Cooperative Fish and Wildlife Research Units Program: Florida
Education, Research and Technical Assistance for Managing Our Natural Resources

Florida Project


Structured decision making, ecological thresholds and the establishment of management trigger points

July 2007 - December 2009


Personnel

Participating Agencies

  • Patuxent Wildlife Research Center

Discussions of "ecological thresholds", "acceptable variation" and "management trigger points" occur frequently in discussions of ecological monitoring programs (e.g., Noon 2003). However, these discussions tend to be vague and rambling, with some agreement on the general need for thinking about such issues, but little detail about how to proceed to actually define these concepts either generally or for specific problems (e.g., specific monitored systems). This recognition appears to have motivated the Request for Proposals on this topic as part of the USGS National Park Monitoring Program. Researchers thus propose to do the following. (1) Provide a conceptual framework for thinking about the concepts of thresholds, acceptable variation and trigger points in terms of a structured decision process. In particular, researchers will demonstrate that structured decision making provides a natural framework for such concepts and leads to clear thinking about the nature of such concepts and means of defining them. (2) Provide a step by step procedure that leads to a decision matrix for optimal decisions. Decision matrices specify what management action to take for each possible set of values of the state variable(s) of interest and thus explicitly provide thresholds and trigger points that are optimal with respect to objectives. Researchers will work with National Park personnel from one or more parks to implement the approach with one or more example issues. Specifically, they will begin with the development of objectives and available management actions, move to model(s) development, consider the kind of monitoring program(s) available to estimate system state and then develop decision matrices that are optimal with respect to the objectives.