Residency and space use estimation methods based on passive acoustic telemetry data

Abstract 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...
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Autor*in:	Kraft, S. [verfasserIn] Gandra, M. Lennox, R. J. Mourier, J. Winkler, A. C. Abecasis, D.

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2023

Schlagwörter:	Home range Range distribution Movement ecology Biotelemetry Data analysis

Anmerkung:	© The Author(s) 2023

Übergeordnetes Werk:	Enthalten in: Movement Ecology - London : BioMed Central, 2013, 11(2023), 1 vom: 01. März
Übergeordnetes Werk:	volume:11 ; year:2023 ; number:1 ; day:01 ; month:03

Links:	Volltext

DOI / URN:	10.1186/s40462-022-00364-z

Katalog-ID:	SPR051517817

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allfields	10.1186/s40462-022-00364-z doi (DE-627)SPR051517817 (SPR)s40462-022-00364-z-e DE-627 ger DE-627 rakwb eng Kraft, S. verfasserin (orcid)0000-0003-0719-8040 aut Residency and space use estimation methods based on passive acoustic telemetry data 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2023 Abstract 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. Home range (dpeaa)DE-He213 Range distribution (dpeaa)DE-He213 Movement ecology (dpeaa)DE-He213 Biotelemetry (dpeaa)DE-He213 Data analysis (dpeaa)DE-He213 Gandra, M. (orcid)0000-0003-1506-5141 aut Lennox, R. J. (orcid)0000-0003-1010-0577 aut Mourier, J. (orcid)0000-0001-9019-1717 aut Winkler, A. C. (orcid)0000-0001-7864-8243 aut Abecasis, D. (orcid)0000-0002-9802-8153 aut Enthalten in Movement Ecology London : BioMed Central, 2013 11(2023), 1 vom: 01. März (DE-627)755706498 (DE-600)2724975-X 2051-3933 nnns volume:11 year:2023 number:1 day:01 month:03 https://dx.doi.org/10.1186/s40462-022-00364-z kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 11 2023 1 01 03
spelling	10.1186/s40462-022-00364-z doi (DE-627)SPR051517817 (SPR)s40462-022-00364-z-e DE-627 ger DE-627 rakwb eng Kraft, S. verfasserin (orcid)0000-0003-0719-8040 aut Residency and space use estimation methods based on passive acoustic telemetry data 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2023 Abstract 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. Home range (dpeaa)DE-He213 Range distribution (dpeaa)DE-He213 Movement ecology (dpeaa)DE-He213 Biotelemetry (dpeaa)DE-He213 Data analysis (dpeaa)DE-He213 Gandra, M. (orcid)0000-0003-1506-5141 aut Lennox, R. J. (orcid)0000-0003-1010-0577 aut Mourier, J. (orcid)0000-0001-9019-1717 aut Winkler, A. C. (orcid)0000-0001-7864-8243 aut Abecasis, D. (orcid)0000-0002-9802-8153 aut Enthalten in Movement Ecology London : BioMed Central, 2013 11(2023), 1 vom: 01. März (DE-627)755706498 (DE-600)2724975-X 2051-3933 nnns volume:11 year:2023 number:1 day:01 month:03 https://dx.doi.org/10.1186/s40462-022-00364-z kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 11 2023 1 01 03
allfields_unstemmed	10.1186/s40462-022-00364-z doi (DE-627)SPR051517817 (SPR)s40462-022-00364-z-e DE-627 ger DE-627 rakwb eng Kraft, S. verfasserin (orcid)0000-0003-0719-8040 aut Residency and space use estimation methods based on passive acoustic telemetry data 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2023 Abstract 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. Home range (dpeaa)DE-He213 Range distribution (dpeaa)DE-He213 Movement ecology (dpeaa)DE-He213 Biotelemetry (dpeaa)DE-He213 Data analysis (dpeaa)DE-He213 Gandra, M. (orcid)0000-0003-1506-5141 aut Lennox, R. J. (orcid)0000-0003-1010-0577 aut Mourier, J. (orcid)0000-0001-9019-1717 aut Winkler, A. C. (orcid)0000-0001-7864-8243 aut Abecasis, D. (orcid)0000-0002-9802-8153 aut Enthalten in Movement Ecology London : BioMed Central, 2013 11(2023), 1 vom: 01. März (DE-627)755706498 (DE-600)2724975-X 2051-3933 nnns volume:11 year:2023 number:1 day:01 month:03 https://dx.doi.org/10.1186/s40462-022-00364-z kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 11 2023 1 01 03
