Using identity calls to detect structure in acoustic datasets

1. Acoustic analyses can be powerful tools for illuminating structure within and between populations, especially for cryptic or difficult to access taxa. Acoustic repertoires are often compared using aggregate similarity measures across all calls of a particular type, but specific group identity cal...

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Published in:Methods in Ecology and Evolution
Main Authors: Hersh, Taylor A., Gero, Shane, Rendell, Luke, Whitehead, Hal
Format: Article in Journal/Newspaper
Language:English
Published: 2021
Subjects:
Online Access:https://research-portal.st-andrews.ac.uk/en/researchoutput/using-identity-calls-to-detect-structure-in-acoustic-datasets(2feaf8aa-8ed4-4b3a-bcd0-429625a64a1c).html
https://doi.org/10.1111/2041-210X.13644
https://research-repository.st-andrews.ac.uk/bitstream/10023/23286/1/Hersh_2021_MEE_Identitycalls_CC.pdf
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spelling ftunstandrewcris:oai:research-portal.st-andrews.ac.uk:publications/2feaf8aa-8ed4-4b3a-bcd0-429625a64a1c 2024-09-15T18:37:36+00:00 Using identity calls to detect structure in acoustic datasets Hersh, Taylor A. Gero, Shane Rendell, Luke Whitehead, Hal 2021-05-29 application/pdf https://research-portal.st-andrews.ac.uk/en/researchoutput/using-identity-calls-to-detect-structure-in-acoustic-datasets(2feaf8aa-8ed4-4b3a-bcd0-429625a64a1c).html https://doi.org/10.1111/2041-210X.13644 https://research-repository.st-andrews.ac.uk/bitstream/10023/23286/1/Hersh_2021_MEE_Identitycalls_CC.pdf eng eng https://research-portal.st-andrews.ac.uk/en/researchoutput/using-identity-calls-to-detect-structure-in-acoustic-datasets(2feaf8aa-8ed4-4b3a-bcd0-429625a64a1c).html info:eu-repo/semantics/openAccess Hersh , T A , Gero , S , Rendell , L & Whitehead , H 2021 , ' Using identity calls to detect structure in acoustic datasets ' , Methods in Ecology and Evolution , vol. Early View . https://doi.org/10.1111/2041-210X.13644 Bioinformatics Community ecology Conservation Diversity Population ecology article 2021 ftunstandrewcris https://doi.org/10.1111/2041-210X.13644 2024-07-10T23:32:29Z 1. Acoustic analyses can be powerful tools for illuminating structure within and between populations, especially for cryptic or difficult to access taxa. Acoustic repertoires are often compared using aggregate similarity measures across all calls of a particular type, but specific group identity calls may more clearly delineate structure in some taxa. 2. We present a new method-the identity call method-that estimates the number of acoustically distinct subdivisions in a set of repertoires and identifies call types that characterize those subdivisions. The method uses contaminated mixture models to identify call types, assigning each call a probability of belonging to each type. Repertoires are hierarchically clustered based on similarities in call type usage, producing a dendrogram with 'identity clades' of repertoires and the (identity calls) that best characterize each clade. We validated this approach using acoustic data from sperm whales, grey-breasted wood-wrens, and Australian field crickets, and ran a suite of tests to assess parameter sensitivity. 3. For all taxa, the method detected diagnostic signals (identity calls) and structure (identity clades; sperm whale subpopulations, wren subspecies, and cricket species) that were consistent with past research. Some datasets were more sensitive to parameter variation than others, which may reflect real uncertainty or biological variability in the taxa examined. We recommend that users perform comparative analyses of different parameter combinations to determine which portions of the dendrogram warrant careful versus confident interpretation. 4. The presence of group-characteristic identity calls does not necessarily mean animals perceive them as such. Fine scale experiments like playbacks are a key next step to understand call perception and function. This method can help inform such studies by identifying calls that may be salient to animals and are good candidates for investigation or playback stimuli. For cryptic or difficult to access taxa with ... Article in Journal/Newspaper Sperm whale University of St Andrews: Research Portal Methods in Ecology and Evolution 12 9 1668 1678
institution Open Polar
collection University of St Andrews: Research Portal
op_collection_id ftunstandrewcris
language English
topic Bioinformatics
Community ecology
Conservation
Diversity
Population ecology
spellingShingle Bioinformatics
Community ecology
Conservation
Diversity
Population ecology
Hersh, Taylor A.
