Bode, N. W. F., Wood, A. J., & Franks, D. W. (2011). The impact of social networks on animal collective motion. Anim. Behav., 82(1), 29–38.
Abstract: Many group-living animals show social preferences for relatives, familiar conspecifics or individuals of similar attributes such as size, personality or sex. How such preferences could affect the collective motion of animal groups has been rather unexplored. We present a general model of collective animal motion that includes social connections as preferential reactions between individuals. Our conceptual examples illustrate the possible impact of underlying social networks on the collective motion of animals. Our approach shows that the structure of these networks could influence: (1) the cohesion of groups; (2) the spatial position of individuals within groups; and (3) the hierarchical dynamics within such groups. We argue that the position of individuals within a social network and the social network structure of populations could have important fitness implications for individual animals. Counterintuitive results from our conceptual examples show that social structures can result in unexpected group dynamics. This sharpens our understanding of the way in which collective movement can be interpreted as a result of social interactions.
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Lusseau, D., Whitehead, H., & Gero, S. (2008). Incorporating uncertainty into the study of animal social networks. Anim. Behav., 75(5), 1809–1815.
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Hasenjager, M. J., & Dugatkin, L. A. Social Network Analysis in Behavioral Ecology. Advances in the Study of Behavior. Academic Press.
Abstract: Abstract In recent years, behavioral ecologists have embraced social network analysis (SNA) in order to explore the structure of animal societies and the functional consequences of that structure. We provide a conceptual introduction to the field that focuses on historical developments, as well as on novel insights generated by recent work. First, we discuss major advances in the analysis of nonhuman societies, culminating in the use of SNA by behavioral ecologists. Next, we discuss how network-based approaches have enhanced our understanding of social structure and behavior over the past decade, focusing on: (1) information transmission, (2) collective behaviors, (3) animal personality, and (4) cooperation. These behaviors and phenomena possess several features—e.g., indirect effects, emergent properties—that network analysis is well equipped to handle. Finally, we highlight recent developments in SNA that are allowing behavioral ecologists to address increasingly sophisticated questions regarding the structure and function of animal sociality.
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Wey, T., Blumstein, D. T., Shen, W., & Jordán, F. (2008). Social network analysis of animal behaviour: a promising tool for the study of sociality. Anim. Behav., 75(2), 333–344.
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.
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