IDEAS home Printed from https://ideas.repec.org/a/pal/palcom/v5y2019i1d10.1057_s41599-019-0360-4.html
   My bibliography  Save this article

Trait specialization, innovation, and the evolution of culture in fluctuating environments

Author

Listed:
  • Dominik Deffner

    (Max Planck Institute for Evolutionary Anthropology)

  • Anne Kandler

    (Max Planck Institute for Evolutionary Anthropology)

Abstract

Individuals often respond phenotypically to environmental challenges by innovating and adopting novel behavioral variants. Behavioral (or ‘cultural’) variants are defined here as alternative ways to solve adaptive problems, such as finding food or building shelter. In unpredictable environments, individuals must both be able to adapt to current conditions but also to cope with potential changes in these conditions, they must “hedge their evolutionary bets” against the variability of the environment. Here, we loosely apply this idea to the context of behavioral adaptation and develop an evolutionary model, where cultural variants differ in their level of generality, i.e. the range of environmental conditions in which they provide fitness benefits: generalist variants are characterized by large ranges, specialist variants by small ranges. We use a Moran model (with additional learning opportunities) and assume that each individual’s propensity for innovation is genetically determined, while the characteristics of cultural variants can be modified through processes of individual and social learning. Our model demonstrates that flexibly adjusting the level of generality allows individuals to navigate the trade-off between fast and reliable initial adaptation and the potential for long-term improvements. In situations with many (social or individual) learning opportunities, no adjustment of the innovation rate, i.e. the propensity to learn individually, is required to adapt to changed environmental conditions: fast adaptation is guaranteed by solely adjusting the level of generality of the cultural variants. Few learning opportunities, however, require both processes, innovation and trait generality, to work hand in hand. To explore the effects of different modes of innovation, we contrast independent invention and modification and show that relying largely on modifications improves both short-term and long-term adaptation. Further, inaccuracies in social learning provide another source of variant variation that facilitates adaptation after an environmental change. However, unfaithful learning is detrimental to long-term levels of adaptation. Our results demonstrate that the characteristics of cultural variants themselves can play a major role in the adaptation process and influence the evolution of learning strategies.

Suggested Citation

  • Dominik Deffner & Anne Kandler, 2019. "Trait specialization, innovation, and the evolution of culture in fluctuating environments," Palgrave Communications, Palgrave Macmillan, vol. 5(1), pages 1-10, December.
  • Handle: RePEc:pal:palcom:v:5:y:2019:i:1:d:10.1057_s41599-019-0360-4
    DOI: 10.1057/s41599-019-0360-4
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1057/s41599-019-0360-4
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1057/s41599-019-0360-4?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Aoki, Kenichi & Feldman, Marcus W., 2014. "Evolution of learning strategies in temporally and spatially variable environments: A review of theory," Theoretical Population Biology, Elsevier, vol. 91(C), pages 3-19.
    2. Elena Miu & Ned Gulley & Kevin N. Laland & Luke Rendell, 2018. "Innovation and cumulative culture through tweaks and leaps in online programming contests," Nature Communications, Nature, vol. 9(1), pages 1-8, December.
    3. Kandler, Anne & Laland, Kevin N., 2009. "An investigation of the relationship between innovation and cultural diversity," Theoretical Population Biology, Elsevier, vol. 76(1), pages 59-67.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Salva Duran-Nebreda & Michael J. O’Brien & R. Alexander Bentley & Sergi Valverde, 2022. "Dilution of expertise in the rise and fall of collective innovation," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-10, December.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Salva Duran-Nebreda & Michael J. O’Brien & R. Alexander Bentley & Sergi Valverde, 2022. "Dilution of expertise in the rise and fall of collective innovation," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-10, December.
    2. R. Bentley & Michael O’Brien & Paul Ormerod, 2011. "Quality versus mere popularity: a conceptual map for understanding human behavior," Mind & Society: Cognitive Studies in Economics and Social Sciences, Springer;Fondazione Rosselli, vol. 10(2), pages 181-191, December.
    3. Brand, Charlotte Olivia & Acerbi, Alberto & Mesoudi, Alex, 2019. "Cultural evolution of emotional expression in 50 years of song lyrics," SocArXiv 3j6wx, Center for Open Science.
    4. Mullon, Charles & Lehmann, Laurent, 2017. "Invasion fitness for gene–culture co-evolution in family-structured populations and an application to cumulative culture under vertical transmission," Theoretical Population Biology, Elsevier, vol. 116(C), pages 33-46.
    5. Michael Foley & Rory Smead & Patrick Forber & Christoph Riedl, 2021. "Avoiding the bullies: The resilience of cooperation among unequals," PLOS Computational Biology, Public Library of Science, vol. 17(4), pages 1-18, April.
    6. Jie Yu & Bahodirhon Safarov & Lu Yi & Makhina Buzrukova & Bekzot Janzakov, 2023. "The Adaptive Evolution of Cultural Ecosystems along the Silk Road and Cultural Tourism Heritage: A Case Study of 22 Cultural Sites on the Chinese Section of the Silk Road World Heritage," Sustainability, MDPI, vol. 15(3), pages 1-21, January.
    7. Ram, Yoav & Liberman, Uri & Feldman, Marcus W., 2019. "Vertical and oblique cultural transmission fluctuating in time and in space," Theoretical Population Biology, Elsevier, vol. 125(C), pages 11-19.
    8. Clampit, Jack & Kedia, Ben & Fabian, Frances & Gaffney, Nolan, 2015. "Offshoring satisfaction: The role of partnership credibility and cultural complementarity," Journal of World Business, Elsevier, vol. 50(1), pages 79-93.
    9. Ohtsuki, Hisashi & Wakano, Joe Yuichiro & Kobayashi, Yutaka, 2017. "Inclusive fitness analysis of cumulative cultural evolution in an island-structured population," Theoretical Population Biology, Elsevier, vol. 115(C), pages 13-23.
    10. Bentley, R. Alexander & Ormerod, Paul, 2010. "A rapid method for assessing social versus independent interest in health issues: A case study of 'bird flu' and 'swine flu'," Social Science & Medicine, Elsevier, vol. 71(3), pages 482-485, August.
    11. Dentoni, Domenico & English, Francis, 2012. "Dealing with Cultural Differences in Public-Private R&D Projects: The Experience of the Australian Seafood Sector," International Food and Agribusiness Management Review, International Food and Agribusiness Management Association, vol. 15(A), pages 1-6, June.
    12. Kobayashi, Yutaka & Ohtsuki, Hisashi, 2014. "Evolution of social versus individual learning in a subdivided population revisited: Comparative analysis of three coexistence mechanisms using the inclusive-fitness method," Theoretical Population Biology, Elsevier, vol. 92(C), pages 78-87.
    13. Aoki, Kenichi, 2015. "Modeling abrupt cultural regime shifts during the Palaeolithic and Stone Age," Theoretical Population Biology, Elsevier, vol. 100(C), pages 6-12.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:pal:palcom:v:5:y:2019:i:1:d:10.1057_s41599-019-0360-4. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: https://www.nature.com/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.