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dc.contributor.authorSeaborn, Travis
dc.contributor.authorHauser, Samantha S.
dc.contributor.authorKonrade, Lauren A.
dc.contributor.authorWaits, Lisette P.
dc.contributor.authorGoldberg, Caren S.
dc.date.accessioned2019-05-08T22:15:38Z
dc.date.available2019-05-08T22:15:38Z
dc.date.issued2019-04-15
dc.identifier.citationSeaborn, Travis; Hauser, Samantha S.; Konrade, Lauren A.; Waits, Lisette P.; Goldberg, Caren S. 2019. Landscape genetic inferences vary with sampling scenario for a pond-breeding amphibian. Ecology and Evolution 2019en_US
dc.identifier.issn2045-7758
dc.identifier.urihttps://doi.org/10.1002/ece3.5023
dc.identifier.urihttp://hdl.handle.net/10057/16170
dc.description© 2019 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.en_US
dc.description.abstractA 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 low-density forest when restricted maximum likelihood was used, but a combination model of most variables when maximum likelihood was used. We also saw variations when AIC was used compared to BIC. ISS supported this model as well as additional models when testing hypotheses of land cover 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. As number of individuals increased, model support converged at 7–9 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.en_US
dc.language.isoen_USen_US
dc.publisherJohn Wiley and Sonsen_US
dc.relation.ispartofseriesEcology and Evolution;2019
dc.subjectAmphibian ecologyen_US
dc.subjectCircuitscapeen_US
dc.subjectColumbia spotted frogen_US
dc.subjectConnectivityen_US
dc.subjectLandscape geneticsen_US
dc.subjectSampling schemesen_US
dc.titleLandscape genetic inferences vary with sampling scenario for a pond-breeding amphibianen_US
dc.typeArticleen_US
dc.rights.holder© John Wiley & Sons Ltden_US


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