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Drivers of polar bear behavior and the possible effects of prey availability on foraging strategy

BACKGROUND: Change in behavior is one of the earliest responses to variation in habitat suitability. It is therefore important to understand the conditions that promote different behaviors, particularly in areas undergoing environmental change. Animal movement is tightly linked to behavior and remot...

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Autores principales: Togunov, Ron R., Derocher, Andrew E., Lunn, Nicholas J., Auger-Méthé, Marie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9670556/
https://www.ncbi.nlm.nih.gov/pubmed/36384775
http://dx.doi.org/10.1186/s40462-022-00351-4
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author Togunov, Ron R.
Derocher, Andrew E.
Lunn, Nicholas J.
Auger-Méthé, Marie
author_facet Togunov, Ron R.
Derocher, Andrew E.
Lunn, Nicholas J.
Auger-Méthé, Marie
author_sort Togunov, Ron R.
collection PubMed
description BACKGROUND: Change in behavior is one of the earliest responses to variation in habitat suitability. It is therefore important to understand the conditions that promote different behaviors, particularly in areas undergoing environmental change. Animal movement is tightly linked to behavior and remote tracking can be used to study ethology when direct observation is not possible. METHODS: We used movement data from 14 polar bears (Ursus maritimus) in Hudson Bay, Canada, during the foraging season (January–June), when bears inhabit the sea ice. We developed an error-tolerant method to correct for sea ice drift in tracking data. Next, we used hidden Markov models with movement and orientation relative to wind to study three behaviors (stationary, area-restricted search, and olfactory search) and examine effects of 11 covariates on behavior. RESULTS: Polar bears spent approximately 47% of their time in the stationary drift state, 29% in olfactory search, and 24% in area-restricted search. High energy behaviors occurred later in the day (around 20:00) compared to other populations. Second, olfactory search increased as the season progressed, which may reflect a shift in foraging strategy from still-hunting to active search linked to a shift in seal availability (i.e., increase in haul-outs from winter to the spring pupping and molting seasons). Last, we found spatial patterns of distribution linked to season, ice concentration, and bear age that may be tied to habitat quality and competitive exclusion. CONCLUSIONS: Our observations were generally consistent with predictions of the marginal value theorem, and differences between our findings and other populations could be explained by regional or temporal variation in resource availability. Our novel movement analyses and finding can help identify periods, regions, and conditions of critical habitat. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40462-022-00351-4.
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spelling pubmed-96705562022-11-18 Drivers of polar bear behavior and the possible effects of prey availability on foraging strategy Togunov, Ron R. Derocher, Andrew E. Lunn, Nicholas J. Auger-Méthé, Marie Mov Ecol Research BACKGROUND: Change in behavior is one of the earliest responses to variation in habitat suitability. It is therefore important to understand the conditions that promote different behaviors, particularly in areas undergoing environmental change. Animal movement is tightly linked to behavior and remote tracking can be used to study ethology when direct observation is not possible. METHODS: We used movement data from 14 polar bears (Ursus maritimus) in Hudson Bay, Canada, during the foraging season (January–June), when bears inhabit the sea ice. We developed an error-tolerant method to correct for sea ice drift in tracking data. Next, we used hidden Markov models with movement and orientation relative to wind to study three behaviors (stationary, area-restricted search, and olfactory search) and examine effects of 11 covariates on behavior. RESULTS: Polar bears spent approximately 47% of their time in the stationary drift state, 29% in olfactory search, and 24% in area-restricted search. High energy behaviors occurred later in the day (around 20:00) compared to other populations. Second, olfactory search increased as the season progressed, which may reflect a shift in foraging strategy from still-hunting to active search linked to a shift in seal availability (i.e., increase in haul-outs from winter to the spring pupping and molting seasons). Last, we found spatial patterns of distribution linked to season, ice concentration, and bear age that may be tied to habitat quality and competitive exclusion. CONCLUSIONS: Our observations were generally consistent with predictions of the marginal value theorem, and differences between our findings and other populations could be explained by regional or temporal variation in resource availability. Our novel movement analyses and finding can help identify periods, regions, and conditions of critical habitat. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40462-022-00351-4. BioMed Central 2022-11-16 /pmc/articles/PMC9670556/ /pubmed/36384775 http://dx.doi.org/10.1186/s40462-022-00351-4 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Togunov, Ron R.
Derocher, Andrew E.
Lunn, Nicholas J.
Auger-Méthé, Marie
Drivers of polar bear behavior and the possible effects of prey availability on foraging strategy
title Drivers of polar bear behavior and the possible effects of prey availability on foraging strategy
title_full Drivers of polar bear behavior and the possible effects of prey availability on foraging strategy
title_fullStr Drivers of polar bear behavior and the possible effects of prey availability on foraging strategy
title_full_unstemmed Drivers of polar bear behavior and the possible effects of prey availability on foraging strategy
title_short Drivers of polar bear behavior and the possible effects of prey availability on foraging strategy
title_sort drivers of polar bear behavior and the possible effects of prey availability on foraging strategy
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9670556/
https://www.ncbi.nlm.nih.gov/pubmed/36384775
http://dx.doi.org/10.1186/s40462-022-00351-4
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