A Bayesian Network approach to developing effective policies for more sustainable rural land use and development is presented which: • incorporates several different stakeholder viewpoints • integrates and balances the results from different viewpoints, and thus facilitates compromise land use solutions • elucidates the main factors affecting stakeholders' decisions, on which policy levers will operate more effectively • allows differences between "expected change" and "observed change" to be understood as arising from uncertainty and variation about "the average situation" • demonstrates the crucial roles of beliefs and uncertainties in determining the preferred options of different groups • emphasises the need to know the beliefs and uncertainties of local land managers • incorporates public participation and social learning while such necessary data are gathered. The approach's merits for fostering pro-active policy design and subsidiarity, and for focusing the research needed to underpin rural policy are discussed.
Spatial and temporal change in urban-rural land use transformation at village scale—A case study of Xuanhua district, North China
