A standardisation framework for bio‐logging data to advance ecological research and conservation
Supporting Files
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2021
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Details
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Journal Title:Methods in Ecology and Evolution
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Personal Author:Sequeira, Ana M. M.
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O'Toole, Malcolm
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Keates, Theresa R.
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McDonnell, Laura H.
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Braun, Camrin D.
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Hoenner, Xavier
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Jaine, Fabrice R. A.
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Jonsen, Ian D.
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Newman, Peggy
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Pye, Jonathan
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Bograd, Steven J.
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Hays, Graeme C.
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Hazen, Elliott L.
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Holland, Melinda
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Tsontos, Vardis M.
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Blight, Clint
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Cagnacci, Francesca
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Davidson, Sarah C.
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Dettki, Holger
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Duarte, Carlos M.
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Dunn, Daniel C.
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Eguíluz, Victor M.
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Fedak, Michael
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Gleiss, Adrian C.
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Hammerschlag, Neil
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Hindell, Mark A.
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Holland, Kim
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Janekovic, Ivica
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McKinzie, Megan K.
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Muelbert, Mônica M. C.
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Pattiaratchi, Chari
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Rutz, Christian
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Sims, David W.
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Simmons, Samantha E.
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Townsend, Brendal
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Whoriskey, Frederick
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Woodward, Bill
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Costa, Daniel P.
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Heupel, Michelle R.
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McMahon, Clive R.
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Harcourt, Rob
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Weise, Michael
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NOAA Program & Office:
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Description:1. Bio- logging data obtained by tagging animals are key to addressing global conser - vation challenges. However, the many thousands of existing bio- logging datasets are not easily discoverable, universally comparable, nor readily accessible through existing repositories and across platforms, slowing down ecological research and effective management. A set of universal standards is needed to ensure discover - ability, interoperability and effective translation of bio- logging data into research and management recommendations.
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Keywords:
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Source:Methods in Ecology and Evolution, 12(6), 996-1007
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DOI:
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ISSN:2041-210X ; 2041-210X
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Format:
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Publisher:
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Document Type:
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License:
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Rights Information:CC BY-NC
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Compliance:Library
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Main Document Checksum:urn:sha256:1a777367bda7c2de2685dec1b4073e9c4272e9a3f99e3ab87949cf82c87d519a
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Download URL:
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File Type:
Supporting Files
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