Abstract
Introduction: The Florida coast is one of the most species-rich ecosystems in the world. This paper focuses on the sensitivity of the habitat of threatened and endangered shorebirds to sea level rise induced by climate change, and on the relationship of the habitat with the coastline evolution. We consider the resident Snowy Plover (Charadrius alexandrinus nivosus), and the migrant Piping Plover (Charadrius melodus) and Red Knot (Calidris canutus) along the Gulf Coast of Mexico in Florida. Methods: We analyze and model the coupled dynamics of habitat patches of these imperiled shorebirds and of the shoreline geomorphology dictated by land cover change with consideration of the coastal wetlands. The land cover is modeled from 2006 to 2100 as a function of the A1B sea level rise scenario rescaled to 2 m. Using a maximum-entropy habitat suitability model and a set of macroecological criteria we delineate breeding and wintering patches for each year simulated. Results: Evidence of coupled ecogeomorphological dynamics was found by considering the fractal dimension of shorebird occurrence patterns and of the coastline. A scaling relationship between the fractal dimensions of the species patches and of the coastline was detected. The predicted power law of the patch size emerged from scale-free habitat patterns and was validated against 9 years of observations. We predict an overall 16% loss of the coastal landforms from inundation. Despite the changes in the coastline that cause habitat loss, fragmentation, and variations of patch connectivity, shorebirds self-organize by preserving a power-law distribution of the patch size in time. Yet, the probability of finding large patches is predicted to be smaller in 2100 than in 2006. The Piping Plover showed the highest fluctuation in the patch fractal dimension; thus, it is the species at greatest risk of decline. Conclusions: We propose a parsimonious modeling framework to capture macroscale ecogeomorphological patterns of coastal ecosystems. Our results suggest the potential use of the fractal dimension of a coastline as a fingerprint of climatic change effects on shoreline-dependent species. Thus, the fractal dimension is a potential metric to aid decision-makers in conservation interventions of species subjected to sea level rise or other anthropic stressors that affect their coastline habitat.
| Original language | English (US) |
|---|---|
| Article number | 9 |
| Pages (from-to) | 1-17 |
| Number of pages | 17 |
| Journal | Ecological Processes |
| Volume | 1 |
| Issue number | 1 |
| DOIs | |
| State | Published - 2012 |
Bibliographical note
Funding Information:This research was supported by the US Department of Defense, through the Strategic Environmental Research and Development Program (SERDP), Project SI-1699. M.C. acknowledges the funding of project “Decision and Risk Analysis Applications Environmental Assessment and Supply Chain Risks” for his research at the Risk and Decision Science Team. The computational resources of the University of Florida High-Performance Computing Center ( http://hpc.ufl.edu ) are kindly acknowledged. The authors cordially thank Dr. RA Fisher (Engineering Research and Development Center of the US Army Corps of Engineers) and the Eglin Air Force Base personnel for their help in obtaining the data and for the useful information about the breeding information of SNPL. Tyndall Air Force Base and Florida Wildlife Commission are also gratefully acknowledged for the assistance with the data. We thank M.L. Chu-Agor (currently at the Center of Environmental Sciences, Department of Biology and Earth and Atmospheric Sciences, Saint Louis University, St. Louis, MO) for her computational effort with SLAMM at the University of Florida. Permission was granted by the USACE Chief of Engineers to publish this material. The views and opinions expressed in this paper are those of the individual authors and not those of the US Army or other sponsor organizations.
Keywords
- Coastal wetlands
- Coastline complexity
- Fractal dimension
- Habitat suitability
- Land cover change
- Patches
- Sea level rise
