Spear Stephen F, Peterson Charles R, Matocq Marjorie D, Storfer Andrew
Department of Biological Sciences, Idaho State University, Pocatello, Idaho 83209, USA.
Mol Ecol. 2005 Jul;14(8):2553-64. doi: 10.1111/j.1365-294X.2005.02573.x.
The field of landscape genetics has great potential to identify habitat features that influence population genetic structure. To identify landscape correlates of genetic differentiation in a quantitative fashion, we developed a novel approach using geographical information systems analysis. We present data on blotched tiger salamanders (Ambystoma tigrinum melanostictum) from 10 sites across the northern range of Yellowstone National Park in Montana and Wyoming, USA. We used eight microsatellite loci to analyse population genetic structure. We tested whether landscape variables, including topographical distance, elevation, wetland likelihood, cover type and number of river and stream crossings, were correlated with genetic subdivision (F(ST)). We then compared five hypothetical dispersal routes with a straight-line distance model using two approaches: (i) partial Mantel tests using Akaike's information criterion scores to evaluate model robustness and (ii) the BIOENV procedure, which uses a Spearman rank correlation to determine the combination of environmental variables that best fits the genetic data. Overall, gene flow appears highly restricted among sites, with a global F(ST) of 0.24. While there is a significant isolation-by-distance pattern, incorporating landscape variables substantially improved the fit of the model (from an r2 of 0.3 to 0.8) explaining genetic differentiation. It appears that gene flow follows a straight-line topographic route, with river crossings and open shrub habitat correlated with lower F(ST) and thus, decreased differentiation, while distance and elevation difference appear to increase differentiation. This study demonstrates a general approach that can be used to determine the influence of landscape variables on population genetic structure.
景观遗传学领域在识别影响种群遗传结构的栖息地特征方面具有巨大潜力。为了以定量方式识别遗传分化的景观关联因素，我们开发了一种利用地理信息系统分析的新方法。我们展示了来自美国蒙大拿州和怀俄明州黄石国家公园北部区域10个地点的带斑虎螈（Ambystoma tigrinum melanostictum）的数据。我们使用8个微卫星位点分析种群遗传结构。我们测试了包括地形距离、海拔、湿地可能性、覆盖类型以及河流和溪流穿越数量在内的景观变量是否与遗传细分（F(ST)）相关。然后，我们使用两种方法将五条假设的扩散路线与直线距离模型进行比较：（i）使用赤池信息准则分数的偏曼特尔检验来评估模型的稳健性，以及（ii）BIOENV程序，该程序使用斯皮尔曼等级相关性来确定最适合遗传数据的环境变量组合。总体而言，各地点之间的基因流似乎受到高度限制，全局F(ST)为0.24。虽然存在显著的距离隔离模式，但纳入景观变量极大地改善了模型对遗传分化的拟合度（从r2为0.3提高到0.8）。基因流似乎遵循直线地形路线，河流穿越和开阔灌木栖息地与较低的F(ST)相关，因此分化程度降低，而距离和海拔差异似乎会增加分化程度。这项研究展示了一种可用于确定景观变量对种群遗传结构影响的通用方法。
