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A Mixture of "Cheats'' and "Co-Operators'' Can Enable Maximal Group Benefit

MacLean, RC and Fuentes-Hernandez, A and Greig, D and Hurst, LD and Gudelj, I (2010) A Mixture of "Cheats'' and "Co-Operators'' Can Enable Maximal Group Benefit. PLOS BIOL , 8 (9) , Article e1000486. 10.1371/journal.pbio.1000486.

An open access publication

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.

Type:Article
Title:A Mixture of "Cheats'' and "Co-Operators'' Can Enable Maximal Group Benefit
Open access status:An open access publication
DOI:10.1371/journal.pbio.1000486
Keywords:COUPLED RECEPTOR GPR1, WINE YEAST STRAINS, SACCHAROMYCES-CEREVISIAE, PRISONERS-DILEMMA, MICROBIAL-POPULATIONS, ESCHERICHIA-COLI, SNOWDRIFT GAME, SUC GENES, COOPERATION, SUCROSE
UCL classification:UCL > School of Life and Medical Sciences > Faculty of Life Sciences > Biosciences (Division of) > Genetics, Evolution and Environment

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