ArticleGenetics2005
Variogram analysis of the spatial genetic structure of continuous populations using multilocus microsatellite data.
Article in Genetics, 2005. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Spatially VaryingEvolutionary applications · 2024Article
- Article
- The effect of sampling density and study area size on landscape genetics inferences for the Mississippi slimy salamander (Ecology and evolution · 2021Article
- Deep divergence between island populations in lichenized fungi.Scientific reports · 2021Article
- Landscape genetics reveals unique and shared effects of urbanization for two sympatric pool-breeding amphibians.Ecology and evolution · 2019Article
- Article
- The genetic structure of a Venturia inaequalis population in a heterogeneous host population composed of different Malus species.BMC evolutionary biology · 2013Article
- Hitchhiking with forests: population genetics of the epiphytic lichen Lobaria pulmonaria in primeval and managed forests in southeastern Europe.Ecology and evolution · 2012Article
- A review of techniques for spatial modeling in geographical, conservation and landscape genetics.Genetics and molecular biology · 2009Article
- Non-parametric smoothing of multivariate genetic distances in the analysis of spatial population structure at fine scale.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2008Article
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Authors and funding
6 authors.
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No grant is acknowledged in the PubMed record.
Abstract
A geostatistical perspective on spatial genetic structure may explain methodological issues of quantifying spatial genetic structure and suggest new approaches to addressing them. We use a variogram approach to (i) derive a spatial partitioning of molecular variance, gene diversity, and genotypic diversity for microsatellite data under the infinite allele model (IAM) and the stepwise mutation model (SMM), (ii) develop a weighting of sampling units to reflect ploidy levels or multiple sampling of genets, and (iii) show how variograms summarize the spatial genetic structure within a population under isolation-by-distance. The methods are illustrated with data from a population of the epiphytic lichen Lobaria pulmonaria, using six microsatellite markers. Variogram-based analysis not only avoids bias due to the underestimation of population variance in the presence of spatial autocorrelation, but also provides estimates of population genetic diversity and the degree and extent of spatial genetic structure accounting for autocorrelation.
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