Network analysis reveals underlying syntactic features in a vocally learnt mammalian display, humpback whale song

J.A.A. was funded by an Australian Government Research Training Program Scholarship and the Australian American Association University of Queensland Fellowship. E.C.G. was funded by a Royal Society Newton International Fellowship and a Royal Society University Research Fellowship. HARC was funded by...

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Published in:Proceedings of the Royal Society B: Biological Sciences
Main Authors: Allen, Jenny A., Garland, Ellen C., Dunlop, Rebecca A., Noad, Michael J.
Other Authors: The Royal Society, University of St Andrews. School of Biology, University of St Andrews. Centre for Biological Diversity, University of St Andrews. Sea Mammal Research Unit, University of St Andrews. Centre for Social Learning & Cognitive Evolution
Format: Article in Journal/Newspaper
Language:English
Published: 2020
Subjects:
DAS
BDC
R2C
Online Access:http://hdl.handle.net/10023/19288
https://doi.org/10.1098/rspb.2019.2014
id ftstandrewserep:oai:research-repository.st-andrews.ac.uk:10023/19288
record_format openpolar
institution Open Polar
collection University of St Andrews: Digital Research Repository
op_collection_id ftstandrewserep
language English
topic Vocal learning
Network modelling
Syntax
Humpback whale
Song
QH301 Biology
DAS
BDC
R2C
QH301
spellingShingle Vocal learning
Network modelling
Syntax
Humpback whale
Song
QH301 Biology
DAS
BDC
R2C
QH301
Allen, Jenny A.
Garland, Ellen C.
Dunlop, Rebecca A.
Noad, Michael J.
Network analysis reveals underlying syntactic features in a vocally learnt mammalian display, humpback whale song
topic_facet Vocal learning
Network modelling
Syntax
Humpback whale
Song
QH301 Biology
DAS
BDC
R2C
QH301
description J.A.A. was funded by an Australian Government Research Training Program Scholarship and the Australian American Association University of Queensland Fellowship. E.C.G. was funded by a Royal Society Newton International Fellowship and a Royal Society University Research Fellowship. HARC was funded by the US Office of Naval Research, the Australian Defence Science and Technology Organisation, and the Australian Marine Mammal Centre. BRAHSS was funded by the E&P Sound and Marine Life Joint Industry Programme and the US Bureau of Ocean Energy Management. Vocal communication systems have a set of rules that govern the arrangement of acoustic signals, broadly defined as ‘syntax’. However, there is a limited understanding of potentially shared or analogous rules across vocal displays in different taxa. Recent work on songbirds has investigated syntax using network-based modelling. This technique quantifies features such as connectivity (adjacent signals in a sequence) and recurring patterns. Here, we apply network-based modelling to the complex, hierarchically structured songs of humpback whales (Megaptera novaeangliae) from east Australia. Given the song's annual evolving pattern and the cultural conformity of males within a population, network modelling captured the patterns of multiple song types over 13 consecutive years. Song arrangements in each year displayed clear ‘small-world’ network structure, characterized by clusters of highly connected sounds. Transitions between these connected sounds further suggested a combination of both structural stability and variability. Small-world network structure within humpback songs may facilitate the characteristic and persistent vocal learning observed. Similar small-world structures and transition patterns are found in several birdsong displays, indicating common syntactic patterns among vocal learning in multiple taxa. Understanding the syntactic rules governing vocal displays in multiple, independently evolving lineages may indicate what rules or structural ...
author2 The Royal Society
University of St Andrews. School of Biology
University of St Andrews. Centre for Biological Diversity
University of St Andrews. Sea Mammal Research Unit
University of St Andrews. Centre for Social Learning & Cognitive Evolution
format Article in Journal/Newspaper
author Allen, Jenny A.
Garland, Ellen C.
Dunlop, Rebecca A.
Noad, Michael J.
author_facet Allen, Jenny A.
Garland, Ellen C.
Dunlop, Rebecca A.
Noad, Michael J.
author_sort Allen, Jenny A.
