2024 CSDMS meeting-043: Difference between revisions
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|CSDMS Pronouns=He/Him | |CSDMS Pronouns=He/Him | ||
|CSDMS meeting institute=Montclair State University | |CSDMS meeting institute=Montclair State University | ||
|CSDMS meeting city= | |CSDMS meeting city=Montclair | ||
|CSDMS meeting country=United States | |CSDMS meeting country=United States | ||
|CSDMS meeting state=New Jersey | |CSDMS meeting state=New Jersey | ||
Revision as of 08:39, 14 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 greenhouse gas with more warming potential than carbon dioxide. As sulfate availability increases sulfate-reducers outcompete methanogens, and methane production decreases. Such a shift from methanogenesis to sulfate reduction as the predominant decompositional pathway can occur within tidal marshes experiencing 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 rate of SLR, the 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 edge of the marsh/lagoon boundary and the labile carbon available for decomposition. We parameterize the model to marshes along the Mullica River, NJ. 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 marshes for ecosystem services or for carbon emission reduction may arise in management decisions. Generally, policy makers and coastal managers can use this model to account for emission reduction goals in marsh restoration projects.
