The challenges of effective model scoping: a FLORES case study from the Mafungausti forest margins, Zimbabwe

This paper explores the challenge of defining the scope of a systems model, emphasising three aspects: boundary, granularity and conceptual scope. The significance of these is illustrated by reference to a model of land-use decisions made in villages bordering on the Mafungautsi forest in zimbabwe. The purpose of this model was to help policy players (Forestry Commission staff, non-governmental organisations, researchers and local people) to understand the impact of policy interventions on local people's livelihoods. Scoping decisions that were made in building the Mafungautsi model were deliberately liberal, to encompass the inerests of all participants in the modelling process. These decisions now present a range of serious challenges: the difficulty of model calibration, the computational expense of running simulations, and the difficulty for new users to understand the model. Facilitators of modelling teams need to consider the serious implications of giving everyone what they want and including all participants' ideas in a model. In the long run, it may be better to be tough and reject many suggestions at the outset. The former approach is unlikely to lead to a tractable model, while the latter may ultimately offer greater satisfaction for all.