Natural re-colonization and admixture of wolves (Canis lupus) in the US Pacific Northwest: challenges for the protection and management of rare and endangered taxa

Admixture resulting from natural dispersal processes can potentially generate novel phenotypic variation that may facilitate persistence in changing environments or result in the loss of population-specific adaptations. Yet, under the US Endangered Species Act, policy is limited for management of individuals whose ancestry includes a protected taxon; therefore, they are generally not protected under the Act. This issue is exemplified by the recently re-established grey wolves of the Pacific Northwest states of Washington and Oregon, USA. This population was likely founded by two phenotypically and genetically distinct wolf ecotypes: Northern Rocky Mountain (NRM) forest and coastal rainforest. The latter is considered potentially threatened in southeast Alaska and thus the source of migrants may affect plans for their protection. To assess the genetic source of the re-established population, we sequenced a similar to 300 bp portion of the mitochondrial control region and similar to 5 Mbp of the nuclear genome. Genetic analysis revealed that the Washington wolves share ancestry with both wolf ecotypes, whereas the Oregon population shares ancestry with NRM forest wolves only. Using ecological niche modelling, we found that the Pacific Northwest states contain environments suitable for each ecotype, with wolf packs established in both environmental types. Continued migration from coastal rainforest and NRM forest source populations may increase the genetic diversity of the Pacific Northwest population. However, this admixed population challenges traditional management regimes given that admixture occurs between an adaptively distinct ecotype and a more abundant reintroduced interior form. Our results emphasize the need for a more precise US policy to address the general problem of admixture in the management of endangered species, subspecies, and distinct population segments.