Cascade reservoirs construction can greatly alter flow regime and sediment transport of rivers, further affecting migration and transformation processes of biogenic elements. The Jinsha River (JSR) is the China's largest hydropower base and the main runoff, sediment suspension, and nutrient source areas of the Yangtze River. However, the distribution, transport, and retention patterns of biogenic elements in the JSR are still unclear under the influence of cascade reservoirs. Therefore, monthly concentration monitoring work was conducted from November 2021 to October 2023 for various forms of carbon (C), nitrogen (N), phosphorus (P), and silicon (Si). Results showed that the concentrations and fluxes of total phosphorus (TP) and particulate phosphorus (PP) exhibited continuous decreasing trends along the reservoirs cascade, whereas N exhibited contrasting trends. The concentrations of dissolved total carbon (DTC), dissolved inorganic carbon (DIC), and total silicon also showed decreasing trends from upstream to downstream, whereas their fluxes were primarily influenced by runoff and exhibited upward fluctuations. Compared with other biogenic elements, there was a more pronounced retention effect on TP and PP by reservoirs, with average retention rates of 8.29 % and 16.01 %, respectively. Longer hydraulic retention time (HRT) can retain more TP and PP. Meanwhile, the retention rates of DTC, DIC, and particulate silicon were positively correlated with HRT, while the retention rate of dissolved silicon (DSi) showed a positive correlation with reservoir age. Moreover, the higher ratios of dissolved inorganic nitrogen to dissolved inorganic phosphorus (DIP) and DSi to DIP have occurred, resulting in apparent P limitation, particularly during the non-flood season due to lower DIP concentration. Overall, cascade reservoirs construction exists great influences on the spatial allocation, fluxes transport, and biogeochemical cycles of biogenic elements, potentially affecting the stability of rivers ecosystem along the food chain network.
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