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Ecological inference using data from accelerometers needs careful protocols

Baptiste Garde, Rory Wilson Orcid Logo, Adam Fell, Nik Cole, Vikash Tatayah, Mark Holton Orcid Logo, Kayleigh Rose Orcid Logo, Richard Metcalfe Orcid Logo, Hermina Robotka, Martin Wikelski Orcid Logo, Fred Tremblay, Shannon Whelan Orcid Logo, Kyle H. Elliott, Emily Shepard Orcid Logo

Methods in Ecology and Evolution, Volume: 13, Issue: 4

Swansea University Authors: Baptiste Garde, Rory Wilson Orcid Logo, Adam Fell, Mark Holton Orcid Logo, Kayleigh Rose Orcid Logo, Richard Metcalfe Orcid Logo, Emily Shepard Orcid Logo

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DOI (Published version): 10.1111/2041-210x.13804

Abstract

Accelerometers in animal-attached tags are powerful tools in behavioural ecology, they can be used to determine behaviour and provide proxies for movement-based energy expenditure. Researchers are collecting and archiving data across systems, seasons and device types. However, using data repositorie...

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Published in: Methods in Ecology and Evolution
ISSN: 2041-210X 2041-210X
Published: Wiley 2022
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Researchers are collecting and archiving data across systems, seasons and device types. However, using data repositories to draw ecological inference requires a good understanding of the error introduced according to sensor type and position on the study animal and protocols for error assessment and minimization.Using laboratory trials, we examine the absolute accuracy of tri-axial accelerometers and determine how inaccuracies impact measurements of dynamic body acceleration (DBA), a proxy for energy expenditure, in human participants. We then examine how tag type and placement affect the acceleration signal in birds, using pigeons Columba livia flying in a wind tunnel, with tags mounted simultaneously in two positions, and back- and tail-mounted tags deployed on wild kittiwakes Rissa tridactyla. Finally, we present a case study where two generations of tag were deployed using different attachment procedures on red-tailed tropicbirds Phaethon rubricauda foraging in different seasons.Bench tests showed that individual acceleration axes required a two-level correction to eliminate measurement error. This resulted in DBA differences of up to 5% between calibrated and uncalibrated tags for humans walking at a range of speeds. Device position was associated with greater variation in DBA, with upper- and lower back-mounted tags varying by 9% in pigeons, and tail- and back-mounted tags varying by 13% in kittiwakes. The tropicbird study highlighted the difficulties of attributing changes in signal amplitude to a single factor when confounding influences tend to covary, as DBA varied by 25% between seasons.Accelerometer accuracy, tag placement and attachment critically affect the signal amplitude and thereby the ability of the system to detect biologically meaningful phenomena. We propose a simple method to calibrate accelerometers that can be executed under field conditions. This should be used prior to deployments and archived with resulting data. 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spelling 2022-10-31T15:11:34.5057227 v2 59252 2022-01-26 Ecological inference using data from accelerometers needs careful protocols 0d5e96ee58acfec4771c81cd2cb4cca8 Baptiste Garde Baptiste Garde true false 017bc6dd155098860945dc6249c4e9bc 0000-0003-3177-0177 Rory Wilson Rory Wilson true false cb6508f9a11c818182f66041cef277f2 Adam Fell Adam Fell true false 0e1d89d0cc934a740dcd0a873aed178e 0000-0001-8834-3283 Mark Holton Mark Holton true false 83a47731b96af0d69fcbdb6c4c5a20aa 0000-0001-7023-2809 Kayleigh Rose Kayleigh Rose true false 9bb783273dd9d54a2f3f66f75c43abdf 0000-0003-0980-2977 Richard Metcalfe Richard Metcalfe true false 54729295145aa1ea56d176818d51ed6a 0000-0001-7325-6398 Emily Shepard Emily Shepard true false 2022-01-26 SBI Accelerometers in animal-attached tags are powerful tools in behavioural ecology, they can be used to determine behaviour and provide proxies for movement-based energy expenditure. Researchers are collecting and archiving data across systems, seasons and device types. However, using data repositories to draw ecological inference requires a good understanding of the error introduced according to sensor type and position on the study animal and protocols for error assessment and minimization.Using laboratory trials, we examine the absolute accuracy of tri-axial accelerometers and determine how inaccuracies impact measurements of dynamic body acceleration (DBA), a proxy for energy expenditure, in human participants. We then examine how tag type and placement affect the acceleration signal in birds, using pigeons Columba livia flying in a wind tunnel, with tags mounted simultaneously in two positions, and back- and tail-mounted tags deployed on wild kittiwakes Rissa tridactyla. Finally, we present a case study where two generations of tag were deployed using different attachment procedures on red-tailed tropicbirds Phaethon rubricauda foraging in different seasons.Bench tests showed that individual acceleration axes required a two-level correction to eliminate measurement error. This resulted in DBA differences of up to 5% between calibrated and uncalibrated tags for humans walking at a range of speeds. Device position was associated with greater variation in DBA, with upper- and lower back-mounted tags varying by 9% in pigeons, and tail- and back-mounted tags varying by 13% in kittiwakes. The tropicbird study highlighted the difficulties of attributing changes in signal amplitude to a single factor when confounding influences tend to covary, as DBA varied by 25% between seasons.Accelerometer accuracy, tag placement and attachment critically affect the signal amplitude and thereby the ability of the system to detect biologically meaningful phenomena. We propose a simple