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<p>Rapid transformations in coastal ecosystems brought on by climate change and sea-level rise require adaptive conservation strategies to maintain ecological connectivity into the future. Coastal wetlands are particularly vulnerable to sea-level rise, however, if pathways are available for upland migration, coastal wetland habitats may be able to persist under changing environmental conditions. This study presents and compares two complementary approaches for evaluating coastal-to-inland connectivity using the state of Florida as a case study. An improved understanding of connectivity between coastal and inland ecosystems can support state and regional conservation planning initiatives and promote climate resilience. The first analytical approach, the Florida Ecological Greenways Network (FEGN) Coastal to Inland Connectivity Model, is a data efficient method that uses Esri’s Cost Distance tool to identify coastal ecosystem migration corridors based on land cover type. The second approach, the Integrated Coastal Connectivity Model, is a data-rich model that incorporates topographic diversity, a high-resolution flood risk model, and sea-level rise projections from the SLAMM and NOAA marsh migration models. Agreement between the two analytical approaches was as low as 59% in some regions, indicating that while both approaches are valid, model differences can have a considerable impact on predictions. Incorporation of topographic diversity data in the Integrated Coastal Connectivity model reduced agreement between the two approaches by an additional 5–10%, indicating that micro-elevational features can be important determinants for consideration in the development of future migration pathways. The model predictions from this study can inform priorities for land acquisition to protect Florida’s network of aquatic preserves and advance statewide resilience goals. By integrating climate exposure and geomorphological variation into the connectivity analysis, the model presented in this study bridges traditional and advanced spatial modeling techniques to support resilient landscape design in a changing coastal environment.</p>

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Sea level rise escape planning for Florida’s coastal ecosystems

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年11月15日

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  • Eve Bohnett,
  • Michael O’Brien,
  • Reed Noss,
  • Laura Doyle,
  • Paul J. Young,
  • Asena Goren,
  • Thomas S. Hoctor

摘要

Rapid transformations in coastal ecosystems brought on by climate change and sea-level rise require adaptive conservation strategies to maintain ecological connectivity into the future. Coastal wetlands are particularly vulnerable to sea-level rise, however, if pathways are available for upland migration, coastal wetland habitats may be able to persist under changing environmental conditions. This study presents and compares two complementary approaches for evaluating coastal-to-inland connectivity using the state of Florida as a case study. An improved understanding of connectivity between coastal and inland ecosystems can support state and regional conservation planning initiatives and promote climate resilience. The first analytical approach, the Florida Ecological Greenways Network (FEGN) Coastal to Inland Connectivity Model, is a data efficient method that uses Esri’s Cost Distance tool to identify coastal ecosystem migration corridors based on land cover type. The second approach, the Integrated Coastal Connectivity Model, is a data-rich model that incorporates topographic diversity, a high-resolution flood risk model, and sea-level rise projections from the SLAMM and NOAA marsh migration models. Agreement between the two analytical approaches was as low as 59% in some regions, indicating that while both approaches are valid, model differences can have a considerable impact on predictions. Incorporation of topographic diversity data in the Integrated Coastal Connectivity model reduced agreement between the two approaches by an additional 5–10%, indicating that micro-elevational features can be important determinants for consideration in the development of future migration pathways. The model predictions from this study can inform priorities for land acquisition to protect Florida’s network of aquatic preserves and advance statewide resilience goals. By integrating climate exposure and geomorphological variation into the connectivity analysis, the model presented in this study bridges traditional and advanced spatial modeling techniques to support resilient landscape design in a changing coastal environment.