Application of one Preference Modeling Methodology (Outranking Method) to the Development of a Predictive Tool to Assess the Vulnerability of the Ecosystem Regarding Mercury Concentration in Fish

摘要

The objective of this study is to use a preference modeling methodology as a predictive tool to roughly assess the vulnerability of the ecosystems regarding mercury concentration in fish. Concretely, we apply a preference modeling methodology to outrank lakes from highest to lowest mercury concentration in fish using simple environmental factors. Among the numerous variable influencing mercury fate in the environment, we only retain simple key-indicators which are expected to influence mercury concentration in fish tissue such as pH, wetland area, and chlorophyll concentration. The preliminary results of the first tests of modeling that we carried out using a set of Canadian Lakes of Boreal forest data are encouraging. Indeed, with only a minimum of criteria, we are able to reproduce the trends of mercury contamination in fish caught in the Outaouais and Chibougamau regions. We are now continuing to apply this methodology to a larger set of lakes from different environments across Canada. We are testing other criteria expected to have influence on mercury concentration in order to refine modeling results and at the same time we are implementing the parameters for model calibration.