Shorebird patches as fingerprints of fractal coastline fluctuations due to climate change

Convertino, M., A. Bockelie, G.A Kiker, R. Muñoz-Carpena and I. Linkov. Shorebird patches as fingerprints of fractal coastline fluctuations due to climate change

2012. Ecological Processes 1:9, 2012-10-30

Abstract: 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. 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. 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. 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.

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