 •! Fish in Middle Lake taste like moss 2 •! In smaller lakes fish taste like moss 2 •! In years when fish are less plump, due to cooler weather, 1 they taste different, taste depends on the bugs on which they feed DIET •! Have not observed changes to Arctic Char diet over time 9 (n=12) •! Char consume anything 3 •! “Bugs” (aquatic emergent insects) in lakes; bugs (insects) 7 from land flowing in from ephemeral melt or rainfall creeks; including emerging mosquitoes (Culicidae), blackflies (Simuliidae) and midges (Chironimidae), and caddisflies (Trichoptera) •! “Shrimps” (amphipods) 6 •! “Minnows” (all fish smaller than ~20-25cm of any 6 species) •! “Weeds” (macrophytes) and moss 2 •! “Tiny red dots” (zooplankton) 3
2.3.3.1 Qualitative Analysis of Arctic Char Condition
Elder Geddes Wolki shared that “char from Capron Lake are really big and really good to eat”. Upon requesting what was meant by this, he explained there are very long char in Capron Lake, that were fat for their length, and had a better flavour than those from
Middle and Kuptan lakes because they tasted fatty. According to IKO, “healthy” char –
! ! 65! and the ones most coveted for eating – were those that were plump for their length
(n=18/18, Table 5). When assessing the qualitative condition of the char, reports from local experts focused on girth and other “healthy” traits indicated by the absence of deformities, disease, lumps or cysts, and flesh colour, texture and flavour. A firm flesh also indicated a healthy char. Flesh colour of char varied from pale white-orange to “dark red” (a deep red- orange) (n=4/18, Table 5).
The majority of local experts (n=14/18, Table 5) explained that char qualitative body condition did not change much from year to year and that char were very healthy in the three study lakes. Local experts explained that when char annual qualitative char condition changed (e.g. from thin to plump, or vice versa) there were no patterns or trends observed as to the years (e.g. every set number of years) when this would occur. For example, Donna Keogak who regularly fished Middle Lake, reported that the char have been skinnier since 1999, and even skinnier in the years leading up to 2009, however, in
2014 she reported no skinny char were caught. However, while not necessarily following a trend over decades, shifts in the plumpness of char were reported to be predictable based on weather conditions in a given year as noted by three local experts (Table 5). This was explained by Elder Edith Haogak (with a translator), “it changes over the years so [char] gets skinnier, fatter, skinnier, fatter and this depends on the weather and the bugs, so how much food [the fish] have...the bugs follow the weather. When it’s a long, warm summer, then all those bugs are plentiful on the water, and then the fish eat well. And if it’s a bad summer, say a cold summer, then there’s not much of that food for the fish. So, those would be the leaner years.”
! ! 66!
Additional IKO of qualitative condition of the char was shared by five local experts who had not noticed changes in regards to fish diseases (n=5/7, Table 5). Two local experts
(n=2/7, Table 5) observed that fish in some lakes were healthier than others, and that specifically char in Middle Lake were considered less healthy than in the other lakes. Elder
Lena Wolki reported that in fished lakes she had observed, “sometimes inside the stomach they have little lumps…on the little skinny [fish] in the little lakes [they’re] full of lumps…
[there have been] a little more…[since] just a few years ago”. Observations of deformities
(n=4/18, Table 5) appear to have been increasing in Middle and Kuptan lake fish, along with an increase in reports of cysts (n=3/18, Table 5) in the meat and near the backbones, starting around 2003. “[We are] finding the fish [with] the cysts around their back, around their backbone…and inside the meat…[since] five, six years ago. We started seeing more and more of them. I never used to see them when I was young…we’re starting to notice some sick fish…we don’t eat those. We just throw those away right away” (Donna Keogak).
Two local experts (n=2/7, Table 5) reported that they started seeing sores on the flesh as of the 1980s which they had not seen before. Despite this, the majority of char caught today were considered healthy and good for human consumption.
2.3.3.2 Quantitative Analysis of Arctic Char Condition
To quantitatively assess char condition over the multi-year survey, Arctic Char were sampled from all three lakes including 103 fish from Capron, 98 from Kuptan and 356 from
Middle. Only one sampled Arctic Char had a cyst out of all the fish sampled and no diseases, deformities, or lumps were observed. From the ten largest sampled char in each lake across all survey years, it appeared that Capron Lake char were generally longer than the other two lakes (Figure 5). However, these differences were not significant among all
! ! 67!
three lakes (ANOVA, F2,27=2.64, p=0.09) and a more detailed examination of the data confirmed that the higher maximum length in Capron was influenced by two particularly long char.
A general additive statistical model of length-weight relationships for Arctic Char on Banks Island yielded a significant interaction term for lakes (p<0.0001) and the log- transformed linear regression gave an exponent greater than 3. An ordinary least squares regression of quantitative fish condition (Fulton’s K) with fish length (FL, in mm) yielded a significant and positive relationship for only Capron Lake (K = 0.0004 FL + 0.78, r2 =
0.38, p<0.05). This indicated that Capron Lake Arctic Char grow relatively fatter as they age, therefore this justified that a size subset is appropriate for comparing fish condition across lake (i.e. fish with a length greater than 250 mm; Froese 2006) (see Figure 6 for sample sizes). Arctic Char caught in Capron Lake were in significantly higher condition than those in the other two lakes (Figure 6; ANOVA, F2,259=23.03, p<0.00001; Tukey post- hoc pairwise comparisons with adjusted p-values are p<0.0001 for Capron-Middle, p<0.0001 for Capron-Kuptan, and p=0.08 for Middle-Kuptan).
! ! 68!
!!
Figure 5. The ten largest fish caught in Middle (green), Kuptan (red) and Capron (black) lakes on Banks Island NT across all survey years (Capron Lake 2008, 2010, 2011; Kuptan
Lake 2009, 2011; Middle Lake 2008, 2009, 2011).
Figure 6. Condition of Arctic Char in Capron (black; n=62), Kuptan (red; n=89) and
Middle (green; n=138) lakes on Banks Island NT calculated using Fulton’s K.
Pooling all lake samples together, approximately 20% of all individuals sampled were mature and in running ripe (spawning) condition, whereas 60% of individuals caught
! ! 69! were mature and in resting condition, 19% were immature, and 1% were unknown. There was no significant difference in Gonado-Somatic-Indices among lakes, rather GSI was significant only between sexes (Figure 7; ANOVA, F1,36=19.92, p<0.0001).
Figure 7. Gonado-Somatic Indices of running ripe Arctic Char for male (left) and female
(right) char in Capron (black; n♂ = 9; n♀ = 1), Kuptan (red; n♂ = 20; n♀ = 7) and Middle
(green; n♂ = 14; n♀ = 6) lakes on Banks Island NT.
2.3.3.3 Qualitative Analysis of Arctic Char Taste in Relation to Diet
Nearly one third of the local experts interviewed (n=5/18, Table 5) reported Arctic
Char from different lakes taste different. A few local experts (n=3/18) observed differences in the taste of Arctic Char among the study lakes despite their proximity (the two furthest study lakes, Capron and Kuptan, are 32.02 km apart). Elders Roger Kuptana and Geddes
Wolki both noted that Arctic Char tasted the best from Capron Lake out of the three study lakes. ‘Tastiness’ was assessed based on general flavour as well as the richness or fattiness of the flesh. The colour of the flesh was also observed to be noticeably different among the lakes with Capron Lake Arctic Char having brighter red orange meat and Middle Lake char flesh being pale (n=5/18, Table 5).
! ! 70!
However, because a clear explanation could not be drawn as to why lakes in such close proximity would produce fish with such differences in taste and colour, the local experts who noted this were approached again to further explore potential explanations.
Upon further investigation into the IKO, it was suggested by several local experts that a potential cause for the differences in the taste and flesh condition (n=9/18, Table 5) of
Arctic Char among the three lakes was due to prey availability and diet (n=12/18, Table 5).
These local experts also explained that prey consumed could affect the colour of the meat.
For example, the meat can become red in Arctic Char that consume amphipods (n=5/18,
Table 5) and Lake Trout that consume zooplankton (n=3/18, Table 5).
Elders John (Sr.) and Samantha Lucas had observed that in lakes nearby the study locations, “Mostly the [fish] we catch, they have small fish in their stomachs. Not as much as the smaller lakes, you know the smaller lakes have them amphipods. Some lakes, you know, you could notice the taste of the fish. They’re more mossy, than the bigger lakes. The bigger lakes you don’t taste moss or anything, but the small ones you could taste a lot of moss. And [when] they’re really fat, and they have a lot, some of these little ‘worms’
[amphipods] that they eat…Usher Lake, got beautiful different kind of char. Really red char.
[We have seen them eating] just like ‘shrimp’…what do you call them…amphipods, yeah a lot…lots in the lake. When you pull one [char] out, they eat so much, crowds their stomach and they all come out…and some lakes have more [amphipods].” Other local experts observed that in Middle Lake – a big lake with shallow areas – Arctic Char tasted like moss
(n=2, Table 5) and this was of note as it was not always a preferred flavour.
It was also noted that there are “lots of ‘freshwater shrimp’ [amphipods] in Capron
Lake” (Elder Geddes Wolki). Geddes Wolki also shared “…the chars they get really fat,
! ! 71! they eating shrimps [amphipods]. They get more red, just like the flesh…they get fat and taste really good…In the fall I always go to Capron Lake, just red flesh, eating shrimps…Every lake that got shrimps, they got the best fishes, those lakes. Their flesh get red, that's from shrimps [amphipods]…from their food.” “Some lakes you could get some really nice char, red. When you’re jiggling in the fall time, you know the ice is not really thick, once you start pulling them up…when they get close, you could just see them down there because they’re so red, the char [because they are eating amphipods], yeah very healthy fish” (Elder John Lucas Sr.). No SEKO was collected or available pertaining to the flavour or colour of flesh (meat) in the three study lakes, however SEKO for diet composition and prey (zooplankton) availability was collected and analysed.
2.3.3.4 Qualitative and Quantitative Analyses of Arctic Char Diet
The majority (n=12/18, Table 5) of local experts observed char eating “little fish or minnows” (fish smaller than the size required for consumption, ~25 cm), “tiny red dots”
(zooplankton), “little bugs” (insects) from the land and in the water, “freshwater shrimp”
(amphipods), moss, and “weeds” (macrophytes). A few local experts (n=3/18, Table 5) noted char will “eat anything” and sometimes their stomachs are empty when they don’t have anything to eat. Elder Edith Haogak (communicating with the assistance of a translator) knew that “the fish depend on the ‘bugs’…sometimes they get skinnier, maybe because of lack of food. It was always different – sometimes they’d be skinny, and then they’d taste different”. Edith Haogak also explained she had “seen fish ‘hunting’ blackflies and mosquitoes when they are surfacing and eating the flies in the air too, when they are in swarms.”
! ! 72!
The difference in diet affecting the flavour of the char determined through the analysis of the IKO led to further quantitative investigation examining the stomach contents of sampled Arctic Char. Over 85% of the Arctic Char stomachs subsampled in the laboratory from all three lakes were full of prey items at various stages of decomposition indicating the char were actively feeding at the time of capture. Arctic Char diets varied among lakes. The main diet item in both field (Figure 8; see methods for in-field diet categorization) and laboratory expert identification was Insects. In the laboratory-analyzed subsamples, the majority of insects consumed by char in all lakes were Dipteran pupae and larva (see Table 6 for taxonomic identification of invertebrate prey including life stages from the subsample of char stomach contents). Middle Lake char stomachs (n=16) contained a smaller prey item abundance (Wilcoxon Rank Test, p<0.0001) than the other two lakes (e.g. Diptera was most common prey in all three lakes; 1.8, 62.9 and 97.3 average
Dipteran prey items per char stomach for Middle, Kuptan and Capron lakes, respectively); however, no significant difference was found between the char stomach contents in Kuptan
(n=8) and Capron (n=20) lakes. Capron Lake char also consumed Amphipods, Plants and
Fish Eggs, whereas in Middle and Kuptan lakes, the secondary prey items were
Zooplankton and Plants (aquatic and terrestrial detritus) (Figure 8).
! ! 73!
Figure 8. Proportions of diet items found in Arctic Char stomachs during 2008-2012 in- field analyses in Capron (n = 57; 9 empty stomachs), Kuptan (n = 88; 1 empty stomach) and Middle (n = 127; 16 empty stomachs) lakes on Banks Island NT.
! ! 74!
Table 6. The taxonomic identification of invertebrate prey species (excluding zooplankton) found in Arctic Char stomach samples from Middle (n=9), Kuptan (n=12) and Capron (n=38) lakes on Banks Island NT in 2011.
Superfamily/ Middle Kuptan Capron Class Order Suborder Subfamily Genus Species Life stage Family Lake Lake Lake Bivalvia Sphaeriidae adult X Insecta Diptera adult X Brachycera adult X Heliomyzidae adult X Tachinidae adult X Nematocera Chironomidae adult X X Chironominae Chironomini larvae X pupae X Corynocera ambigua larvae X Glyptotendipes larvae X Heterotanytarsus pupae X Micropsectra pupae X Paratanytarsus pupae X Sergentia pupae X Tanytarsini pupae X X Tanytarsus pupae X Zavreliella pupae X Diamesinae Protanypus larvae X Pseudodiamesa larvae X arctica larvae X X X Orthocladiinae pupae X X X Abiskomyia larvae X Brillia pupae X Cricotopus larvae X pupae X Heterotanytarsus pupae X Heterotrissocladius larvae X Oliveridia larvae X
! ! 75!
Superfamily/ Middle Kuptan Capron Class Order Suborder Subfamily Genus Species Life stage Family Lake Lake Lake pupae X X Orthocladius pupae X larvae X Paracladius larvae X X pupae X X Parakeiferriella larvae X Paraphaenocladius larvae X Tanypodinae pupae X Procladius larvae X Hymenoptera adult X Tenthridoidea adult X Braconidae adult X Ichneumoidea adult X Lepidoptera adult X Pieridae adult X Plecoptera Baetidae Baetis bundyae adult X Trichoptera Apatanidae Apatania adult X larvae X pupae X X X Limnephilidae adult X pupae X Grensia praeterita larvae X Nematoda X
! ! 76!
A significant level of diet overlap (i.e. at a p-value < 0.05) using Schoener’s Index
(SI) was found only between Middle and Kuptan lakes (SIobserved = 0.58, randomized SI95%
= 0.46), whereas no significant overlap was found between Capron and Kuptan lakes
(SIobserved = 0.32, randomized SI95% = 0.45) or Capron and Middle lakes (SIobserved = 0.45, randomized SI95% = 0.48). Although amphipods were not noted in the in-field analysis of prey items in chars from Middle and Kuptan lakes, the laboratory analysis identified amphipods within Kuptan Lake stomach contents. While they were not a dominant prey item, it is worth noting that fish remains were found in two Middle Lake char stomachs.
Further, in Capron Lake, the stomachs from the largest fish generally contained amphipods and fish eggs.
Zooplankton as a potential prey item of Arctic Char, was also examined. Three local experts provided observations on zooplankton (Table 5). In their discussions on zooplankton, John and Donna Keogak explained that there are “little red bugs, like tiny…bright red dots [in the water] …that’s why I think, how come a lot of the fish [meat] turns red, because of all of that [zooplankton]”. Zooplankton samples from all three lakes contained similar species (Table 7), however, the dominant species and general biomass characteristics differed among all three lakes. In Capron Lake, both Calanoid spp. and
Cyclopid spp. copepodids were the most dominant taxa, followed by much higher densities of Leptodiaptomus sicilis than in the other two lakes. In Kuptan Lake Calanoid spp. copepodids were dominant, however, Cyclops strenuous also occurred in higher densities than in the other two lakes and the only samples of Limnocalanus macrurus were found in
Kuptan Lake. In Middle Lake, all zooplankton densities were generally low (i.e. 17% and
4% of the densities of Kuptan and Capron, respectively), although it contained the highest
! ! 77! species richness with populations of Bosmina longirostris and Diacyclops bicuspidatus thomasi. Mean biomass (sample mean, µ; with standard deviations, σ) averaged across the two samples collected from each lake was highest in Capron Lake (µ=50.3 mg/m3, σ=2.8) followed by Kuptan Lake (µ =14.7 mg/m3, σ = 6.7), and lowest in Middle Lake (µ=3.1 mg/m3, σ=1.7). Capron Lake zooplankton biomass was significantly higher than Middle
Lake (Tukey adjusted p<0.01) and Kuptan Lake (Tukey adjusted p<0.05), while there was no significant difference between Kuptan and Middle lakes. Further, Capron Lake contained higher biomasses of the dominant larger-bodied zooplankton (e.g. D. longiremis,
L. sicilis and C. strenuous) than the other two lakes. However, L. macrurus was the largest zooplankton species in the samples, but only found in Kuptan Lake and overall at relatively low densities (see Table 7 for zooplankton densities and average weight of each species).
!
! ! 78!
Table 7. Summary of zooplankton average species densities (#/m3) and average weight
(µg) in the three study lakes on Banks Island NT from two plankton tows from each of
Kuptan and Middle lakes, and one plankton tow from Capron Lake. (Note: “N/A” refers to an undetected species.)
Zooplankton
Species thomasi Lake Cyclops strenuusCyclops Daphnia longiremis Cyclopid copepodids Cyclopid Calanoid copepodids Calanoid Bosmina longirostris Leptodiaptomus sicilis Leptodiaptomus Diacyclops bicuspidatus Diacyclops Limnocalanus macrurusLimnocalanus Zooplankton Density (#/m3)
Capron Lake 157.8 N/A N/A 960.4 615.9 N/A 8967 6782.7
Kuptan Lake 3.6 N/A 3.6 145.1 924.5 N/A 2220.6 254.7
Middle Lake 0.6 0.2 N/A 29.6 500.9 0.4 71 14.1
Zooplankton Average Weight (µg)
Capron Lake 4.76 N/A N/A 6.66 7.35 N/A 2.31 2.21
Kuptan Lake 9.99 N/A 28.49 7.37 6.20 N/A 3.30 1.23
Middle Lake 8.94 6.26 N/A 7.39 5.16 4.96 3.94 1.85
2.3.3.5 Qualitative and Quantitative Analyses of Arctic Char Parasites
Local experts explained they were not aware of parasites because they had not looked for them before as they thought it was off-putting due to the fact they consume the char and usually throw away the guts. However, a few local experts knew about the presence of parasites (n=4/6, Table 5) through observing “white balls” or a worm in the
! ! 79! guts of the fish. The white balls were determined to be encapsulated tapeworms of the genus Diphyllobothrium through further discussion with these local experts and examination of photos of common northern fish parasites from Stewart and Bernier (1999).
Once confirmed that these observations were indeed a type of parasite, these three local experts could provide information over the course of their lifetime on the amount of the white balls in char, and shared there was an increased number of char in Middle Lake with encapsulated tapeworms than in chars from the other two study lakes. However, there were fewer char with this parasite in Middle Lake in 2014. Also, a few (n=3/18, Table 5) local experts described seeing more white balls since 2000-2003, or since they were younger
(~30 years ago (since ~1986), in all fished lakes.
In-field estimates of parasite loads were verified by comparing them to in- laboratory gut parasite counts from 48 char guts collected from all three lakes in 2011. A one-way ANOVA found that the qualitative groupings from in-field load estimates (i.e.
None, Low, Medium or High) were accurately characterized by in-laboratory parasite counts (F3,43=7.35, p<0.001), although it was noted using post-hoc Tukey comparisons only between Low and Medium, and Low and High, comparisons were significantly different with adjusted p-values less than 0.005 and 0.0001, respectively.
Parasite loads using the in-field scale were highest in Middle Lake, in which almost half of all 138 char sampled had High loads, and combined with Medium loads included over 80% of the sampled fish (Figure 9). In Kuptan Lake, High loads were found in nearly a quarter of the 90 sampled char, and with Medium loads comprised over 60% of the samples. The 62 sampled char from Capron Lake exhibited much lower parasite loads such that High and Medium loads combined were found in only 13% of the sample. Chi-squared
! ! 80! pairwise tests conducted among all lake pairs indicated that char populations from all lakes had significantly different proportions of parasite loads (p < 0.0001).
Figure 9. Proportion of Arctic Char containing None, Low, Medium and High (dark to light; see Methods for grouping criteria) parasite loads in Capron, Kuptan and Middle lakes on Banks Island NT based on in-field visual-assessment results. The width of the bars represents the relative sample size among lakes (Capron Lake n=62, Kuptan Lake n=90,
Middle Lake n=138).
In all three lakes, the most common parasite within gut and flesh samples identified in-laboratory was Diphyllobothrium sp. (likely D. ditremum or D. dentriticum), a tapeworm, in both the free moving plerocercoid form and as encapsulated cysts (white balls local experts were observing). Other gut parasites included Eubothrium salvelini (a pseudophyllidean tapeworm) and Echinorhynchus salmonis (a spiny-headed worm) (Table
8). The gill parasite Salmincola sp. (likely S. edwardsii), included in the in-field assessment, was found in char from all three lakes. Gill parasites were not identified in-
! ! 81! laboratory, however, the in-field visual load assessment for this species mirrored the gut results such that they were found in 4%, 2% and 0% of sampled fish in Middle, Kuptan and
Capron lakes, respectively.
Table 8. Summary of average counts of gut and flesh parasite species identified in- laboratory in the three study lakes on Banks Island NT (Capron Lake n=12, Kuptan Lake n=19, Middle Lake n=17).
Lake Count of Encysted Free plerocercoid Eubothrium Tapeworm Echinorhynchus parasite plerocercoid (Diphyllobothrium salvelini Segments sp. specimens (Diphyllobothrium sp.) sp.) Capron 15.25 5.92 3.25 0.17 1.00 4.83 Kuptan 30.47 20.16 8.74 0.11 0.21 1.26 Middle 29.65 22.76 6.76 0.00 0.00 0.00
2.3.3.6 Quantitative Analyses of Arctic Char Condition and Parasite Abundance
A t-test of presence (n = 261 char) or absence (n = 28 char) of parasites on body condition using all pooled field assessment data across lakes and years revealed a significant difference (t=3.9, df=31, p<0.001) and an 8% reduction in quantitative body condition with the presence of parasites. Using all in-field parasite load data, a two-factor
ANOVA revealed significant Lake (F2=16.4, p<0.0001) and Parasite Load (F3=10.7, p<0.00001; Figure 10) effects on quantitative body condition. Although, it was noted using
Tukey post-hoc comparisons that while having no parasites was significant in all comparisons (adjusted p-value < 0.01), the difference between having low and medium parasite loads was only weakly significant (adjusted p-value = 0.055) and there was no significant difference in fish condition among medium and high parasite loads, or even low and high parasite loads.
! ! 82!
Figure 10. Body condition (i.e. Fulton’s K) of Arctic Char pooled from Capron, Kuptan and Middle lakes on Banks Island NT at None, Low, Medium and High parasite loads.
2.3.4 Triangulation of Knowledge Bases
Triangulation of the information generated in the qualitative and quantitative methods of this study was conducted across two scales of the knowledge bases: at the spatial scale (lake) and conceptual scale (elements of habitat that influence char condition)
(Table 9). Although ecological parameters and associations influencing char condition are assumed to be important over time, triangulation of information at the same temporal scale was not possible for trends over time as the IKO was developed over the course of several decades, whereas the SEKO was specific to a five-year period. Condition of char based on deformities, diseases, lumps, and cysts could not be triangulated because the IKO provided had no conceptual or spatial information. Only temporal IKO as to changes to these conditions over several decades was provided, and no SEKO at an equivalent time scale was available.
! ! 83!
Table 9. Matrix triangulating Inuvialuit knowledge and observation and Scientific ecological knowledge and observation results for Arctic Char condition, diet, and lake habitat on Banks Island NT.
Parameter Inuvialuit Knowledge Scientific Ecological Results of and Observation Knowledge and Knowledge Base (IKO) Observation (SEKO) Comparisons
Lake Habitat Allochthonous Input •!Fish always eating at •!No SEKO available IKO Enriches first creeks flowing Lack of SEKO through candle ice in spring and summer •!Less snow to provide flow to these creeks Fish Species in Study •!Arctic Char •! Arctic Char in all three Knowledge Bases Lakes •!Lake Trout lakes Corroborate •!“Minnows” (all small •! Lake Trout in all three fish) lakes •!One person knew of •! Ninespine Sticklebacks Sticklebacks in lake ice observed in Capron Lake puddles on Middle Lake •! One Least Cisco caught in Capron Lake Lake Bottom •! Middle Lake has mossy •!Sand and moss in stomach Knowledge Bases plants on bottom, deeper contents of char Corroborate areas of lakes do not •!Observed moss and have moss macrophytes in shallow •!Some areas of lakes areas of Middle Lake have sand, some have •!Observed sand, gravel and gravel, some have rocks rocks in shallow areas of lakes Lake Depth •! Capron Lake is shallow •! Capron Lake is shallow Knowledge Bases (Bathymetry) throughout throughout Corroborate •! Middle Lake is •! Middle Lake is extremely extremely deep in parts deep in parts •! Kuptan Lake depths are •! Kuptan Lake depths are in in between Capron and between Capron and Middle lakes Middle lakes Water Quality •!Water has always been •!Within normal parameters SEKO Enriches clear and potable in for the region understanding of lakes •!Total Dissolved Solids parameter •! Erosion has not (TDS) were within normal noticeably affected parameters for the region water clarity in study •!TDS, sodium and lakes strontium were higher in Middle and Kuptan lakes •!Low chlorophyll a in all three lakes
! ! 84!
Water Temperature •!Limited IKO available •!Comparable in all three SEKO Enriches •!Some observations of lakes and likely does not Limited IKO warmer surface waters affect fish habitat since ~1999-2001 in availability Middle Lake •!Annual temperatures in all three lakes ranged between 0-13ºC Arctic Char Condition and Diet
Condition based on •!“Big/healthy” char in •!Capron Lake char were Knowledge Bases size (body weight or Capron Lake [fat for significantly fatter (higher Corroborate width to length) their length] condition factor) than in •!Middle Lake has “less the other two lakes healthy” fish (skinny for •!Both Kuptan and Middle their length) lakes had char with lower condition factors Condition based on •!White balls on outside •!In all lakes most common Knowledge Bases parasites of guts and meat parasite was Corroborate for (determined to be Diphyllobothrium sp. parasite encapsulated tapeworms (tapeworm observed as Diphyllobothrium Diphyllobothrium sp.) “white balls in the guts” by sp. observed local experts) •!Higher amounts of these •!Other parasites identified SEKO Enriches white balls in Middle include: Eubothrium IKO for other Lake salvelini parasite species •!Other parasites were not (pseudophyllidean known through IKO tapeworm) and Echinorhynchus salmonis (thorny-headed worm) •!Middle Lake had the highest parasite loads of all three lakes Condition based on •!Skinnier fish taste •! No scientific sampling for IKO Enriches taste and colour of different than fatter fish taste or colour of meat SEKO for Colour meat •!Fish from different lakes •! The second most common and Taste of Meat have different coloured prey item in Capron Lake meat, some are really char was amphipods and Knowledge Bases orange and red while these were found in higher Corroborate for others are pale abundance in stomach possible •!Fish that eat “freshwater contents than in the other explanation of shrimp” (amphipods) two lakes differences in and zooplankton, have •! Middle Lake char had Colour and Taste tastier (“fatty” taste) and highest proportions of of Meat brighter colour meat moss and plants in their •!Fish in Capron Lake stomach contents taste better because “fattier” •!Fish in Middle Lake taste like “moss”
Diet •!Eats “bugs” from the •! Stomach content analyses Knowledge Bases land and water revealed adult and larval Corroborate forms of insects in all three lakes
! ! 85!
•!Hatching mosquitoes, •! Mosquitoes and blackflies blackflies, midges and not found in the subset of caddisflies Arctic Char stomachs •!“Freshwater shrimp” analyzed in the lab, but (amphipods) midges and caddisflies •!“Little red dots” were (zooplankton) •! Zooplankton •!“Weeds” (macrophytes) •! Moss and moss •! Fish •! Char eat “other fish” •! Capron Lake had the most •! Lakes that have lots of amphipods in the char “freshwater shrimp” stomach contents and (amphipods) had the significantly fatter fish best fish for eating (based on Fulton’s K) (plump char, e.g. Capron Lake) Zooplankton •!Limited Inuvialuit •!Zooplankton biomass was SEKO Enriches knowledge, local experts highest in Capron Lake, Limited IKO knew that char ate “little followed by Kuptan Lake, red dots that could be and lowest in Middle Lake seen moving in the •!Capron contained higher water” biomasses of the dominant larger-bodied zooplankton •! In Middle Lake all zooplankton densities were generally low, although it contained the highest species richness
For all 12 parameters (Table 9), the knowledge bases enriched or corroborated one another, and there were no instances where the knowledge bases contradicted or were inconsistent. For just over half of the parameters (n=7/12, Table 9), the knowledge bases corroborated one another.
2.4 Discussion
This study used a mixed methods approach to gain an understanding of the potential lake habitat drivers of Arctic Char condition in three lakes on Banks Island NT using both ecological and social science methods to collect and analyze scientific ecological knowledge and observation (SEKO) and Inuvialuit knowledge and observation (IKO).
Evidence for multiple ecological parameters ascertained from both SEKO and IKO were
! ! 86! found to play a potential role in the condition of Arctic Char and included allochthonous inputs, lake temperature regimes, lower trophic level diversity and productivity, and parasite loads. This study demonstrates the utility of combining two information sources to gain an improved understanding of the effects of lake habitat parameters on Arctic Char condition.
2.4.1 Lake Habitat
Allochthonous input was considered an important influencing parameter for Arctic
Char feeding by 27% of the local expert interviewees. Earlier lake ice breakup and delayed freeze-up could result in, among other changes, increased nutrient input from the lake catchment areas (Vincent et al. 2011). Lim et al. (2005) observed that Banks Island is an unusual setting in the Canadian Arctic Archipelago as its vegetation is considerably lusher than other islands and it is highly populated by wildlife, both of which could potentially affect limnological conditions through higher levels of allochthonous input. All of this suggests the need for further examination, using both IKO and SEKO, of the effects of allochthonous input on Arctic Char condition in the study area.
Regarding lake bathymetry, the IKO and SEKO knowledge bases corroborated one another in that Middle Lake had the greatest depths and Capron the shallowest (Figure 3).
IKO had limited information on changes to temperature throughout the water column of the lakes, although 33% of interviewed local experts observed that surface water temperatures in Middle Lake had warmed starting in the late 1990s or early 2000s. While
SEKO collection methods used in this study may not have allowed for the detection of a thermocline in the lakes, it was deduced from the data as well as the thermal regime of most other high-Arctic circumpolar lakes (Vincent et al. 2008) that two of the three study lakes
! ! 87! had warm epilimnions and colder hypolimnions, and the shallowest lake (Capron) appeared to be isothermal in the summer. Annual temperatures in all three lakes ranged between 0-
13ºC (Figure 4). As juvenile Arctic Char growth peaks at 10-13°C (Jobling et al. 1993) and their optimum temperature for growth is 14-17°C with unlimited food availability
(Elliott and Elliott 2010) or slightly lower within natural conditions (Elliot 1982), it is unlikely that the upper range in lake water temperature prohibits Arctic Char growth or habitat accessibility in any of the three study lakes. In a similar study on Arctic Char in
Northern Quebec, in landlocked Lake Tasiapik, evidence was found for water temperatures that exceeded this optimal growth range and resulted in reduced growth rates for young ages (Murdoch and Power 2013).
Water quality was reported not to have changed in terms of clarity or taste over the lifetime of 100% of the local experts interviewed. While significant differences were seen among some of the laboratory results among the lakes, none of the water chemistry analyses suggested that fish habitat was constrained by differing water quality among the lakes.
Compared to published water chemistry surveys on 46 lakes on Banks Island (Lim et al.
2005), none of the study lakes represented extreme conditions, nor presented any metal or ion concentrations known to limit fish health. However, some indicators of nutrient concentrations, such as conductivity and total dissolved solids in Middle and Kuptan lakes, were higher compared to mean levels observed across Banks Island (Lim et al. 2005), and higher than comparable lakes surveyed on the northwestern portion of the mainland within the Northwest Territories (Pienitz et al. 1997). High conductivities are associated with more productive salmonid lake habitats (Shuter et al. 1998), however, on Banks Island the three study lakes are characterized by equally low levels of nutrients and chlorophyll a.
! ! 88!
Note that it was not possible to collect the nutrient or chlorophyll a samples immediately following the spring thaw which is typically the most appropriate time.
