The Emergence of Animal Social Complexity: theoretical and biobehavioral evidence

TL;DR

This paper proposes a comprehensive theory of emergent animal social complexity, integrating computational and empirical evidence to explain how social structures arise from lower-level biological mechanisms.

Contribution

It introduces a novel vertical model of social complexity based on complex systems principles, linking individual processes to social phenomena.

Findings

Social complexity emerges from lower-level biological mechanisms.

Metastable networks of social relations constrain individual physiological processes.

Five principles of social complexity are identified from a complex systems perspective.

Abstract

This paper will introduce a theory of emergent animal social complexity using various results from computational models and empirical results. These results will be organized into a vertical model of social complexity. This will support the perspective that social complexity is in essence an emergent phenomenon while helping to answer two interrelated questions. The first of these involves how behavior is integrated at units of analysis larger than the individual organism. The second involves placing aggregate social events into the context of processes occurring within individual organisms over time (e.g. genomic and physiological processes). By using a complex systems perspective, five principles of social complexity can be identified. These principles suggest that lower-level mechanisms give rise to high-level mechanisms, ultimately resulting in metastable networks of social relations. These network structures then constrain lower-level phenomena ranging from transient, collective social groups to physiological regulatory mechanisms within individual organisms. In conclusion, the broader implications and drawbacks of applying the theory to a diversity of natural populations will be discussed.