Strategies for transforming fine scale knowledge to management usability

Simulation tools used for management purposes should fulfill several conditions by being computationally fast, user-friendly, realistic, generic and reliable. These traits are often counteracting since they simultaneously demand for model complexity as well as simplicity. Here we develop a strategy to overcome this general problem of environmental modelling for management use. Major ingredients are model analysis and reduction as new core components of the modelling process. In detail, a set of combined methods is proposed. Within a large class of models the set allows for automatically exploring model behaviour and for aggregating fine scale process knowledge together with spatio temporal resolution. Applications to a huge aquatic European regional seas ecosystem model (ERSEM), a complex photosynthesis model (PGEN) as well as a simple diagenetic model are presented. The analysis and aggregation methods provide first steps towards a new generation of decision support tools able to cope with an increase in scientific knowledge as well as management demands.