Xavier Vekemans

QUANTIFYING GENE FLOW FROM SPATIAL GENETIC STRUCTURE DATA IN A METAPOPULATION OF CHAMAECRISTA FASCICULATA (LEGUMINOSAE)

Abstract An extensive allozyme survey was conducted within a natural “meta” population of the native North American annual legume, Chamaecrista fasciculata (Leguminosae) to quantify genetic structure at different spatial scales. Gene flow was then estimated by a recently developed indirect method based on a continuous population model, using pairwise kinship coefficients between individuals. The indirect estimates of gene flow, quantified in terms of neighborhood size, with an average value on the order of 150 individuals, were concordant among different spatial scales (subpopulation, population, metapopulation). This gene‐flow value lies within the range of direct estimates previously documented from observations of pollen and seed dispersal for the same metapopulation. Monte Carlo simulations using the direct measures of gene flow as parameters further demonstrated that the observed spatial pattern of allozyme variation was congruent with a model of isolation by distance. Combining previously published estimates of pollen dispersal distances with kinship coefficients from this study, we quantified biparental inbreeding relative to either a single subpopulation or the whole metapopulation. At the level of a neighborhood, little biparental inbreeding was observed and most departure from Hardy‐Weinberg genotypic proportions was explained by self‐fertilization, whereas both selfing and biparental inbreeding contributed to nonrandom mating at the metapopulation level. Gene flow was also estimated from indirect methods based on a discontinuous population structure model. We discuss these results with respect to the effect of a patchy population structure on estimation of gene flow.

Spatial autocorrelation of allozyme and quantitative markers within a natural population of Centaurea jacea (Asteraceae)

This paper compares the fine‐scale genetic structure of quantitative traits and allozyme markers within a natural population of Centaurea jacea s.l. To that end, a spatial autocorrelation approach is developed based on pairwise correlation coefficients between individuals and using sib families. Statistical properties of the proposed statistics are investigated with numerical simulations. Our results show that most quantitative traits have a significant spatial structure for their genetic component. On average, allozyme markers and the genetic component of quantitative traits have similar patterns of spatial autocorrelation that are consistent with a neutral model of isolation by distance. We also show evidence that environmental heterogeneity generates a spatial structure for the environmental component of quantitative traits. Results are discussed in terms of mechanisms generating spatial structure and are compared with those obtained on a large geographical scale.