2.4.2 Arctic Char Condition and Diet
Variations in both qualitative body condition (Inuvialuit assessment based on char being plump, free of abnormalities or parasites, with firm flesh) and quantitative body condition (Fulton’s K) among the lakes were observed in both the IKO and SEKO. The results of the SEKO showed Arctic Char caught in Capron Lake were in significantly higher quantitative condition than those in the other two lakes. This was also reflected in the IKO, where Capron Lake char were considered “healthier” (higher qualitative condition) by 11% of interviewees and Middle Lake char less healthy by 22% of IKO interviewees.
SEKO found a lump on only one sampled char out of 557 fish sampled. However, over a third (38%) of interviewed local experts had observed increases in deformities, sores, cysts or lumps on a small number of Arctic Char over their lifetimes. Despite this, the vast majority of char caught through subsistence harvest were considered healthy and good to eat. Arctic Char qualitative condition based on physical deformities could not be triangulated as the IKO provided information only at the temporal scale, and no SEKO at an equivalent scale was available. However, increases in deformities, sores, cysts and lumps as observed through IKO may prove a useful qualitative measure of condition to be considered as a potentially relevant IKO parameter for monitoring char condition.
Variation in qualitative and quantitative body condition among the three study lakes led to further analysis in relation to IKO and SEKO parameters deemed to have the potential to affect char condition. The differences in taste of raw and cooked the Arctic Char within the three proximate study lakes shared through IKO by over a quarter (28%) of the
! ! 89! interviewed local experts led to the examination of diet. An omnivorous diet for Arctic
Char was described in both the IKO (Table 5) and SEKO (Figure 8) in all three lakes. Char often occupy the top of the aquatic food chain and consume a significant proportion of the biotic energy budget through omnivory (Finstad et al. 2001). This omnivorous diet in lakes was also observed in Arctic Char in other lakes of the Western Arctic where diets included fish (sticklebacks, char, and char eggs), macroinvertebrates (Diptera, Gammaridae,
Trichoptera and Isopoda), water mites, zooplankton (Copepoda, Cladocera), detritus and larger crustaceans where available (Gantner et al. 2010). However, differences in the components of the omnivorous diet were seen among the three lakes, with Capron Lake having the highest amount of higher-nutrient prey items (fish eggs and amphipods, Figure
8), and Middle Lake having the largest range of taxonomic diet items observed in the in- field assessment of prey items from stomach contents.
While IKO of zooplankton was limited, SEKO showed that Capron Lake zooplankton biomass was significantly higher than in Middle and Kuptan lakes. Also,
Capron Lake was more productive in terms of zooplankton densities and contained higher biomasses of the dominant larger-bodied zooplankton than Kuptan or Middle lakes (Table
7). This is a possible explanation for the higher char condition seen in Capron Lake (Table
5). The zooplankton samples were collected within a short time period and there was little difference among the zooplankton body sizes within species among lakes (data not shown), so it is unlikely that density rankings are due to differences in the particular life stages at the time of sampling. The species found in the three lakes were similar to those reported for other Canadian circumpolar lakes (Samchyshyna et al. 2008) and lakes in Alaska (Kling et al. 1992). It is suggested that follow up studies should consider examining zooplankton
! ! 90! in similar fashion to work done by Barbiero et al. (2001) where zooplankton size was used for categorizations to determine trophic status among the Great Lakes. This approach may be worthwhile to determine if zooplankton size and density or biomass is an appropriate indicator for an Arctic Char monitoring program on Banks Island.
All taxonomic groups of parasites identified in the scientific samples were similar to those found in freshwater fishes and Arctic Char in the Northwest Territories and
Nunavut (Stewart and Bernier 1999, Gallagher et al. 2009). A Diphyllobothrium sp. (likely
D. ditremum or D. dentriticum) was the most common parasite found in Arctic Char gut samples. IKO provided some insight into Diphyllobothrium spp. from three interviewees: loads were highest in Middle Lake and seemed to have increased since at least the early
2000s. These results partially corroborate the SEKO in that parasite loads were significantly higher in Middle Lake. The SEKO also showed that fish in lower condition typically had a higher parasite load. However, whether low fish condition is directly due to a high parasite load, or instead low condition makes fish more susceptible to parasites, is not clear from this study, nor were there enough char samples to distinguish between the two scenarios. In addition, copepods are the intermediate host for the parasite
Diphyllobothrium spp. Copepods were more abundant in the diet of Arctic Char from
Kuptan and Middle lakes, where Diphyllobothrium infections were also highest. While amphipods are the intermediate host for the parasite Echinorhynchus spp. and this diet item was most abundant in the diet Capron Lake char, where Echinorhynchus spp. infections were highest. Further studies are required to ascertain the linkages between diet, parasite infections and body condition.
! ! 91!
As both quantitative and qualitative condition estimates in this study were primarily on older fish, and the younger fish in all lakes appeared to have similar condition (data not shown), it is likely that the presence of parasites could result in decreased fish condition over time. This hypothesis is supported both by the known life-cycle of Diphyllobothrium spp. and through the results of another study. Fish become infected with Diphyllobothrium spp. by eating copepods (zooplankton) that are infected with the parasitic larvae. As the parasite is long-lived, it can accumulate within the fish host as the fish matures (Stewart and Bernier 1999) and increased prevalence of tapeworms has been observed with increasing char age (Frandsen et al. 1989). This could be the situation in the lakes on Banks
Island as calanoid and cyclopoid copepods were found in the zooplankton tows from all three lakes (Table 7), zooplankton were found in the Arctic Char diets, and are copepods are known to be a standard diet of young char (Curtis et al. 1995, Gallagher and Dick 2010).
Therefore, further studies on the correlation between char age, diet, parasite load, and condition are recommended.
2.4.3 Triangulation
Bell and Harwood (2012) stated “the credible blending of indigenous and scientific views and skills improves the likelihood of ultimately understanding the resource, its habitats, and its inherent ecological relationships”. This was seen in the combining of
SEKO and IKO in this study for some parameters. The mixed methods approach supports greater confidence when the results of the analysed knowledge bases corroborate one another. Corroboration occurred for the following parameters: fish species present in lakes, lake depth, lake bottom, Arctic Char condition (girth:length), diet, parasite
(Diphyllobothrium spp.) loads, and the cause of the different flavours of char from different
! ! 92! lakes. The IKO enriched the understanding of several parameters for which SEKO was limited or lacking in this study including allochthonous input, and the differences in taste and colour of the meat of Arctic Char among the three study lakes. The SEKO enriched the understanding of several parameters for which IKO was limited or lacking including water temperature, water quality, identification of parasite species infecting char, and zooplankton species and biomass. The mixed methods approach was valuable in developing a better understanding of the influence of limnological conditions and lake habitat parameters on Arctic Char quantitative and qualitative condition in the study lakes, and provided a more advanced understanding of current conditions for new monitoring programs for landlocked Arctic Char in the region.
2.4.4 Summary of Lake Habitat Drivers of Arctic Char Condition
Given the results from both the IKO and SEKO, it appears that char with the highest quantitative and qualitative condition were found in the smallest, shallowest and warmest lake (Capron) while the char with the lowest condition were found in the largest, deepest and coldest (Middle). None of the lakes appeared to be warm enough to exceed the optimal growth temperatures of Arctic Char and all three lakes had higher concentrations of TDS and conductivity than found in other Arctic regions (Lim et al. 2005) suggesting that the lake habitats provided productive environments for Arctic Char growth.
Information collected on diet and parasite load further described several differences between Capron Lake and Middle and Kuptan lakes. Capron Lake char had low parasite loads and high zooplankton biomass while Kuptan and Middle lake char had high parasite loads and lower zooplankton biomass. Two of the three lakes had a potentially rich source of nutrients for adult char with evidence of fish eggs in Capron Lake and fish remains in
! ! 93!
Middle Lake char stomach contents. Examining these ecological drivers, it would be expected that juvenile growth would be high in Capron and lower in Middle and Kuptan lakes due to the difference in zooplankton biomass, and adult growth should be constrained in Middle and Kuptan lakes due to higher parasite loads. This scenario would lead to higher fish condition indices in Capron Lake over Middle and Kuptan lakes, and therefore provide a plausible explanation to the observations in the IKO and SEKO.
Several ecological mechanisms could have the potential to influence Arctic Char condition but were not addressed in this study. First, it is important to note that the findings in this study are indicative of the relatively high productivity of Banks Island lakes (Lim et al. 2005) when compared to other studies. For example, in Greenland’s ultra-oligotrophic lakes, the larger landlocked char were found in deeper lakes and smaller char in the shallower lakes (Riget et al. 2000). However, if the shallower lakes in Greenland were also relatively warmer, Arctic Char might grow faster if the ambient temperature approaches their optimal growth conditions. This would only be possible, if they could access sufficient prey items to match their higher metabolism and growth. In this study, given the high productivity and wide range of prey items identified in all three lakes, it is unlikely that the Arctic Char in Capron Lake are constrained by a low availability of prey items.
Second, it is known that predation, inter- and intra-specific competition, and food availability drives the diversity in foraging behaviour and morphology in char (Guiguer et al. 2002, Dick et al. 2009), and the effects of density-dependent competition for restricted food resources drives char somatic growth (e.g. Amundsen et al. 2007). Examples of interactions between Arctic Char and Lake Trout causing shifts in diet in the central Arctic.
For example, in Peter Lake (near Rankin Inlet) isotope analyses determined that Lake Trout
! ! 94! were tertiary consumers, whereas Arctic Char, Lake Whitefish and Ninespine Sticklebacks, were secondary consumers (Kidd et al. 1998). The presence of Lake Trout in all three of the study lakes could have a dual effect on the char population as both a potential predator and a competitor, which could force char into substandard habitat with lower availability of optimal prey items or temperature regimes outside of their most efficient metabolic range. This could lead to lower char growth rates, earlier maturity and smaller body sizes
(Kidd et al. 1998). The effects of predation, inter- and intra-specific competition, and food availability on char condition were not examined in this study and should be explored to better understand what aspects of lake limnology are the primary and interacting drivers of
Arctic Char condition.
Last, the level of exploitation on each of the three lakes was not included as a parameter in this study. Some of the effects of exploitation on landlocked and anadromous
Arctic Char are known including changes in the age-frequency and age-weight distributions of the population (e.g. Johnson 1994, Dempson et al. 2008). The magnitude of the Arctic
Char harvest from each lake is likely very low given the low levels of activity of harvesters from Sachs Harbour observed over the course of this research. However, it is still important to acknowledge that exploitation could lead to changes in Arctic Char abundances which could have cascading effects throughout the food web and parasite cycles within each lake.
Therefore, the magnitude of the harvest should be explored in further studies.
2.5 Conclusion
A mixed methods approach provided a comprehensive understanding of the state of lake habitat and Arctic Char condition, as well as provided more in-depth explanations as to why char condition differed among proximate lakes in the study area. While no clear
! ! 95! lake habitat indicators for monitoring of Arctic Char condition were revealed, several parameters showed promise for community-based monitoring. Evidence for multiple ecological mechanisms were found to be important in the condition of char including allochthonous input, lake temperature regime, lower trophic level diversity and productivity, and parasite load. In addition, the qualitative parameter of taste (based on
IKO of any potential changes to taste) may also be an effective indicator. Qualitative scales for monitoring char taste could be developed following methods outlined in the FAO report
Quality and Quality Changes in Fresh Fish (1995). These five parameters should be incorporated into monitoring programs in the area to collect long-term datasets and information to determine their efficacy and suitability as indicators of Arctic Char condition.
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! ! 107!
CHAPTER 3:
Understanding Growth Variability in Landlocked Arctic Char in Response
to Local Environmental Conditions using
Scientific Ecological and Inuvialuit Knowledge and Observation
!
3.1 Introduction
Globally, fisheries are critical contributors to food supply, food security and livelihoods (Shelton, 2014). In many regions of the world, marine, anadromous and freshwater fish populations are being affected by climate change (Stram & Evans, 2009;
Jiménez Cisneros et al., 2014; Larsen et al., 2014; Hansen et al., 2015). The full effects of climate changes on fisheries resources remain unclear (Stram & Evans, 2009; Heenan et al., 2015). However, many freshwater and marine species have shifted geographic ranges, abundances and behaviours (IPCC, 2014). While fisheries managers have always worked with some level of uncertainty when managing fish resources, climate variability and change (CVC) has added another degree of uncertainty beyond current forecasting capabilities (Hansen et al., 2015).
Amplified CVC is apparent in the circumpolar Arctic as a result of both environmental drivers and anthropogenic stressors. Global mean surface temperature is projected to rise by 0.3ºC to 1.7ºC by the end of the 21st century, with the Arctic region continuing to warm more rapidly than the global mean (IPCC, 2014). Annual mean sea- ice extent in the Arctic is experiencing the most pronounced signs of global warming with decreases between 3.5 to 4.1% per decade between of 1979 and 2012. Arctic sea ice
! ! 108! coverage has decreased in every season and every successive decade from 1979-2013 with the most rapid decreases observed in summer and early fall, corresponding to an approximate loss of 3 X 106 km2 over the 35-year period (Barber et al., 2012; IPCC, 2014;
Larsen et al., 2014; Meier et al. 2014; Simmonds, 2015). Globally, high latitudes are predicted to experience an increase in mean annual precipitation, leading to altered hydrological systems. The IPCC (2014) summarizes the effects of CVC in the Arctic as already resulting in moderate effects on Arctic marine, terrestrial and freshwater ecosystems, as well as moderate effects on human health and livelihoods.
Many ecosystems are interdependent and the effects of CVC will directly affect physical and chemical systems in the marine and freshwater environments. Evidence already exists for connections of CVC on changes in the Arctic environment including decreases in sea ice, permafrost degradation, and altered flow regimes. Changes in the cryosphere are resulting in altered physical, biogeochemical, and biological linkages as well as causing positive feedbacks that exacerbate effects of climate warming (Vincent et al., 2011). The linkages from direct effects of CVC on the environment to biological systems (i.e. freshwater ecosystem) are more tenuous, speculative in nature, and less- documented, particularly in the north.
An example of a cascade of CVC linkages is the effect of El Niño – Southern
Oscillation (ENSO) and CVC on the Arctic ocean environment. These climate drivers have led to decreased annual sea ice coverage (Liu et al., 2004; Hutchings and Rigor, 2012).
Low-sea ice coverage in ocean environments can lead to more open water, which has a lower albedo than sea ice, resulting in the absorption of more solar radiation leading to warmer water (Barber et al., 2008; Galley et al., 2008). Reduced sea ice and warmer ocean
! ! 109! waters could lead to warmer ambient air temperatures and increased winds and precipitation. This, in turn, could result in warmer conditions in the local environment, including effects on the freshwater environment such as a longer lake ice-free season (e.g.
Screen and Simmonds, 2010; Arp et al., 2015; Alexeev et al., 2016; Brock, 2016). Further indirect CVC effects on underlying ecosystem shifts may lead to effects on fish populations, such as a longer lake-ice-free season resulting in increased solar absorption resulting in warmer lake water and increases in Growing Degree Days. This could then lead to increased lake productivity and increased fish growth through warmer water temperatures and higher prey availability (Wrona et al., 2005). These indirect effects of
CVC are even more poorly known and as yet are mostly undocumented in the Arctic.
As CVC progresses, Arctic freshwater ecosystems are under increasing threats from a variety of drivers that will result in changes to biota as well as the structure and function of these systems (Culp et al., 2012; Prowse et al., 2015). Further projections of CVC effects on Arctic freshwater systems include a suite of effects including: thermal, hydrological, sediment, wind and UV regime shifts; changes in nutrient availability and food web structure; introduction of new species; and shifting renewable resource exploitation (Wrona et al., 2005; Culp et al., 2012; Vincent et al., 2013; Shelton, 2014). In northern Alaska, declines in early fall sea-ice concentrations have already been linked to a thinning trend in seasonal Arctic lake-ice growth since 1991 due to the effects that sea ice has on local climate processes effecting terrestrial-freshwater systems (Alexeev et al., 2016).
Projections are that fish numbers and growth will increase in the north with warming temperatures and new stock dynamics will need to be monitored as freshwater species begin to experience changes in their habitat (Huntington & Fox, 2005; Reist et al.,
! ! 110!
2006a; Prowse et al., 2009; Larsen et al., 2014).! Environmental drivers leading to changes in the freshwater ecosystems will affect freshwater fish and fisheries in the following four ways: effects on the quantity and species of fish available; effects on the quality of fish available; effects on the access to fisheries; and, effects on the success of fishing efforts
(Nuttall, 2005; Reist et al., 2006a; Larsen et al., 2014). These changes to fish and fisheries are critically important to monitor as freshwater and anadromous fish contribute significantly to the subsistence harvests and commercial fisheries in the circumpolar north.
People in northern communities who eat country foods have a healthier diet than those who eat store-bought foods and are provided with the nutrients they need (Blanchet et al., 2000; Gagné et al., 2012; Laird et al., 2013). Dietary fish oils are high in omega-3 fatty acids, which may offer protection against conditions such as high blood pressure, diabetes, and certain types of cancers (Blanchet et al., 2000). Accordingly, the fish species
Arctic Char (Salvelinus alpinus (L.)), with its circumpolar distribution and diverse habitat including lakes, rivers and nearshore marine areas, is an important subsistence food for
Inuit (Berkes, 1990; Stephenson, 2004; Blanchet and Rochette, 2008; Egeland et al., 2010a,
2010b and 2010c).
Obtaining and eating local country foods, including fish, provides important cultural, social, and economic benefits as well (Blanchet et al., 2000; Nuttall, 2005; Laird et al., 2013; Tagalik, 2015). Therefore, the human context must be seriously considered when understanding the effects of CVC on freshwater and anadromous fish, as harvesters will have to adapt quickly to the current and predicted changes in this resource including availability and accessibility (Jolly et al., 2002; Nuttall, 2005; Communities et al., 2005;
Reist et al., 2006a; Furgal & Seguin, 2006; Larsen et al., 2014). However, there are several
! ! 111! difficulties surrounding the management of Arctic fisheries beyond complications presented by CVC. First, a poor understanding of basic Arctic freshwater fish biology and linkages with ecosystem drivers result in a poor ability to generally predict fish population dynamics and responses to CVC drivers and stressors. Second, very poor to non-existent quantitative and qualitative linkages have been made between stressors such as CVC and potential responses from both the ecosystem and the fish populations (Lim et al., 2006;
Reist et al., 2006a). Harvesters and local management organizations will still have to develop proactive and precautionary strategies to deal with the effects of CVC on the fish populations (Stram & Evans, 2009).
To monitor fisheries resources in a changing climate, there is a need to understand how climate-driven changes will alter aquatic ecosystem function and the mechanisms for biological and chemical processes. This type of data and information can be accomplished through an ecosystem approach to fisheries management and thorough monitoring and data collection designed to address critical uncertainties (Michalsen et al., 2013; Andersson et al. 2015; Hansen et al., 2015; Heenan et al., 2015). Fisheries data for use towards ecosystem-based management can be generated from many sources including stakeholders and local experts of ecological knowledge (Lapointe et al., 2014). It was recognized that different knowledge systems and engaging multiple methods could provide a more comprehensive understanding of phenomena studied (Furgal et al., 2006), and support the development of a more rigorous suite of suitable monitoring indicators. As a result, a mixed methods design was adapted for use in this study combining both quantitative (ecological) and qualitative (local expert) approaches and information.
The goals of this exploratory mixed methods research were to better understand the
! ! 112! effects of environmental drivers on Arctic Char growth in three landlocked lakes fished by
Inuvialuit on Banks Island in Canada’s western Arctic, and to determine if certain environmental parameters could be used as potential monitoring indicators of char growth.
In this study, ecological sampling and analysis of quantitative data were used to measure the relationship between local environment and Arctic Char growth. At the same time, the effects of environmental conditions on char growth were also explored using qualitative interviews, scoping sessions and meetings with Inuvialuit fish experts from Sachs Harbour on Banks Island in the Inuvialuit Settlement Region (ISR) in Canada.
3.2 Methods
3.2.1 Research Design
A literature review was conducted to identify known environmental drivers and stressors with the potential to affect Arctic Char growth in both the scientific literature and documented Inuit knowledge. The literature search used online databases of both grey and peer-reviewed papers, books and reports. In addition to online databases, documented Inuit
Knowledge was accessed through ISR libraries.
In this paper, the term Inuvialuit knowledge and observation (IKO) is used as it was preferred by the Inuvialuit involved in the study to Local Ecological Knowledge or
Traditional Knowledge, commonly used in this literature. IKO is the ecological knowledge held by Inuvialuit based on information gathered individually or as a group through living on or using the land within their lifetime (Community Corporations, 2006, personal communication with local experts in the Inuvialuit Settlement Region 2008-2015). This knowledge is sometimes represented in long-term syntheses of that data and information, and sometimes is connected with cultural beliefs or worldviews. In this paper, scientific
! ! 113! ecological knowledge and observation (SEKO) refers to data and information gained through scientific inquiry within the belief that a phenomenon of interest must be
“understood in context” (Peterat 2008, p. 237).
A modified mixed methods parallel concurrent design, with some sequential steps and final knowledge and observation triangulation, organized and directed information collection and analyses in the study (adapted from Creswell, 2009; Figure 1). This research design facilitated the linking of quantitative ecological and qualitative social science methods and information. Collection and analysis of the IKO from local fish experts helped identify candidate environmental parameters for study, in recognition that standard scientific approaches and literature may miss local indicators of environmental change
(Noon, 2003; Huntington et al., 2004). This effort, along with biological rationalizations, allowed for the a priori selection of the environmental parameters to be studied to determine potential correlations with char growth. Triangulation (Creswell, 2007;
Rothbauer, 2008) involved comparing the quantitative (SEKO) and qualitative (IKO) knowledge bases when they were comparable across the same scales (temporal, spatial, or conceptual) to determine convergence or divergence between the two knowledge bases
(Gagnon & Berteaux, 2009; Furgal & Laing, 2012).
! ! 114!
Figure 1. Diagram of research design followed in this study showing the modified parallel concurrent design with some sequential steps and final information triangulation.
Sequential steps occurred in instances where qualitative analysis dictated further quantitative inquiry (arrow A), prior to final information triangulation and interpretation
(adapted from Creswell, 2009).
3.2.2 Research Location
Due to the paucity of freshwater fish research in the area, the community’s reliance on Arctic Char as a country food resource, the community’s history of documenting local
CVC in the surrounding environment (e.g. IISD, 1999-2000 (4 trip reports; Riedlinger &
Berkes, 2001; Nichols et al., 2004), and the community’s interest in developing an Arctic
Char community-based monitoring program, this location was chosen for the study. The history of documenting local climate change was also indicative of the community’s
! ! 115! interest and motivation in observing and understanding the effects of changing environmental conditions on their char resource.
Five lakes near the community of Sachs Harbour were identified by the Sachs
Harbour Hunters and Trappers Committee (SHHTC) as important char fishing locations
(Capron, Fish, Kuptan, Middle and Raddi lakes). Landlocked char were chosen for study as they are isolated in the same location for their entire life and therefore present the opportunity to examine the effects of local environmental factors on growth over time in one location (Kristensen et al., 2006). Therefore, the study was restricted to three of the five lakes that met this criteria: Kuptan, Middle and Capron lakes (Figure 2). These three lakes are essentially landlocked and act as closed systems with only rare opportunities for
Arctic Char to migrate elsewhere. Kuptan and Capron lakes each have only one outlet to the surrounding landscape, one to the sea and the other to the watershed, respectively, whereas Middle is completely closed. However, the outlet streams of Kuptan and Capron lakes are shallow and ephemeral, and therefore only allow spring migration under extreme precipitation events.
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Figure 2. Map of the Inuvialuit Settlement Region (bottom) situated in the northern portions of the Northwest Territories and Yukon, Canada. The study area is marked with a black star. Inset shows locations of Kuptan, Middle and Capron lakes in relation to Sachs
Harbour (marked with a black circle), on the southwest side of Banks Island NT. (Both maps adapted from files courtesy of J. Babaluk, Fisheries and Oceans Canada)
Banks Island is classified as Arctic Cordellia terrestrial ecozone
(http://sis.agr.gc.ca/cansis/nsdb/ecostrat/hierarchy.html, access May 14, 2016) and is split into three ecoclimatic zones (High-, Mid- and Low-Arctic), defined by distinct ecological responses to climate. The study lakes are located in the southern-most Low-Arctic zone characterized by similar annual precipitation to Mid-Arctic (≤300 mm) but the growing
! ! 117! season is longer at ~3 months and warmer with a mean July temperature of ~8°C
(Ecoclimatic Regions of Canada, 1989; Lim et al., 2005). The study lakes are in a series of thermokarst lake basins in close proximity to the Sachs River (Manson et al., 2005). The field and in-community research took place between January 2008 and May 2015.
3.2.3 Local Experts and Community Participation
Local experts (as defined by Davis & Wagner, 2003) on fish in the community were determined through a specific process which involved asking two community organizations to independently create lists of people who fit the criteria of being individuals who: fished in all fishing seasons; fished several times per month during the fishing seasons; and had fished locally for at least ten years. Individuals whose names appeared on both lists were approached for interviews. Prior to interviews, the final list was reviewed with the two organizations to ensure it collectively included individuals with experience from all three study lakes.
While some local experts were also members of the Sachs Harbour Hunters and
Trappers Committee (SHHTC), only identified local experts were involved in the qualitative information collection through participation in scoping sessions, semi-directed interviews and validation workshops. SHHTC members were included in study site selection and design due to their elected role as the fish and wildlife management representatives for the community. Other community members, including SHHTC members and local fishers (not identified as local fish experts), participated in community meetings and workshops at various stages of the project as well, but were not involved in the scoping sessions, semi-directed IKO interviews or validation workshops.
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3.2.4 In Situ Data Collection
3.2.4.1 Collection of Inuvialuit Knowledge and Observation (IKO)
Exploratory semi-directed interviews (Creswell, 2009) were conducted with local experts in spring of 2010. Community residents fluent in Siglitun or Inuinnaqtun (local
Inuvialuktun dialects) were used as translators and present at an interview whenever required or requested by the interviewee. Interviews focused on IKO of: historical and current char size and growth; potential changes in average char size or growth over time; local environmental conditions including climate, meteorology, cryosphere, and shorelines of lakes; any potential changes in local environmental conditions over time; and, observed effects and knowledge of local climate on char size or growth. Information on local expert interviewee attributes, human use of the resource, perspectives on monitoring of char, and other related topics of interest to the interviewee were also discussed and recorded. The interviews provided background information on interviewees and context to the IKO.
This project followed a community-collaborative approach (Tondu et al., 2014) with members of the SSHTC and local expert group being consulted on plans and decisions throughout the project. In addition to the semi-directed interviews, ethnographic fieldwork
(Nadasdy, 2003) and prolonged engagement (Lundy, 2008), were used to build trust with research participants to create an environment of open and reciprocal learning between the researcher and local experts. Ethnography is a qualitative methodology in which the researcher studies a cultural group in situ over a prolonged time, primarily through observation and interviews, and where the research process is flexible to respond to the lived field setting (Creswell, 2009). Prolonged engagement is a qualitative methodology referring to spending extended time with study participants in their native culture and
! ! 119! everyday world, resulting in the immersion of the researcher in the culture, and allowing the study to go farther in investigating phenomena that cannot be adequately explored with short-term studies (Lundy, 2008).
In addition to conducting on-going community consultations, update meetings and validation workshops, time was spent on additional participant observation activities
(McKechnie, 2008) done in an ethnographic format (see Chapter 2). Over the course of the first five of seven years of in situ research, a minimum of two-months cumulative time each year was spent in the community and on the land interacting and collaborating with local experts and community members. Participant observation activities included: attending and participating in community meetings and gatherings, visiting local experts at their homes, and trips on the land accompanying, assisting and learning from fishers in their travels and fishing activities. This information complemented the semi-directed interviews by providing additional insights and explanations of phenomena studied.
In addition, during the last two years, several weeks per year were spent in the community for knowledge transfer to the SHHTC for ongoing data collection efforts beyond the life of this study. These efforts included training additional local monitors in scientific data collection techniques, and carrying out final reporting and results validation meetings. The ethnographic, prolonged engagement and participant observation components of the research were conducted at times deemed important by the community for fishing efforts and times of community gatherings. Research involving IKO was carried out under Trent University Research Ethics Board Approval (#21069) with approval from the SHHTC and local expert participants.
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3.2.4.2 Field Sampling Techniques for Arctic Char
Local assistants were trained in scientific sampling methods and worked with the researcher throughout the project to collect field data from fish caught in scientific and subsistence nets. Arctic Char from the three study lakes were captured from 2008-2012 using randomly-set floating and sinking multi-mesh gillnets with a total length of 120 m and 20 m bar mesh sizes: 10 mm (110/2 twine), 19 mm (110/3), 33 mm (110/3), 45 mm
(210/2), 55 mm (210/3) and 60 mm (210/3); net depth = 1.8 m. A maximum of 75 char per year (as dictated as per the Fisheries and Oceans Canada Scientific Fishing Licence) were dead sampled each summer from Capron (2008, 2010, 2011), Kuptan (2009, 2011, 2102), and Middle (2008, 2009, 2011, 2012) lakes. In addition to summer net sets, and whenever possible, subsistence catch was also sampled. In spring (April-May), char were also caught using jiggling (wooden stick and line fishing through augured ice holes) during the community spring fishing season.
Char were sampled for a variety of parameters including fork length and weight (see
Chapter 2). Sagittal otoliths were collected for laboratory age and back-calculation analyses. All fish were cared for in accordance with the Guide to the Care and Use of
Experimental Animals and following Trent University Animal Care Committee Approvals as well as the Department of Fisheries and Oceans Canada Animal Use Protocol approvals.
3.2.5 Analyses of Expert Interviews and Ecological Data
3.2.5.1 Qualitative Analysis of Local Expert Interviews
Audio files of semi-directed interviews were transcribed verbatim and individual transcripts returned to interviewed local experts for the opportunity to verify their transcript prior to data analysis. Transcripts were entered into the qualitative analytical software
! ! 121!
NVivo (QSR International Pty Ltd. 1999-2014, v. 10). A two-pass thematic coding process
(Saldana, 2009) was used (see Chapter 2). Inter-coder variability was checked to increase reliability in the development and application of the coding scheme to the qualitative information and member checks (Jensen, 2008) were used during follow-up visits to the community to validate coding and IKO interpretation (see Chapter 2). Additional external validation of researcher interpretation of results was achieved through a series of fishing community meetings and in-community home visits (Creswell, 2009). The results of the
IKO were used to identify key environmental parameters potentially affecting fish growth.
3.2.5.2 Quantitative Analysis of Environmental Conditions
Environmental conditions on Banks Island were obtained and estimated for the period from 1970 to 2011 using climate data from Environment Canada
(http://climate.weather.gc.ca/), and satellite imagery from Radarsat (http://www.asc- csa.gc.ca/eng/satellites/radarsat1/, accessed between May 16 and August 28, 2012) and
Landsat (http://landsatlook.usgs.gov/viewer.html, accessed between May 16 and
September 23, 2012). Daily average air temperature and daily total precipitation (rain and snowfall) were collected from historical climate data series from the Sachs Harbour weather station. Reliable wind data was not available from the Sachs Harbour weather station. From the average air temperatures, Growing Degree Days above 0°C were calculated for each year. Ordinary least squares linear regressions were conducted for annual and monthly mean, minimum and maximum temperatures over a 42-year timespan from 1970 to 2011 to discern trends in changes in temperature (as used in Turner et al.,
2005; Dobiesz & Lester, 2009; Schneider & Hook, 2010). Zero degrees Celsius was chosen as the threshold following Chezik et al. (2014) because Arctic Char are known to begin
! ! 122! feeding at this ambient temperature. Note that air temperature was not converted into water temperature, as not enough data was available for water temperature.
Ice cover on lakes was estimated from the ice phenology models presented in Shuter et al. (2013) and verified from direct observation by scrutinizing available satellite data following similar methods outlined in Duguay & LaFleur (2010) and Crétaux et al. (2011).
The "delay to freeze-up" model (Equation 1 in Shuter et al., 2013, page 986) was used for all three lakes and the "Break-up Model 1" was used for Capron Lake and "Break-up Model
2" was used for Kuptan and Middle lakes (Equations 2 and 3 in Shuter et al., 2013, respectively, page 988). As there was no rationale presented in their study to preferentially choose the "Break-up" models, the ones selected here for each lake reduced the residual variation from the break-up dates available from the satellite data the most using root mean squared error (Brian J. Shuter, personal communication, February 2016). Satellite images were available from 1984 onwards, and for available data typically for approximately 10% of the days from June 1st until lakes were observed to be completely free of ice, and often not available after October 30th. Consequently, the last day of ice-free water was often identified, yet the first day of a completely frozen lake was only observed 8-9 out of 27 years for Kuptan and Middle, and 16 of 27 years for Capron. As such, the models’ estimates of the length of time from the onset of ice break-up to the end of the freezing period was compared to this subset of available satellite data.
