Integration of Field- and Space-Based Observations Toward Assessing Drivers of Biogeochemical Variability Across Vulnerable Coastal Ecosystems

This thesis uses new field datasets and satellite ocean color products to quantify biogeochemical variability in three coastal regions: Long Island Sound estuary, the coastline of the Bay of Bengal extending east to the Mekong Delta, and the Yukon River Delta. These three study regions have vastly different size domains, climates, populations, and economies, but all require enhanced coastal water monitoring in the face of climate change. These regions are all naturally dynamic and experience strong seasonal phenomena but are also subject to changing hydrological forcings and direct anthropogenic perturbations. This leaves these coastal areas vulnerable to altered biogeochemical cycling, diminished water quality, and recurring ecosystem threats, such as hypoxia and eutrophication, with implications for coastal carbon cycling and threatening livelihoods, nutrition, and cultures dependent on healthy marine ecosystems. The four chapters in this thesis integrate different methods based on the unique data availabilities of each area but are all motivated by the same science question: What are the drivers of biogeochemical variability across vulnerable coastal ecosystems? Focusing on two key indicators of the biogeochemical state of an aquatic system, dissolved organic matter (DOM) and chlorophyll-a, the main objective is to assess spatial and temporal dynamics of these variables in relation to changing water quality conditions and ecological processes across urban-to-rural and temperate-to-polar-regions. Chapter 1 presents a robust new dataset of colored DOM (CDOM) absorption and fluorescence across Long Island Sound’s urban-to-rural longitudinal gradient, across its dynamic river mouths, and during all seasons over five years. These comprehensive in situ measurements allowed us to elucidate the impact of hydrologic, anthropogenic, and biological processes on DOM dynamics and, subsequently, biogeochemical variability and trophic status in this complex urban estuary. The mechanisms identified that exhibit control on Long Island Sound CDOM – freshwater discharge, wastewater inputs, and primary productivity – are all subject to climate change impacts. Chapter 2 presents novel machine learning algorithms for high spatial satellite retrievals of CDOM absorption at 300 nm (aCDOM(300)), a proxy for CDOM amount, and S275-295, the spectral slope of CDOM from 275-295 nm, a strong indicator of terrestrial CDOM inputs and photochemical degradation; satellite retrieved aCDOM and S275-295 were used to estimate dissolved organic carbon concentration. Applied to the entire mission time series of Landsat-8 in Western Narrows, these satellite retrievals provide new insights into the anthropogenic inputs, terrigenous inputs, and primary productivity of Long Island Sound’s most impaired water quality region that cannot be captured with coarser resolution satellite sensors. In Chapter 3, a retrospective ocean color analysis was conducted synchronously across ten large river basin mouths in South and Southeast Asia from 2003 to 2019. The chlorophyll-a product from the Ocean Colour Climate Change Index was used and further processed with pixel-filling. Chlorophyll-a was systematically quantified at river basin mouths using static polygons of ocean color pixels at monthly timestamps, allowing for capturing seasonal and interannual changes across basins. This ocean color data was analyzed alongside model outputs of river basin precipitation and discharge to understand drivers of primary productivity for a region with strong anthropogenic impacts to river discharges, land use, nutrient inputs, and cycling that is simultaneously subject to domineering seasonal shifts from monsoons. Chapter 4 focuses on the importance of new data collection for the changing coastal Arctic and highlights research collaborations with the Native Village of Alakanuk, Alaska, in the Yukon River Delta. With regime shifts from warming, permafrost carbon mobilization, and altered river discharge timing and magnitudes, high-temporal data is needed to determine shifts in CDOM and DOC amounts and compositions across the ice-free hydrograph. This data collection could only be achieved with local community collaboration. It is essential that all scientific Arctic research centers and directly benefits communities, as Indigenous peoples are the experts on changes manifesting in the Arctic.

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