Understanding Resilience in Coastal Wetlands Using a Multi-Method Model
This study aimed to reduce inconsistent model predictions of coastal wetland change by incorporating eco-geomorphological processes (interactions between organisms and the surrounding landforms/environment) in a multi-algorithm approach.
Image from the U.S. Fish and Wildlife Service
To compete with rising sea levels, coastal wetlands must receive adequate supplies of sediment and organic matter. Presently, there is disagreement in the scientific community on how fast these processes happen due to varying uncertainty and estimates among different models. This has made it difficult to predict whether wetlands can survive as the planet warms. In response, this study created a novel framework that models eco-geomorphological processes (i.e., interactions between organisms and the surrounding landforms/environment) using multiple methods to reduce uncertainty. The new approach better predicts how these processes change over space in three representative coastal wetland sites. It also reveals how many observations and wetland sites are needed to improve predictions.
Coastal wetlands are crucial in global water and carbon cycles, so the inclusion of these ecosystems in Earth system models (ESMs) will improve climate predictions. However, current models used to predict how coastal wetlands will change in response to sea level rise often produce significantly different results. This study uses a new approach to combine several modeling methods of eco-geomorphological processes into one framework. The results of each method were then compared against data from three representative coastal wetland sites to determine the optimal approach for simulating coastal wetlands in ESMs. This study also emphasized the importance of coordinated observations in different elevations across diverse wetland sites to reduce model uncertainty.
Coastal wetlands are crucial in global water and biogeochemical cycles. To keep pace with rising sea levels, these wetlands must accumulate sediment and organic matter to elevate their ground level. However, current models of predicting these eco-geomorphological processes often give different results on coastal wetland survival. This inconsistency has hindered the representation of these ecosystems in ESMs. To bridge the gap, this study developed a multi-algorithm model framework that integrates different methods of simulating sediment and organic matter buildup within a unified hydrodynamics model. The framework was then tested at three well-known coastal wetland sites: two salt marshes and one mangrove wetland. The comparison between model predictions and observations showed that the new multi-algorithm approach is more reliable than traditional single-method models. Additionally, this study highlights the current lack of sufficient eco-geomorphological observations needed to constrain these models. This emphasizes the need for coordinated observations at various elevations across diverse wetland sites to reduce model uncertainties. The outcomes of this research not only advance the representation of coastal wetlands in ESMs but also help better predict the impacts of climate change on these vital ecosystems.