| Summary: | Migration is an adaptive mechanism for species to meet life cycle needs in heterogeneous habitats such as the Arctic. The Arctic Charr (Salvelinus alpinus) is a northerly-distributed, partially anadromous fish that is culturally and economically important in Nunavut, Canada. Previous studies have investigated charr migratory choices in specific areas of Nunavut, but our understanding is limited of how these vary across the territory’s freshwater ecosystems. Understanding environmental influences on charr migratory choices can give insight on population reactions to climate change. To assess the drivers behind and differences in Arctic Charr migratory ecotype distribution across Nunavut, I compiled and cleaned three pre-existing sources—the Arctic Fisheries Stock Assessment database (scientific research), the Nunavut Coastal Resource Inventory (mapped Inuit knowledge) and the Nunavut Wildlife Harvest Study (Inuit fishermen harvest records). I used generalized linear mixed models to compare 691 cleaned Inuit knowledge records of anadromous and resident charr populations to river, lake, and geographic variables. I validated these models using 51 independent scientific records and k-fold cross-validation. Inuit knowledge data had more observations across a broader geographic and environmental space. Both models strongly fit the training data, but the resident model was not transferrable to the independent data. There was substantial overlap between the models. Both anadromous and resident charr are more likely to be found in larger lakes further east, and are more readily detected close to communities. Anadromy is less likely in longer rivers, although the effect is reduced for large lakes. This analysis demonstrates that existing Inuit knowledge data is underutilized for wildlife research and management in Nunavut. Combining two complementary types of records allowed a broader scale analysis than previously. Modelling at the lake level, however, primarily identified distributional drivers for the Arctic Charr ...
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