Dong Xin, Zeng Siyu, Bai Fei, Li Dan, He Miao
Environmental Simulation and Pollution Control (ESPC) State Key Joint Laboratory, School of Environment, Tsinghua University, Beijing 100084, China.
Sci Rep. 2016 Feb 15;6:20886. doi: 10.1038/srep20886.
Existing models for predicting microcystin concentration in water body generally use chlorophyll or cyanobacteria concentration as input variables, although microcystins only originate from toxigenic strains of a few species. Moreover, the nonconcurrency between harmful algal growth and toxin release has yet to be quantified. Therefore, this study explored a new prediction method that considers these toxin production mechanisms for the eutrophic Yangcheng Lake, a large-scale drinking water source in China. The Lake was monitored weekly at six sampling sites from July to October in 2012, including the detection of toxigenic Microcystis (expressed as mcyA copy number) by qPCR. Compared with chlorophyll a, cyanobacteria, and total Microcystis abundance, toxigenic Microcystis concentration was more significant in predicting extracellular microcystin. Site-specific nonlinear regression models that link mcyA to microcystins were established. Parameters for toxin release delay (i.e., one or two weeks) were embedded in these models. Further analysis ascribed the different release timescale to NH3-N:TN and TN:TP ratios of approximately 0.015 and 9.2, respectively, which may decrease the delay in microcystin release. Model applications in determining mcyA monitoring frequency and its warning thresholds were discussed.
现有的预测水体中微囊藻毒素浓度的模型通常使用叶绿素或蓝藻浓度作为输入变量,尽管微囊藻毒素仅源自少数几个物种的产毒菌株。此外,有害藻类生长与毒素释放之间的不同步性尚未得到量化。因此,本研究探索了一种新的预测方法,该方法考虑了中国大型饮用水源富营养化的阳澄湖的这些毒素产生机制。2012年7月至10月期间,每周在六个采样点对该湖进行监测,包括通过qPCR检测产毒微囊藻(以mcyA拷贝数表示)。与叶绿素a、蓝藻和总微囊藻丰度相比,产毒微囊藻浓度在预测细胞外微囊藻毒素方面更具显著性。建立了将mcyA与微囊藻毒素联系起来的特定地点非线性回归模型。这些模型中嵌入了毒素释放延迟的参数(即一周或两周)。进一步分析将不同的释放时间尺度归因于氨氮与总氮(NH3-N:TN)和总氮与总磷(TN:TP)的比率,分别约为0.015和9.2,这可能会减少微囊藻毒素释放的延迟。讨论了模型在确定mcyA监测频率及其预警阈值方面的应用。