2024 CSDMS meeting-043: Difference between revisions

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{{CSDMS meeting abstract title temp2024
{{CSDMS meeting abstract title temp2024
|CSDMS meeting abstract title=Methane Production in Tidal Marshes over Decadal Time Scales: Insights from a Morpho-dynamic Model
|Working_group_member_WG_FRG=Coastal Working Group, Chesapeake Focus Research Group, Human Dimensions Focus Research Group, Ecosystem Dynamics Focus Research Group
|Working_group_member_WG_FRG=Coastal Working Group, Chesapeake Focus Research Group, Human Dimensions Focus Research Group, Ecosystem Dynamics Focus Research Group
}}
}}

Revision as of 09:27, 7 February 2024



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Methane Production in Tidal Marshes over Decadal Time Scales: Insights from a Morpho-dynamic Model


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 for substrate, 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 its distance from the marsh/lagoon boundary and its carbon pool available for decomposition. 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 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.