| Summary: | Thesis (M.S.) University of Alaska Fairbanks, 2016 Pacific salmon (Oncorhynchus spp.) are an economically and culturally important genus of fishes endemic to the North Pacific. Their sustainable management depends on an understanding of the drivers of their abundance and migration dynamics. In many instances, statistical models are employed to predict abundance and run timing before harvest takes place to more effectively meet management objectives. In this thesis, I created a general-purpose predictive model of run timing that can be applied to many salmon populations. I then applied it to Yukon River Chinook salmon (O. tshawytscha) by generating pre-season predictions of inriver run timing, which I then compared with existing observations of run timing at two upriver locations. Prediction errors were low enough for the model to be useful to management. Models such as the one created in this study represent an objective tool that can be used to reduce subjectivity in fisheries management.
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