Last, the type of precipitation (i.e. rain or snow) was not consistently recorded at the Sachs Harbour weather station since 2005. To determine rain versus snowfall from
2005 to 2011, a logistic regression based on mean daily air temperatures was used to estimate the type of precipitation that fell for days with records of precipitation. The model
! ! 123! was verified using a linear regression of observed vs. predicted data points, done separately for rain and snow.
3.2.5.3 Arctic Char Otoliths
One of each pair of the sagittal otoliths obtained from Fisheries and Oceans Canada
(1992, 1994) and field sampling (2008-2012) from the three study lakes was embedded in an epoxy resin, and a transverse cut was made near the dorso-ventral cross section where the annuli were positioned perpendicular to the section line (Babaluk et al., 2002). The cut section was polished and photographed using an Olympus SZ61 model SZ2-ILST microscope with a digital ocular-mounted camera. The photos were then imported into the image analysis software, ImageJ (version 1.46r, 2012, Wayne Rasband, National Institutes of Health, USA, http://imagej.nih.gov/ij) where otolith annuli were enumerated (to determine age). A subset of half of the otoliths were verified by two trained analysts to ensure concordance of ages. Back-calculation was performed by measuring the width of each annulus as a ratio of the total length of the radii of the otolith (e.g. Kristoffersen &
Klemetsen, 1991; Kristensen et al., 2006; Høie et al., 2008).
3.2.5.6 von Bertalanffy Growth
Growth of Arctic Char in all three lakes was estimated from von Bertalanffy growth curves (Lester et al., 2004) using two datasets: 1) fork length at time of capture (in mm) and age (in years) of fish caught in the three lakes from 1992-1994 and 2008-2012; and 2) the back-calculations of the individual fish's annual growth increments from analyzed otoliths from the same set of surveys. In the latter method, age and length data were derived for each year over the lifetime of each fish, and then the entire sample for the lake and survey period was analyzed. All growth curves were estimated from non-linear regressions
! ! 124! conducted using the R programming language (R Core Team, 2014) statistical package FSA
(Ogle, 2015) with nls2 (Grothendieck, 2015).
Recognizing that otolith annuli widths and annual growth rates are not perfectly coupled in fish, which has also been experimentally demonstrated in Arctic Char
(Mosegaard et al., 1988), the length-at-age estimates from back-calculated dataset were derived for each lake following the Campana (1990) algorithm. Small char (80-120 mm) were available for assigning biological intercepts, and plots of otolith-length versus fish- length were scrutinized to ensure there were no outliers. Lake-specific von Bertalanffy growth curves were compared between survey periods (1992 and 1994 plus 2008-2012), among lakes and between captured fork length at age and back-calculated length-at-age by creating 99% confidence intervals and visually scrutinizing the curves for overlap (note that the 99% confidence intervals adjust the significance level to p < 0.01 to account for the three comparisons among the three lakes). Confidence intervals were generated by resampling the data with replacement over 10,000 iterations for each regression model.
Growth curves of the different lakes within one set of years, and of different sets of years within one lake, were considered significantly different from each other if the confidence intervals did not overlap. This method is likely conservative yet simplifies comparisons between growth curves, which can be difficult due to non-normal distributions of the three von Bertalanffy parameters and the strong correlation expected between the asymptotic length parameter and the Brody growth coefficient parameter (Chen et al.,
1992). To ensure using confidence intervals was an appropriate approach, pairwise comparisons between growth curves (i.e. from different lakes, or different years) were conducted following Ogle (2015) in which the Akaike Information Criterion (AIC) was
! ! 125! computed for each possible model combination in which none, one, two or all of the parameters were calculated based on group data (i.e. pooled data across the pairwise datasets). The lowest AIC selected model parameters that were best at defining the two sets of data, and thus indicated whether parameters were common across lake populations, and consequently, whether the growth curves differed. Given multiple comparisons, a conservative level of significance for the parameter estimates of p < 0.001 was used.
3.2.5.7 Arctic Char Maturity
Maturity was determined in the field at the time of sampling. Mature char were those in a ripe or resting state, immature char were those with underdeveloped gonads. The maturity of Arctic Char in each of the three lakes was estimated by a logistic regression of the field estimates of either “immature” or “mature” with age. Maturity was assumed to occur when the probability of being mature surpassed 50%. Field estimates of maturity were verified by observing the age at which gonad development, based on gonad weight, appeared to occur across members of the population. Fish gonads were weighed in the field to an accuracy of 1 gram.
3.2.5.8 Linear Mixed-Effects Model Analysis
Using R (R Core Team, 2014) and lme4 (Bates et al., 2015), a linear mixed-effects model analysis was performed on the relationship between Arctic Char growth and environmental conditions on Banks Island. The environmental parameters were chosen a priori (Power et al., 2000; Kristensen et al., 2006; Chavarie, 2008), as dictated by the results of the IKO semi-directed interview analyses and from biological rationalizations ascertained from the peer-reviewed literature, in order to prevent possible spurious correlations. The three a priori environmental parameters tested were: 1) annual regional
! ! 126! air temperatures as defined by growing degree days; 2) annual number of ice-free days on each lake, and 3) the total annual precipitation in the region. Fixed effects identified in the full models were growing degree days above 0°C (GDD0), the length of the ice-free period on the lakes in days (Ice), total annual precipitation (Precip), fish age (Age), fish maturity
(i.e. Mat: either pre- or post-maturation), and lake name (i.e. Lake). Random effects included intercepts for individual fish (Fish) and year of growth (YearAge), as well as the interactions between YearAge and fish age (i.e. YearAge:Age), and between YearAge and the lake (i.e. YearAge:Lake). This is the full complement of variables available for use in the statistical models. However, because some variables were collinear with others, and the full model could be quickly overwhelmed by the amount of data available leading to rank deficiencies in running lme4, sub-models were run with subsets of the data.
Further, including all ages in a prediction of annual growth (i.e. absolute growth in mm) may cloud the effect size of the environmental fixed-effects (i.e. growth at age 2 is much larger than the effect expected from long growing seasons). Therefore, two sub- models were created: 1) a model that analysed annual growth (in mm) per age and retained
Age as a fixed-effect but dropped maturity status, and 2) a model that analysed relative growth (i.e. annual growth divided by average annual growth for all fish of that age from the lake population; (see Appendix 1 for mean relative growth per year for each lake)) and retains maturity status as a fixed-effect but drops Age. For both these models, as GDD0 and Ice were strongly correlated, the models were run separately with either GDD0 or Ice, and the one with a stronger significance and effect size was retained.
In all modeling analyses, the objective was to simplify the full model by removing parameters. The difference in the AIC (i.e. ΔAIC ≥5), as well as one-way ANOVAs among
! ! 127! nested models (i.e. p<0.001), were used to evaluate whether a parameter should be retained in the model. Fixed-effects were considered significant if they exhibited a t-value that was greater than 2 or less than -2 (Baayen et al., 2008). The best model’s fit was estimated using the co-efficient of determination, R2, as calculated for the marginal variation (i.e. that explained by the fixed effects) and the conditional variation (explained by both the random and fixed effects) as described in Nakagawa & Schielzeth (2013) and calculated using the
MuMIn R package (Barton, 2016).
Visual inspections of residual plots were conducted to identify any deviations from homoscedasticity or normality. As both annual and relative growth variables were not found to be normally distributed, these response variables were log-transformed for the analysis. Further, as linear mixed-effects models are sensitive to outliers, the final models were run with and without outliers in the response variables which were identified as data points outside of the 1% and 99% confidence intervals, and the model estimates were compared to ensure consistency.
3.2.6 Triangulation of SEKO and IKO
Once all data analysis, interpretation and validation was complete, a process of triangulation was conducted by creating a matrix of comparisons (Leech & Onwuegbuzie,
2008) for parameters at a minimum of two of the same scales (Furgal & Laing, 2012). The matrix compared the results from the SEKO and IKO (e.g. Huntington et al., 2004;
Gilchrist et al., 2005; Furgal & Laing, 2012). This led to the determination of whether the results of the datasets enriched, corroborated, contradicted or were inconsistent with one another with respect to the same phenomenon being explored (adapted from Mathison,
1998; Furgal & Laing, 2012). One dataset was seen to enrich the other when it provided
! ! 128! additional information where the other was lacking. They corroborated each other when similar information and explanations of observed phenomenon were found. Datasets contradicted one another when data from the two sources diverged or disagreed. Datasets were inconsistent when they did not corroborate, nor did they contradict. In instances where the datasets contradicted or were inconsistent, further investigations were conducted, when possible, to better understand the differences in the observed phenomenon, or follow up studies are recommended when further investigations were not possible.
3.3 Results
3.3.1 Literature Review
The SEKO literature review revealed a compilation of environmental information for southwestern Banks Island and Thesiger Bay. Data include climate, ozone depletion, marine cryosphere, erosion and permafrost melt on both marine coasts and lake shorelines
(e.g. Porsild, 1950; Lewkowicz, 1987; Trenberth et al., 2003; Manson et al., 2005 and
2007; Grenfell & Putkonen, 2008; Seabrook et al., 2011; Barber et al., 2012; Galley et al.,
2008 and 2012; Harwood et al., 2012; Hutchings & Rigor, 2012; Babb et al., 2016), and a new written record of two species of anadromous salmon to the region (e.g. Babaluk et al.,
2000). The IKO literature review discovered 13 reports and peer-reviewed publications documenting local expert knowledge on climate change around Sachs Harbour and
Thesiger Bay (i.e. IISD, 1999-2000 (4 trip reports); Ashford & Castelden, 2001; Riedlinger,
2001; Riedlinger & Berkes, 2001; Jolly et al., 2002; Nichols et al., 2004; Barber et al.,
2008; Barber et al., 2012) as well as general observations within the Inuvialuit Settlement
Region (i.e. Communities et al., 2005; Nuttall, 2005). The results in this study aligned with those documented in these papers and showed that environmental change on southwestern
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Banks Island has continued to, on average, progress towards warmer ambient air temperatures in all seasons, increasing erosion, lower annual sea ice coverage, and increased variability in climatic conditions over the past 15 years.
3.3.2 Inuvialuit Knowledge and Observation
A total of 18 local experts were interviewed. Disclosed ages ranged from 43-80 and interviewees had a combined 795 years of IKO about fish and fish habitat on Banks
Island. Table 1 provides a summary of the interviewee attributes including the number of years of knowledge and observation for each of the three study lakes. As different family units fished at different lakes, knowledge and observations were spread out among the three lakes (Table 1). Middle and Kuptan lakes were popular fishing locations, so the majority of local experts (89%, Table 1) interviewed had knowledge about these two lakes
(combined 707 years of knowledge and observations, Table 1). Capron Lake was further away from the community with a rougher travel route, and was a less common fishing location. Therefore, fewer interviewed local experts (50%, Table 1) had knowledge of
Arctic Char in this lake (combined 437 years of knowledge and observations, Table 1). All local experts interviewed shared IKO about the local abiotic and biotic environment obtained throughout their lifetimes.
!
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Table 1. Summary of Sachs Harbour local expert interviewee attributes including age, number years fishing experience and knowledge of the Capron, Kuptan and Middle lakes on Banks Island NT.
Female Male Interviewee Attributes (n=8) (n=10) Span Ages 44-79 43-80 Median Age 68 58 Mean Age 63.2 60.2 Span # Years Fishing Experience 22-58 24-71 Median # Years Fishing Experience 42.5 46 Mean # Years Fishing Experience 43 45.1 Knowledge of Capron Lake 50% 50% Knowledge of Kuptan Lake 88% 90% Knowledge of Middle Lake 88% 90%
3.3.3 Local Abiotic and Climatic Conditions
The analysis of the local expert IKO interviews revealed information on local climate, environment and associated changes, that stemmed predominantly from fishing, harvesting and on-the-land activities, as well as living in Sachs Harbour. A listing of the thematic codes and the number of respondents reporting specific environmental conditions as being potentially important to char growth is provided in Table 2. Further description of habitat parameters perceived or understood as important to char growth and examples of local expert explanations are provided below.
!
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Table 2. List of topics from Inuvialuit knowledge and observation local expert interviews on abiotic environmental conditions and features having the potential to influence Arctic
Char growth, with number of Sachs Harbor NT local expert interviewees (n=18) reporting the information.
Thematic codes of List of topics of Inuvialuit Knowledge and Observation of Number of lake habitat lake habitat features having the potential to influence interviewees characteristics Arctic Char condition reporting (n = total number of observation interviewees who provided IKO for thematic code)
AIR •!Warmer in all seasons since late 1980s to early 1990s; 11 TEMPERATURE getting warmer every year in spring, summer, fall, winter; (n=11) much hotter in summer •!Past spring temperatures ranged from -20 to -25˚; -40 to - 5 70˚C throughout winter; hasn’t happened for ~ 2 decades (since ~1996), since then average winter temperature ranges were closer to -20 to -30˚C •!Warmer weather in spring results in earlier snow melt, 4 making it difficult to travel for harvesting •!Does not get as cold when there is open water on the ocean 1 in winter near the community CONDITION OF •!Ground absorbs more snow melt and rainfall since ~1999, 6 GROUND gets soft and does not dry out anymore, surface water (n=13) doesn’t flow into streams (and eventually) lakes anymore •!Ground and rivers used to stay frozen until end of June, now 11 by May, cracks have developed in land that make it difficult for summer travel, started ~2001 •!Areas where ground has started “sliding over itself” in past 3 ~15 years (starting ~2001) EROSION AND •!No local expert had seen erosion or mudslides when young, 18 PERMAFROST now getting a lot of erosion along ocean coast, coastline MELT (OCEAN beside community used to be 90-degree angle now slumped COAST) with exposed gravel and can walk down, first noticed (n=18) “melting mud” (mudslides) in late 1980s, erosion worse over the last ~17 years (since ~1999) especially along east and southeast coast •!After coastline started eroding, noticed more waves hitting 4 shores and when there are storms in summer the beach gets really muddy now, waves are bigger EROSION AND •!More mudslides and erosion each year on lake shores, started 12 PERMAFROST 25-30 years ago (~1986-1991), sometimes can see permafrost MELT (LAKE underneath, when the permafrost melts from beneath the SHORES) mudslides start, happens mostly where the sun is beating (n=15) down (shores most exposed to sun, noted shores facing east and southeast), for most part seems to be more every year •!Big pieces of land falling into lakes and rivers, seeing big 14 black landslides, trail at Angus Lake (fished lake close to
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Sachs Harbour) falling into lake, lake is going to connect to the Sachs River soon and drain into ocean due to erosion and permafrost melt •!Did not appear that erosion sediment entering study lakes 7 was affecting fish or water, water remained clear as always •!Fish Lake and Raddi Lake (other fished lakes) both have 3 mudslides, Raddi Lake now has a big creek coming out of shore into lake, slides at Raddi Lake have happened to the same degree every year since they started ~15-22 years ago (started ~1994-2001), but slowed down in recent years LAKE ICE AND •!Lake ice has always been 6-8ft thick, has stayed the same 13 SNOW COVER ON even with the warmer weather, candle ice still forms in LAKES spring when melting (n=18) •!Ice melts earlier and more rapidly, takes longer to form for 9 past 15-20 years (started ~1996-2001), changed by at least a month, also takes longer to reach full thickness, in 1960s used to drive dog teams over lake ice and snow on land until June 29th now begins melting in late May •!Used to be an ice-chunk moving around with the wind in the 1 centre of study lakes all summer, this is not the case anymore, ice would not completely melt long ago, changes started 15- 20 years ago (started ~1996-2001) •!Up to 13-15 years ago (up to ~2001-2003) always 2ft of 5 snow on ice, now all glare ice because stronger winds blow snow away, ice used to be thinner in areas where there was snow cover •!If there is a lot of wind, ice does not stay long on the lakes in 1 spring OCEAN ICE •!Every year the ice is different, however in past 20-25 years 11 (n=13) (since ~1991-1996) ice has generally been thinner, melting earlier and more quickly in spring, takes longer to freeze in fall, bay used to freeze in September or October now December •!Used to have large icebergs and ice floes year-round up to 9 1950s and 1960s, some icebergs were high and large with lots of little freshwater “lakes”, have not seen since ~1999- 2000, now no more icebergs, in 2006-2008 would see icebergs along the coast from the community but would melt by end of day, no more ice in Thesiger Bay in the summer •!Less multiyear ice over the past 5 decades, now none in 6 summer, just cubes and small chunks of ice in Thesiger Bay and open ocean beside southwest Banks Island •!More movement of ice sheet because not as much grounded 5 multiyear ice to hold it in one place, all left ~16 years ago (since ~2000) •!Less ice floes, used to come from northwest now come from 6 east, used to hunt seals from ice floes and sometimes drift out but nothing like that anymore, 2007 quite a few ice floes, none in summer anymore since ~1999 •!Thickness of landfast ice decreasing, now only 5ft thick for 5 10-20 miles out from coast, more recently lack of landfast ice (cracks close to coast) affecting travel
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•!Never used to see open water (cracks) near the community 7 in the spring, now getting 1.5-2.5ft wide cracks, February 5 2008 ocean was open right to the coast, recently observe cracks that stay open all winter •!Local environmental conditions affect sea ice: 5 •!In El Niño year no ice in the ocean (1997-98) •!Winds affect it now so it is constantly moving and cannot freeze up, ice stays longer in spring when less wind •!Currents and waves are strong and can take away the ice even when there is no wind •!More open water (no ice coverage) in spring, summer and fall also creates rougher water (more waves) OCEAN WATER •!Ocean was saltier prior to 15-20 years ago (prior to ~1996- 1 SALINITY 2001) (n=2) •!When the ocean has a lot of salt it is harder for it to freeze 2 and it gets like jelly, when less salt seals sink more easily OCEAN WATER •!Water is warming up because there is not as much ice in the 9 TEMPERATURE summer, 2007 kids started playing and swimming on coast (n=11) because water is warmer •!Anadromous Arctic Char in nets used to last up to 12 hours, 3 now get soft more quickly because of warmer water OCEAN WAVES •!Larger waves and increased rough water, spit at outer edge 4 (n=7) of Thesiger Bay broken into three parts from increased wave intensity (never happened in living memory), El Niño year (1998) ocean was really rough with waves all summer •!Waves getting bigger or stronger on coast when wind and 7 storms started getting stronger, and loss of multiyear ice (which used to block or slow waves), ~20-25 years ago (since ~1991-1996), new areas of coastline are getting covered in water and washed out from the larger waves, boats on the shore are almost being washed away, strong winds affecting waves pulling out and moving fish nets PERMANENT •!Erosion and permafrost melt resulting in permanent changes 6 CHANGES TO to landscape and hydrological regime (see above) FRESHWATER •!Two lakes near the coast drained into the ocean, in one all 7 LANDSCAPE that remained was a small amount of water and white (n=9) freshwater bivalve shells, one of the lakes with fish broke and drained into the ocean ~20 years ago (~1996) in the middle of winter because the pressure of lake blew out the ground and permafrost RAIN •!Heavier rains in spring, summer and fall, increased number 10 PRECIPITATION of cloudy days, not same every year but general increase, (n=12) when growing up no rain (up to 1970s), at most would rain once or twice in the summer or no rain at all, would be sunny without clouds most of the summer •!In 2000 dry all summer then heavy rains in fall, a lot of rain 2 in 2007, not much rain in 2008 or 2010 •!Starting ~17 years ago (starting ~ 1999) ground would stay 4 wet until winter due to heavy rains and stay soft (muddy) with lots of little puddles in some years, then it would freeze and muskox died because could not get through ice to food, have seen hard frozen ground making it difficult for travel and animals (muskox and foxes) to eat ~ 2004
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•!One time rain-on-snow event in January caused mass 4 muskox and caribou die-off (100s) due to frozen surface and animals could not reach food believed to be in 1980s
RIVER FLOW AND •!Creeks from hills coming into non-landlocked lakes do not 3 ICE have much flow anymore (n=11) •!Rivers running first part of May, used to travel to the end of 9 June on the ocean, started ~15 years ago (started ~2001), warmer water in rivers •!Rivers are a lot lower now summer through fall, used to be 9 places could not cross while traveling but can now, this is especially noticeable when the snow melts early in the year, started ~15 years ago (since ~2001) SNOW •!Amount of snow precipitation is different each year, in 8 PRECIPITATION general there is less snow falling, often winds just blow it (n=14) away, years with bare frozen ground in recent years, in 1960s used to be able to drive dog teams over lake ice and snow on land until end of June now lucky to be traveling in June because snow is already melted and ground is too soft •!Snow melts much more quickly and earlier in spring, now 8 the snow can melt in one day •!Hardly any snowy blizzards now, just strong winds with 5 little snow, increased winds melt the snow more quickly •!Different type of snow now, harder and doesn’t form drifts 5 like long ago, used to have snow drifts that would reach to the top of homes, hasn’t happened since ~17 years ago (since ~1999) •!In winter 2008 not much snow, 2009 lots of snow, 2010 4 snow melted a little right after it fell and then refroze and made the snow really hard, same ~47 years ago (~1969) made it hard for caribou to get their food, coming right into town and not scared of humans because they were starving •!Lake allochthonous input lessened with decreased amounts 2 of snow STORMS •!Increased frequency and intensity of storms, including rain 5 (n=11) storms and wind storms •!Started getting thunder and lightning storms with rain and 8 snow, started ~1986 and increasing in frequency •!Less blizzards (blowing snow) and more wind storms 5 without snow in winter SUN •!When the sun goes down it gets dark right away, long ago it 3 (n=7) used to still be light for a while after the sun sets, however over the course of the night it is brighter, noticeably changed since 1940s •!Sun getting bigger and hotter/stronger, never used to get a 4 sunburn in the summer, increased intensity earlier in the year WEATHER •!Weather is very different since 1950-1960s, weather really 7 (GENERAL) started changing in ~1998 (n=9) •!Inclement weather has gradually been becoming worse, in 3 the past used to be stable for days or weeks, can no longer predict the weather as it changes within a day •!Seasons are changing, spring is shorter, summer is longer 2
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WIND •!Winds much stronger since early 1990s, especially in spring 13 (n=13) and fall and increased number of windy days, winds causing bigger waves on the ocean, snow used to blow off ground in winter but now more wind without snow too (less blizzards) •!Prevailing east winds, but more south-southeast winds now 2
3.3.3.1 Local Climatic Conditions
IKO included information on major changes in general weather conditions over the past seven decades, however, changes became more pronounced around 1998. Local experts (Table 2, n=9/18) indicated changes in the seasons (shorter spring and longer summer), inclement weather that is getting worse, and increasing rapid changes in the weather. Elder Roger Kuptana shared the following observation: “When I was growing up, my father used to predict the weather for the next two or three days, now you can’t. You wake up and just kind of look at the sky and just kind of shrug your shoulders and wonder.”
A little over half of the local experts (Table 2, n=11/18) noted that the local air temperature had increased in all seasons since the late 1980s to early 1990s. Larry
Carpenter discussed the change in winter temperatures, “We don't get very many -40s
[days], although [in winter 2008-2009] we have had -30s to -40s, but the past years before this year, 10 years I’d say, we are lucky to get one week of -40 to -45. Even -30 these last few years there is very few [days that are that cold]. Used to be springtime when […] it would reach -20 to -25. That was nice spring weather. Now that’s almost winter to us.”
Roger Kuptana also noted “Weather-wise, it’s changed a lot. When I was growing up, it was so cold when we used to trap [foxes] that even the kerosene, it used to turn like an almost like
Jell-O it was so thick…that’s from the freezing at 60-70 below at least anyways. Nowadays it’s not very cold anymore compared to what it was.” John and Donna Keogak explained the
! ! 136! changes in summer temperatures, “The temperature is hotter, every year is a bit warmer, but in the [mid to late 2000s], it’s like we were gonna cook at the beginning of July.”
The weather recorded by the Sachs Harbour Environment Canada weather station changed between 1970 and 2011. Linear regressions of annual temperatures over the 42- year period demonstrated a significant 2.5°C increase in mean temperatures (r2 = 0.27, p <
0.01), a significant 6.4°C increase in minimum temperatures (r2 = 0.39, p < 0.01), and no significant change in maximum temperatures. Increases in temperatures were much higher in winter months than in summer (Figure 3). Increases in monthly mean, maximum and minimum air temperatures over all years were highest in December over the time-series, demonstrating significant (r2 > 0.36, p < 0.05) increases of 5.7°C, 5.1°C, and 8.1°C, respectively. The annual GDD0 was on average 458 (±21 S.E.), and between 1970 and
2011 the GGD0 increased by 82 degree days, with a major increase occurring in the past 10 years (Figure 4).
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Figure 3. Daily temperatures for the months of July (top) and December (bottom) as recorded by the Sachs Harbour Environment Canada weather station on Banks Island NT between 1970 and 2011.
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!
Figure 4. Growing degree days over 0°C (top) and total annual precipitation (bottom) as recorded by the Sachs Harbour Environment Canada weather station on Banks Island NT between 1970 and 2011. The solid lines with points are the observed data, and the dotted lines are fifth degree polynomial regression lines added for illustrative purposes
(Environment Canada, 2013).
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Over half (Table 2, n=12/18) local experts explained that there were heavier rains and more rain events in recent decades. When some of the experts were growing up (up to
1960s – early 1980s), and prior to that, there was no rain. It might have rained once or twice in the summer, and it would be sunny without clouds for most of the summer. Elder
Geddes Wolki recalled a large rain event in the late 1990s that really stood out to him and why: “It pour, it keep raining steady even the ground get soft, never get dry anymore. Long ago when there was lots of medicine men, [they would say there was] always good weather in Sachs Harbour, so medicine man sometimes ago get good weather from Sachs Harbour, they say.” Most local experts (Table 2, n=14/18) said that the amount of snow is different each year, however, there is less snow falling with an increased amount of bare ground with the wind blowing it away, smaller and less snow drifts and banks, since ~1997. This was particularly noticeable in spring when harvesters were used to traveling by snow machine to head out goose hunting: “Well, spring time, [for] so many springs now you can't even go out anymore, you can't go far, you can’t go on the land ’cause it’s melting. I think we're getting at least two weeks earlier melt” (Larry Carpenter). The analysis of the climate station data showed total annual precipitation was generally high in the late 1990s and early 2000s, and has more recently declined (Figure 4).
The logistic model predicting whether precipitation fell as rain or snow depending on the mean daily temperature was highly significant (p < 0.0001, Odds Ratio = 0.43 with a 95% Confidence Interval of 0.39–0.46) suggesting that precipitation surpassed a 50% probability of falling as rain if the mean daily temperature was greater than -0.84°C (Figure
5). Linear regressions of predicted versus observed values from 1970 to 2006 showed that rain was only slightly underestimated (y=0.91x, r2 = 0.94, p<0.0001) and snow was only
! ! 140! slight overestimated (y=1.14x, r2 = 0.84, p<0.0001) by the model. Using the predicted values of precipitation as snow, the amount and number of days of snowfall greatly decreased following 2004 from averages of 84 mm to 44 mm and 64 days to 41 days, respectively, while the amount and numbers of days of predicted values of precipitation as rain remained generally at 56 mm and 27 days across the time-series (Figure 6). Years of high annual rainfall (i.e. > 107 mm, the 95% confidence interval) were found in 1998 and
2005.
! ! Figure 5. Probability of observed levels of precipitation on Banks Island falling as rain at a mean daily temperature generated from a logistic regression (line) of observations of rain or snow (points) at daily temperature as recorded by the Sachs Harbour Environment
Canada weather station on Banks Island NT between 1970 and 2011.
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!! Figure 6. Total annual precipitation (top) and total annual days of precipitation (bottom) as predicted to have fallen as rain (dashed line) and snow (solid line) using total precipitation and mean temperature data as recorded by the Sachs Harbour Environment
Canada weather station on Banks Island NT between 1970 and 2011.
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3.3.3.2 Lake Ice
All interviewed local experts had IKO of lake ice (Table 2, n=18). Most local expert interviewees (Table 2, n=13/18) shared environmental observations on lake ice and snow cover, pointing out that the thickness of lake ice had remained the same at 6-8 ft (1.8-2.4 m). However, half indicated ice off and on dates were earlier in the spring and later in the fall, so the open water season had been extended by several weeks over the past 15-20 years
(since ~1996-2001, Table 2, n=9/18). Elders Martha and Frank Kudlak indicated that there used to be ice in the lakes all summer, with a large ice-chunk that would move around with the wind. This is not seen anymore. Also, snow cover on the lake ice used to be 2ft (~0.6 m) thick but this had decreased and now mostly glare ice is found (due to less snowfall and stronger winds). Overall, satellite data generally matched the ice phenology model (Shuter et al. 2013) for the length of the ice-free period with an average of a 9-day discrepancy and a root mean squared error of 12 (Figure 7). The length of the ice-free period on the three lakes was estimated by the ice phenology model to average 82, 99 and 106 days for Capron,
Kuptan and Middle lakes, respectively (Figure 8). One important discrepancy was that the ice phenology model assigned different ice-free periods to Kuptan and Middle lakes, yet, observations from satellite imagery typically assigned the same ice-off and ice-on dates to both lakes.
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120 110 100 90 80 70
Satellite Observations Satellite 60 50 50 70 90 110 Shuter et al. (2013) Model !
Figure 7. The length of the ice-free period (in days) on Capron, Kuptan and Middle lakes,
Banks Island NT calculated from Radarsat and Landsat imagery of ice cover compared with the results from the ice phenology model (Shuter et al., 2013). The black line is the
1:1 line.
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140
130
120
110
100
90
80
Days!of!Ice!Free!Water 70
60 1970 1980 1990 2000 2010
Year !
Figure 8. Length of ice-free periods on Capron (blue – solid line), Kuptan (red – dashed line) and Middle (green – dotted line) lakes, Banks Island NT, estimated using the Shuter et al. (2013) empirical forecasting model that predicts freeze and thaw dates on Canadian lakes.
3.3.3.3 Erosion and Melting Permafrost of Coast and Shores
All local experts had extensive IKO of marine coastal erosion and permafrost melt
(Table 2, n=18/18), whereas the majority of experts had IKO of erosion and permafrost melt along lake shores (Table 2, n=15/18). Mudslides along the coast were first noticed in the
1980s and mudslides, melting permafrost and erosion have been increasing on both ocean coasts since the late 1980s and lake shorelines for the past 25-30 years (since ~1986-1991), especially in locations exposed to sunlight. Elder Roger Kuptana shared the following knowledge on both the marine coast and lake shores during his interview in 2010, “Oh there’s
! ! 145! a great deal of erosion going on. Towards the east coast there, the erosion is really coming down at alarming rates. What I grew up with, we [didn’t see any erosion] for 40 years, now within the last 10, 15 years...the mud is sliding, the permafrost is melting, even along the coast. I think Angus Lake [lake fished near the community] is one good indicator of what’s going on. It’s just a matter of time before that lake goes into, spills into the ocean there. In the last little while, [the erosion and mudslides are] every year now.” Despite these observations, no noticeable changes to water clarity or quality were noted in the study lakes.
3.3.3.4 Ocean Ice
Elder Edith Haogak was adamant when interviewed in 2010, and in subsequent validation meetings up to early 2015, that the sea ice was different every year. However,
Edith (through a translator), along with many interviewed local experts (Table 2, n=13/18), had observed major changes in the ocean over the past 20-25 years (since ~1991-1996).
These changes included that the ice has been thinner, melted earlier and took longer to freeze, that there were no more icebergs or multiyear ice, and no more ice in the summer.
“In 2008 we had nothing. And the only ice that we were getting was through that strait there that was coming right past. You know, the ice that moves in the, that McClure Strait? It was coming outta there from the north. But it was just floating past here. No more big patches of ice out there anymore. I mean the seal hunting and that is starting to… getting kinda tough
'cause there’s no ice up there all the time” (John Lucas Sr.). Larry Carpenter shared, “You notice there's no icebergs…usually when we have freeze up in the fall there's usually some ice out there, icebergs, and from there it would make more solid ice.”
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3.3.4 Arctic Char Growth and Biotic Environmental Conditions
The majority of local experts (Table 3, n=15/18) had IKO on landlocked Arctic
Char size and growth, observing that on average they remain the same size, but that they are bigger (longer and fatter) in “good weather years”. As elder Edith Haogak shared “[Fish in lakes] follow the weather…long, warm summer, all those bugs [emergent insects] are plentiful on the water, and then the fish eat good. And if it’s a bad [cold] summer, then there’s not much of that food for the fish. So, those would be the leaner years.”
Table 3. List of topics from Inuvialuit knowledge and observation on Arctic Char size and biotic environmental conditions with the potential to predict changes in Arctic Char growth, with number of Sachs Harbor, Banks Island NT local experts reporting observation (local experts interviewed: n=18).
