Using network synchrony to identify drivers of social dynamics.

Social animals frequently show dynamic social network patterns, the consequences of which are felt at the individual and group level. It is often difficult, however, to identify what drivers are responsible for changes in these networks. We suggest that patterns of network synchronization across multiple social groups can be used to better understand the relative contributions of extrinsic and intrinsic drivers. When groups are socially separated, but share similar physical environments, the extent to which network measures across multiple groups covary (i.e. network synchrony) can provide an estimate of the relative roles of extrinsic and intrinsic drivers. As a case example, we use allogrooming data from three adjacent vervet monkey groups to generate dynamic social networks. We found that network strength was strongly synchronized across the three groups, pointing to shared extrinsic environmental conditions as the driver. We also found low to moderate levels of synchrony in network modularity, suggesting that intrinsic social processes may be more important in driving changes in subgroup formation in this population. We conclude that patterns of network synchronization can help guide future research in identifying the proximate mechanisms behind observed social dynamics in animal groups.