The utility of drones for studying polar bear behaviour in the Canadian Arctic: opportunities and recommendations
Climate-induced sea-ice loss represents the greatest threat to polar bears (Ursus maritimus Phipps, 1774), and utilizing drones to characterize behavioural responses to sea-ice loss is valuable for forecasting polar bear persistence. In this manuscript, we review previously published literature and...
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2022
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crcansciencepubl:10.1139/dsa-2021-0018 2023-12-17T10:25:27+01:00 The utility of drones for studying polar bear behaviour in the Canadian Arctic: opportunities and recommendations Jagielski, Patrick M. Barnas, Andrew F. Grant Gilchrist, H. Richardson, Evan S. Love, Oliver P. Semeniuk, Christina A.D. 2022 http://dx.doi.org/10.1139/dsa-2021-0018 https://cdnsciencepub.com/doi/full-xml/10.1139/dsa-2021-0018 https://cdnsciencepub.com/doi/pdf/10.1139/dsa-2021-0018 en eng Canadian Science Publishing http://www.nrcresearchpress.com/page/about/CorporateTextAndDataMining Drone Systems and Applications volume 10, issue 1, page 97-110 ISSN 2564-4939 journal-article 2022 crcansciencepubl https://doi.org/10.1139/dsa-2021-0018 2023-11-19T13:38:46Z Climate-induced sea-ice loss represents the greatest threat to polar bears (Ursus maritimus Phipps, 1774), and utilizing drones to characterize behavioural responses to sea-ice loss is valuable for forecasting polar bear persistence. In this manuscript, we review previously published literature and draw on our own experience of using multirotor aerial drones to study polar bear behaviour in the Canadian Arctic. Specifically, we suggest that drones can minimize human–bear conflicts by allowing users to observe bears from a safe vantage point; produce high-quality behavioural data that can be reviewed as many times as needed and shared with multiple stakeholders; and foster knowledge generation through co-production with northern communities. We posit that in some instances drones may be considered as an alternative tool for studying polar bear foraging behaviour, interspecific interactions, human–bear interactions, human safety and conflict mitigation, and den-site location at individual-level small spatial scales. Finally, we discuss flying techniques to ensure ethical operation around polar bears, regulatory requirements to consider, and recommend that future research focus on understanding polar bears’ behavioural and physiological responses to drones and the efficacy of drones as a deterrent tool for safety purposes. Article in Journal/Newspaper Arctic Sea ice Ursus maritimus Canadian Science Publishing (via Crossref) Arctic Journal of Unmanned Vehicle Systems |
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Open Polar |
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Canadian Science Publishing (via Crossref) |
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crcansciencepubl |
language |
English |
description |
Climate-induced sea-ice loss represents the greatest threat to polar bears (Ursus maritimus Phipps, 1774), and utilizing drones to characterize behavioural responses to sea-ice loss is valuable for forecasting polar bear persistence. In this manuscript, we review previously published literature and draw on our own experience of using multirotor aerial drones to study polar bear behaviour in the Canadian Arctic. Specifically, we suggest that drones can minimize human–bear conflicts by allowing users to observe bears from a safe vantage point; produce high-quality behavioural data that can be reviewed as many times as needed and shared with multiple stakeholders; and foster knowledge generation through co-production with northern communities. We posit that in some instances drones may be considered as an alternative tool for studying polar bear foraging behaviour, interspecific interactions, human–bear interactions, human safety and conflict mitigation, and den-site location at individual-level small spatial scales. Finally, we discuss flying techniques to ensure ethical operation around polar bears, regulatory requirements to consider, and recommend that future research focus on understanding polar bears’ behavioural and physiological responses to drones and the efficacy of drones as a deterrent tool for safety purposes. |
format |
Article in Journal/Newspaper |
author |
Jagielski, Patrick M. Barnas, Andrew F. Grant Gilchrist, H. Richardson, Evan S. Love, Oliver P. Semeniuk, Christina A.D. |
spellingShingle |
Jagielski, Patrick M. Barnas, Andrew F. Grant Gilchrist, H. Richardson, Evan S. Love, Oliver P. Semeniuk, Christina A.D. The utility of drones for studying polar bear behaviour in the Canadian Arctic: opportunities and recommendations |
author_facet |
Jagielski, Patrick M. Barnas, Andrew F. Grant Gilchrist, H. Richardson, Evan S. Love, Oliver P. Semeniuk, Christina A.D. |
author_sort |
Jagielski, Patrick M. |
title |
The utility of drones for studying polar bear behaviour in the Canadian Arctic: opportunities and recommendations |
title_short |
The utility of drones for studying polar bear behaviour in the Canadian Arctic: opportunities and recommendations |
title_full |
The utility of drones for studying polar bear behaviour in the Canadian Arctic: opportunities and recommendations |
title_fullStr |
The utility of drones for studying polar bear behaviour in the Canadian Arctic: opportunities and recommendations |
title_full_unstemmed |
The utility of drones for studying polar bear behaviour in the Canadian Arctic: opportunities and recommendations |
title_sort |
utility of drones for studying polar bear behaviour in the canadian arctic: opportunities and recommendations |
publisher |
Canadian Science Publishing |
publishDate |
2022 |
url |
http://dx.doi.org/10.1139/dsa-2021-0018 https://cdnsciencepub.com/doi/full-xml/10.1139/dsa-2021-0018 https://cdnsciencepub.com/doi/pdf/10.1139/dsa-2021-0018 |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic Sea ice Ursus maritimus |
genre_facet |
Arctic Sea ice Ursus maritimus |
op_source |
Drone Systems and Applications volume 10, issue 1, page 97-110 ISSN 2564-4939 |
op_rights |
http://www.nrcresearchpress.com/page/about/CorporateTextAndDataMining |
op_doi |
https://doi.org/10.1139/dsa-2021-0018 |
container_title |
Journal of Unmanned Vehicle Systems |
_version_ |
1785576925741187072 |