Predicting the persistence of coastal wetlands to global change stressors

Abstract

Despite progress toward understanding the response of coastal wetlands to increases in relative sea-level rise and an improved understanding of the effect of elevated CO2 on plant species allocation patterns, we are limited in our ability to predict the response of coastal wetlands to the effects associated with global change. Static simulations of the response of coastal wetlands to sea-level rise using LIDAR and GIS lack the biological and physical feedback mechanisms present in such systems. Evidence from current research suggests that biotic processes are likely to have a major influence on marsh vulnerability to future accelerated rates of sea-level rise and the influence of biotic processes likely varies depending on hydrogeomorphic setting and external stressors. We have initiated a new research approach using a series of controlled mesocosm and field experiments, landscape scale studies, a comparative network of brackish coastal wetland monitoring sites and a suite of predictive models that address critical questions regarding the vulnerability of coastal brackish wetland systems to global change. Specifically, this research project evaluates the interaction of sea level rise and elevated CO2 concentrations with flooding, nutrient enrichment and disturbance effects. The study is organized in a hierarchical structure that links mesocosm, field, landscape and biogeographic levels so as to provide important new information that recognizes that coastal wetland systems respond to multiple interacting drivers and feedback effects controlling wetland surface elevation, habitat stability and ecosystem function. We also present a new statistical modelling technique (Structural Equation Modelling) that synthesizes and integrates our environmental and biotic measures in a predictive framework that forecasts ecosystem change and informs managers to consider adaptive shifts in strategies for the sustainable management of coastal wetlands.