Marco A. Janssen

The evolution of cooperation is a fundamental problem in biology, especially for non-relatives, where indirect fitness benefits cannot counter within-group inequalities. Multilevel selection models show how cooperation can evolve if it generates a group-level advantage, even when cooperators are disadvantaged within their group. This allows the possibility of group selection, but few examples have been described in nature. Here we show that group selection can explain the evolution of cooperative nest founding in the harvester ant Pogonomyrmex californicus. Through most of this species’ range, colonies are founded by single queens, but in some populations nests are instead founded by cooperative groups of unrelated queens. In mixed groups of cooperative and single-founding queens, we found that aggressive individuals had a survival advantage within their nest, but foundress groups with such non-cooperators died out more often than those with only cooperative members. An agent-based model shows that the between-group advantage of the cooperative phenotype drives it to fixation, despite its within-group disadvantage, but only when population density is high enough to make between-group competition intense. Field data show higher nest density in a population where cooperative founding is common, consistent with greater density driving the evolution of cooperative foundation through group selection.

Information sharing is a critical task for group-living animals. The pattern of sharing can be modeled as a network whose structure can affect the decision-making performance of individual members as well as that of the group as a whole. A fully connected network, in which each member can directly transfer information to all other members, ensures rapid sharing of important information, such as a promising foraging location. However, it can also impose costs by amplifying the spread of inaccurate information (if, for example the foraging location is actually not profitable). Thus, an optimal network structure should balance effective sharing of current knowledge with opportunities to discover new information. We used a computer simulation to measure how well groups characterized by different network structures (fully connected, small world, lattice, and random) find and exploit resource peaks in a variable environment. We found that a fully connected network outperformed other structures when resource quality was predictable. When resource quality showed random variation, however, the small world network was better than the fully connected one at avoiding extremely poor outcomes. These results suggest that animal groups may benefit by adjusting their information-sharing network structures depending on the noisiness of their environment.

Keywords: agent-based model; collective cognition; conformity; small world networks; speed–accuracy; trade-off

How do groups of social agents organize themselves to cope with stress and disturbances? We address this question by looking at ant colonies. We review the suites of traits that allow ant species to adapt to different disturbance and stress regimes, and changes in these regimes. Low temperatures and low nest site and food resource availability are important stresses that affect ant abundance and distribution. Large-scale habitat disturbances, such as fire, grazing and mining, and small-scale disturbances that more directly affect individual colonies, such as predation, parasitism and disease, also affect ant abundance and distribution. We use functional groups to study the social and individual traits underlying different responses to temperature stress, large-scale habitat disturbance and competition from other ants. Specific individual and colony traits, such as colony size, queen number and worker specialization, seem to underlie adaptation to various stress and disturbance regimes.