Departamento de Biología, C. Darwin 2, Universidad Autónoma de Madrid, 28049 Cantoblanco, Spain.
Water Res. 2012 Jun 1;46(9):3043-53. doi: 10.1016/j.watres.2012.03.005. Epub 2012 Mar 16.
Cyanobacterial blooms are a frequent phenomenon in eutrophic freshwaters worldwide and are considered potential hazards to ecosystems and human health. Monitoring strategies based on conventional sampling often fail to cover the marked spatial and temporal variations in cyanobacterial distribution and fluctuating toxin concentrations inherent to cyanobacterial blooms. To deal with these problems, we employed a multi-scale approach for the study of a massive Microcystis bloom in Tajo River (Spain) utilizing 1) remote sensing techniques, 2) conventional water sampling and 3) analysis of chemotypical subpopulations. Tajo River at the study area is influenced by high temperatures waters diverted upstream from a nuclear power plant, the presence of a dam downstream and a high nutrient load, which provide optimal conditions for massive cyanobacterial proliferation. MERIS imagery revealed high Chl-a concentrations that rarely fell below 20 μg L(-1) and moderate spatiotemporal variations throughout the study period (March-November 2009). Although the phytoplanktonic community was generally dominated by Microcystis, sampling points highly differed in cyanobacterial abundance and community composition. Microcystin (MC) concentrations were highly heterogeneous, varying up to 3 orders of magnitude among sampling points, exceeding in some cases WHO guideline values for drinking and also for recreational waters. The analysis of single colonies by MALDI-TOF MS revealed differences in the proportion of MC-producing colonies among points. The proportion of toxic colonies showed a highly significant linear correlation with total MC: biovolume ratio (r(2) = 0.9; p < 0.001), evidencing that the variability in toxin concentrations can be efficiently addressed by simple analysis of subpopulations. We propose implementing a multi-scale monitoring strategy that allows covering the spatiotemporal heterogeneities in both cyanobacterial distribution (remote sensing) and MC concentrations (subpopulation analysis) and thereby reduce the main sources of uncertainty in the assessment of the risks associated to bloom events.
蓝藻水华是全球富营养化淡水水体中的一种常见现象，被认为对生态系统和人类健康构成潜在威胁。基于常规采样的监测策略往往无法涵盖蓝藻分布的显著时空变化以及蓝藻水华固有的毒素浓度波动。为了解决这些问题，我们采用多尺度方法研究了塔霍河（西班牙）的大规模微囊藻水华，利用了 1）遥感技术、2）常规水样采集和 3）化学型亚群分析。研究区域的塔霍河受到来自核电站上游的高温水、下游大坝的存在以及高营养负荷的影响，这些条件为大规模蓝藻增殖提供了最佳条件。MERIS 图像显示，Chl-a 浓度很高，很少低于 20μg/L，整个研究期间（2009 年 3 月至 11 月）都有中度的时空变化。尽管浮游植物群落通常以微囊藻为主，但采样点在蓝藻丰度和群落组成上存在很大差异。微囊藻毒素（MC）浓度高度不均匀，在采样点之间变化达 3 个数量级，在某些情况下超过了世界卫生组织（WHO）对饮用水和娱乐用水的指导值。MALDI-TOF MS 对单个菌落的分析显示，不同采样点之间产 MC 菌落的比例存在差异。有毒菌落的比例与总 MC：生物量比呈高度显著的线性相关（r(2) = 0.9；p < 0.001），表明通过对亚群的简单分析可以有效地解决毒素浓度的变异性。我们建议实施一种多尺度监测策略，该策略可以涵盖蓝藻分布（遥感）和 MC 浓度（亚群分析）的时空异质性，从而降低评估与水华事件相关风险的主要不确定性来源。
