A multi-indicator spatial similarity approach for evaluating ecological restoration scenarios
Context
The greater Everglades region in Florida (USA) is an area of wetlands that has been altered and reduced to 50% of its original area and faces multiple threats. Spatial landscape analysis can help guide a large and complex ecosystem restoration process, involving billions of dollars and multiple groups of stakeholders.
Objectives
To guide Everglades restoration efforts, we evaluated ecological performance of different hydrologic restoration scenarios using a novel technique, the structural similarity index (SSIM), which quantitatively compares similarity between pairs of gridded maps in terms of mean, variance, and covariance.
Methods
Using the SSIM, we evaluated system-wide performance of apple snails, American alligators, Great egrets, and long- and short-hydroperiod vegetation types under multiple restoration scenarios that varied in water management strategies, amounts of water storage, removal of levees and canals (decompartmentalization), and seepage control barriers. We then compared species and habitat responses under each restoration scenario to a target scenario simulating the historical, natural system.
Results
The SSIM approach provides a reliable means of scenario comparison, accounting for both the local magnitude and spatial structure of the underlying data. Our results demonstrated that decompartmentalization benefits the indicator species. In general, scenarios with increased water storage were closer to the target scenario.
Conclusions
This spatial comparison technique is useful for evaluating restoration efforts at multiple spatial scales, ranging from the entire ecosystem down to individual compartments or sub-compartments. The results can be used to inform management and restoration efforts and to guide policy for the greater Everglades area.
Citation Information
| Publication Year | 2019 |
|---|---|
| Title | A multi-indicator spatial similarity approach for evaluating ecological restoration scenarios |
| DOI | 10.1007/s10980-019-00904-w |
| Authors | Ruscena Wiederholt, Rajendara Paudel, Yogesh Khare, Stephen E. Davis, G.M. Naja, Stephanie Romanach, L. Pearlstine, Thomas Van Lent |
| Publication Type | Article |
| Publication Subtype | Journal Article |
| Series Title | Landscape Ecology |
| Index ID | 70205868 |
| Record Source | USGS Publications Warehouse |
| USGS Organization | Wetland and Aquatic Research Center |