Abstract
Further development of process-based spatial models is needed to facilitate explanation in landscape ecology. We discuss the dual modeling goals of prediction and explanation and identify challenges faced in explaining landscape patterns. These challenges are especially acute in attempts to explain patterns that result from complex adaptive systems. We compare examples of two process models used to describe landscape changes in Yellowstone National Park as a consequence of predator-prey interactions. Generative landscape science is offered as a complementary approach to explanation, combining models of candidate processes that are believed to give rise to observed patterns with empirical observations.