Journal article 1713 views 295 downloads
Identification of animal movement patterns using tri-axial magnetometry
Hannah J. Williams,
Mark Holton 
,
Emily Shepard ,
Nicola Largey,
Brad Norman,
Peter G. Ryan,
Olivier Duriez,
Michael Scantlebury,
Flavio Quintana,
Elizabeth A. Magowan,
Nikki J. Marks,
Abdulaziz N. Alagaili,
Nigel C. Bennett,
Rory Wilson
,
Emily Shepard ,
Nicola Largey,
Brad Norman,
Peter G. Ryan,
Olivier Duriez,
Michael Scantlebury,
Flavio Quintana,
Elizabeth A. Magowan,
Nikki J. Marks,
Abdulaziz N. Alagaili,
Nigel C. Bennett,
Rory Wilson
Movement Ecology, Volume: 5, Issue: 1
Swansea University Authors:
Mark Holton , Emily Shepard , Rory Wilson
-
PDF | Version of Record
This article is distributed under the terms of the Creative Commons Attribution 4.0 International License
Download (3.44MB)
DOI (Published version): 10.1186/s40462-017-0097-x
Abstract
BackgroundAccelerometers are powerful sensors in many bio-logging devices, and are increasingly allowing researchers to investigate the performance, behaviour, energy expenditure and even state, of free-living animals. Another sensor commonly used in animal-attached loggers is the magnetometer, whic...
| Published in: | Movement Ecology |
|---|---|
| ISSN: | 2051-3933 |
| Published: |
2017
|
| Online Access: |
Check full text
|
| URI: | https://cronfa.swan.ac.uk/Record/cronfa32735 |
| first_indexed |
2017-03-28T20:51:48Z |
|---|---|
| last_indexed |
2020-06-24T12:44:39Z |
| id |
cronfa32735 |
| recordtype |
SURis |
| fullrecord |
<?xml version="1.0"?><rfc1807><datestamp>2020-06-24T11:21:32.2385168</datestamp><bib-version>v2</bib-version><id>32735</id><entry>2017-03-28</entry><title>Identification of animal movement patterns using tri-axial magnetometry</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>54729295145aa1ea56d176818d51ed6a</sid><ORCID>0000-0001-7325-6398</ORCID><firstname>Emily</firstname><surname>Shepard</surname><name>Emily Shepard</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>2017-03-28</date><deptcode>BGPS</deptcode><abstract>BackgroundAccelerometers are powerful sensors in many bio-logging devices, and are increasingly allowing researchers to investigate the performance, behaviour, energy expenditure and even state, of free-living animals. Another sensor commonly used in animal-attached loggers is the magnetometer, which has been primarily used in dead-reckoning or inertial measurement tags, but little outside that. We examine the potential of magnetometers for helping elucidate the behaviour of animals in a manner analogous to, but very different from, accelerometers. The particular responses of magnetometers to movement means that there are instances when they can resolve behaviours that are not easily perceived using accelerometers.MethodsWe calibrated the tri-axial magnetometer to rotations in each axis of movement and constructed 3-dimensional plots to inspect these stylised movements. Using the tri-axial data of Daily Diary tags, attached to individuals of number of animal species as they perform different behaviours, we used these 3-d plots to develop a framework with which tri-axial magnetometry data can be examined and introduce metrics that should help quantify movement and behaviour.ResultsTri-axial magnetometry data reveal patterns in movement at various scales of rotation that are not always evident in acceleration data. Some of these patterns may be obscure until visualised in 3D space as tri-axial spherical plots (m-spheres). A tag-fitted animal that rotates in heading while adopting a constant body attitude produces a ring of data around the pole of the m-sphere that we define as its Normal Operational Plane (NOP). Data that do not lie on this ring are created by postural rotations of the animal as it pitches and/or rolls. Consequently, stereotyped behaviours appear as specific trajectories on the sphere (m-prints), reflecting conserved sequences of postural changes (and/or angular velocities), which result from the precise relationship between body attitude and heading. This novel approach shows promise for helping researchers to identify and quantify behaviours in terms of animal body posture, including heading.ConclusionMagnetometer-based techniques and metrics can enhance our capacity to identify and examine animal behaviour, either as a technique used alone, or one that is complementary to tri-axial accelerometry.</abstract><type>Journal Article</type><journal>Movement Ecology</journal><volume>5</volume><journalNumber>1</journalNumber><publisher/><issnElectronic>2051-3933</issnElectronic><keywords>Magnetometry, visualization, patterns,</keywords><publishedDay>27</publishedDay><publishedMonth>3</publishedMonth><publishedYear>2017</publishedYear><publishedDate>2017-03-27</publishedDate><doi>10.1186/s40462-017-0097-x</doi><url>https://movementecologyjournal.biomedcentral.com/articles/10.1186/s40462-017-0097-x</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/><lastEdited>2020-06-24T11:21:32.2385168</lastEdited><Created>2017-03-28T16:10:36.6139123</Created><authors><author><firstname>Hannah J.