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Isolation by resistance.

¹National Center for Ecological Analysis and Synthesis, University of California, Santa Barbara, California 93101-5504, USA. mcrae@nceas.ucsb.edu

Evolution; International Journal of Organic Evolution

|October 5, 2006

Summary

The new isolation-by-resistance model accurately predicts genetic structuring in complex landscapes. It uses resistance distance to account for landscape heterogeneity, improving upon traditional methods for population genetic studies.

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Area of Science:

Population Genetics
Landscape Ecology
Spatial Analysis

Background:

Growing interest in landscape heterogeneity's effects on genetic structuring.
Limited tools exist to integrate landscape composition into population genetic studies.
Traditional isolation-by-distance analyses often assume spatial homogeneity or use theoretically weak distance metrics.

Purpose of the Study:

To propose the isolation-by-resistance (IBR) model as an alternative for predicting genetic structuring in complex landscapes.
To provide a theoretically justified and robust method for incorporating landscape heterogeneity into population genetic analyses.

Main Methods:

Introduced the isolation-by-resistance (IBR) model.
Utilized resistance distance, derived from random walk times and effective resistances in electronic networks, to predict genetic differentiation.
Demonstrated applicability with diverse data inputs, from range maps to complex habitat datasets.

Main Results:

The IBR model predicts a positive relationship between genetic differentiation and resistance distance.
Resistance distance is more theoretically justified and robust to spatial heterogeneity than Euclidean or least cost path distances.
The IBR model offers flexibility in data input, accommodating various landscape complexity levels.

Conclusions:

The IBR model provides a flexible and efficient tool for accounting for habitat heterogeneity in isolation-by-distance studies.
This approach enhances understanding of how landscape characteristics influence genetic structuring.
The IBR model can predict the genetic and evolutionary consequences of landscape change.

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