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The effect of sampling density and study area size on landscape genetic inferences for the Mississippi slimy salamander (Plethodon mississippi)

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Dec 14, 2021 version files 126.13 MB

Abstract

In the field of landscape genetics, it is largely unknown how choices regarding population sampling density and study area size impact inferences about which habitat features impede vs. facilitate gene flow. While it is commonly recommended that sampling locations be spaced no further apart than the average individual dispersal distance, for low mobility species, this could lead to a logistically challenging number of sampling locations, or a small and unrepresentative study area. We assessed the effects of sampling density and study area size on landscape genetics inferences for a dispersal-limited amphibian, the Mississippi slimy salamander (Plethodon mississippi), via comparative analysis of nested datasets. Microsatellite-based genetic distances among individuals were divided into three datasets representing either sparse sampling across a large study area, dense sampling across a small study area, or sparse sampling across the same small study area. These datasets were each used as a response variable in maximum likelihood population effects models that assessed the nature and strength of the relationship, if any, between each of five land use classes (i.e., potential predictor variables) and the response variable. Comparative analyses were based on the rank order of effect (i.e., strongest to weakest), sign of effect (i.e., gene flow resistance vs. facilitation), spatial scale of effect, and functional relationship with gene flow. Outcomes were interpreted within the context of five possible combinations of congruence among datasets. We found that each best-fit model associated with the three datasets had the same sign of effect for hardwood forests, manmade structures, and pine forests. However, different sampling densities led to a different inferred functional relationship between agricultural areas and gene flow. Furthermore, study area size appeared to influence the inferred scale of effect of manmade structures and sign of effect of pine forests. Taken together, our findings provided evidence for an influence of sampling density, study area size, and sampling effort upon inferences. Accordingly, in the absence of strong a priori information about spatial-genetic structure and species’ life history traits, we recommend iterative subsampling and reanalysis of empirical datasets, coupled with continued investigation into the sensitivities of landscape genetics analyses using simulations or other controlled experimental designs.