Kinds of kindness: classifying the causes of altruism and cooperation.

As it was realized that natural selection should favour behaviours that benefit the individual rather than the species it belongs to, explaining the occurrence of altruistic behaviours has become one of the central problems in evolutionary biology. The seminal work of William Hamilton (1964) paved the way for a revolutionary approach, focusing on how genes may benefit copies present in other individuals. After some time it was realized; however, that such ‘kin selection’ (as the mechanism became known) alone could not explain all observations of individuals helping others. Trivers (1971) suggested that by being nice individuals could induce others to return favours. This idea of reciprocal altruism was put on a sound game-theoretical footing by Axelrod’s study of the Iterated Prisoners Dilemma Game (Axelrod & Hamilton, 1981). Reciprocal altruism is generally considered to be a fundamentally different form of altruism but the distinction between these two forms has become blurred, in particular as numerous researchers have started exploring spatial variants of the reciprocal altruism games (Doebeli & Hauert, 2005). In this issue of JEB Lehmann & Keller (2006) review the theoretical literature on the evolution of altruism and cooperation. They synthesize and unify the models into a general theoretical framework. Using this framework they classify the causes of evolution of helping (comprising both altruism and cooperation) into four broad categories. We think this is a laudable and useful undertaking and that such a common framework will facilitate communication, avoid duplication of results and will help identifying and understanding novel scenarios for the evolution of helping. Lehmann and Keller’s model is based on the direct fitness approach, which was pioneered by Taylor & Frank (1996) and is essentially a precise bookkeeping scheme for the costs and benefits of interactions to all members of the population. The scheme focuses on a typical individual (the focal individual or FI) and keeps track of all increments and decrements in the payoff it receives while it is followed through all possible interactions. If the coefficients of relatedness in the population are known this allows one to cast the selective pressures in terms of kin selection theory. Lehmann and Keller’s unified framework is particularly notable for the fact that it incorporates the costs and benefits of a repeated interaction between individuals, in which the costs and benefits can depend on the history of the interaction. This allows a fair comparison between models based on single moves (where strategies are fixed traits) and those based on repeated games (with responsive strategies). A textbook example is the interaction of two players playing the repeated prisoner’s dilemma game. If two players play tit-for-tat with each other both will accrue a net benefit after playing many rounds of the game (Maynard Smith, 1989). Lehmann and Keller’s scheme tells us that the interaction between two tit-for-tat players should therefore be interpreted as cooperative. Lehmann and Keller’s formalism thus helps to overcome the potential confusion resulting from mixing up the cost and benefit per move with the overall costs and benefits through a repeated interaction. Although we think there is great merit in Lehmann and Keller’s attempt at synthesis we see a number of obstacles that might stand in the way of its general acceptance as a common framework. A first important obstacle is that it does not make clear how kin selection relates to kin discrimination. This is unfortunate as Lehmann and Keller’s approach will help to perpetuate the common misconception that kin selection requires discrimination or recognition of related individuals. As Hamilton showed in his classic paper (Hamilton, 1964), altruistic behaviour can be selected if one meets, on balance, sufficiently many individuals who carry the same gene, without having to know who is related and who is not. Part of the confusion is probably caused by Hamilton himself when he remarks that kin selection would probably more effective when individuals adjust their behaviour according to their genealogical relationship with the individuals they interact with. Lehmann and Keller contribute to this confusion because their formalism suggests that discrimination is a necessary condition for kin selection to operate. That is, they model the efficacy of kin selection as the product of r, the standard coefficient of relatedness (indicating the probability of sharing genes identical by descent) and a component x which, they claim, represents kin discrimination. If true, this implies that kin selection cannot work if individuals do not adjust their behaviour with respect to whom they perceive as kin (if x 1⁄4 0 the model reverts to pure individual selection). However, kin selection can also operate when it is ‘blind’. For instance, in so-called ‘viscous’ populations, where individuals do not disperse far from their place of birth, individuals are highly likely to have kin among their neighbours. Altruism can than be favoured in such populations without kin recognition (Hamilton, 1964; van Baalen & Correspondence: M. van Baalen, ENS-UPMC-CNRS UMR 7625 Fonctionnement et Evolution des Systèmes Ecologiques, Bât. A. 7ème Etage CC 237, 7 quai St Bernard, 75252 Paris Cedex 05, France. 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