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Reconstructing the demographic history of orang-utans using Approximate Bayesian Computation

Nater, A., Greminger, M.P., Arora, N., van Schaik, C.P., Goossens, B., Singleton, I., Verschoor, E.J., Warren, K.S. and Krützen, M. (2015) Reconstructing the demographic history of orang-utans using Approximate Bayesian Computation. Molecular Ecology, 24 (2). pp. 310-327.

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Investigating how different evolutionary forces have shaped patterns of DNA variation within and among species requires detailed knowledge of their demographic history. Orang-utans, whose distribution is currently restricted to the South-East Asian islands of Borneo (Pongo pygmaeus) and Sumatra (Pongo abelii), have likely experienced a complex demographic history, influenced by recurrent changes in climate and sea levels, volcanic activities and anthropogenic pressures. Using the most extensive sample set of wild orang-utans to date, we employed an Approximate Bayesian Computation (ABC) approach to test the fit of 12 different demographic scenarios to the observed patterns of variation in autosomal, X-chromosomal, mitochondrial and Y-chromosomal markers. In the best-fitting model, Sumatran orang-utans exhibit a deep split of populations north and south of Lake Toba, probably caused by multiple eruptions of the Toba volcano. In addition, we found signals for a strong decline in all Sumatran populations ~24 ka, probably associated with hunting by human colonizers. In contrast, Bornean orang-utans experienced a severe bottleneck ~135 ka, followed by a population expansion and substructuring starting ~82 ka, which we link to an expansion from a glacial refugium. We showed that orang-utans went through drastic changes in population size and connectedness, caused by recurrent contraction and expansion of rainforest habitat during Pleistocene glaciations and probably hunting by early humans. Our findings emphasize the fact that important aspects of the evolutionary past of species with complex demographic histories might remain obscured when applying overly simplified models.

Publication Type: Journal Article
Murdoch Affiliation: School of Veterinary and Life Sciences
Publisher: Blackwell Publishing
Copyright: © 2014 John Wiley & Sons Ltd
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