Restoring the Florida Everglades: Insights on Integrating Sea Level Rise into Decision-Support Tools
Year: 2025
Type: article
Abstract: Although coastal ecosystems are impacted by climate change and sea-level rise, many ecological and hydrological models do not yet incorporate sea-level rise projections in their modeling outputs. Therefore, this research examined the various challenges that may prevent sea-level rise from being effectively incorporated in modeling and decision-support tools. We conducted semi-structured interviews with twenty-six professionals involved in Florida's Everglades restoration. We applied the Diffusions of Innovations Theory to better understand factors that can impact practitioners' adoption of newly designed decision-support tools that examine sea-level rise in the freshwater Everglades. The Diffusions of Innovations Theory provided insights into practitioners' perceptions of these tools. We found that these practitioners have a strong interest in using dynamic decision-support tools to plan for sea-level rise impacts on Everglades restoration, particularly when they receive information at appropriate geographic and temporal scales and are given hands-on tools and training. However, challenges that prevent developing these tools include outdated data, limited organizational capacity and funding, limited use of long-term indicators, uncertainty about climate change impacts on local ecosystems, and lack of integration between hydrological and ecological models. Our research also highlights that greater availability of different types of tools can help to meet the needs of the scientific and non-scientific audiences involved in Everglades restoration.
Source: Environmental Management
Authors: Stephanie Castellano, Mysha Clarke, Laura D’Acunto, Stephanie Romañach, Stephanie Cadaval
Institutions: University of Florida, United States Geological Survey
Language: English
Subfield: Global and Planetary Change
Field: Environmental Science
Domain: Physical Sciences
SDGs: Climate action, Life on land
Open Access status: hybrid
Estimated APC paid: $2,690
Award: G3521405599
OpenAlex ID: W4416987108
