Abstract
Genetic data can be used to estimate the stock composition of mixed-stock fisheries. Designing efficient strategies for estimating mixture proportions is important, but several aspects of study design remain poorly understood, particularly the relationship between genetic polymorphism and estimation error. In this study, computer simulation was used to investigate how the following variables affect expected squared error of mixture estimates: the number of loci examined, the number of alleles at those loci, and the size of baseline data sets. This work showed that (i) loci with more alleles produced estimates of stock proportions that had a lower expected squared error than less polymorphic loci, (ii) highly polymorphic loci did not require larger samples than less polymorphic loci, and (iii) the total number of independent alleles examined is a reasonable indicator of the quality of estimates of stock proportions.
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