Coastal wetlands play an important role in the global water and biogeochemical cycles. Climate change is making them more difficult to adapt to the fluctuation of sea levels and other environment changes. Given the importance of eco-geomorphological processes for coastal wetland resilience, many eco-geomorphology models differing in complexity and numerical schemes have been developed in recent decades. But their divergent estimates on the response of coastal wetlands to climate change indicate that substantial structural uncertainties exist in these models. To investigate the structural uncertainty of coastal wetland eco-geomorphology models, we developed a multi-algorithm model framework of eco-geomorphological processes, such as mineral accretion and organic matter accretion, within a single hydrodynamics model. The framework is designed to explore possible ways to represent coastal wetland eco-geomorphology in Earth system models and reduce the related uncertainties in global applications. We tested this model framework at three representative coastal wetland sites: two saltmarsh wetland (Venice Lagoon and Plum Island Estuary) and a mangrove wetland (Hunter Estuary). Through the model-data comparison, we showed the importance to use a multi-algorithm ensemble approach for more robust predictions of the evolution of coastal wetlands. We also find that more observations of mineral and organic matter accretion at different elevations of coastal wetlands and evaluation of the coastal wetland models at different sites of diverse environments can help reduce the model uncertainty.

The effect of non-uniform solar radiation over opposing hillslopes leads to aspect-controlled vegetation patterns in semi-arid ecosystems. It creates a differentiation in soil properties and vegetation characteristics. In mid- to high-latitudes where available soil moisture is a limiting factor for vegetation growth, slopes with polewardfacing aspect tend to develop denser vegetation cover that provides more erosion protection than on the equatorward-facing hillslopes. The variation in erosion rates across opposing hillslopes causes the topographic asymmetry of hillslopes over long timescales. The magnitude of this asymmetry is measured by the hillslope asymmetry index (HAI), a metric given as the ratio of the median slope angles of opposite hillslopes. In this study, we present a novel approach to investigate the relationships of HAI with climatological, geomorphic, and ecologic variables at a global scale. Here, we analyzed these relationships using DEM data to compute HAI for 80 different catchments across the world, in which aspect-controlled vegetation has been reported in the literature. We used the CHILD landscape evolution model (LEM), which uses the continuity equation for water, sediment, and biomass, in order to investigate the control of climatological, geomorphic, and ecologic variables on the development of hillslope asymmetry. Preliminary results show that latitude and mean topographic gradient are the two dominant factors affecting hillslope asymmetry due to their vital role in controlling vegetation density through the modulation of incoming solar radiation. These results improve our understanding on how different climatic variables and geographic properties affect the magnitude of hillslope asymmetry and their implications on landform evolution modelling.

Estimates of global carbon stocks in coastal wetlands reveal that these are some of the most efficient carbon-sequestering environments in the world, which has prompted a renewed interest in conservation and restoration programs as an opportunity for greenhouse gas abatement. Accumulation of carbon in coastal wetlands is linked to diverse factors such as the type of vegetation, geomorphic setting, and sediment supply. Feedbacks between these factors and the tidal flow conditions drive the dynamics of carbon accumulation rates. Climate change-induced sea-level rise has been shown to increase the vulnerability to submergence of saltmarsh and mangroves in coastal wetlands, even if accommodation and landward colonization are possible. These potential losses of wetland vegetation combined with the reduced productivity of newly colonized areas will directly affect the capacity of the wetlands to sequester carbon from sediments and root growth. Here, we implement an eco-geomorphic model to simulate vegetation dynamics, soil carbon accumulation, and changes in soil carbon stock for a restored mangrove-saltmarsh wetland experiencing accelerated sea-level rise. We evaluate model outcomes for existing conditions and two different management scenarios aimed at mitigating sea-level rise effects and conserve wetland vegetation. Even though some management measures can result in partial conservation of wetland vegetation, they do not necessarily result in the best option for soil carbon capture. Our results suggest that accelerated sea-level can trigger accelerated wetland colonization resulting in wetland areas with limited opportunities for soil carbon capture from sediment and root mineralization, an issue that has not been considered in previous studies.

Variability in precipitation frequency, intensity and duration deeply affect vegetation and erosion yields. Under climate change scenarios, alterations in precipitation are expected but it is not well understood how it could affect erosion rates and what is the role of vegetation on landscape geomorphic response. Traditional erosion models normally include basic representations of vegetation that do not account for the dynamic character of biomass variability and feedbacks with hydrological and erosion/deposition processes. Hence, using a new modelling frameworks that account for the effect of varying vegetation cover on erosion, and that includes climate change scenarios is needed. Here we use a new model: COPLAS, a tool that couples a Landform Evolution Model with dynamic vegetation and carbon pools modules to investigate the response of landscapes to climate change. The vegetation module includes a coupled photosynthesis-stomatal conductance representation that responds to climatic data inputs as temperature, CO2 concentration and water availability. We use the model to simulate the erosional and geomorphic responses of dynamic vegetation in Howard Springs (Australia) to predicted changes in daily precipitation under future CO2 concentrations of about 940 ppm. The model was calibrated using Ozflux site historical data. Catchment scale simulations were run for a period of 100 years for three scenarios (bare soil, constant and dynamic vegetation) using a daily time step. We found that, for our study case, bare soil produces on average 139% more erosion than the constant vegetation case and 124% more than the dynamic vegetation case. Moreover, an increase in precipitation of around 23% induces an increase of 25%, 35% and 43% in the erosion rates for dynamic vegetation, constant vegetation and bare soil respectively, while a decrease in 26% reduces it in 36%, 60% and 59%. This could be explained by the nonlinear relation between erosion and vegetation (higher rainfall induces higher erosion potential which can be counteracted by an increase in vegetation cover leading to a decrease in soil erodibilty). This finding highlights the importance of considering the dynamic character of vegetation in order to understand the nonlinear relations between fluvial erosion and vegetation cover.