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This paper discusses research aiming at assessing Common Agricultural Policy impacts on agriculture and forestry. For this purpose an approach is developed that includes a linear programming model to estimate the Positive Mathematical Programming production cost function coefficients of current agriculturalforestry activities. It further includes a heuristic -simulated annealing -to generate solutions for each policy scenario. This model base approach is integrated within a decision support system (DSS) for testing purposes. The DSS further encompasses a relational database that stores agricultural-forestry technical and economic data and a geographic information system that stores topological data of regional farm-type land units. The DSS Graphical User Interface provides tabular and geographical reporting capabilities. Results are discussed for an application to the Alentejo region in Southern Portugal. Results demonstrate the usefulness and relevance of the proposed approach to assess the impact of changes in prices and in agricultural policy on land use patterns and on forestry.

The management of forests in the Mediterranean basin is a complex problem, for which many political solutions have been used. In Portugal, these solutions tried to overcome the small property dimension, the elderly and/or absent owners and their relation with new functions and new approaches of forestry areas linked with changes on Common Agricultural Policy and the agriculture development paradigm. The solution must take into account the valorization of all economic activities that exist in the forest, but also the fire risk decreasing and the biodiversity preservation. This paper proposes a model that allows designing several economic scenarios, producing biodiversity and fire risk indicators, but also achieving the best compromise solution between these issues using compromise programming. The model was applied in a Forest Intervention Zone Arade-Alte/S. B. Messines, in the South of Portugal. The results show that the model is able to provide important information by creating a complete management plan and simulating the best compromise solution among fire risk, economic result and the biodiversity indicator, providing an added background for the analysts.

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