Machine learning reveals cryptic dialects that explain mate choice in a songbird

Lade...
Vorschaubild
Dateien
Wang_2-nlzpdr7he9461.pdf
Wang_2-nlzpdr7he9461.pdfGröße: 1.82 MBDownloads: 80
Datum
2022
Autor:innen
Wang, Daiping
Forstmeier, Wolfgang
Martin, Katrin
Pei, Yifan
Klarevas-Irby, James A.
Herausgeber:innen
Kontakt
ISSN der Zeitschrift
Electronic ISSN
ISBN
Bibliografische Daten
Verlag
Schriftenreihe
Auflagebezeichnung
ArXiv-ID
Internationale Patentnummer
Link zur Lizenz
Angaben zur Forschungsförderung
Projekt
Open Access-Veröffentlichung
Open Access Gold
Core Facility der Universität Konstanz
Gesperrt bis
Titel in einer weiteren Sprache
Publikationstyp
Zeitschriftenartikel
Publikationsstatus
Published
Erschienen in
Nature Communications. Nature Publishing Group. 2022, 13, 1630. eISSN 2041-1723. Available under: doi: 10.1038/s41467-022-28881-w
Zusammenfassung

Culturally transmitted communication signals – such as human language or bird song – can change over time through cultural drift, and the resulting dialects may consequently enhance the separation of populations. However, the emergence of song dialects has been considered unlikely when songs are highly individual-specific, as in the zebra finch (Taeniopygia guttata). Here we show that machine learning can nevertheless distinguish the songs from multiple captive zebra finch populations with remarkable precision, and that ‘cryptic song dialects’ predict strong assortative mating in this species. We examine mating patterns across three consecutive generations using captive populations that have evolved in isolation for about 100 generations. We cross-fostered eggs within and between these populations and used an automated barcode tracking system to quantify social interactions. We find that females preferentially pair with males whose song resembles that of the females’ adolescent peers. Our study shows evidence that in zebra finches, a model species for song learning, individuals are sensitive to differences in song that have hitherto remained unnoticed by researchers.