Thematic Codes of List of topics of Inuvialuit Knowledge and Observations of Number of Arctic Char Arctic Char qualitative condition and diet interviewees qualitative reporting condition and diet observation (n = total number of local experts who provided IKO for thematic code) ARCTIC CHAR •! Arctic Char size has not changed very much on average in 15 (LANDLOCKED) living memory, although some years larger landlocked char SIZE AND (longer and/or fatter) are harvested, in other years smaller GROWTH ones (n=15) CHANGES TO FISH •! Long warm summers result in more “bugs” in lakes (insects 3 GROWTH IN hatching) and bigger char, cold summers there is less for the CORRELATION char to eat WITH •! Arctic Char in Middle Lake declined in size and numbers 5 ENVIRONMENT then recovered the following years (1997-1998) years when (n=10) major climate changes occurred (see Table 2: warmer air temperature, increased precipitation, stronger winds, decreased sea ice, longer lake ice-free season) •! Mud from permafrost melt and erosion is blocking creeks 9 running into lakes where char used to be seen feeding in spring, becoming harder to catch fish in two non-study lakes with erosion on banks, Angus Lake (fished lake near Sachs Harbour) is getting wider as erosion is filling it up and it is believed fish are stressed with deformities and cysts because the lake was always changing shape as no changes to water quality have been observed
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•! Searun Arctic Char getting bigger with warmer weather, in 3 recent years have been seeing much larger searun char or none at all, low river levels have resulted in low river water levels and the searun char cannot get back to the lake to overwinter •! Whitefish started entering Thesiger Bay (from lakes) when 1 the weather started to get warmer •! More salmon arriving from elsewhere in bay and mouth of 3 Sachs River with warmer ocean water CHANGES IN •! ~ 25 years ago (~1991), used to have much higher catch-per- 3 NUMBERS OF unit-effort of Arctic Char in the lakes, used to be every cast, KNOWN SPECIES some believe linked to increased fishing pressure on some (n=15) lakes •! Almost no searun Arctic Char in coast near community in 6 past (~2007-2015), natural cycle noted of high and low numbers depending on the year (cycles ~ every 4-5 years), but 2011 first time not enough to harvest, however on average Arctic Char that are harvested are bigger (longer) than in the past, ~1999 searun char declined at same time saw lots of salmon, happened again in ~2007 •! Less “cod” in coastal waters (likely Arctic* and Greenland 1 Cod* based on specimen photo identification by fisheries scientists) •! First salmon caught in 1991, consistently getting more 11 “salmon” (described as Chum* (Dog), Pink*, Coho* and Sockeye* salmon) in coastal waters in last 10-15 years (since ~2001-2006), numbers gradually increasing (a late elder used to share stories of getting 1-2 salmon over the summer in the 1970s), caught a few in the 1990s, hardly any in ~2009-2011, sometimes eggs are pouring out of the salmon caught, some have a kype •! Caught Lake Whitefish* in nets in Sachs River estuary and 1 along coast near community in summer, ~year 2007 •! Caught Lake Trout* in ocean in summer, ~ year 2000 1 •! More “herring” in coastal waters (not able to identify to 11 species) in past 15-20 years (since ~1996-2001) •! Many more small silvery fish in coastal waters (likely 2 Capelin* based on photo identification by local experts), schools are getting bigger, one local expert said used to be lots long ago (1960s) •! More “flatfish” (also referred to locally as “Flounder”, not 4 able to identify to species) in Thesiger Bay •! Major increase in jellyfish in coastal waters in 2006 only 1 •! A lot of dead “little pink shrimp” washed up on coast July 2 2007 where they died and rotted •! A lot of seals in the Sachs River in summer 2014, never seen 2 before •! Beluga Whales in coastal waters near community (used to 4 see in offshore waters every 5-10 years), saw one near coast ~1999, started see many near coast in 2008-2009 and now getting consistently every year (some think because main pack ice is gone), nearly 100 throughout summer in 2014 (elders had never seen this before)
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•! Muskox numbers going down and Parry Caribou numbers 2 going up in recent years •! Unidentified songbirds no longer come around in 7 spring/summer; less shorebirds; more Tundra Swans, Lesser Canada Geese, Lesser Snow Geese, White-Fronted Geese (in last 1-1.5 decades); mass die-off eider ducks (spring 2013) NEW SPECIES •! Killer Whales are new to region, two sightings of 3 and 2 in 1 OBSERVED summer 2014 (n=11) •! In ~ 1998 lots of red amphipods (“sea lice”) and jelly balls 3 with black dots in them washed up on shore, same year very low number of searun char and had lots of salmon, in 1999 or 2000 a lot washed up on shore including little dead crabs and all different types of dead organisms from the ocean, was not a result of a big storm •! Merganser Ducks, Yellow Leg Geese, unidentified 8 songbirds, sometimes see them show up in the middle of winter, Swallows started showing up ~15 years ago trying to get into their tents to keep warm in spring, Ravens, never used to have them in the past, Barn and Great Horned Owls, Golden Eagle •! New “Bugs” plus flying ants, beetles with long antennae 8 (referred to as “hair eaters”, some believed that these insects were transported on the annual barge delivery, likely a longhorn beetle), June bugs, wasps and hornets (some are believed to be brought by barge and planes, other on the wind) •! Polar-Grizzly Bear crosses (“Polar Grizz”), first one 1 captured on Banks Island 2006 * Arctic Cod = Arctogadus glacialis, Capelin = Mallotus villosus, Chum Salmon = Oncorhynchus keta, Coho Salmon = Oncorhynchus kisutch, Greenland Cod = Gadus ogac, Lake Whitefish = Corregonus clupeaformis, Lake Trout = Salvelinus namaycush, Pink Salmon = Oncorhynchus gorbuscha, Sockeye Salmon = Oncorhynchus nerka.
Growth increments determined from back-calculation for char captured in 1992 and
1994 from Capron, Kuptan and Middle lakes allowed for extension back in time to years
1970, 1970, and 1977, respectively. Growth increments determined from back-calculation for char caught in 2008, 2009, 2010, 2011 and 2012 from Capron, Kuptan and Middles lakes allowed for extension back in time to years 1993, 1985 and 1988, respectively. Von
Bertalanffy growth curves were estimated for the number of char included in the capture and back-calculated data sets (see Figure 9; Appendix 2; Table 4). Spring sampling of subsistence harvest at some of the study lakes produced useable otoliths in 2011 (Middle n=10) and 2012 (Kuptan n=12, Middle n=4). While this data could be included in the back-
! ! 149! calculated von Bertalanffy growth curves, it could not be used for the length at age of capture growth curves because the fish were caught earlier in the year (May) than all the other char, which were caught in the late summer (July-August).
Table 4. Number of Arctic Char included in the capture (length and age at time of capture) dataset and the number of Arctic Char used in the back-calculated dataset per year and lake on Banks Island NT.
Year Capture Dataset Back-Calculated Dataset Capron Kuptan Middle Capron Kuptan Middle 1992 - 29 - - 27 - 1994 132 71 51 80 56 30 2008 28 - 206 26 - 41 2009 - 56 50 - 47 43 2010 10 - - 7 - - 2011 12 14 13 11 14 23 2012 - - - - 12 4 !
! ! 150!
A! B!
C! D!
!
Figure 9. Von Bertalanffy growth curve 99% confidence intervals for Arctic Char populations in Capron (blue – solid lines), Kuptan (red –dashed lines) and Middle (green – dotted lines) lakes from fish collected in the 1992-1994 (i.e. left panels: A and C) and 2008-
2012 (i.e. right panels: B and D) survey periods, and data analyzed using the char lengths and ages at time of capture (i.e. the top panels: A and B) and the lifetime size and ages of a subset of captured char analyzed using otolith back-calculation (i.e. the bottom panels: C and D).
! ! 151!
During 1992-1994, Middle Lake char grew to the largest fork length, followed by the Kuptan Lake population and last, the Capron Lake population. In the 2008-2012 period, all three populations had relatively similar growth curves to the 1992-1994 period, however char from Middle Lake were not as long and the char from Capron Lake had an increased growth rate. Scrutinizing the 99% confidence intervals of the growth curves for overlap gave similar results to those generated from testing the model parameters between lake pairs following Ogle’s (2015) method (Table 5). During 1992-1994, the asymptotic maximum lengths were significantly different among lakes, the Brody growth co-efficients
(K) were narrowly distributed between 0.008 and 0.12, and generally similar across lakes, and the size at age 0 (t0) was only shared between Middle and Capron lakes. In the 2008-
2012 dataset, Kuptan and Capron lakes shared the same von Bertalanffy growth parameters, whereas Middle Lake remained statistically different from the other two lakes. Note that the wider 99% confidence intervals exhibited in the growth curves generated from length and age data from caught fish (Figure 9A and 9B) is due there being fewer data points available for the non-linear regression compared to the back-calculated dataset (Figure 9C and 9D).
! ! 152!
Table 5. The best model as determined by pairwise comparisons among the Arctic Char growth curves estimated from lengths and ages from Capron, Kuptan and Middle lakes,
Banks Island NT in the 1990s and 2000s survey periods. Asymptotic maximum length
(L∞), Brody’s growth co-efficient (K) and the theoretical fork length at an age of 0 years
(t0) are given for the best model for each comparison and the standard error of the parameter estimate is in parentheses.
Lake-Specific Growth Curve Parameters Comparison Best Model Lake L∞ K t0 1990s Middle vs Kuptan 472 0.12 0.91 Kuptan (16.8) (0.01) (0.19) General Model Middle 614 0.08 0.13 (43.5) (0.01) (0.25) Kuptan vs Capron 426 0.51 Capron (12.4) 0.11 (0.19) Common K Kuptan 489 (0.01) 0.76 (13.2) (0.15) Capron vs Middle 583 Middle Common K (20.6) 0.09 0.21 and t0 Capron 459 (0.007) (0.17) (18.1) 2000s Middle vs Kuptan 429 0.17 Kuptan (10.3) (0.02) -0.67 Common t 0 Middle 598 0.07 (0.17) (35.7) (0.01) Kuptan vs Common Capron 430 0.20 1.41 Capron Model Kuptan (7.37) (0.02) (0.52) Capron vs Middle 599 0.07 -0.67 Middle (39.8) (0.01) (0.19) General Model Capron 420 0.21 1.51 (16) (0.04) (0.68)
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3.3.4.1 Arctic Char Maturity
The logistic regression of field estimates of maturity with age were highly significant (p < 0.0001, Odds Ratio = 1.76 with a 95% Confidence Interval of 1.61–1.95) suggesting that 50% of the population from all three lakes matured at 11 years of age
(Figure 10). Age at maturity did not differ among lakes or time periods if the data was analyzed by logistic regression in subsets. Gonad mass was available for some 1992-1994 samples, and all 2008-2012 fish samples, and demonstrated that gonad mass generally increased after age 10 (Figure 11).
!
Figure 10. Probability of Arctic Char reaching maturity at age from a logistic regression fit of a curve (line) of field observations of maturity at age (points) in Capron, Kuptan and
Middle lakes, Banks Island NT.
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Figure 11. Natural logarithm of gonad mass at age from Arctic Char caught in Capron,
Middle and Kuptan lakes, Banks Island NT.
3.3.5 Environmental Conditions Affecting Arctic Char Growth
Just over a quarter of the IKO local expert interviewees (Table 3, n=5/18) explained there had been a decrease in Arctic Char size and abundance in Middle Lake in the year prior to observations of major climate changes (1997-1998). The IKO suggested recovery of the char population in the following year that saw warmer air temperatures, significant increases in rain and intensity of winds as well as a decrease in snow and longer ice-free season on the lakes, correlated with the local expert IKO that fish grew bigger in “warmer weather years” and led to the decision to examine these parameters in the SEKO analyses.
3.3.5.1 Linear Mixed-Effects Models Analysis
Linear mixed-effects model analyses using lme4 revealed overall that the growing degree days above 0 °C (GDD0) was a positive predictor of fish growth in both age-specific annual growth (in mm) and relative growth as response variables (see Table 6 and 7 for
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model statistics). GDD0 was only a slightly stronger predictor of fish growth than the length of the ice-free period but much stronger than the total annual precipitation. With age- specific annual growth (in mm) as the response variable, char from ages 1 to 14 were also significant predictors of annual growth (older fish showed no significant relationship between age and growth). The Lake parameter was significant for only the relative growth model (ΔAIC = 226.3, χ2 = 232.3, df = 3, p < 0.0001), which included the Year:Lake interaction term which explained 15% of the residual variation. Char maturity was only a significant predictor for relative growth in Middle Lake (ΔAIC = 42, χ2 = 46, df = 2, p <
0.001), and so the dataset was further subdivided by pre- and post-maturation. Age and
GDD0 explained between 74% and 82% of the variation in the age-specific annual growth models, in both the full model including all lake data, and the lake-specific models.
Including the Lake parameter in the full model predicting relative growth led to the poorest model fit (i.e. marginal R2 = 0.05, conditional R2 = 0.29), yet this was not found in the lake- specific models in which GDD0 explained 38% to 43% of variation in relative growth. The parameter estimate for the effect of GDD0 were largest in Capron Lake in both the annual and relative growth models, and similar among Middle and Kuptan lakes.
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Table 6. Parameter estimates and marginal and conditional R2 from best fitting linear mixed-effects model analysis of back-calculated growth in Arctic Char from Capron,
Kuptan and Middle lakes, Banks Island NT.
Lakes Response Fixed Random Interactions Marginal Conditional Variable Effects Effects R2 R2 Annual GDD , Fish, All 0 Year:Age 0.79 0.85 Growth Age Year Relative GDD , Fish, Year:Age, All 0 0.11 0.27 Growth Lake Year Year:Lake Annual GDD , Fish, Capron 0 Year:Age 0.74 0.87 Growth Age Year Annual GDD , Fish, Kuptan 0 Year:Age 0.82 0.84 Growth Age Year Annual GDD , Fish, Middle 0 Year:Age 0.79 0.83 Growth Age Year Relative GDD Fish, Capron 0 Year:Age 0.43 0.82 Growth Year Relative GDD Fish, Kuptan 0 Year:Age 0.38 0.75 Growth Year Relative GDD , Fish, Middle 0 Year:Age 0.39 0.75 Growth Maturity Year
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Table 7. Parameter estimates of Growing Degree Days over 0 °C from a linear mixed- effects model analysis of back-calculated growth in Arctic Char from Capron, Kuptan, and
Middle lakes, Banks Island NT. Note: The t-value refers to the parameter, and ΔAIC refers to the comparison among the contrasting models (i.e. GDD0 with length of ice-free period for the all lakes models, and GDD0 with Total Annual Precipitation for the lake-specific models).
Response Lakes Parameter Estimate t-value ΔAIC Variable Full models with Lakes as a fixed effect contrasting GDD0 with lake ice All Annual Growth GDD 0.0006 3.7 0 2 All Annual Growth Ice 0.004 2.9 All Relative Growth GDD 0.0004 4.3 0 2 All Relative Growth Ice 0.004 3.3 Lake-specific models contrasting GDD0 with precipitation Capron Annual Growth GDD0 0.023 5.1 9 Relative Growth GDD0 0.002 20.8 9 Kuptan Annual Growth GDD0 0.0058 3.2 6 Relative Growth GDD0 0.0011 5 5 Middle Annual Growth GDD0 0.0079 2.5 10 Pre-maturation Relative Growth GDD0 0.0012 4.5 8 Post-maturation Relative Growth GDD0 0.0011 3.4 8
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!
Figure 12. Relative growth (annual growth divided by the average annual growth for all fish of that age from the lake population) across all ages per year for Arctic Char populations in Capron (blue –top panel), Kuptan (red – middle panel) and Middle (green – bottom panel) lakes, Banks Island NT.
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3.3.6 Triangulation of Knowledge Bases
Triangulation of the IKO and SEKO information generated through the qualitative and quantitative methods of this study (Table 9) was conducted considering conceptual, spatial and temporal scales. The conceptual scale considered environmental conditions or changes with the potential to affect Arctic Char growth. The spatial scale considered the local environment surrounding southwestern Banks Island including Sachs Harbour, the study lakes, and the surrounding ocean environment. The temporal scale considered trends over time within a relatively similar time period (observations over several decades). Only knowledge bases that contained information collected at least at two similar scales were triangulated. Triangulation was conducted to identify topics for which the knowledge bases enriched, corroborated, contradicted, or were inconsistent with one another. For all parameters, the knowledge bases enriched or corroborated one another. The triangulation resulted in no instances where knowledge bases contradicted or were inconsistent with each other, however, limited information was available for several phenomena studied.
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Table 8. Matrix triangulating Inuvialuit knowledge and observation and scientific ecological knowledge and observation relating environmental conditions to Arctic Char growth on southwest Banks Island NT.
Area of Inuvialuit Knowledge and Observation (IKO) Scientific Ecological Knowledge and Observation Results of Knowledge (SEKO) Knowledge Base Comparisons Local Climate and Abiotic Environmental Conditions
Air •!Warmer in all seasons since late 1980s to early •!This Study: Mean temperatures on average rose by Knowledge Bases Temperature 1990s 2.5°C between 1970-2011, and a 6.4°C increase in Corroborate minimum temperatures •!This Study: Between 1970 and 2011 the GGD0 increased by 82 degree days •!Averaged winter temperatures have increased •!This Study: December temperatures did not drop from -40 to -70˚C to -20 to -30˚C for ~ 2 decades below -30˚C from 2000-2011 (Figure 3) (since ~1996) Condition of •!Active layer deeper in recent time and ground •!No known environmental data at same scale IKO Enriches Ground absorbs more snow melt and rainfall (less going Lack of SEKO into lakes and rivers) •!Cracks developed, ground sliding over itself •!Ground used to stay frozen with snow on top until end of June, now melted by May
Erosion and •! First noticed melting permafrost and mudslides in •! No documented date when erosion and permafrost Knowledge Bases Permafrost late 1980s melt started in region Corroborate Melt (Coast) •! Increasing erosion along coast, beside community •! Lewkowicz, 1987: Sand Hills moraine of southwest used to be 90-degree cliff, now slumped and can Banks Island is extensively affected by backwearing walk down to ocean thermokarst in the form of ground ice slumps, most are initiated by coastal erosion, with the result that 75% of the land within 100 m of the coastline has been transgressed by slumps
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•! Erosion of banks worse over last ~17 years (since •! Manson et al., 2007: Changes to the Beaufort Sea ~1999), to east and southeast along the coast, shoreline [including near Sachs Harbour] occur due when it storms in summer the beach gets really to the effect of storms and rising relative sea level, muddy now during the open-water season (June to October) storm winds predominantly from the north-west generate waves and storm surges which are effective in eroding thawing ice-rich cliffs and causing overwash of gravel beaches •! When coastline started eroding late 1980s, also •! Manson et al., 2005: High concentrations of ground noticed more waves hitting banks ice along coast near Sachs Harbour, likely have an erosion regime such that several metres of erosion can occur in individual storms Erosion and •!Mudslides and erosion at non-study lakes started •!Qualitative in-field visual assessment during this IKO Enriches Permafrost ~15-22 years ago (since ~1994-2001), happening study: Limited SEKO Melt (Lake to the same degree every year since, but slowed •!Capron Lake shorelines have 5-10% of banks are Shorelines) down in recent years started eroding •!One non-study lake is going to drain into the Sachs •!Kuptan Lake shorelines have 50-70% of banks River soon due to erosion and permafrost melt are eroding •!Have not noticed changes to shores of study lakes, •!Middle Lake shorelines have 80-90% of banks have always looked as they do are eroding •!More mudslides and erosion starting each year, •!Lewkowicz, 1987: Long-term headwall retreat for first started 25-30 years ago (since ~1986-1991) slumps in southern Banks Island with different •!When the permafrost melts from beneath the orientations and ice contents can be estimated using mudslides start a model based on meteorological information, model •!Mudslides and erosion of wet soil happens mostly predicts headwall retreat of 11 m/a for a ground-ice where the sun is beating down on the shore (noted slump facing south and 8.8-9.3 m/a for one facing east and southeast) north, predictions are close to the maximum rates of retreat over a 10-year period as measured from aerial photographs •!Big pieces of land falling into lakes and rivers •!No known environmental data at same scale •!Did not notice erosion sediment entering the lakes affecting fish or water in the study lakes, water remained clear Lake Ice and •!Ice goes away faster and sooner, takes longer to •!This Study: Increase in the length of the open water IKO Enriches Snow Cover form for past 12-17 years (since ~1999-2004), season on lakes has been gradually occurring since Limited SEKO on Lake Ice changed by at least a month the mid 1980s (Figure 8) •!Used to be an ice-chunk that would remain in •!Porsild, 1950: Reported large lakes were ice-free on centre of lake all summer 17-22 years ago (prior to Banks Island in 1949, definition of “large” is not ~1994-1999), not anymore provided
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•!Lake ice always been 6-8ft thick •!No known environmental data at same scale! •!Ice takes longer now to get to 6ft thick •!Prior to 12-15 years ago (prior to ~2001-2004) used to always have 2ft of snow on the ice, now all glare ice, ice used to get thicker in areas with snow cover Ocean Ice •! Every year the ice is different, in general is has •! Harwood et al., 2012: In the Beaufort and Knowledge Bases been thinner starting ~20-25 years ago (started Amundsen seas observations over the last 40 years Corroborate ~1991-1996), melting earlier and more quickly, revealed large fluctuations in ice presence and takes longer to freeze thickness over intervals of years to decades, up to 2012 only small trends toward earlier ice clearance and longer open water seasons •! No more ice in the bay in the summer, no more •! Babb et al., 2016: Record sea ice minimum in icebergs, have not seen for ~20 years (since Beaufort Sea September 2012, negative trends in sea ~1996), 2006-2008 would see icebergs along the ice concentration between 1979-2012 from June to coast around community but would melt by end October, change towards younger and thinner pack of day, El Niño year (summer 1998) no ice in the ice in Beaufort Sea ocean in summer •! Barber et al., 2012: Greatest declines in sea ice •! Less multiyear ice over past 5 decades, now none 2007–2008 in the southern Beaufort Sea (Canadian in summer just small chunks Sector and north of Alaska) from July–August Sea, •! Less ice floes, used to come from northwest now 2009 ice in region consisted largely of rotten ice or come from east, 2007 quite a few ice floes, floating ice in an advanced stage of disintegration, usually none in summer since ~1999 this contributed to significant loss of sea ice summer •! No more ice in Thesiger Bay in the summer of 2010 and 2011 •! Hutchings & Rigor, 2012: Both 2006 and 2007 saw an opening of the Eastern Beaufort multi-year ice pack near Banks Island, such a large ice retreat had only previously been observed in this region in 1988 and 1998, in 2007 conditions were so open, there was only 60% cover •! Galley et al., 2008: Massive reduction in summer sea ice extent in 1998, however rebounded to conditions prior to 1998, eastward shift in high- concentration perennial pack ice in south Beaufort Sea towards west coast of Banks Island, earliest occurrences of open water occurred in 1988, 1993 and 1998 (mid-June), and late refreeze in 1988 and 1998
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•! More movement of the ice in winter because not •! Barber et al., 2012: Ice charts for the western as much multiyear ice to hold it in one place Arctic illustrated a decline in the distribution of thick (grounded multiyear ice), all left ~15 years ago multi-year ice in the Beaufort Sea in September (~2001) 2010 , scarcity of thick multiyear ice, present only as thin bands dispersed throughout a region of relatively lower concentrations of first-year ice •! Thickness of landfast ice decreasing, February 5 •! Galley et al., 2012: Statistically significant trends in 2008 ocean was open right to the coast both onset (later) and breakup (earlier) dates of •! Never used to see cracks in the ice near landfast ice in area around southwestern Banks community in the spring, now getting 1.5-2.5ft Island and Sachs Harbour wide cracks •! Winds affect it now so it is constantly moving •! No known environmental data at same scale and can’t freeze up, ice stays longer in spring when less wind •! Currents are strong and can take away the ice even when there is no wind Ocean Water •!Water is warming up, can tell because no ice in •! No known environmental data at same scale IKO Enriches Temperature the summer Lack of SEKO •!Since 2007 kids started playing and swimming on coast because water is warmer •!Arctic Char in nets used to last up to 12 hours, now they start to get soft more quickly because of warmer water Ocean Waves •!Waves getting bigger on coast when wind and •! Manson et al., 2007: Changes to the Beaufort Sea IKO Enriches storms started getting stronger since no multiyear shoreline occurring due to the effect of storms and Limited SEKO ice ~20-25 years ago (since ~1991-1996) rising relative sea level, during the open-water •!After coastline started eroding and melting, also season (June to October) storm winds predominantly noticed more waves hitting coastline, coast getting from the north-west generate waves and storm surges covered in water and washed out from the larger which are effective in eroding thawing ice-rich waves shores, future forcing scenario include likely increased frequency of severe storms and likely overall increased wave energy •!More waves and rough water, spit at outer edge •! No known environmental data at same scale of Thesiger Bay broken into three parts from increased wave intensity •!In El Niño year (1997-98) the ocean was really rough with waves all summer
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Permanent •!Erosion and permafrost melt (see above) •! No known environmental data at same scale IKO Enriches Changes to •!Lower flow in river and creeks (due to lower Lack of SEKO Freshwater snowfall and increased active layer) Landscape •!Two ponds along the coast drained into the ocean ~20 years ago (~1996), one in the middle of winter Rain •!Not same every year, in general increase in rainy •!This Study: Increased amount rain falling between Knowledge Bases Precipitation and cloudy days 1990–2005, lowest rainfall since 1989 seen in 2007 Corroborate •!Starting ~1998-1999 ground would stay wet until (Figure 6) winter due to heavy rains, then freeze in winter •!This Study: Years of high annual rainfall (i.e. > 107 •!In ~2000 dry all summer then heavy rains in fall, mm, the 95% confidence interval) were found in a lot of rain in ~2006, not much rain in ~2008- 1998 and 2005 2010 •!Up to ~1970s there was no rain, maybe once or •!This Study: Number of days of rain did not change twice in the summer at most on average over time between 1970-2011, however no data to compare prior to 1970 •!This Study: Between 1970-2011, 1998 had the highest numbers of days of rain •!One-time rain-on-snow event in January caused •!Grenfell & Putkonen, 2008: Well-documented that mass muskox and caribou die-off (100s) due to severe winter rain-on-snow events (ROS) affect frozen surface and animals could not reach food ungulate herds and permafrost temperatures in the believed to be some time in 1980s Arctic, an ROS event took place on Banks Island in •!Hard frozen ground making it difficult for early October 2003 that resulted in the death of animals (muskox and foxes) to eat ~2004 20,000 muskox River Flow •!Creeks coming into non-landlocked lakes do not •! No known environmental data at same scale IKO Enriches and Ice have much flow anymore Lack of SEKO •!Rivers running first part of May we used to travel to the end of June on the ocean, started ~15 years ago (started ~2001) •!Rivers are a lot lower now summer through fall, used to be places could not cross while traveling but can now, this is especially noticeable when the snow melts early in the year since ~15 years ago (since ~2001) •!Warmer water in rivers Snow •!Amount of snow precipitation is different each •!This Study: Amount and number of days of Knowledge Bases Precipitation year, in general less snow falling, less days of snowfall greatly decreased following 2004 from Corroborate snow, lots of years with bare frozen ground, snow averages of 84 mm to 44 mm and 64 days to 41 days melts much more quickly and earlier in spring (Figure 6)
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•!This Study: Mean temperatures on average rose by 2.5°C between 1970-2011, and a 6.4°C increase in minimum temperatures •!Winter 2008-2009 lots of snow •!This Study: 2009 snowfall was highest since extreme low of 2004 (Figure 6) •!Snow too hard one year ~47 years ago (~1969) •!This Study: Weather station data shows high for caribou to get their food amounts of snowfall in 1970 (Figure 6) •!In 2010 the snow melted slightly after it fell and •!No known environmental data at same scale then refroze, made the snow really hard •!Hardly any snowy blizzards, just strong winds with little snow, wind now blows most of snow away •!More sleet in fall •!Different type of snow now, harder and doesn’t form drifts like long ago •!Used to have snow banks that would reach to the top of homes prior to ~17 years ago (~1999) Storms •!More storms, including rain storms and wind •! Barber et al., 2012: Increased cyclogenesis in the Knowledge Bases storms, storms are more severe Northern Hemisphere is accelerating storminess Corroborate •!Started getting thunder and lightning storms with •! Manson et al., 2007: In eastern Beaufort Sea near rain and snow, started ~1986 and increasing in Sachs Harbour peak storm-surge heights correlated frequency with peak storm wind speed, mean direction, •!Less blizzards (blowing snow) and more wind minimum storm air pressure and percentage of open storms without snow in winter water, a future forcing scenario includes increased frequency of severe storms possibly occurring later in the year Sun •!When sun goes down gets dark right away, long •! Inuit Knowledge and Climate Change Isuma Knowledge Bases ago it used to still be light for a while after the Video, 2010 (http://www.isuma.tv/inuit- Corroborate sun set, however over the course of the night it is knowledge-and-climate-change, 42:01 time stamp, brighter, noticeably changed since 1940s accessed May 14, 2016): Inuit in Nunavut communities hundreds of km apart noticing the sun sets further along the horizon in recent years, Dr. Ian Mauro (co-producer of the Isuma documentary) believes these observations are related to the polar mirage Novaya Zemlya •!Sun looks like it is getting bigger and feels like it •! Seabrook et al., 2011: In 2008 recorded several is getting hotter/stronger ozone depletion events within the atmospheric •! Never used to get a sunburn in the summer boundary layer, 10-40km off the coast of Banks
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Island (decreased ozone results in more UV radiation reaching the earth) Weather •!Weather is very different since 1950-1960s, •!Trenberth et al., 2003: For 1950–1998, the El IKO Enriches (general) started really changing in ~1998, seasons are Niño-Southern Oscillation accounts for 0.06°C of Limited SEKO changing where spring is much shorter and global surface temperature increase, teleconnections summer is longer contribute to the extensive warming over Alaska and western Canada regions 0–12 months later
•!Inclement weather has gradually been becoming •! No known environmental data at same scale worse, in past used to be stable for days or weeks, can no longer predict the weather as it changes within a day Wind •!Winds much stronger since 1990s, especially in •! Manson et al., 2007: Wind records indicate stormy IKO Enriches spring and fall, increased number of windy days periods during the early 1960s and late 1980s to Limited SEKO early 1990s near Sachs Harbour •!Prevailing winds were east but now more south- •! No known environmental data at same scale southeast, northwest winds are the most dangerous, as they bring icebergs (in the past) and rough water and dangerous conditions Arctic Char Growth and Biotic Environmental Conditions
Arctic Char •!Arctic Char size hadn’t change much on average •! This Study: Arctic Char relative growth was Knowledge Bases (Landlocked) in living memory, some years bigger landlocked variable over three decades, however increased Corroborate Size and char (longer and/or fatter) are harvested and some relative growth was seen in years with higher Growth years smaller, long warm summers result in more growing degree days above 0°C bugs (in lakes) and bigger char, cold summers •! This Study: Capron Lake char grew larger in the there is less for the char to eat and they are second time series as determined from back- smaller calculated growth (1993-2011) •!Capron Lake char are larger than other two lakes Changes to •!Mud from permafrost melt and erosion is •!No known environmental data at same scale IKO Enriches Fish Growth blocking creeks running into lakes where char are Lack of SEKO in Correlation often seen feeding with •!Become harder to catch fish in non-study lakes Environment with erosion on banks, or fish are showing more deformities and cysts •!Approximately 25 years ago (prior ~1991), used to have much higher catch per effort of Arctic Char in the lakes (might be also result of exploitation)
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•!Searun Arctic Char getting bigger with warmer weather •!In recent years, low rainfall has resulted in low river water levels and the searun char cannot get back to the lake to overwinter Changes in •!Consistently getting more “salmon” (described as •! Babaluk et al., 2000: First written record** of IKO Enriches Numbers of Chum (Dog), Pink, Coho and Sockeye) in coastal Sockeye Salmon (Oncorhynchus nerka) and Pink Limited SEKO Known waters in last 10-15 years (since ~2001-2006), Salmon (O. gorbuscha) collected from Banks Island Species increasing numbers with warmer weather, first **Note: First written records of salmon near Sachs salmon caught in 1991*, numbers gradually Harbour may not be first observed record according increasing, eggs are sometimes pouring out of the to IKO. salmon caught, some have a kype *Note: A late elder used to share stories of getting 1-2 salmon over the summer in the 1970s. •! Less song birds and shore birds; more Tundra •! Environment and Climate Change Canada Swans, Lesser Canada Geese, Lesser Snow (https://www.ec.gc.ca/rcom- Geese, White-Fronted Geese (in last 1-1.5 mbhr/default.asp?lang=En&n=a297b56f-1, decades); mass die-off eider ducks (spring 2013) accessed May 14, 2016): Snow Goose overabundant special conservation measures increased hunter harvest for Fall 2015-Spring 2016 due dramatic increase in population numbers over past several decades, Banks Island had longer special conservation hunt •! Hinterland Who’s Who – Snow Goose Fact Sheet (http://www.hww.ca/assets/pdfs/factsheets/lesser- snow-goose-en.pdf, accessed May 14, 2016): Snow goose numbers have increased dramatically since the 1970s •! Less fish in lakes (some believe linked to •! No known environmental data at same scale increased fishing pressure) •! Lake Whitefish started entering bay (from lakes) when weather started warming •! Almost no searun Arctic Char in coast near community in past couple years, natural cycle noted of high and low numbers depending on the year, but first time have not had enough to harvest, however Arctic Char that are harvested are much bigger (longer) than in the past
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•!Less “cod” in coastal, more “herring” in coastal waters and “small silvery fish” in past 15-20 years (since ~1996-2001) •! Increase in jellyfish in coastal waters in 2006, a lot of “little pink shrimp” washed up on coast July 2007, a lot of seals in the Sachs River in summer 2014 (never seen before) •! Seeing Bowhead Whales almost every year now •! Muskox numbers going down and Parry Caribou numbers going up in recent years New Species •!1999 or 2000 dead crabs and dead organisms from •! No known environmental data at same scale IKO Enriches Observed the ocean washed up on shore, not a result of a big Limited SEKO storm •!Beluga Whales near coast in ~1999, 2008-2009, now getting consistently every year, some believed because less pack ice •!Killer Whales summer 2014 •!New ducks, geese, ravens, owls and eagle •!New insects •!Polar-Grizzly bear crosses, first one captured on •! Kelly et al., 2010: A white bear with brown patches Banks Island 2006 shot by hunters in 2006 in the Arctic (on Banks Island) was confirmed to be a hybrid between a polar bear and a grizzly by DNA test ! !
