The use of approximate Bayesian computation in conservation genetics and its application in a case study on yellow-eyed penguins |
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Authors: | Joao S Lopes Sanne Boessenkool |
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Institution: | (1) School of Biological Sciences, University of Reading, Reading, RG6 6AJ, UK;(2) Department of Zoology, University of Otago, Great King Street, Dunedin, 9016, New Zealand;(3) Present address: National Centre for Biosystematics, Natural History Museum, University of Oslo, Blindern, P.O. Box 1172, 0318 Oslo, Norway |
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Abstract: | The inference of demographic parameters from genetic data has become an integral part of conservation studies. A group of
Bayesian methods developed originally in population genetics, known as approximate Bayesian computation (ABC), has been shown
to be particularly useful for the estimation of such parameters. These methods do not need to evaluate likelihood functions
analytically and can therefore be used even while assuming complex models. In this paper we describe the ABC approach and
identify specific parts of its algorithm that are being the subject of intensive studies in order to further expand its usability.
Furthermore, we discuss applications of this Bayesian algorithm in conservation studies, providing insights on the potentialities
of these tools. Finally, we present a case study in which we use a simple Isolation-Migration model to estimate a number of
demographic parameters of two populations of yellow-eyed penguins (Megadyptes antipodes) in New Zealand. The resulting estimates confirm our current understanding of M. antipodes dynamic, demographic history and provide new insights into the expansion this species has undergone during the last centuries. |
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