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Dead-reckoning animal movements in R: a reappraisal using Gundog.Tracks

Richard M. Gunner, Mark Holton Orcid Logo, Mike D. Scantlebury, O. Louis van Schalkwyk, Holly M. English, Hannah J. Williams, Phil Hopkins, Flavio Quintana, Agustina Gómez-Laich, Luca Borger Orcid Logo, James Redcliffe, Ken Yoda, Takashi Yamamoto, Sam Ferreira, Danny Govender, Pauli Viljoen, Angela Bruns, Stephen H. Bell, Nikki J. Marks, Nigel C. Bennett, Mariano H. Tonini, Carlos M. Duarte, Martin C. van Rooyen, Mads F. Bertelsen, Craig J. Tambling, Rory Wilson Orcid Logo

Animal Biotelemetry, Volume: 9, Issue: 1

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

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Abstract

BackgroundFine-scale data on animal position are increasingly enabling us to understand the details of animal movement ecology and dead-reckoning, a technique integrating motion sensor-derived information on heading and speed, can be used to reconstruct fine-scale movement paths at sub-second resolu...

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Published in: Animal Biotelemetry
ISSN: 2050-3385
Published: Springer Science and Business Media LLC 2021
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fullrecord <?xml version="1.0"?><rfc1807><datestamp>2022-07-07T13:17:58.1210504</datestamp><bib-version>v2</bib-version><id>57810</id><entry>2021-09-08</entry><title>Dead-reckoning animal movements in R: a reappraisal using Gundog.Tracks</title><swanseaauthors><author><sid>0e1d89d0cc934a740dcd0a873aed178e</sid><ORCID>0000-0001-8834-3283</ORCID><firstname>Mark</firstname><surname>Holton</surname><name>Mark Holton</name><active>true</active><ethesisStudent>false</ethesisStudent></author><author><sid>8416d0ffc3cccdad6e6d67a455e7c4a2</sid><ORCID>0000-0001-8763-5997</ORCID><firstname>Luca</firstname><surname>Borger</surname><name>Luca Borger</name><active>true</active><ethesisStudent>false</ethesisStudent></author><author><sid>4046e46611e52bf1ee798d17411df8e9</sid><firstname>James</firstname><surname>Redcliffe</surname><name>James Redcliffe</name><active>true</active><ethesisStudent>false</ethesisStudent></author><author><sid>017bc6dd155098860945dc6249c4e9bc</sid><ORCID>0000-0003-3177-0177</ORCID><firstname>Rory</firstname><surname>Wilson</surname><name>Rory Wilson</name><active>true</active><ethesisStudent>false</ethesisStudent></author></swanseaauthors><date>2021-09-08</date><deptcode>SBI</deptcode><abstract>BackgroundFine-scale data on animal position are increasingly enabling us to understand the details of animal movement ecology and dead-reckoning, a technique integrating motion sensor-derived information on heading and speed, can be used to reconstruct fine-scale movement paths at sub-second resolution, irrespective of the environment. On its own however, the dead-reckoning process is prone to cumulative errors, so that position estimates quickly become uncoupled from true location. Periodic ground-truthing with aligned location data (e.g., from global positioning technology) can correct for this drift between Verified Positions (VPs). We present step-by-step instructions for implementing Verified Position Correction (VPC) dead-reckoning in R using the tilt-compensated compass method, accompanied by the mathematical protocols underlying the code and improvements and extensions of this technique to reduce the trade-off between VPC rate and dead-reckoning accuracy. These protocols are all built into a user-friendly, fully annotated VPC dead-reckoning R function; Gundog.Tracks, with multi-functionality to reconstruct animal movement paths across terrestrial, aquatic, and aerial systems, provided within the Additional file 4 as well as online (GitHub).ResultsThe Gundog.Tracks function is demonstrated on three contrasting model species (the African lion Panthera leo, the Magellanic penguin Spheniscus magellanicus, and the Imperial cormorant Leucocarbo atriceps) moving on land, in water and in air. We show the effect of uncorrected errors in speed estimations, heading inaccuracies and infrequent VPC rate and demonstrate how these issues can be addressed.ConclusionsThe function provided will allow anyone familiar with R to dead-reckon animal tracks readily and accurately, as the key complex issues are dealt with by Gundog.Tracks. This will help the community to consider and implement a valuable, but often overlooked method of reconstructing high-resolution animal movement paths across diverse species and systems without requiring a bespoke application.