College of Agricultural Science and Engineering, Hohai University, Nanjing 210098, Jiangsu, China E-mail:
Water Sci Technol. 2020 Dec;82(11):2316-2330. doi: 10.2166/wst.2020.489.
Phytoplankton is capable of responding to aquatic conditions and can therefore be used to monitor freshwater reservoir water quality. Numerous classification techniques, including morpho-functional approaches, have been developed. This study examined changes in phytoplankton assemblages and water quality, which were sampled quarterly from July 2018 to April 2019. The purpose was to contrast the applicability of three classification approaches (functional, morpho-functional and morphological-based functional groupings) for understanding the spatial and seasonal distribution of the biomass variance in phytoplankton functional groups and their driving environmental factors in the ecological zones of the Shanxi Reservoir through multivariate analysis. The results showed that the phytoplankton biomass was highest in the watercourse zone and lowest in the transition zone. Furthermore, the Shanxi Reservoir was characterized by several cyanobacteria (Microcystis spp.) and numerous bacillariophytes (Asterionella sp., Navicula spp. and Aulacoseira granulata). After evaluating the advantages and disadvantages of morpho-functional classifications, we determined that water temperature appeared to be an essential factor, and the morphology-based functional group approach provided the best results for demonstrating phytoplankton succession, despite having lower sensitivity than the others. Nevertheless, these approaches are all appropriate for identifying and monitoring phytoplankton community structure in aquatic systems of reservoirs with complex terrains.
浮游植物能够对水生环境做出响应,因此可用于监测淡水水库水质。已经开发了许多分类技术,包括形态功能方法。本研究调查了浮游植物群落和水质的变化,这些变化是从 2018 年 7 月到 2019 年 4 月每季度采样的。目的是通过多元分析对比三种分类方法(功能、形态功能和基于形态的功能分组)在理解浮游植物功能组生物量方差的空间和季节分布及其在山西水库生态区的驱动环境因素方面的适用性。结果表明,浮游植物生物量在河道区最高,过渡区最低。此外,山西水库的特征是存在几种蓝藻(微囊藻属)和许多硅藻(盘星藻属、舟形藻属和颗粒直链藻)。在评估形态功能分类的优缺点之后,我们确定水温似乎是一个重要因素,基于形态的功能分组方法在演示浮游植物演替方面提供了最佳结果,尽管其灵敏度低于其他方法。然而,这些方法都适用于识别和监测具有复杂地形的水库水生系统中的浮游植物群落结构。