</firstname><surname>Williams</surname><order>1</order></author><author><firstname>Mark</firstname><surname>Holton</surname><orcid>0000-0001-8834-3283</orcid><order>2</order></author><author><firstname>Emily</firstname><surname>Shepard</surname><orcid>0000-0001-7325-6398</orcid><order>3</order></author><author><firstname>Nicola</firstname><surname>Largey</surname><order>4</order></author><author><firstname>Brad</firstname><surname>Norman</surname><order>5</order></author><author><firstname>Peter G.</firstname><surname>Ryan</surname><order>6</order></author><author><firstname>Olivier</firstname><surname>Duriez</surname><order>7</order></author><author><firstname>Michael</firstname><surname>Scantlebury</surname><order>8</order></author><author><firstname>Flavio</firstname><surname>Quintana</surname><order>9</order></author><author><firstname>Elizabeth A.</firstname><surname>Magowan</surname><order>10</order></author><author><firstname>Nikki J.</firstname><surname>Marks</surname><order>11</order></author><author><firstname>Abdulaziz N.</firstname><surname>Alagaili</surname><order>12</order></author><author><firstname>Nigel C.</firstname><surname>Bennett</surname><order>13</order></author><author><firstname>Rory</firstname><surname>Wilson</surname><orcid>0000-0003-3177-0177</orcid><order>14</order></author></authors><documents><document><filename>0032735-28032017161802.pdf</filename><originalFilename>WilliamsIdentificationOfMovement2017.pdf</originalFilename><uploaded>2017-03-28T16:18:02.7800000</uploaded><type>Output</type><contentLength>3676610</contentLength><contentType>application/pdf</contentType><version>Version of Record</version><cronfaStatus>true</cronfaStatus><embargoDate>2017-03-28T00:00:00.0000000</embargoDate><documentNotes>This article is distributed under the terms of the Creative Commons Attribution 4.0
International License</documentNotes><copyrightCorrect>true</copyrightCorrect><language>eng</language><licence>http://creativecommons.org/licenses/by/4.0/</licence></document></documents><OutputDurs/></rfc1807> |
| spelling |
2020-06-24T11:21:32.2385168 v2 32735 2017-03-28 Identification of animal movement patterns using tri-axial magnetometry 0e1d89d0cc934a740dcd0a873aed178e 0000-0001-8834-3283 Mark Holton Mark Holton true false 54729295145aa1ea56d176818d51ed6a 0000-0001-7325-6398 Emily Shepard Emily Shepard true false 017bc6dd155098860945dc6249c4e9bc 0000-0003-3177-0177 Rory Wilson Rory Wilson true false 2017-03-28 BGPS BackgroundAccelerometers are powerful sensors in many bio-logging devices, and are increasingly allowing researchers to investigate the performance, behaviour, energy expenditure and even state, of free-living animals. Another sensor commonly used in animal-attached loggers is the magnetometer, which has been primarily used in dead-reckoning or inertial measurement tags, but little outside that. We examine the potential of magnetometers for helping elucidate the behaviour of animals in a manner analogous to, but very different from, accelerometers. The particular responses of magnetometers to movement means that there are instances when they can resolve behaviours that are not easily perceived using accelerometers.MethodsWe calibrated the tri-axial magnetometer to rotations in each axis of movement and constructed 3-dimensional plots to inspect these stylised movements. Using the tri-axial data of Daily Diary tags, attached to individuals of number of animal species as they perform different behaviours, we used these 3-d plots to develop a framework with which tri-axial magnetometry data can be examined and introduce metrics that should help quantify movement and behaviour.ResultsTri-axial magnetometry data reveal patterns in movement at various scales of rotation that are not always evident in acceleration data. Some of these patterns may be obscure until visualised in 3D space as tri-axial spherical plots (m-spheres). A tag-fitted animal that rotates in heading while adopting a constant body attitude produces a ring of data around the pole of the m-sphere that we define as its Normal Operational Plane (NOP). Data that do not lie on this ring are created by postural rotations of the animal as it pitches and/or rolls. Consequently, stereotyped behaviours appear as specific trajectories on the sphere (m-prints), reflecting conserved sequences of postural changes (and/or angular velocities), which result from the precise relationship between body attitude and heading. This novel approach shows promise for helping researchers to identify and quantify behaviours in terms of animal body posture, including heading.ConclusionMagnetometer-based techniques and metrics can enhance our capacity to identify and examine animal behaviour, either as a technique used alone, or one that is complementary to tri-axial accelerometry. Journal Article Movement Ecology 5 1 2051-3933 Magnetometry, visualization, patterns, 27 3 2017 2017-03-27 