Nonlinear Dynamics and Alternative Stable States in Shallow Coastal Systems

The dynamics of shallow-water coastal environments are controlled by external drivers—sea level rise, storms, and sediment and nutrient supplies—and by internal feedbacks. Interactions of biotic processes (vegetation growth, trophic dynamics) and abiotic drivers can lead to nonlinear responses to changing conditions and to the emergence of thresholds, hysteresis, and alternative stable states. We develop a conceptual framework for studying interactions between the dynamics of marshes and habitats in shallow coastal bays with unconsolidated sediments (seagrass, oyster reefs). Using examples primarily from the Virginia Coast Reserve Long Term Ecological Research site, we show that in the subtidal part of the landscape, two alternative stable states can exist—one dominated by seagrass up to a certain depth that represents a tipping point to the second, unvegetated stable state. The depth limit of the seagrass stable state is influenced by (1) the positive feedback of vegetation on reducing sediment suspension and improving the light environment for growth, (2) climate (e.g., temperature), and (3) water quality. Two stable states are also present in intertidal areas, with salt marshes lying above mean sea level and tidal flats below mean sea level. State transitions are driven by sediment availability, sea level rise, the relative strength of wind waves with respect to tidal currents, and the biotic feedback of vegetation on sediment stabilization and accretion. State-change dynamics in one system may propagate to adjacent systems, and this coupling may influence the landscape-scale response to environmental change. Seagrass meadows and oyster reefs affect adjacent marshes both positively (wave attenuation) and negatively (reduced sediment supply), and marsh-edge erosion could negatively influence the light environment for seagrass growth. Forecasting the resilience of coastal ecosystems and the landscape-scale response to environmental change in the next century requires an understanding of nonlinear dynamics, including the possibility of multiple stable states, the coupled evolution of adjacent systems, and potential early warning signs of thresholds of change