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3.4 Discussion
This study used a mixed methods approach to gain an understanding of the potential local environmental drivers (direct drivers or through a series of linked effects) on Arctic
Char growth in three lakes on Banks Island NT using both ecological and social science methods to collect and analyze scientific ecological knowledge and observation (SEKO) and Inuvialuit knowledge and observation (IKO). Local experts observed noticeable changes in local environmental conditions around the same time other changes to the local environment, the lakes (Chapter 2) and landlocked char were occurring. Notably, local residents remember a decline in the size and abundance of Arctic Char caught in the late
1990s (~1996-1997), followed by recovery (~1997-1998). These observations were associated with local effects of the 1997-98 El Niño, which included thinner and lesser extent of sea ice, warmer than average seasonal air temperatures, increased rain, less snow, longer ice-free season on lakes, and the start of extensive erosion and permafrost melt along coasts and lake shorelines.
Similar environmental responses to the 1997-98 El Niño are also documented in the scientific literature including a warming of western Canada (including the western
Canadian Arctic) 0-12 months after the 1997-1998 El Niño event (Trenberth et al., 2003).
Little first-year sea ice and the earliest occurrences of open water in the southern Beaufort
Sea were reported in 1988 and 1997-1999 coupled with a massive reduction in summer sea ice (Galley et al., 2008). Local experts noted late sea ice formation, increased coastal and lakeshore erosion, major shifts in climate including an increase in storms and winds, and a lack of summer sea ice in the same range of dates, and observed particularly major shifts in these environmental features around both 1988 and 1997-98. Correlation of Arctic Char
! ! 170! recovery to in size to observations of unprecedented environmental change provided some rationale for the a priori chosen environmental parameters for scientific study.
Mutually reinforced findings (knowledge bases corroborated) in both the SEKO and
IKO knowledge bases regarding climate-driven environmental changes that appeared to be linked to biological responses in fish populations led to more confidence in determining potential parameters for monitoring char growth. Evidence for direct and indirect environmental mechanisms ascertained from both knowledge bases were found to play a potential role in Arctic Char growth and included GDD0 and to a lesser degree the length of lake ice-free period.
3.4.1 Environmental Conditions Affecting Arctic Char Growth
While the majority of local expert interviewees (83%) described that Arctic Char size has not changed on average over living memory, it was also indicated that in some years, char were longer and/or fatter than in other years. Long warm summers were a known factor for increased Arctic Char growth by 16% of the interviewed local experts who believed that increased production of prey (specifically emergent insects), was responsible for increased char growth. Nearly three quarters (72%) of local experts said the lake ice had always been ~1.8–2.5m thick, however half indicated that the ice melts earlier and more rapidly in the spring and takes longer to form in the fall over the past 15-
20 years (since ~1996-2001), resulting in a longer ice-free season on the lakes. The IKO and SEKO corroborated for prey abundance and lake ice having the potential to affect
Arctic char growth.
A linear mixed-effects model analysis for the available SEKO that corroborated the
IKO (ambient air temperature transformed into GDD0, rain and snow precipitation, lake ice
! ! 171! on and off dates), showed that Arctic Char growth for the populations in the three lakes on
Banks Island from 1970 to 2011 (obtained through back-calculation) suggested that: 1) growing degree days above 0 °C (GDD0) and the estimates of the ice-free period on each lake were both strong predictors of growth (although because both these parameters were significantly correlated with each other, this discussion will focus on GDD0), 2) warmer weather years appear to benefit growth of all ages of fish, and 3) Capron Lake char have gone through a recent period of accelerated growth compared to the other two lakes. Total precipitation was not retained as a significant fixed-effect in any of the linear mixed-effects models nor did it appear to co-vary with GDD0 (i.e. was not masked by a stronger relationship with air temperature). This suggests that precipitation was not a strong driver of Arctic Char growth on the lakes on Banks Island.
Further, sharp peaks in GDD0 in 1988 and 1998 (859 and 656 GDD0 respectively) were accompanied by immediate increases in relative growth rates across all three lakes.
This SEKO corroborates with the IKO that described noticeably warmer weather and low sea ice conditions (leading to warmer weather) in 1998, and as noted above, long warm summers lead to larger (fatter and/or longer) char. This leads to the conclusion that it is important to distinguish between the effect of GDD0 across the entire time series, and the effect of extreme shifts in annual temperatures. For example, over the entire time series, the effect size of GDD0 was relatively low in Kuptan and Middle lakes versus Capron Lake, suggesting that Capron Lake is generally more sensitive to warmer air temperatures.
The higher effect size of GDD0 in Capron Lake across the entire time series is likely due to its smaller volume (1.9 X 107 m3) relative to the other two lakes (i.e. an order of magnitude lower; see Chapter 2). With a smaller volume and relatively shallow maximum
! ! 172! depth (13 m), the water most likely warms faster under higher air temperatures leading to faster growth in Arctic Char provided optimal growth temperatures are not eventually exceeded. Summer water temperature profiles for 2011 presented in Chapter 2 for all three lakes indicated that the shallowest lake (Capron) appeared to be isothermal in the summer with a uniform 12°C profile. This temperature was warmer than the maximum temperatures detected within the epilimnions of Kuptan and Middle lakes (11.5°C and
10°C, respectively). In Kuptan and Middle lakes, temperatures dropped below 9°C at 10 m of depth suggesting that Capron Lake had a warmer environment for Arctic Char growth.
The von Bertalanffy growth curves also indicated the Capron Lake Arctic Char had an overall increase in growth rate over the second time series (2008-2012), whereas the growth rates of Kuptan and Middle lake populations remained relatively stable. As demonstrated in Chapter 2 in both the IKO and SEKO, Arctic Char in Capron Lake had a significantly higher body condition and significantly lower parasite loads than did those from Kuptan and Middle lakes. Given that 2011, when the lake temperature profiles were measured in summer and isothermal at 12˚ Celsius, was the second highest GDD0 at 753 degree days in the time-series, and that optimal growth temperatures in the laboratory range from 12 to 16°C (Johnson, 1980; Reist et al., 2006b; Gunnarsson, 2011), it is unlikely that water temperatures in Capron Lake exceeded those for optimal growth over this time-series.
Therefore, the differences in lake water temperatures might explain why the fish from
Capron Lake have gone through a recent acceleration in growth that was not observed to the same extent in Middle and Kuptan lakes. The uniform 12°C observed in Capron Lake likely results in more accessible habitat within the optimal temperature range for growth.
! ! 173!
In a study by Kristensen et al. (2006) landlocked Arctic Char in Kangarssuk and
Rode Elv lakes on Disko Island near Greenland were analyzed in a manner similar to those in this study, with surveys in the 1990s and in the early 2000s, and a comparison of growth rates with environmental conditions over that time period. Although char sample sizes were small, making interpretations of regression results for temperature and precipitation linkages to Arctic Char growth difficult, Kristensen et al. (2006) found higher air temperature resulted in decreased growth. However, the authors explained that despite increased growth opportunity due to increased temperatures, increased growth was not realized due to counter-vailing factors such as low food availability and higher vulnerability to disease and parasites at higher temperatures (i.e. finite energy stores were expended for uses other than growth). These assumptions have been echoed in other discussions on the implications of climate change to fish growth in the Arctic (Reist et al., 2006b). However, the results of this study do not align with Kristensen et al. (2006) in that there was evidence that the warmer temperatures experienced up to 2011 had resulted in increased growth.
Perhaps this an indication of generally high resource availability and low disease and parasite loads on Banks Island compared to Disko Island.
Murdoch & Power (2013) compared back-calculated growth rates of Arctic Char in two lakes in northern Quebec to summer air temperatures. Lake Tasiapik, is landlocked, and smaller (0.3 km2) and shallower (~10 m) than Capron Lake (5.77 km2; 13 m). Lake
Qamutissait, is connected to Ungava Bay, and has a similar surface area to Middle Lake
(12.6 km2) with a relatively shallow depth of ~20 m. The authors measured the first six years of growth in Lake Tasiapik and the first three years of growth in Lake Qamutissait
(after age 3 the char migrate to the ocean). No effects of air temperature were found on
! ! 174! early-life growth in Lake Qamutissait, and only a slight negative effect was found in ages
3, 4 and 5 in Lake Tasiapik. Summer water temperatures in Lake Tasiapik peaked at 16.8°C and 18.2°C in 2009 and 2010, and the authors argued that these warm temperatures could reduce growth rates. Murdoch & Power’s (2013) study thus provides an example of the potential effect of exceeding optimal growth temperatures on Arctic Char growth rates.
Although there are no other known studies using back-calculation of freshwater
Arctic Char otoliths to examine the relationships between environmental conditions and growth to compare to this study, back-calculation studies in related species or other approaches in anadromous Arctic Char have reached similar conclusions. For example, in a closely related species, Lake Trout, growth rates derived from otolith back-calculation were found be to positively related to August air temperatures from 1964 to 1984 in the
Chandler Lake systems in Alaska (Black et al., 2013). Latitudinal studies on Arctic Char have generally shown that populations in warmer environments have larger body sizes
(Chavarie et al., 2010) and are more fecund (Power et al., 2005). In a study on the size-at- age of the harvested anadromous Hornaday River (Northwest Territories, Canada) Arctic
Char stock, Chavarie (2008) found that sizes-at-age varied positively with temperature from 1990-2003, and that the relationship weakened as fish became mature (this latter point also reported by Hesthagen et al., 2004). Indeed, the overall effect size of GGD0 should weaken with age as older fish devote less energy to somatic growth because they divert it to reproduction. However, in terms of relative growth, we found little difference in the effect of GDD0 on growth between pre- and post-maturation. One aspect of Arctic Char growth that is important to explore further is whether periods of accelerated growth in
Arctic fish is sustainable in the long term (Reist et al., 2006b).
! ! 175!
While the analysis in this study indicates that peaks in GDD0 can initiate higher growth rates within the same year, no testing was conducted to examine potential time lags in the system (Power et al., 2000). Evidence from Chavarie et al. (2010) suggests that northern populations of Arctic Char increase their growth rate relative to southern populations to compensate for shorter growing seasons, and so, if growing seasons elongate with climate change and char life history mimics the southern populations, char growth rates could gradually decrease. Further, whereas peaks in GDD0 can lead to short term boosts in lake productivity, the prediction of increasing temperatures in the future could require that the increased metabolism of the Arctic Char or strong year-classes are matched by a corresponding higher availability of food (Reist et al., 2006b).
3.4.2 Environmental Conditions with Potential to Affect Arctic Char Growth Identified through IKO
IKO identified several environmental conditions and changes to the abiotic environment over the past four decades (~1980s–2010s) including: changing condition of the ground with a thicker active layer and more absorption of precipitation (snow and rain), lower creek and river flow (including less flow entering lakes), earlier ice breakup and later ice formation on rivers, increasing coastal and shoreline erosion and permafrost melt, less summer sea ice and thinner winter ice with less landfast ice, warmer ocean water temperature, more forceful ocean waves, increased frequency and intensity of storms and wind, unpredictability of weather with more frequent and intense storms, and hotter sun in summer. Of these 10 observed parameters, four exhibited corroboration between equivalent observations at the same conceptual and spatial scales in the environmental literature (coastal erosion, sea ice, storms and sun), however, no SEKO on these factors
! ! 176! was available through this study. IKO also identified several changes to the biotic environment including changes of known numbers of species and new species records.
Both of these instances enriched the understanding of the local environment where SEKO was limited or lacking.
While the inferred causality of the above observations to char growth were not explicitly indicated by local expert interviewees, indirect and direct effects on lake habitat were clear. Changes to numbers of known species and new species records were indicators of a changing and increasingly variable climate and ocean environment, as were the increased frequency and intensity of storms, wind and ocean waves. A deeper active layer, lower river and creek flows, decreases in sea ice and increases in the length of the open water season on the ocean, warmer ocean water, coastal and lake shoreline erosion all indicated warmer ambient air temperatures, and changes to precipitation patterns. Also, the observations by local experts of a warmer sun and increases in sunburns were potentially explained by Seabrook et al. (2011) who found several ozone depletion events
10-40 km off coast of Banks Island in 2008. Decreases in atmospheric ozone are known to cause increases in solar (UV) radiation reaching the earth’s surfaces (Bais et al., 2015), which can result in more heat being generated from those surfaces, and has the potential for increased UV radiation exposure for aquatic organisms in Arctic lakes (Reist et al.,
2006a; Pienitz & Vincent, 2000).
Both warmer ambient air temperatures, water temperatures, and decreased winter precipitation may affect Arctic Char lake habitat through decreasing the length of the lake ice-cover season. Also, decreasing allochthonous input into the system (see Chapter 2) through reduced spring creek flow (due to lower snowfall) could result in a decrease in lake
! ! 177! productivity. Both water temperature and prey availability affect Arctic Char growth.
Based on observations provided by IKO, further studies and monitoring should include how reduced amounts of snow and an increased active layer decreases allochthonous input into the lakes and affect char growth, especially in the spring when char are seen feeding at ephemeral creek inlets to lakes.
The results of this study may prove useful in locations where CVC, and similar effects seen by Sachs Harbour local experts, have been experienced elsewhere in the circumpolar Arctic. For example, the draining and disappearance of Arctic lakes in Siberia and rain-on-snow (ROS) events across the circumpolar Arctic that impede animal foraging leading to mass die-offs (Vincent et al., 2011). Mass die-offs of terrestrial animals could result in temporary increases allochthonous input into lakes, increasing productivity and potentially fish growth at least in the short term. The interplay between decreasing allochthonous input from reduced runoff and increased input from the potential for an increasing number of ROS events should be studied further to understand how changes to lake productivity may result and how this will affect fish growth. Though some of these parameters are difficult to quantify or measure, it does not exclude their importance as potential parameters in monitoring of Arctic Char, as they could also play the role of locally-observed harbingers of change in addition to Growing Degree Days and the length of the annual lake ice-free period. Parameters commonly observed by local experts are useful candidate parameters for community-based monitoring of the resource, as they are already observed by local fishers on an on-going basis.
IKO also indicated that lake shoreline erosion was increasing, and while no direct observations by local experts noted effects on water clarity (water is extremely clear) or
! ! 178! fish condition in the three study lakes, in two non-study lakes with heavily eroding shores
(Blackfish and Angus lakes) experts noted that it was harder to catch fish and fish had more deformities. Also, Mesquita et al. (2010) found that eight lakes averaging 1.92-4.59 m in depth between Inuvik and Richards Island (NWT) disturbed by permafrost thaw slump had sediments richer in specific elements (calcium, magnesium and strontium) with greater transparency of the water column. Thompson et al. (2012) found lower levels of nutrients and ultraviolet and photosynthetically active radiation absorbance in small tundra lakes affected by permafrost thaw-induced shoreline slumping than those that were unaffected in the Mackenzie Delta uplands (within the southern portion of the Inuvialuit Settlement
Region). Dugan et al. (2012) found that localized permafrost disturbance in watersheds resulted in chemical changes in deep large lakes but increased sediment transport from disturbances did not have a sustained effect in two lakes on Ellesmere Island in Nunavut.
Water quality results (Chapter 2) showed much higher Total Dissolved Solids in Middle and Kuptan lakes, which through visual assessment had higher levels of shoreline erosion.
All of these findings warrant further study into lake shore erosion as a potential indicator for landlocked Arctic Char growth.
Additionally, the IKO described linkages on how increased winds and decreased snow cover affected lake ice in recent years by removing the insulating layer of snow that results in decreased lake ice thickness. Wind was also seen to be increasing in intensity and frequency, and the prevailing winds had changed from east to southeast. Local experts indicated that winds were related to a general increase in storminess and less snow accumulating in the winter (as there is less snow falling, and what is falling is being blown away), earlier break-up and later formation of sea ice, and increased intensity of ocean
! ! 179! waves. In a study in Clyde River Nunavut by Gearheard et al. (2009), wind in particular was identified by Inuit as one of the most important environmental parameters as it plays a key role in driving sea ice, ocean and weather conditions, as well as human travel and harvest activities. Inuit in Clyde River on Baffin Island also observed changes to wind variability, speed and direction just as the local experts in Sachs Harbour had described. As wind has the potential to affect both sea ice, which can drive local climate and thus Growing
Degree Days (as explained in the introduction), as well as the length of the ice-off season on lakes thus affecting the lake water temperature, wind is an important parameter to study further to determine if it can be used as a potential indicator for monitoring Arctic Char growth.
3.5 Conclusions
By determining if there were similarities and differences in char growth within and among study lakes, interpretation of resulting patterns supported both lake-specific (Capron
Lake char showed an increase in growth over Kuptan and Middle lakes, see also Chapter
2) and regional climate-driven changes (increased char growth in all three lakes in years with increased GDD0). Parallel similarities in a given year of growth across a range of age classes across all study lakes indicated a regional rather than a lake-specific effect of climate. Anomalous climate conditions in a given year, or previous years, may be an indicator of the link between climate and fish growth, and will be important indicators for monitoring of the resource in a changing climate. Growing Degree Days, the closely linked parameters of lake ice on and off dates, as well as the extent of annual sea ice coverage are important environmental indicators to consider in Arctic Char monitoring, because of their effects on char growth.
! ! 180!
This study demonstrates the utility of combining two information sources to gain an improved understanding of the effects of environmental parameters on Arctic Char growth. The mixed methods approach was valuable in that it provided: 1) a more advanced understanding of historical and current conditions for use towards new monitoring programs for landlocked Arctic Char in the region, 2) a more comprehensive understanding of the effects of environmental changes on Arctic Char growth, and 3) key environmental indicators for potential use in monitoring of the resource. Monitoring parameters that can use IKO techniques for information collection should also be considered by fisheries managers, as they may be the easiest for the community to monitor on their own. These parameters should include, but are not limited to, lake ice on/off dates in addition to ambient air and lake water temperatures as they relate to Growing Degree Days. Other parameters for consideration include increasing shoreline erosion and mass ungulate die-offs resulting in increasing allochthonous input, and decreasing spring allochthonous input resulting from changes in precipitation patterns and an increasing active layer depth.
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3.7 Appendices
Appendix 1. Mean relative growth of Arctic Char of all ages within a year for each study lake (Capron, Kuptan and Middle lakes on Banks Island NT) determined from otolith back-calculation.
Year Capron Lake Kuptan Lake Middle Lake N Mean Variance N Mean Variance N Mean Variance 1970 1 0.754170844 N/A 1 1.027318542 N/A N/A N/A N/A 1971 1 0.80912502 N/A 1 1.336395265 N/A N/A N/A N/A 1972 1 0.939796014 N/A 2 1.22086952 N/A N/A N/A N/A 1973 1 0.752593392 N/A 3 0.802586681 0.007722238 N/A N/A N/A 1974 1 0.793804531 N/A 4 0.979339196 0.060816659 N/A N/A N/A 1975 1 0.955464585 N/A 6 0.76440124 0.003720289 N/A N/A N/A 1976 2 1.182370763 N/A 14 1.09238828 0.024750638 N/A N/A N/A 1977 3 1.049794563 0.104798577 33 1.119700413 0.075229309 7 1.3140837 0.02928147 1978 7 0.878039858 0.001623954 45 1.023604836 0.049736235 12 1.011139625 0.020492089 1979 12 0.90820293 0.053854289 53 0.934219552 0.064312066 17 0.965243435 0.031316659 1980 21 0.896662443 0.029470327 65 0.88907666 0.027706823 20 0.943343492 0.032289638 1981 27 1.026941343 0.018505842 73 1.069592577 0.049337531 21 1.06156357 0.02708244 1982 43 0.96656362 0.028038347 78 1.070928488 0.036151498 26 1.048494778 0.015988934 1983 50 0.971600098 0.021822627 80 1.006259901 0.028975393 28 1.054515906 0.020616042 1984 54 1.016558304 0.023159187 83 1.041078162 0.028855138 29 1.087757236 0.02307571 1985 55 0.946032509 0.022751978 84 0.974506239 0.030910927 29 1.12232715 0.037580694 1986 61 0.856038045 0.022679079 84 0.918727191 0.034023479 29 0.999915392 0.033252499 1987 71 0.973637094 0.037700696 85 0.996484198 0.044018828 29 1.163462173 0.088921872 1988 79 1.137880328 0.062512531 85 1.137381044 0.039369968 31 1.285422429 0.082178295 1989 80 1.065385268 0.042289107 87 1.107665887 0.042640867 32 1.310666999 0.072642875 1990 80 0.825809731 0.026698287 89 1.002606568 0.056875079 36 1.050151204 0.036072557 1991 80 0.70456058 0.021662087 96 0.914362605 0.054672547 46 1.041084043 0.034734086
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1992 80 0.762786005 0.020585975 77 0.908206828 0.057459258 60 1.089713862 0.056808641 1993 84 0.818802085 0.039103563 94 1.048103076 0.083389937 81 1.152287541 0.122035473 1994 5 1.178958105 0.017182896 58 1.024462616 0.044161604 73 1.06858095 0.084951711 1995 8 1.077620127 0.022925951 65 1.010558534 0.059558034 91 0.981891274 0.055129872 1996 19 1.0485971 0.016919201 70 0.980354987 0.026146561 97 0.949722126 0.0522792 1997 25 0.969645369 0.025544982 72 0.965165988 0.058236297 98 0.938656971 0.05368995 1998 29 1.3492458 0.083031341 73 1.028656872 0.076475733 98 1.128303309 0.139270218 1999 29 1.095344499 0.082372296 73 1.18324136 0.149183633 98 1.116916968 0.121341704 2000 35 1.07753995 0.051135051 73 1.00861366 0.075050631 98 0.944232424 0.087560223 2001 36 0.975574304 0.032661635 73 0.904388931 0.031677777 101 0.88596356 0.044267833 2002 39 0.882878045 0.021325663 73 0.826389789 0.02473138 102 0.805323737 0.041420424 2003 42 0.868334209 0.034528102 73 0.837271326 0.042124198 104 0.874841428 0.045811086 2004 43 1.016545701 0.038161199 73 0.900897781 0.067400866 107 0.923266859 0.052040653 2005 43 1.136875109 0.047311857 73 0.981909183 0.077927555 109 0.914295335 0.055449161 2006 44 1.568440219 0.165079979 73 1.049366094 0.13603373 109 1.035433988 0.080942667 2007 44 1.4330931 0.124353982 73 1.126646597 0.103579536 109 1.036933025 0.097084773 2008 18 1.422337808 0.079089711 73 1.050145997 0.072149007 71 0.975197367 0.095659031 2009 18 1.267559017 0.178665319 26 0.995104171 0.061283582 28 0.975371004 0.257755127 2010 11 1.478940065 0.130018964 26 1.031222649 0.072364679 28 0.881721004 0.121763972 2011 12 1.040372305 0.113343294 4 1.048427242 0.047274076
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Appendix 2. Von Bertalanffy growth curves (solid lines) with 99% confidence intervals
(dashed lines) calculated from the captured lengths and ages of Arctic Char sampled from
Capron, Kuptan and Middle lakes on Banks Island NT during 1992-1994 and 2008-2012.
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CHAPTER 4:
Factors Influencing the Community Monitoring of Arctic Char Fisheries
4.1 Introduction
Globally, fisheries provide an essential source of food, employment, and recreation
(FAO, 2015). Indigenous people around the world rely on marine and anadromous fisheries for food, and an estimated 26.6 million coastal Indigenous people globally have an average annual fish consumption per capita of 74 kg (Cisneros-Montemayor et al., 2016). This is nearly four times the global average of 19 kg/per capita (Cisneros-Montemayor et al.,
2016). Fish are also an important resource to many Indigenous groups in Canada (Berkes,
1990; Cooke and Murchie, 2013). Fishing communities and management organizations require rigorous monitoring programs to provide data towards sustainable management of fisheries (vanGerwen-Toyne et al., 2013).
In the Canadian Arctic, freshwater, anadromous and marine fish are still captured for subsistence and commercial purposes (Dempson et al., 2008; Donaldson et al., 2010;
Roux et al., 2011; Porta and Ayles, 2015; AMAP Assessment, 2015). Even though a wage- earning economy has become predominant in many northern Indigenous communities, subsistence hunting, trapping and fishing remain primary sources of food and fish contributes significant to the daily diets of individuals in many regions (Nuttall, 2005;
Community Corporations et al., 2006; Donaldson et al., 2010; Lyons, 2010; Blanchet and
Rochette, 2008; Egeland et al., 2010a, 2010b and 2010c).
As in the past, fishers transport fish back to the community to distribute to elders and people who can no longer travel or harvest on the land. This practice of country food
! ! 202! sharing and food distribution among community members still plays a central role in the social fabric of northern communities (Codon et al., 1996; Papik et al., 2003; Nuttall, 2005).
Arctic Char (Salvelinus alpinus (L.)) is one of the most frequently consumed subsistence species in each of the four Inuit land claim regions in Arctic Canada (Inuvialuit Settlement
Region, Nunavut, Nunavik and Nunatsiavut) (Blanchet and Rochette, 2008; Egeland et al.,
2010a, 2010b and 2010c; Sharma et al., 2010) and remains an essential part of the diet, culture, and subsistence economy of the Inuit (Cockney, 1997; Usher, 2002; Papik, 2003;
Priest and Usher, 2004; Nuttall, 2005; Communities et al., 2005; Community Corporations et al., 2006; Sharma et al., 2010).
In Arctic Canada, fish monitoring activities include tracking abundance, recruitment, stock size and distribution, fishing pressure, stock health, and socio-economic factors (e.g. Day and Harris, 2013); contaminants in fish tissues (e.g. McKinney et al.,
2012); and fish passage effected by natural barriers or hydroelectric developments as seen in Nunavik (e.g. Dumas, 1990). Monitoring fish in the Canadian Arctic is driven by concerns surrounding climate change and anthropogenic impacts on fish resources including harvesting pressure (e.g. Reist et al.; 2006a; Culp et al., 2012; Cooke and
Murchie, 2013; Harwood et al., 2015). However, data for Arctic fisheries are sparse (Reist et al. 2006c; Roux et al., 2011) and climatic changes have already begun to have an effect on these fish and aquatic environments (Reist et al., 2006b; Wrona et al., 2006; Prowse et al., 2009; AMAP, 2011; CliC/AMAP/IASC, 2016; Poesch et al. 2016).
Inuit have been observing unprecedented climate variability and environmental change over the past two decades (e.g. Cockney, 1997; Riedlinger and Berkes, 2001; Jolly et al., 2002; Nichols et al., 2004; Communities et al., 2005), which has affected local Arctic
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Char fisheries (Knopp, 2010; Knopp et al., 2011, 2012). Specific examples of observed changes that have the potential to effect, or have already effected, anadromous Arctic Char fisheries in the western Canadian Arctic include: increased numbers of Pacific Salmon and concerns they will become a potential competitor to char; Arctic Char becoming larger resulting in local harvesters perceiving the meat to be too rich to eat; meat becoming soft and pale; and, shifts to the timing of migration of Arctic Char (Babaluk et al., 2000; Jolly et al., 2002; Parent, 2002; Papik et al., 2003; Communities et al., 2005; Huntington and
Fox, 2005; Barber et al., 2008; Knopp et al, 2011, 2012). These changes are believed to be the results of climate change. For example, Dunmall et al. (2013) showed that the geographic distribution of Pacific Salmon is increasing and that there are trends towards higher abundance in the Arctic. This supports the observations of Inuit. These changes are believed to be indicative of climate changes in the Arctic marine environment, allowing the
Pacific Salmon to disperse through warm water layers or by following feeding opportunities that were not previously available (Dunmall et al., 2013). Inuit who reported larger and richer char, soft and pale char meat, or changes to the timing of char migrations explained that these observations started occurring after the weather became noticeably warmer and the ocean started to have less ice.
In consideration of climate-driven changes, monitoring Arctic Char fisheries on which Inuit rely is needed to both manage the resource and mitigate effects on local resource users as a result of impacts to the fishery. Arctic residents being both the first to observe changes in their local environment and directly affected are well-suited to monitor local resources. In confronting unprecedented environmental change, community-based monitoring plays a critical role in remote Arctic fisheries management (Kristofferson and
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Berkes, 2005; Ayles et al., 2007; Bell and Harwood, 2012). Community-based monitoring supports opportunities for the inclusion of local knowledge and study approaches as well as local collection of scientific data (Parlee and Łutsël K’é Dene First Nations, 1998;
Danielsen, 2009; Gofman, 2010). However, community-based monitoring projects in the circumpolar north remain poorly documented (Johnson et al., 2015; Kouril et al., 2016). In remote Arctic locations, community monitoring of fisheries can contribute data towards setting sustainable harvest levels and safeguarding fisheries productivity (Roux et al., 2011; vanGerwen-Toyne et al. 2013) thus ensuring sustained human use of the resource in subsistence, large-scale and small-scale commercial fishing contexts, and recreational uses including local sport-fishing outfitters.
There are three important questions to keep in mind when considering the monitoring of natural resources: 1) Why should we monitor?; 2) What should we monitor?; and, 3) How should we monitor? (Busch and Trexler, 2003). To date, research in Canada has focused on the review of individual Arctic Char fisheries monitoring programs (e.g.
Paylor, 1998; Kristofferson and Berkes, 2005; Bell and Harwood, 2012). However, there is a need to understand common factors influencing program approaches and success in order to support the creation of lasting Arctic Char community-based monitoring programs
(CBMPs) in the future. Therefore, the intent of this research was to compare and contrast various aspects of char CBMP, to identify parameters and factors used in Arctic Char community-based monitoring programs in the Canadian North that have led to the sustained collection of data useful for fishery management.
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4.2 Methods
This project followed a qualitative exploratory design, included the collection and analysis of existing literature on the topic. Key informant interviews with identified representatives from Arctic Char CBMP across the Canadian North were also conducted and analysed. The focus for the char CBMP review was on programs that included, at minimum, a biological sampling and/or data collection component. However, other monitored parameters were also considered.
4.2.1 Literature Search
A review of academic and grey literature was conducted to identify and gather information on existing fish monitoring programs in the Canadian Arctic. Online databases used for the search were: Web of ScienceTM, Google Scholar, Canada Thesis Portal, and the WAVES online catalogue (Fisheries and Oceans Canada). Based on preliminary findings and trial runs of key words, combinations and permutations of three terms were used in the search (asterisk denotes variations of the word): char AND monitor*; community
AND monitor* AND arctic AND canad*; and, fish* AND monitor* AND arctic AND canad*. All documents that contained information on CBMPs for Arctic Char or closely- related Salmonidae species were retained. Once searches were complete, authors working on Arctic Char (and related species) CBMPs in northern Canada were identified from the literature. A subsequent search of the databases listed above was completed for all authors identified from the initial search to ensure no further relevant literature was discovered.
Reading the documents obtained through the literature search assisted with the development of questions for the interview guide in addition to including them in the qualitative analysis described below.
