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Lying and truth-telling are conflicting behavioral strategies that pervade much of the lives of social animals and, as such, have always been topics of interest to both biology and philosophy. This age-old conflict is linked to one of the most serious threats facing society today, viz., the collapse of trustworthy sources of information. Here, we revisit this problem in the context of the two-choice sender–receiver game: the sender tosses a coin and reports the supposed outcome to the receiver, who must guess the true outcome of the toss. For the sender, the options are to lie or tell the truth, while for the receiver, the options are to believe or disbelieve the sender’s account. We assume that social learning determines the strategy used by players and, in particular, that players tend to imitate successful individuals and thus change their strategies. Using the replicator equation formulation for infinite populations and stochastic simulations for finite populations, we find that when the sender benefits from the receiver’s failure, the outcome of the game dynamics depends strongly on the choice of initial strategies. This sensitivity to the initial conditions may reflect the unpredictability of social systems whose members have antagonistic interests.

Free-forming or casual groups are groups in which individuals are in face-to-face interactions and are free to maintain or terminate contact with one another, such as clusters of people at a cocktail party, play groups in a children’s playground or shopping groups in a mall. Stochastic models of casual groups assume that group sizes are the products of natural processes by which groups acquire and lose members. The size distributions predicted by these models have been the object of controversy since their derivation in the 1960s because of the neglect of fluctuations around the mean values of random variables that characterize a collection of groups. Here, we check the validity of these mean-field approximations using an exact stochastic simulation algorithm to study the processes of the acquisition and loss of group members. In addition, we consider the situation where the appeal of a group of size i to isolates is proportional to iα. We find that, for α≤1, the mean-field approximation fits the equilibrium simulation results very well, even for a relatively small population size N. However, for α>1, this approximation scheme fails to provide a coherent description of the distribution of group sizes. We find a discontinuous phase transition at αc>1 that separates the regime where the variance of the group size does not depend on N from the regime where it grows linearly with N. In the latter regime, the system is composed of a single large group that coexists with a large number of isolates. Hence, the same underlying acquisition-and-loss process can explain the existence of small, temporary casual groups and of large, stable social groups.

Humans are the ultimate ecosystem engineers who have profoundly transformed the world’s landscapes in order to enhance their survival. Somewhat paradoxically, however, sometimes the unforeseen effect of this ecosystem engineering is the very collapse of the population it intended to protect. Here we use a spatial version of a standard population dynamics model of ecosystem engineers to study the colonization of unexplored virgin territories by a small settlement of engineers. We find that during the expansion phase the population density reaches values much higher than those the environment can support in the equilibrium situation. When the colonization front reaches the boundary of the available space, the population density plunges sharply and attains its equilibrium value. The collapse takes place without warning and happens just after the population reaches its peak number. We conclude that overpopulation and the consequent collapse of an expanding population of ecosystem engineers is a natural consequence of the nonlinear feedback between the population and environment variables.