10.1186/s40462-017-0097-x https://movementecologyjournal.biomedcentral.com/articles/10.1186/s40462-017-0097-x COLLEGE NANME Biosciences Geography and Physics School COLLEGE CODE BGPS Swansea University 2020-06-24T11:21:32.2385168 2017-03-28T16:10:36.6139123 Hannah J. Williams 1 Mark Holton 0000-0001-8834-3283 2 Emily Shepard 0000-0001-7325-6398 3 Nicola Largey 4 Brad Norman 5 Peter G. Ryan 6 Olivier Duriez 7 Michael Scantlebury 8 Flavio Quintana 9 Elizabeth A. Magowan 10 Nikki J. Marks 11 Abdulaziz N. Alagaili 12 Nigel C. Bennett 13 Rory Wilson 0000-0003-3177-0177 14 0032735-28032017161802.pdf WilliamsIdentificationOfMovement2017.pdf 2017-03-28T16:18:02.7800000 Output 3676610 application/pdf Version of Record true 2017-03-28T00:00:00.0000000 This article is distributed under the terms of the Creative Commons Attribution 4.0 International License true eng http://creativecommons.org/licenses/by/4.0/ |
| title |
Identification of animal movement patterns using tri-axial magnetometry |
| spellingShingle |
Identification of animal movement patterns using tri-axial magnetometry Mark Holton Emily Shepard Rory Wilson |
| title_short |
Identification of animal movement patterns using tri-axial magnetometry |
| title_full |
Identification of animal movement patterns using tri-axial magnetometry |
| title_fullStr |
Identification of animal movement patterns using tri-axial magnetometry |
| title_full_unstemmed |
Identification of animal movement patterns using tri-axial magnetometry |
| title_sort |
Identification of animal movement patterns using tri-axial magnetometry |
| author_id_str_mv |
0e1d89d0cc934a740dcd0a873aed178e 54729295145aa1ea56d176818d51ed6a 017bc6dd155098860945dc6249c4e9bc |
| author_id_fullname_str_mv |
0e1d89d0cc934a740dcd0a873aed178e_***_Mark Holton 54729295145aa1ea56d176818d51ed6a_***_Emily Shepard 017bc6dd155098860945dc6249c4e9bc_***_Rory Wilson |
| author |
Mark Holton Emily Shepard Rory Wilson |
| author2 |
Hannah J. Williams Mark Holton Emily Shepard Nicola Largey Brad Norman Peter G. Ryan Olivier Duriez Michael Scantlebury Flavio Quintana Elizabeth A. Magowan Nikki J. Marks Abdulaziz N. Alagaili Nigel C. Bennett Rory Wilson |
| format |
Journal article |
| container_title |
Movement Ecology |
| container_volume |
5 |
| container_issue |
1 |
| publishDate |
2017 |
| institution |
Swansea University |
| issn |
2051-3933 |
| doi_str_mv |
10.1186/s40462-017-0097-x |
| url |
https://movementecologyjournal.biomedcentral.com/articles/10.1186/s40462-017-0097-x |
| document_store_str |
1 |
| active_str |
0 |
| description |
BackgroundAccelerometers are powerful sensors in many bio-logging devices, and are increasingly allowing researchers to investigate the performance, behaviour, energy expenditure and even state, of free-living animals. Another sensor commonly used in animal-attached loggers is the magnetometer, which has been primarily used in dead-reckoning or inertial measurement tags, but little outside that. We examine the potential of magnetometers for helping elucidate the behaviour of animals in a manner analogous to, but very different from, accelerometers. The particular responses of magnetometers to movement means that there are instances when they can resolve behaviours that are not easily perceived using accelerometers.MethodsWe calibrated the tri-axial magnetometer to rotations in each axis of movement and constructed 3-dimensional plots to inspect these stylised movements. Using the tri-axial data of Daily Diary tags, attached to individuals of number of animal species as they perform different behaviours, we used these 3-d plots to develop a framework with which tri-axial magnetometry data can be examined and introduce metrics that should help quantify movement and behaviour.ResultsTri-axial magnetometry data reveal patterns in movement at various scales of rotation that are not always evident in acceleration data. Some of these patterns may be obscure until visualised in 3D space as tri-axial spherical plots (m-spheres). A tag-fitted animal that rotates in heading while adopting a constant body attitude produces a ring of data around the pole of the m-sphere that we define as its Normal Operational Plane (NOP). Data that do not lie on this ring are created by postural rotations of the animal as it pitches and/or rolls. Consequently, stereotyped behaviours appear as specific trajectories on the sphere (m-prints), reflecting conserved sequences of postural changes (and/or angular velocities), which result from the precise relationship between body attitude and heading. This novel approach shows promise for helping researchers to identify and quantify behaviours in terms of animal body posture, including heading.ConclusionMagnetometer-based techniques and metrics can enhance our capacity to identify and examine animal behaviour, either as a technique used alone, or one that is complementary to tri-axial accelerometry. |
| published_date |
2017-03-27T07:03:33Z |
| _version_ |
1821297463449878528 |
| score |
11.047306 |