Comparing two sensitivity analysis approaches for two scenarios with a spatially explicit rural agent-based model

In this paper two sensitivity analysis approaches are applied for scenario analysis in a spatially explicit rural agent-based simulation. The simulation aims to assess the socioeconomic and ecological impacts of agricultural policy interventions, market dynamics and environmental change on a regional scale. Two different methods of sensitivity analysis are investigated: i) a one-at-a-time approach where each parameter is varied one after the other, while all other parameters are kept at their nominal values; and ii) a procedure based on Monte Carlo sampling where random sets of input parameter values are related to outputs of the simulation. The complementarity of both approaches and their contribution to the overall interpretation of the model is shown in two scenarios simulating alternative European policy instruments for biodiversity conservation. Results show that a mixed approach of sensitivity analysis leads to a better understanding of the model's behaviour, and further enhances the description of the simulation's response to changes in inputs and parameter settings.