ISOLATION BY RESISTANCE
2006/08/01 by Brad H. McRae · 926 citations
Agricultural and Biological Sciences · Biochemistry, Genetics and Molecular Biology · Engineering · #Animal Behavior and Reproduction #Artificial intelligence #Biology #Computer science #Ecology #Engineering #Euclidean distance #Fitness landscape #Genetic and phenotypic traits in livestock #Genetic distance #Genetic diversity and population structure #Genetic structure #Genetic variation #Genetics #Geographical distance #Isolation by distance #Metric (unit) #Population #Range (aeronautics) #Structuring
paper · pdf · doi:10.1111/j.0014-3820.2006.tb00500.x
published in Evolution 60(8), 1551-1561 (Oxford University Press)
openalex publication_date 2006/08/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/30
Abstract
Despite growing interest in the effects of landscape heterogeneity on genetic structuring, few tools are available to incorporate data on landscape composition into population genetic studies. Analyses of isolation by distance have typically either assumed spatial homogeneity for convenience or applied theoretically unjustified distance metrics to compensate for heterogeneity. Here I propose the isolation‐by‐resistance (IBR) model as an alternative for predicting equilibrium genetic structuring in complex landscapes. The model predicts a positive relationship between genetic differentiation and the resistance distance, a distance metric that exploits precise relationships between random walk times and effective resistances in electronic networks. As a predictor of genetic differentiation, the resistance distance is both more theoretically justified and more robust to spatial heterogeneity than Euclidean or least cost path‐based distance measures. Moreover, the metric can be applied with a wide range of data inputs, including coarse‐scale range maps, simple maps of habitat and nonhabitat within a species' range, or complex spatial datasets with habitats and barriers of differing qualities. The IBR model thus provides a flexible and efficient tool to account for habitat heterogeneity in studies of isolation by distance, improve understanding of how landscape characteristics affect genetic structuring, and predict genetic and evolutionary consequences of landscape change.
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