Abstract: Recent studies have revealed a variety of left–right asymmetries among vertebrates and invertebrates. In many species, left- and right-lateralized individuals coexist, but in unequal numbers (‘population-level’ lateralization). It has been argued that brain lateralization increases individual efficiency (e.g. avoiding unnecessary duplication of neural circuitry and reducing interference between functions), thus counteracting the ecological disadvantages of lateral biases in behaviour (making individual behaviour more predictable to other organisms). However, individual efficiency does not require a definite proportion of left- and right-lateralized individuals. Thus, such arguments do not explain population-level lateralization. We have previously shown that, in the context of prey–predator interactions, population-level lateralization can arise as an evolutionarily stable strategy when individually asymmetrical organisms must coordinate their behaviour with that of other asymmetrical organisms. Here, we extend our model showing that populations consisting of left- and right-lateralized individuals in unequal numbers can be evolutionarily stable, based solely on strategic factors arising from the balance between antagonistic (competitive) and synergistic (cooperative) interactions.

Abstract: This paper reviews the literature on leadership in vertebrate groups, including recent work on human groups, before presenting the results of three new experiments looking at leadership and decision making in small and large human groups. In experiment 1, we find that both group size and the presence of uninformed individuals can affect the speed with which small human groups (eight people) decide between two opposing directional preferences and the likelihood of the group splitting. In experiment 2, we show that the spatial positioning of informed individuals within small human groups (10 people) can affect the speed and accuracy of group motion. We find that having a mixture of leaders positioned in the centre and on the edge of a group increases the speed and accuracy with which the group reaches their target. In experiment 3, we use large human crowds (100 and 200 people) to demonstrate that the trends observed from earlier work using small human groups can be applied to larger crowds. We find that only a small minority of informed individuals is needed to guide a large uninformed group. These studies build upon important theoretical and empirical work on leadership and decision making in animal groups.

Abstract: Geographical cataloguing of traits, as used in human ethnography, has led to the description of “culture” in some non-human great apes. Culture, in these terms, is detected as a pattern of local ignorance resulting from environmental constraints on knowledge transmission. However, in many cases, the geographical variations may alternatively be explained by ecology. Social transmission of information can reliably be identified in many other animal species, by experiment or distinctive patterns in distribution; but the excitement of detecting culture in great apes derives from the possibility of understanding the evolution of cumulative technological culture in humans. Given this interest, I argue that great ape research should concentrate on technically complex behaviour patterns that are ubiquitous within a local population; in these cases, a wholly non-social ontogeny is highly unlikely. From this perspective, cultural transmission has an important role in the elaborate feeding skills of all species of great ape, in conveying the “gist” or organization of skills. In contrast, social learning is unlikely to be responsible for local stylistic differences, which are apt to reflect sensitive adaptations to ecology.

Abstract: In recent years, the concept of self-organization has been used to understand collective behaviour of animals. The central tenet of self-organization is that simple repeated interactions between individuals can produce complex adaptive patterns at the level of the group. Inspiration comes from patterns seen in physical systems, such as spiralling chemical waves, which arise without complexity at the level of the individual units of which the system is composed. The suggestion is that biological structures such as termite mounds, ant trail networks and even human crowds can be explained in terms of repeated interactions between the animals and their environment, without invoking individual complexity. Here, I review cases in which the self-organization approach has been successful in explaining collective behaviour of animal groups and societies. Ant pheromone trail networks, aggregation of cockroaches, the applause of opera audiences and the migration of fish schools have all been accurately described in terms of individuals following simple sets of rules. Unlike the simple units composing physical systems, however, animals are themselves complex entities, and other examples of collective behaviour, such as honey bee foraging with its myriad of dance signals and behavioural cues, cannot be fully understood in terms of simple individuals alone. I argue that the key to understanding collective behaviour lies in identifying the principles of the behavioural algorithms followed by individual animals and of how information flows between the animals. These principles, such as positive feedback, response thresholds and individual integrity, are repeatedly observed in very different animal societies. The future of collective behaviour research lies in classifying these principles, establishing the properties they produce at a group level and asking why they have evolved in so many different and distinct natural systems. Ultimately, this research could inform not only our understanding of animal societies, but also the principles by which we organize our own society.