allfieldsGer	10.1186/s40462-022-00364-z doi (DE-627)SPR051517817 (SPR)s40462-022-00364-z-e DE-627 ger DE-627 rakwb eng Kraft, S. verfasserin (orcid)0000-0003-0719-8040 aut Residency and space use estimation methods based on passive acoustic telemetry data 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2023 Abstract 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. Home range (dpeaa)DE-He213 Range distribution (dpeaa)DE-He213 Movement ecology (dpeaa)DE-He213 Biotelemetry (dpeaa)DE-He213 Data analysis (dpeaa)DE-He213 Gandra, M. (orcid)0000-0003-1506-5141 aut Lennox, R. J. (orcid)0000-0003-1010-0577 aut Mourier, J. (orcid)0000-0001-9019-1717 aut Winkler, A. C. (orcid)0000-0001-7864-8243 aut Abecasis, D. (orcid)0000-0002-9802-8153 aut Enthalten in Movement Ecology London : BioMed Central, 2013 11(2023), 1 vom: 01. März (DE-627)755706498 (DE-600)2724975-X 2051-3933 nnns volume:11 year:2023 number:1 day:01 month:03 https://dx.doi.org/10.1186/s40462-022-00364-z kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 11 2023 1 01 03
allfieldsSound	10.1186/s40462-022-00364-z doi (DE-627)SPR051517817 (SPR)s40462-022-00364-z-e DE-627 ger DE-627 rakwb eng Kraft, S. verfasserin (orcid)0000-0003-0719-8040 aut Residency and space use estimation methods based on passive acoustic telemetry data 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2023 Abstract 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. Home range (dpeaa)DE-He213 Range distribution (dpeaa)DE-He213 Movement ecology (dpeaa)DE-He213 Biotelemetry (dpeaa)DE-He213 Data analysis (dpeaa)DE-He213 Gandra, M. (orcid)0000-0003-1506-5141 aut Lennox, R. J. (orcid)0000-0003-1010-0577 aut Mourier, J. (orcid)0000-0001-9019-1717 aut Winkler, A. C. (orcid)0000-0001-7864-8243 aut Abecasis, D. (orcid)0000-0002-9802-8153 aut Enthalten in Movement Ecology London : BioMed Central, 2013 11(2023), 1 vom: 01. März (DE-627)755706498 (DE-600)2724975-X 2051-3933 nnns volume:11 year:2023 number:1 day:01 month:03 https://dx.doi.org/10.1186/s40462-022-00364-z kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 11 2023 1 01 03
language	English
source	Enthalten in Movement Ecology 11(2023), 1 vom: 01. März volume:11 year:2023 number:1 day:01 month:03
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institution	findex.gbv.de
topic_facet	Home range Range distribution Movement ecology Biotelemetry Data analysis
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container_title	Movement Ecology
authorswithroles_txt_mv	Kraft, S. @@aut@@ Gandra, M. @@aut@@ Lennox, R. J. @@aut@@ Mourier, J. @@aut@@ Winkler, A. C. @@aut@@ Abecasis, D. @@aut@@
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author	Kraft, S.
spellingShingle	Kraft, S. misc Home range misc Range distribution misc Movement ecology misc Biotelemetry misc Data analysis Residency and space use estimation methods based on passive acoustic telemetry data
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topic_title	Residency and space use estimation methods based on passive acoustic telemetry data Home range (dpeaa)DE-He213 Range distribution (dpeaa)DE-He213 Movement ecology (dpeaa)DE-He213 Biotelemetry (dpeaa)DE-He213 Data analysis (dpeaa)DE-He213
topic	misc Home range misc Range distribution misc Movement ecology misc Biotelemetry misc Data analysis
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title	Residency and space use estimation methods based on passive acoustic telemetry data
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title_sort	residency and space use estimation methods based on passive acoustic telemetry data
title_auth	Residency and space use estimation methods based on passive acoustic telemetry data
abstract	Abstract 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. © The Author(s) 2023
abstractGer	Abstract 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. © The Author(s) 2023
abstract_unstemmed	Abstract 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. © The Author(s) 2023
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title_short	Residency and space use estimation methods based on passive acoustic telemetry data
url	https://dx.doi.org/10.1186/s40462-022-00364-z
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author2	Gandra, M. Lennox, R. J. Mourier, J. Winkler, A. C. Abecasis, D.
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Residency and space use estimation methods based on passive acoustic telemetry data

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