Setting restoration targets in the absence of historical data and reference sites

Setting goals for ecological restoration is a critical step for evaluation of alternative scenarios and assessment of monitoring data as management unfolds.  While regaining historical ecosystem functions is a commonly stated goal for restoration, historical ecological data are seldom available for managed ecosystems, and even more rarely are the data consistent with contemporary quantitative standards.  Furthermore, regional-scale restoration initiatives may lack areas to serve as references for setting management goals.  Thus, models provide an important tool for setting expectations and goals for restoration activities. Regaining historical productivity of wading birds is a key goal for restoration of the Everglades ecosystem.  Small fish and macroinvertebrates are abundant components of Everglades food webs and their availability is linked to wading bird nesting success in modern times. These taxa respond relatively quickly to environmental parameters controlled by managers and provide quantitative metrics of ecosystem function whose dynamics are well studied and readily quantified.  However, no data are available on aquatic communities (fish and macroinvertebrates) in the Florida Everglades prior to the outset of drainage in the late 1800’s, and few ecological data of any kind remain from this period.  An added complication in this wetland ecosystem is its dynamic nature resulting from inter-annual variation in rainfall.  Interpretation of monitoring data must be made in the context of expectations based on successional dynamics driven by hydrological fluctuation and mediated by landscape features affecting use of dry-season aquatic refuges.  Statistical and simulation models are the only tools that permit estimating indices of these groups from the historical Everglades for comparison with contemporary conditions.  This presentation will review these challenges for planning, monitoring, and interpreting Everglades restoration efforts, and present strategies for application of contemporary data to simulated hydrologic landscapes.