Description

Abstract: Underlying all decision support systems are criteria scoring and decision rules. A multi-objectives decision support tool known as the Spatial Environment and Agricultural Decision Support (SEADS) tool was developed by SUMAWA team members to be used by land managers and scientists in the identification of appropriate and desirable decisions for landscape management in settings where a variety of multiple competing interests exist. The SEADS toolkit passes observational and model data through mathematical equations termed “scoring functions” that establish a score for various potential land use options; these scores can be used to support decisions made on the ground. As part of the SEADS development, an uncertainty analysis was carried out to determine the degree to which these scoring functions affect the final score, therefore analyzing the extent to which SEADS outcomes may be improperly influenced by functions. Seven methods were used to parameterize three scoring functions that are part of SEADS. Results indicate that parameterization (the programming of the model) disproportionately influenced model outcomes when utilizing the SEADS scoring method. Further research is currently underway to assess the extent to which the model is sensitive to this parameterization. It is therefore important to understand that models like SEADS are intended to be tools that provide decision makers with an additional layer of information for land-use management. Using modeled data must be tempered with rigorous scientific research. In the end, it is the people and not the models that have to make the decisions.