Social Dynamics: Knowledgeable Lemurs Gain Status

The role of social attraction and social avoidance in shaping modular networks

How interactions between individuals contribute to the emergence of complex societies is a major question in behavioural ecology. Nonetheless, little remains known about the type of immediate social structure (i.e. social network) that emerges from relationships that maximize beneficial interactions (e.g. social attraction towards informed individuals) and minimize costly relationships (e.g. social avoidance of infected group mates). We developed an agent-based model where individuals vary in the degree to which individuals signal benefits versus costs to others and, on this basis, choose with whom to interact depending on simple rules of social attraction (e.g. access to the highest benefits) and social avoidance (e.g. avoiding the highest costs). Our main findings demonstrate that the accumulation of individual decisions to avoid interactions with highly costly individuals, but that are to some extent homogeneously beneficial, leads to more modular networks. On the contrary, individuals favouring interactions with highly beneficial individuals, but that are to some extent homogeneously costly, lead to less modular networks. Interestingly, statistical models also indicate that when individuals have multiple potentially beneficial partners to interact with, and no interaction cost exists, this also leads to more modular networks. Yet, the degree of modularity is contingent upon the variability in benefit levels held by individuals. We discuss the emergence of modularity in the systems and their consequences for understanding social trade-offs.

A unified account of culture should accommodate animal cultures

Discoveries about social learning and culture in non-human animals have burgeoned this century, yet despite aspiring to offer a unified account of culture, the target article neglects these discoveries almost totally. I offer an overview of principal findings in this field including phylogenetic reach, intraspecies pervasiveness, stability, fidelity, and attentional funnelling in social learning. Can the authors’ approach accommodate these?

Dynamic Relationships between Information Transmission and Social Connections

Understanding the drivers of sociality is a major goal in biology. Individual differences in social connections determine the overall group structure and have consequences for a variety of processes, including if and when individuals acquire information from conspecifics. Effects in the opposite direction, where information acquisition and transmission have consequences for social connections, are also likely to be widespread. However, these effects are typically overlooked. We propose that individuals who successfully learn about their environment become valuable social partners and become highly connected, leading to feedback-based dynamic relationships between social connections and information transmission. These dynamics have the potential to change our understanding of social evolution, including how selection acts on behavior and how sociality influences population-level processes.