Bayesian inference of a historical bottleneck in a heavily exploited marine mammal

Hoffman, J .I.; Grant, Susie ORCID: https://orcid.org/0000-0001-7941-3948; Forcada, Jaume ORCID: https://orcid.org/0000-0002-2115-0150; Phillips, C. D.. 2011 Bayesian inference of a historical bottleneck in a heavily exploited marine mammal. Molecular Ecology, 20 (19). 3989-4008. 10.1111/j.1365-294X.2011.05248.x

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Abstract/Summary

Emerging Bayesian analytical approaches offer increasingly sophisticated means of reconstructing historical population dynamics from genetic data, but have been little applied to scenarios involving demographic bottlenecks. Consequently, we analysed a large mitochondrial and microsatellite dataset from the Antarctic fur seal Arctocephalus gazella, a species subjected to one of the most extreme examples of uncontrolled exploitation in history when it was reduced to the brink of extinction by the sealing industry during the late eighteenth and nineteenth centuries. Classical bottleneck tests, which exploit the fact that rare alleles are rapidly lost during demographic reduction, yielded ambiguous results. In contrast, a strong signal of recent demographic decline was detected using both Bayesian skyline plots and Approximate Bayesian Computation, the latter also allowing derivation of posterior parameter estimates that were remarkably consistent with historical observations. This was achieved using only contemporary samples, further emphasizing the potential of Bayesian approaches to address important problems in conservation and evolutionary biology.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	10.1111/j.1365-294X.2011.05248.x
Programmes:	BAS Programmes > Polar Science for Planet Earth (2009 - ) > Ecosystems
ISSN:	0962-1083
Additional Keywords:	Antarctic fur seal, Approximate Bayesian Computation (ABC), Bayesian Skyline Plot (BSP), Conservation genetics, Demographic history, Heterozygosity excess, Microsatellite, Pinniped
Date made live:	02 Mar 2012 17:43 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/17070

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