Journal article
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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Bibliographic Details
- 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
Item Description
- Keywords:
- Pubs id:
-
pubs:810054
- UUID:
-
uuid:69d73ebb-6350-4497-9b67-eac0bfd3912a
- Local pid:
- pubs:810054
- Source identifiers:
-
810054
- Deposit date:
- 2018-10-01
Terms of use
- Copyright holder:
- Browning, et al
- Copyright date:
- 2017
- Notes:
-
© 2017 The Authors. Methods in Ecology and Evolution published by John Wiley and Sons Ltd on behalf of British Ecological Society.
This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
- Licence:
- CC Attribution (CC BY)
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