Landscape-based spatially explicit species index models for everglades restoration
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Abstract
As part of the effort to restore the ∼10 000-km2 Everglades drainage in southern Florida, USA, we developed spatially explicit species index (SESI) models of a number of species and species groups. In this paper we describe the methodology and results of three such models: those for the Cape Sable Seaside Sparrow and the Snail Kite, and the species group model of long-legged wading birds. SESI models are designed to produce relative comparisons of one management alternative to a base scenario or to another alternative. The model outputs do not provide an exact quantitative prediction of future biotic group responses, but rather, when applying the same input data and different hydrologic plans, the models provide the best available means to compare the relative response of the biotic groups. We compared four alternative hydrologic management scenarios to a base scenario (i.e., predicted conditions assuming that current water management practices continue). We ranked the results of the comparisons for each set of models. No one scenario was beneficial to all species; however, they provide a uniform assessment, based on the best available observational information, of relative species responses to alternative water-management plans. As such, these models were used extensively in the restoration planning.
Study Area
| Publication type | Article |
|---|---|
| Publication Subtype | Journal Article |
| Title | Landscape-based spatially explicit species index models for everglades restoration |
| Series title | Ecological Applications |
| DOI | 10.1890/1051-0761(2000)010[1849:LBSESI]2.0.CO;2 |
| Volume | 10 |
| Issue | 6 |
| Year Published | 2000 |
| Language | English |
| Publisher | Ecological Society of America |
| Description | 12 p. |
| First page | 1849 |
| Last page | 1860 |
| Country | United States |
| State | Florida |
| Other Geospatial | Big Cypress National Preserve, Everglades National Park |
| Google Analytic Metrics | Metrics page |