Using 2 Genetic Markers to Discriminate Among Canada Goose Populations in Ohio

Abstract: Canada goose (Branta canadensis) harvest management depends on reliable estimates of harvest composition, and established genetic methods provide an alternative to traditional methods. We expanded upon previous genetic studies by comparing the utility of 6 nuclear microsatellite loci and mitochondrial (mtDNA) control region sequences for discriminating among giant (B. c. maxima) and interior (B. c. interior) populations in Ohio (USA) Canada goose harvests at both individual and population levels. Subspecies and populations exhibited greater differentiation in mtDNA (F_ST = 0.202) than microsatellites (F_ST = 0.021), as would be expected based on differences in effective population size. Neither microsatellites nor mtDNA alone were sufficient for estimating harvest composition at the subspecies or population level in simulations and empirical blind tests using individuals of known origin; however, a combined microsatellite + mtDNA dataset yielded accurate and precise harvest derivations at the subspecies level. Both population-level mixed stock analysis and individual-level assignment tests provided accurate results, but a large proportion of birds could not be assigned with confidence at the individual level. We applied mixed stock analysis and the combined microsatellite + mtDNA dataset to Ohio's 2003–2004 harvest and found that interior populations accounted for 4.9% (95% CI = 1.7–8.0%) of the statewide early season and 9.3% (95% CI = 6.9–11.6%) of the regular and late-season harvested sample. These results suggest that maximum likelihood harvest derivations are highly dependent on the choice of genetic markers. Studies should only employ markers that exhibit sufficient variation and have been shown through simulations and empirical testing to accurately discriminate among the subspecies or management populations of interest.