Landscape-level analysis of mountain goat population connectivity in Washington and southern British Columbia

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• 作者：Leslie C. Parks ; David O. Wallin ; Samuel A. Cushman ; Brad H. McRae
• 关键词：Population connectivity ; geneland ; Circuit theory ; Causal modeling ; Oreamnos americanus
• 刊名：Conservation Genetics
• 出版年：2015
• 出版时间：October 2015
• 年：2015
• 卷：16
• 期：5
• 页码：1195-1207
• 全文大小：3,363 KB
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• 作者单位：Leslie C. Parks (1)
  David O. Wallin (1)
  Samuel A. Cushman (2)
  Brad H. McRae (3)
  
  1. Department of Environmental Sciences, Huxley College of the Environment, Western Washington University, 516 High St., Bellingham, WA, 98225, USA
  2. Rocky Mountain Research Station, U.S. Forest Service, 2500 S. Pine Knoll Dr., Flagstaff, AZ, 86001, USA
  3. The Nature Conservancy, North America Region, 117 Mountain Ave., Suite 201, Fort Collins, CO, 80524, USA
  
• 刊物类别：Biomedical and Life Sciences
• 刊物主题：Biomedicine
  Human Genetics
  Animal Anatomy, Morphology and Histology
  Plant Sciences
  Evolutionary Biology
  
• 出版者：Springer Netherlands
• ISSN：1572-9737

文摘

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. Keywords Population connectivity geneland Circuit theory Causal modeling Oreamnos americanus