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Bayesian species delimitation in West African forest geckos (Hemidactylus fasciatus).

TitleBayesian species delimitation in West African forest geckos (Hemidactylus fasciatus).
Publication TypeJournal Article
Year of Publication2010
AuthorsLeaché AD, Fujita MK
JournalProceedings. Biological sciences / The Royal Society
Date Published2010 Oct 22
KeywordsAnimals, Bayes Theorem, Biodiversity, Genetic Speciation, Lizards, Markov Chains, Monte Carlo Method, population density, Population Dynamics

Genealogical data are an important source of evidence for delimiting species, yet few statistical methods are available for calculating the probabilities associated with different species delimitations. Bayesian species delimitation uses reversible-jump Markov chain Monte Carlo (rjMCMC) in conjunction with a user-specified guide tree to estimate the posterior distribution for species delimitation models containing different numbers of species. We apply Bayesian species delimitation to investigate the speciation history of forest geckos (Hemidactylus fasciatus) from tropical West Africa using five nuclear loci (and mtDNA) for 51 specimens representing 10 populations. We find that species diversity in H. fasciatus is currently underestimated, and describe three new species to reflect the most conservative estimate for the number of species in this complex. We examine the impact of the guide tree, and the prior distributions on ancestral population sizes () and root age (&tau;(0)), on the posterior probabilities for species delimitation. Mis-specification of the guide tree or the prior distribution for can result in strong support for models containing more species. We describe a new statistic for summarizing the posterior distribution of species delimitation models, called speciation probabilities, which summarize the posterior support for each speciation event on the starting guide tree.</p>

Alternate JournalProc. Biol. Sci.