Automated peak detection method for behavioral event identification : detecting Balaenoptera musculus and Grampus griseus feeding attempts
This project was supported by the U.S. Office of Naval Research (Grant No. N00014-16-1-3089). Tag deployments used here from the SOCAL-Behavioral Response Study were funded by the U.S. Office of Naval Research and Navy Living Marine Resources under multiple grants and contracts. Further funding was...
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Online Access: | http://hdl.handle.net/10023/17477 https://doi.org/10.1186/s40317-019-0169-3 |
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ftstandrewserep:oai:research-repository.st-andrews.ac.uk:10023/17477 2023-07-02T03:31:45+02:00 Automated peak detection method for behavioral event identification : detecting Balaenoptera musculus and Grampus griseus feeding attempts Sweeney, David A. Deruiter, Stacy L. McNamara-Oh, Ye Joo Marques, Tiago A. Arranz, Patricia Calambokidis, John Office of Naval Research University of St Andrews. School of Mathematics and Statistics University of St Andrews. Scottish Oceans Institute University of St Andrews. Centre for Research into Ecological & Environmental Modelling 2019-04-08T10:30:01Z 10 application/pdf http://hdl.handle.net/10023/17477 https://doi.org/10.1186/s40317-019-0169-3 eng eng Animal Biotelemetry Sweeney , D A , Deruiter , S L , McNamara-Oh , Y J , Marques , T A , Arranz , P & Calambokidis , J 2019 , ' Automated peak detection method for behavioral event identification : detecting Balaenoptera musculus and Grampus griseus feeding attempts ' , Animal Biotelemetry , vol. 7 , 7 . https://doi.org/10.1186/s40317-019-0169-3 2050-3385 PURE: 258517854 PURE UUID: 2264f32e-c484-44e3-a852-22de8858bd84 RIS: urn:9EFDBE33155731F0FAE15B2EFFAE89F5 RIS: Sweeney2019 ORCID: /0000-0002-2581-1972/work/56861262 Scopus: 85063946899 WOS: 000696381300001 http://hdl.handle.net/10023/17477 https://doi.org/10.1186/s40317-019-0169-3 n00014-16-1-3089 Copyright © The Author(s) 2019. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Blue whale Detection Lunge Norm-jerk Prey capture Risso's dolphin QH301 Biology Signal Processing Animal Science and Zoology Instrumentation Computer Networks and Communications DAS QH301 Journal article 2019 ftstandrewserep https://doi.org/10.1186/s40317-019-0169-3 2023-06-13T18:28:14Z This project was supported by the U.S. Office of Naval Research (Grant No. N00014-16-1-3089). Tag deployments used here from the SOCAL-Behavioral Response Study were funded by the U.S. Office of Naval Research and Navy Living Marine Resources under multiple grants and contracts. Further funding was provided by the Kuipers Research Fellowship and the Calvin Alumni Association. TAM thanks partial support by CEAUL (funded by FCT—Fundação para a Ciência e a Tecnologia, Portugal, through the project UID/MAT/00006/2013). The desire of animal behaviorists for more flexible methods of conducting inter-study and inter-specific comparisons and meta-analysis of various animal behaviors compelled us to design an automated, animal behavior peak detection method that is potentially generalizable to a wide variety of data types, animals, and behaviors. We detected the times of feeding attempts by 12 Risso’s dolphins (Grampus griseus) and 36 blue whales (Balaenoptera musculus) using the norm-jerk (rate of change of acceleration) time series. The automated peak detection algorithm identified median true-positive rates of 0.881 for blue whale lunges and 0.410 for Risso’s dolphin prey capture attempts, with median false-positive rates of 0.096 and 0.007 and median miss rates of 0.113 and 0.314, respectively. Our study demonstrates that our peak detection method is efficient at automatically detecting animal behaviors from multisensor tag data with high accuracy for behaviors that are appropriately characterized by the data time series. Publisher PDF Peer reviewed Article in Journal/Newspaper Balaenoptera musculus Blue whale University of St Andrews: Digital Research Repository Calvin ENVELOPE(165.100,165.100,-71.283,-71.283) Kuipers ENVELOPE(161.400,161.400,-77.900,-77.900) Animal Biotelemetry 7 1 |
institution |
Open Polar |
collection |
University of St Andrews: Digital Research Repository |
op_collection_id |
ftstandrewserep |
language |
English |
topic |
Blue whale Detection Lunge Norm-jerk Prey capture Risso's dolphin QH301 Biology Signal Processing Animal Science and Zoology Instrumentation Computer Networks and Communications DAS QH301 |
spellingShingle |
Blue whale Detection Lunge Norm-jerk Prey capture Risso's dolphin QH301 Biology Signal Processing Animal Science and Zoology Instrumentation Computer Networks and Communications DAS QH301 Sweeney, David A. Deruiter, Stacy L. McNamara-Oh, Ye Joo Marques, Tiago A. Arranz, Patricia Calambokidis, John Automated peak detection method for behavioral event identification : detecting Balaenoptera musculus and Grampus griseus feeding attempts |
