Ex situ population management in the absence of pedigree information

Authors

  • M. A. RUSSELLO,

    Corresponding author
    1. Department of Ecology, Evolution and Environmental Biology, Columbia University, New York,
    2. Wildlife Conservation Society, Science Resource Center, Bronx,
    3. American Museum of Natural History, Molecular Systematics Laboratory, New York, NY, USA
      M. Russello. Department of Ecology and Evolutionary Biology, Yale University, PO Box 208105, New Haven, CT 06520–8105, USA. Fax: (203) 432 7394; E-mail: michael.russello@yale.edu
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  • G. AMATO

    1. Department of Ecology, Evolution and Environmental Biology, Columbia University, New York,
    2. Wildlife Conservation Society, Science Resource Center, Bronx,
    3. American Museum of Natural History, Molecular Systematics Laboratory, New York, NY, USA
    Search for more papers by this author

M. Russello. Department of Ecology and Evolutionary Biology, Yale University, PO Box 208105, New Haven, CT 06520–8105, USA. Fax: (203) 432 7394; E-mail: michael.russello@yale.edu

Abstract

For captive breeding to play a significant role in conservation, ex situ populations must be scientifically managed to meet objective goals for retaining representative genetic variation. Imperfect genealogical information requires fundamental assumptions to be made that may bias downstream measures of genetic importance, upon which management decisions are based. The impacts of such assumptions are most pronounced within breeding programmes characterized by a high proportion of individuals of unknown ancestry, as exemplified by the large captive population of the St Vincent parrot (Amazona guildingii). The degree to which microsatellite-based estimates of relatedness may improve upon the assumptions of conventional pedigree-based management was investigated using genotypic data collected at eight microsatellite loci and two marker-based relatedness estimators. The measure, rxyLR, was found to explain the highest amount of variation in true relatedness. Integration of pairwise estimates of founder relatedness with studbook data transformed current understanding of the relatedness structure of the A. guildingii population from two subgroups characterized by a high and low degree of relatedness, respectively, to a situation where all 72 individuals are prioritized for breeding according to their estimated mean kinships. Furthermore, the discovery of opposing, directional bias exhibited by rxyLR and rxyQG in assigning dyads to a given relationship category suggests that an approach that utilizes a combination of pairwise relatedness estimators may provide the most genetic information for balancing the dual considerations of maximizing gene diversity and minimizing inbreeding in developing breeding recommendations.

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