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Document Details
Title |
Tidal marsh vertical carbon fluxes across spatial and environmental gradients: enhancing satellite-derived blue carbon modeling |
Archive |
All Files / Documents / Publications / Theses - Dissertations |
Abstract |
Tidal marshes, with other tidal wetlands collectively known as blue carbon (BC), are important ecosystems in the global carbon (C) cycle. The IPCC Special Report on the Ocean and Cryosphere in a Changing Climate highlights the importance of quantifying BC in combating climate change. Satellite remote sensing (RS) models fusing surface reflectance and weather/climatology products are often used to quantify and predict gross primary production (GPP) at broad spatiotemporal scales. However, existing RS GPP models are not parameterized for tidal wetlands, and only a few studies have investigated this issue. Therefore, research was needed to determine specific drivers of vertical C fluxes in tidal marshes across space and time. We focused on a bottom-up approach to study the influence of marsh heterogeneity on ecosystem scale vertical C fluxes. Specifically, we looked at how changes in emergent leaf area (ELA) through the tidal cycle across Spartina alterniflora morphological canopy types altered C fluxes. We then determined a simple RS-based relationship between a vegetation index (NIRv) and ELA, allowing data capturing inundated marshes to be used in GPP models. Next, we increased our scale to the marsh domain and measured the differences and drivers of interannual net ecosystem exchange (NEE) by S. alterniflora canopy type. This work highlighted the spatial heterogeneity of C exchange across a single tidal marsh. Then, expanding to a comparison between two marshes in Georgia and Mississippi dominated by different species, we identified and ranked the environmental gradients impacting each marsh's light use efficiency, the ratio of gross productivity and light absorption, a key variable in GPP modeling. Finally, we broadened our scale to assess the C and greenness phenologies of different tidal marshes and used our previous research findings to parameterize and tidal marsh specific GPP RS model. Our new model could predict tidal marsh GPP with an accuracy of 7.4 g Cm-2 per 8-day, representing a 10.5% error. Our research highlighted how important spatial heterogeneity is in marsh C fluxes and will inform future work measuring and modeling C dynamics under future climate conditions. |
Contributor |
Peter Hawman |
Citation |
Hawman, P. 2024. Tidal marsh vertical carbon fluxes across spatial and environmental gradients: enhancing satellite-derived blue carbon modeling. Ph.D. Dissertation. University of Georgia, Athens, GA. |
Key Words |
carbon fluxes, modeling |
File Date |
2024 |
Web Link |
 view/download Web link |
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