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Cultural conformity generates extremely stable traditions in bird song

Author

Listed:
  • Robert F. Lachlan

    (Queen Mary University of London)

  • Oliver Ratmann

    (Imperial College London)

  • Stephen Nowicki

    (Duke University
    Duke University Medical School)

Abstract

Cultural traditions have been observed in a wide variety of animal species. It remains unclear, however, what is required for social learning to give rise to stable traditions: what level of precision and what learning strategies are required. We address these questions by fitting models of cultural evolution to learned bird song. We recorded 615 swamp sparrow (Melospiza georgiana) song repertoires, and compared syllable frequency distributions to the output of individual-based simulations. We find that syllables are learned with an estimated error rate of 1.85% and with a conformist bias in learning. This bias is consistent with a simple mechanism of overproduction and selective attrition. Finally, we estimate that syllable types could frequently persist for more than 500 years. Our results demonstrate conformist bias in natural animal behaviour and show that this, along with moderately precise learning, may support traditions whose stability rivals those of humans.

Suggested Citation

  • Robert F. Lachlan & Oliver Ratmann & Stephen Nowicki, 2018. "Cultural conformity generates extremely stable traditions in bird song," Nature Communications, Nature, vol. 9(1), pages 1-9, December.
    • Handle: RePEc:nat:natcom:v:9:y:2018:i:1:d:10.1038_s41467-018-04728-1
    DOI: 10.1038/s41467-018-04728-1
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    Cited by:

    1. Heather Williams & Andrew Scharf & Anna R. Ryba & D. Ryan Norris & Daniel J. Mennill & Amy E. M. Newman & Stéphanie M. Doucet & Julie C. Blackwood, 2022. "Cumulative cultural evolution and mechanisms for cultural selection in wild bird songs," Nature Communications, Nature, vol. 13(1), pages 1-11, December.
    2. Mason Youngblood & Joseph M. Stubbersfield & Olivier Morin & Ryan Glassman & Alberto Acerbi, 2023. "Negativity bias in the spread of voter fraud conspiracy theory tweets during the 2020 US election," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-11, December.
    3. Tim Sainburg & Marvin Thielk & Timothy Q Gentner, 2020. "Finding, visualizing, and quantifying latent structure across diverse animal vocal repertoires," PLOS Computational Biology, Public Library of Science, vol. 16(10), pages 1-48, October.

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