Abstract: Close associations between adult males and lactating females and their dependent infants are not commonly described in non-monogamous mammals. However, such associations [sometimes called friendships (Smuts 1985)] are regularly observed in several primate species in which females mate with multiple males during the fertile period. The absence of mating exclusivity among friends suggests that males should invest little in infant care, raising questions about the adaptive significance of friendship bonds. Using data from genetic paternity analyses, patterns of behavior, and long-term demographic and reproductive records, we evaluated the extent to which friendships in four multi-male, multi-female yellow baboon (Papio cynocephalus) groups in Amboseli, Kenya represent joint parental care of offspring or male mating effort. We found evidence that mothers and infants benefited directly from friendships; friendships provided mother–infant dyads protection from harassment from other adult and immature females. In addition, nearly half of all male friends were the genetic fathers of offspring and had been observed mating with mothers during the days of most likely conception for those offspring. In contrast, nearly all friends who were not fathers were also not observed to consort with the mother during the days of most likely conception, suggesting that friendships between mothers and non-fathers did not result from paternity confusion. Finally, we found no evidence that prior friendship increased a male’s chances of mating with a female in future reproductive cycles. Our results suggest that, for many male–female pairs at Amboseli, friendships represented a form of biparental care of offspring. Males in the remaining friendship dyads may be trading protection of infants in exchange for some resources or services not yet identified. Our study is the first to find evidence that female primates gain social benefits from their early associations with adult males.

Abstract: Researchers are increasingly turning to network theory to understand the social nature of animal populations. We present a computational framework that is the first step in a series of works that will allow us to develop a quantitative methodology of social network sampling to aid ecologists in their social network data collection. To develop our methodology, we need to be able to generate networks from which to sample. Ideally, we need to perform a systematic study of sampling protocols on different known network structures, as network structure might affect the robustness of any particular sampling methodology. Thus, we present a computational tool for generating network structures that have user-defined distributions for network properties and for key measures of interest to ecologists. The user defines the values of these measures and the tool will generate appropriate network randomizations with those properties. This tool will be used as a framework for developing a sampling methodology, although we do not present a full methodology here. We describe the method used by the tool, demonstrate its effectiveness, and discuss how the tool can now be utilized. We provide a proof-of-concept example (using the assortativity measure) of how such networks can be used, along with a simulated egocentric sampling regime, to test the level of equivalence of the sampled network to the actual network.

Abstract: Abstract   We present here an attempt to understand behaviors of dominant individuals and of subordinate individuals as behavior strategies in an asymmetric “hawk-dove” game. We assume that contestants have perfect information about relative fighting ability and the value of the resource. Any type of asymmetry, both relevant to and irrelevant to the fighting ability, can be considered. It is concluded that evolutionarily stable strategies (ESSs) depend on the resource value (V), the cost of injury (D), and the probability that the individual in one role will win (x). Different ESSs can exist even when values of V, D, and x are the same. The characteristics of dominance relations detected by observers may result from the ESSs that the individuals are adopting. The model explains some characteristics of dominance relations, for example, the consistent outcome of contests, the rare occurrence of escalated fights, and the discrepancy between resource holding potential (RHP) and dominance relations, from the viewpoint of individual selection.

Abstract: Network analysis has a long history in the mathematical and social sciences and the aim of this introduction is to provide a brief overview of the potential that it holds for the study of animal behaviour. One of the most attractive features of the network paradigm is that it provides a single conceptual framework with which we can study the social organisation of animals at all levels (individual, dyad, group, population) and for all types of interaction (aggressive, cooperative, sexual etc.). Graphical tools allow a visual inspection of networks which often helps inspire ideas for testable hypotheses. Network analysis itself provides a multitude of novel statistical tools that can be used to characterise social patterns in animal populations. Among the important insights that networks have facilitated is that indirect social connections matter. Interactions between individuals generate a social environment at the population level which in turn selects for behavioural strategies at the individual level. A social network is often a perfect means by which to represent heterogeneous relationships in a population. Probing the biological drivers for these heterogeneities, often as a function of time, forms the basis of many of the current uses of network analysis in the behavioural sciences. This special issue on social networks brings together a diverse group of practitioners whose study systems range from social insects over reptiles to birds, cetaceans, ungulates and primates in order to illustrate the wide-ranging applications of network analysis.

Abstract: We use two novel techniques to analyze association patterns in a group of wild spider monkeys (Ateles geoffroyi) studied continuously for 8 years. Permutation tests identified association rates higher or lower than chance expectation, indicating active processes of companionship and avoidance as opposed to passive aggregation. Network graphs represented individual adults as nodes and their association rates as weighted edges. Strength and eigenvector centrality (a measure of how strongly linked an individual is to other strongly linked individuals) were used to quantify the particular role of individuals in determining the network's structure. Female–female dyads showed higher association rates than any other type of dyad, but permutation tests revealed that these associations cannot be distinguished from random aggregation. Females formed tightly linked clusters that were stable over time, with the exception of immigrant females who showed little association with any adult in the group. Eigenvector centrality was higher for females than for males. Adult males were associated mostly among them, and although their strength of association with others was lower than that of females, their association rates revealed a process of active companionship. Female–male bonds were weaker than those between same-sex pairs, with the exception of those involving young male adults, who by virtue of their strong connections both with female and male adults, appear as temporary brokers between the female and male clusters of the network. This analytical framework can serve to develop a more complete explanation of social structure in species with high levels of fission–fusion dynamics.