Zusammenfassung in einer weiteren Sprache
Fachgebiet (DDC)
570 Biowissenschaften, Biologie
Schlagwörter
Konferenz
Rezension
undefined / . - undefined, undefined
Forschungsvorhaben
Organisationseinheiten
Zeitschriftenheft
Datensätze
Zitieren
ISO 690WANG, Daiping, Wolfgang FORSTMEIER, Damien R. FARINE, Adriana A. MALDONADO CHAPARRO, Katrin MARTIN, Yifan PEI, Gustavo ALARCON NIETO, James A. KLAREVAS-IRBY, Shouwen MA, Lucy M. APLIN, Bart KEMPENAERS, 2022. Machine learning reveals cryptic dialects that explain mate choice in a songbird. In: Nature Communications. Nature Publishing Group. 2022, 13, 1630. eISSN 2041-1723. Available under: doi: 10.1038/s41467-022-28881-w
BibTex
@article{Wang2022-03-28Machi-57174,
  year={2022},
  doi={10.1038/s41467-022-28881-w},
  title={Machine learning reveals cryptic dialects that explain mate choice in a songbird},
  volume={13},
  journal={Nature Communications},
  author={Wang, Daiping and Forstmeier, Wolfgang and Farine, Damien R. and Maldonado Chaparro, Adriana A. and Martin, Katrin and Pei, Yifan and Alarcon Nieto, Gustavo and Klarevas-Irby, James A. and Ma, Shouwen and Aplin, Lucy M. and Kempenaers, Bart},
  note={Article Number: 1630}
}
RDF
<rdf:RDF
    xmlns:dcterms="http://purl.org/dc/terms/"
    xmlns:dc="http://purl.org/dc/elements/1.1/"
    xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"
    xmlns:bibo="http://purl.org/ontology/bibo/"
    xmlns:dspace="http://digital-repositories.org/ontologies/dspace/0.1.0#"
    xmlns:foaf="http://xmlns.com/foaf/0.1/"
    xmlns:void="http://rdfs.org/ns/void#"
    xmlns:xsd="http://www.w3.org/2001/XMLSchema#" > 
  <rdf:Description rdf:about="https://kops.uni-konstanz.de/server/rdf/resource/123456789/57174">
    <dc:creator>Martin, Katrin</dc:creator>
    <dcterms:rights rdf:resource="http://creativecommons.org/licenses/by/4.0/"/>
    <dc:contributor>Kempenaers, Bart</dc:contributor>
    <dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/28"/>
    <bibo:uri rdf:resource="https://kops.uni-konstanz.de/handle/123456789/57174"/>
    <dc:contributor>Aplin, Lucy M.</dc:contributor>
    <dc:creator>Kempenaers, Bart</dc:creator>
    <dc:creator>Ma, Shouwen</dc:creator>
    <dc:creator>Wang, Daiping</dc:creator>
    <dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/28"/>
    <dcterms:hasPart rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/57174/1/Wang_2-nlzpdr7he9461.pdf"/>
    <dc:creator>Pei, Yifan</dc:creator>
    <dc:language>eng</dc:language>
    <dc:creator>Forstmeier, Wolfgang</dc:creator>
    <dc:creator>Aplin, Lucy M.</dc:creator>
    <dc:creator>Alarcon Nieto, Gustavo</dc:creator>
    <dc:contributor>Wang, Daiping</dc:contributor>
    <dc:contributor>Forstmeier, Wolfgang</dc:contributor>
    <dc:contributor>Pei, Yifan</dc:contributor>
    <dc:contributor>Farine, Damien R.</dc:contributor>
    <dc:contributor>Alarcon Nieto, Gustavo</dc:contributor>
    <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2022-04-05T11:35:57Z</dc:date>
    <dcterms:title>Machine learning reveals cryptic dialects that explain mate choice in a songbird</dcterms:title>
    <dc:creator>Farine, Damien R.</dc:creator>
    <dcterms:abstract xml:lang="eng">Culturally transmitted communication signals – such as human language or bird song – can change over time through cultural drift, and the resulting dialects may consequently enhance the separation of populations. However, the emergence of song dialects has been considered unlikely when songs are highly individual-specific, as in the zebra finch (Taeniopygia guttata). Here we show that machine learning can nevertheless distinguish the songs from multiple captive zebra finch populations with remarkable precision, and that ‘cryptic song dialects’ predict strong assortative mating in this species. We examine mating patterns across three consecutive generations using captive populations that have evolved in isolation for about 100 generations. We cross-fostered eggs within and between these populations and used an automated barcode tracking system to quantify social interactions. We find that females preferentially pair with males whose song resembles that of the females’ adolescent peers. Our study shows evidence that in zebra finches, a model species for song learning, individuals are sensitive to differences in song that have hitherto remained unnoticed by researchers.</dcterms:abstract>
    <dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/43615"/>
    <dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/43615"/>
    <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/>
    <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2022-04-05T11:35:57Z</dcterms:available>
    <dc:contributor>Ma, Shouwen</dc:contributor>
    <dc:contributor>Klarevas-Irby, James A.</dc:contributor>
    <dc:contributor>Martin, Katrin</dc:contributor>
    <dc:creator>Maldonado Chaparro, Adriana A.</dc:creator>
    <dc:rights>Attribution 4.0 International</dc:rights>
    <foaf:homepage rdf:resource="http://localhost:8080/"/>
    <dc:creator>Klarevas-Irby, James A.</dc:creator>
    <dc:contributor>Maldonado Chaparro, Adriana A.</dc:contributor>
    <dcterms:issued>2022-03-28</dcterms:issued>
    <dspace:hasBitstream rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/57174/1/Wang_2-nlzpdr7he9461.pdf"/>
  </rdf:Description>
</rdf:RDF>
Interner Vermerk
xmlui.Submission.submit.DescribeStep.inputForms.label.kops_note_fromSubmitter
Kontakt
URL der Originalveröffentl.
Prüfdatum der URL
Prüfungsdatum der Dissertation
Finanzierungsart
Kommentar zur Publikation
Allianzlizenz
Corresponding Authors der Uni Konstanz vorhanden
Internationale Co-Autor:innen
Universitätsbibliographie
Begutachtet
Ja
Diese Publikation teilen