Fine-scale landscape genetics of the American badger (Taxidea taxus): disentangling landscape effects and sampling artifacts in a poorly understood species

Landscape genetics is a powerful tool for conservation because it identifies landscape features that are important for maintaining genetic connectivity between populations within heterogeneous landscapes. However, using landscape genetics in poorly understood species presents a number of challenges, namely, limited life history information for the focal population and spatially biased sampling. Both obstacles can reduce power in statistics, particularly in individual-based studies. In this study, we genotyped 233 American badgers in Wisconsin at 12 microsatellite loci to identify alternative statistical approaches that can be applied to poorly understood species in an individual-based framework. Badgers are protected in Wisconsin owing to an overall lack in life history information, so our study utilized partial redundancy analysis (RDA) and spatially lagged regressions to quantify how three landscape factors (Wisconsin River, Ecoregions and land cover) impacted gene flow. We also perfo...

景观遗传学（Landscape genetics）是助力保护工作的高效工具，其可在异质景观中识别出对维持种群间遗传连通性至关重要的景观特征。然而，针对认知程度较低的物种开展景观遗传学研究时，会面临诸多挑战，具体表现为目标种群的生活史信息匮乏，以及采样存在空间偏倚。这两类障碍均会削弱统计检验效能，在基于个体的研究中这一问题尤为显著。本研究对美国威斯康星州的233只美洲獾进行了12个微卫星位点（microsatellite loci）的基因分型，旨在探索可应用于认知程度较低物种的基于个体研究框架的替代统计方法。由于美洲獾的生活史信息整体匮乏，威斯康星州已将其列为保护物种，因此本研究采用偏冗余分析（Partial Redundancy Analysis, RDA）与空间滞后回归（spatially lagged regressions）模型，量化了三类景观因子——威斯康星河（Wisconsin River）、生态区（Ecoregions）与土地覆盖（land cover）——对基因流（gene flow）的影响。本研究还开展了相关工作，原文后续内容未完整呈现