Confronting Complexity in Agroecology: Simple Models From Turing to Simon

Abstract

There are two interrelated issues that seem to be emerging as central to the understanding of ecological systems more generally, particularly relevant to agroecosystems. First is the key insights of Alan Turing in which spatial pattern emerges from a system in which there is a reaction between two objects, both of which are diffusing in space, a pest and its natural enemy, for example. Secondly, as small-scale farmers make complex decisions about their farm's ecosystem management, they are forced to contemplate market forces as much as the background ecology. This necessity automatically involves a time lag in that remuneration for produce is realized substantially after the decision to plant is made. Here, behavioral economics intersects with non-linear ecological dynamics to produce an expectation of chaotic patterns. It is suggested that these two core ideas, spatial dynamics (e.g., Turing's dynamic instability in space) and chaos (e.g., Simon's constrained rationality in farm decisions) form a qualitative theoretical foundation for understanding the ecology of agroecosystems.