Evaluating consequences of land-use strategies on wildlife populations using multiple-species predictive scenarios

Agricultural activities cause changes to land-use and vegetation characteristics at a smaller temporal scale and at a larger spatial scale than most corresponding natural processes. Simulation models have become important tools to predict future land-use change as a consequence of management policies and in advancing our understanding of the behaviour of complex managed ecosystems. To capture the temporal dynamics and the non-equilibrium properties of agroecosystems and to deal with multidisciplinary trade-offs between economic and conservation interests, it is often necessary for models to be both spatially and temporally explicit and incorporate some component of human decision-making. This paper presents a multiple-species assessment of land-use change scenarios related to ground water protection and pesticide use in a Danish agroecosystem. A spatially explicit simulation model is used that incorporates the temporal dynamics, driven by weather and farming decisions, of an agricultural landscape in great detail. Numeric and spatial outcome of multiple-species predictive scenarios based on real landscapes and realistic simulations of species behaviour and demographics were captured in simple spatial impact indices. Ecological type species were selected for a range of attributes relevant for specific cases to enable a comprehensive description of a broad species response based on a limited number of species. Five ecological type species, a carabid beetle (Bembidion lampros), a linyphiid spider (Oedothorax fuscus), a small farmland bird (skylark, Alauda arvensis), a small mammal (field vole, Microtus agrestis) and an ungulate (roe deer, Capreolus capreolus) were used. Simulation results were aggregated into two values indicating the overall numeric response and the overall spatial response of each type species. These two values indicate the change of conditions experienced by a species and thus make it possible to classify large numbers of species according to their general response.