KnightBradleyClarkEtAl2018

Référence

Knight, S.M., Bradley, D.W., Clark, R.G., Gow, E.A., Belisle, M., Berzins, L.L., Blake, T., Bridge, E.S., Burke, L., Dawson, R.D., Dunn, P.O., Garant, D., Holroyd, G.L., Hussell, D.J.T., Lansdorp, O., Laughlin, A.J., Leonard, M.L., Pelletier, F., Shutler, D., Siefferman, L., Taylor, C.M., Trefry, H.E., Vleck, C.M., Vleck, D., Winkler, D.W., Whittingham, L.A. and Norris, D.R. (2018) Constructing and evaluating a continent-wide migratory songbird network across the annual cycle. Ecological Monographs, 88(3):445-460. (Scopus )

Résumé

Determining how migratory animals are spatially connected between breeding and non-breeding periods is essential for predicting the effects of environmental change and for developing optimal conservation strategies. Yet, despite recent advances in tracking technology, we lack comprehensive information on the spatial structure of migratory networks across a species’ range, particularly for small-bodied, long-distance migratory animals. We constructed a migratory network for a songbird and used network-based metrics to characterize the spatial structure and prioritize regions for conservation. The network was constructed using year-round movements derived from 133 archival light-level geolocators attached to Tree Swallows (Tachycineta bicolor) originating from 12 breeding sites across their North American breeding range. From these breeding sites, we identified 10 autumn stopover nodes (regions) in North America, 13 non-breeding nodes located around the Gulf of Mexico, Mexico, Florida, and the Caribbean, and 136 unique edges (migratory routes) connecting nodes. We found strong migratory connectivity between breeding and autumn stopover sites and moderate migratory connectivity between the breeding and non-breeding sites. We identified three distinct “communities” of nodes that corresponded to western, central, and eastern North American flyways. Several regions were important for maintaining network connectivity, with South Florida and Louisiana as the top ranked non-breeding nodes and the Midwest as the top ranked stopover node. We show that migratory songbird networks can have both a high degree of mixing between seasons yet still show regionally distinct migratory flyways. Such information will be crucial for accurately predicting factors that limit and regulate migratory songbirds throughout the annual cycle. Our study highlights how network-based metrics can be valuable for identifying overall network structure and prioritizing specific regions within a network for conserving a wide variety of migratory animals. © 2018 by the Ecological Society of America

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@ARTICLE { KnightBradleyClarkEtAl2018,
    AUTHOR = { Knight, S.M. and Bradley, D.W. and Clark, R.G. and Gow, E.A. and Belisle, M. and Berzins, L.L. and Blake, T. and Bridge, E.S. and Burke, L. and Dawson, R.D. and Dunn, P.O. and Garant, D. and Holroyd, G.L. and Hussell, D.J.T. and Lansdorp, O. and Laughlin, A.J. and Leonard, M.L. and Pelletier, F. and Shutler, D. and Siefferman, L. and Taylor, C.M. and Trefry, H.E. and Vleck, C.M. and Vleck, D. and Winkler, D.W. and Whittingham, L.A. and Norris, D.R. },
    TITLE = { Constructing and evaluating a continent-wide migratory songbird network across the annual cycle },
    JOURNAL = { Ecological Monographs },
    YEAR = { 2018 },
    VOLUME = { 88 },
    NUMBER = { 3 },
    PAGES = { 445-460 },
    NOTE = { cited By 1 },
    ABSTRACT = { Determining how migratory animals are spatially connected between breeding and non-breeding periods is essential for predicting the effects of environmental change and for developing optimal conservation strategies. Yet, despite recent advances in tracking technology, we lack comprehensive information on the spatial structure of migratory networks across a species’ range, particularly for small-bodied, long-distance migratory animals. We constructed a migratory network for a songbird and used network-based metrics to characterize the spatial structure and prioritize regions for conservation. The network was constructed using year-round movements derived from 133 archival light-level geolocators attached to Tree Swallows (Tachycineta bicolor) originating from 12 breeding sites across their North American breeding range. From these breeding sites, we identified 10 autumn stopover nodes (regions) in North America, 13 non-breeding nodes located around the Gulf of Mexico, Mexico, Florida, and the Caribbean, and 136 unique edges (migratory routes) connecting nodes. We found strong migratory connectivity between breeding and autumn stopover sites and moderate migratory connectivity between the breeding and non-breeding sites. We identified three distinct “communities” of nodes that corresponded to western, central, and eastern North American flyways. Several regions were important for maintaining network connectivity, with South Florida and Louisiana as the top ranked non-breeding nodes and the Midwest as the top ranked stopover node. We show that migratory songbird networks can have both a high degree of mixing between seasons yet still show regionally distinct migratory flyways. Such information will be crucial for accurately predicting factors that limit and regulate migratory songbirds throughout the annual cycle. Our study highlights how network-based metrics can be valuable for identifying overall network structure and prioritizing specific regions within a network for conserving a wide variety of migratory animals. © 2018 by the Ecological Society of America },
    AFFILIATION = { Department of Integrative Biology, University of Guelph, Guelph, ON N1G 2W1, Canada; Bird Studies Canada, Delta, BC V4K 3N2, Canada; Environment and Climate Change Canada, Saskatoon, SK S7N 0X4, Canada; Département de Biologie, Université de Sherbrooke, Sherbrooke, QC J1K 2R1, Canada; Ecosystem Science and Management Program, University of Northern British Columbia, Prince George, BC V2N 4Z9, Canada; Alaska Songbird Institute, Fairbanks, AK 99708, United States; Oklahoma Biological Survey, University of Oklahoma, Norman, OK 73019, United States; Department of Biology, Dalhousie University, Halifax, NS B3H 4R2, Canada; Behavioral and Molecular Ecology Group, Department of Biological Sciences, University of Wisconsin, Milwaukee, WI 53201, United States; Beaverhill Bird Observatory, Edmonton, AB T5J 2N5, Canada; Ontario Ministry of Natural Resources, Peterborough, ON K9J 7BS, Canada; Department of Biological Sciences, Simon Fraser University, Burnaby, BC V5A 1S6, Canada; Department of Environmental Studies, UNC Asheville, Asheville, NC 28804, United States; Department of Biology, Acadia University, Wolfville, NS B4P 2R6, Canada; Biology Department, Appalachian State University, Boone, NC 28608, United States; Department of Ecology and Evolutionary Biology, Tulane University, New Orleans, LA 70118, United States; Department of Ecology, Evolution and Organismal Biology, Iowa State University, Ames, IA 50011-1020, United States; Department of Ecology and Evolutionary Biology, Museum of Vertebrates, Cornell University, Ithaca, NY 14853, United States; Lab of Ornithology, Cornell University, Ithaca, NY 14853, United States },
    AUTHOR_KEYWORDS = { flyway; geolocator; migration; migratory connectivity; network theory; Tree Swallow },
    DOCUMENT_TYPE = { Article },
    DOI = { 10.1002/ecm.1298 },
    SOURCE = { Scopus },
    URL = { https://www.scopus.com/inward/record.uri?eid=2-s2.0-85046164058&doi=10.1002%2fecm.1298&partnerID=40&md5=07ca7585433d890310a27aa5245451aa },
}

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