Coastal wetlands are among the most valuable ecosystems on earth, and are thought to be one of the most at risk to climate change. Marshes in many regions of the world appear to be drowning, and assumptions of a static landscape inspire predictions that about half of the world’s coastal wetlands will submerge in response to sea-level acceleration during this century. Moderate increases in inundation tend to enhance vegetation productivity, mineral sediment trapping, and soil organic matter production, allowing marshes to adjust to increases in sea level rise rate through enhanced vertical accretion. Nevertheless, global sea level rise has been accelerating during the last two centuries and widespread observations of marsh submergence suggest there are limits in the ability of coastal wetlands to adapt. Here we report ensemble simulations of 5 numerical models, capable of predicting dynamic marsh evolution, to consider the conditions under which tidal wetlands can adapt to sea level rise and maintain a position within the intertidal zone. We use this modeling framework to predict whether marshes or subtidal environments represent a stable ecosystem, and to determine threshold rates of sea level rise that trigger a state change.
Results/Conclusions
Our results suggest that marshes will likely survive moderate projections of sea level rise (e.g. estimates from the IPCC that do not incorporate the melting of terrestrial ice sheets) where sediment concentrations are greater than ~0.02 g/L. Under more rapid scenarios of sea level rise (e.g. those that include ice sheet melting), and at lower sediment concentrations, our results suggest that marshes will likely drown and thus convert to subtidal environments near the end of the 21st century. Threshold rates of sea level rise strongly depend on sediment supply, and we hypothesize that historical reductions in sediment delivery rates have made wetland landscapes more prone to ecological collapse than in the past. Our results emphasize that in areas of rapid geomorphic change, predicting the response of ecosystems to climate change requires simultaneous consideration of life and landscape, and the ability of biological processes to modify their physical environment.
