When is bigger better? The effects of group size on the evolution of helping behaviours.

Understanding the evolution of sociality in humans and other species requires understanding how selection on social behaviour varies with group size. However, the effects of group size are frequently obscured in the theoretical literature, which often makes assumptions that are at odds with empirical findings. In particular, mechanisms are suggested as supporting large-scale cooperation when they would in fact rapidly become ineffective with increasing group size. Here we review the literature on the evolution of helping behaviours (cooperation and altruism), and frame it using a simple synthetic model that allows us to delineate how the three main components of the selection pressure on helping must vary with increasing group size. The first component is the marginal benefit of helping to group members, which determines both direct fitness benefits to the actor and indirect fitness benefits to recipients. While this is often assumed to be independent of group size, marginal benefits are in practice likely to be maximal at intermediate group sizes for many types of collective action problems, and will eventually become very small in large groups due to the law of decreasing returns. The second component is the response of social partners on the past play of an actor, which underlies conditional behaviour under repeated social interactions. We argue that under realistic conditions on the transmission of information in a population, this response on past play decreases rapidly with increasing group size so that reciprocity alone (whether direct, indirect, or generalised) cannot sustain cooperation in very large groups. The final component is the relatedness between actor and recipient, which, according to the rules of inheritance, again decreases rapidly with increasing group size. These results explain why helping behaviours in very large social groups are limited to cases where the number of reproducing individuals is small, as in social insects, or where there are social institutions that can promote (possibly through sanctioning) large-scale cooperation, as in human societies. Finally, we discuss how individually devised institutions can foster the transition from small-scale to large-scale cooperative groups in human evolution.

Reproductive competition triggers mass eviction in cooperative banded mongooses.

In many vertebrate societies, forced eviction of group members is an important determinant of population structure, but little is known about what triggers eviction. Three main explanations are: (i) the reproductive competition hypothesis, (ii) the coercion of cooperation hypothesis, and (iii) the adaptive forced dispersal hypothesis. The last hypothesis proposes that dominant individuals use eviction as an adaptive strategy to propagate copies of their alleles through a highly structured population. We tested these hypotheses as explanations for eviction in cooperatively breeding banded mongooses (Mungos mungo), using a 16-year dataset on life history, behaviour and relatedness. In this species, groups of females, or mixed-sex groups, are periodically evicted en masse. Our evidence suggests that reproductive competition is the main ultimate trigger for eviction for both sexes. We find little evidence that mass eviction is used to coerce helping, or as a mechanism to force dispersal of relatives into the population. Eviction of females changes the landscape of reproductive competition for remaining males, which may explain why males are evicted alongside females. Our results show that the consequences of resolving within-group conflict resonate through groups and populations to affect population structure, with important implications for social evolution.

A decentralized batch-based group key management potocol for mobile Internet of Thngs (DBGK).

It is anticipated that constrained devices in the Internet of Things (IoT) will often operate in groups to achieve collective monitoring or management tasks. For sensitive and mission-critical sensing tasks, securing multicast applications is therefore highly desirable. To secure group communications, several group key management protocols have been introduced. However, the majority of the proposed solutions are not adapted to the IoT and its strong processing, storage, and energy constraints. In this context, we introduce a novel decentralized and batch-based group key management protocol to secure multicast communications. Our protocol is simple and it reduces the rekeying overhead triggered by membership changes in dynamic and mobile groups and guarantees both backward and forward secrecy. To assess our protocol, we conduct a detailed analysis with respect to its communcation and storage costs. This analysis is validated through simulation to highlight energy gains. The obtained results show that our protocol outperforms its peers with respect to keying overhead and the mobility of members.