Complexity and behavioral ecology

Reductionism, the practice of predicting large system properties by adding up the measured behaviors of components, has had a long and successful run in recent science. However, in the last 2 decades, fields as diverse as physics, ecology, neurobiology, and economics have recognized that many complicated systems have emergent and self-organized properties that cannot be explained as the linear sum of components, but instead must be viewed as the potentially diverse outcomes of system nonlinearity. Despite some pioneering efforts to apply complexity theory to group movements and decision making, most behavioral ecologists have avoided invoking complexity perspectives in their research. In this essay, we argue that the reductionist focus on dyads in our field has largely run its course and that the next frontier is to examine whether and how social and communication networks function as complex nonlinear systems. To this end, we provide a sampling of topics within behavioral ecology where we think complexity theory may be illuminating.