ABSTRACT
Understanding the effects of spatial processes on population dynamics is essential to the advancement of the science of ecological modeling. Inclusion of spatial processes in a model can signiÞcantly alter the dynamic predictions made by nonspatial models. While models that allow for spatial interactions can provide insights into ecological dynamics, there are difÞculties as well. It can be difÞcult to deduce the relative importance of underlying mechanisms causing the altered dynamics from simulation results without the tools of mathematical analysis. Also, conÞrming that the computer code driving the model is working is a nontrivial task. As additional complexity is added to increase realism of the model, these tasks increase in difÞculty. Using different model types to represent the dynamic(s) under study can provide both additional ways to test that models are working correctly and better understanding of the various mechanisms contributing to the system dynamics.
