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<p>To evaluate phytoplankton’s indicative value for water quality parameters (including total suspended substances, total phosphorus, total nitrogen, chemical oxygen demand, and pH) under China's aquaculture discharge standards and analyze interactions of nutrients, weather-related parameters, and management practices on phytoplankton, this study conducted an annual survey of water quality and phytoplankton dynamics in ponds stocked with four fish groups: omnivorous crucian carp (<i>Carassius carassius</i>), carnivorous mandarin fish (<i>Siniperca chuatsi</i>), herbivorous grass carp (<i>Ctenopharyngodon idella</i>), and a hybrid fish (<i>Megalobrama amblycephala</i> × <i>Culter Alburnus</i>), along with their water source. Results revealed that fish species significantly affected water quality and phytoplankton abundance in ponds. Hierarchical cluster analysis based on Bray–Curtis similarity classified the phytoplankton communities into three groups: 1. a Cyanobacteria-dominated group, 2. a group with higher phytoplankton diversity, and 3. a Bacillariophyta- and Euglenophyta-dominated group. Compared to α-diversity, the phytoplankton abundance, biomass, and community shifts were more closely associated with water quality, highlighting their value as water quality indicators. Classification and Regression Tree identified total phosphorus (TP) and wind speeds as the predominant factors affecting the phytoplankton community shifts and biomass, respectively. Cyanobacteria domination and high phytoplankton biomass were more likely under low wind speed and high TP. Conditional plot demonstrated that the positive TP-phytoplankton biomass relationship increased with temperature and wind speed within a specific range, differing from natural waters. Partial least squares path modeling (PLS-PM) indicated that fish species and feed application directly affected nitrogen and phosphorus levels, indirectly influencing phytoplankton through these nutrients. Our results highlighted the indicative value of phytoplankton community shifts and importance of reducing phosphorus input from feed to regulate the phytoplankton community. Our study can be applied to evaluate and regulate the water quality by the phytoplankton community in fish ponds.</p>

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Phytoplankton dynamics in aquaculture ponds in China: roles of nutrient loading, weather-related parameters, and management practices

  • 期刊论文

  • 发表日期：

    2025年8月30日

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  • Ke Rao,
  • Chang Wu,
  • Lu Yang,
  • Minghao Sun,
  • Liang Guo,
  • Dan Wu,
  • Xia Cao,
  • Jing Xu

摘要

To evaluate phytoplankton’s indicative value for water quality parameters (including total suspended substances, total phosphorus, total nitrogen, chemical oxygen demand, and pH) under China's aquaculture discharge standards and analyze interactions of nutrients, weather-related parameters, and management practices on phytoplankton, this study conducted an annual survey of water quality and phytoplankton dynamics in ponds stocked with four fish groups: omnivorous crucian carp (Carassius carassius), carnivorous mandarin fish (Siniperca chuatsi), herbivorous grass carp (Ctenopharyngodon idella), and a hybrid fish (Megalobrama amblycephala × Culter Alburnus), along with their water source. Results revealed that fish species significantly affected water quality and phytoplankton abundance in ponds. Hierarchical cluster analysis based on Bray–Curtis similarity classified the phytoplankton communities into three groups: 1. a Cyanobacteria-dominated group, 2. a group with higher phytoplankton diversity, and 3. a Bacillariophyta- and Euglenophyta-dominated group. Compared to α-diversity, the phytoplankton abundance, biomass, and community shifts were more closely associated with water quality, highlighting their value as water quality indicators. Classification and Regression Tree identified total phosphorus (TP) and wind speeds as the predominant factors affecting the phytoplankton community shifts and biomass, respectively. Cyanobacteria domination and high phytoplankton biomass were more likely under low wind speed and high TP. Conditional plot demonstrated that the positive TP-phytoplankton biomass relationship increased with temperature and wind speed within a specific range, differing from natural waters. Partial least squares path modeling (PLS-PM) indicated that fish species and feed application directly affected nitrogen and phosphorus levels, indirectly influencing phytoplankton through these nutrients. Our results highlighted the indicative value of phytoplankton community shifts and importance of reducing phosphorus input from feed to regulate the phytoplankton community. Our study can be applied to evaluate and regulate the water quality by the phytoplankton community in fish ponds.