Dataset Information

Landscape genetic inferences vary with sampling scenario for a pond-breeding amphibian.

ABSTRACT: 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 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.

SUBMITTER: Seaborn T

PROVIDER: S-EPMC6509389 | biostudies-literature | 2019 May

REPOSITORIES: biostudies-literature

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Landscape genetic inferences vary with sampling scenario for a pond-breeding amphibian.

Seaborn Travis T Hauser Samantha S SS Konrade Lauren L Waits Lisette P LP Goldberg Caren S CS

Ecology and evolution 20190415 9

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, ...[more]

PMID: 31110662

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Project description:Understanding metapopulation dynamics requires knowledge about local population dynamics and movement in both space and time. Most genetic metapopulation studies use one or two study species across the same landscape to infer population dynamics; however, using multiple co-occurring species allows for testing of hypotheses related to different life history strategies. We used genetic data to study dispersal, as measured by gene flow, in three ambystomatid salamanders (Ambystoma annulatum, A. maculatum, and A. opacum) and the Central Newt (Notophthalmus viridescens louisianensis) on the same landscape in Missouri, USA. While all four salamander species are forest dependent organisms that require fishless ponds to reproduce, they differ in breeding phenology and spatial distribution on the landscape. We use these differences in life history and distribution to address the following questions: (1) Are there species-level differences in the observed patterns of genetic diversity and genetic structure? and (2) Is dispersal influenced by landscape resistance? We detected two genetic clusters in A. annulatum and A. opacum on our landscape; both species breed in the fall and larvae overwinter in ponds. In contrast, no structure was evident in A. maculatum and N. v. louisianensis, species that breed during the spring. Tests for isolation by distance were significant for the three ambystomatids but not for N. v. louisianensis. Landscape resistance also contributed to genetic differentiation for all four species. Our results suggest species-level differences in dispersal ability and breeding phenology are driving observed patterns of genetic differentiation. From an evolutionary standpoint, the observed differences in dispersal distances and genetic structure between fall breeding and spring breeding species may be a result of the trade-off between larval period length and size at metamorphosis which in turn may influence the long-term viability of the metapopulation. Thus, it is important to consider life history differences among closely related and ecologically similar species when making management decisions.

Project description:In landscape genetics, it is largely unknown how choices regarding sampling density and study area size impact inferences upon which habitat features impede vs. facilitate gene flow. While it is recommended that sampling locations be spaced no further apart than the average individual's dispersal distance, for low-mobility species, this could lead to a challenging number of sampling locations, or an unrepresentative study area. We assessed the effects of sampling density and study area size on landscape genetic inferences for a dispersal-limited amphibian, Plethodon mississippi, via analysis of nested datasets. Microsatellite-based genetic distances among individuals were divided into three datasets representing 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 a proxy for gene flow (i.e., the response variable) in maximum-likelihood population effects models that assessed the nature and strength of their relationship with each of five land-use classes (i.e., potential predictor variables). Comparisons of outcomes were based on the rank order of effect, sign of effect (i.e., gene flow resistance vs. facilitation), spatial scale of effect, and functional relationship with gene flow. The best-fit model for each dataset had the same sign of effect for hardwood forests, manmade structures, and pine forests, indicating the impacts of these land-use classes on dispersal and gene flow in P. mississippi are robust to sampling scheme. Contrasting sampling densities led to a different inferred functional relationship between agricultural areas and gene flow. Study area size appeared to influence the scale of effect of manmade structures and the sign of effect of pine forests. Our findings provided evidence for an influence of sampling density, study area size, and sampling effort upon inferences. Accordingly, we recommend iterative subsampling of empirical datasets and continued investigation into the sensitivities of landscape genetic analyses using simulations.

Dataset Information

Landscape genetic inferences vary with sampling scenario for a pond-breeding amphibian.

Publications

Landscape genetic inferences vary with sampling scenario for a pond-breeding amphibian.

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