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Population Biology |
2Department of Biology, Gyeongsang National University, Jinju 660–701, Republic of Korea, 3Department of Ecology, Evolution and Organismal Biology, 353 Bessey Hall, Iowa State University, Ames, Iowa 50011 USA
Orchid seeds are unusual for being the smallest among flowering plants. These dust-like seeds are wind-borne and, thus, would seem to have the potential for long-distance dispersal (a common perception); this perception has led to a prediction of near-random spatial genetic structure within orchid populations. Mathematical models (e.g., simple ballistic model) for wind-dispersed seeds and wind-tunnel experiments, in contrast, indicate that most seeds of orchids should fall close to the maternal plant (<6 m), supporting a prediction of significant fine-scale genetic structure within populations. In reality we do not know much about seed dispersion in orchids. To determine which of these two predictions is more appropriate, Wright's F statistics and spatial autocorrelation analysis were used to examine the genetic structure within two adult populations of the terrestrial orchid Cephalanthera longibracteata (Orchidaceae) in southern Korea. In results comparable to those of other self-compatible, mixed-mating plant species, C. longibracteata populations exhibited low levels of genetic diversity (mean He = 0.036) and a significant excess of homozygosity (mean FIS = 0.330), consistent with substantial inbreeding via selfing and/or mating among close relatives in a spatially structured population. Spatial autocorrelation analysis revealed significant positive genetic correlations among plants located <10 m, with relatedness at <3 m comparable to that expected for half sibs and first cousins. This genetic structure supports the prediction that the majority of seed dispersal occurs over distances of less than 10 m and is responsible for generating substantial overlap in seed shadows within C. longibracteata populations.
Key Words: allozymes • Cephalanthera longibracteata • Orchidaceae • seed dispersal • spatial genetic structure • spatial autocorrelation analysis
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