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Energy‐based step selection analysis: Modelling the energetic drivers of animal movement and habitat use

Natasha J. Klappstein Orcid Logo, Jonathan R. Potts Orcid Logo, Théo Michelot Orcid Logo, Luca Borger Orcid Logo, Nicholas W. Pilfold Orcid Logo, Mark A. Lewis Orcid Logo, Andrew E. Derocher Orcid Logo

Journal of Animal Ecology, Volume: 91, Issue: 5, Pages: 946 - 957

Swansea University Author: Luca Borger Orcid Logo

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DOI (Published version): 10.1111/1365-2656.13687

Abstract

The energetic gains from foraging and costs of movement are expected to be key drivers of animaldecision-making, as their balance is a large determinant of body condition and survival. Thisfundamental perspective is often missing from habitat selection studies, which mainly describecorrelations betw...

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Published in: Journal of Animal Ecology
ISSN: 0021-8790 1365-2656
Published: Wiley 2022
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URI: https://cronfa.swan.ac.uk/Record/cronfa59601
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To address this gap, we present a novel parameterisation of step selection functions (SSFs), thatwe term the energy selection function (ESF). In this model, the likelihood of an animal selectinga movement step depends directly on the corresponding energetic gains and costs, and we cantherefore assess how moving animals choose habitat based on energetic considerations. The ESF retains the mathematical convenience and practicality of other SSFs and can be quicklyfitted using standard software. In this paper, we outline a workflow, from data-gathering to statis-tical analysis, and use a case study of polar bears (Ursus maritimus) to demonstrate application ofthe model. We explain how defining gains and costs at the scale of the movement step allows us to includeinformation about resource distribution, landscape resistance, and movement patterns. 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spelling 2022-05-05T16:41:30.5061675 v2 59601 2022-03-14 Energy‐based step selection analysis: Modelling the energetic drivers of animal movement and habitat use 8416d0ffc3cccdad6e6d67a455e7c4a2 0000-0001-8763-5997 Luca Borger Luca Borger true false 2022-03-14 SBI The energetic gains from foraging and costs of movement are expected to be key drivers of animaldecision-making, as their balance is a large determinant of body condition and survival. Thisfundamental perspective is often missing from habitat selection studies, which mainly describecorrelations between space use and environmental features, rather than the mechanisms behindthese correlations. To address this gap, we present a novel parameterisation of step selection functions (SSFs), thatwe term the energy selection function (ESF). In this model, the likelihood of an animal selectinga movement step depends directly on the corresponding energetic gains and costs, and we cantherefore assess how moving animals choose habitat based on energetic considerations. The ESF retains the mathematical convenience and practicality of other SSFs and can be quicklyfitted using standard software. In this paper, we outline a workflow, from data-gathering to statis-tical analysis, and use a case study of polar bears (Ursus maritimus) to demonstrate application ofthe model. We explain how defining gains and costs at the scale of the movement step allows us to includeinformation about resource distribution, landscape resistance, and movement patterns. We further demonstrate this process with a case study of polar bears, and show how the parameters can beinterpreted in terms of selection for energetic gains and against energetic costs. The ESF is a flexible framework that combines the energetic consequences of both movement andresource selection, thus incorporating a key mechanism into habitat selection analysis. Further,because it is based on familiar habitat selection models, the ESF is widely applicable to any studysystem where energetic gains and costs can be derived, and has immense potential for methodolog-ical extensions. Journal Article Journal of Animal Ecology 91 5 946 957 Wiley 0021-8790 1365-2656 animal movement, energetics, energy landscapes, habitat selection, movement ecology, optimal foraging theory, polar bear, step selection functions 1 5 2022 2022-05-01 10.1111/1365-2656.13687 http://dx.doi.org/10.1111/1365-2656.13687 COLLEGE NANME Biosciences COLLEGE CODE SBI Swansea