From pattern to practice: a scaling-down strategy for spatially explicit modelling illustrated by the spread and control of rabies

A major problem in ecological modelling is finding the appropriate level of resolution when describing the processes and structures of ecological syst ems. When modelling basic ecological questions, as a rule the best approach is to ignore as much detail as possible in order to obtain general insight s. However, for applied problems focusing in particular on ecological syste ms, there are no clear guidelines for identifying the most appropriate reso lution in space, time and the detail of description. Spatially explicit mod elling thus has to mainly rely on trial and error in scaling-up from modell ing at the local scale to exploration of the model at the global scale. We demonstrate here a modelling strategy that takes the opposite approach: sta rting at the global scale, with a strategic model of minimum resolution, we proceed step by step to a model addressing applied questions. The strategi c model is designed to reproduce a certain pattern observed in nature. As a n example, we use the wave-like spreading pattern of rabies. The applied mo del addresses the question of whether rabies might persist in areas with a high proportion of foxes immunized by oral vaccination. As a consequence of our scaling-down strategy, the resolution of the applied model is not chos en a priori, but emerges from the step by step modelling strategy. During e ach step of model refinement, one module of the preceding model is describe d with a slightly increased resolution. This stepwise approach allows both a backward reference to the pattern reproduced by the strategic model and a cross-reference between the coarser and finer version of the module refine d. The main potential of the scaling-down strategy is that it leads to effi cient models in an efficient way, but since scaling-down is a complement to scaling-up approaches, it might also help to bridge the gap between theore tical and applied ecological modelling. (C) 1999 Elsevier Science B.V. All rights reserved.