The strategy should be implemented soon to test and refine the approach. The CERP AM Strategy proposes a process for addressing uncertainty and supporting collaborative decision making. The objectives, mechanisms, and responsibilities are well specified in the adaptive management strategy, but the all-critical linkages among the planning, assessment, integration, and update activities require further development. The adaptive management strategy should be fully implemented soon to test these all-important linkages to refine the strategy accordingly.
Incorporating active adaptive management practices whenever possible will reduce the likelihood of making management mistakes and reduce the overall cost of the restoration. Active adaptive management approaches that are specifically designed to address uncertainties, such as the Decomp Physical Model (see Chapter 5), offer greater opportunities for learning than an entirely passive approach. Regardless of which adaptive management approach is used, it remains to be seen how willing decision makers will be to make significant alterations to project design and sequencing, as opposed to limiting adaptive management to making modest adjustments in the operation of the CERP projects after their construction.
A coordinated, multidisciplinary approach is required to improve modeling tools and focus modeling efforts toward direct support of the CERP adaptive management process. Models are used to forecast the short- and long-term responses of the South Florida ecosystem to CERP projects and, thus, are the critical starting point for adaptive management. An impressive variety of models has been developed to support the CERP, but better linkages between models, especially between hydrologic and ecological models, are needed to better integrate scientific knowledge and to extrapolate new information to the spatial scales at which decisions are made. In addition, hydrologic models suffer from the lack of high-resolution input data describing the basic terrain, so that their predictions are sometimes in error, and their connections to other more high-resolution ecosystem models is difficult. The development of quantitative ecological models is lagging behind the development of hydrologic models, hindering the model linkages necessary to support the restoration efforts. Because models themselves must be improved through comparison with actual outcomes, coordination between modeling and monitoring efforts, within the adaptive management framework of iterative improvement, should be a high priority.