Evolving migration.

M ass migrations of wildebeest, caribou, song birds, sting rays, and monarch butterflies are among the wonders of the natural world (Fig. 1). At a very different scale, the coordinated migration of cells within the body is central to embryological development, immune responses, and wound healing. Although the scale, functions, and mechanisms may differ, these examples share one key feature: they are the product of local interactions among individual agents (wildebeest, butterflies, or cells). The proximate mechanisms where collective behavior arises from local interactions between individuals have become a fertile area of research, founded on models from statistical physics in which interacting agents are modeled as self-propelled particles (1–4). Guttal and Couzin (5) take such analyses to the next level and ask how and under what ecological circumstances might collective migration have evolved. Collective migration is a group level phenomenon, but its underlying mechanisms are at the level of individuals. What, then, are the individual level traits that might be subject to selection, and how might the collective level phenomena arising from these traits feed back to affect the fitness of the individuals involved? Guttal and Couzin (5) model a situation where two traits are subject to selection. The first is the capacity of an organism to respond to a gradient or some other external cue, indicating the correct direction of migration. Real examples of cues used by migrating organisms include magnetic fields, sunlight, wind direction, temperature, and chemical gradients. The second evolvable trait in the model is the sociability of an organism: specifically, its tendency to be attracted to and align with moving neighbors. Examples include the visually guided responses of starlings and locusts or physical adhesion and chemical signaling among bacteria. Various combinations of traits values in the model could result in a spectrum of population level outcomes, including individuals moving randomly (low gradient detection and low sociability), migrating independently of one another (high gradient detection and low sociability), forming aggregations but not migrating (low gradient detection and high sociability), migrating together along the gradient (high gradient detection and high sociability), or forming filamentous groups that split and fuse again as they move along the gradient (high gradient detection and intermediate sociability). As grist for evolution in the model, cost functions were specified for each of these variable traits: the greater the gradient detection ability and level of sociability, the higher the cost to the individual. Costs of detecting and following a gradient might include reduced vigilance to predators and the energetic costs of maintaining gradient detection mechanisms, whereas the costs of sociability could include increased competition for food, disease transmission, or greater visibility to predators (6). On the positive side of the evolutionary ledger, fitness benefits were gained according to how far and precisely organisms migrated in the direction of the gradient. Having set their agents free to evolve, Guttal and Couzin (5) find that populations typically evolved two coexisting and equally fit individual strategies: a minority of individuals evolved to become leaders, and the rest were highly sociable followers. Leaders assiduously followed the environmental gradient and largely ignored other individuals, whereas sociable individuals were attracted by one another but had little or no ability to detect the gradient. As a consequence, the entire group tracked the gradient together, with leaders showing the way and sociable individuals tagging along and freeloaded on the gradient-following ability of the leaders. Couzin et al. (1) had previously shown in an agent-based simulation how a small number of informed individuals can direct a large group of naive individuals to a resource site, as seen, for example, in the way that a small number of informed scout honey bees directs a large swarm of ignorant insects to a new nest site (7). In the model by Guttal and Couzin (5), such a situation evolved spontaneously. Distinct groups of leaders and sociable individuals arose under a wide range of scenarios in which population density and cost functions were varied. However, other outcomes were possible under certain conditions. At very low densities with low gradient-following costs, most individuals were leaders, resulting in individuals migrating independently rather than collectively. Conversely, at extremely high population densities when gradient following costs were high, stationary aggregations resulted. Nevertheless, collective migration in which a majority of sociable followers exploited the gradient-following abilities of a minority of leaders was observed over the vast majority of the parameter space explored. The process by which the two stable strategies arise and coexist reveals the central role of information structure and collective dynamics in affecting the fitness payoffs to individual group members. Under most conditions, all individuals in a population that initially lacks both gradient detection and sociability rapidly evolve the ability to detect a gradient because of the associated fitness benefits of migration. At the same time, individuals who also acquire a mutation to become sociable gain an additional fitness advantage because of the increased migratory accuracy accrued through the many wrongs principle of group navigation (8). Thus, individuals with both strong gradient detection and sociability parameters initially come to dominate the population. It is at this point that the information provided within the group facilitates some surprising evolutionary dynamics. Individuals can achieve higher relative fitness by relaxing their gradient detection ability while obtaining the benefits of migration through increased social attraction to gradient-detecting group members or their followers. As a result, an overall decrease in gradient detection ability is observed, whereas the strength of sociability increases. The stage is now set for a split in strategies. Some individuals achieve higher relative fitness by further reducing the Fig. 1. Caribou migration: a spectacular annual event in the Arctic. (Photograph courtesy of Ryan K. Brook.)