Data from: Examining the full effects of landscape heterogeneity on spatial genetic variation: a multiple matrix regression approach for quantifying geographic and ecological isolation

Understanding the effects of landscape heterogeneity on spatial genetic variation is a primary goal of landscape genetics. Ecological and geographic variables can contribute to genetic structure through geographic isolation, in which geographic barriers and distances restrict gene flow, and ecological isolation, in which gene flow among populations inhabiting different environments is limited by selection against dispersers moving between them. Although methods have been developed to study geographic isolation in detail, ecological isolation has received much less attention, partly because disentangling the effects of these mechanisms is inherently difficult. Here, I describe a novel approach for quantifying the effects of geographic and ecological isolation using multiple matrix regression with randomization. I explored the parameter space over which this method is effective using a series of individual-based simulations and found that it accurately describes the effects of geographic and ecological isolation over a wide range of conditions. I also applied this method to a set of real-world datasets to show that ecological isolation is an often overlooked but important contributor to patterns of spatial genetic variation and to demonstrate how this analysis can provide new insights into how landscapes contribute to the evolution of genetic variation in nature.

解析景观异质性对空间遗传变异的影响，是景观遗传学（Landscape Genetics）的核心研究目标。生态与地理变量可通过地理隔离（Geographic Isolation）与生态隔离（Ecological Isolation）两种途径影响种群遗传结构：其中地理隔离指地理屏障与地理距离限制基因流（Gene Flow）；生态隔离则指栖息于不同环境的种群间，跨环境扩散的个体因遭遇选择压力而无法成功完成扩散，进而限制了种群间的基因交流。尽管学界已开发出可细致研究地理隔离的相关方法，但针对生态隔离的研究仍相对匮乏，部分原因在于区分这两种机制的影响本身颇具难度。本文提出一种全新研究方法，可借助随机化多重矩阵回归（Multiple Matrix Regression with Randomization）量化地理隔离与生态隔离的效应。通过一系列基于个体的模拟（Individual-based Simulations），本文探索了该方法有效的参数区间，结果显示其可在广泛的实验条件下准确反映地理隔离与生态隔离的影响。本文还将该方法应用于多组真实世界数据集，证实生态隔离虽常被忽视，却实为空间遗传变异格局的重要驱动因素，并展示了该分析框架可如何为理解景观如何推动自然种群遗传变异的演化提供全新研究视角。