topic_facet |
Blue whale Detection Lunge Norm-jerk Prey capture Risso's dolphin QH301 Biology Signal Processing Animal Science and Zoology Instrumentation Computer Networks and Communications DAS QH301 |
description |
This project was supported by the U.S. Office of Naval Research (Grant No. N00014-16-1-3089). Tag deployments used here from the SOCAL-Behavioral Response Study were funded by the U.S. Office of Naval Research and Navy Living Marine Resources under multiple grants and contracts. Further funding was provided by the Kuipers Research Fellowship and the Calvin Alumni Association. TAM thanks partial support by CEAUL (funded by FCT—Fundação para a Ciência e a Tecnologia, Portugal, through the project UID/MAT/00006/2013). The desire of animal behaviorists for more flexible methods of conducting inter-study and inter-specific comparisons and meta-analysis of various animal behaviors compelled us to design an automated, animal behavior peak detection method that is potentially generalizable to a wide variety of data types, animals, and behaviors. We detected the times of feeding attempts by 12 Risso’s dolphins (Grampus griseus) and 36 blue whales (Balaenoptera musculus) using the norm-jerk (rate of change of acceleration) time series. The automated peak detection algorithm identified median true-positive rates of 0.881 for blue whale lunges and 0.410 for Risso’s dolphin prey capture attempts, with median false-positive rates of 0.096 and 0.007 and median miss rates of 0.113 and 0.314, respectively. Our study demonstrates that our peak detection method is efficient at automatically detecting animal behaviors from multisensor tag data with high accuracy for behaviors that are appropriately characterized by the data time series. Publisher PDF Peer reviewed |
author2 |
Office of Naval Research University of St Andrews. School of Mathematics and Statistics University of St Andrews. Scottish Oceans Institute University of St Andrews. Centre for Research into Ecological & Environmental Modelling |
format |
Article in Journal/Newspaper |
author |
Sweeney, David A. Deruiter, Stacy L. McNamara-Oh, Ye Joo Marques, Tiago A. Arranz, Patricia Calambokidis, John |
author_facet |
Sweeney, David A. Deruiter, Stacy L. McNamara-Oh, Ye Joo Marques, Tiago A. Arranz, Patricia Calambokidis, John |
author_sort |
Sweeney, David A. |
title |
Automated peak detection method for behavioral event identification : detecting Balaenoptera musculus and Grampus griseus feeding attempts |
title_short |
Automated peak detection method for behavioral event identification : detecting Balaenoptera musculus and Grampus griseus feeding attempts |
title_full |
Automated peak detection method for behavioral event identification : detecting Balaenoptera musculus and Grampus griseus feeding attempts |
title_fullStr |
Automated peak detection method for behavioral event identification : detecting Balaenoptera musculus and Grampus griseus feeding attempts |
title_full_unstemmed |
Automated peak detection method for behavioral event identification : detecting Balaenoptera musculus and Grampus griseus feeding attempts |
title_sort |
automated peak detection method for behavioral event identification : detecting balaenoptera musculus and grampus griseus feeding attempts |
publishDate |
2019 |
url |
http://hdl.handle.net/10023/17477 https://doi.org/10.1186/s40317-019-0169-3 |
long_lat |
ENVELOPE(165.100,165.100,-71.283,-71.283) ENVELOPE(161.400,161.400,-77.900,-77.900) |
geographic |
Calvin Kuipers |
geographic_facet |
Calvin Kuipers |
genre |
Balaenoptera musculus Blue whale |
genre_facet |
Balaenoptera musculus Blue whale |
op_relation |
Animal Biotelemetry Sweeney , D A , Deruiter , S L , McNamara-Oh , Y J , Marques , T A , Arranz , P & Calambokidis , J 2019 , ' Automated peak detection method for behavioral event identification : detecting Balaenoptera musculus and Grampus griseus feeding attempts ' , Animal Biotelemetry , vol. 7 , 7 . https://doi.org/10.1186/s40317-019-0169-3 2050-3385 PURE: 258517854 PURE UUID: 2264f32e-c484-44e3-a852-22de8858bd84 RIS: urn:9EFDBE33155731F0FAE15B2EFFAE89F5 RIS: Sweeney2019 ORCID: /0000-0002-2581-1972/work/56861262 Scopus: 85063946899 WOS: 000696381300001 http://hdl.handle.net/10023/17477 https://doi.org/10.1186/s40317-019-0169-3 n00014-16-1-3089 |
op_rights |
Copyright © The Author(s) 2019. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
op_doi |
https://doi.org/10.1186/s40317-019-0169-3 |
container_title |
Animal Biotelemetry |
container_volume |
7 |
container_issue |
1 |
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