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Abstract of paper 5:
Wagner, H. H., R. Holderegger, S. Werth,
F. Gugerli, S. E. Hoebee, and C. Scheidegger. 2005. Variogram analysis
of the spatial genetic structure of continuous populations using
multilocus microsatellite data. Genetics 169:1739-1752.
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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