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Predictive ethoinformatics reveals the complex migratory behaviour of a pelagic seabird, the Manx Shearwater

Freeman, R; Dean, B; Kirk, H; Leonard, K; Phillips, RA; Perrins, CM; Guilford, T; (2013) Predictive ethoinformatics reveals the complex migratory behaviour of a pelagic seabird, the Manx Shearwater. Journal of the Royal Society Interface , 10 (84) , Article 20130279. 10.1098/rsif.2013.0279. Green open access

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Abstract

Understanding the behaviour of animals in the wild is fundamental to conservation efforts. Advances in bio-logging technologies have offered insights into the behaviour of animals during foraging, migration and social interaction. However, broader application of these systems has been limited by device mass, cost and longevity. Here, we use information from multiple logger types to predict individual behaviour in a highly pelagic, migratory seabird, the Manx Shearwater (Puffinus puffinus). Using behavioural states resolved from GPS tracking of foraging during the breeding season, we demonstrate that individual behaviours can be accurately predicted during multi-year migrations from low cost, lightweight, salt-water immersion devices. This reveals a complex pattern of migratory stopovers: some involving high proportions of foraging, and others of rest behaviour. We use this technique to examine three consecutive years of global migrations, revealing the prominence of foraging behaviour during migration and the importance of highly productive waters during migratory stopover.

Type: Article
Title: Predictive ethoinformatics reveals the complex migratory behaviour of a pelagic seabird, the Manx Shearwater
Location: England
Open access status: An open access version is available from UCL Discovery
DOI: 10.1098/rsif.2013.0279
Publisher version: http://dx.doi.org/10.1098/rsif.2013.0279
Language: English
Additional information: This work is licensed under the Creative Commons Attribution License, Attribution 3.0 Unported (CC BY 3.0) http://creativecommons.org/licenses/by/3.0/ which permits unrestricted use, distribution, and reproduction in any medium. However, you must attribute the work to the author (but not in any way that suggests that they endorse you or your use of the work).
Keywords: Behaviour, Bio-logging, Ethoinformatics, Foraging, Machine learning, Migration
UCL classification: UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > Div of Biosciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > Div of Biosciences > Genetics, Evolution and Environment
URI: http://discovery.ucl.ac.uk/id/eprint/1369122
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