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Representing genetic variation as continuous surfaces: An approach for identifying spatial dependency in landscape genetic studiesAuthor(s): Melanie A. Murphy; Jeffrey S. Evans; Samuel A. Cushman; Andrew Storfer
Source: Ecography. 31: 685-697.
Publication Series: Scientific Journal (JRNL)
Station: Rocky Mountain Research Station
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DescriptionLandscape genetics, an emerging field integrating landscape ecology and population genetics, has great potential to influence our understanding of habitat connectivity and distribution of organisms. Whereas typical population genetics studies summarize gene flow as pairwise measures between sampling localities, landscape characteristics that influence population genetic connectivity are often continuously distributed in space. Thus, there are currently gaps in both the ability to analyze genotypic data in a continuous spatial context and our knowledge of expected of landscape genetic structure under varying conditions. We present a framework for generating continuous "genetic surfaces", evaluate their statistical properties, and quantify statistical behavior of landscape genetic structure in a simple landscape. We simulated microsatellite genotypes under varying parameters (time since vicariance, migration, effective population size) and used ancestry (q) values from STRUCTURE to interpolate a genetic surface.
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CitationMurphy, Melanie A.; Evans, Jeffrey S.; Cushman, Samuel A.; Storfer, Andrew. 2008. Representing genetic variation as continuous surfaces: An approach for identifying spatial dependency in landscape genetic studies. Ecography. 31: 685-697.
Keywordslandscape genetics, genetic variation, spatial dependency
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