Population genetics and mixed stock analysis of chum salmon (Oncorhynchus keta) with molecular genetics
Dates
Year
2012
Citation
Garvin, Michael R., 2012, Population genetics and mixed stock analysis of chum salmon (Oncorhynchus keta) with molecular genetics: University of Alaska Fairbanks.
Summary
Chum salmon (Oncorhynchus keta ) are important for subsistence and commercial harvest in Alaska. Variability of returns to western Alaskan drainages that caused economic hardship for stakeholders has led to speculation about reasons, which may include both anthropogenic and environmental causes in the marine environment. Mixed stock analysis (MSA) compares genetic information from an individual caught at sea to a reference baseline of genotypes to assign it to its population of origin. Application of genetic baselines requires several complex steps that can introduce bias. The bias may reduce the accuracy of MSA and result in overly-optimistic evaluations of baselines. Moreover, some applications that minimize bias cannot use informative [...]
Summary
Chum salmon (Oncorhynchus keta ) are important for subsistence and commercial harvest in Alaska. Variability of returns to western Alaskan drainages that caused economic hardship for stakeholders has led to speculation about reasons, which may include both anthropogenic and environmental causes in the marine environment. Mixed stock analysis (MSA) compares genetic information from an individual caught at sea to a reference baseline of genotypes to assign it to its population of origin. Application of genetic baselines requires several complex steps that can introduce bias. The bias may reduce the accuracy of MSA and result in overly-optimistic evaluations of baselines. Moreover, some applications that minimize bias cannot use informative haploid mitochondrial variation. Costs of baseline development are species-specific and difficult to predict. Finally, because populations of western Alaskan chum salmon demonstrate weak genetic divergence, samples from mixtures cannot be accurately assigned to a population of origin. The chapters of this thesis address three challenges. The first chapter describes technical aspects of genetic marker development. The second chapter describes a method to evaluate the precision and accuracy of a genetic baseline that accepts any type of data and reduces bias that may have been introduced during baseline development. This chapter also includes a method that places a cost on baseline development by predicting the number of markers needed to achieve a given accuracy. The final chapter explores the reasons for the weak genetic structure of western Alaskan chum salmon populations. The results of those analyses and both geological and archaeological data suggest that recent environmental and geological processes may be involved. The methods and analyses in this thesis can be applied to any species and may be particularly useful for other western Alaskan species.