title Network analysis reveals underlying syntactic features in a vocally learnt mammalian display, humpback whale song
title_short Network analysis reveals underlying syntactic features in a vocally learnt mammalian display, humpback whale song
title_full Network analysis reveals underlying syntactic features in a vocally learnt mammalian display, humpback whale song
title_fullStr Network analysis reveals underlying syntactic features in a vocally learnt mammalian display, humpback whale song
title_full_unstemmed Network analysis reveals underlying syntactic features in a vocally learnt mammalian display, humpback whale song
title_sort network analysis reveals underlying syntactic features in a vocally learnt mammalian display, humpback whale song
publishDate 2020
url http://hdl.handle.net/10023/19288
https://doi.org/10.1098/rspb.2019.2014
geographic Queensland
geographic_facet Queensland
genre Humpback Whale
Megaptera novaeangliae
genre_facet Humpback Whale
Megaptera novaeangliae
op_relation Proceedings of the Royal Society B: Biological Sciences
Allen , J A , Garland , E C , Dunlop , R A & Noad , M J 2019 , ' Network analysis reveals underlying syntactic features in a vocally learnt mammalian display, humpback whale song ' , Proceedings of the Royal Society B: Biological Sciences , vol. 286 , no. 1917 , 20192014 . https://doi.org/10.1098/rspb.2019.2014
0962-8452
PURE: 265420428
PURE UUID: e80ce595-4020-4a6b-ac9e-17b88ca3f7c9
RIS: urn:7095BA96094B8BE87927405E5837D458
Scopus: 85076825929
ORCID: /0000-0002-8240-1267/work/67167736
WOS: 000504313100007
http://hdl.handle.net/10023/19288
https://doi.org/10.1098/rspb.2019.2014
NF140667
UF160081
op_rights Copyright © 2019 The Author(s). Published by the Royal Society. All rights reserved. This work has been made available online in accordance with publisher policies or with permission. Permission for further reuse of this content should be sought from the publisher or the rights holder. This is the author created accepted manuscript following peer review and may differ slightly from the final published version. The final published version of this work is available at https://doi.org/10.1098/rspb.2019.2014
op_doi https://doi.org/10.1098/rspb.2019.2014
container_title Proceedings of the Royal Society B: Biological Sciences
container_volume 286
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spelling ftstandrewserep:oai:research-repository.st-andrews.ac.uk:10023/19288 2023-07-02T03:32:32+02:00 Network analysis reveals underlying syntactic features in a vocally learnt mammalian display, humpback whale song Allen, Jenny A. Garland, Ellen C. Dunlop, Rebecca A. Noad, Michael J. The Royal Society University of St Andrews. School of Biology University of St Andrews. Centre for Biological Diversity University of St Andrews. Sea Mammal Research Unit University of St Andrews. Centre for Social Learning & Cognitive Evolution 2020-01-15T11:30:04Z application/pdf http://hdl.handle.net/10023/19288 https://doi.org/10.1098/rspb.2019.2014 eng eng Proceedings of the Royal Society B: Biological Sciences Allen , J A , Garland , E C , Dunlop , R A & Noad , M J 2019 , ' Network analysis reveals underlying syntactic features in a vocally learnt mammalian display, humpback whale song ' , Proceedings of the Royal Society B: Biological Sciences , vol. 286 , no. 1917 , 20192014 . https://doi.org/10.1098/rspb.2019.2014 0962-8452 PURE: 265420428 PURE UUID: e80ce595-4020-4a6b-ac9e-17b88ca3f7c9 RIS: urn:7095BA96094B8BE87927405E5837D458 Scopus: 85076825929 ORCID: /0000-0002-8240-1267/work/67167736 WOS: 000504313100007 http://hdl.handle.net/10023/19288 https://doi.org/10.1098/rspb.2019.2014 NF140667 UF160081 Copyright © 2019 The Author(s). Published by the Royal Society. All rights reserved. This work has been made available online in accordance with publisher policies or with permission. Permission for further reuse of this content should be sought from the publisher or the rights holder. This is the author created accepted manuscript following peer review and may differ slightly from the final published version. The final published version of this work is available at https://doi.org/10.1098/rspb.2019.2014 Vocal learning Network modelling Syntax Humpback whale Song QH301 Biology DAS BDC R2C QH301 Journal article 2020 ftstandrewserep https://doi.org/10.1098/rspb.2019.2014 2023-06-13T18:30:03Z J.A.A. was funded by an Australian Government Research Training Program Scholarship and the Australian American Association University of Queensland Fellowship. E.C.G. was funded by a Royal Society Newton International Fellowship and a Royal Society University Research Fellowship. HARC was funded by the US Office of Naval Research, the Australian Defence Science and Technology Organisation, and the Australian Marine Mammal Centre. BRAHSS was funded by the E&P Sound and Marine Life Joint Industry Programme and the US Bureau of Ocean Energy Management. Vocal communication systems have a set of rules that govern the arrangement of acoustic signals, broadly defined as ‘syntax’. However, there is a limited understanding of potentially shared or analogous rules across vocal displays in different taxa. Recent work on songbirds has investigated syntax using network-based modelling. This technique quantifies features such as connectivity (adjacent signals in a sequence) and recurring patterns. Here, we apply network-based modelling to the complex, hierarchically structured songs of humpback whales (Megaptera novaeangliae) from east Australia. Given the song's annual evolving pattern and the cultural conformity of males within a population, network modelling captured the patterns of multiple song types over 13 consecutive years. Song arrangements in each year displayed clear ‘small-world’ network structure, characterized by clusters of highly connected sounds. Transitions between these connected sounds further suggested a combination of both structural stability and variability. Small-world network structure within humpback songs may facilitate the characteristic and persistent vocal learning observed. Similar small-world structures and transition patterns are found in several birdsong displays, indicating common syntactic patterns among vocal learning in multiple taxa. Understanding the syntactic rules governing vocal displays in multiple, independently evolving lineages may indicate what rules or structural ... Article in Journal/Newspaper Humpback Whale Megaptera novaeangliae University of St Andrews: Digital Research Repository Queensland Proceedings of the Royal Society B: Biological Sciences 286 1917 20192014