Finnegan2012415

Référence

Finnegan, L.A., Wilson, P.J., Price, G.N., Lowe, S.J., Patterson, B.R., Fortin, M.-J., Murray, D.L. (2012) The complimentary role of genetic and ecological data in understanding population structure: A case study using moose (Alces alces). European Journal of Wildlife Research, 58(2):415-423. (Scopus )

Résumé

Landscape features can influence animal movements and gene flow, so rigorous analysis of population structure should include both levels of analysis. We conducted individual-based landscape genetic analysis, using data from eight microsatellite loci, on adult female moose (Alces alces; n = 92) from two areas in southern Ontario, and also monitored movements of a subsample of animals (n = 38) to gauge complementarity of the data sources (genetic and telemetry data) in understanding patterns of population structure. Genetic data indicated that female moose constituted a single panmictic population encompassing both areas, with no evidence of isolation by Euclidean (Mantel test p < 0.38) or least-cost (Mantel test p < 0.19) distances, even when such distances were calculated from costs extracted from resource selection functions of the radio-collared individuals. In contrast, throughout the 2.5-year study radio-telemetry data failed to reveal large-scale movement of female moose. In fact, although moose tended to occupy home ranges in a wide range of sizes, their locations were largely fixed at a larger spatial scale encompassing both study areas. This finding implies that radio-telemetry data alone would not have revealed the extent of connectivity between moose populations, whereas least-cost genetic measures in the absence of telemetry data would not have shown the localised movements of adult females. Our contrasting results highlight the importance of multiple sources of information when assessing population connectivity of large mammals. © 2011 Springer-Verlag.

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@ARTICLE { Finnegan2012415,
    AUTHOR = { Finnegan, L.A. and Wilson, P.J. and Price, G.N. and Lowe, S.J. and Patterson, B.R. and Fortin, M.-J. and Murray, D.L. },
    TITLE = { The complimentary role of genetic and ecological data in understanding population structure: A case study using moose (Alces alces) },
    JOURNAL = { European Journal of Wildlife Research },
    YEAR = { 2012 },
    VOLUME = { 58 },
    NUMBER = { 2 },
    PAGES = { 415-423 },
    NOTE = { cited By 15 },
    ABSTRACT = { Landscape features can influence animal movements and gene flow, so rigorous analysis of population structure should include both levels of analysis. We conducted individual-based landscape genetic analysis, using data from eight microsatellite loci, on adult female moose (Alces alces; n = 92) from two areas in southern Ontario, and also monitored movements of a subsample of animals (n = 38) to gauge complementarity of the data sources (genetic and telemetry data) in understanding patterns of population structure. Genetic data indicated that female moose constituted a single panmictic population encompassing both areas, with no evidence of isolation by Euclidean (Mantel test p < 0.38) or least-cost (Mantel test p < 0.19) distances, even when such distances were calculated from costs extracted from resource selection functions of the radio-collared individuals. In contrast, throughout the 2.5-year study radio-telemetry data failed to reveal large-scale movement of female moose. In fact, although moose tended to occupy home ranges in a wide range of sizes, their locations were largely fixed at a larger spatial scale encompassing both study areas. This finding implies that radio-telemetry data alone would not have revealed the extent of connectivity between moose populations, whereas least-cost genetic measures in the absence of telemetry data would not have shown the localised movements of adult females. Our contrasting results highlight the importance of multiple sources of information when assessing population connectivity of large mammals. © 2011 Springer-Verlag. },
    AFFILIATION = { Natural Resources DNA Profiling and Forensic Centre, Trent University, Peterborough, ON, Canada; Environmental and Life Sciences Graduate Program, Trent University, Peterborough, ON, Canada; Wildlife Research and Development Section, Ontario Ministry of Natural Resources, Trent University, Peterborough, ON, Canada; Department of Ecology and Evolutionary Biology, University of Toronto, Toronto, ON, Canada; Department of Biology, Trent University, Peterborough, ON, Canada },
    AUTHOR_KEYWORDS = { Barriers to gene flow; Dispersal; Landscape genetics; Moose; Resource utilisation },
    DOCUMENT_TYPE = { Article },
    DOI = { 10.1007/s10344-011-0590-2 },
    SOURCE = { Scopus },
    URL = { https://www.scopus.com/inward/record.uri?eid=2-s2.0-84858708726&doi=10.1007%2fs10344-011-0590-2&partnerID=40&md5=e290203b7c6848dcb8e4939190b3739f },
}

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