Big data analyses reveal patterns and drivers of the movements of southern elephant seals

• Published in: Scientific Reports
• Main Authors: Rodríguez-García, Jorge Pablo, Fernández-Gracia, Juan, Thums, Michael, Hindell, Mark A., Sequeira, Ana M. M., Meekan, Mark G., Costa, Daniel P., Guinet, Christophe, Harcourt, Robert G., McMahon, Clive R., Muelbert, Monica M. C., Duarte, Carlos M., Eguíluz, Víctor M.
• Other Authors: Indian Ocean Marine Research Centre, Australian Research Council, Ministerio de Educación, Cultura y Deporte (España), National Institutes of Health (US), Conselho Nacional de Desenvolvimento Científico e Tecnológico (Brasil), European Commission, King Abdullah University of Science and Technology
• Format: Article in Journal/Newspaper
• Language: English
• Published: Springer Nature 2017
• Subjects: Southern Ocean; Elephant Seals; Mirounga leonina; Southern Elephant Seals
• Online Access: http://hdl.handle.net/10261/172915; https://doi.org/10.1038/s41598-017-00165-0; https://doi.org/10.13039/501100004052; https://doi.org/10.13039/501100000780; https://doi.org/10.13039/501100003593; https://doi.org/10.13039/100000002; https://doi.org/10.13039/501100003176; https://doi.org/10.13039/501100000923

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. A.M.M.S. was supported by an IOMRC (UWA/AIMS/CSIRO) collaborative Postdoctoral Fellowship (Australia) and by ARC grant DE170100841; J.P.R. acknowledges support by the FPU program of MECD (Spain); J.F.G. is supported by NIH grant U54GM088558-06 (Lipsitch); M.M. acknowledges support from CNPq; V.M.E. acknowledges support from SPASIMM (FIS2016-80067-P (AEI/FEDER, UE)). Research reported in this publication was supported by research funding from King Abdullah University of Science and Technology (KAUST). Peer reviewed