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Inferring landscape effects on gene flow: a new model selection framework

Category: Wildlife Research and Management - Wildlife Research

Date Published: May 19, 2010

Number of Pages: 17

Author(s): A.J. Shirk, D.O. Wallin, S.A. Cushman, C.G. Rice and K.I. Warheit


Originally published in, Molecular Ecology (2010) 19, 3603–3619

Keywords: circuit theory, gene flow, isolation by distance, landscape resistance, mountain goat

Populations in fragmented landscapes experience reduced gene flow, lose genetic diversity over time and ultimately face greater extinction risk. Improving connectivity in fragmented landscapes is now a major focus of conservation biology. Designing effective wildlife corridors for this purpose, however, requires an accurate understanding of how landscapes shape gene flow. The preponderance of landscape resistance models generated to date, however, is subjectively parameterized based on expert opinion or proxy measures of gene flow. While the relatively few studies that use genetic data are more rigorous, frameworks they employ frequently yield models only weakly related to the observed patterns of genetic isolation. Here, we describe a new framework that uses expert opinion as a starting point. By systematically varying each model parameter, we sought to either validate the assumptions of expert opinion, or identify a peak of support for a new model more highly related to genetic isolation. This approach also accounts for interactions between variables, allows for nonlinear responses and excludes variables that reduce model performance. We demonstrate its utility on a population of mountain goats inhabiting a fragmented landscape in the Cascade Range, Washington.