Experimental manipulation of avian social structure reveals segregation is carried over across contexts

Our current understanding of animal social networks is largely based on observations or experiments that do not directly manipulate associations between individuals. Consequently, evidence relating to the causal processes underlying such networks is limited. By imposing specified rules controlling individual access to feeding stations, we directly manipulated the foraging social network of a wild bird community, thus demonstrating how external factors can shape social structure. We show that experimentally imposed constraints were carried over into patterns of association at unrestricted, ephemeral food patches, as well as at nesting sites during breeding territory prospecting. Hence, different social contexts can be causally linked, and constraints at one level may have consequences that extend into other aspects of sociality. Finally, the imposed assortment was lost following the cessation of the experimental manipulation, indicating the potential for previously perturbed social networks of wild animals to recover from segregation driven by external constraints.     

How to make methodological decisions when inferring social networks

Social network analyses allow studying the processes underlying the associations between individuals and the consequences of those associations. Constructing and analyzing social networks can be challenging, especially when designing new studies as researchers are confronted with decisions about how to collect data and construct networks, and the answers are not always straightforward. The current lack of guidance on building a social network for a new study system might lead researchers to try several different methods and risk generating false results arising from multiple hypotheses testing. Here, we suggest an approach for making decisions when starting social network research in a new study system that avoids the pitfall of multiple hypotheses testing. We argue that best edge definition for a network is a decision that can be made using a priori knowledge about the species and that is independent from the hypotheses that the network will ultimately be used to evaluate. We illustrate this approach with a study conducted on a colonial cooperatively breeding bird, the sociable weaver. We first identified two ways of collecting data using different numbers of feeders and three ways to define associations among birds. We then evaluated which combination of data collection and association definition maximized (a) the assortment of individuals into previously known “breeding groups” (birds that contribute toward the same nest and maintain cohesion when foraging) and (b) socially differentiated relationships (more strong and weak relationships than expected by chance). This evaluation of different methods based on a priori knowledge of the study species can be implemented in a diverse array of study systems and makes the case for using existing, biologically meaningful knowledge about a system to help navigate the myriad of methodological decisions about data collection and network inference.