Can we predict foraging success in a marine predator from dive patterns only? Validation with prey capture attempt data.

Predicting how climatic variations will affect marine predator populations relies on our ability to assess foraging success, but evaluating foraging success in a marine predator at sea is particularly difficult. Dive metrics are commonly available for marine mammals, diving birds and some species of...

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Autores principales: Morgane Viviant, Pascal Monestiez, Christophe Guinet
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Publicado: Public Library of Science (PLoS) 2014
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Acceso en línea:https://doaj.org/article/cab265722e454c259afb560f7f85d029
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spelling oai:doaj.org-article:cab265722e454c259afb560f7f85d0292021-11-18T08:29:28ZCan we predict foraging success in a marine predator from dive patterns only? Validation with prey capture attempt data.1932-620310.1371/journal.pone.0088503https://doaj.org/article/cab265722e454c259afb560f7f85d0292014-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/24603534/?tool=EBIhttps://doaj.org/toc/1932-6203Predicting how climatic variations will affect marine predator populations relies on our ability to assess foraging success, but evaluating foraging success in a marine predator at sea is particularly difficult. Dive metrics are commonly available for marine mammals, diving birds and some species of fish. Bottom duration or dive duration are usually used as proxies for foraging success. However, few studies have tried to validate these assumptions and identify the set of behavioral variables that best predict foraging success at a given time scale. The objective of this study was to assess if foraging success in Antarctic fur seals could be accurately predicted from dive parameters only, at different temporal scales. For this study, 11 individuals were equipped with either Hall sensors or accelerometers to record dive profiles and detect mouth-opening events, which were considered prey capture attempts. The number of prey capture attempts was best predicted by descent and ascent rates at the dive scale; bottom duration and descent rates at 30-min, 1-h, and 2-h scales; and ascent rates and maximum dive depths at the all-night scale. Model performances increased with temporal scales, but rank and sign of the factors varied according to the time scale considered, suggesting that behavioral adjustment in response to prey distribution could occur at certain scales only. The models predicted the foraging intensity of new individuals with good accuracy despite high inter-individual differences. Dive metrics that predict foraging success depend on the species and the scale considered, as verified by the literature and this study. The methodology used in our study is easy to implement, enables an assessment of model performance, and could be applied to any other marine predator.Morgane ViviantPascal MonestiezChristophe GuinetPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 9, Iss 3, p e88503 (2014)
institution DOAJ
collection DOAJ
language EN
topic Medicine
R
Science
Q
spellingShingle Medicine
R
Science
Q
Morgane Viviant
Pascal Monestiez
Christophe Guinet
Can we predict foraging success in a marine predator from dive patterns only? Validation with prey capture attempt data.
description Predicting how climatic variations will affect marine predator populations relies on our ability to assess foraging success, but evaluating foraging success in a marine predator at sea is particularly difficult. Dive metrics are commonly available for marine mammals, diving birds and some species of fish. Bottom duration or dive duration are usually used as proxies for foraging success. However, few studies have tried to validate these assumptions and identify the set of behavioral variables that best predict foraging success at a given time scale. The objective of this study was to assess if foraging success in Antarctic fur seals could be accurately predicted from dive parameters only, at different temporal scales. For this study, 11 individuals were equipped with either Hall sensors or accelerometers to record dive profiles and detect mouth-opening events, which were considered prey capture attempts. The number of prey capture attempts was best predicted by descent and ascent rates at the dive scale; bottom duration and descent rates at 30-min, 1-h, and 2-h scales; and ascent rates and maximum dive depths at the all-night scale. Model performances increased with temporal scales, but rank and sign of the factors varied according to the time scale considered, suggesting that behavioral adjustment in response to prey distribution could occur at certain scales only. The models predicted the foraging intensity of new individuals with good accuracy despite high inter-individual differences. Dive metrics that predict foraging success depend on the species and the scale considered, as verified by the literature and this study. The methodology used in our study is easy to implement, enables an assessment of model performance, and could be applied to any other marine predator.
format article
author Morgane Viviant
Pascal Monestiez
Christophe Guinet
author_facet Morgane Viviant
Pascal Monestiez
Christophe Guinet
author_sort Morgane Viviant
title Can we predict foraging success in a marine predator from dive patterns only? Validation with prey capture attempt data.
title_short Can we predict foraging success in a marine predator from dive patterns only? Validation with prey capture attempt data.
title_full Can we predict foraging success in a marine predator from dive patterns only? Validation with prey capture attempt data.
title_fullStr Can we predict foraging success in a marine predator from dive patterns only? Validation with prey capture attempt data.
title_full_unstemmed Can we predict foraging success in a marine predator from dive patterns only? Validation with prey capture attempt data.
title_sort can we predict foraging success in a marine predator from dive patterns only? validation with prey capture attempt data.
publisher Public Library of Science (PLoS)
publishDate 2014
url https://doaj.org/article/cab265722e454c259afb560f7f85d029
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AT christopheguinet canwepredictforagingsuccessinamarinepredatorfromdivepatternsonlyvalidationwithpreycaptureattemptdata
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