Modelling the Evolution of Social Structure

PLoS One. 2016 Jul 18;11(7):e0158605. doi: 10.1371/journal.pone.0158605. eCollection 2016.

Abstract

Although simple social structures are more common in animal societies, some taxa (mainly mammals) have complex, multi-level social systems, in which the levels reflect differential association. We develop a simulation model to explore the conditions under which multi-level social systems of this kind evolve. Our model focuses on the evolutionary trade-offs between foraging and social interaction, and explores the impact of alternative strategies for distributing social interaction, with fitness criteria for wellbeing, alliance formation, risk, stress and access to food resources that reward social strategies differentially. The results suggest that multi-level social structures characterised by a few strong relationships, more medium ties and large numbers of weak ties emerge only in a small part of the overall fitness landscape, namely where there are significant fitness benefits from wellbeing and alliance formation and there are high levels of social interaction. In contrast, 'favour-the-few' strategies are more competitive under a wide range of fitness conditions, including those producing homogeneous, single-level societies of the kind found in many birds and mammals. The simulations suggest that the development of complex, multi-level social structures of the kind found in many primates (including humans) depends on a capacity for high investment in social time, preferential social interaction strategies, high mortality risk and/or differential reproduction. These conditions are characteristic of only a few mammalian taxa.

MeSH terms

  • Animals
  • Biological Evolution*
  • Competitive Behavior
  • Computer Simulation
  • Cooperative Behavior
  • Hierarchy, Social*
  • Humans
  • Interpersonal Relations*
  • Models, Biological
  • Population Density
  • Reproduction
  • Social Behavior*

Grants and funding

This work was supported by Engineering and Physical Sciences Research Council, UK EP/D05088X/1. RD’s research is supported by an ERC Advanced Investigator award. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.