Computer models to synthesize/ communicate complex information for management and political decision
We combine elements of our previous work to generate a computer-assisted procedure to give the various stakeholders of the Lerma-Santiago basin (the second largest river basin in Mexico) a greater say in the economic and environmental decisions that affect them. The basic concept of the project is to represent the most important aspects of the basin in a series of images and graphs that can be displayed simultaneously, and which represent historical reality as well as future scenarios. Our model is based on a computer model/visualization Charles Hall constructed for the country of Costa Rica. Two important issues are represented by this complex evolving image. First, the data are linked: e.g. one cannot have agricultural expansion without deforestation and/or increased use of fertilizers. Second, the simulations are an extension of displayed past patterns, so that mostly they seem intuitively reasonable. With the simulations one can “joystick” a quite different future. Thus if one stakeholder group is interested in e.g. conserving natural forests it has implications for agricultural production, economic change and nutrients. If citizens do not like some of the consequences they can make their complaints explicit. Then the scientists involved have to show and defend (or change) the relations they have built into the model, give the studies that support that and make their case. This can be done with a layered approach to each graphlet, where it is possible to click on the graphs and examine the empirical and modeled relation between and among variables. Ideally, this contributes to the ability of stakeholders to examine the explicit, quantitative relations behind the impacts of their own, or someone else’s, decisions. The stakeholder then sees the impact of his or her assumptions about the relation. We perceive this entire process as bringing the political decision making process out from “behind the curtain” and into direct stakeholder scrutiny.