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  A mixture of "cheats" and "co-operators" can enable maximal group benefit

MacLean, R. C., Fuentes-Hernandez, A., Greig, D., Hurst, L. D., & Gudelj, I. (2010). A mixture of "cheats" and "co-operators" can enable maximal group benefit. PLoS Biology, 8(9): e1000486. doi:10.1371/journal.pbio.1000486.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-000F-EBE8-A Version Permalink: http://hdl.handle.net/11858/00-001M-0000-000F-EBE9-8
Genre: Journal Article

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 Creators:
MacLean, R. Craig, Author
Fuentes-Hernandez, Ayari, Author
Greig, Duncan1, Author              
Hurst, Laurence D., Author
Gudelj, Ivana, Author
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1Max-Planck Research Group Experimental Evolution, Max Planck Institute for Evolutionary Biology, Max Planck Society, ou_1445640              

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 Abstract: 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.

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Language(s): eng - English
 Dates: 2010-05-272010-08-042010-09-14
 Publication Status: Published in print
 Pages: -
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 Rev. Method: -
 Identifiers: DOI: 10.1371/journal.pbio.1000486
Other: 2779/S 39117
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Title: PLoS Biology
  Abbreviation : PLoS Biol.
Source Genre: Journal
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Publ. Info: Public Library of Science
Pages: 11 p. Volume / Issue: 8 (9) Sequence Number: e1000486 Start / End Page: - Identifier: ISSN: 1544-9173 (print)
ISSN: 1545-7885 (online)
CoNE: /journals/resource/111056649444170