CHARACTERIZING SOURCE–SINK DYNAMICS WITH GENETIC PARENTAGE ASSIGNMENTS

Authors

  • M. Zachariah Peery,

    Corresponding author
    1. Department of Environmental Science, Policy and Management, 137 Mulford Hall, University of California, Berkeley, California 94720-3114 USA
    2. Museum of Vertebrate Zoology, 3101 Valley Life Sciences Building, University of California, Berkeley, California 94720-3160 USA
    3. Moss Landing Marine Laboratories, 8272 Moss Landing Road, Moss Landing, California 95039 USA
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  • Steven R. Beissinger,

    1. Department of Environmental Science, Policy and Management, 137 Mulford Hall, University of California, Berkeley, California 94720-3114 USA
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  • Roger F. House,

    1. 12655 Fiori Lane, Sebastopol, California 95472 USA
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  • Martine Bérubé,

    1. Department of Environmental Science, Policy and Management, 137 Mulford Hall, University of California, Berkeley, California 94720-3114 USA
    2. Department of Genetics, Microbiology and Toxicology, Stockholm University, SE-106 91, Stockholm, Sweden
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  • Laurie A. Hall,

    1. Moss Landing Marine Laboratories, 8272 Moss Landing Road, Moss Landing, California 95039 USA
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  • Anna Sellas,

    1. Department of Environmental Science, Policy and Management, 137 Mulford Hall, University of California, Berkeley, California 94720-3114 USA
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  • Per J. Palsbøll

    1. Department of Environmental Science, Policy and Management, 137 Mulford Hall, University of California, Berkeley, California 94720-3114 USA
    2. Department of Genetics, Microbiology and Toxicology, Stockholm University, SE-106 91, Stockholm, Sweden
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  • Corresponding Editor: R. Greenberg.

Abstract

Source–sink dynamics have been suggested to characterize the population structure of many species, but the prevalence of source–sink systems in nature is uncertain because of inherent challenges in estimating migration rates among populations. Migration rates are often difficult to estimate directly with demographic methods, and indirect genetic methods are subject to a variety of assumptions that are difficult to meet or to apply to evolutionary timescales. Furthermore, such methods cannot be rigorously applied to high-gene-flow species. Here, we employ genetic parentage assignments in conjunction with demographic simulations to infer the level of immigration into a putative sink population. We use individual-based demographic models to estimate expected distributions of parent–offspring dyads under competing sink and closed-population models. By comparing the actual number of parent–offspring dyads (identified from multilocus genetic profiles) in a random sample of individuals taken from a population to expectations under these two contrasting demographic models, it is possible to estimate the rate of immigration and test hypotheses related to the role of immigration on population processes on an ecological timescale. The difference in the expected number of parent–offspring dyads between the two population models was greatest when immigration into the sink population was high, indicating that unlike traditional population genetic inference models, the highest degree of statistical power is achieved for the approach presented here when migration rates are high. We used the proposed genetic parentage approach to demonstrate that a threatened population of Marbled Murrelets (Brachyramphus marmotus) appears to be supplemented by a low level of immigration (∼2–6% annually) from other populations.

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