Nitrogen cycling processes in the surface water of Dongshan Bay in summer based on stable isotope method
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Abstract
Excessive nitrogen input driven by anthropogenic activities has become one of the primary causes of eutrophication in coastal bays. Elucidating the nitrogen cycling processes in bay areas is fundamental to effectively managing coastal ecosystems and understanding biogeochemical cycles. Dongshan Bay is a prominent mariculture bay located in southeastern Fujian; however, the transport and transformation of nitrogen in Dongshan Bay’s surface water remain poorly understood. In this study, the concentrations of nutrients (NO3− and NH4+) and their corresponding stable nitrogen and oxygen isotope compositions (δ15N-NO3−, δ18O-NO3−, δ15N-NH4+), alongside the stable nitrogen isotope values of particulate organic nitrogen (δ15N-PON), were measured in the surface water of Dongshan Bay during the summer of 2022. By integrating these data with the Keeling plot approach, end-member mixing models, and other statistical methods, we characterized the nitrogen cycling processes in the bay’s summer surface waters. The salinity-based mixing model and the relationships of δ15N-NO3− and δ18O-NO3− relative to NO3− concentrations indicated the occurrence of non-conservative transformation processes, including nitrification and assimilation, in the surface waters during summer. Furthermore, the enrichment ratio of δ15N-NO3− to δ18O-NO3− deviated from the 1∶1 ratio, with ∆(15,18) values ranging from −12.54‰ to 5.47‰ mean of (−5.05±4.57)‰. Coupled with the significant negative linear correlation between δ15N-NH4+ and δ15N-PON (R2 = 0.40, P < 0.05), these findings demonstrate that nitrogen transformation in the surface waters of Dongshan Bay is predominantly driven by particulate organic matter mineralization coupled with nitrification. This study provides valuable insights for preventing, controlling, and managing nitrogen pollution in Dongshan Bay, and establishes a baseline for future research on microbial-mediated nitrogen cycling processes.
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