Landscape-level analysis of mountain goat population connectivity in Washington and southern British Columbia
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Habitat fragmentation and habitat loss diminish population connectivity, reducing genetic diversity and increasing extinction risk over time. Improving connectivity is widely recommended to preserve the long-term viability of populations, but this requires accurate knowledge of how landscapes influence connectivity. Detectability of landscape effects on gene flow is highly dependent on landscape context, and drawing conclusions from single landscape studies may lead to ineffective management strategies. We present a novel approach to elucidate regional variation in the relative importance of landscape variable effects on gene flow. We demonstrate this approach by evaluating gene flow between isolated, genetically impoverished mountain goat (Oreamnos americanus) populations in Washington and much larger, genetically robust populations in southern British Columbia. We used geneland to identify steep genetic gradients and then employed individual-based landscape genetics in a causal modeling framework to independently evaluate landscape variables that may be generating each of these genetic gradients. Our results support previous findings that freeways, highways, water, agriculture and urban landcover limit gene flow in this species. Additionally, we found that a previously unsupported landscape variable, distance to escape terrain, also limits gene flow in some contexts. By integrating geneland and individual-based methods we effectively identified regional limiting factors that have landscape-level implications for population viability.
KeywordsPopulation connectivity geneland Circuit theory Causal modeling Oreamnos americanus
We thank Andrew Shirk (University of Washington), Cliff Rice (WDFW), Brian Harris, Darryl Reynolds and Christ Proctor (BC Ministry of Forests, Lands and Natural Resource Operations), Cliff Nietvelt (BC Ministry of the Environment), Katy Chambers (BC Parks and Protected Areas), Aaron Shafer (Uppsala University), Kim Poole (Aurora Wildlife Research) and David Paetkau (Wildlife Genetics International) for their collaboration. We thank Samuel Wasser and Rebecca Nelson Booth (University of Washington) for assistance developing sample collection protocol and Ken Warheit, Scott Blankenship and Cheryl Dean (WDFW) for genotyping. Funding was provided by the WDFW Aquatic Lands Enhancement Account, Seattle City Light, the Mountaineers Foundation, the Mazamas, the Safari Club International Foundation, the Washington Chapter of the Wildlife Society, Western Washington University Office of Research and Sponsored Programs and Huxley College of the Environment.
Conflict of interest
The authors declare that they have no conflict of interest.
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