2024 CSDMS meeting-043
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Eric Dammann,
(He/Him),Montclair State University Montclair New Jersey, United States. dammanne1@montclair.edu
Jorge Lorenzo-Trueba, Montclair State University Montclair New Jersey, United States. lorenzotruej@montclair.edu
Charles Schutte, Rowan University Glassboro New Jersey, United States. schutte@rowan.edu
Tidal marshes store blue carbon because biomass production by vegetation exceeds organic matter decomposition. When methanogenic microorganisms drive decomposition, organic biomass decomposes into methane, a more potent greenhouse gas than carbon dioxide. As sulfate availability increases sulfate-reducers outcompete methanogens, and methane production decreases. Such a shift from methanogenesis to sulfate reduction can occur under sea level rise (SLR), as marsh inundation by saline water increases. Additionally, SLR can lead to changes in marsh morphology and extent. To address this interplay, we adapt a cross-shore numerical model for the evolution of a marsh-lagoon system to predict methane emissions over decadal time scales and under different SLR scenarios. We compute total methane emissions by integrating the methane flux at each location over the width of the marsh platform, which is controlled by the SLR rate, wave energy in the lagoon, and the rate of marsh upland migration. We calculate the methane flux at a given location as a function of the salinity level and type of marsh vegetation. We apply the model to marshes along the Mullica River, NJ, where we have salinity gradient constraints based on three monitoring stations, located at different distances from the river mouth. We find that the highest methane emissions occur in upstream marshes with low salinity exposure; in contrast, the lowest emissions are close to the river mouth, under higher salinity exposure. We found that generally methane emissions increase with higher rates of SLR, however certain environmental conditions allow for scenarios in which higher rates of SLR lead to lower methane emissions. In these specific scenarios, a potential tradeoff between optimizing for ecosystem services or for carbon emission reduction may arise in management decisions. Generally, policy makers and coastal managers could use this model to account for emission reduction goals in marsh restoration projects.
