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Data from: Landscape genetic inferences vary with sampling scenario for a pond breeding amphibian


Seaborn, Travis et al. (2018), Data from: Landscape genetic inferences vary with sampling scenario for a pond breeding amphibian, Dryad, Dataset,


A critical decision in landscape genetic studies is whether to use individuals or populations as the sampling unit. This decision affects the time and cost of sampling and may affect ecological inference. We analyzed 334 Columbia spotted frogs at 8 microsatellite loci across 40 sites in northern Idaho to determine how inferences from landscape genetic analyses would vary with sampling design. At all sites, we compared a proportion available sampling scheme (PASS), in which all samples were used, to resampled datasets of 2-11 individuals. Additionally, we compared a population sampling scheme (PSS) to an individual sampling scheme (ISS) at 18 sites with sufficient sample size. We applied an information theoretic approach with both restricted maximum likelihood and maximum likelihood estimation to evaluate competing landscape resistance hypotheses. We found that PSS supported a low-density forest model (0.87) and ISS supported this model as well as additional models when testing hypotheses of landcover types that create the greatest resistance to gene flow for Columbia spotted frogs. Increased sampling density and study extent, seen by comparing PSS to PASS, showed a change in model support from a model of only low-density forest to a model of only high-density forest. As number of individuals increased, model support converged at 7 individuals for ISS to PSS. ISS may be useful to increase study extent and sampling density, but may lack power to provide strong support for the correct model with microsatellite datasets. Our results highlight the importance of additional research on sampling design effects on landscape genetics inference.

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National Science Foundation, Award: NSF-IGERT 0114304