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4.2.2 Identification of Key Informants for Interviews
Arctic Char CBMP key informants were identified through initial informal interviews with researchers, government officials, regional research institute representatives, and co-management organizations. A key informant was defined as someone who had worked within an Arctic Char (or related species) CBMP for at least a year, who had worked in an Arctic Char (or related species) CBMP in the Canadian Arctic, who worked for a program that collected at minimum biological data (additional data such as harvest studies were also considered), and who had a role within the program as either a
Federal Government (FG) representative (i.e., Fisheries and Oceans Canada) or a Land
Claim Organization (LCO) representative (e.g., regional organization, co-management board or community hunters and trappers organization). An initial list of key informants was compiled from these recommendations. Upon completion of an interview with a key informant (as described below), a referral strategy (Creswell, 2005) was used to identify additional interviewees.
4.2.3 Interviews with Key Informants across the Canadian Arctic
A semi-directed interview guide was created and was used to facilitate oral and written interviews with participants (Appendix 1). Once identified, key informants were approached for an interview via email or phone. Once key informants agreed to be interviewed, informed consent was obtained and the option of conducting an oral interview via telephone or providing a written response was offered. Oral interviews were preferred because they do not limit “the researcher’s ability to understand the key informant’s perceptions of the phenomenon” by being able to probe with further questions (Creswell,
2005:216). Key informant responses were collected in whatever format agreed to (oral
! ! 207! interviews via telephone or written responses). Interviews were conducted between
February 17th and March 28th 2010.
Interview questions covered a broad range of topics including: attributes of the
CBMP (location, length of time running, partner organizations, etc.), purpose of the program, community involvement, government involvement, parameters monitored and data collected, methods and tools used, cost and funding sources, analyses, dissemination of results, and suggestions for communities interested in starting or improving Arctic Char community-based monitoring programs. Key informants were also asked to identify any literature they may have published (peer-reviewed or grey) relevant to Arctic Char community-based monitoring. Oral interviews were digitally recorded and then transcribed. Transcripts were provided to each respective participant for review, correction, deletion or addition of content prior to analysis. Further clarification of interview responses was obtained from key informants when required.
In addition to the literature review and interviews, an Inuvialuit-Canada Fisheries
Joint Management Committee (FJMC) representative traveled with the researcher to
Kuujjuaq, Nunavik (Arctic Quebec) and Montreal to meet staff from the Nunavik Research
Centre involved with Arctic Char monitoring in that region. During these meetings the researcher and the FJMC representative learned further about methods used in Nunavik
Arctic Char CBMPs. Notes taken during this trip by the researcher were included in the analysis. Oral interviews were also conducted with two key informants from the Nunavik region. All research was carried out under the Trent University Research Ethics Board approval #21920.
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4.2.4 Data Analysis
All interview transcripts and written responses were entered into the qualitative analytical software NVivo (QSR International Pty Ltd. 1999-2014, v. 10). Documents obtained from the initial literature review as well as those identified by key informants, were also entered into NVivo. A two-pass coding process for thematic content analysis was used (Creswell, 2009; Saldana, 2009) for both the transcribed interviews and the documents. In the first step, descriptive coding examined patterns of responses to the interview questions. The second pass analysed narrative data for common thematic patterns that were not explicitly asked in the interviews, but emerged in responses to several questions across more than one participant. If these passages were present, they were coded into categories of emergent themes. This type of analysis allows for the identification of themes and topics emerging from the participants’ viewpoints and understandings
(Creswell 2007) in addition to those provided in response to questions posed by the researcher.
To categorize the model of Arctic Char community-based monitoring programs identified and included in this study in the Canadian Arctic, a spectrum of models (adapted from Danielsen et al., 2009; Table 1) was used to classify the Arctic Char CBMPs analysed in this paper.
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Table 1. Five models of community-based monitoring (adapted from Danielsen et al.,
2009).
CBMP Model Primary Data Gatherers Primary Users of Data
1) Externally driven, Non-community members University, Research Externally executed (i.e. government or Centre or non-local researcher) Government 2) Externally driven, Local Local community members University, Research data collectors along with Government or Centre or non-local Researcher Government 3) Collaborative Local community members Local community members monitoring with external with Government or and organizations and data interpretation Researcher advice University, Research Centre or non-local Government 4) Collaborative Local community members Local community members monitoring with with Government or and organizations community-requested Researcher advice advice from external agencies and local data interpretation 5) Autonomous local Local community members Local community members monitoring and organizations
4.3 Results
A total of five Arctic Char (Salvelinus alpinus (L.)) and one Dolly Varden Char
(Salvelinus malma (W.)) CBMP across the four Inuit land claim regions in Canada were identified and included in the research (Figure 1). Of the six CBMPs analysed, three were in the Inuvialuit Settlement Region in the northern part of the Northwest Territories, the
Rat River near Aklavik (CBMP of Dolly Varden (Salvelinus malma malma) only), the
Hornaday River near Paulatuk, and the Kujjuaq River and Fish Lake near Ulukhaktok. The other three Arctic Char CBMPs analysed included: Wellington Bay and Ekalluk River near
Cambridge Bay in Nunavut Territory, the Nephijee and Koksoak rivers near Kuujjuaq in
Nunavik land claim region in northern Quebec (the Koksoak River CBMP included
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Atlantic Salmon (Salmo salar) monitoring in addition to Arctic Char), and the Voisey, Nain and Okak stock complexes near Nain in Nunatsiavut land claim region in Northern
Labrador. As Dolly Varden and Atlantic Salmon are closely related salmonid species, these two species were also considered in this study. All five Arctic Char and the one Dolly
Varden CBMPs analysed were monitoring anadromous char populations. No examples of formal CBMPs were identified for freshwater-restricted Arctic Char populations.
Figure 1. Map of northern Canada showing Inuit Nunangat (homeland of the Inuit of
Canada) depicting the four Inuit land claim regions: Inuvialuit Settlement Region (orange),
Nunavut (light green), Nunavik (dark green) and Nunatsiavut (purple). Locations of the key informant Arctic Char (and one Dolly Varden Char) community-based monitoring program affiliations are identified with red dots.
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Of 19 key informants identified, nine agreed to participate in an oral or written interview. The participating key informants had an approximate cumulative total of 146 years of experience working with char (Salvelinus spp.) CBMPs. Five key informants worked for the FG (three as program leaders) and four worked for LCO (one as a program leader). Five key informants completed oral interviews and four completed written interviews (Table 2). Oral interviews were 41 to 75 minutes in length. Written interview responses were between three and six pages of text in length. Key informants also provided recommendations for peer-reviewed papers or government documents they had authored in relation to the char CBMP with which they were affiliated.
Table 2. Summary of key informant attributes who provided information on Arctic Char community-based monitoring programs across the four Inuit Land Claim regions in Canada
(Inuvialuit Settlement Region, Nunavut, Nunavik, and Nunatsiavut) (n=9).
Attributes Federal Land Claim Government Organization Land Claim Region Inuvialuit Settlement Region 3 2 Nunavut 1 0 Nunavik 0 2 Nunatsiavut 1 0 Number of CBMP Program Leaders 4 1 Average Years of Experience* 19.4 9.75 Median Years of Experience 20 12 Type of Interview Oral 3 2 Written 2 2 *Several key informants responded with an approximation of their years involved in a CBMP(s). Number of years of experience are stated up to the year of the interview (2010).
A total of 28 documents were identified from the literature review providing information on the six programs considered in this study (Appendix 2). In addition, key informants also provided a total of seven additional internal documents (presentations and
! ! 212! internal notes) which they deemed relevant to the study, but were otherwise unavailable.
The qualitative analysis of all data sources organized findings into three overarching themes including Program Operations, Community Perspectives on CBMPs, and Insights,
Considerations, and Recommendations (Table 3), and 33 subthemes. The complete data set included 43 sources including key informant interviews (n=9), documents provided by key informants (n=7), and relevant literature (n=28, Appendix 2). The char CBMPs analysed had been conducted for 21 to 45 years (Table 4) and remained operational at the time of the analysis.
Table 3. Themes and subthemes from thematic content analysis on community-based monitoring programs for Arctic Char and related species in the Canadian Arctic.
Associated number of interviews (n=9) and documents (n=35) providing information on each subtheme are included.
Themes Subthemes Number of Number of Total key documents number informants containing of who shared information sources information on theme (n=44) on theme (n=35) (n=9) Community, Government or 6 17 23 Industry Initiated and/or Executed Initial Community 7 11 18 Involvement in Program Design Community Monitor Pay and 8 14 22 Hiring Arrangement Program Cost to Run Program 6 5 11 Operations Equipment and Tools Used 8 23 31 Frequency and Timing of 5 15 20 Monitoring Funding Sources 3 8 11 Inuit Knowledge and 5 11 16 Observations Included Length of Program 9 24 33 Location 9 35 44
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Monitoring Methods 9 28 37 Parameters Sampled 9 18 27 Program Partners 7 24 31 Purpose 8 30 38 Reporting and Outreach 7 10 17 Style of Monitoring 7 14 21 Training 8 10 18 Type of Fishery 5 25 30 Who Does the Analyses 9 14 23 (samples and data) Who Uses Data and Results 9 10 19 Communication between 5 4 9 Government and Community Organization Community Engagement 8 7 15 Ongoing Community 9 14 23 Involvement in Design and Implementation Community Interest in 3 2 5 Community Program Perspectives on Community Monitor 1 1 2 CBMPs Retention Community Perception of 4 9 13 Monitoring Program Community Use of Char 2 21 23 Resource Lifestyle and Social Changes 4 4 8 with potential to alter CBMP Design Benefits and Positive 6 15 21 Attributes of Program Changes to Fishery that Affect 6 15 21 Insights, the Program Considerations, Changes to Government or 4 8 12 and Decision-Makers that Affect Recommendations the Program Recommendations and 9 26 35 Considerations Struggles and Challenges 9 20 29
4.3.1 Program Operations
A summary of comparisons across the six CBMPs for subthemes within the theme of Program Operations is provided in Tables 4 and 5 (for a detailed comparison of Program
Operations see Appendices 3-1 to 3-3). Among the six CBMPs, there were different
! ! 214! purposes for the initiation and execution of the programs. The three char CBMPs in the
Inuvialuit Settlement Region monitored stock trends over time to address community concerns about diminished abundance, and how this might affect subsistence harvest needs
(Table 4). The purpose of the Nunavik CBMPs were to determine fish passage and enhance habitat when fish passage when required. Arctic Char were monitored on the Nephijee
River due to fish passage concerns resulting from natural barriers (isostatic rebound, barriers created from movement of boulders during high flows) and Arctic Char and
Atlantic Salmon on the Koksoak River due to fish passage concerns resulting from Hydro
Quebec projects. The Nunavut and Nunatsiavut char CBMPs provided data for the management of the commercial fisheries in conjunction with the subsistence fisheries. In
Nunavut, Kitikmeot Foods is a subsidiary of the Nunavut Development Corporation of the
Government of Nunavut, and has a plant in Cambridge Bay that processes wild-caught
Arctic Char obtained from local harvesters. In Nunatsiavut, the Nain Fish Plant is run by the Torngat Fish Producers Co-operative Society Ltd., an Inuit-owned co-operative.
All six char CBMPs monitored a population or populations that supported a subsistence fishery (Table 4). Three of the six CBMPs (Table 4) also included recreational fisheries (sport-fishing outfitters in the past or currently) and included the Hornaday River
(ISR), Ekalluk River and Wellington Bay (Nunavut) and the Nephijee and Koksoak rivers
(Nunavik). Three of the waterbodies monitored in the char CBMP currently supported commercial fisheries. A local small-scale fishery occurred on the Kuujjuaq River and Fish
Lake (and nearshore ocean environments) in the ISR. Both the Wellington Bay and Ekalluk
River in Nunavut and the Voisey, Nain, and Okak Stocks in Nunatsiavut supported large- scale commercial fisheries with fish plants in the local community. In Nunavut, the
! ! 215! subsistence harvest of char was concentrated near the community and the Ekalluk River, and was estimated to equal approximately one half of the commercial harvest (Day and de
March, 2004). Similar to the Nunavut char CBMP, a subsistence harvest also occurred from the same Arctic Char stocks as the commercial harvest in Nunatsiavut, however, the quantity taken through the subsistence harvest was not available.
All programs had partnerships with university researchers (Table 4). Five of the six programs had partnerships with Fisheries and Oceans Canada (DFO), co-management boards, and the local hunters and trappers group, whereas the Nunavik CBMP partners included the local hunters and trappers groups, and the Nunavik Research Centre (a division of the regional land claim organization, the Makivik Corporation). The Nunatsiavut char
CBMP also partnered with the Nain Research Centre. Five of six programs received funding from the federal government as well as land claims organizations. Again, the
Nunavik CBMP was different in that it received funding from the land claim organization and industry. The Nunavut and Nunavik CBMPs identified additional funding from university research collaborations.
All six char CBMPs monitored annually in late summer to early fall, and hired community monitors on a seasonal basis, and monitored fish morphometrics and meristics
(Table 4 and Appendix 3-2). All programs, except for the CBMP in Nunavik, monitored catch-per-unit-effort, harvest levels, and conducted stock assessments. In addition to morphometrics and meristics, Nunavik also monitored fish passage, migration, contaminants, and collaborated on food-web studies with university researchers (Table 4 and Appendix 3-2). The three ISR char CBMPs monitored additional environmental parameters such as unusual observations, weather, water levels and water temperature in
! ! 216! addition to conducting harvest-based monitoring (Appendix 3-2). The Nunatsiavut program collaborated with university researchers to better understand aspects of the char resource including genetic and stock structures (Appendix 3-2).
All monitoring programs included Inuit knowledge and observations (IKO) (Table
4), however to varying degrees (Appendix 3-3), and this knowledge was not collected or integrated following a specific methodology or protocol. In the ISR, Inuit knowledge and observation was used to determine changes to and concerns about the fishery, subsistence harvest levels, and char condition. In Nunavut, the CBMP proponents used IKO to determine the location of spawning grounds for research related to the CBMP, as well as subsistence harvest levels. In Nunavik, Inuit observations were used to determine locations of disrupted fish passage associated with natural causes or hydroelectric developments. In
Nunatsiavut, voluntary reporting of subsistence harvest levels was recorded, and Creel surveys had been used in the past. All programs collected IKO through community meetings, local land claim organizations, or community monitors.
All programs utilized community meetings, reports, and publications for reporting and outreach with the local community (Table 4). Additional reporting and outreach methods included dissemination of information through Char Working Groups (ISR), radio broadcasting (Nunavik and Nunatsiavut) and outreach in local schools (all char CBMPs except Nunavut).
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Table 4. Comparison of information obtained from the thematic content analysis of six Arctic Char community-based monitoring programs across the Canadian Arctic, summarized for several subthemes under the main theme of ‘Program Operations’* (n=9 key informant interviews and n=35 documents).
PROGRAM Rat River, Hornaday Kuujjuaq Wellington Nephijee and Voisey, Nain NAME ISR River, ISR River and Bay and Koksoak and Okak PROGRAM Fish Lake, Ekalluk rivers, Stocks, OPERATIONS ISR River, Nunavik Nunatsiavut SUBTHEMES Nunavut Subsistence Subsistence Subsistence Subsistence Subsistence≠ Type of Fishery Subsistence Commercial† Recreational Commercial§ Recreational Commercial† Recreational Manage Manage Main Purpose Monitor stock Monitor stock Monitor stock commercial Fish passage commercial of CBMP trends trends trends fishery fishery Length of 21 27 25 45 39 39 CBMP (years) DFO DFO DFO DFO DFO NWMB Nunavik RC NG and NICG Program FJMC FJMC FJMC HTA HFTA Nain RC Partners HTC HTC HTC University University University University University University Local Plant Local Plant $20K/year (in- Cost $90K/year $28K/year Undisclosed community Undisclosed Undisclosed (total) (total) component) Federal Gov. Funding Federal Gov. Federal Gov. Federal Gov. Land Claims Federal Gov. Land Claims Sources Land Claims Land Claims Land Claims University Land Claims University
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Morphometric Morphometric Morphometric Morphometric Morphometric Morphometric s s s s s s Meristics Meristics Meristics Monitoring Meristics Meristics Meristics CPUE CPUE CPUE Methods CPUE Contaminants CPUE Harvest Harvest Harvest Harvest Fish Passage Harvest Stock Assess. Stock Assess. Stock Assess. Stock Assess. Migration Stock Assess. Environmental Environmental Environmental Frequency of Annually Annually Annually Annually Annually Annually Monitoring Timing of Late Summer Late Summer Late Summer Late Summer Late Summer Late Summer Monitoring to Early Fall to Early Fall to Early Fall Community Seasonally Seasonally Seasonally Seasonally Seasonally Seasonally Monitor Hired Training Federal Gov. Federal Gov. Federal Gov. Federal Gov. Nunavik RC Federal Gov.
IKO Included Yes Yes Yes Yes Yes Incidental Meetings Meetings Meetings Radio Char WG Char WG Radio Char WG Meetings Meetings Reporting and Newsletters Newsletters Meetings Newsletters Reports Reports Outreach Reports Reports Reports Reports Publications Publications Publications Publications Schools Publications Schools Schools Schools
* Acronyms used in Table: CPUE = Catch-per-unit-effort; DFO = Fisheries and Oceans Canada; FJMC = Inuvialuit-Canada Fisheries Joint Management Committee; HTA = Hunters and Trappers Association (Nunavut); HTC = Hunters and Trappers Committee (ISR); HFTA = Hunters Fishers and Trappers Association (Nunavik); ISR = Inuvialuit Settlement Region; NG = Nunatsiavut Government; NIGC = Nain Inuit Community Government; NWMB = Nunavut Wildlife Management Board; RC = Research Centre; WG = Working Group. § Small-scale commercial fishery. † Large-scale commercial fishery. ≠ No data obtained from subsistence fishery through CBMP.
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All six char CBMPs were compared with Danielsen et al.’s (2009) models presented in Table 1 to determine which category they fit on the spectrum of community-based monitoring program designs (Table 5). Out of the five possible models, with Model 1 being externally driven and executed, and Model 5 being autonomous local monitoring, five out of the six char CBMPs fit Model 3: Collaborative monitoring with external data interpretation. The programs that fit Model 3 included all three CBMPs from the ISR, the
Nunavut CBMP and the Nunatsiavut CBMP. The char CBMP from Nunavik fit Model 4:
Collaborative monitoring with community-requested advice from external agencies and local data interpretation because the data analysis was carried out by the Nunavik Research
Centre, a regional land claim organization, instead of the federal government.
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Table 5. Model categories (from Table 1) assigned to each of the six Arctic Char CBMPs analysed in this study* (n=9 key informant interviews and n=35 documents).
Data and Community Primary Primary Initiated by Executed by Samples CBMP Program Name Involved in Data Users of Whom Whom Analysed by Model Design Gatherers Data Whom Community Community Community Rat River, ISR Community Co-Mgmt. Co-Mgmt. Yes Fed. Gov. Co-Mgmt 3 Monitors Fed. Gov. Fed. Gov. Fed. Gov. Hornaday Community Community Community Community River, Co-Mgmt. Co-Mgmt. Yes Fed. Gov. Co-Mgmt. 3 Monitors ISR Fed. Gov. Fed. Gov. Fed. Gov.
Kuujjuaq Community Community Community Community River and Fish Co-Mgmt. Co-Mgmt. Yes Fed. Gov. Co-Mgmt 3 Monitors Lake, ISR Fed. Gov. Fed. Gov. Fed. Gov.
Wellington Community Community Community Community Bay and Co-Mgmt. Monitors and Co-Mgmt Reg. Gov. Yes Fed. Gov. 3 Ekalluk River, Reg. Gov. Fed. Gov. Reg. Gov. Fed. Gov. Nunavut Fed. Gov. Techs Fed. Gov.
Nephijee and Community Koksoak Community Community L.C. Org. Yes Monitors and L.C. Org. 4 rivers, L.C. Org. L.C. Org. Industry Local Techs Nunavik
Voisey, Nain, Community Reg. Gov. and Okak Monitors and Fed. Gov. Fed. Gov. Yes Fed. Gov. Fed. Gov. 3 Stocks, Fed. Gov. Industry Nunatsiavut Techs
*Abbreviations used: Co-Mgmt = co-management board; Fed. Gov. = Federal Government; L.C. Org. = Land Claim Organization; Reg. Gov. = Regional Government, e.g. Government of Nunavut and Nunatsiavut Government); Tech = Technicians.
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4.3.2 Community Perspectives on CBMPs
Subthemes within this theme covered aspects of how community perspectives, or changes to community perspectives, were seen to affect char CBMPs. In the analysed documents and interviews, these themes were presented in the context of how they can affect the success or failure of a community-based monitoring program.
4.3.2.1 Community Use of Char Resource
Two key informant interviews of nine and 21 documents out of 35 from all four land claim regions (Table 3) contained information about community use of char resource, specifically focusing on how and where char were fished for subsistence purposes, including consumption and sharing of fish among families. Arctic Char had always been, and remained, an important country food, highly valued by the Inuit as an excellent source of nutrition. This was described in Fisheries and Oceans Canada (2014; p.4), “Arctic Char is very important to the social connection, cultural definition and food requirements of
Inuit…Arctic Char play an important role in the nutrition and social culture of the community
– fostering the continuation of traditional culture and lifestyles, provision of traditional foods, and local self-sufficiency.”
While all six char CBMPs analysed in this study had a subsistence fishery at locations where monitoring was occurring (Table 4), not all of the programs were carried out to monitor subsistence harvest. The three CBMPs in the Inuvialuit Settlement Region and the program in Nunavik were driven by the need for subsistence fisheries monitoring
(Table 4). Char populations in Nunavut and Nunatsiavut Arctic Char CBMPs were large enough to sustain commercial fisheries and as such, CBMPs focused on management of commercial harvests. The importance of the subsistence fisheries, and local employment
! ! 222! created through the commercial fishery, helped maintain local interest in community-based monitoring (FG key informant from Nunavut CBMP and FG key informant from
Nunatsiavut CBMP, n=2/2, Table 3).
4.3.2.2 Lifestyle and Social Changes with Potential to Alter CBMP Design
A total of eight data sources (interviews n=4/9 and documents n=4/35, Table 3) contained information about changes to lifestyle and social changes that affected subsistence CBMPs. For example, the passing of elders and a decrease in nomadic lifestyle resulted in the loss of relying on a cycle of subsistence harvesting to survive, that, in turn, resulted in an altered use of fish resources (two documents from ISR: Paylor et al., 1998;
Bell and Harwood, 2012). A decrease in the use of dog teams since the 1970s also meant fewer fish were required to feed dogs (document from Nunavut: Kristofferson and Berkes,
2005).
As reported by two FG key informants (ISR and Nunavut, n=2/4, Table 3), in recent times, people were fishing closer to their community than in the past, both because of the decrease in nomadic lifestyles with the creation of settlements, and more recently because of the high cost of fuel required for travel to fishing locations. This was also evident to
Dumas (1990), Paylor et al. (1998), and Kristofferson and Berkes (2005). According to the authors a shift in fishing locations closer to communities, or closer to hunting locations so the activity of fishing could be combined with the harvest of other species, to save money on fuel (for overland vehicles used for travel) was observed. This resulted in a change in commonly fished locations. According to Paylor (1998, p.162), “Altering the traditional fishing practices employed in the fishery imposes the risk of disturbing both social and stock conditions. Therefore, the monitoring program should continue to collect data from
! ! 223! active fishers, in addition to carrying out separate random sampling on various components of the stock.”
Another example of a lifestyle and social change with the potential to affect the subsistence char CMBPs was population increase and growing family sizes (n=3/4 documents, Table 3). According to Dumas (1990), Paylor et al. (1998), and Kristofferson and Berkes (2005), an increase in family size results in the need for more food to feed family members, that in turn paired with limited economic opportunities in communities, leads to an increase in subsistence fishing, which resulted in increased interest in Arctic
Char subsistence harvests in Kuujjuaq Nunavik, Ulukhaktok ISR, and Cambridge Bay
Nunavut. Lastly, the FG key informant from the Nunatsiavut char CBMP shared, “with the land claims being not settled too long ago, [there have been] a lot of growing pains and personnel changes…fisheries [commercial and subsistence] issues are just one minor element of what they’ve been trying to do.”
4.3.2.3 Ongoing Community Involvement in CBMP Design and Implementation
All key informants (n=9/9) and 14 of 35 documents (Table 3) shared information on community involvement in the design and implementation of the CBMP. All key informants (n=9/9, Table 3) expressed that the CBMP needed to be initiated and executed as a co-operative effort between the local decision-makers and external government, and that without community acceptance of the char CBMP, the program would not succeed. In addition, regular community meetings were important among all char CBMPs (Table 4, see
Reporting and Outreach) to obtain local input and review of the char CBMPs.
However, the approach to community involvement in the CBMP design and implementation varied among the six programs (Table 4). In the Ulukhaktok (ISR),
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Cambridge Bay (Nunavut), and Kuujjuaq (Nunavik) char CBMPs, household surveys were conducted during a random subset of years within each program. Household surveys were seen as important for collecting data and to allow community fishers to have an opportunity to interact with the community monitors and provide feedback on program design and implementation (n=4/9 documents, Table 3). However, household surveys were not carried out consistently in these three CBMPs. Two FG key informants (n=2/9, Table 3), one working with the Nunavut char CBMP and the other with the Nunatsiavut CBMP, expressed that involvement in program design and cooperation from the local fish plant, and harvesters contributing to the commercial capture of char, was a crucial element for program success.
Another form of community involvement in program design and implementation was seen in the ISR, which had Char Working Groups with community representatives who would provide feedback and input (n=5/9 key informants, Table 3).
All key informants (n=9/9, Table 3) reported community monitors having a specific role in char CBMP implementation. Community monitors were responsible for scientific capture of char, and sampling scientific catches in addition to subsistence catches from local fishers. Community monitor sampling focused on length and weight measurements along with tissue and otolith collection (n=9/9 key informants, Table 3). Ageing and sample analyses were all carried out by regional research centres (i.e. Nunavik and Nain Research
Centres) or Fisheries and Oceans laboratories (ISR and Nunavut). All key informants (n=9/9 key informants, Table 3) stated that data entry and analyses, securing of funds, funding reports, and dissemination of results, were all the responsibility of the char CBMP leader. In the ISR, Nunavut, and Nunatsiavut these tasks were conducted by FG staff. In Nunavik, these tasks were carried out by the fish biologists at the LCO (Nunavik Research Centre).
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According to one FG key informant (n=1/9, Table 3) working on char CBMPs in the
ISR, program leaders were required to ensure that monitors could accurately record data, monitored the work for data and sample quality control, trained monitors, checked that equipment was working, and ensured monitors were paid fairly and in a timely manner
(usually through the local organization). In addition, the same key informant explained that program leaders were also required to ensure gas and other supplies were available early for an on-time program start and adjusted the work and contracts as necessary (e.g. extending the annual end date of the program if the fish run was later than usual). According to this key informant, all this work on the part of the program leader was critical to the success of char
CBMPs.
As reported by two FG key informants (n=2/9, Table 3), one from Nunavut and one from the Nunatsiavut char CBMPs, communities were not accustomed to taking on the tasks conducted by the program leader, having relied on external organizations to head these initiatives on their behalf. As the FG Nunatsiavut key informant shared, “in our case, there was a long history, going back to the early ‘70s, and I think it’s tradition for people [in communities] to just expect to see Fisheries and Oceans people in red floater coats showing up every summer.” However, the Nunavut FG key informant explained this did not reflect that communities were not interested in being involved, “When [communities] become comfortable with these programs and they get used to it and you show them the results and you point out to them how important it is for maintaining the resource so that their grandchildren can fish there too, they often buy into the programs. There is a learning curve and it does take time, but once in place, [char community-based monitoring] is an excellent tool.”
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4.3.2.4 Community Engagement
Community engagement by the program leader was tied to a sense of community responsibility, involvement, empowerment, and pride in the program. Eight of nine key informant interviews and seven of 35 documents (Table 3) provided information supporting this concept. The program leader needed to maintain consistent interest and involvement in the project to retain – and gauge – community enthusiasm and engagement. As an FG key informant from the ISR explained, “never leave the projects unattended, they do not run themselves.” According to a second FG key informant from the ISR and one from Nunavut
(n=2/8, Table 3), a constant feedback loop between the program leader, the community monitors, and LCO was required. This constant feedback led to on-going community involvement in decisions related to the CBMP design and implementation, leading to a sense of shared stewardship of the resource. As reported by an FG key informant from
Nunatsiavut (n=1/8, Table 3), “If the community could be more engaged in with working with us…have them more [involved] in the overall program rather than having them pigeon- holed for [sampling and reporting harvest] related duties…it would go a lot further to engage people in the communities to understand a little bit more of everything going on…a lot of the communities don’t know which way [the data or results] are going to be used.”
4.3.2.5 Community Monitor Retention
As reported by one FG key informant from the ISR in both their interview and a document they authored (n=1/1 key informant, n=1/1 documents, Table 3), local LCO
(hunters and trappers organizations) played an important role in ensuring community monitor retention through the identification of local monitors who were both familiar with local fishing sites and practices. The same key informant also expressed the importance of
! ! 227! recognizing the contribution of local fishers in the success of the char CBMP, because without the samples and data they obtained, the three programs in the ISR would not have been possible. In some cases, fisher recognition was rewarded in the form of cash, public accreditation, or gifts (Bell and Harwood, 2012). As Bell and Harwood (2012, p. 427) noted,
“It is paramount to strive for consistency in samples, often by using the same [community monitor every year]. Without this effort, unnecessary error and bias can be introduced that will be difficult to detect or control…since these studies run for many years, if not decades, it is prudent to train for future replacements while instilling interest and pride in the younger generation” and (p. 429) “aboriginal harvest monitors work as an integral part of a scientific team while still maintaining and using local skills and knowledge…the importance of fairly recognizing and justly compensating Aboriginal partners for their contributions to program design and delivery ‘at par’ with science partners cannot be overstated.”
4.3.2.6 Community Perceptions of Program
Four of nine key informant interviews (Table 3, one FG and two LCO key informants from the ISR CBMPs and one FG key informant from Nunatsiavut) and nine documents of 35 covering the ISR and Nunavut regions (Table 3) described how community perceptions of char CBMPs can affect the outcomes of a program. According to these sources, there were two requirements for community acceptance of the CBMP: 1) the CBMP needed to address the concerns of the local fishers in order to have fishing community support and acceptance of the purpose and design of the CBMP and, 2) the program leader and LCOs needed to maintain the ongoing interest and acceptance of the
CBMP by hired community monitors, as the monitor’s commitment to the program could influence other fishing community member’s perspectives. If these two items could be
! ! 228! addressed, community compliance of management decisions (e.g. harvest quotas, household quotas, mesh sizes used for harvest) resulting from the CBMP would mostly likely occur. This concept was further explained by Bell and Harwood (2012, p. 428), “the results from a scientific project in which scientists arrive from the south, conduct the work, and leave at the end of the field study are often (and understandably) not viewed favourably or understood by the communities affected by them.” Also, Paylor (1998, p. 163) explained,
“the feedback of community perceptions plays a fundamental role in the implementation of practical management initiatives…in order to develop appropriate management strategies resulting from the monitoring results, local opinion and social conditions must also be monitored”.
4.3.3 Insights, Considerations, and Recommendations
4.3.3.1 Benefits and Positive Attributes of the Program
Six of nine key informant interviews and 15 of 35 documents (Table 3) contained information on benefits and positive attributes of the programs, including information from
CBMPs in all four of the Inuit land claim regions. According to the two FG key informants
(n=2/6, Table 3) involved with the two char CBMPs that monitored commercial harvests
(Nunavut and Nunatsiavut), and four documents from the Nunavut CBMP (n=4/15, Table
3), a positive attribute of the programs were having the fish plant as a consistent platform and central location for the in-community monitoring activities such as collecting data and samples. This removed the need for monitors or technicians to travel to fishing locations to obtain data and samples. The char processed at the fish plant were traceable to the location where they were harvested, due to the protocols followed by the commercial fishers. Therefore, the fish plant ensured that a large number of char could be accurately
! ! 229! sampled. Also, as the fish plants employed community members, it ensured community involvement in the two CBMPs, and fostered cooperation and continuing interest in monitoring to sustainably manage the Arctic Char resource.
A similar benefit was described by the two LCO key informants (n=2/6) and one document (n=1/15, Table 3) from the Nunavik char CBMPs. The Nunavik Research Centre
(NRC) also served as a central location to receive fish to be sampled in a single location.
It was also explained that a Lake Trout (Salvelinus namaycush) winter fishery monitoring program was highly successful both because the communities were familiar with the NRC process for submitting fish, it was an easy process to follow, and the fishers were paid per fish so many Lake Trout were sent in for processing (no further information was obtained on the monitoring of the Lake Trout winter fishery).
