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pamlr: A toolbox for analysing animal behaviour using pressure, acceleration, temperature, magnetic or light data in R
1. Light‐level geolocators have revolutionised the study of animal behaviour. However, lacking spatial precision, their usage has been primary targeted towards the analysis of large‐scale movements. Recent technological developments have allowed the integration of magnetometers and accelerometers in...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9542251/ https://www.ncbi.nlm.nih.gov/pubmed/35362103 http://dx.doi.org/10.1111/1365-2656.13695 |
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author | Dhanjal‐Adams, Kiran L. Willener, Astrid S. T. Liechti, Felix |
author_facet | Dhanjal‐Adams, Kiran L. Willener, Astrid S. T. Liechti, Felix |
author_sort | Dhanjal‐Adams, Kiran L. |
collection | PubMed |
description | 1. Light‐level geolocators have revolutionised the study of animal behaviour. However, lacking spatial precision, their usage has been primary targeted towards the analysis of large‐scale movements. Recent technological developments have allowed the integration of magnetometers and accelerometers into geolocator tags in addition to barometers and thermometers, offering new behavioural insights. 2. Here, we introduce an R toolbox for identifying behavioural patterns from multisensor geolocator tags, with functions specifically designed for data visualisation, calibration, classification and error estimation. More specifically, the package allows for the flexible analysis of any combination of sensor data using k‐means clustering, expectation maximisation binary clustering, hidden Markov models and changepoint analyses. Furthermore, the package integrates tailored algorithms for identifying periods of prolonged high activity (most commonly used for identifying migratory flapping flight), and pressure changes (most commonly used for identifying dive or flight events). 3. Finally, we highlight some of the limitations, implications and opportunities of using these methods. |
format | Online Article Text |
id | pubmed-9542251 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-95422512022-10-14 pamlr: A toolbox for analysing animal behaviour using pressure, acceleration, temperature, magnetic or light data in R Dhanjal‐Adams, Kiran L. Willener, Astrid S. T. Liechti, Felix J Anim Ecol Research Methods Guide 1. Light‐level geolocators have revolutionised the study of animal behaviour. However, lacking spatial precision, their usage has been primary targeted towards the analysis of large‐scale movements. Recent technological developments have allowed the integration of magnetometers and accelerometers into geolocator tags in addition to barometers and thermometers, offering new behavioural insights. 2. Here, we introduce an R toolbox for identifying behavioural patterns from multisensor geolocator tags, with functions specifically designed for data visualisation, calibration, classification and error estimation. More specifically, the package allows for the flexible analysis of any combination of sensor data using k‐means clustering, expectation maximisation binary clustering, hidden Markov models and changepoint analyses. Furthermore, the package integrates tailored algorithms for identifying periods of prolonged high activity (most commonly used for identifying migratory flapping flight), and pressure changes (most commonly used for identifying dive or flight events). 3. Finally, we highlight some of the limitations, implications and opportunities of using these methods. John Wiley and Sons Inc. 2022-04-22 2022-07 /pmc/articles/PMC9542251/ /pubmed/35362103 http://dx.doi.org/10.1111/1365-2656.13695 Text en © 2022 The Authors. Journal of Animal Ecology published by John Wiley & Sons Ltd on behalf of British Ecological Society. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes. |
spellingShingle | Research Methods Guide Dhanjal‐Adams, Kiran L. Willener, Astrid S. T. Liechti, Felix pamlr: A toolbox for analysing animal behaviour using pressure, acceleration, temperature, magnetic or light data in R |
title |
pamlr: A toolbox for analysing animal behaviour using pressure, acceleration, temperature, magnetic or light data in R |
title_full |
pamlr: A toolbox for analysing animal behaviour using pressure, acceleration, temperature, magnetic or light data in R |
title_fullStr |
pamlr: A toolbox for analysing animal behaviour using pressure, acceleration, temperature, magnetic or light data in R |
title_full_unstemmed |
pamlr: A toolbox for analysing animal behaviour using pressure, acceleration, temperature, magnetic or light data in R |
title_short |
pamlr: A toolbox for analysing animal behaviour using pressure, acceleration, temperature, magnetic or light data in R |
title_sort | pamlr: a toolbox for analysing animal behaviour using pressure, acceleration, temperature, magnetic or light data in r |
topic | Research Methods Guide |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9542251/ https://www.ncbi.nlm.nih.gov/pubmed/35362103 http://dx.doi.org/10.1111/1365-2656.13695 |
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