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Factors structuring phytoplankton community in a large tropical river: Case study in the Red River (Vietnam)

机译：在大型热带河流中构建浮游植物群落的因素：红河（越南）案例研究

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摘要

Algal assemblages have been widely used as an ecological indicator of aquatic ecosystem health conditions because of their specific sensitivity to a wide variety of environmental conditions. In turbid rivers, as in other aquatic systems, phytoplankton structure plays an important role in structuring aquatic food webs. Worldwide, phytoplankton is less studied in turbid, large tropical rivers compared to temperate river systems. The present study aimed to describe the phytoplankton diversity and abundance in a turbid tropical river (the Red River, northern part of Vietnam from 20 degrees 00 to 25 degrees 30 North; from 100 degrees 00 to 107 degrees 10 East) and to determine the importance of a series of environmental variables in controlling the phytoplankton community composition. Phytoplankton community was composed of 169 phytoplankton taxa from six algal groups including Bacillariophyceae, Chlorophyceae, Cryptophyceae, Euglenophyceae, Dinophyceae and Cyanobacteria. Community composition varied both spatially and with season. Sixteen measurement environmental variables were used as input variables for a three-layer backpropagation neural network that was developed to predict the phytoplankton abundance. Phytoplankton abundance was successfully predicted using the tagsig transfer function and the Levenberg-Marquardt backpropagation algorithm. The network was trained to provide a good overall linear fit to the total data set with a slope (R) and mean square error (MSE) of 0.808 and 0.0107, respectively. The sensitivity analysis and neutral interpretation diagram revealed that total phosphorus (TP), flow discharge, water temperature and P-PO43- were the significant variables. The results showed that the developed ANN model was able to simulate phytoplankton abundance in the Red River. These findings can help for gaining insight into and the relationship between phytoplankton and environmental factors in this complex, turbid, tropical river.
机译：由于其对各种环境条件的特​​异性敏感性，藻类组合被广泛用作水生生态系统健康状况的生态指标。在混浊的河流中，如在其他水生系统中，浮游植物结构在构造水生食品网中起着重要作用。与温带河流系统相比，在全球范围内，植物大型热带河流较少研究。本研究旨在描述浮游植物的多样性和丰富的潮汐热带河流（红河，越南北部，从20 00至25度北北部;从100度00到107度东）并确定重要性控制浮游植物群落组成的一系列环境变量。浮游植物群落由169个藻类群组成的六个藻类组成，包括杆菌病，叶绿素，加密酵母，uuglenophyceae，Dinophyceae和Cyanobacteria。社区成分在空间和季节变化。十六个测量环境变量被用作开发的三层背部化神经网络的输入变量，以预测浮游植物丰富。使用Tagsig传递函数和Levenberg-Marquardt BackPropagation算法成功预测了浮游植物丰富。培训网络以提供良好的整体线性拟合，分别具有0.808和0.0107的斜率（R）和均方误差（MSE）的总数据集。敏感性分析和中性解释图显示，总磷（TP），流量放电，水温和P-PO43-是显着的变量。结果表明，发达的ANN模型能够在红河中模拟浮游植物丰富。这些调查结果可以帮助洞察洞察力，浮游植物和环境因素之间的关系，浑浊，热带河流。

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