An analysis of pilot whale vocalization activity using hidden Markov models
Vocalizations of cetaceans form a key component of their social interactions. Such vocalization activity is driven by the behavioral states of the whales, which are not directly observable, so that latent-state models are natural candidates for modeling empirical data on vocalizations. In this paper...
Published in: | The Journal of the Acoustical Society of America |
---|---|
Main Authors: | , , , |
Other Authors: | , , |
Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
2017
|
Subjects: | |
Online Access: | https://hdl.handle.net/10023/11194 https://doi.org/10.1121/1.4973624 |
id |
ftstandrewserep:oai:research-repository.st-andrews.ac.uk:10023/11194 |
---|---|
record_format |
openpolar |
spelling |
ftstandrewserep:oai:research-repository.st-andrews.ac.uk:10023/11194 2024-06-23T07:54:29+00:00 An analysis of pilot whale vocalization activity using hidden Markov models Popov, Valentin Mina Langrock, Roland De Ruiter, Stacy Lynn Visser, Fleur Office of Naval Research University of St Andrews. Statistics University of St Andrews. Centre for Research into Ecological & Environmental Modelling 2017-07-12 833809 application/pdf https://hdl.handle.net/10023/11194 https://doi.org/10.1121/1.4973624 eng eng Journal of the Acoustical Society of America 248904926 33319143-75fc-4fb8-be55-5b2c0951aaf5 85009446520 000395308700030 Popov , V M , Langrock , R , De Ruiter , S L & Visser , F 2017 , ' An analysis of pilot whale vocalization activity using hidden Markov models ' , Journal of the Acoustical Society of America , vol. 141 , no. 1 , pp. 159-171 . https://doi.org/10.1121/1.4973624 0001-4966 https://hdl.handle.net/10023/11194 doi:10.1121/1.4973624 N00014-12-1-0204 GC Oceanography QH301 Biology QA Mathematics QL Zoology NDAS GC QH301 QA QL Journal article 2017 ftstandrewserep https://doi.org/10.1121/1.4973624 2024-06-11T23:58:14Z Vocalizations of cetaceans form a key component of their social interactions. Such vocalization activity is driven by the behavioral states of the whales, which are not directly observable, so that latent-state models are natural candidates for modeling empirical data on vocalizations. In this paper, we use hidden Markov models to analyze calling activity of long-finned pilot whales (Globicephala melas) recorded over three years in the Vestfjord basin off Lofoten, Norway. Baseline models are used to motivate the use of three states, while more complex models are fit to study the influence of covariates on the state-switching dynamics. Our analysis demonstrates the potential usefulness of hidden Markov models in concisely yet accurately describing the stochastic patterns found in animal communication data, thereby providing a framework for drawing meaningful biological inference. Peer reviewed Article in Journal/Newspaper Lofoten University of St Andrews: Digital Research Repository Lofoten Norway Vestfjord ENVELOPE(-28.750,-28.750,70.500,70.500) The Journal of the Acoustical Society of America 141 1 159 171 |
institution |
Open Polar |
collection |
University of St Andrews: Digital Research Repository |
op_collection_id |
ftstandrewserep |
language |
English |
topic |
GC Oceanography QH301 Biology QA Mathematics QL Zoology NDAS GC QH301 QA QL |
spellingShingle |
GC Oceanography QH301 Biology QA Mathematics QL Zoology NDAS GC QH301 QA QL Popov, Valentin Mina Langrock, Roland De Ruiter, Stacy Lynn Visser, Fleur An analysis of pilot whale vocalization activity using hidden Markov models |
topic_facet |
GC Oceanography QH301 Biology QA Mathematics QL Zoology NDAS GC QH301 QA QL |
description |
Vocalizations of cetaceans form a key component of their social interactions. Such vocalization activity is driven by the behavioral states of the whales, which are not directly observable, so that latent-state models are natural candidates for modeling empirical data on vocalizations. In this paper, we use hidden Markov models to analyze calling activity of long-finned pilot whales (Globicephala melas) recorded over three years in the Vestfjord basin off Lofoten, Norway. Baseline models are used to motivate the use of three states, while more complex models are fit to study the influence of covariates on the state-switching dynamics. Our analysis demonstrates the potential usefulness of hidden Markov models in concisely yet accurately describing the stochastic patterns found in animal communication data, thereby providing a framework for drawing meaningful biological inference. Peer reviewed |
author2 |
Office of Naval Research University of St Andrews. Statistics University of St Andrews. Centre for Research into Ecological & Environmental Modelling |
format |
Article in Journal/Newspaper |
author |
Popov, Valentin Mina Langrock, Roland De Ruiter, Stacy Lynn Visser, Fleur |
author_facet |
Popov, Valentin Mina Langrock, Roland De Ruiter, Stacy Lynn Visser, Fleur |
author_sort |
Popov, Valentin Mina |
title |
An analysis of pilot whale vocalization activity using hidden Markov models |
title_short |
An analysis of pilot whale vocalization activity using hidden Markov models |
title_full |
An analysis of pilot whale vocalization activity using hidden Markov models |
title_fullStr |
An analysis of pilot whale vocalization activity using hidden Markov models |
title_full_unstemmed |
An analysis of pilot whale vocalization activity using hidden Markov models |
title_sort |
analysis of pilot whale vocalization activity using hidden markov models |
publishDate |
2017 |
url |
https://hdl.handle.net/10023/11194 https://doi.org/10.1121/1.4973624 |
long_lat |
ENVELOPE(-28.750,-28.750,70.500,70.500) |
geographic |
Lofoten Norway Vestfjord |
geographic_facet |
Lofoten Norway Vestfjord |
genre |
Lofoten |
genre_facet |
Lofoten |
op_relation |
Journal of the Acoustical Society of America 248904926 33319143-75fc-4fb8-be55-5b2c0951aaf5 85009446520 000395308700030 Popov , V M , Langrock , R , De Ruiter , S L & Visser , F 2017 , ' An analysis of pilot whale vocalization activity using hidden Markov models ' , Journal of the Acoustical Society of America , vol. 141 , no. 1 , pp. 159-171 . https://doi.org/10.1121/1.4973624 0001-4966 https://hdl.handle.net/10023/11194 doi:10.1121/1.4973624 N00014-12-1-0204 |
op_doi |
https://doi.org/10.1121/1.4973624 |
container_title |
The Journal of the Acoustical Society of America |
container_volume |
141 |
container_issue |
1 |
container_start_page |
159 |
op_container_end_page |
171 |
_version_ |
1802646648531189760 |