Within the ISR, two of six FG key informants (Table 3) and ten of 15 documents
(Table 3) described six benefits or positive attributes of the three programs: 1) collection of additional data or samples in the field for other research projects; 2) participation at all levels of the monitoring process resulted in the local LCOs setting of voluntary quotas and creating local fishing plans, and community fishers being in full compliance with these management decisions; 3) harvest enumeration studies continued to play a role in management by answering questions that could not be addressed through science-based evidence alone; 4) costs of these programs were relatively small compared to the long-term benefit; 5) the result of sustainable harvest rates; and, 6) successful co-management through the trust and agreement on management approaches by both federal government and land claims organizations.
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4.3.3.2 Changes to Fishery that Affect CBMPs
Changes to the local fishery that affected char CBMPs were comprised of changes in human fishing behaviours, such as increasing or decreasing pressure on the char fishery
(described above under Changes to Community Interests that Affect CBMPs). According to six of nine key informants and 15 of 35 documents (Table 3), the other change to the char fisheries with the potential to affect CBMPs was unforeseen environmental change.
An example of this was observed in the Hornaday River CBMP (ISR). As reported by two key informants, one from the FG and one from an LCO, both involved in this CBMP, the outlet of the Hornaday River that drains into Darnley Bay had shifted due to melting permafrost and erosion. This was the location where people used to fish, but it had become more difficult for the community to access. As a result, local fishers reportedly relocated their fishing efforts to the Brock River. However, according to the FG key informant, the
Arctic Char community-based monitoring program had occurred at the Hornaday River for over 20 years, and FG program lead was reluctant to start over with a new CBMP in a new location. The same key informant and one LCO key informant (n=2/6, Table 3) also reported that community interests in the CBMP shifted as fishing at this site waned, and the community suggested a second Arctic Char community-based monitoring site be setup at the new Brock River subsistence fishing location.
4.3.3.3 Changes to Government or Decision-Makers that Affect CBMPs
Four of nine key informants (Table 3), three from the ISR CBMPs and one from the
Nunatsiavut CBMP, and eight of 35 documents (Table 3) provided information on this subtheme, and described how leadership changes resulted in disruptions to the delivery of the CBMP. According to one ISR char CBMP FG key informant, who was also a long-
! ! 231! standing CBMP program leader, if government staff involved in CBMPs retired or moved onto other projects, a loss of institutional memory resulted. This same key informant also explained that it would take time for the new program leader to build trust with the community and this could lead to delays in program delivery. A second FG key informant
– who had recently taken over as the program lead on an ISR CBMP – explained that they did not have a good grasp on the community consultation work that had occurred in the long-standing CBMP even after working on the program for two years. This same key informant also reported plans to add new components to the CBMP to collect additional data, thus altering the established design.
4.3.3.4 Struggles and Challenges
All nine key informants and 20 of 35 documents (Table 3) provided information on the subtheme of Struggles and Challenges. The two themes of Struggles and Challenges and Recommendations and Considerations (see below) were intrinsically linked, in that recommendations could often be ascertained from expressed struggles and challenges.
There was one struggle shared for which no direct recommendation was provided.
All nine key informants (Table 3) reported that voluntary fisher log books (used to document fishing location, date, method, catch-per-unit-effort, and number of each species captured) did not work. Reported issues with log books included: not all catches were logged throughout the entire fishing effort, many fishers forgot the log books at their camps or forgot to submit them entirely, the few that were submitted contained incomplete data, and there was no way of verifying the data that had been submitted. However, according to the FG key informant from the Nunavut CBMP, even if 25% of log books were handed
! ! 232! in, and half of them contained reliable data, that was better than receiving no information at all.
The use of harvest-based monitoring and harvest studies data was also considered to be a challenge in CBMPs, as reported by one of nine key informant interviews and four of the 26 documents (Table 3). According to Paylor (1998), “A reliance on catch data in community-based fisheries management presents scientific mangers with several challenges resulting from biases such as gear selectivity [and targeted size selection resulting in only mature char being harvested]. It is often difficult to develop catch-per- unit-effort models for small-scale subsistence fisheries, where fishing effort, timing and location can be affected by social and cultural influences, as well as biological influences”.
Paylor et al. (1998) also expressed concerns regarding fish harvest-based monitoring, explaining that larger harvested mammals (e.g. caribou, muskox, whales) were usually accurately reported in recall surveys, whereas the number of fish harvested was not easy to remember as they were harvested in large numbers over longer periods of time. Therefore, harvest surveys and harvested-based monitoring could be subject to biases and potentially inaccurate data if not designed properly. However, if designed properly, they could be a valuable source of information for social and economic analyses, in addition to biological analyses, and one way of incorporating IKO into CBMPs (Bell and Harwood, 2012). !
4.3.3.5 Recommendations and Considerations
Recommendations and considerations for Arctic Char community-based monitoring programs were expressed in all interviews (n=9/9, Table 3) and 26 of 35 documents (Table 3) from all four land claim regions.
! ! 233!
As reported by two of nine key informants (Table 3, one from ISR and one from
Nunatsiavut), one recommendation was to the take the time to design the program properly from the beginning. This meant that the program leadership needed to have a clear understanding of why the program was being initiated, including management goals.
According to the FG key informant from the ISR who had been a CBMP program lead for
20 years, any group initiating an Arctic Char community-based monitoring programs needed to ask “what question are you trying to answer?” and “is community-based monitoring the appropriate tool to answer the question?”. If community-based monitoring was determined to be the appropriate tool, program goals needed to be established and agreed upon amongst all parties involved, and statements on desired data and outcomes also needed to be developed. Without this, the program may be appealing to some, but the end product may not address management needs. Once these steps were completed, easily understood monitoring protocols needed to be constructed to ensure the inclusion of IKO, adequate sample size, and consistency (repeatability) in sample collection.
Once the above design parameters were decided by program leader and the supporting organizations, “A division of labour is needed in the actual conduct of the fieldwork. The planners must recognize and allow for partners to bring their own special skills and knowledge to bear on the work. Each must recognize the contributions, constraints, and successes of their counterparts. There will be both fieldwork specialists (likely led by the harvesters, with their lifetime knowledge of where, when, and how to access harvested resources) and technical-reporting and analytical specialists (likely led by the scientific staff).
Each must trust the judgement, planning, and field delivery skills of the other. If both come
! ! 234! with experience, mutual respect, and a willingness to seek assistance and advice as needed, the project will have the best chance to be successful” (Bell and Harwood, 2012, p. 427).
The FG key informant from the Nunatsiavut CBMP (n=1/9, Table 3) recommended that a better understanding of the subsistence fishery harvest was important to complement the removals from the commercial fishery, especially when the subsistence harvest would contribute significantly to the total removals from the stocks. It was recommended that all removals from the population should be known for the best possible management approaches to be considered. This key informant, along with a FG key informant from the ISR CBMPs
(n=2/9, Table 3) also suggested to be curious, imaginative and have the forethought to collect additional data samples (within logistical and funding means) so that you can collaborate with researchers in the future when questions arise that cannot be answered by monitoring alone. Collaborations with research studies allowed for a full picture of what was happening within the fishery. Examples of additional research that was done with data and information collected from the Nunatsiavut char CBMP included: by-catch, natal locations, oxygen isotopes from otoliths to infer temperature histories, and studies on the use of the resource as country food.
The four LCO key informants (n=4/9, Table 3), two from the ISR CBMPs and two from the Nunatsiavut CBMP, reported four distinct recommendations and suggestions: 1) conduct a user-needs assessment before starting the execution of the CBMP; 2) make use of the knowledge gained through the experiences of other communities with Arctic Char
CBMPs; 3) learn as much as you can from the program leader while they are in the community; and, 4) create training modules for the in-community CBMP members so they can be used in future training and as an educational resource when the government program
! ! 235! leader may not be in the community. Similar suggestions, were made by an FG program lead key informant from the ISR CBMPs, and included having the program lead or government biologists on site at the start of each monitoring season, or for the whole season if possible, in order to have more direct involvement with the community monitors. According to this same key informant, people learned better by seeing and doing, than reading, and suggested that monitoring methods and procedures be documented through photos and video recordings to create a training package for the in-community program members.
The majority of documents (n=26/35, Table 3, including CBMPs from all four land claim regions) also described the recommendations and suggestions outlined above.
Additional suggestions for Arctic Char CBMPs included: 1) incorporating efforts to examine the impacts of industry, habitat alteration, and climate change on char populations; 2) monitoring prey species distribution and abundance, and identifying or improving understanding feeding habitat; 3) monitoring parasite and contaminant loads in char; 4) monitoring water quality, water levels, and sea ice thickness; 5) collecting fishery- independent data in addition to fishery-dependent data in order to remove sampling bias (e.g. add scientific net sets and juvenile char sampling); 6) understanding stock distinctions (where not already established, e.g. ISR); 7) expanding sampling programs to include spring and/or winter monitoring; 8) understanding inter-annual variation in abundance of each stock to assess sustainable harvest rates, as natural variation in recruitment and growth may impact exploitation; 9) improving community harvest surveys by including questions about char biology, ecology, environment, and habitat conditions that have the potential to influence harvest; 10) considering harvest-based monitoring as a practical solution for remote subsistence fisheries that are difficult or costly to reach; 11) creating or engaging a
! ! 236! community champion for the CBMP to assist with community acceptance and assistance with the program; 12) conducting program evaluations; and, 13) including periodic household surveys which could provide CBMP leaders and fisheries managers with insight into factors impacting the fishery (e.g. number of nets used, changes in fishing locations, subsistence needs, and the degree of community support regarding management options).
4.4 Discussion
This study used a qualitative exploratory design to examine program components and factors required to initiate and execute long-term Arctic Char community-based monitoring. An analysis of 35 documents obtained through a literature review and nine key informant interviews were conducted for six Arctic Char (and closely related species) community-based monitoring programs across the four Inuit land claim regions in the
Canadian Arctic. The thematic content analysis resulted in a total of 33 subthemes under three main themes: program operations, community perspectives, and insights, considerations, and recommendations. All six char CBMPs analysed provided data towards informed management, used for setting commercial quotas, voluntary subsistence quotas, or voluntary temporary fisheries closures. This study demonstrated that community perspectives and changing lifestyles, as well as environmental changes impacting a fishery, can have direct effects on the successful operation of a community-based monitoring program.
4.4.1 Program Operations
In all six Arctic Char CBMPs analysed, the overall purpose of the CBMP was to ensure the continued local use of the resource, whether it be for subsistence, commercial, or sport-fishing (recreational fishing), or a combination of these uses. Specific program
! ! 237! purposes addressed local concerns and included: monitoring stock trends (ISR), providing data towards managing a commercial fishery (Nunavut and Nunatsiavut), and monitoring and enhancing fish passage (Nunavik). Within the five models of the community-based monitoring spectrum (Table 1), five of the six char CBMPs analysed fit Model 3:
Collaborative monitoring with external data interpretation. The char CBMP in Nunavik fit Model 4: Collaborative monitoring with community-requested advice from external agencies and local data interpretation because the data analysis was carried out by the
Nunavik Research Centre, a regional land claim organization.
Monitoring parameters, methods, program partners, and funding sources varied across the six programs. This was expected considering the differences in the land claim structures in the four land claims regions, as well as the differences in the local landscape and environment across such a vast geographic area. Limited information was obtained regarding the cost of Arctic Char community-based monitoring programs. However, the different CBMP approaches, scales and scopes used in the programs analysed from across the country would have likely hindered cost comparisons or made them irrelevant.
Despite the aforementioned differences among CBMP operations, common aspects were also identified. Monitoring occurred annually, in the late summer and/or early fall.
In all programs, an FG or LCO biologist or scientist was the program lead. In Nunavik, this was a representative from the Nunavik Research Centre, a division of the Makivik
Corporation (created under the Nunavik Inuit Land Claim). In the remaining five programs the lead was an FG individual from southern Fisheries and Oceans Canada offices.
Community monitors were hired on a seasonal contract basis to collect samples and data.
In all programs except in Nunavik, government (Fisheries and Oceans Canada) staff
! ! 238! biologists or research scientists provided training for local monitors. Nunavik Research
Centre staff provided training to local monitors or conducted the monitoring themselves.
Program leaders were also responsible for data analyses as well as dissemination of results.
Inuit knowledge and observation was considered in all six programs. However, no structured process to include IKO was present in any of the programs. In five of the six char CBMPs, Fisheries and Oceans Canada, LCOs and the local Hunters and Trappers organizations were the primary users of the data. In Nunavik, the community Landholdings
Corporation were the primary users of the data.
4.4.2 Community Perspectives on Char CBMPs
The analysis of available data and information revealed that Arctic Char remain an important resource for subsistence use in all six CBMPs. All key informants expressed that an Arctic Char CBMP needed to be designed and executed as a co-operative effort between the local decision-makers and federal government, and that without community acceptance, the program would likely not have succeeded. The community perspective on the char
CBMP was influenced by the level of involvement of community members in the design and implementation, as well as the program leader’s effort to gain community trust and input, and to maintain an open dialogue. Similar to these results, in a literature review of
84 sources examining key elements of Arctic and Subarctic community-based monitoring,
Kouril et al. (2016) found that local interest was an important element to ensure long-term motivation of monitors. Kouril et al. (2016) and Brook et al. (2009) also found that a local champion or coordinator, who saw the value for the community in the long-term, was important to keep communities informed and facilitate capacity building at the local level, as did an FG program lead key informant from the ISR.
! ! 239!
Despite the results of the analysis revealing that communities needed to play an active role in CBMP design for community acceptance of the program, the analysis also revealed that the six char CBMPs were mostly designed and led by government scientists and biologists, whereas local monitors played the role of scientific data and sample collectors or field technicians in all six programs. Kofinas (2012) shared a similar observation, outlining that community-based monitoring in northern Canada usually relied on scientific-based methods of data collection and knowledge assessment.
Through the analysis of available sources from the six char CBMPs, an important consideration revealed was that program member turnover affected the CBMP due to a loss of institutional memory. As a result, this could affect the integrity of data collected throughout the life of a program. Thus, the development and maintenance of a program design document as well as a methodologies training package could help to ensure the security and transfer of institutional memory as well as serve as training tool for community monitors or future program leads.
The analysis of available data from the six char CBMPs also revealed that lifestyle and social changes can lead to a change in community interests regarding the use of the char resource. For example, in this study, the increasing cost of fuel required to travel to fishing sites resulted in a shift to fish in locations closer to the community or hunting grounds. Whereas, increasing population and family sizes led to increased pressure on the fishery as an increased amount of country foods was required. The Inuit are a resilient people who have continuously and rapidly adapted to changes in their environment, culture and lifestyle (Huntington and Fox, 2005; Ford and Pearce, 2010). As a fishing community
! ! 240! is adaptable in their use of the Arctic Char resource, their interests and use of the resource can also shift rapidly, having the potential to alter monitoring regimes without notice.
4.4.3 Insights, Considerations, and Recommendations from Six Char CBMPs
One of the insights resulting from the thematic content analysis was the benefit of having a single location to carry out monitoring, where data and sample collection could be conducted without the need for on-going travel by community monitors. Analysis of the three char CBMPs in Nunavut, Nunavik and Nunatsiavut indicated that a central location for fish sampling helped with ease of sampling as well as accuracy. A fish plant, research centre, or common fishing location were suggested as potential locations.
A recommendation revealed through the analysis explained the need for a complete understanding of the entire system, including the ecosystem and social system. All char removals from the population, including subsistence, commercial and recreational removals, should be monitored to have a complete understanding of total harvest.
Additional data collection suggestions through included: collecting data and samples for research collaborations, monitoring char health such as parasites and contaminant loads, expanding monitoring programs to include spring and/or winter monitoring and environmental parameters such as water quality, habitat and prey, and understanding stock structure as well as natural inter-annual variation in abundance of each stock. Adding these parameters to a monitoring program could result in a more in-depth understanding of the char population, leading to better management decisions.
A consideration revealed through the thematic content analysis was the need to design the CBMP properly from the beginning by asking “what question are you trying to answer?” and “is community-based monitoring the appropriate tool to answer the question?”.
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If community-based monitoring was the correct tool, program goals needed to be established and agreed upon by all parties. Additionally, program evaluation was recommended, as were user-needs assessments, however, no descriptions of how these evaluations should be conducted were provided. On-going program evaluation could be included as an essential tool in assessing both the accuracy of the data and the efficacy of results in addressing management and community needs for decision-making. In two separate literature reviews examining key elements in community-based monitoring, Kouril et al. (2016) and Johnson et al. (2015) also found that evaluation ensured program goals were being met, including linking the resulting data to decision-making.
While no explicit information on the definition of program efficacy was obtained from the analysis of the six programs, several factors that could be used to measure efficacy were implied. These included long-term accurate data collection, results leading to management decisions, maintained community interest and acceptance of the program, and on-going funding. However, the term “efficacy” could lead to issues of subjective interpretation. For example, one key informant might think their program was successful because the data was used by local decision-makers to set quotas or to influence policy.
However, another could argue all programs were effective if they simply existed, collected some form of data, and created seasonal jobs in the community. As such, further study into the evaluation of efficacy of char CBMPs should be conducted.
Another insight revealed through the thematic content analysis of the six programs was the requirement to be prepared for unexpected environmental changes that have the potential to shift local fishing locations, such a permafrost melt altering the outlet of a river into the ocean. This type of event could result in a sudden change of fishing locations, thus
! ! 242! rendering long-term monitoring locations ineffective. One of the findings of this study was that Arctic Char CBMPs could to be designed to use appropriate monitoring indicators and methods that will detect changes over time, while still being flexible to accommodate changes to community use of the resource. This framework for monitoring, referred to in the peer-reviewed literature as adaptive monitoring, enables monitoring programs to evolve iteratively as new information emerges and questions or interests change (Ringold et al.,
1996; Lindenmayer and Likens, 2009; Lindenmayer et al., 2011). It is an iterative learn- and-adapt approach to monitoring whereby all program steps from the development of the conceptual model through to data interpretation are linked in iterative steps without affecting the integrity of the data (Lindenmayer et al., 2011). Adaptive monitoring is particularly relevant for subsistence fishery CBMPs.
In addition, an adaptive co-management process is used to manage the char fisheries in the ISR (Ayles et al., 2007) and Nunavut (Kristofferson and Berkes, 2005). The adaptive management approach realizes the complexity of ecosystems, and the need to synthesize experience, experimentation and new ideas by following a learning by doing approach, in order to deal with uncertainties and learn about the system (Holling, 1978; Kristofferson and Berkes, 2005). The data produced by an adaptive char CBMP could also provide needed information towards adaptive co-management processes.
4.4.4 Additional Recommendations and Suggested Future Research
Meaningful incorporation of IKO, as well as Inuit monitoring methods, could be a key to well-founded community-based monitoring, leading to increased community engagement and increased understanding of the study system or population. Berkes et al.
(2007) shared examples of the importance of including Inuit approaches and methods, IKO,
! ! 243! as well as local indicators in monitoring regimes. While Berkes et al. (2007) pointed out that IKO could not provide information at certain scales (e.g. at the cellular level), they found local indicators and combinations of observations that led to new information in monitoring programs not obtained through scientific methods or instrumentation.
Huntington et al. (2004) in a paper comparing scientific and Inuit Traditional knowledge on a variety of documented environmental and ecological changes in the Canadian and
Alaskan north, found that IKO was important for detecting trends and new phenomena when monitoring environmental change. Parlee et al. (2014) also found that Łutsël K’é
Dene Traditional Knowledge was important in the long-term monitoring of caribou and moose populations facing exposure to new diseases resulting from climate change, especially when scientific resources and funding became limited.
Manseau et al. (2005) explained that IKO in marine resource management in the
Inuvialuit Settlement Region, including marine fisheries, was used to redefine marine health indicators, influence data gathering and influence the analysis and interpretation of results. This rich knowledge base could also provide local expert information on indicator benchmarks and baseline information on the fishery. While all six CBMPs analysed in this study incorporated some form of IKO, no formal inclusion processes or methodologies existed. As seen in other types of community-based monitoring programs, a well-defined process is required to capture and integrate IKO in a reliable, repeatable and accurate manner, allowing for the determination of patterns and trends over time, and is in a format that is easy for community fishers to use. Gearheard et al. (2007) describe the Igliniit technology that allows Inuit hunters to record their observations on maps while on the land with the purpose of monitoring changes occurring in the Arctic. This tool provides a means
! ! 244! for standardized knowledge sharing and can be customized to the needs of each community.
Similar observation entry and management systems could be considered for the inclusion of IKO in Arctic Char CBMPs.
No information was shared on data management other than the need for quality control and assurance of the data collected by community monitors. While this was likely a result of the lack of a direct question within the interview guide designed for this study, no information was contained in the documents analysed either. As the purpose of any monitoring program is to collect data for informed decision-making, a data management system is likely critical to the success of a program. Also, the theme of “effective” sample size was not revealed in the thematic content analysis. This may be an important theme that was missed in this analysis. VanGerwen-Toyne et al. (2014) found in a study on CBMP for Arctic and sub-Arctic subsistence fisheries, that statistical power resulting in increased confidence in monitoring results versus the cost of additional data collection and analyses was an important factor to be considered. Data management and effective sample size are themes that should be studied in future reviews to provide an understanding of best practices towards the execution of Arctic Char CBMPs.
Lastly, to address changes occurring in both the environment and northern communities, and in addition to the recommendation for an adaptive monitoring approach noted above, a Systems Thinking approach could be considered for subsistence Arctic Char
CBMPs. This was suggested by Paylor (1998) in her practicum on community-based fisheries management and monitoring development and evaluation based in Ulukhaktok
(Holman) Northwest Territories (ISR). To the best of my knowledge, such an approach has yet to be tried in Arctic Char community-based monitoring in the Canadian Arctic. A
! ! 245!
Systems Thinking approach is a process of understanding how all the components depend on one another and influence the system as a whole (Capra, 1998), similar to an ecosystem- based approach to monitoring (Ludwig et al., 1993). Additional program components would expand to include the monitoring of ecosystems features, social structures, beliefs, and, knowledge bases, along with each of these components various elements. Considering all of these components together could allow for the determination of whether the program is successful or requires improvements in any one area. This could ensure community and government decision-makers needs for reliable data are met. It could also be seen as an approach to ongoing program evaluation.
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4.6 Appendices
Appendix 1: Semi-directed interview guide.
Interview Guide for Community-Based Monitoring Programs of Arctic Char in Northern Canada
Research Conducted by: Jennie Knopp PhD Candidate, Watershed Ecosystem Graduate Studies Trent University, Peterborough ON [email protected]
Purpose of Research:
I am examining different examples of char monitoring plans across the Canadian Arctic both for a summary report for Fisheries and Oceans Canada (DFO) and the Fisheries Joint Management Committee (FJMC), as well as for a chapter in my PhD thesis. This research is part of the IPY project “Climate Variability and Change Effects on Chars in the Arctic”. The purpose of the research is to provide an overview of current methods and best practices for implementation of char community-based monitoring plans (CBMPs) in the region. Specifically, I am focusing on the creation of a char CBMP for Sachs Harbour, NT in the Inuvialuit Settlement Region (ISR).
Please use as much space as you require to fully respond to each question. If you have any questions at all regarding the items below, or the research, please do not hesitate to contact me by phone or e-mail. The knowledge that will be contained in my thesis, as well as the final report delivered to DFO and FJMC will be of great use to these organizations and the people of the ISR. You will be listed as a contributor on this report, if you agree. The interview should take approximately 45-60 minutes to complete.
Thank you very much for your time in completing this interview.
Questions for Key Informant:
1)! Please provide your name, organization and any char monitoring plans with which you are (or were) involved.
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2)! Where are (were) these monitoring plans located (closest community and names of waterbodies on which the monitoring is (was) conducted)?
3)! When did the char monitoring plan(s) commence? Are they still on-going today?
4)! Why was the monitoring plan(s) created (e.g. community request, commercial fishery located in the region which required monitoring, government mandate, etc.)? Please include all details and levels of involvement from all organizations involved in the creation of the plan.
5)! What information is (was) collected through the monitoring plan (e.g. samples, parameters including length, weight, etc., creel and/or household surveys, local knowledge about fishing techniques and/or locations, etc.)?
6)! What are (were) the methods and tools used to collect the data in the char CBMP (e.g. GIS, community monitors who submit data to DFO, online reporting, submission of fish samples for analysis, etc.)?
7)! In your opinion, how effective are (were) these methods and tools for collecting data through the monitoring plan?
8)! a)! Who is (was) involved in the monitoring of the char (e.g. community residents, local officials, government representatives, which government offices, etc.)?
b)! How much does it cost to run the program? Where does funding come from?
c)! Who conducts the monitoring and who oversees the monitoring process?
d)! Who conducts the data analysis?
e)! What are the results of the data analysis used for and by whom?
9)! What level of community involvement exists in the monitoring plan? If community involvement exists, please describe in detail. Include the number of paid monitors, amount of pay and work period, if the work is seasonal or year round, training of local residents in sampling techniques, data analysis, dissemination of data results to community, etc.
10)!Were there any community consultation or is there ongoing community consultation to obtain community input regarding sampling methods and parameters or desired outcomes for the char monitoring plan? If so, please describe this process and the outcomes of the community consultation in detail.
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11)!Please describe any monitoring methods which simply did not work or were not possible to be carried out at the community level and why these methods were not feasible?
12)!What are some of the specific methods or tools that you or the community implemented that you feel really helped to facilitate the success of the CBMP?
13)!Are there any specific suggestions you would give regarding communities who are just starting their Arctic Char CBMP?
14)!Is there anyone else you think we should talk to about Arctic Char community- based monitoring plans in the Canadian Arctic?
Thank you very much for your time and for contributing to this research. I will send you a copy of the final report once it is complete. (If a phone interview was completed: I will be sending you an electronic text copy of the interview so that you can review and confirm that the information recorded is correct and accurate.) If you have any questions at all regarding this research, please do not hesitate to contact me by phone or e-mail.
Sincerely, Jennie Knopp
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Appendix 2: Grey and peer-reviewed literature used for the thematic coding analysis
(n=28).
Bell, R.K., and Harwood, L.A. 2012. Harvest-based Monitoring in the Inuvialuit Settlement Region: Steps for Success. Arctic 65(4):421–432.
Carder, G.W., and Stewart, D.B. 1989. Data from the commercial fishery for Arctic charr, Salvelinus alpinus (L.), in central Keewatin regions of the Northwest Territories, 1987-88. Canadian Data Report Fisheries and Aquatic Sciences 766: vi + 47 p.
Chum, M. 2009. Development of the Nephijee System for Arctic Charr; Kuujjuaq, Nunavik. In Anderson, R.B. and Bone, R.M., eds. Natural Resources and Aboriginal Peoples in Canada Readings, Cases, and Commentary, Second Edition. Concord, Ontario: Captus Press Inc. 447–464.
Day, A.C., and B. de March. 2004. Status of Cambridge Bay Anadromous Arctic Char Stocks. DFO Can. Sci. Advis. Sec. Res. Doc. 2004/052, ii + 78 p.
Dempson, J.B., Scruton, D. A., and Shears, M. 1997. Aspects related to the characterization of fisheries resources and habitats in the Voisey's Bay region of northern Labrador, with emphasis on Arctic charr, Salvelinus alpinus. Science Branch, Department of Fisheries and Oceans, St. John's, Newfoundland. 47pp.
DFO. 1999. Hornaday River Arctic Charr: Stock Status Report D5-68(1999). Fisheries and Oceans Canada, Central and Arctic Region. 12 pp.
DFO. 2001a. Northern Labrador Arctic Charr: Stock Status Report D2-07(2001). Fisheries and Oceans Canada, Newfoundland Region. 8 pp.
DFO. 2001b. Rat River Dolly Varden: Stock Status Report D5-61(2001). Fisheries and Oceans Canada, Central and Arctic Region. 15 pp.
DFO. 2004. Cambridge Bay Arctic Char: Stock Status Report 2004/010. Fisheries and Oceans Canada, Central and Arctic Region. 17 pp.
DFO. 2013. Update Assessment of the Cambridge Bay Arctic Char Fishery, 1960- 2009: Science Advisory Report 2013/051. Fisheries and Oceans Canada, Central and Arctic Region. 15 pp.
DFO. 2014. Proceedings of the regional assessment for Dolly Varden (Salvelinus malma) in the Rat River, Northwest Territories; March 17-19, 2008. DFO Can. Sci. Advis. Sec. Proceed. Ser. 2014/024.
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DFO. 2016. Assessment of Arctic Char (Salvelinus alpinus) in the Darnley Bay area of the Northwest Territories. DFO Can. Sci. Advis. Sec. Sci. Advis. Rep. 2015/024.
Dumas, R. 1990. Arctic Charr stream enhancement in Nunavik: Summary of activities in 1989. Preliminary report presented to: Kativik Regional Government (Hunter Support Program), Economic Regional Development Agreement Committee, Makivik Corporation (Economic Development Department) and Seaku Corporation. Makivik Corporation, Renewable Resource Development, Kuujjuaq, Quebec. 88 pp.
Fisheries and Oceans Canada. 2014. Integrated Fisheries Management Plan: Cambridge Bay Arctic Char Commercial Fishery, Nunavut Settlement Region, Effective 2014. Fisheries and Oceans Canada Central and Arctic Region, Resource Management and Aboriginal Affairs. i-v + 44 pp.
Harwood, L.A. 1999. Status of anadromous Arctic charr (Salvelinus alpinus) of the Hornaday River, Northwest Territories, as assessed through harvest-based sampling of the subsistence fishery, August-September 1990-1998. Canadian Stock Assessment Secretariat Research Document 99/182. 32 p.
Harwood, L.A. 2001. Status of anadromous Dolly Varden (Salvelinus malma) of the Rat River, Northwest Territories, as assessed through community-based sampling of the subsistence fishery, August-September 1989-2000. Canadian Science Advisory Secretariat, Research Document 2001/090. 31 pp.
Harwood, L.A. 2009. Status of anadromous Arctic charr (Salvelinus alpinus) of the Hornaday River, Northwest Territories, as assessed through harvest-based sampling of the subsistence fishery, August-September 1990-2007. Can. Manuscr. Rep. Fish. Aquat. Sci. 2890: viii + 33 p.
Harwood, L., Sandstrom, S.J., Papst, M.H., and Melling, H. 2013. Kuujjua River Arctic Char: Monitoring stock trends using catches from under-ice subsistence fishery, Victoria Island, Northwest Territories, Canada, 1991-2009. Arctic 66(3):291-300.
Kristofferson, A. and Berkes, F. 2005. Adaptive co-management of Arctic Char in Nunavut Territory. In: Berkes, F., Huebert, R., Fast, H., Manseau, M. and Diduck A., eds. Breaking Ice: Renewable Resource and Ocean Management in the Canadian North. Calgary: University of Calgary Press. 249–268.
Kristofferson, A.H., and Carder, G.W. 1980. Data from the commercial fishery for Arctic char, Salvelinus alpinus (Linnaeus) in the Cambridge Bay area, Northwest Territories, 1971-78. Canadian Data Report Fisheries and Aquatic Sciences 184: v + 25p.
Lewis, P.N.B., Kristofferson, A.H., and Dowler, D.H. 1989. Data from fisheries for Arctic charr, Kuujjua River and Holman Areas, Victoria Island, Northwest
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Territories, 1966-87. Canadian Data Report Fisheries and Aquatic Sciences 769: iv + 17p.
Mesher, C. 1995. “Fish Habitat Action Plan” Arctic Char Habitat Restoration in Nunavik. (1994-1995): Kangiqsujuaq and Quaqtaq. Submitted to Department of Fisheries and Oceans Fisheries and Habitat Management Branch Northern Quebec Area and Native Affairs and The Kativik Regional Government. Renewable Resource Development Department, Makivik Corporation. 22 pp.
Mesher, C. 1999. Char Habitat Improvement Projects Report 1998. Prepared for the Hunting Fishing and Trapping Associations of Nunavik and the Kativik Regional Government. Renewable Resource Development Department, Makivik Corporation. 30 pp.
Olokhaktomiut Char Working Group. 2004. Holman Char Fishing Plan 2001-2004. Olokhaktomiut Hunters and Trappers Committee, Department of Fisheries and Oceans Canada and the Fisheries Joint Management Committee. 11 pp.
Paulatuk Charr Working Group. 2002. Paulatuk Charr Management Plan, 1998- 2002. Paulatuk Hunters and Trappers Committee (HTC) and the Fisheries Joint Management Committee (FJMC). 13 pp.
Paylor, A.D. 1998. Community-based fisheries management and monitoring development and evaluation. MNRM Thesis, University of Manitoba, Winnipeg, Manitoba. 215 pp.
