Using agent-based models to understand the role of individuals in the song evolution of humpback whales (Megaptera novaeangliae)
Male humpback whales produce hierarchically structured songs, primarily during the breeding season. These songs gradually change over the course of the breeding season, and are generally population specific. However, instances have been recorded of more rapid song changes where the song of a populat...
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ftstandrewserep:oai:research-repository.st-andrews.ac.uk:10023/12929 2023-07-02T03:32:32+02:00 Using agent-based models to understand the role of individuals in the song evolution of humpback whales (Megaptera novaeangliae) Mcloughlin, Michael Lamoni, Luca Garland, Ellen C. Ingram, Simon Kirke, Alexis Noad, Michael J. Rendell, Luke Miranda, Eduardo University of St Andrews. School of Biology University of St Andrews. Sea Mammal Research Unit University of St Andrews. Centre for Social Learning & Cognitive Evolution University of St Andrews. Centre for Biological Diversity 2018-03-13T11:30:05Z 17 application/pdf http://hdl.handle.net/10023/12929 https://doi.org/10.1177/2059204318757021 eng eng Music & Science Mcloughlin , M , Lamoni , L , Garland , E C , Ingram , S , Kirke , A , Noad , M J , Rendell , L & Miranda , E 2018 , ' Using agent-based models to understand the role of individuals in the song evolution of humpback whales ( Megaptera novaeangliae ) ' , Music & Science , vol. 1 . https://doi.org/10.1177/2059204318757021 2059-2043 PURE: 252136011 PURE UUID: b5a079c9-0aaa-4b25-9d43-4d474bb2b6f7 ORCID: /0000-0002-8240-1267/work/49580206 ORCID: /0000-0002-1121-9142/work/60428002 Scopus: 85073217770 http://hdl.handle.net/10023/12929 https://doi.org/10.1177/2059204318757021 © The Author(s) 2018. This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (http://www.creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage). Agent-based model Humpback whale Song Song evolution Vocal learning QH301 Biology NDAS QH301 Journal article 2018 ftstandrewserep https://doi.org/10.1177/2059204318757021 2023-06-13T18:31:08Z Male humpback whales produce hierarchically structured songs, primarily during the breeding season. These songs gradually change over the course of the breeding season, and are generally population specific. However, instances have been recorded of more rapid song changes where the song of a population can be replaced by the song of an adjacent population. The mechanisms that drive these changes are not currently understood, and difficulties in tracking individual whales over long migratory routes mean field studies to understand these mechanisms are not feasible. In order to help understand the mechanisms that drive these song changes, we present here a spatially explicit agent-based model inspired by methods used in computer music research. We model the migratory patterns of humpback whales, a simple song learning and production method coupled with sound transmission loss, and how often singing occurs during these migratory cycles. This model is then extended to include learning biases that may be responsible for driving changes in the song, such as a bias towards novel song, production errors, and the coupling of novel song bias and production errors. While none of the methods showed population song replacement, our model shows that shared feeding grounds where conspecifics are able to mix provides key opportunities for cultural transmission, and production errors facilitated gradually changing songs. Our results point towards other learning biases being necessary in order for population song replacement to occur. Publisher PDF Peer reviewed Article in Journal/Newspaper Humpback Whale Megaptera novaeangliae University of St Andrews: Digital Research Repository Music & Science 1 205920431875702 |
institution |
Open Polar |
collection |
University of St Andrews: Digital Research Repository |
op_collection_id |
ftstandrewserep |
language |
English |
topic |
Agent-based model Humpback whale Song Song evolution Vocal learning QH301 Biology NDAS QH301 |
spellingShingle |
Agent-based model Humpback whale Song Song evolution Vocal learning QH301 Biology NDAS QH301 Mcloughlin, Michael Lamoni, Luca Garland, Ellen C. Ingram, Simon Kirke, Alexis Noad, Michael J. Rendell, Luke Miranda, Eduardo Using agent-based models to understand the role of individuals in the song evolution of humpback whales (Megaptera novaeangliae) |
