IDEAS home Printed from
   My bibliography  Save this article

Rethinking birdsong evolution: meta-analysis of the relationship between song complexity and reproductive success


  • Masayo Soma
  • László Zsolt Garamszegi


The theory of sexual selection predicts a relationship between male sexual traits and reproductive success. This prediction has been tested extensively using the complexity of birdsong as a model for trait elaboration. However, contradictory results have emerged. Some studies have demonstrated that males with large repertoires enjoy a reproductive advantage, whereas other studies have failed to support this prediction. To make general inferences from this mixed evidence, we quantitatively reviewed the relevant literature using a meta-analytic approach. The mean effect size for the song/mating success association was significant, but the effects were generally weak, affected by publication bias, confounded by uncontrolled variables, and differing across the traits examined. Effect sizes were heterogeneous across studies due to species-specific effects, differences in mating systems, and song phenotypes. The degree of association between song complexity and reproductive success was independent of the strength of sexual selection, as assessed by the degree of polygyny and extrapair paternity. Our results highlight the importance of considering various biological factors to understand the role of repertoires in mediating mating success in different species. Copyright 2011, Oxford University Press.

Suggested Citation

  • Masayo Soma & László Zsolt Garamszegi, 2011. "Rethinking birdsong evolution: meta-analysis of the relationship between song complexity and reproductive success," Behavioral Ecology, International Society for Behavioral Ecology, vol. 22(2), pages 363-371.
  • Handle: RePEc:oup:beheco:v:22:y:2011:i:2:p:363-371

    Download full text from publisher

    File URL:
    Download Restriction: Access to full text is restricted to subscribers.

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

    References listed on IDEAS

    1. Bates, Douglas & Mächler, Martin & Bolker, Ben & Walker, Steve, 2015. "Fitting Linear Mixed-Effects Models Using lme4," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 67(i01).
    Full references (including those not matched with items on IDEAS)

    More about this item


    Access and download statistics


    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:oup:beheco:v:22:y:2011:i:2:p:363-371. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Oxford University Press) or (Christopher F. Baum). General contact details of provider: .

    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.

    We have no references for this item. You can help adding them by using 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.