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Inferring recent historic abundance from current genetic diversity

Authors

  • Per J. Palsbøll,

    Corresponding author
    1. Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, USA
    • Marine Evolution and Conservation, Centre of Evolutionary and Ecological Studies, University of Groningen, Groningen, The Netherlands
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  • M. Zachariah Peery,

    1. Department of Forest and Wildlife Ecology, University of Wisconsin-Madison, Madison, WI, USA
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  • Morten T. Olsen,

    1. Department of Genetics, Microbiology and Toxicology, Stockholm University, Stockholm, Sweden
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  • Steven R. Beissinger,

    1. Department of Environmental Science, Policy and Management, University of California Berkeley, Berkeley, CA, USA
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  • Martine Bérubé

    1. Marine Evolution and Conservation, Centre of Evolutionary and Ecological Studies, University of Groningen, Groningen, The Netherlands
    2. Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, USA
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Correspondence: Per J. Palsbøll, Fax: +31 (0)50 363 9620; E-mail: p.j.palsboll@rug.nl

Abstract

Recent historic abundance is an elusive parameter of great importance for conserving endangered species and understanding the pre-anthropogenic state of the biosphere. The number of studies that have used population genetic theory to estimate recent historic abundance from contemporary levels of genetic diversity has grown rapidly over the last two decades. Such assessments often yield unexpectedly large estimates of historic abundance. We review the underlying theory and common practices of estimating recent historic abundance from contemporary genetic diversity, and critically evaluate the potential issues at various estimation steps. A general issue of mismatched spatio-temporal scales between the estimation itself and the objective of the estimation emerged from our assessment; genetic diversity–based estimates of recent historic abundance represent long-term averages, whereas the objective typically is an estimate of recent abundance for a specific population. Currently, the most promising approach to estimate the difference between recent historic and contemporary abundance requires that genetic data be collected from samples of similar spatial and temporal duration. Novel genome-enabled inference methods may be able to utilize additional information of dense genome-wide distributions of markers, such as of identity-by-descent tracts, to infer recent historic abundance from contemporary samples only.

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