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International Journal of Ecology
Volume 2012 (2012), Article ID 539109, 8 pages
http://dx.doi.org/10.1155/2012/539109
Research Article

Simulating Pattern-Process Relationships to Validate Landscape Genetic Models

1Climate Impacts Group, University of Washington, Box 355672, Seattle, WA 98195, USA
2Rocky Mountain Research Station, United States Forest Service, Missoula, MT 59808, USA
3Division of Biological Sciences, University of Montana, Missoula, MT 59812, USA

Received 28 September 2011; Accepted 6 January 2012

Academic Editor: Daniel Rubenstein

Copyright © 2012 A. J. Shirk et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Landscapes may resist gene flow and thereby give rise to a pattern of genetic isolation within a population. The mechanism by which a landscape resists gene flow can be inferred by evaluating the relationship between landscape models and an observed pattern of genetic isolation. This approach risks false inferences because researchers can never feasibly test all plausible alternative hypotheses. In this paper, rather than infer the process of gene flow from an observed genetic pattern, we simulate gene flow and determine if the simulated genetic pattern is related to the observed empirical genetic pattern. This is a form of inverse modeling and can be used to independently validate a landscape genetic model. In this study, we used this approach to validate a model of landscape resistance based on elevation, landcover, and roads that was previously related to genetic isolation among mountain goats (Oreamnos americanus) inhabiting the Cascade Range, Washington (USA). The strong relationship between the empirical and simulated patterns of genetic isolation we observed provides independent validation of the resistance model and demonstrates the utility of this approach in supporting landscape genetic inferences.