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Development of a multisensor biologging collar and analytical techniques to describe high‐resolution spatial behavior in free‐ranging terrestrial mammals

Michael S. Painter Orcid Logo, Václav Silovský Orcid Logo, Justin Blanco, Mark Holton Orcid Logo, Monika Faltusová Orcid Logo, Rory Wilson Orcid Logo, Luca Borger Orcid Logo, Liza Psotta, Fabian Ramos‐Almodovar Orcid Logo, Luis Estrada, Lukas Landler, Pascal Malkemper, Vlastimil Hart, Miloš Ježek

Ecology and Evolution, Volume: 14, Issue: 9

Swansea University Authors: Mark Holton Orcid Logo, Rory Wilson Orcid Logo, Luca Borger Orcid Logo

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DOI (Published version): 10.1002/ece3.70264

Abstract

Biologging has proven to be a powerful approach to investigate diverse questions related to movement ecology across a range of spatiotemporal scales and increasingly relies on multidisciplinary expertise. However, the variety of animal-borne equipment, coupled with little consensus regarding analyti...

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Published in: Ecology and Evolution
ISSN: 2045-7758 2045-7758
Published: Wiley 2024
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spelling v2 67457 2024-08-24 Development of a multisensor biologging collar and analytical techniques to describe high‐resolution spatial behavior in free‐ranging terrestrial mammals 0e1d89d0cc934a740dcd0a873aed178e 0000-0001-8834-3283 Mark Holton Mark Holton true false 017bc6dd155098860945dc6249c4e9bc 0000-0003-3177-0177 Rory Wilson Rory Wilson true false 8416d0ffc3cccdad6e6d67a455e7c4a2 0000-0001-8763-5997 Luca Borger Luca Borger true false 2024-08-24 BGPS Biologging has proven to be a powerful approach to investigate diverse questions related to movement ecology across a range of spatiotemporal scales and increasingly relies on multidisciplinary expertise. However, the variety of animal-borne equipment, coupled with little consensus regarding analytical approaches to interpret large, complex data sets presents challenges and makes comparison between studies and study species difficult. Here, we present a combined hardware and analytical approach for standardizing the collection, analysis, and interpretation of multisensor biologging data. Here, we present (i) a custom-designed integrated multisensor collar (IMSC), which was field tested on 71 free-ranging wild boar (Sus scrofa) over 2 years; (ii) a machine learning behavioral classifier capable of identifying six behaviors in free-roaming boar, validated across individuals equipped with differing collar designs; and (iii) laboratory and field-based calibration and accuracy assessments of animal magnetic heading measurements derived from raw magnetometer data. The IMSC capacity and durability exceeded expectations, with a 94% collar recovery rate and a 75% cumulative data recording success rate, with a maximum logging duration of 421 days. The behavioral classifier had an overall accuracy of 85% in identifying the six behavioral classes when tested on multiple collar designs and improved to 90% when tested on data exclusively from the IMSC. Both laboratory and field tests of magnetic compass headings were in precise agreement with expectations, with overall median magnetic headings deviating from ground truth observations by 1.7° and 0°, respectively. Although multisensor equipment and sophisticated analyses are now commonplace in biologging studies, the IMSC hardware and analytical framework presented here provide a valuable tool for biologging researchers and will facilitate standardization of biologging data across studies. In addition, we highlight the potential of additional analyses available using this framework that can be adapted for use in future studies on terrestrial mammals. Journal Article Ecology and Evolution 14 9 Wiley 2045-7758 2045-7758 accelerometer, behavioral classification, biologging, dead-reckoning, GPS, machine learning,magnetic compass heading, magnetometer 23 9 2024 2024-09-23 10.1002/ece3.70264 COLLEGE NANME Biosciences Geography and Physics School COLLEGE CODE BGPS Swansea University Another institution paid the OA fee Ministerstvo Zemědělství, Grant/AwardNumber: QK1910462; EVA4.0, Grant/Award Number: CZ.02.1.01/0.0/0.0/16_019/0000803 2024-09-30T12:30:06.2381559 2024-08-24T20:56:09.4294954 Faculty of Science and Engineering School of Biosciences, Geography and Physics - Biosciences Michael S. Painter 0000-0001-9640-6387 1 Václav Silovský 0000-0001-6115-2516 2 Justin Blanco 3 Mark Holton 0000-0001-8834-3283 4 Monika Faltusová 0000-0003-1847-2877 5 Rory Wilson 0000-0003-3177-0177 6 Luca Borger 0000-0001-8763-5997 7 Liza Psotta 8 Fabian Ramos‐Almodovar 0000-0001-9094-7895 9 Luis Estrada 10 Lukas Landler 11 Pascal Malkemper 12 Vlastimil Hart 13 Miloš Ježek 14 67457__31479__939fbd8bf2d34a7d976c6d4bd28a8acc.pdf 67457.VoR.pdf 2024-09-30T12:28:48.9209901 Output 2830413 application/pdf Version of Record true © 2024 The Author(s). This is an open access article under the terms of the Creative Commons Attribution License. true eng http://creativecommons.org/licenses/by/4.0/
