Understanding the Impacts of Freshwater Fluxes on the Biogeochemistry of the Coastal Arctic: A Case Study of Prudhoe Bay
The Arctic region, undergoing significant environmental changes due to rapid warming, faces alterations in air temperatures, melting permafrost, declining sea ice, and changes in riverine inputs. These shifts have profound implications for Arctic coastal ecology and biogeochemical cycles. This study...
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| Format: | Thesis |
| Language: | English |
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CUNY Academic Works
2023
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| Online Access: | https://academicworks.cuny.edu/cc_etds_theses/1116 https://academicworks.cuny.edu/context/cc_etds_theses/article/2184/viewcontent/auto_convert.pdf |
| Summary: | The Arctic region, undergoing significant environmental changes due to rapid warming, faces alterations in air temperatures, melting permafrost, declining sea ice, and changes in riverine inputs. These shifts have profound implications for Arctic coastal ecology and biogeochemical cycles. This study, focusing on Alaska's North Slope, explores the influence of freshwater fluxes on water optical properties, vital for accurate satellite remote sensing interpretations. Our approach combined field measurements, existing data, and satellite remote sensing retrievals to identify biogeochemical gradients and their seasonal and interannual variations. A novel finding was the unique CDOM composition in Prudhoe Bay, characterized by a lower molecular weight of organic matter, potentially due to high primary production or low terrestrial inputs. Seasonal influences on chlorophyll-a concentrations and primary productivity were identified, driven by changes in light availability and nutrient supply due to sea ice coverage. While the coefficient of determination (R^2) between the MDN and Level-2 chlorophyll-a data were both found to be low compared to the observed data, the utilization of weights in a Taylor diagram analysis provided more nuanced insights. By considering the influence of river distance and discharge in the weighted calculations, the analysis revealed distinct characteristics of the two algorithms. Specifically, the Level-2 chlorophyll algorithm exhibited a stronger relationship with the observed data but was less accurate in its estimates. In contrast, the MDN-trained chlorophyll algorithm demonstrated more accurate predictions but had a weaker relationship with the observed data. This approach underscores the importance of considering weighted metrics in evaluating the performance of different algorithms, offering a more comprehensive understanding of their behavior in relation to observed data. Our nine-year comprehensive study emphasizes the complex relationship between environmental factors and ... |
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