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Genetic structure of Mesoamerican populations of Big-leaf mahogany (Swietenia macrophylla) inferred from microsatellite analysis


Rachel Roth Novick. ¶Present address: Yale University, Department of Ecology & Evolutionary Biology, OML 165 Prospect Street, New Haven, CT 06511, USA. E-mail:


While microsatellites have been used to examine genetic structure in local populations of Neotropical trees, genetic studies based on such high-resolution markers have not been carried out for Mesoamerica as a whole. Here we assess the genetic structure of the Mesoamerican mahogany Swietenia macrophylla King (big-leaf mahogany), a Neotropical tree species recently listed as endangered in CITES which is commercially extinct through much of its native range. We used seven variable microsatellite loci to assess genetic diversity and population structure in eight naturally established mahogany populations from six Mesoamerican countries. Measures of genetic differentiation (FST and RST) indicated significant differences between most populations. Unrooted dendrograms based on genetic distances between populations provide evidence of strong phylogeographic structure in Mesoamerican mahogany. The two populations on the Pacific coasts of Costa Rica and Panama were genetically distant from all the others, and from one another. The remaining populations formed two clusters, one comprised of the northern populations of Mexico, Belize and Guatemala and the other containing the southern Atlantic populations of Nicaragua and Costa Rica. Significant correlation was found between geographical distance and all pairwise measures of genetic divergence, suggesting the importance of regional biogeography and isolation by distance in Mesoamerican mahogany. The results of this study demonstrate greater phylogeographic structure than has been found across Amazon basin S. macrophylla. Our findings suggest a relatively complex Mesoamerican biogeographic history and lead to the prediction that other Central American trees will show similar patterns of regional differentiation.