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Monitoring Stock-Specific Abundance, Run Timing, and Straying of Chinook Salmon in the Columbia River Using Genetic Stock Identification (GSI)

Feb 10, 2014


Genetic stock identification (GSI) provides a method of characterizing stock-specific abundance, run timing, and straying as they pertain to the population demographics and behavior of both hatchery and wild fish and thus assists with fisheries management. In this study, tissues were collected and genotyped at 13 microsatellite loci from adult Chinook Salmon Oncorhynchus tshawytscha that passed Bonneville Dam during four consecutive migration years (2004–2007). GSI methods were used to estimate the proportions of stocks in a broad genetic baseline, with high-density coverage of Chinook Salmon across the eastern Pacific Rim. The estimates of abundance for interior Columbia River stocks showed widespread decline consistent with a shift to poor ocean conditions during the years when the fish in this study were at sea, but divergent stock- and age-specific patterns were also observed. For example, the upper Columbia River spring-run stock experienced a unique net gain in abundance during this period, and the interior Columbia River summer–fall-run stock experienced a delayed decline of 4-year-olds. Stocks with early run timing shifted to later migrations. However, run timing distributions did not shift unidirectionally for all stocks across years, and stock membership in three major run timing categories was maintained. Of 9,215 total adults sampled, 27 (0.3%) were out-of-basin strays and a quarter of the strays were putatively of wild origin. The general concordance of GSI results with those based on more traditional methods supports the effectiveness of GSI as a tool for fisheries management.



Hess J.E., J.M. Whiteaker , J.K. Fryer, and S.R. Narum. 2014. Monitoring stock-specific abundance, Run Timing, and straying of Chinook Salmon in the Columbia River using genetic stock identification (GSI). North American Journal of Fisheries Management 34(1):184-201. Online at



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Journal Article