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Automated Subdaily Sampling of Cyanobacterial Toxins on a Buoy Reveals New Temporal Patterns in Toxin Dynamics

机译:浮标上的蓝细菌毒素的自动次日采样揭示了毒素动力学中的新时间模式

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摘要

Temporal variability of toxins produced by cyanobacteria in lakes is relatively unknown at time scales relevant to public health (i.e., hourly). In this study, a water quality monitoring buoy was outfitted with an automated water sampler taking preserved samples every 6 h for 68.75 days over a drinking water intake. A total of 251 samples were analyzed by tandem mass spectrometry for 21 cyanotoxin congeners in S classes producing 5020 data points. Microcystins (MCs) were the most abundant toxins measured (mean +/- sd = 3.9 +/- 3.3 mu g/L) followed by cyanopeptolins (CPs) (1.1 +/- 1.5 mu g/L), anabaenopeptins (APs) (1.0 +/- 0.6 mu g/L), anatoxin-a (AT-A) (0.03 +/- 0.06 mu g/L), and microginin-690 (MG-690) (0.002 +/- 0.01 mu g/L). Advanced time series analyses uncovered patterns in cyanotoxin production. The velocity of cyanotoxin concentration varied from -0.7 to 0.9 mu g/L/h with a maximum positive velocity just prior to peak toxin concentration during nonbloom periods. A backward-looking moving window of variance analysis detected major increases in cyanotoxin concentration and predicted the two greatest increases in MC. A wavelet analysis identified a significant (p 0.01) 2.8-4.2 day periodicity in toxin concentration over a similar to 25 day period during peak toxin production, which is partially explained by easterly wind velocity (R = 0.2, p 0.05). Diversity in congener profiles was explored with principle component analysis showing that cyanotoxin dynamics followed a seasonal trajectory where toxin profiles were significantly clustered (ANOSIM R = 0.7, p 0.05) on a daily basis. Variability in toxin profiles was strongly correlated with time (R = -0.8, p 0.001) as well as the C:N ratio of the toxin pool (R = 0.17, p 0.05). The methods employed here should be useful for uncovering patterns in cyanotoxin dynamics in other systems.
机译:在与公共卫生相关的时间尺度上(即每小时),由蓝细菌在湖泊中产生的毒素的时间变化相对未知。在这项研究中,水质监测浮标配备了自动进水采样器,每6小时采集一次饮用水中保存的样本,持续68.75天。通过串联质谱法共分析了251个样品,分析了S类中的21种氰毒素同源物,产生了5020个数据点。微囊藻毒素(MCs)是测量到的最丰富的毒素(平均+/- sd = 3.9 +/- 3.3μg / L),其次是氰肽肽(CP)(1.1 +/- 1.5μg / L),阿那贝肽(APs)( 1.0 +/- 0.6μg / L),抗毒素a(AT-A)(0.03 +/- 0.06μg / L)和microginin-690(MG-690)(0.002 +/- 0.01μg / L) )。高级时间序列分析了氰毒素生产中未发现的模式。氰毒素浓度的速度从-0.7到0.9μg / L / h不等,最大正速度刚好在非开花期的峰值毒素浓度之前。向后方差分析的移动窗口检测到氰毒素浓度显着增加,并预测了MC的两个最大增加。小波分析发现在峰值毒素产生期间的类似于25天的时间段内,毒素浓度具有显着的(p <0.01)2.8-4.2天周期,这部分由东风(R = 0.2,p <0.05)解释。通过主成分分析探索了同类同源物谱的多样性,结果表明,氰毒素动力学遵循季节性轨迹,其中毒素谱每天显着聚集(ANOSIM R = 0.7,p <0.05)。毒素谱的可变性与时间(R = -0.8,p <0.001)以及毒素库的C:N比(R = 0.17,p <0.05)密切相关。此处采用的方法对于揭示其他系统中氰毒素动力学的模式应该是有用的。

著录项

  • 来源
    《Environmental Science & Technology》 |2019年第10期|5661-5670|共10页
  • 作者单位

    Univ Wisconsin, Joseph J Zilber Sch Publ Hlth, Milwaukee, WI 53211 USA;

    Univ Wisconsin, Joseph J Zilber Sch Publ Hlth, Milwaukee, WI 53211 USA|Univ Wisconsin, Sch Freshwater Sci, Milwaukee, WI 53204 USA;

    Univ Wisconsin, Joseph J Zilber Sch Publ Hlth, Milwaukee, WI 53211 USA;

    Univ Wisconsin, Joseph J Zilber Sch Publ Hlth, Milwaukee, WI 53211 USA;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);美国《生物学医学文摘》(MEDLINE);美国《化学文摘》(CA);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

  • 入库时间 2022-08-18 04:24:32

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