Paylor, A.D., Papst, M.H., and Harwood, L.A. 1998. Community household survey on the Holman subsistence Arctic charr (Salvelinus alpinus) fishery priorities, needs and traditions. Can. Tech. Rep. Fish. Aquat. Sci. 2234: iv + 16 p.
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Appendix 3-1: Summary of information from the thematic content analysis on Arctic Char and related species CBMPs in the
Canadian Arctic for the subthemes from the theme Program Operations focusing on the type of fishery, purpose and length of program, program partners, cost and funding sources.1
Location Community Type of Purpose of CBMP Length of Program Cost Primary and Land Fishery Program Partners Funding Claim Sources Region 1) Rat River Aklavik, Subsistence Informed 1995-present DFO, FJMC, Undisclosed DFO (ISR (Dolly Varden Inuvialuit management HTCs, Implementation Char) Settlement decisions, monitor University Funds), FJMC Region and stock trends over time Researchers Fort to address community McPherson, concerns about Gwich’in downturns, fully Settlement engage communities Region and harvesters in management, monitoring and recovery 2) Hornaday Paulatuk, Subsistence, Informed 1989-present DFO, FJMC, $20K DFO (ISR River Inuvialuit (Small-scale management HTCs, annually for Implementation Settlement Commercial decisions, monitor University in-community Funds), FJMC Region and Sport- stock trends over time Researchers costs fishing outfits to address community including in past) concerns about monitors, downturns, fully equipment engage communities and fuel, etc. and harvesters in in 2010 management, monitoring and recovery
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3) Kuujjuaq Ulukhaktok, Subsistence, Informed 1991-present DFO, FJMC, Undisclosed DFO (ISR River and Fish Inuvialuit Small-Scale management HTCs, Implementation Lake, Settlement Commercial decisions, monitor University Funds), FJMC surrounding Region stock trends over time Researchers coastal areas to address community concerns about downturns, fully engage communities and harvesters in management, monitoring and recovery 4) Cambridge Cambridge Subsistence, Management of 1971-Present DFO, Kitikmeot Undisclosed, DFO (Nunavut Bay, Bay, Large-scale commercial fishery (river weir Foods (Fish monitors paid Implementation Wellington Nunavut Commercial, (dates back over 50 assessments Plant), HTA, $200/day in Funds), Bay and Settlement (Sport-fishing years) in conjunction usually only 1-2 Nunavut 2010 University- Ekalluk River, Area outfitters in with subsistence and years in length) Wildlife secured funding nearby coastal past) recreational fishery, Management areas and determine harvest Board, rivers levels, population University parameters, Researchers modelling, recommend sustainable harvest levels 5) Nephijee Kuujjuaq, Subsistence, Nephijee River: Fish Nephijee River: Makivik $90K annually Makivik River and Nunavik Sport-fishing passage monitoring 2000-Present Corporation, for Nephijee Corporation, Koksoak Inuit outfitters and enhancement, Koksoak River: HFTA, Nunavik River CBMP University- River (Arctic Settlement requested by 1977-2001 Research in 2016 secured funding, Char and Area community Land Centre, (includes ArcticNet Atlantic Holding Corporation Community project Salmon) Koksoak River: Fish Land Holding manager and passage monitoring, Corporations, local monitor requested by Industry University pay, (Hydro Quebec) Researchers, equipment, Hydro Quebec travel, etc.)
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6) Northern Nain, Subsistence* Management of 1977-Present DFO, $28K annual DFO, Nain Inuit Labrador Nunatsiavut Large-Scale commercial fishery (sporadic river Nunatsiavut operating Community coastal area Commercial (over 100 years), assessments) Government, budget in 2010 Government, and rivers (Little known trends in commercial Nain Inuit (includes Nunatsiavut (Primary about catch, determine Community office costs Government, Arctic Char potential harvest levels, Government, and International stock recreational/ population Nain Research government Polar Year complexes: sport fishery) parameters, Centre scientist Voisey, Nain recommend Kaujisapvinga, travel) and Okak) sustainable harvest Nain Fish Plant, levels University Researchers 1Acronyms for Appendices 3-1 to 3-3: CBMP – Community-Based Monitoring Program; CPUE – Catch Per Unit Effort; DFO – Department of Fisheries and Oceans Canada; EA – Environmental Assessment; FJMC – Inuvialuit-Canada Fisheries Joint Management Committee; HTA – Hunters and Trappers Association (Nunavut) ; HTC – Hunters and Trappers Committee (ISR); HFTA – Hunters, Fishers and Trappers Association (Nunavik); IPY – International Polar Year 2007-2008; ISR – Inuvialuit Settlement Region; IK – Inuit Knowledge. * Have not obtained data from subsistence fishery through CBMP. ! !
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Appendix 3-2: Summary of information from the thematic content analysis on Arctic Char and related species CBMPs in the
Canadian Arctic for the subthemes from the theme Program Operations focusing on the methods, tools and parameters used, frequency and timing of monitoring, hiring of community members, local training and community reporting and communication.
Location Community Methods, Tools Frequency Equipment Used Community Training Reporting and and Land and Parameters and Timing Hiring Provided Outreach Claim Region Used Program Leader 1) Rat River Aklavik, Length, weight, Annually, Helicopters, Community Yes (DFO, In-community Inuvialuit sex, maturity, age late August ATVs, members hired sometimes meetings and Settlement (from otoliths), to mid- snowmobiles, on a seasonal FJMC and presentations in Region and Fort population September boats, gill nets, basis annually researchers) plain language, McPherson, numbers, harvest weirs, counting to collect Char Working Gwich’in levels, catch rates, fences, water samples and Group, Fishing Settlement catch location gauges, tags, field data Plan and FJMC Region data sheets, meetings, Harvest-based fisher’s journals, school monitoring, mesh freezers presentations, sizes used, newsletters, CPUE, tag reports, co- returns, unusual authored peer- observations, reviewed weather, water publications levels, water temperature 2) Hornaday Paulatuk, Length, weight, Annually, Helicopters, Community Yes (DFO, In-community River Inuvialuit sex, maturity, age late July and ATVs, members hired sometimes meetings and Settlement (from otoliths), all of August snowmobiles, on a seasonal FJMC and presentations in Region population (during char boats, gill nets, basis annually researchers) plain language, numbers, harvest migration to weirs, counting to collect Char Working levels, catch rates, overwinter fences, water samples and Group, Fishing catch location habitat) gauges, tags, field data Plan and FJMC
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data sheets, meetings, Harvest-based fisher’s journals, school monitoring, mesh freezers presentations, sizes used, newsletters, CPUE, tag reports, co- returns, unusual authored peer- observations, reviewed weather, water publications levels, water temperature 3) Kuujjuaq Ulukhaktok, Length, weight, Annually, Helicopters, Community Yes (DFO, In-community River and Fish Inuvialuit sex, maturity, age July and ATVs, members hired sometimes meetings and Lake, Settlement (from otoliths), August snowmobiles, on a seasonal FJMC and presentations in surrounding Region population (coastal boats, gill nets, basis annually researchers) plain language, coastal areas numbers, harvest fishery) and weirs, counting to collect Char Working levels, catch rates, mid-October fences, water samples and Group, Fishing catch location to early gauges, tags, field data Plan and FJMC November data sheets, meetings, Harvest-based (under ice fisher’s journals, school monitoring, mesh fishery), freezers presentations, sizes used, each year newsletters, CPUE, tag (summer and reports, co- returns, unusual winter) authored peer- observations, reviewed weather, water publications levels, water temperature 4) Wellington Cambridge Bay, Length, weight, Annually, Boats, gill nets, Community Yes (DFO) In-community and Cambridge Nunavut sex, maturity, age during weirs, counting members hired meetings and Bays, Ekalluk Settlement Area (from otoliths), downstream fences, freezers on a seasonal presentations River, nearby population and basis annually including HTA bays and rivers numbers, harvest upstream to collect and fish plant levels, catch rates, runs (2 samples and meetings, catch location weeks in data reports, peer- July, Aug 1- reviewed Sept 10) publications.
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Stock delineation, stock size, stock trends, variability in recruitment 5) Nephijee and Kuujjuaq, Length, weight, Annually or Helicopters, Summer Yes Disseminate Koksoak Rivers Nunavik Inuit sex, maturity, age as required, counting fences, students, (Nunavik results to Settlement Area (from otoliths), August- field data sheets, Fisherman Research Community catch location September fisher journals, paid per fish Centre, and Land Holding (during char GPS head (some sometimes Corporations, Fish passage, migration to communities), researchers) who use the migration timing, overwinter Technicians radio and mercury levels, habitat) hired at meetings to CPUE, food Research share results webs, growth, Centre with sporadic Lake community, Trout sampling results shared with schools, reports, grey literature 6) Northern Nain, Length, weight, Annually, Boats, gill nets, 1-4 Yes (DFO) In-community Labrador Nunatsiavut sex, maturity, age mid-June to weirs, counting community meetings and coastal area and (from otoliths), early fences, field data members hired presentations, rivers (Primary population September sheets, fisher’s on a seasonal annual fisher’s stocks numbers, harvest journals, GPS, basis annually meetings and complexes: levels, catch rates, freezers to collect Nain Fisheries Voisey, Nain catch location samples and conference, and Okak) data (summer) radio Latitudinal interviews, variation, oxygen reports, peer- isotope analyses, reviewed migration timing, publications, genetics, stock paper outputs structure, stock sent to schools. size, parasites, growth
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Appendix 3-3: Summary of information from the thematic content analysis on Arctic Char and related species CBMPs in the
Canadian Arctic for the subthemes from the theme Program Operations focusing on which organization initiated and ran the program, community involvement in program design, who conducts analyses of samples and data, and who uses the results.
The last column on the right provides the community-based monitoring category (from Table 1) assigned to each program.
Location Community Community, Community, Community Inuit Who Who Model of and Land Government Government Involvement Knowledge Conducts Uses the CBMP* Claim or Industry or Industry in Design Included Analyses Results Region Initiated Executed (Samples and Data) 1) Rat River Aklavik, Community Community Identify Included: IK DFO DFO, FJMC, 3) Inuvialuit and and Federal location and used to HTC Collaborative Settlement Government Government need for determine monitoring Region and (DFO) monitoring changes to with external Fort and concerns data McPherson, about interpretation Gwich’in fishery, Settlement subsistence Region harvest levels, fish condition 2) Hornaday Paulatuk, Community Community Identify Included: IK DFO DFO, FJMC, 3) River Inuvialuit and and Federal location and used to HTC Collaborative Settlement Government Government need for determine monitoring Region (DFO) monitoring changes to with external and concerns data about interpretation fishery, subsistence harvest
! ! 270!
levels, fish condition 3) Kuujjuaq Ulukhaktok, Community Community Identify Included: IK DFO DFO, FJMC, 3) River and Fish Inuvialuit and and Federal location and used to HTC Collaborative Lake, Settlement Government Government need for determine monitoring surrounding Region (DFO) monitoring changes to with external coastal areas and concerns data about interpretation fishery, subsistence harvest levels, fish condition 4) Wellington Cambridge Community Community Input from Included: IK DFO DFO, HTA, 3) and Bay, and and Federal commercial used to Kitikmeot Collaborative Cambridge Nunavut Government Government fishers and the determine Foods Fish monitoring Bays, Ekalluk Settlement (DFO) Inuit-owned spawning Plant with external River, nearby Area Fish Plant grounds and data bays and rivers subsistence interpretation harvest levels 5) Nephijee Kuujjuaq, Community Local Identify Included: IK Nunavik Community 4) and Koksoak Nunavik and Industry Government location and determines Research Land Collaborative Rivers Inuit and Industry need for locations Centre Holdings monitoring Settlement monitoring where fish Corporations with Area passage has community- been altered requested or prohibits advice from migration external agencies and local data interpretation 6) Northern Nain, Government Government Input from Incidental DFO DFO, 3) Labrador Nunatsiavut (DFO) commercial inclusion: Voisey’s Bay Collaborative coastal area fishers and the Voluntary Mine-Mill monitoring and rivers subsistence Complex EA with external
! ! 271!
(Primary Inuit-owned harvest data stocks Fish Plant reporting, interpretation complexes: creel surveys Voisey, Nain conducted in and Okak) past * Model type designation based on information provided in the key informant interviews.
! ! 272!
CHAPTER 5:
Integrated Discussion
5.1 Summary and Contributions
This dissertation made both ecological and methodological contributions towards the understanding of community-based monitoring (CBM) of Arctic Char. Arctic Char subsistence and commercial fisheries are important to northern communities. The impending effects of a changing environment on this resource necessitates long-term, systematic, and reliable information in order to detect changes in, and make management decisions about, the resource over time. Therefore, my dissertation focused on the central question of: Which community-based monitoring factors and parameters would provide the information needed by local resources users and decision-makers to make informed choices for managing Arctic Char populations in light of climate change and variability (CVC)? The purpose of this research was to build on methods and processes used for monitoring fish in Canada’s north, to address existing limitations in the understanding of landlocked Arctic Char ecology and ecological drivers that affect growth and condition, as well as determine which factors should be considered for Arctic Char community-based monitoring programs (CBMP). A mixed methods research design was used where I collected and analyzed data, integrated the findings, and drew inferences using both qualitative and quantitative methods (as per Creswell 2008, p.526). Three manuscripts investigated different aspects of the central question.
This dissertation contributes novel research towards the existing literature in several ways. First, literature reviews were conducted in order to obtain documented Inuit or
! ! 273!
Inuvialuit knowledge and observation (IKO) on Arctic Char from across the Canadian north, including the study area, using online databases of both the grey literature and peer- reviewed papers. Additional searches for documented IKO contained in paper documents in Inuvialuit Settlement Region (ISR) libraries were also conducted. Despite these extensive searches, no documents containing rich information on Arctic Char biology or life histories from IKO were found. The few documents found that contained IKO on
Arctic Char (or the closely-related Dolly Varden Char) focused specifically on fishing practices and locations, observations of harvest such as abundance and size, or timing of migration and known spawning areas near fishing sites (e.g. Morrison 2000, Riedlinger
2001, Papik et al. 2003, Kugluktuk HTO and Sabina Gold and Silver Corp. 2015, Janjua et al. 2016). As such, my research contributes to the literature by sharing the breadth and depth of Inuvialuit Knowledge and Observation (IKO) on Arctic Char biology and ecology.
Second, my research contributes to the literature by improving the understanding of factors and parameters required to conduct lasting Arctic Char CBMP. While there are several long-term Arctic Char CBMPs in the Canadian Arctic, they are focused on mixed commercial-subsistence fisheries for anadromous Arctic Char populations only. Despite the growing interest in CBM by northern communities, government and researchers, program factors and approaches remain poorly documented (Johnson et al. 2015, Johnson et al. 2016, Kouril et al. 2016). In a review of the state of environmental monitoring in
Canada through a collection monitoring metadata complied by the Canadian Polar
Commission (accessed online, January 12 2017, https://www.canada.ca/en/polar- knowledge/publications/cpc-stateofenv.html), they found “numerous programs exist for which the full suite of metadata has not yet been acquired…for example, locally based,
! ! 274! small-scale monitoring initiatives were more challenging to incorporate into this collection exercise…however, initiatives are underway to better capture community-based monitoring and traditional knowledge in the Canadian Arctic”. !!Two previous studies reviewed trends and key elements of Arctic CBMPs and suggested practices (i.e. Johnson et al. 2016, Kouril et al. 2016). However, to the best of my knowledge, no study to date has compared and contrasted the various aspects of Arctic Char CBM programs in the
Canadian Arctic, to identify the factors and parameters of these programs that led to the sustained collection of useful data for management purposes. My research also provides further insights into factors that influence the success of Arctic CBM. !
Last, Arctic freshwater fisheries and ecosystems (Culp et al., 2012, Cooke and
Murchie 2013) are poorly understood due to a lack of data and therefore a limited understanding of Arctic freshwater mechanisms and tolerances to CVC perturbations (Reist et al. 2006, Niemi et al. 2016). This dissertation contributes novel research and understanding on Arctic freshwater fish biology and habitat interactions in the north, by using both scientific knowledge and observation (SEKO) and IKO to better understand landlocked Arctic Char biology and ecology. While the incorporation of fishers’ expert knowledge into resource management is not a new concept, most examples of this type of research and management application are focused around “southern” or equatorial regions
(e.g. UNESCO 2007, FAO 2015).
Few studies incorporate both SEKO and IKO to study fish in Canada’s north (e.g.
Neiss et al. 1999, Morris et al. 2002, Howland et al. 2004, Fraser et al. 2006, Fraser et al.
2013, Brewster et al. 2016) and even fewer focus on Arctic Char (e.g. Pellerin and Grondin
1998, Kristofferson and Berkes 2005, Bell and Harwood 2012). However, most of these
! ! 275! studies focus on a single topic such as fish movement, body condition, or population size.
Also, to the best of my knowledge, there is only one other known study using back- calculation of landlocked Arctic Char otoliths to examine relationships between a suite of environmental conditions and Arctic Char growth (in two landlocked lakes in Greenland, i.e. Kristensen et al. 2006) and those study results differed from those herein. Therefore, the mixed methods approach used in my study results in a more holistic understanding of landlocked Arctic Char ecology and contributes information towards a lack of basic knowledge regarding fish biology and habitat interactions in the north.
In the first manuscript, I investigated which habitat and biological parameters showed consistent relationships with landlocked char quantitative condition (numerically calculated using Fulton’s K) and qualitative condition (as determined by local experts through fatness, texture, taste and absence of disease or deformities) to determine the value of these parameters for use in Arctic Char CBMPs. This manuscript used a mixed methods exploratory design to integrate SEKO and IKO. Social science methods were used to obtain information relating to char biology and lake ecology and included: ethnographic field work, prolonged engagement, participant observation community-collaborative research, semi-directed interviews with local experts, thematic content analysis, and member checks.
Concurrently, multiple scientific methods were used to obtain data, information, and knowledge relating to char biology and lake ecology and included: char condition and diet sampling, zooplankton collection and analyses and lake habitat parameter assessments.
This manuscript demonstrated that available SEKO and IKO knowledge bases corroborated or enriched one another for all parameters studied. Evidence for multiple ecological mechanisms were found to be important in the condition of landlocked Arctic Char
! ! 276! including allochthonous inputs, lake temperature regimes, lower trophic level diversity and productivity, and parasite loads. These parameters showed promise as potential CBM parameters, as did the qualitative parameter of char taste.
In the second manuscript, I investigated which local environmental parameters showed a consistent relationship with landlocked char growth, such that they could be considered for use in Arctic Char CBM. In this manuscript, I also used a mixed methods exploratory design in order to integrate SEKO and IKO. The same social science methods were used to obtain information relating to char biology and lake ecology. Concurrently, multiple scientific methods were used to obtain data, information, and knowledge relating to char biology and local environmental conditions and included: sampling char for size at time of capture, otolith back-calculation to determine historical char size, and obtaining and analyzing historical and contemporary air temperature, precipitation and lake ice-on and ice-off dates. This manuscript also demonstrated that available SEKO and IKO knowledge bases corroborated or enriched one another for all parameters studied. Parallel similarities in a given year of char growth across a range of age classes across all study lakes indicated a regional rather than a lake-specific phenomenon. Growing Degree Days, and the significantly linked parameters of lake ice on and off dates, as well as the extent of local annual sea ice coverage, were determined to be important environmental parameters to consider in Arctic Char CBM.
The third and final manuscript was focused on comparing and contrasting a variety of aspects of community-based monitoring programs (CBMPs) for char populations across the Canadian Arctic, to identify factors and components that have led to the sustained collection of useful data, information and knowledge for management purposes. While no
! ! 277! information on CBMPs for freshwater-restricted Arctic Char were found, the information obtained from a review of anadromous char CBMPs was still relevant to landlocked fisheries used by the community of Sachs Harbour. As Arctic Char spawn and overwinter in freshwater habitats, and many of the monitoring parameters and factors remain the same including: size, age, condition, catch-per-unit-effort, harvest levels, stock assessment, environmental parameters (e.g. water quality), and the social aspects of char harvesting. In addition, both anadromous and freshwater-restricted Arctic Char CBMPs would require support from federal government and land claim organizations. Two major differences between char anadromous and freshwater-restricted monitoring are 1) anadromous populations often require genetic work to determine stock delineation, and 2) anadromous char are usually harvested at a single location during the fall migration when returning from the marine environment to overwinter in freshwater. While genetic analyses would likely not be required in landlocked populations, the lack of a common harvest or sampling location can pose an increased issue for freshwater-restricted Arctic Char CBMPs. This could result in increased effort and time required by community monitors to both sample subsistence harvests, and to collect scientific samples. Local monitors will have to travel to all local fishing locations on various lakes, and conduct scientific sampling in various locations on each fished lake in order to ensure random stratification of samples. However, one of the advantages of monitoring landlocked Arctic Char is that population size and harvest estimates are likely easier to obtain due to the contained nature of lake fisheries and a smaller number of harvesters.
In this third manuscript, I used qualitative exploratory methodologies including a literature review of 35 peer-reviewed papers and grey literature documents, semi-directed
! ! 278! interviews with nine key informants, and thematic content analysis examining six char
CBMPs in all four Inuit land claim regions in Canada. The six programs existed to monitor either commercial, subsistence or mixed commercial-subsistence char fisheries. Despite differences among the six char CBMPs, this manuscript demonstrated common methods and approaches across the north including: programs leaders were either federal government or regional land claim organization representative who trained local monitors; community monitors were hired on a seasonal contract basis to collect samples and data; monitoring occurred annually in the late summer and/or early fall; program leaders were also responsible for data analyses as well as dissemination of results; Inuit knowledge and observation was considered in all six programs although no formal processes existed for the inclusion of this knowledge. This manuscript also demonstrated that adaptive monitoring was particularly relevant for subsistence Arctic Char fisheries as community perspectives and changing lifestyles, as well as environmental changes impacting a fishery, can have direct effects on the successful operation of char CBMPs.
5.2 Mixed Methods Approach to Research
Mixed methods is a recent approach to research attracting interest over the past 30 years within social, health, and anthropological research (Driscoll et al. 2007, Creswell
2008). Researchers have warned that a mixed methods approach to research can be a daunting undertaking due to the shear amount of time and cost required to obtain, analyze and integrate several sources of information (Driscoll et al. 2007, Wolf 2010). However, recognizing the lack of tools and methodologies for appropriately integrating IKO and
SEKO, the mixed methods approach was adapted for use in this ecological study.
! ! 279!
The use of a mixed methods design in Chapters 2 and 3, integrating both scientific and social science methods to collect quantitative and qualitative information respectively, as well as using multiple methods within each of the two overarching methods, led to an increased understanding of what lake habitat and environmental parameters may be affecting Arctic Char growth and condition. The analysis of IKO revealed the importance of an increasing active layer, decreasing allochthonous input, shore erosion and permafrost melt, lake ice and snow cover on lake ice, local sea ice conditions, and taste in monitoring landlocked char on Banks Island. The analysis of SEKO revealed the importance of differences in char quantitative condition among lakes, parasite loads, zooplankton as a prey item, and difference in diet among lakes in monitoring landlocked char on Banks
Island. Each of these knowledge bases provided understanding towards ecological and environmental effects on char condition and growth that would not have been revealed had only one methodology or knowledge base been used.
Parameters where the knowledge bases corroborated provided confidence in the results. For example, the knowledge bases corroborated in that the interpretation of the resulting patterns supported both lake-specific and regional climate-driven changes of increased char growth in all three study lakes. Regional climate-driven changes found to affect Arctic Char growth was GDD0, and the closely linked parameters of warmer weather, lake ice on and off dates, as well as the extent of annual sea ice coverage. Therefore, confidence was gained in suggesting the use of these parameters as potential indicators for monitoring landlocked Arctic Char on Banks Island.
Beyond the use of a mixed methods approach, the social science methodologies employed in this study were crucial to the research process. Ethnographic field work,
! ! 280! prolonged engagement, participant observation, community-collaborative research, member checks and learning through an Inuvialuit pedagogy provided both rigour to the information collected and to the process of analysis and integration of the knowledge bases.
Having an understanding of the Sachs Harbour local expert fisher’s worldview regarding
Arctic Char and the environment was required to conduct effective semi-directed interviews, but also to conduct the thematic coding of the qualitative information.
Understanding their worldview was also crucial throughout the iterative stages of data and information collection, due to a need understand how to address questions that arose from previous analyses.
Last, the qualitative methodology used in Chapter 4 allowed for not only an analysis of common monitoring parameters and program operations, but also the human component of Arctic Char CBMPs. My dissertation provides new perspectives on the local char resource user, monitoring program leaders, local monitors and land claim and government organizations roles and actions, and how they affect the successful implementation of char
CBM. Adding this information to the research allowed for a holistic understanding of all components required for successful char CBMPs, beyond simply studying potential indicators for use in monitoring.
5.3 Ecological Complexity
My research took an ecosystem-based approach to the study, realizing that interacting effects of trophic and environmental conditions complicate the management of fisheries, and that this approach has led to considerations of more holistic approaches to fisheries management (Holling 1978, Harvey and Coon 1997, Hall and Maniprize 2004,
Harvey and Walsworth and Schindler 2016). There has been a rise in ecosystem-based
! ! 281! fisheries management in recent decades, which uses indicators to monitor fisheries (Link et al. 2012, Moffit et al. 2016). Indicators must be able to robustly detect the changes being monitored, and must be evaluated for their performance in assessing ecosystem state and effects on the fishery (Fulton et al. 2005). However, there is not one single approach to indicators used across fisheries, and therefore indicators need to be developed on a case- by-case basis (Jennings 2005, de Kerckhove 2015).
My dissertation has provided a more comprehensive understanding of the trophic and environmental effects on Arctic Char condition and growth in landlocked lakes on
Banks Island. It has shown the differences in ecological complexity that exists within the three study lakes that are exposed to similar local environmental conditions due to their proximity. In addition, the identification of locally-specific parameters for monitoring landlocked Arctic Char have been suggested for use by the local renewable resource management organization (Sachs Harbour Hunters and Trappers Committee) and the co- management organization (Inuvialuit-Canada Fisheries Joint Management Committee) in a local CBMP program. Justified selection of these suggested monitoring parameters – which will need to be tested as to their effectiveness as indicators – comes from the confidence gained due to the agreement between the IKO and SEKO as indicators of char condition and growth.
The extensive temporal scale at which IKO has been developed has also proved to add comprehension towards ecosystem linkages and effects on char that were simply not be available through shorter-term scientific studies. An ecosystem-based approach to
Arctic Char CBMPs that incorporate SEKO and IKO will provide greater comprehension of the inherent linkages between ecosystem conditions, changes, and causes-and-effects
! ! 282! that will lead to better management decisions as a result.
5.4 Monitoring Implications
As seen in the results in Chapter 4, current subsistence Arctic Char CBMPs do not adequately capture the effects of the adaptive nature of resource users. Humans are a part of the ecosystem, and need to be considered as part of a monitoring program, beyond simply monitoring exploitation levels. As Ludwig et al. (1993, p. 548) stated as one of the principles of effective management, “include human motivation and responses as part of the system to be [monitored] and managed.” A Systems Thinking approach (Capra 1998) was originally recommended for use in Arctic Char CBMPs in the Inuvialuit Settlement
Region by Paylor (1989). This approach includes the collection of information on social structures, beliefs, and, knowledge bases, in addition to the monitoring of ecosystems features. These additional metrics would allow for information on fisher demographics and socio-ecological measures to be included in CBMPs, contributing further to the holistic ecosystem-based approach to fisheries monitoring and management (Sethi et al. 2014).
An adaptive community-based monitoring program, that incorporates ecosystem- based and systems thinking approaches, and allows for the monitoring framework to evolve iteratively as new information emerges and questions or interests change, is an important approach for consideration in subsistence char CBMPs. Adaptive monitoring is defined by
Lindenmayer et al. (2011, p. 641) as:
“A monitoring program in which the development of conceptual models, question
setting, experimental design, data collection, data analysis, and data interpretation
are linked as iterative steps…that can evolve in response to new questions, new
information, situations or conditions, or the development of new protocols but…not
! ! 283!
distort or breach the integrity of the data record.”
This approach to CBM may be the key to collecting the information required to make effective management decision regarding the Arctic Char resource on Banks Island.
The collection of additional IKO and SEKO for ecological indicators of Arctic Char condition and growth through an adaptive CBM approach may be resource-prohibitive (due to increased time for training and information collection and analysis). However, as the
FJMC works within an adaptive co-management structure, this approach to monitoring may well fit this management model. Lindenmayer et al. (2011, p. 642) explain that:
“Adaptive monitoring is a crucially important component of adaptive management
because the testing of different plausible management options lies at the core of
adaptive management. When that testing identifies a superior option, which is then
subsequently embraced but which must be compared against yet other new
management options as part of the adaptive management cycle, then such changes
in experimental contrasts can demand changes in monitoring, namely adaptive
monitoring.”
Furthermore, adaptive monitoring will likely be required due to the unforeseen future impacts of climate change and variability, and the adaptation responses of local fishers to these changes.
5.5 Recommendations and Considerations for Future Research
Beyond what is recommended in each chapter, there are several recommendations and considerations for future research. One important consideration is the effect of alteration of the qualitative data that occurs when trying to present it in a paper slated for a scientific peer-reviewed journal. “Qualitative [thematic] codes are multidimensional,
! ! 284! meaning they can and do provide insights into a host of interrelated conceptual themes or issues during analysis” (Driscoll et al. 2007). There is an inherent loss of complexity, profundity of thought, and flexibility that occurs when qualitative data are quantified into simple measures of frequency of observations or number of local experts reporting on a particular topic. Ways to further incorporate the depth and richness of the IKO in mixed methods publications need to be explored further.
Another consideration is that mixed methods research including the integration and triangulation of knowledge bases is a demanding research strategy (Wolf 2010). Collecting separate quantitative and qualitative datasets, and the associated verification, analysis, validation, and integration takes much longer than focusing on a single methodology or dataset. Moreover, while mixed methods and triangulation is promising in many research contexts, it should not be used simply because it is trendy (Wolf 2010). For example, if a researcher were to study parasites in fish on Banks Island, a mixed methods approach is likely not the best option due to the limited knowledge local experts hold on the topic.
While literature reviews assist somewhat towards addressing this concern, most Inuit knowledge and observation is not documented due to the history of oral knowledge transmission. Therefore, a recommendation is to discuss existing levels of knowledge with community organizations before planning a mixed methods research design, to ascertain the level of knowledge held by local experts related to the researcher’s particular topics of interest.
Another recommendation for the approach to the research is to explicitly explain to local experts how qualitative research methodologies work. This would allow the interviewees to understand the approaches used to ensure the rigour of the information and
! ! 285! knowledge collected. Having the interviewees understand this before starting semi- directed interviews could result in more direct knowledge and observation shared by interviewees, potentially avoiding the sharing of indirectly acquired information such as information learned from fellow harvesters, family members, other researchers in the community or even radio or television programs. It would also be beneficial for communities involved in community-collaborative research to have an understanding at the outset of the project as to the length of time it takes to complete the laboratory and statistical analyses that occur outside of the community – especially when it is a graduate research project without a team of researchers tackling the analysis of samples and data. The time it takes to complete the sample and data analyses is further compounded when navigating ways to integrate the two knowledge bases. This would avoid unrealistic expectations of the time required for results to be available.
Further research could include examining ways in which qualitative data collection can be robustly incorporated into char CBMPs. Chapter 2 makes the recommendation to monitor the taste of char using qualitative scales outlined in the FAO report Quality and
Quality Changes in Fresh Fish (1995). However, additional qualitative parameters for consideration were also revealed from the analysis of IKO. Qualitative observations such as the colour of char meat, qualitative char condition (assessed by Inuvialuit using sight, touch, and taste) and general conditions of local sea and lake ice conditions should also be considered as parameters for monitoring. Ways to standardize the documentation of these qualitative observations in order to allow for the comparison across local experts and years of observations should be developed.
! ! 286!
5.6 Conclusions
It was the hope of the local experts that their knowledge would be used towards monitoring, and management, of the local Arctic Char resources. Specifically, local experts hoped that local, regional and federal decision-makers, as well as future generations of Bankslamiut (the people of Banks Island) would learn from their knowledge. It was also the hope of the community, as well as my own, that this research would develop a way to integrate IKO and SEKO on ecological drivers of landlocked Arctic Char condition and growth. This research has successfully demonstrated the use of a mixed methods approach.
Through the use of mixed methods, an ecosystem-based approach to research, and the detailed exploration of local ecosystem parameters and their effects on char condition and growth using both SEKO and IKO, this dissertation has made significant contributions to the literature on monitoring Arctic freshwater fishes. It is my hope that this research and writing will promote the continuation of examining ways in which SEKO and IKO knowledge bases can be integrated for a greater understanding of Arctic freshwater ecosystems.
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