Climate change can have particularly severe consequences for high-elevation species that are well-adapted to long-lasting snow conditions within their habitats. One such species is the wolverine, Gulo gulo, with several studies showing a strong, year-round association of the species with the area defined by persistent spring snow cover. This bioclimatic niche also predicts successful dispersal paths for wolverines in the contiguous United States, where the species shows low levels of genetic exchange and low effective population size. Here, we assess the influence of additional climatic, vegetative, topographic, and anthropogenic, variables on wolverine genetic structure in this region using a multivariate, multiscale, landscape genetic approach. This approach allows us to detect landscape-genetic relationships both due to typical, small-scale genetic exchange within habitat, as well as exceptional, long-distance dispersal among habitats. Results suggest that a combination of snow depth, terrain ruggedness, and housing density, best predict gene flow in wolverines, and that the relative importance of variables is scale-dependent. Environmental variables (i.e., isolation-by-resistance, IBR) were responsible for 79% of the explained variation at small scales (i.e., up to ∼230 km), and 65% at broad scales (i.e., beyond ∼420 km). In contrast, a null model based on only space (i.e., isolation-by-distance, IBD) accounted only for 17% and 11% of the variation at small and broad scales, respectively. Snow depth was the most important variable for predicting genetic structures overall, and at small scales, where it contributed 43% to the variance explained. At broad spatial scales, housing density and terrain ruggedness were most important with contributions to explained variation of 55% and 25%, respectively. While the small-scale analysis most likely captures gene flow within typical wolverine habitat complexes, the broad-scale analysis reflects long-distance dispersal across areas not typically inhabited by wolverines. These findings help to refine our understanding of the processes shaping wolverine genetic structure, which is important for maintaining and improving functional connectivity among remaining wolverine populations.

中文翻译：

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狼獾 (Gulo gulo) 的景观遗传学：生物气候、地形和人为变量的规模依赖效应

气候变化会对高度适应栖息地内长期积雪条件的高海拔物种造成特别严重的后果。其中一个物种是狼獾，Gulo gulo，几项研究表明，该物种与春季持续积雪覆盖的区域有很强的全年联系。这种生物气候生态位还预测了美国本土狼獾的成功扩散路径，在那里，该物种的基因交换水平低，有效种群规模低。在这里，我们使用多变量、多尺度、景观遗传方法评估了额外的气候、植物、地形和人为变量对该地区狼獾遗传结构的影响。这种方法使我们能够检测由于典型的景观遗传关系，栖息地内的小规模遗传交换，以及栖息地之间特殊的远距离传播。结果表明，积雪深度、地形崎岖程度和住房密度的组合最能预测狼獾中的基因流动，并且变量的相对重要性与规模有关。环境变量（即，电阻隔离，IBR）在小尺度（即高达~230 公里）中解释了 79% 的变异，在宽尺度（即，超过~420 公里）中占 65%。相比之下，仅基于空间（即，按距离隔离，IBD）的零模型分别仅占小尺度和大尺度变异的 17% 和 11%。雪深是预测整体遗传结构的最重要变量，在小尺度上，它对解释的方差贡献了 43%。在广阔的空间尺度上，住房密度和地形坚固性是最重要的，对解释变异的贡献分别为 55% 和 25%。虽然小规模分析最有可能捕获典型狼獾栖息地复合体内的基因流，但大规模分析反映了在狼獾通常不居住的地区的长距离扩散。这些发现有助于完善我们对塑造狼獾遗传结构过程的理解，这对于维持和改善剩余狼獾种群之间的功能连通性很重要。大规模分析反映了狼獾通常不居住的地区的长距离分散。这些发现有助于完善我们对塑造狼獾遗传结构过程的理解，这对于维持和改善剩余狼獾种群之间的功能连通性很重要。大规模分析反映了狼獾通常不居住的地区的长距离分散。这些发现有助于完善我们对塑造狼獾遗传结构过程的理解，这对于维持和改善剩余狼獾种群之间的功能连通性很重要。