Big data analyses reveal patterns and drivers of the movements of southern elephant seals
International audience The growing number of large databases of animal tracking provides an opportunity for analyses ofmovement 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 be...
Published in: | Scientific Reports |
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Main Authors: | , , , , , , , , , , , , |
Other Authors: | , , , , , , , , , , , , , , , , , , , |
Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
HAL CCSD
2017
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Subjects: | |
Online Access: | https://hal.archives-ouvertes.fr/hal-01500421 https://doi.org/10.1038/s41598-017-00165-0 |
Summary: | International audience The growing number of large databases of animal tracking provides an opportunity for analyses ofmovement 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 thetarget agents, to analyse a pooled tracking dataset of 272 elephant seals (Mirounga leonina) in theSouthern Ocean, that was comprised of >500,000 location estimates collected over more than adecade. Our analyses showed that the displacements of these seals were described by a truncatedpower law distribution across several spatial and temporal scales, with a clear signature of directedmovement. This pattern was evident when analysing the aggregated tracks despite a wide diversity ofindividual trajectories. We also identified marine provinces that described the migratory and foraginghabitats 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 resultshighlight the potential for “big data” techniques to provide new insights into movement behaviourwhen applied to large datasets of animal tracking. |
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