Abstract
Abstract Understanding how landscape features affect functional connectivity among populations is a cornerstone of spatial ecology and landscape genetic analyses. However, parameterization of resistance surfaces that best describe connectivity is a challenging and often subjective process. ResistanceGA is an R package that utilizes a genetic algorithm to optimize resistance surfaces based on pairwise genetic data and effective distances calculated using CIRCUITSCAPE, least cost paths or random‐walk commute times. Functions in this package allow for the optimization of categorical and continuous resistance surfaces, and simultaneous optimization of multiple resistance surfaces. ResistanceGA provides a coherent framework to optimize resistance surfaces without a priori assumptions, conduct model selection, and make inference about the contribution of each surface to total resistance. ResistanceGA fills a void in the landscape genetic toolbox, allowing for unbiased optimization of resistance surfaces and for the simultaneous optimization of multiple resistance surfaces to create novel composite resistance surfaces, but could have broader applicability to other fields of spatial ecological research.
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