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<p>The increasing frequency of freshwater cyanobacterial blooms has emerged as a critical ecological and environmental concern, yet long-term time series data documenting such blooms remain scarce. This study presents a 13-year dataset (2010–2022) from two adjacent subtropical reservoirs (Shidou and Bantou) in Xiamen, Fujian Province, Southeast China. It provides a monthly and quarterly overview of 20 physicochemical parameters (348 samples), microscope-based phytoplankton (348 samples), and DNA sequence-based data for bacteria (342 samples) and microeukaryotes (348 samples). The dataset highlights recurrent cyanobacterial blooms dominated by <i>Raphidiopsis raciborskii</i> (basionym <i>Cylindrospermopsis raciborskii</i>). This long-term dataset serves as a valuable resource for investigating, predicting, and controlling cyanobacterial blooms, and will support efforts in biodiversity forecasting, ecological restoration, and targeted management of freshwater ecosystems.</p>

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Time series of environment and plankton during Raphidiopsis raciborskii blooms in two subtropical Chinese reservoirs

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年5月2日

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  • Shuzhen Li,
  • Huihuang Chen,
  • Lei Jin,
  • Peng Xiao,
  • Jun R. Yang,
  • Zijie Xu,
  • Lemian Liu,
  • Jun Yang

摘要

The increasing frequency of freshwater cyanobacterial blooms has emerged as a critical ecological and environmental concern, yet long-term time series data documenting such blooms remain scarce. This study presents a 13-year dataset (2010–2022) from two adjacent subtropical reservoirs (Shidou and Bantou) in Xiamen, Fujian Province, Southeast China. It provides a monthly and quarterly overview of 20 physicochemical parameters (348 samples), microscope-based phytoplankton (348 samples), and DNA sequence-based data for bacteria (342 samples) and microeukaryotes (348 samples). The dataset highlights recurrent cyanobacterial blooms dominated by Raphidiopsis raciborskii (basionym Cylindrospermopsis raciborskii). This long-term dataset serves as a valuable resource for investigating, predicting, and controlling cyanobacterial blooms, and will support efforts in biodiversity forecasting, ecological restoration, and targeted management of freshwater ecosystems.