| Abstract: |
Modelers attempt to synthesize data and knowledge about natural systems in a meaningful way to support policy decision-making for resource managers. Thus, our overarching goal is to turn data into meaningful, actionable information. Throughout this process, modelers and managers must deal with uncertainty – limited knowledge where it is not possible to describe exactly the current state or future state of a system – and risks of undesired effects or losses. The authors illustrate a generalized flow of how data about the natural system are converted into estimates and predictions of quantities of interest to managers (via modeling and analysis) and how those quantities are used for decision-making and for developing natural resource policy. We discuss where uncertainties and risks arise in this flow and suggest some ways to deal with the risks. This symposium session is designed to initiate an ongoing conversation between modelers, resource managers, and other users of model assessment and predictions about how to best communicate and deal with uncertainty and risks for more effective modeling and decision-making. This presentation will develop a taxonomy a risk and uncertainty for framing the discussion that follows during the session and in the future, as well. |