</abstract><type>Journal Article</type><journal>Animal Biotelemetry</journal><volume>9</volume><journalNumber>1</journalNumber><paginationStart/><paginationEnd/><publisher>Springer Science and Business Media LLC</publisher><placeOfPublication/><isbnPrint/><isbnElectronic/><issnPrint/><issnElectronic>2050-3385</issnElectronic><keywords>Animal behaviour; Animal movement; Global Positioning System; R (programming language); Track integration; Tri-axial accelerometers; Tri-axial magnetometers</keywords><publishedDay>1</publishedDay><publishedMonth>7</publishedMonth><publishedYear>2021</publishedYear><publishedDate>2021-07-01</publishedDate><doi>10.1186/s40317-021-00245-z</doi><url/><notes/><college>COLLEGE NANME</college><department>Biosciences</department><CollegeCode>COLLEGE CODE</CollegeCode><DepartmentCode>SBI</DepartmentCode><institution>Swansea University</institution><apcterm>Another institution paid the OA fee</apcterm><funders>This research contributes to the CAASE project funded by King Abdullah University of Science and Technology (KAUST) under the KAUST Sensor Initiative. Fieldwork in the Kgalagadi Transfrontier Park was supported in part by a Department for Economy Global Challenges Research Fund grant to MS. Fieldwork within the Chubut Province was supported in part by the National Agency for Scientifc and Technological Promotion of Argentina (PICT 20171996 and PICT 2018-1480), and the Grants-in-Aid for Scientifc Research from the Japan Society for the Promotion of Science (16K18617).</funders><lastEdited>2022-07-07T13:17:58.1210504</lastEdited><Created>2021-09-08T00:12:02.7667639</Created><path><level id="1">Faculty of Science and Engineering</level><level id="2">School of Biosciences, Geography and Physics - Biosciences</level></path><authors><author><firstname>Richard M.</firstname><surname>Gunner</surname><order>1</order></author><author><firstname>Mark</firstname><surname>Holton</surname><orcid>0000-0001-8834-3283</orcid><order>2</order></author><author><firstname>Mike D.</firstname><surname>Scantlebury</surname><order>3</order></author><author><firstname>O. Louis van</firstname><surname>Schalkwyk</surname><order>4</order></author><author><firstname>Holly M.</firstname><surname>English</surname><order>5</order></author><author><firstname>Hannah J.</firstname><surname>Williams</surname><order>6</order></author><author><firstname>Phil</firstname><surname>Hopkins</surname><order>7</order></author><author><firstname>Flavio</firstname><surname>Quintana</surname><order>8</order></author><author><firstname>Agustina</firstname><surname>G&#xF3;mez-Laich</surname><order>9</order></author><author><firstname>Luca</firstname><surname>Borger</surname><orcid>0000-0001-8763-5997</orcid><order>10</order></author><author><firstname>James</firstname><surname>Redcliffe</surname><order>11</order></author><author><firstname>Ken</firstname><surname>Yoda</surname><order>12</order></author><author><firstname>Takashi</firstname><surname>Yamamoto</surname><order>13</order></author><author><firstname>Sam</firstname><surname>Ferreira</surname><order>14</order></author><author><firstname>Danny</firstname><surname>Govender</surname><order>15</order></author><author><firstname>Pauli</firstname><surname>Viljoen</surname><order>16</order></author><author><firstname>Angela</firstname><surname>Bruns</surname><order>17</order></author><author><firstname>Stephen H.</firstname><surname>Bell</surname><order>18</order></author><author><firstname>Nikki J.</firstname><surname>Marks</surname><order>19</order></author><author><firstname>Nigel C.</firstname><surname>Bennett</surname><order>20</order></author><author><firstname>Mariano H.</firstname><surname>Tonini</surname><order>21</order></author><author><firstname>Carlos M.</firstname><surname>Duarte</surname><order>22</order></author><author><firstname>Martin C. van</firstname><surname>Rooyen</surname><order>23</order></author><author><firstname>Mads F.</firstname><surname>Bertelsen</surname><order>24</order></author><author><firstname>Craig J.