Optimization methodology for land use patterns using spatially explicit landscape models

Spatially explicit ecosystem models allow the calculation of water and matter dynamics in a landscape as functions of spatial localization of habitat structures and matter input. For a mainly agricultural region we studied the nutrient balance as a function of different management schemes. For this purpose we formulated optimization tasks. This required the definition of performance criteria, which compare economic aspects, such like farmer's income from harvest, with ecologic aspects, such like nutrient loss out of the watershed. The task was to calculate optimum land use maps and fertilizer application maps maximizing the performance criterion. We developed a framework of procedures for numerical optimization in spatially explicit dynamic ecosystem simulation models. The results were tested using Monte-Carlo's simulation, which based on different stochastic generators for the independent control variables. Gradient free optimization procedures (Genetic Algorithms) were used to verify the simplifying assumptions. Parts of the framework offer tools for optimization with the computation effort independent of the size of the study area. As a result, important areas with high retention capabilities were identified and fertilizer maps were set up depending on soil properties. This shows that optimization methods even in complex simulation models can be a useful tool for a systematic analysis of management strategies of ecosystem use.