method to calibrate accelerometers that can be executed under field conditions. This should be used prior to deployments and archived with resulting data. We also suggest a way that researchers can assess accuracy in previously collected data, and caution that variable tag placement and attachment can increase sensor noise and even generate trends that have no biological meaning. Journal Article Methods in Ecology and Evolution 13 4 Wiley 2041-210X 2041-210X biologger; biotelemetry; DBA; Accelerometer; biologging; tag placement; accuracy; calibration; tagging protocol 7 2 2022 2022-02-07 10.1111/2041-210x.13804 COLLEGE NANME Biosciences COLLEGE CODE SBI Swansea University Another institution paid the OA fee H2020 European Research Council. Grant Number: 715874 Horizon 2020 European Union European Research Council 2022-10-31T15:11:34.5057227 2022-01-26T13:27:38.8859548 Faculty of Science and Engineering School of Biosciences, Geography and Physics - Biosciences Baptiste Garde 1 Rory Wilson 0000-0003-3177-0177 2 Adam Fell 3 Nik Cole 4 Vikash Tatayah 5 Mark Holton 0000-0001-8834-3283 6 Kayleigh Rose 0000-0001-7023-2809 7 Richard Metcalfe 0000-0003-0980-2977 8 Hermina Robotka 9 Martin Wikelski 0000-0002-9790-7025 10 Fred Tremblay 11 Shannon Whelan 0000-0003-2862-327x 12 Kyle H. Elliott 13 Emily Shepard 0000-0001-7325-6398 14 59252__22332__0942866f2f88417dbdaddaa76cd320de.pdf VOR.59252.pdf 2022-02-08T09:12:53.0501737 Output 1516668 application/pdf Version of Record true © 2022 The Authors. Methods in Ecology and Evolution published by John Wiley & Sons Ltd on behalf of British Ecological Society. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. true eng http://creativecommons.org/licenses/by/4.0/
title Ecological inference using data from accelerometers needs careful protocols
spellingShingle Ecological inference using data from accelerometers needs careful protocols
Baptiste Garde
Rory Wilson
Adam Fell
Mark Holton
Kayleigh Rose
Richard Metcalfe
Emily Shepard
title_short Ecological inference using data from accelerometers needs careful protocols
title_full Ecological inference using data from accelerometers needs careful protocols
title_fullStr Ecological inference using data from accelerometers needs careful protocols
title_full_unstemmed Ecological inference using data from accelerometers needs careful protocols
title_sort Ecological inference using data from accelerometers needs careful protocols
author_id_str_mv 0d5e96ee58acfec4771c81cd2cb4cca8
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author_id_fullname_str_mv 0d5e96ee58acfec4771c81cd2cb4cca8_***_Baptiste Garde
017bc6dd155098860945dc6249c4e9bc_***_Rory Wilson
cb6508f9a11c818182f66041cef277f2_***_Adam Fell
0e1d89d0cc934a740dcd0a873aed178e_***_Mark Holton
83a47731b96af0d69fcbdb6c4c5a20aa_***_Kayleigh Rose
9bb783273dd9d54a2f3f66f75c43abdf_***_Richard Metcalfe
54729295145aa1ea56d176818d51ed6a_***_Emily Shepard
author Baptiste Garde
Rory Wilson
Adam Fell
Mark Holton
Kayleigh Rose
Richard Metcalfe
Emily Shepard
author2 Baptiste Garde
Rory Wilson
Adam Fell
Nik Cole
Vikash Tatayah
Mark Holton
Kayleigh Rose
Richard Metcalfe
Hermina Robotka
Martin Wikelski
Fred Tremblay
Shannon Whelan
Kyle H. Elliott
Emily Shepard
format Journal article
container_title Methods in Ecology and Evolution
container_volume 13
container_issue 4
publishDate 2022
institution Swansea University
issn 2041-210X
2041-210X
doi_str_mv 10.1111/2041-210x.13804
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 Accelerometers in animal-attached tags are powerful tools in behavioural ecology, they can be used to determine behaviour and provide proxies for movement-based energy expenditure. Researchers are collecting and archiving data across systems, seasons and device types. However, using data repositories to draw ecological inference requires a good understanding of the error introduced according to sensor type and position on the study animal and protocols for error assessment and minimization.Using laboratory trials, we examine the absolute accuracy of tri-axial accelerometers and determine how inaccuracies impact measurements of dynamic body acceleration (DBA), a proxy for energy expenditure, in human participants. We then examine how tag type and placement affect the acceleration signal in birds, using pigeons Columba livia flying in a wind tunnel, with tags mounted simultaneously in two positions, and back- and tail-mounted tags deployed on wild kittiwakes Rissa tridactyla. Finally, we present a case study where two generations of tag were deployed using different attachment procedures on red-tailed tropicbirds Phaethon rubricauda foraging in different seasons.Bench tests showed that individual acceleration axes required a two-level correction to eliminate measurement error. This resulted in DBA differences of up to 5% between calibrated and uncalibrated tags for humans walking at a range of speeds. Device position was associated with greater variation in DBA, with upper- and lower back-mounted tags varying by 9% in pigeons, and tail- and back-mounted tags varying by 13% in kittiwakes. The tropicbird study highlighted the difficulties of attributing changes in signal amplitude to a single factor when confounding influences tend to covary, as DBA varied by 25% between seasons.Accelerometer accuracy, tag placement and attachment critically affect the signal amplitude and thereby the ability of the system to detect biologically meaningful phenomena. We propose a simple method to calibrate accelerometers that can be executed under field conditions. This should be used prior to deployments and archived with resulting data. We also suggest a way that researchers can assess accuracy in previously collected data, and caution that variable tag placement and attachment can increase sensor noise and even generate trends that have no biological meaning.
published_date 2022-02-07T04:16:25Z
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score 11.012924

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