title Development of a multisensor biologging collar and analytical techniques to describe high‐resolution spatial behavior in free‐ranging terrestrial mammals
spellingShingle Development of a multisensor biologging collar and analytical techniques to describe high‐resolution spatial behavior in free‐ranging terrestrial mammals
Mark Holton
Rory Wilson
Luca Borger
title_short Development of a multisensor biologging collar and analytical techniques to describe high‐resolution spatial behavior in free‐ranging terrestrial mammals
title_full Development of a multisensor biologging collar and analytical techniques to describe high‐resolution spatial behavior in free‐ranging terrestrial mammals
title_fullStr Development of a multisensor biologging collar and analytical techniques to describe high‐resolution spatial behavior in free‐ranging terrestrial mammals
title_full_unstemmed Development of a multisensor biologging collar and analytical techniques to describe high‐resolution spatial behavior in free‐ranging terrestrial mammals
title_sort Development of a multisensor biologging collar and analytical techniques to describe high‐resolution spatial behavior in free‐ranging terrestrial mammals
author_id_str_mv 0e1d89d0cc934a740dcd0a873aed178e
017bc6dd155098860945dc6249c4e9bc
8416d0ffc3cccdad6e6d67a455e7c4a2
author_id_fullname_str_mv 0e1d89d0cc934a740dcd0a873aed178e_***_Mark Holton
017bc6dd155098860945dc6249c4e9bc_***_Rory Wilson
8416d0ffc3cccdad6e6d67a455e7c4a2_***_Luca Borger
author Mark Holton
Rory Wilson
Luca Borger
author2 Michael S. Painter
Václav Silovský
Justin Blanco
Mark Holton
Monika Faltusová
Rory Wilson
Luca Borger
Liza Psotta
Fabian Ramos‐Almodovar
Luis Estrada
Lukas Landler
Pascal Malkemper
Vlastimil Hart
Miloš Ježek
format Journal article
container_title Ecology and Evolution
container_volume 14
container_issue 9
publishDate 2024
institution Swansea University
issn 2045-7758
2045-7758
doi_str_mv 10.1002/ece3.70264
publisher Wiley
college_str Faculty of Science and Engineering
hierarchytype
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
document_store_str 1
active_str 0
description Biologging has proven to be a powerful approach to investigate diverse questions related to movement ecology across a range of spatiotemporal scales and increasingly relies on multidisciplinary expertise. However, the variety of animal-borne equipment, coupled with little consensus regarding analytical approaches to interpret large, complex data sets presents challenges and makes comparison between studies and study species difficult. Here, we present a combined hardware and analytical approach for standardizing the collection, analysis, and interpretation of multisensor biologging data. Here, we present (i) a custom-designed integrated multisensor collar (IMSC), which was field tested on 71 free-ranging wild boar (Sus scrofa) over 2 years; (ii) a machine learning behavioral classifier capable of identifying six behaviors in free-roaming boar, validated across individuals equipped with differing collar designs; and (iii) laboratory and field-based calibration and accuracy assessments of animal magnetic heading measurements derived from raw magnetometer data. The IMSC capacity and durability exceeded expectations, with a 94% collar recovery rate and a 75% cumulative data recording success rate, with a maximum logging duration of 421 days. The behavioral classifier had an overall accuracy of 85% in identifying the six behavioral classes when tested on multiple collar designs and improved to 90% when tested on data exclusively from the IMSC. Both laboratory and field tests of magnetic compass headings were in precise agreement with expectations, with overall median magnetic headings deviating from ground truth observations by 1.7° and 0°, respectively. Although multisensor equipment and sophisticated analyses are now commonplace in biologging studies, the IMSC hardware and analytical framework presented here provide a valuable tool for biologging researchers and will facilitate standardization of biologging data across studies. In addition, we highlight the potential of additional analyses available using this framework that can be adapted for use in future studies on terrestrial mammals.
published_date 2024-09-23T12:30:05Z
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