The analysis of the relationships between people and nature is complex, because it involves bringing together insights from a range of disciplines, and, when stakeholders are involved, the perspectives and values of different interest groups. Although it has been suggested that analytical-deliberate approaches may be useful in dealing with some of this complexity, the development of methods is still at an early stage. This is particularly so in relation to debates around the concept of ecosystem services where biophysical, social and economic insights need to be integrated in ways that can be accessed by decision-makers. The paper draws on case studies to examine the use of Bayesian Belief Networks (BBNs) as a means of implementing analytical-deliberative approaches in relation to mapping ecosystem services and modelling scenario outcomes. It also explores their use as a tool for representing individual and group values. It is argued that when linked with GIS techniques BBNs allow mapping and modelling approaches rapidly to be developed and tested in an efficient and transparent way, and that they are a valuable scenario-building tool. The case-study materials also show that BBNs can support multicriteria forms of deliberative analysis that can be used to capture stakeholder opinions so that different perspectives can be compared and shared social values identified.
CASH FLOW FORECASTING WITH RISK CONSIDERATION USING BAYESIAN BELIEF NETWORKS (BBNS)
