The evolution of helping and harming on graphs: the return of the inclusive fitness effect.
Evolutionary graph theory has been proposed as providing new fundamental rules for the evolution of co-operation and altruism. But how do these results relate to those of inclusive fitness theory? Here, we carry out a retrospective analysis of the models for the evolution of helping on graphs of Ohtsuki et al. [Nature (2006) 441, 502] and Ohtsuki & Nowak [Proc. R. Soc. Lond. Ser. B Biol. Sci (2006) 273, 2249]. We show that it is possible to translate evolutionary graph theory models into classical kin selection models without disturbing at all the mathematics describing the net effect of selection on helping. Model analysis further demonstrates that costly helping evolves on graphs through limited dispersal and overlapping generations. These two factors are well known to promote relatedness between interacting individuals in spatially structured populations. By allowing more than one individual to live at each node of the graph and by allowing interactions to vary with the distance between nodes, our inclusive fitness model allows us to consider a wider range of biological scenarios leading to the evolution of both helping and harming behaviours on graphs.
Lehmann
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L
Morrison Institute for Population and Resource Studies, University of Stanford, Stanford, CA 94305-5020, USA. lehmann@stanford.edu
Keller
L
L
Sumpter
D J T
DJ
D000533:Altruism; D005075:Biological Evolution; D003299:Cooperative Behavior; D008957:Models, Genetic; D012641:Selection, Genetic