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Big data analyses reveal patterns and drivers of the movements of southern elephant seals
The growing number of large databases of animal tracking provides an opportunity for analyses of movement patterns at the scales of populations and even species. We used analytical approaches, developed to cope with “big data”, that require no ‘a priori’ assumptions about the behaviour of the target...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5427936/ https://www.ncbi.nlm.nih.gov/pubmed/28273915 http://dx.doi.org/10.1038/s41598-017-00165-0 |
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author | Rodríguez, Jorge P. Fernández-Gracia, Juan Thums, Michele Hindell, Mark A. Sequeira, Ana M. M. Meekan, Mark G. Costa, Daniel P. Guinet, Christophe Harcourt, Robert G. McMahon, Clive R. Muelbert, Monica Duarte, Carlos M. Eguíluz, Víctor M. |
author_facet | Rodríguez, Jorge P. Fernández-Gracia, Juan Thums, Michele Hindell, Mark A. Sequeira, Ana M. M. Meekan, Mark G. Costa, Daniel P. Guinet, Christophe Harcourt, Robert G. McMahon, Clive R. Muelbert, Monica Duarte, Carlos M. Eguíluz, Víctor M. |
author_sort | Rodríguez, Jorge P. |
collection | PubMed |
description | The growing number of large databases of animal tracking provides an opportunity for analyses of movement patterns at the scales of populations and even species. We used analytical approaches, developed to cope with “big data”, that require no ‘a priori’ assumptions about the behaviour of the target agents, to analyse a pooled tracking dataset of 272 elephant seals (Mirounga leonina) in the Southern Ocean, that was comprised of >500,000 location estimates collected over more than a decade. Our analyses showed that the displacements of these seals were described by a truncated power law distribution across several spatial and temporal scales, with a clear signature of directed movement. This pattern was evident when analysing the aggregated tracks despite a wide diversity of individual trajectories. We also identified marine provinces that described the migratory and foraging habitats of these seals. Our analysis provides evidence for the presence of intrinsic drivers of movement, such as memory, that cannot be detected using common models of movement behaviour. These results highlight the potential for “big data” techniques to provide new insights into movement behaviour when applied to large datasets of animal tracking. |
format | Online Article Text |
id | pubmed-5427936 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-54279362017-05-12 Big data analyses reveal patterns and drivers of the movements of southern elephant seals Rodríguez, Jorge P. Fernández-Gracia, Juan Thums, Michele Hindell, Mark A. Sequeira, Ana M. M. Meekan, Mark G. Costa, Daniel P. Guinet, Christophe Harcourt, Robert G. McMahon, Clive R. Muelbert, Monica Duarte, Carlos M. Eguíluz, Víctor M. Sci Rep Article The growing number of large databases of animal tracking provides an opportunity for analyses of movement patterns at the scales of populations and even species. We used analytical approaches, developed to cope with “big data”, that require no ‘a priori’ assumptions about the behaviour of the target agents, to analyse a pooled tracking dataset of 272 elephant seals (Mirounga leonina) in the Southern Ocean, that was comprised of >500,000 location estimates collected over more than a decade. Our analyses showed that the displacements of these seals were described by a truncated power law distribution across several spatial and temporal scales, with a clear signature of directed movement. This pattern was evident when analysing the aggregated tracks despite a wide diversity of individual trajectories. We also identified marine provinces that described the migratory and foraging habitats of these seals. Our analysis provides evidence for the presence of intrinsic drivers of movement, such as memory, that cannot be detected using common models of movement behaviour. These results highlight the potential for “big data” techniques to provide new insights into movement behaviour when applied to large datasets of animal tracking. Nature Publishing Group UK 2017-03-08 /pmc/articles/PMC5427936/ /pubmed/28273915 http://dx.doi.org/10.1038/s41598-017-00165-0 Text en © The Author(s) 2017 This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Article Rodríguez, Jorge P. Fernández-Gracia, Juan Thums, Michele Hindell, Mark A. Sequeira, Ana M. M. Meekan, Mark G. Costa, Daniel P. Guinet, Christophe Harcourt, Robert G. McMahon, Clive R. Muelbert, Monica Duarte, Carlos M. Eguíluz, Víctor M. Big data analyses reveal patterns and drivers of the movements of southern elephant seals |
title | Big data analyses reveal patterns and drivers of the movements of southern elephant seals |
title_full | Big data analyses reveal patterns and drivers of the movements of southern elephant seals |
title_fullStr | Big data analyses reveal patterns and drivers of the movements of southern elephant seals |
title_full_unstemmed | Big data analyses reveal patterns and drivers of the movements of southern elephant seals |
title_short | Big data analyses reveal patterns and drivers of the movements of southern elephant seals |
title_sort | big data analyses reveal patterns and drivers of the movements of southern elephant seals |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5427936/ https://www.ncbi.nlm.nih.gov/pubmed/28273915 http://dx.doi.org/10.1038/s41598-017-00165-0 |
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