The linkages between ecology and geomorphology can be difficult to identify because of physical complexity and the limitations of the current theoretical representations in these two fields of study. Deep divisions between these disciplines are manifest in the methods used to simulate process, such as rigidly physical-deterministic methods for many aspects of geomorphology compared with purely stochastic simulations in many models of change in landcover. Practical and theoretical research into ecology–geomorphology linkages cannot wait for a single simulation schema which may never come; as a result, studies of these linkages often appear disjointed and inconsistent.
The grid-based simulation framework for cellular automata (CA) allows simultaneous use of competing schemas. CA use in general geographic studies has been primarily limited to urban simulations models of change for land cover, both highly stochastic and/or expert rule-based. In the last decade, however, methods for describing physically deterministic systems in the CA framework have become much more accurate. The possibility now exists to merge separate CA simulations of different environmental systems into unified “multiautomata” models. Because CAs allow transition rules that are deterministic, probabilistic, or expert rule-based, they can immediately incorporate the existing knowledge rules in ecology and geomorphology. The explicitly spatial nature of CA provides a map-like framework that should allow a simple and deeply rooted connection with the mapping traditions of the geosciences and ecological sciences.