Gero, Shane
Rendell, Luke
Whitehead, Hal
Using identity calls to detect structure in acoustic datasets
topic_facet Bioinformatics
Community ecology
Conservation
Diversity
Population ecology
description 1. Acoustic analyses can be powerful tools for illuminating structure within and between populations, especially for cryptic or difficult to access taxa. Acoustic repertoires are often compared using aggregate similarity measures across all calls of a particular type, but specific group identity calls may more clearly delineate structure in some taxa. 2. We present a new method-the identity call method-that estimates the number of acoustically distinct subdivisions in a set of repertoires and identifies call types that characterize those subdivisions. The method uses contaminated mixture models to identify call types, assigning each call a probability of belonging to each type. Repertoires are hierarchically clustered based on similarities in call type usage, producing a dendrogram with 'identity clades' of repertoires and the (identity calls) that best characterize each clade. We validated this approach using acoustic data from sperm whales, grey-breasted wood-wrens, and Australian field crickets, and ran a suite of tests to assess parameter sensitivity. 3. For all taxa, the method detected diagnostic signals (identity calls) and structure (identity clades; sperm whale subpopulations, wren subspecies, and cricket species) that were consistent with past research. Some datasets were more sensitive to parameter variation than others, which may reflect real uncertainty or biological variability in the taxa examined. We recommend that users perform comparative analyses of different parameter combinations to determine which portions of the dendrogram warrant careful versus confident interpretation. 4. The presence of group-characteristic identity calls does not necessarily mean animals perceive them as such. Fine scale experiments like playbacks are a key next step to understand call perception and function. This method can help inform such studies by identifying calls that may be salient to animals and are good candidates for investigation or playback stimuli. For cryptic or difficult to access taxa with ...
format Article in Journal/Newspaper
author Hersh, Taylor A.
Gero, Shane
Rendell, Luke
Whitehead, Hal
author_facet Hersh, Taylor A.
Gero, Shane
Rendell, Luke
Whitehead, Hal
author_sort Hersh, Taylor A.
title Using identity calls to detect structure in acoustic datasets
title_short Using identity calls to detect structure in acoustic datasets
title_full Using identity calls to detect structure in acoustic datasets
title_fullStr Using identity calls to detect structure in acoustic datasets
title_full_unstemmed Using identity calls to detect structure in acoustic datasets
title_sort using identity calls to detect structure in acoustic datasets
publishDate 2021
url https://research-portal.st-andrews.ac.uk/en/researchoutput/using-identity-calls-to-detect-structure-in-acoustic-datasets(2feaf8aa-8ed4-4b3a-bcd0-429625a64a1c).html
https://doi.org/10.1111/2041-210X.13644
https://research-repository.st-andrews.ac.uk/bitstream/10023/23286/1/Hersh_2021_MEE_Identitycalls_CC.pdf
genre Sperm whale
genre_facet Sperm whale
op_source Hersh , T A , Gero , S , Rendell , L & Whitehead , H 2021 , ' Using identity calls to detect structure in acoustic datasets ' , Methods in Ecology and Evolution , vol. Early View . https://doi.org/10.1111/2041-210X.13644
op_relation https://research-portal.st-andrews.ac.uk/en/researchoutput/using-identity-calls-to-detect-structure-in-acoustic-datasets(2feaf8aa-8ed4-4b3a-bcd0-429625a64a1c).html
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