  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.
