Selfish and spiteful behaviour in an evolutionary model.

Nature (Impact Factor: 38.6). 01/1971; 228(5277):1218-20. DOI: 10.1038/2281218a0
Source: PubMed
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    ABSTRACT: The presence of apparently irrational fair play in the ultimatum game remains a focal point for studies in the evolution of social behaviour. We investigate the role of negative assortment in the evolution of fair play in the ultimatum game. Spite-social behaviour that inflicts harm with no direct benefit to the actor-can evolve when it is disproportionally directed at individuals playing different strategies. The introduction of negative assortment alters the dynamics in a way that increases the chance fairness evolves, but at a cost: spite also evolves. Fairness is usually linked to cooperation and prosocial behaviour, but this study shows that it may have evolutionary links to harmful antisocial behaviour.
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    ABSTRACT: We survey the population genetic basis of social evolution, using a logically consistent set of arguments to cover a wide range of biological scenarios. We start by reconsidering Hamilton's (Hamilton 1964 J. Theoret. Biol. 7, 1-16 (doi:10.1016/0022-5193(64)90038-4)) results for selection on a social trait under the assumptions of additive gene action, weak selection and constant environment and demography. This yields a prediction for the direction of allele frequency change in terms of phenotypic costs and benefits and genealogical concepts of relatedness, which holds for any frequency of the trait in the population, and provides the foundation for further developments and extensions. We then allow for any type of gene interaction within and between individuals, strong selection and fluctuating environments and demography, which may depend on the evolving trait itself. We reach three conclusions pertaining to selection on social behaviours under broad conditions. (i) Selection can be understood by focusing on a one-generation change in mean allele frequency, a computation which underpins the utility of reproductive value weights; (ii) in large populations under the assumptions of additive gene action and weak selection, this change is of constant sign for any allele frequency and is predicted by a phenotypic selection gradient; (iii) under the assumptions of trait substitution sequences, such phenotypic selection gradients suffice to characterize long-term multi-dimensional stochastic evolution, with almost no knowledge about the genetic details underlying the coevolving traits. Having such simple results about the effect of selection regardless of population structure and type of social interactions can help to delineate the common features of distinct biological processes. Finally, we clarify some persistent divergences within social evolution theory, with respect to exactness, synergies, maximization, dynamic sufficiency and the role of genetic arguments.
    Philosophical Transactions of The Royal Society B Biological Sciences 01/2014; 369(1642):20130357. · 6.23 Impact Factor
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    ABSTRACT: In the face of costs, cooperative interactions maintained over evolutionary time present a central question in biology. What forces maintain this cooperation? Two potential ways to explain this problem are spatially structured environments (kin selection) and kin-recognition (directed benefits). In a two-locus population genetic model, we investigated the relative roles of spatial structure and kin recognition in the maintenance of cooperation among rhizobia within the rhizobia-legume mutualism. In the case where the cooperative and kin recognition loci are independently inherited, spatial structure alone maintains cooperation, while kin recognition decreases the equilibrium frequency of cooperators. In the case of co-inheritance, spatial structure remains a stronger force, but kin recognition can transiently increase the frequency of cooperators. Our results suggest that spatial structure can be a dominant force in maintaining cooperation in rhizobium populations, providing a mechanism for maintaining the mutualistic nodulation trait. Further, our model generates unique and testable predictions that could be evaluated empirically within the legume-rhizobium mutualism.
    PLoS ONE 01/2014; 9(4):e95141. · 3.73 Impact Factor