IDEAS home Printed from https://ideas.repec.org/a/plo/pbio00/1000486.html
   My bibliography  Save this article

A Mixture of “Cheats” and “Co-Operators” Can Enable Maximal Group Benefit

Author

Listed:
  • R Craig MacLean
  • Ayari Fuentes-Hernandez
  • Duncan Greig
  • Laurence D Hurst
  • Ivana Gudelj

Abstract

It is commonly assumed that the world would be best off if everyone co-operates. Experimental and mathematical analysis of “co-operation” in yeast show why this isn't always the case.Is a group best off if everyone co-operates? Theory often considers this to be so (e.g. the “conspiracy of doves”), this understanding underpinning social and economic policy. We observe, however, that after competition between “cheat” and “co-operator” strains of yeast, population fitness is maximized under co-existence. To address whether this might just be a peculiarity of our experimental system or a result with broader applicability, we assemble, benchmark, dissect, and test a systems model. This reveals the conditions necessary to recover the unexpected result. These are 3-fold: (a) that resources are used inefficiently when they are abundant, (b) that the amount of co-operation needed cannot be accurately assessed, and (c) the population is structured, such that co-operators receive more of the resource than the cheats. Relaxing any of the assumptions can lead to population fitness being maximized when cheats are absent, which we experimentally demonstrate. These three conditions will often be relevant, and hence in order to understand the trajectory of social interactions, understanding the dynamics of the efficiency of resource utilization and accuracy of information will be necessary.Author Summary: The world is best off, it is usually presumed, when everyone co-operates. However, we discovered in a laboratory experiment involving yeasts that a population can grow more and faster when there is a mix of “cheats” and “co-operators.” In this case “co-operator” cells produce a protein (invertase) that breaks down sugar in the environment enabling it to be used by anyone. “Cheats” eat the broken down sugar but don't produce invertase and so have fewer costs. How can it be that yeast populations do best when such apparently selfish cheats are common? To resolve this we constructed a mathematical model, used this to discover reasons why the classical result wasn't found, and experimentally verified these conclusions. We find three conditions required to recover the unexpected result: (1) the “co-operators” should get more food than “cheats” (e.g. if the two aren't perfectly mixed together), (2) food is used more efficiently when there is a famine than when there is a feast, and (3) the amount of “co-operation” given should not accurately match the amount needed. We argue that all three are likely not to be peculiar to yeast, suggesting that “cheats” may be good for a group in many cases.

Suggested Citation

  • R Craig MacLean & Ayari Fuentes-Hernandez & Duncan Greig & Laurence D Hurst & Ivana Gudelj, 2010. "A Mixture of “Cheats” and “Co-Operators” Can Enable Maximal Group Benefit," PLOS Biology, Public Library of Science, vol. 8(9), pages 1-11, September.
  • Handle: RePEc:plo:pbio00:1000486
    DOI: 10.1371/journal.pbio.1000486
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.1000486
    Download Restriction: no

    File URL: https://journals.plos.org/plosbiology/article/file?id=10.1371/journal.pbio.1000486&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pbio.1000486?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
    ---><---

    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:plo:pbio00:1000486. 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.

    We have no bibliographic 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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosbiology (email available below). General contact details of provider: https://journals.plos.org/plosbiology/ .

    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.