Abstract: Understanding how groups of individuals with different motives come to daily decisions about the exploitation of their environment is a key question in animal behaviour. While interindividual differences are often seen only as a threat to group cohesion, growing evidence shows that they may to some extent facilitate effective collective action. Recent studies suggest that personality differences influence how individuals are attracted to conspecifics and affect their behaviour as an initiator or a follower. However, most of the existing studies are limited to a few taxa, mainly social fish and arthropods. Horses are social herbivores that live in long-lasting groups and show identifiable personality differences between individuals. We studied a group of 38 individuals living in a 30-ha hilly pasture. Over 200 h, we sought to identify how far individual differences such as personality and affinity distribution affect the dynamic of their collective movements. First, we report that individuals distribute their relationships according to similar personality and hierarchical rank. This is the first study that demonstrates a positive assortment between unrelated individuals according to personality in a mammal species. Second, we measured individual propensity to initiate and found that bold individuals initiated more often than shy individuals. However, their success in terms of number of followers and joining duration did not depend on their individual characteristics. Moreover, joining process is influenced by social network, with preferred partners following each other and bolder individuals being located more often at the front of the movement. Our results illustrate the importance of taking into account interindividual behavioural differences in studies of social behaviours.

Abstract: Third-party interventions are defined as the interruption of dyadic interactions by third animals through direct physical contact, interposing or threats. Previous studies focused on the analysis of interventions against agonistic encounters. However, there have been no evaluations of interventions against affiliative behaviours, particularly in relation to the intervening animal�s social relationships and its social and spatial position. Horses, Equus caballus, are an interesting model species, as interventions against affiliative interactions occur more frequently than against agonistic interactions. In this study, 64 feral horses displayed 67 interventions in affiliative interactions and eight interventions in agonistic interactions within the observation period. We analysed the interventions in affiliative encounters, and found that it was mainly higher-ranking females that intervened in the affiliative interactions of group mates in the stable horse harems. The intervening animals took an active part in affiliative and agonistic encounters within the group, but did not occupy particular social roles or spatial positions. They intervened in affiliative interactions in which group mates with which they had social bonds interacted with other members of the group. They targeted the nonbonded animal and approached the one with which they were socially bonded. We suggest some species use third-party interventions in affiliative interactions to prevent competition for preferred social interaction partners from escalating into more costly agonistic encounters.

Abstract: Social animals live and interact together, forming complex relationships and social structure. These relationships can have important fitness consequences, but most studies do not explicitly measure those relationships. An approach that explicitly measures relationships will further our understanding of social complexity and the consequences of both direct and indirect interactions. Social network analysis is the study of social groups as networks of nodes connected by social ties. This approach examines individuals and groups in the context of relationships between group members. Application of social network analysis to animal behaviour can advance the field by identifying and quantifying specific attributes of social relationships, many of which are not captured by more common measures of sociality, such as group size. Sophisticated methods for network construction and analysis exist in other fields, but until recently, have seen relatively little application to animal systems. We present a brief history of social network analysis, a description of basic concepts and previous applications to animal behaviour. We then highlight relevance and constraints of some network measures, including results from an original study of the effect of sampling on network parameter estimates, and we end with promising directions for research. By doing so, we provide a prospective overview of social network analysis' general utility for the study of animal social behaviour.

Abstract: There are numerous reports of novel learned behaviour patterns in animal populations, yet the factors influencing the invention and spread of these innovations remain poorly understood. Here we investigated to what extent the pattern of spread of innovations in captive groups of starlings, Sturnus vulgaris, could be predicted by knowledge of individual and social group variables, including association patterns, social rank orders, measures of neophobia and asocial learning performance. We presented small groups of starlings with a series of novel extractive foraging tasks and recorded the latency for each bird to contact and solve each task, as well as the orders of contacting and solving. We then explored which variables best predicted the observed diffusion patterns. Object neophobia and social rank measures characterized who was the first of the group to contact the novel foraging tasks, and the subsequent spread of contacting tasks was associated with latency to feed in a novel environment. Asocial learning performance, measured in isolation, predicted who was the first solver of the novel foraging tasks in each group. Association patterns did not predict the spread of solving. Contact latency and solving duration were negatively correlated, consistent with social learning underlying the spread of solving. Our findings indicate that we can improve our understanding of the diffusion dynamics of innovations in animal groups by investigating group-dependent and individual variables in combination. We introduce novel methods for exploring predictors of the origin and spread of behavioural innovations that could be widely applied.

Abstract: Abstract  Social network theory has made major contributions to our understanding of human social organisation but has found relatively little application in the field of animal behaviour. In this review, we identify several broad research areas where the networks approach could greatly enhance our understanding of social patterns and processes in animals. The network theory provides a quantitative framework that can be used to characterise social structure both at the level of the individual and the population. These novel quantitative variables may provide a new tool in addressing key questions in behavioural ecology particularly in relation to the evolution of social organisation and the impact of social structure on evolutionary processes. For example, network measures could be used to compare social networks of different species or populations making full use of the comparative approach. However, the networks approach can in principle go beyond identifying structural patterns and also can help with the understanding of processes within animal populations such as disease transmission and information transfer. Finally, understanding the pattern of interactions in the network (i.e. who is connected to whom) can also shed some light on the evolution of behavioural strategies.