Li Xiaochuang, Huo Shouliang, Zhang Jingtian, Xiao Zhe, Xi Beidou, Li Renhui
State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, PR China.
Key Laboratory of Algal Biology, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan, Hubei, 430072, PR China.
Environ Sci Ecotechnol. 2020 Jan 11;2:100014. doi: 10.1016/j.ese.2020.100014. eCollection 2020 Apr.
In recent years, blooms have been widely found worldwide. Topics dealing with the mitigation of bloom is of great importance for toxins produced could threaten public health. The paper first investigated dynamics over three years following sediment dredging in a shallow eutrophic Lake Dongqian (China). Based on gene copies, bloom formed with average density of 1.30 × 10 cells/L on July 2009. One year later after sediment dredging, cell density decreased below 1.17 × 10 cells/L or under detected limits during summer days on 2010. While two years later, the bloom period was returned with markedly increased cell density reaching up to 4.15 × 10 cells/L on October 2011, and the maximum peak density was shown at 20.3 °C that was much lower than reported optimal growth temperature. Inferred from Spearman correlation analysis, linear regression showed density was significant and positive with pH and SD, whereas they were significant and negative with TP and DO. Multiple regression analysis further demonstrated that TN, TP, SRP, pH and DO provided the best model and explained 53.1% of the variance in dynamics. The approaches managing nutrients reduction might not control bloom as extremely low TN (avg. 0.18 mg/L) and TP concentrations (avg. 0.05 mg/L) resulted in the highest cell density after sediment dredging.
近年来,水华在全球范围内广泛出现。由于水华产生的毒素可能威胁公众健康,因此应对水华的缓解措施至关重要。本文首先对中国富营养化浅水湖泊东钱湖清淤后三年的[某种藻类]动态变化进行了调查。基于[某种藻类]基因拷贝数,2009年7月形成了平均密度为1.30×10[具体单位]个/升的[某种藻类]水华。清淤一年后,2010年夏季[某种藻类]细胞密度降至1.17×10[具体单位]个/升以下或低于检测限。而两年后,2011年10月水华期再次出现,细胞密度显著增加,达到4.15×10[具体单位]个/升,最高峰值密度出现在20.3℃,远低于报道的最佳生长温度。根据斯皮尔曼相关性分析推断,线性回归显示[某种藻类]密度与pH值和SD呈显著正相关,而与TP和DO呈显著负相关。多元回归分析进一步表明,TN、TP、SRP、pH值和DO提供了最佳模型,解释了[某种藻类]动态变化中53.1%的方差。减少营养物质的管理方法可能无法控制[某种藻类]水华,因为清淤后极低的TN(平均0.18毫克/升)和TP浓度(平均0.05毫克/升)导致了最高的[某种藻类]细胞密度。