How life history and demography promote or inhibit the evolution of helping behaviours

Abstract

In natural populations, dispersal tends to be limited so that individuals are in local competition with their neighbours. As a consequence, most behaviours tend to have a social component, e.g. they can be selfish, spiteful, cooperative or altruistic as usually considered in social evolutionary theory. How social behaviours translate into fitness costs and benefits depends considerably on life-history features, as well as on local demographic and ecological conditions. Over the last four decades, evolutionists have been able to explore many of the consequences of these factors for the evolution of social behaviours. In this paper, we first recall the main theoretical concepts required to understand social evolution. We then discuss how life history, demography and ecology promote or inhibit the evolution of helping behaviours, but the arguments developed for helping can be extended to essentially any social trait. The analysis suggests that, on a theoretical level, it is possible to contrast three critical benefit-to-cost ratios beyond which costly helping is selected for (three quantitative rules for the evolution of altruism). But comparison between theoretical results and empirical data has always been difficult in the literature, partly because of the perennial question of the scale at which relatedness should be measured under localized dispersal. We then provide three answers to this question.

The effect of fecundity derivatives on the condition of evolutionary branching in spatial models

“…In this sense, our result (Corollary 2) confirms the results of Taylor (1992a) and Taylor et al (2011). Under different life-cycle assumptions, spatial structure has been shown to affect the evolution of cooperation (e.g., Taylor and Irwin, 2000;Lehmann and Rousset, 2010;Parvinen, 2010Parvinen, , 2011Seppänen and Parvinen, 2014).…”

“…Here these two opposing effects precisely cancel each other. This result is called Taylor's cancellation result, and has been shown shown to hold when one adopts the same life-cycle assumptions (nonoverlapping generations and so on) as ours (Taylor, 1992a,b;Queller, 1992;Wilson et al, 1992;Rousset, 2004;Gardner and West, 2006;Lehmann et al, 2007;Lehmann and Rousset, 2010;Taylor et al, 2011;Ohtsuki, 2012). In this sense, our result (Corollary 2) confirms the results of Taylor (1992a) and Taylor et al (2011).…”

“…Strictly speaking, our results are valid for Wright's island model with several specific life-history assumptions, such as non-overlapping generations, local regulation among adults after dispersal but before reproduction (in contrast with population regulation among juveniles after reproduction but before dispersal), when a fecundity-affecting trait is under natural selection. Actually, it is known that already a slight modification to those life-cycle assumptions made here may change evolutionary outcomes (Taylor and Irwin, 2000;Lehmann and Rousset, 2010). It is better, therefore, to take our result as one reference point, not as one that applies to all life-history assumptions.…”

A simple rule for the evolution of contingent cooperation in large groups

“…More detail and self-contained derivations that extend the results from [14] (2) Groups compete among themselves for the production of new groups in the next generation. This is the 'budding viscosity' population structure of Gardner & West [17], called 'propagule dispersal with group competition' in [18], and 'two-level Fisher-Wright' (2lFW) in [13]. The idea is that cooperators, at a cost to themselves, help their group in its competition with other groups.…”

“…For example, in the iterated public goods game, a plausible strategy is to cooperate during the first period, and then cooperate if at least a fraction u of the n individuals in the group cooperate. The derivation of this rule also assumes that groups are very large, that relatedness is low and generated by an elastic island model population structure [14], or by budding viscosity population structure [17] (propagule dispersal with group competition [18], two-level Fisher-Wright [13]). We will present numerical results which suggest that this rule provides also useful estimates when some of these assumptions are relaxed and the demographic parameters are in the biologically relevant range, including levels of relatedness in the range from 2% to about 10%.…”