</firstname><surname>Tambling</surname><order>25</order></author><author><firstname>Rory</firstname><surname>Wilson</surname><orcid>0000-0003-3177-0177</orcid><order>26</order></author></authors><documents><document><filename>57810__21088__df8c52746b7e4139a0e1304148944b5d.pdf</filename><originalFilename>57810.pdf</originalFilename><uploaded>2021-10-04T16:49:55.8695601</uploaded><type>Output</type><contentLength>5451625</contentLength><contentType>application/pdf</contentType><version>Version of Record</version><cronfaStatus>true</cronfaStatus><documentNotes>&#xA9; The Author(s) 2021. 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spelling 2022-07-07T13:17:58.1210504 v2 57810 2021-09-08 Dead-reckoning animal movements in R: a reappraisal using Gundog.Tracks 0e1d89d0cc934a740dcd0a873aed178e 0000-0001-8834-3283 Mark Holton Mark Holton true false 8416d0ffc3cccdad6e6d67a455e7c4a2 0000-0001-8763-5997 Luca Borger Luca Borger true false 4046e46611e52bf1ee798d17411df8e9 James Redcliffe James Redcliffe true false 017bc6dd155098860945dc6249c4e9bc 0000-0003-3177-0177 Rory Wilson Rory Wilson true false 2021-09-08 SBI BackgroundFine-scale data on animal position are increasingly enabling us to understand the details of animal movement ecology and dead-reckoning, a technique integrating motion sensor-derived information on heading and speed, can be used to reconstruct fine-scale movement paths at sub-second resolution, irrespective of the environment. On its own however, the dead-reckoning process is prone to cumulative errors, so that position estimates quickly become uncoupled from true location. Periodic ground-truthing with aligned location data (e.g., from global positioning technology) can correct for this drift between Verified Positions (VPs). We present step-by-step instructions for implementing Verified Position Correction (VPC) dead-reckoning in R using the tilt-compensated compass method, accompanied by the mathematical protocols underlying the code and improvements and extensions of this technique to reduce the trade-off between VPC rate and dead-reckoning accuracy. These protocols are all built into a user-friendly, fully annotated VPC dead-reckoning R function; Gundog.Tracks, with multi-functionality to reconstruct animal movement paths across terrestrial, aquatic, and aerial systems, provided within the Additional file 4 as well as online (GitHub).ResultsThe Gundog.Tracks function is demonstrated on three contrasting model species (the African lion Panthera leo, the Magellanic penguin Spheniscus magellanicus, and the Imperial cormorant Leucocarbo atriceps) moving on land, in water and in air. We show the effect of uncorrected errors in speed estimations, heading inaccuracies and infrequent VPC rate and demonstrate how these issues can be addressed.ConclusionsThe function provided will allow anyone familiar with R to dead-reckon animal tracks readily and accurately, as the key complex issues are dealt with by Gundog.Tracks. This will help the community to consider and implement a valuable, but often overlooked method of reconstructing high-resolution animal movement paths across diverse species and systems without requiring a bespoke application. Journal Article Animal Biotelemetry 9 1 Springer Science and Business Media LLC 2050-3385 Animal behaviour; Animal movement; Global Positioning System; R (programming language); Track integration; Tri-axial accelerometers; Tri-axial magnetometers 1 7 2021 2021-07-01 10.1186/s40317-021-00245-z COLLEGE NANME Biosciences COLLEGE CODE SBI Swansea University Another institution paid the OA fee This research contributes to the CAASE project funded by King Abdullah University of Science and Technology (KAUST) under the KAUST Sensor Initiative. Fieldwork in the Kgalagadi Transfrontier Park was supported in part by a Department for Economy Global Challenges Research Fund grant to MS. Fieldwork within the Chubut Province was supported in part by the National Agency for Scientifc and Technological Promotion of Argentina (PICT 20171996 and PICT 2018-1480), and the Grants-in-Aid for Scientifc Research from the Japan Society for the Promotion of Science (16K18617). 2022-07-07T13:17:58.1210504 2021-09-08T00:12:02.7667639 Faculty of Science and Engineering School of Biosciences, Geography and Physics - Biosciences Richard M. Gunner 1 Mark Holton 0000-0001-8834-3283 2 Mike D. Scantlebury 3 O. Louis van Schalkwyk 4 Holly M. English 5 Hannah J. Williams 6 Phil Hopkins 7 Flavio Quintana 8 Agustina Gómez-Laich 9 Luca Borger 0000-0001-8763-5997 10 James Redcliffe 11 Ken Yoda 12 Takashi Yamamoto 13 Sam Ferreira 14 Danny Govender 15 Pauli Viljoen 16 Angela Bruns 17 Stephen H. Bell 18 Nikki J. Marks 19 Nigel C. Bennett 20 Mariano H. Tonini 21 Carlos M. Duarte 22 Martin C. van Rooyen 23 Mads F. Bertelsen 24 Craig J. Tambling 25 Rory Wilson 0000-0003-3177-0177 26 57810__21088__df8c52746b7e4139a0e1304148944b5d.pdf 57810.pdf 2021-10-04T16:49:55.8695601 Output 5451625 application/pdf Version of Record true © The Author(s) 2021. This article is licensed under a Creative Commons Attribution 4.0 International License true eng http://creativecommons.org/licenses/by/4.0/
