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=Hasbrouck Heights
|CSDMS meeting city=Montclair
|CSDMS meeting country=United States
|CSDMS meeting country=United States
|CSDMS meeting state=New Jersey
|CSDMS meeting state=New Jersey
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{{CSDMS meeting abstract title temp2024
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|CSDMS meeting abstract title=Quantifying Methane Emissions in a Tidal Marsh System: Insights from a Morphodynamic 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
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{{CSDMS meeting abstract template 2024
{{CSDMS meeting abstract template 2024
|CSDMS meeting abstract=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.
|CSDMS meeting abstract=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 a higher 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, via the addition of a novel biogeochemical module. 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 test the morphodynamic component of the model on marshes along the Great Bay near the outlet of the Mullica River in southern New Jersey. The model can reproduce the magnitude of morphological change seen in the historical data from 1986-2020. In particular, the model captures that the marsh is eroding faster at the marsh/lagoon boundary than it is being gained by landward migration of the marsh/mainland boundary. Preliminary results of the coupled biogeochemical and morphodynamic model show 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.
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Latest revision as of 13:09, 3 April 2024


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Quantifying Methane Emissions in a Tidal Marsh System: Insights from a Morphodynamic 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 a higher 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, via the addition of a novel biogeochemical module. 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 test the morphodynamic component of the model on marshes along the Great Bay near the outlet of the Mullica River in southern New Jersey. The model can reproduce the magnitude of morphological change seen in the historical data from 1986-2020. In particular, the model captures that the marsh is eroding faster at the marsh/lagoon boundary than it is being gained by landward migration of the marsh/mainland boundary. Preliminary results of the coupled biogeochemical and morphodynamic model show 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.


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