Using dead-reckoning to track movements and map burrows of fossorial species

Redcliffe, James; Boulerice, Jesse; Namir, Itai; Wilson, Rory; McShea, William J.; Shamon, Hila

doi:10.1186/s40317-025-00408-2

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Using dead-reckoning to track movements and map burrows of fossorial species

James Redcliffe, Jesse Boulerice, Itai Namir, Rory Wilson

, William J. McShea, Hila Shamon

Animal Biotelemetry, Volume: 13, Issue: 1

Swansea University Authors: James Redcliffe, Rory Wilson

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DOI (Published version): 10.1186/s40317-025-00408-2

Abstract

BackgroundResearching the movement patterns of fossorial animals and mapping of burrow systems presents a significant challenge due to the difficulty of direct observation and the limitations of most tracking systems to collect location fixes underground. A potential solution is using archival tags...

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Published in:	Animal Biotelemetry
ISSN:	2050-3385
Published:	Springer Science and Business Media LLC 2025
Online Access:	Check full text
URI:	https://cronfa.swan.ac.uk/Record/cronfa69039

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A potential solution is using archival tags combined with dead-reckoning, a technique employed in nautical navigation to track animal movement underwater and through dense vegetation. However, this method has not yet been applied to the mapping of complex burrow systems in fossorial species. This study aims to test this approach using accelerometers and magnetometers attached to collars on black-tailed prairie dogs (Cynomys ludovicianus) The goal was to determine if 2D dead-reckoning, based on vectors derived from speed and heading data, could accurately track prairie dog movements and, by extension, map the structure of their burrows. To evaluate this method, we deployed 12 tags on wild animals and recorded acceleration and magnetometer data at 40 Hz and 16 Hz, respectively. These animals were allowed to move through artificial burrows comprised of plastic tubes of defined shape, before being released into the wild and tracked. The “tube runs” were used to validate 2D dead reckoning trajectory estimation. We compared the accuracy of five techniques for deriving speed: vectorial dynamic body acceleration (VeDBA), vectorial static body acceleration (VeSBA), step count, and constant speed.ResultsAcceleration signals reliably indicated traveling behavior. Among the methods tested, the Vectorial sum of Dynamic Body Acceleration (VeDBA) proved to be the most accurate proxy for speed, with the smallest mean error (Fig. 5). Speed coefficients for VeDBA varied between runs (0.009 to 0.042) with this variation being the result of individual differences The animals moved at speeds ranging from 0.01 to 1.42 m/s. In addition, the 2D dead-reckoning process documented all turns (100%) in our plastic tunnel system and had a mean error of 15.38 cm over all test tunnel lengths of up to 4 m. This highlighted the potential for representing animal movements and the layout of burrows in free-roaming prairie dogs. We also determined that use of acceleration metrics identified 22 of 24 times (92%) when collared animals exited their burrows but only 4 or 6 times (67%) when they entered them.ConclusionsThis work highlights the importance of dead-reckoning in studying space use by fossorial animals, essential for understanding how they interact with their environment, including vegetation and topography. Beyond environmental context, analyzing the specifics of animal movement—such as path tortuosity, speed, step lengths, and turn angles—is crucial for insights into species diffusion, foraging strategies, and vigilance.</abstract><type>Journal Article</type><journal>Animal Biotelemetry</journal><volume>13</volume><journalNumber>1</journalNumber><paginationStart/><paginationEnd/><publisher>Springer Science and Business Media LLC</publisher><placeOfPublication/><isbnPrint/><isbnElectronic/><issnPrint/><issnElectronic>2050-3385</issnElectronic><keywords>Black-tailed prairie dog; Dead-reckoning; Fossorial; Burrows</keywords><publishedDay>4</publishedDay><publishedMonth>4</publishedMonth><publishedYear>2025</publishedYear><publishedDate>2025-04-04</publishedDate><doi>10.1186/s40317-025-00408-2</doi><url/><notes/><college>COLLEGE NANME</college><department>Biosciences Geography and Physics School</department><CollegeCode>COLLEGE CODE</CollegeCode><DepartmentCode>BGPS</DepartmentCode><institution>Swansea University</institution><apcterm>Other</apcterm><funders>This research was supported by the Paul G. 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spelling	2025-04-14T12:30:24.7598718 v2 69039 2025-03-06 Using dead-reckoning to track movements and map burrows of fossorial species 4046e46611e52bf1ee798d17411df8e9 James Redcliffe James Redcliffe true false 017bc6dd155098860945dc6249c4e9bc 0000-0003-3177-0177 Rory Wilson Rory Wilson true false 2025-03-06 BGPS BackgroundResearching the movement patterns of fossorial animals and mapping of burrow systems presents a significant challenge due to the difficulty of direct observation and the limitations of most tracking systems to collect location fixes underground. A potential solution is using archival tags combined with dead-reckoning, a technique employed in nautical navigation to track animal movement underwater and through dense vegetation. However, this method has not yet been applied to the mapping of complex burrow systems in fossorial species. This study aims to test this approach using accelerometers and magnetometers attached to collars on black-tailed prairie dogs (Cynomys ludovicianus) The goal was to determine if 2D dead-reckoning, based on vectors derived from speed and heading data, could accurately track prairie dog movements and, by extension, map the structure of their burrows. To evaluate this method, we deployed 12 tags on wild animals and recorded acceleration and magnetometer data at 40 Hz and 16 Hz, respectively. These animals were allowed to move through artificial burrows comprised of plastic tubes of defined shape, before being released into the wild and tracked. The “tube runs” were used to validate 2D dead reckoning trajectory estimation. We compared the accuracy of five techniques for deriving speed: vectorial dynamic body acceleration (VeDBA), vectorial static body acceleration (VeSBA), step count, and constant speed.ResultsAcceleration signals reliably indicated traveling behavior. Among the methods tested, the Vectorial sum of Dynamic Body Acceleration (VeDBA) proved to be the most accurate proxy for speed, with the smallest mean error (Fig. 5). Speed coefficients for VeDBA varied between runs (0.009 to 0.042) with this variation being the result of individual differences The animals moved at speeds ranging from 0.01 to 1.42 m/s. In addition, the 2D dead-reckoning process documented all turns (100%) in our plastic tunnel system and had a mean error of 15.38 cm over all test tunnel lengths of up to 4 m. This highlighted the potential for representing animal movements and the layout of burrows in free-roaming prairie dogs. We also determined that use of acceleration metrics identified 22 of 24 times (92%) when collared animals exited their burrows but only 4 or 6 times (67%) when they entered them.ConclusionsThis work highlights the importance of dead-reckoning in studying space use by fossorial animals, essential for understanding how they interact with their environment, including vegetation and topography. Beyond environmental context, analyzing the specifics of animal movement—such as path tortuosity, speed, step lengths, and turn angles—is crucial for insights into species diffusion, foraging strategies, and vigilance. Journal Article Animal Biotelemetry 13 1 Springer Science and Business Media LLC 2050-3385 Black-tailed prairie dog; Dead-reckoning; Fossorial; Burrows 4 4 2025 2025-04-04 10.1186/s40317-025-00408-2 COLLEGE NANME Biosciences Geography and Physics School COLLEGE CODE BGPS Swansea University Other This research was supported by the Paul G. Allen Family Foundation under Grant number(s) 505321. 2025-04-14T12:30:24.7598718 2025-03-06T09:10:57.8446791 Faculty of Science and Engineering School of Biosciences, Geography and Physics - Biosciences James Redcliffe 1 Jesse Boulerice 2 Itai Namir 3 Rory Wilson 0000-0003-3177-0177 4 William J. McShea 5 Hila Shamon 6 69039__34027__598ee7dd8829496985fa578f9f9a7bb6.pdf 69039.VoR.pdf 2025-04-14T12:27:24.4497150 Output 3587003 application/pdf Version of Record true © The Author(s) 2025. This article is licensed under a Creative Commons Attribution 4.0 International License. true eng http://creativecommons.org/licenses/by/4.0/
title	Using dead-reckoning to track movements and map burrows of fossorial species
spellingShingle	Using dead-reckoning to track movements and map burrows of fossorial species James Redcliffe Rory Wilson
title_short	Using dead-reckoning to track movements and map burrows of fossorial species
title_full	Using dead-reckoning to track movements and map burrows of fossorial species
title_fullStr	Using dead-reckoning to track movements and map burrows of fossorial species
title_full_unstemmed	Using dead-reckoning to track movements and map burrows of fossorial species
title_sort	Using dead-reckoning to track movements and map burrows of fossorial species
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author_id_fullname_str_mv	4046e46611e52bf1ee798d17411df8e9_*_James Redcliffe 017bc6dd155098860945dc6249c4e9bc_*_Rory Wilson
author	James Redcliffe Rory Wilson
author2	James Redcliffe Jesse Boulerice Itai Namir Rory Wilson William J. McShea Hila Shamon
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description	BackgroundResearching the movement patterns of fossorial animals and mapping of burrow systems presents a significant challenge due to the difficulty of direct observation and the limitations of most tracking systems to collect location fixes underground. A potential solution is using archival tags combined with dead-reckoning, a technique employed in nautical navigation to track animal movement underwater and through dense vegetation. However, this method has not yet been applied to the mapping of complex burrow systems in fossorial species. This study aims to test this approach using accelerometers and magnetometers attached to collars on black-tailed prairie dogs (Cynomys ludovicianus) The goal was to determine if 2D dead-reckoning, based on vectors derived from speed and heading data, could accurately track prairie dog movements and, by extension, map the structure of their burrows. To evaluate this method, we deployed 12 tags on wild animals and recorded acceleration and magnetometer data at 40 Hz and 16 Hz, respectively. These animals were allowed to move through artificial burrows comprised of plastic tubes of defined shape, before being released into the wild and tracked. The “tube runs” were used to validate 2D dead reckoning trajectory estimation. We compared the accuracy of five techniques for deriving speed: vectorial dynamic body acceleration (VeDBA), vectorial static body acceleration (VeSBA), step count, and constant speed.ResultsAcceleration signals reliably indicated traveling behavior. Among the methods tested, the Vectorial sum of Dynamic Body Acceleration (VeDBA) proved to be the most accurate proxy for speed, with the smallest mean error (Fig. 5). Speed coefficients for VeDBA varied between runs (0.009 to 0.042) with this variation being the result of individual differences The animals moved at speeds ranging from 0.01 to 1.42 m/s. In addition, the 2D dead-reckoning process documented all turns (100%) in our plastic tunnel system and had a mean error of 15.38 cm over all test tunnel lengths of up to 4 m. This highlighted the potential for representing animal movements and the layout of burrows in free-roaming prairie dogs. We also determined that use of acceleration metrics identified 22 of 24 times (92%) when collared animals exited their burrows but only 4 or 6 times (67%) when they entered them.ConclusionsThis work highlights the importance of dead-reckoning in studying space use by fossorial animals, essential for understanding how they interact with their environment, including vegetation and topography. Beyond environmental context, analyzing the specifics of animal movement—such as path tortuosity, speed, step lengths, and turn angles—is crucial for insights into species diffusion, foraging strategies, and vigilance.
published_date	2025-04-04T07:34:07Z
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Using dead-reckoning to track movements and map burrows of fossorial species

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