title Dead-reckoning animal movements in R: a reappraisal using Gundog.Tracks
spellingShingle Dead-reckoning animal movements in R: a reappraisal using Gundog.Tracks
Mark Holton
Luca Borger
James Redcliffe
Rory Wilson
title_short Dead-reckoning animal movements in R: a reappraisal using Gundog.Tracks
title_full Dead-reckoning animal movements in R: a reappraisal using Gundog.Tracks
title_fullStr Dead-reckoning animal movements in R: a reappraisal using Gundog.Tracks
title_full_unstemmed Dead-reckoning animal movements in R: a reappraisal using Gundog.Tracks
title_sort Dead-reckoning animal movements in R: a reappraisal using Gundog.Tracks
author_id_str_mv 0e1d89d0cc934a740dcd0a873aed178e
8416d0ffc3cccdad6e6d67a455e7c4a2
4046e46611e52bf1ee798d17411df8e9
017bc6dd155098860945dc6249c4e9bc
author_id_fullname_str_mv 0e1d89d0cc934a740dcd0a873aed178e_***_Mark Holton
8416d0ffc3cccdad6e6d67a455e7c4a2_***_Luca Borger
4046e46611e52bf1ee798d17411df8e9_***_James Redcliffe
017bc6dd155098860945dc6249c4e9bc_***_Rory Wilson
author Mark Holton
Luca Borger
James Redcliffe
Rory Wilson
author2 Richard M. Gunner
Mark Holton
Mike D. Scantlebury
O. Louis van Schalkwyk
Holly M. English
Hannah J. Williams
Phil Hopkins
Flavio Quintana
Agustina Gómez-Laich
Luca Borger
James Redcliffe
Ken Yoda
Takashi Yamamoto
Sam Ferreira
Danny Govender
Pauli Viljoen
Angela Bruns
Stephen H. Bell
Nikki J. Marks
Nigel C. Bennett
Mariano H. Tonini
Carlos M. Duarte
Martin C. van Rooyen
Mads F. Bertelsen
Craig J. Tambling
Rory Wilson
format Journal article
container_title Animal Biotelemetry
container_volume 9
container_issue 1
publishDate 2021
institution Swansea University
issn 2050-3385
doi_str_mv 10.1186/s40317-021-00245-z
publisher Springer Science and Business Media LLC
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 BackgroundFine-scale data on animal position are increasingly enabling us to understand the details of animal movement ecology and dead-reckoning, a technique integrating motion sensor-derived information on heading and speed, can be used to reconstruct fine-scale movement paths at sub-second resolution, irrespective of the environment. On its own however, the dead-reckoning process is prone to cumulative errors, so that position estimates quickly become uncoupled from true location. Periodic ground-truthing with aligned location data (e.g., from global positioning technology) can correct for this drift between Verified Positions (VPs). We present step-by-step instructions for implementing Verified Position Correction (VPC) dead-reckoning in R using the tilt-compensated compass method, accompanied by the mathematical protocols underlying the code and improvements and extensions of this technique to reduce the trade-off between VPC rate and dead-reckoning accuracy. These protocols are all built into a user-friendly, fully annotated VPC dead-reckoning R function; Gundog.Tracks, with multi-functionality to reconstruct animal movement paths across terrestrial, aquatic, and aerial systems, provided within the Additional file 4 as well as online (GitHub).ResultsThe Gundog.Tracks function is demonstrated on three contrasting model species (the African lion Panthera leo, the Magellanic penguin Spheniscus magellanicus, and the Imperial cormorant Leucocarbo atriceps) moving on land, in water and in air. We show the effect of uncorrected errors in speed estimations, heading inaccuracies and infrequent VPC rate and demonstrate how these issues can be addressed.ConclusionsThe function provided will allow anyone familiar with R to dead-reckon animal tracks readily and accurately, as the key complex issues are dealt with by Gundog.Tracks. This will help the community to consider and implement a valuable, but often overlooked method of reconstructing high-resolution animal movement paths across diverse species and systems without requiring a bespoke application.
published_date 2021-07-01T04:09:28Z
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