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Residency and space use estimation methods based on passive acoustic telemetry data
Acoustic telemetry has helped overcome many of the challenges faced when studying the movement ecology of aquatic species, allowing to obtain unprecedented amounts of data. This has made it into one of the most widely used methods nowadays. Many ways to analyse acoustic telemetry data have been made...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9976422/ https://www.ncbi.nlm.nih.gov/pubmed/36859381 http://dx.doi.org/10.1186/s40462-022-00364-z |
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author | Kraft, S. Gandra, M. Lennox, R. J. Mourier, J. Winkler, A. C. Abecasis, D. |
author_facet | Kraft, S. Gandra, M. Lennox, R. J. Mourier, J. Winkler, A. C. Abecasis, D. |
author_sort | Kraft, S. |
collection | PubMed |
description | Acoustic telemetry has helped overcome many of the challenges faced when studying the movement ecology of aquatic species, allowing to obtain unprecedented amounts of data. This has made it into one of the most widely used methods nowadays. Many ways to analyse acoustic telemetry data have been made available and deciding on how to analyse the data requires considering the type of research objectives, relevant properties of the data (e.g., resolution, study design, equipment), habits of the study species, researcher experience, among others. To ease this decision process, here we showcase (1) some of the methods used to estimate pseudo-positions and positions from raw acoustic telemetry data, (2) methods to estimate residency and (3) methods to estimate two-dimensional home and occurrence range using geometric or hull-based methods and density-distribution methods, a network-based approach, and three-dimensional methods. We provide examples of some of these were tested using a sample of real data. With this we intend to provide the necessary background for the selection of the method(s) that better fit specific research objectives when using acoustic telemetry. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40462-022-00364-z. |
format | Online Article Text |
id | pubmed-9976422 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-99764222023-03-02 Residency and space use estimation methods based on passive acoustic telemetry data Kraft, S. Gandra, M. Lennox, R. J. Mourier, J. Winkler, A. C. Abecasis, D. Mov Ecol Review Acoustic telemetry has helped overcome many of the challenges faced when studying the movement ecology of aquatic species, allowing to obtain unprecedented amounts of data. This has made it into one of the most widely used methods nowadays. Many ways to analyse acoustic telemetry data have been made available and deciding on how to analyse the data requires considering the type of research objectives, relevant properties of the data (e.g., resolution, study design, equipment), habits of the study species, researcher experience, among others. To ease this decision process, here we showcase (1) some of the methods used to estimate pseudo-positions and positions from raw acoustic telemetry data, (2) methods to estimate residency and (3) methods to estimate two-dimensional home and occurrence range using geometric or hull-based methods and density-distribution methods, a network-based approach, and three-dimensional methods. We provide examples of some of these were tested using a sample of real data. With this we intend to provide the necessary background for the selection of the method(s) that better fit specific research objectives when using acoustic telemetry. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40462-022-00364-z. BioMed Central 2023-03-01 /pmc/articles/PMC9976422/ /pubmed/36859381 http://dx.doi.org/10.1186/s40462-022-00364-z Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Review Kraft, S. Gandra, M. Lennox, R. J. Mourier, J. Winkler, A. C. Abecasis, D. Residency and space use estimation methods based on passive acoustic telemetry data |
title | Residency and space use estimation methods based on passive acoustic telemetry data |
title_full | Residency and space use estimation methods based on passive acoustic telemetry data |
title_fullStr | Residency and space use estimation methods based on passive acoustic telemetry data |
title_full_unstemmed | Residency and space use estimation methods based on passive acoustic telemetry data |
title_short | Residency and space use estimation methods based on passive acoustic telemetry data |
title_sort | residency and space use estimation methods based on passive acoustic telemetry data |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9976422/ https://www.ncbi.nlm.nih.gov/pubmed/36859381 http://dx.doi.org/10.1186/s40462-022-00364-z |
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