Understanding and Applying Landscape Simulation Models to Predict Sea-Level Rise and Ecosystem Impacts under Climate Change

Thomas W Doyle, USGS Wetland and Aquatic Research Center, Lafayette, LA, United States and Bogdan Chivoiu, University of Louisiana at Lafayette, Lafayette, LA, United States
Abstract:
Coastal wetlands are undergoing retreat and migration from increasing tidal inundation and saltwater intrusion attributed to climate variability and sea-level rise. Eustatic sea level has been rising since the last ice age and over the last century by 2 mm/year, but actual rates vary regionally as dictated by land subsidence, uplift, and other surficial processes. Long-term tide gage records are among the most reliable measures of local and regional land motion and provide the basis for generating projected sea-level heights under climate change. Complementary tools and models that use on-shore tide gage records and short-term off-shore satellite altimetry observations have been developed by the U.S. Geological Survey to construct future sea-level trends and to predict coastal submergence for different coastal reaches and climate change scenarios. The impact of sea-level rise on intertidal wetlands and marsh migration upslope is still poorly understood, but field evidence indicates that tidal freshwater forests exhibit direct loss of structure, density, and species diversity from modest increases in soil salinity that are initiated by complex interactions of storm tides and droughts. For example, Taxodium distichum, baldcypress, is the last survivor and most salt tolerant of freshwater tree species common to degraded, monospecific stands along the marsh-estuarine ecotone for much of the southeastern U.S. coastline. The distribution and range of baldcypress corresponds with the elevation of ancient sea level (about 120 m above current sea level) dating back to highstand shoreline of the late Cretaceous epoch nearly 65 million years ago. Various ecological modeling applications will be discussed to show their utility as decision-support tools for adaptation planning and land management under different climate change scenarios.