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Spatiotemporal Dynamics and Driving Mechanisms of Chlorophyll-a in Shenzhen’s Nearshore Waters: Insights from High-Frequency Buoy Observations

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  • Yao Chen

    (Shenzhen Lightsun Technology Co., Ltd., Shenzhen 518029, China
    These authors contributed equally to this work.)

  • Shuilan Wu

    (Shenzhen Lightsun Technology Co., Ltd., Shenzhen 518029, China
    These authors contributed equally to this work.)

  • Lijun Xu

    (Shenzhen Lightsun Technology Co., Ltd., Shenzhen 518029, China)

  • Kaimin Wang

    (Shenzhen Ocean Development Promotion Center, Shenzhen 518067, China)

  • Yu Li

    (Guangdong-Hong Kong-Macao Greater Bay Area Environmental Technology Research Center, Shenzhen Research Institute of Nankai University, Shenzhen 518063, China)

Abstract

Chlorophyll-a (Chl-a) concentration serves as a crucial indicator for assessing phytoplankton biomass and marine ecological health. This study investigated the spatiotemporal characteristics and influencing factors of Chl-a in Shenzhen’s coastal waters using high-frequency monitoring data from 13 buoys deployed from January 2023 to January 2024. The research methodology incorporated comprehensive statistical analyses, including correlation analysis to identify relationships between Chl-a and environmental parameters and a linear mixed model, as well as stepwise regression analysis to determine the dominant factors controlling Chl-a variability across different sea areas. Results revealed distinct spatiotemporal patterns: seasonal Chl-a concentrations ranked as summer > autumn > winter > spring. Spatially, western waters (Pearl River Estuary and Shenzhen Bay) exhibited elevated levels from winter to summer, whereas the eastern Daya Bay peaked in autumn. Mechanistically, regional drivers diverged significantly. River runoff dominated Chl-a variability in the Pearl River Estuary. Temperature and runoff co-regulated dynamics in Shenzhen Bay. Wind-driven mixing and nutrients were the primary controls in Daya Bay, while oligotrophic conditions maintained low levels in Mirs Bay. Salinity and temperature were universal regulators, but nutrient limitations were region-specific, with phosphorus limitation in Shenzhen Bay and nitrogen limitation in Mirs Bay. The high-frequency buoy data effectively captured complex spatiotemporal variability, providing valuable insights for developing targeted management strategies to mitigate red tide risks and improve water quality in these coastal ecosystems.

Suggested Citation

  • Yao Chen & Shuilan Wu & Lijun Xu & Kaimin Wang & Yu Li, 2025. "Spatiotemporal Dynamics and Driving Mechanisms of Chlorophyll-a in Shenzhen’s Nearshore Waters: Insights from High-Frequency Buoy Observations," Sustainability, MDPI, vol. 18(1), pages 1-26, December.
  • Handle: RePEc:gam:jsusta:v:18:y:2025:i:1:p:150-:d:1824418
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