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Title: Simulating natural selection in landscape genetics

Author: Landguth, E. L.; Cushman, S. A.; Johnson, N.

Date: 2012

Source: Molecular Ecology Resources. 12: 363-368.

Publication Series: Journal/Magazine Article (JRNL)

Description: Linking landscape effects to key evolutionary processes through individual organism movement and natural selection is essential to provide a foundation for evolutionary landscape genetics. Of particular importance is determining how spatially- explicit, individual-based models differ from classic population genetics and evolutionary ecology models based on ideal panmictic populations in an allopatric setting in their predictions of population structure and frequency of fixation of adaptive alleles. We explore initial applications of a spatially-explicit, individual-based evolutionary landscape genetics program that incorporates all factors - mutation, gene flow, genetic drift and selection - that affect the frequency of an allele in a population. We incorporate natural selection by imposing differential survival rates defined by local relative fitness values on a landscape. Selection coefficients thus can vary not only for genotypes, but also in space as functions of local environmental variability. This simulator enables coupling of gene flow (governed by resistance surfaces), with natural selection (governed by selection surfaces).We validate the individual-based simulations under Wright-Fisher assumptions. We show that under isolation-by-distance processes, there are deviations in the rate of change and equilibrium values of allele frequency. The program provides a valuable tool (CDPOP v1.0; http://cel.dbs.umt.edu/software/CDPOP/) for the study of evolutionary landscape genetics that allows explicit evaluation of the interactions between gene flow and selection in complex landscapes.

Keywords: computer simulation, fitness surfaces, individual-based, isolation-by-distance, landscape resistance, population genetics, spatially-explicit

Publication Notes:

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  • This article was written and prepared by U.S. Government employees on official time, and is therefore in the public domain.

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Landguth, E. L.; Cushman, S. A.; Johnson, N. 2012. Simulating natural selection in landscape genetics. Molecular Ecology Resources. 12: 363-368.

 


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