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Predicting animal behaviour using deep learning: GPS data alone accurately predict diving in seabirds

Abstract:

To prevent further global declines in biodiversity, identifying and understanding key habitats is crucial for successful conservation strategies. For example, globally, seabird populations are under threat and animal movement data can identify key at‐sea areas and provide valuable information on the state of marine ecosystems. To date, in order to locate these areas, studies have used global positioning system (GPS) to record position and are sometimes combined with time–depth recorder (TD...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1111/2041-210X.12926

Authors


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Role:
Author
ORCID:
0000-0002-7959-9292
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Institution:
University of Oxford
Division:
MPLS Division
Department:
Zoology
Role:
Author
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Institution:
University of Oxford
Division:
MPLS
Department:
Zoology
Oxford college:
Merton College
Role:
Author
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Publisher:
Wiley Publisher's website
Journal:
Methods in Ecology and Evolution Journal website
Volume:
9
Issue:
3
Pages:
681-692
Publication date:
2017-10-30
Acceptance date:
2017-10-13
DOI:
EISSN:
2041-210X
ISSN:
2041-2096
Source identifiers:
810054
Keywords:
Pubs id:
pubs:810054
UUID:
uuid:69d73ebb-6350-4497-9b67-eac0bfd3912a
Local pid:
pubs:810054
Deposit date:
2018-10-01

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