Predicting foraging dive outcomes in chinstrap penguins using biologging and animal-borne cameras

Direct observation of foraging behavior is not always possible, especially for marine species that hunt underwater. However, biologging and tracking devices have provided detailed information about how various species use their habitat. From these indirect observations, researchers have inferred beh...

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Published in:Behavioral Ecology
Main Authors: Manco, Fabrizio, Lang, Stephen D.J., Trathan, Philip N.
Format: Article in Journal/Newspaper
Language:unknown
Published: Oxford University Press 2022
Subjects:
Online Access:http://nora.nerc.ac.uk/id/eprint/531890/
https://academic.oup.com/beheco/advance-article/doi/10.1093/beheco/arac066/6637777
id ftnerc:oai:nora.nerc.ac.uk:531890
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spelling ftnerc:oai:nora.nerc.ac.uk:531890 2023-05-15T13:41:46+02:00 Predicting foraging dive outcomes in chinstrap penguins using biologging and animal-borne cameras Manco, Fabrizio Lang, Stephen D.J. Trathan, Philip N. 2022-09 http://nora.nerc.ac.uk/id/eprint/531890/ https://academic.oup.com/beheco/advance-article/doi/10.1093/beheco/arac066/6637777 unknown Oxford University Press Manco, Fabrizio; Lang, Stephen D.J.; Trathan, Philip N. orcid:0000-0001-6673-9930 . 2022 Predicting foraging dive outcomes in chinstrap penguins using biologging and animal-borne cameras. Behavioral Ecology, 33 (5), arac066. 989-998. https://doi.org/10.1093/beheco/arac066 <https://doi.org/10.1093/beheco/arac066> Publication - Article PeerReviewed 2022 ftnerc https://doi.org/10.1093/beheco/arac066 2023-02-04T19:52:59Z Direct observation of foraging behavior is not always possible, especially for marine species that hunt underwater. However, biologging and tracking devices have provided detailed information about how various species use their habitat. From these indirect observations, researchers have inferred behaviors to address a variety of research questions, including the definition of ecological niches. In this study, we deployed video cameras with GPS and time-depth recorders on 16 chinstrap penguins (Pygoscelis antarcticus) during the brood phase of the 2018–2019 breeding season on Signy (South Orkney Islands). More than 57 h of footage covering 770 dives were scrutinized by two observers. The outcome of each dive was classified as either no krill encounter, individual krill or krill swarm encounter and the number of prey items caught per dive was estimated. Other variables derived from the logging devices or from the environment were used to train a machine-learning algorithm to predict the outcome of each dive. Our results show that despite some limitations, the data collected from the footage was reliable. We also demonstrate that it was possible to accurately predict the outcome of each dive from dive and horizontal movement variables in a manner that has not been used for penguins previously. For example, our models show that a fast dive ascent rate and a high density of dives are good indicators of krill and especially of swarm encounter. Finally, we discuss how video footage can help build accurate habitat models to provide wider knowledge about predator behavior or prey distribution. Article in Journal/Newspaper Antarc* antarcticus South Orkney Islands Natural Environment Research Council: NERC Open Research Archive South Orkney Islands ENVELOPE(-45.500,-45.500,-60.583,-60.583) Behavioral Ecology
institution Open Polar
collection Natural Environment Research Council: NERC Open Research Archive
op_collection_id ftnerc
language unknown
description Direct observation of foraging behavior is not always possible, especially for marine species that hunt underwater. However, biologging and tracking devices have provided detailed information about how various species use their habitat. From these indirect observations, researchers have inferred behaviors to address a variety of research questions, including the definition of ecological niches. In this study, we deployed video cameras with GPS and time-depth recorders on 16 chinstrap penguins (Pygoscelis antarcticus) during the brood phase of the 2018–2019 breeding season on Signy (South Orkney Islands). More than 57 h of footage covering 770 dives were scrutinized by two observers. The outcome of each dive was classified as either no krill encounter, individual krill or krill swarm encounter and the number of prey items caught per dive was estimated. Other variables derived from the logging devices or from the environment were used to train a machine-learning algorithm to predict the outcome of each dive. Our results show that despite some limitations, the data collected from the footage was reliable. We also demonstrate that it was possible to accurately predict the outcome of each dive from dive and horizontal movement variables in a manner that has not been used for penguins previously. For example, our models show that a fast dive ascent rate and a high density of dives are good indicators of krill and especially of swarm encounter. Finally, we discuss how video footage can help build accurate habitat models to provide wider knowledge about predator behavior or prey distribution.
format Article in Journal/Newspaper
author Manco, Fabrizio
Lang, Stephen D.J.
Trathan, Philip N.
spellingShingle Manco, Fabrizio
Lang, Stephen D.J.
Trathan, Philip N.
Predicting foraging dive outcomes in chinstrap penguins using biologging and animal-borne cameras
author_facet Manco, Fabrizio
Lang, Stephen D.J.
Trathan, Philip N.
author_sort Manco, Fabrizio
title Predicting foraging dive outcomes in chinstrap penguins using biologging and animal-borne cameras
title_short Predicting foraging dive outcomes in chinstrap penguins using biologging and animal-borne cameras
title_full Predicting foraging dive outcomes in chinstrap penguins using biologging and animal-borne cameras
title_fullStr Predicting foraging dive outcomes in chinstrap penguins using biologging and animal-borne cameras
title_full_unstemmed Predicting foraging dive outcomes in chinstrap penguins using biologging and animal-borne cameras
title_sort predicting foraging dive outcomes in chinstrap penguins using biologging and animal-borne cameras
publisher Oxford University Press
publishDate 2022
url http://nora.nerc.ac.uk/id/eprint/531890/
https://academic.oup.com/beheco/advance-article/doi/10.1093/beheco/arac066/6637777
long_lat ENVELOPE(-45.500,-45.500,-60.583,-60.583)
geographic South Orkney Islands
geographic_facet South Orkney Islands
genre Antarc*
antarcticus
South Orkney Islands
genre_facet Antarc*
antarcticus
South Orkney Islands
op_relation Manco, Fabrizio; Lang, Stephen D.J.; Trathan, Philip N. orcid:0000-0001-6673-9930 . 2022 Predicting foraging dive outcomes in chinstrap penguins using biologging and animal-borne cameras. Behavioral Ecology, 33 (5), arac066. 989-998. https://doi.org/10.1093/beheco/arac066 <https://doi.org/10.1093/beheco/arac066>
op_doi https://doi.org/10.1093/beheco/arac066
container_title Behavioral Ecology
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