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Spatiotemporal Dynamics of Mesozooplankton Trophic Structure and Food Web Configuration in the Vicinity of Daya Bay
Yanjiao Lai1, Bingqing Liu2,3, Mianrun Chen1
1South China Sea Development Research Institute, Ministry of Natural Resources (Remote Sensing Technology Application Center of South China Sea, MNR), Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Guangzhou 510300, China.
Abstract:
Mesozooplankton play a pivotal role in marine pelagic food webs, mediating energy and matter transfer between primary producers and higher trophic levels. Daya Bay, a semi-enclosed bay located in the northern South China Sea, has undergone significant environmental changes due to anthropogenic activities, such as thermal discharge from nuclear power plants and eutrophication. This study examined the mesozooplankton community structure, feeding preferences, and food web organization through four seasonal cruises (May 2022, February 2023, August 2023, and November 2023), employing stable isotope analysis and a Bayesian Isotopic Mixing Model. Results indicate that mesozooplankton abundance and diversity were lower in regions affected by thermal discharge, suggesting a suppressive effect of elevated temperatures. Seasonal shifts in dominant species were observed: Penilia avirostris and Dolioletta gegenbauri dominated the community in spring, while Noctiluca scintillans blooms occurred in summer and winter. Isotopic analysis revealed distinct trophic strategies: copepods exhibited omnivorous habits, whereas cladocerans and tunicates showed stronger herbivorous tendencies. N. scintillans functioned as a high-trophic omnivore, preying on copepod larvae and competing for food resources. Overall, the mesozooplankton community was characterized by an omnivory-dominated trophic network, which enhanced resilience yet remains sensitive to anthropogenic disturbances. This study clarifies how human-induced environmental changes reshape trophic pathways in subtropical coastal waters, providing a valuable reference for long-term monitoring and ecosystem management in Daya Bay.
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