期刊
MOLECULAR ECOLOGY
卷 19, 期 17, 页码 3565-3575出版社
WILEY
DOI: 10.1111/j.1365-294X.2010.04757.x
关键词
autocorrelation; dispersal; gene flow; sampling; space-time processes; spatial genetic structure
资金
- NSF [DEB-0553768]
- University of California, Santa Barbara
- State of California
- Department of Fisheries and Wildlife at Michigan State University
- Michigan Department of Natural Resources
- NSERC
- ETH-domain
- National Evolutionary Synthesis Center (NESCent), NSF [EF-0905606]
- University of Alberta
Landscape features exist at multiple spatial and temporal scales, and these naturally affect spatial genetic structure and our ability to make inferences about gene flow. This article discusses how decisions about sampling of genotypes (including choices about analytical methods and genetic markers) should be driven by the scale of spatial genetic structure, the time frame that landscape features have existed in their current state, and all aspects of a species' life history. Researchers should use caution when making inferences about gene flow, especially when the spatial extent of the study area is limited. The scale of sampling of the landscape introduces different features that may affect gene flow. Sampling grain should be smaller than the average home-range size or dispersal distance of the study organism and, for raster data, existing research suggests that simplifying the thematic resolution into discrete classes may result in low power to detect effects on gene flow. Therefore, the methods used to characterize the landscape between sampling sites may be a primary determinant for the spatial scale at which analytical results are applicable, and the use of only one sampling scale for a particular statistical method may lead researchers to overlook important factors affecting gene flow. The particular analytical technique used to correlate landscape data and genetic data may also influence results; common landscape-genetic methods may not be suitable for all study systems, particularly when the rate of landscape change is faster than can be resolved by common molecular markers.
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