Mathematical and process-based simulation models are powerful tools for synthesizing information about invasive species. However, there are a number of different types of models, ranging from simple to complex that can be selected for any given application. In this article, a model classification framework of three types of models is applied to studies of invasive species that allows the objective selection of a model type on the basis of its ability to capture key processes and dynamics, yet minimize the errors in prediction. Model selection is illustrated using a series of increasingly complex models.

Additional index words: Nonspatial models, spatially explicit models, spatially implicit models.