University Natural Sciences and Engineering Research Council of Canada. Grant Numbers: 2019-04270, 261231-03, 261231-2004, 305472-08, 305472-2013 2022-05-05T16:41:30.5061675 2022-03-14T14:07:09.7487920 Faculty of Science and Engineering School of Biosciences, Geography and Physics - Biosciences Natasha J. Klappstein 0000-0001-6527-9629 1 Jonathan R. Potts 0000-0002-8564-2904 2 Théo Michelot 0000-0002-3838-4113 3 Luca Borger 0000-0001-8763-5997 4 Nicholas W. Pilfold 0000-0001-5324-5499 5 Mark A. Lewis 0000-0002-7155-7426 6 Andrew E. Derocher 0000-0002-1104-7774 7 59601__22590__af461dcea5ce4bb6ad6bf7b99ad08c02.pdf JAE-2021-00397.R2_Proof_2022-02-06.pdf 2022-03-14T14:16:16.7320331 Output 3280276 application/pdf Accepted Manuscript true 2023-03-11T00:00:00.0000000 true eng
title Energy‐based step selection analysis: Modelling the energetic drivers of animal movement and habitat use
spellingShingle Energy‐based step selection analysis: Modelling the energetic drivers of animal movement and habitat use
Luca Borger
title_short Energy‐based step selection analysis: Modelling the energetic drivers of animal movement and habitat use
title_full Energy‐based step selection analysis: Modelling the energetic drivers of animal movement and habitat use
title_fullStr Energy‐based step selection analysis: Modelling the energetic drivers of animal movement and habitat use
title_full_unstemmed Energy‐based step selection analysis: Modelling the energetic drivers of animal movement and habitat use
title_sort Energy‐based step selection analysis: Modelling the energetic drivers of animal movement and habitat use
author_id_str_mv 8416d0ffc3cccdad6e6d67a455e7c4a2
author_id_fullname_str_mv 8416d0ffc3cccdad6e6d67a455e7c4a2_***_Luca Borger
author Luca Borger
author2 Natasha J. Klappstein
Jonathan R. Potts
Théo Michelot
Luca Borger
Nicholas W. Pilfold
Mark A. Lewis
Andrew E. Derocher
format Journal article
container_title Journal of Animal Ecology
container_volume 91
container_issue 5
container_start_page 946
publishDate 2022
institution Swansea University
issn 0021-8790
1365-2656
doi_str_mv 10.1111/1365-2656.13687
publisher Wiley
college_str Faculty of Science and Engineering
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hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Biosciences, Geography and Physics - Biosciences{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Biosciences, Geography and Physics - Biosciences
url http://dx.doi.org/10.1111/1365-2656.13687
document_store_str 1
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description The energetic gains from foraging and costs of movement are expected to be key drivers of animaldecision-making, as their balance is a large determinant of body condition and survival. Thisfundamental perspective is often missing from habitat selection studies, which mainly describecorrelations between space use and environmental features, rather than the mechanisms behindthese correlations. To address this gap, we present a novel parameterisation of step selection functions (SSFs), thatwe term the energy selection function (ESF). In this model, the likelihood of an animal selectinga movement step depends directly on the corresponding energetic gains and costs, and we cantherefore assess how moving animals choose habitat based on energetic considerations. The ESF retains the mathematical convenience and practicality of other SSFs and can be quicklyfitted using standard software. In this paper, we outline a workflow, from data-gathering to statis-tical analysis, and use a case study of polar bears (Ursus maritimus) to demonstrate application ofthe model. We explain how defining gains and costs at the scale of the movement step allows us to includeinformation about resource distribution, landscape resistance, and movement patterns. We further demonstrate this process with a case study of polar bears, and show how the parameters can beinterpreted in terms of selection for energetic gains and against energetic costs. The ESF is a flexible framework that combines the energetic consequences of both movement andresource selection, thus incorporating a key mechanism into habitat selection analysis. Further,because it is based on familiar habitat selection models, the ESF is widely applicable to any studysystem where energetic gains and costs can be derived, and has immense potential for methodolog-ical extensions.
published_date 2022-05-01T04:17:02Z
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score 11.013082

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