The greater Everglades region in Florida, USA, is an area of freshwater wetlands that has been highly altered, and reduced to 50% of its original area. The Everglades ecosystem is threatened by a variety of factors including drainage, development, invasive species, climate change, pollution, and changes in regional hydrology. Spatial landscape analysis can help guide a complex restoration process involving billions of dollars, and multiple groups of stakeholders.
To guide Everglades management efforts, we evaluated ecological performance of different hydrologic restoration scenarios using a novel technique, the structural similarity index, which quantitatively compares similarity between pairs of gridded maps in terms of mean, variance, and covariance. Using the structural similarity index, we evaluated performance of several indicator species under multiple restoration scenarios that varied in operations, amounts of water storage, removal of levees and canals (decompartmentalization), and seepage control barriers. We then compared indicator response under each restoration scenario to a target scenario that simulated the natural system.
Results/Conclusions
Our results demonstrated that decompartmentalization benefits these indicator species. In general, scenarios with larger amounts of water storage were also closer to the target scenario. This spatial comparison technique that the structural similarity index provides is a robust, multi-factor evaluation of similarity on both a local and global scale that is useful for evaluating restoration efforts. This approach provides a reliable means of scenario comparison, accounting for both the local magnitude and spatial structure of the underlying data. The results can be used to inform management and restoration efforts, and to guide policy. While we applied this tool to Everglades restoration projects, it can be useful for assessing restorations efforts in different ecosystems as well.