GIS-based modeling of land use systems - Common Agricultural Policy reform and its impact on agricultural land use and plant species richness - Jan Ole Schroers; Patrick Sheridan; Eike Rommelfanger (European Regional Science Association (ERSA), 2005)
An assessment of agricultural policy measures and their sustainability needs to consider economic, social, and ecological aspects. The current paradigm shift of the European Union's Common Agricultural Policy (CAP) from coupled to decoupled transfer payments calls for such an evaluation. Land users have to reevaluate their production program and its spatial allocation. Consequently, agricultural policy influences regional land use patterns and shares of land use systems, which in turn influence regional plant species richness. Connecting land use and ecological models allows to assess socioeconomic and ecologic effects of policy measures by identifying interactions and estimating potential trade-offs. The paper presents the land use model ProLand and the fuzzy expert system UPAL. ProLand models the regional distribution of land use systems while UPAL predicts plant species richness. The models are connected through a GIS and applied to a study area in Hesse, Germany, in order to simulate the effects of changing conditions on land use, economic and social key indicators, and plant species richness. ProLand is a spatially explicit comparative static model that simulates a region's land use pattern based on natural, socioeconomic, political, and technological parameters. The model assumes land rent maximizing behavior of land users. It calculates and assigns the land rent maximizing land use system for every investigated decision unit, generally a field. A land use system is characterized through crop rotation, corresponding outdoor operations, animal husbandry if applicable, and the relevant political and socioeconomic attributes. The fuzzy expert system derives the values of ecologically relevant parameters from several site specific attributes and land use operations. Land use dependent site characteristics that influence plant species richness are derived from predictions generated by ProLand. Detailed information on crop rotation, fertilization and pesticide strategy, and outdoor operations are considered. The expert system then classifies natural and land use dependent site characteristics into aggregate factors. Based on a set of rules it assigns the number of species to the classes and thus to the decision units. Simulation results for the study area show that the CAP reform causes a rise in grassland area. These land use changes mainly occur in areas currently used for arable farming but with natural conditions favoring grassland. Plant species richness is positively influenced by the increase in extensive grassland area.
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