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

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