topic_facet |
Agent-based model Humpback whale Song Song evolution Vocal learning QH301 Biology NDAS QH301 |
description |
Male humpback whales produce hierarchically structured songs, primarily during the breeding season. These songs gradually change over the course of the breeding season, and are generally population specific. However, instances have been recorded of more rapid song changes where the song of a population can be replaced by the song of an adjacent population. The mechanisms that drive these changes are not currently understood, and difficulties in tracking individual whales over long migratory routes mean field studies to understand these mechanisms are not feasible. In order to help understand the mechanisms that drive these song changes, we present here a spatially explicit agent-based model inspired by methods used in computer music research. We model the migratory patterns of humpback whales, a simple song learning and production method coupled with sound transmission loss, and how often singing occurs during these migratory cycles. This model is then extended to include learning biases that may be responsible for driving changes in the song, such as a bias towards novel song, production errors, and the coupling of novel song bias and production errors. While none of the methods showed population song replacement, our model shows that shared feeding grounds where conspecifics are able to mix provides key opportunities for cultural transmission, and production errors facilitated gradually changing songs. Our results point towards other learning biases being necessary in order for population song replacement to occur. Publisher PDF Peer reviewed |
author2 |
University of St Andrews. School of Biology University of St Andrews. Sea Mammal Research Unit University of St Andrews. Centre for Social Learning & Cognitive Evolution University of St Andrews. Centre for Biological Diversity |
format |
Article in Journal/Newspaper |
author |
Mcloughlin, Michael Lamoni, Luca Garland, Ellen C. Ingram, Simon Kirke, Alexis Noad, Michael J. Rendell, Luke Miranda, Eduardo |
author_facet |
Mcloughlin, Michael Lamoni, Luca Garland, Ellen C. Ingram, Simon Kirke, Alexis Noad, Michael J. Rendell, Luke Miranda, Eduardo |
author_sort |
Mcloughlin, Michael |
title |
Using agent-based models to understand the role of individuals in the song evolution of humpback whales (Megaptera novaeangliae) |
title_short |
Using agent-based models to understand the role of individuals in the song evolution of humpback whales (Megaptera novaeangliae) |
title_full |
Using agent-based models to understand the role of individuals in the song evolution of humpback whales (Megaptera novaeangliae) |
title_fullStr |
Using agent-based models to understand the role of individuals in the song evolution of humpback whales (Megaptera novaeangliae) |
title_full_unstemmed |
Using agent-based models to understand the role of individuals in the song evolution of humpback whales (Megaptera novaeangliae) |
title_sort |
using agent-based models to understand the role of individuals in the song evolution of humpback whales (megaptera novaeangliae) |
publishDate |
2018 |
url |
http://hdl.handle.net/10023/12929 https://doi.org/10.1177/2059204318757021 |
genre |
Humpback Whale Megaptera novaeangliae |
genre_facet |
Humpback Whale Megaptera novaeangliae |
op_relation |
Music & Science Mcloughlin , M , Lamoni , L , Garland , E C , Ingram , S , Kirke , A , Noad , M J , Rendell , L & Miranda , E 2018 , ' Using agent-based models to understand the role of individuals in the song evolution of humpback whales ( Megaptera novaeangliae ) ' , Music & Science , vol. 1 . https://doi.org/10.1177/2059204318757021 2059-2043 PURE: 252136011 PURE UUID: b5a079c9-0aaa-4b25-9d43-4d474bb2b6f7 ORCID: /0000-0002-8240-1267/work/49580206 ORCID: /0000-0002-1121-9142/work/60428002 Scopus: 85073217770 http://hdl.handle.net/10023/12929 https://doi.org/10.1177/2059204318757021 |
op_rights |
© The Author(s) 2018. This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (http://www.creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage). |
op_doi |
https://doi.org/10.1177/2059204318757021 |
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Music & Science |
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