Quantifying gene flow from spatial genetic structure data in a metapopulation of Chamaecrista fasciculata (Leguminosae).
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.
Fenster
Charles B
CB
Department of Biology, H.J. Patterson Hall, University of Maryland, College Park, Maryland 20742, USA. cf25@umail.umd.edu
Vekemans
Xavier
X
Hardy
Olivier J
OJ
D031288:Chamaecrista / Q000235:genetics*; D003198:Computer Simulation; D005828:Genetics, Population; D005843:Geography; D007087:Illinois; D007527:Isoenzymes; D008957:Models, Genetic; D009010:Monte Carlo Method; D011157:Population Dynamics; D012098:Reproduction / Q000502:physiology
D007527:Isoenzymes