Impacts of a large river-to-lake water diversion project on lacustrine phytoplankton communities

Dai, Jiangyu; Wu, Shanshan; Wu, Xiufeng; Lv, Xueyan; Sivakumar, Bellie; Wang, Fangfang; Zhang, Yu; Yang, Qiwen; Gao, Ang; Zhao, Yuhang; Yu, Lei; Zhu, Senlin

doi:10.1016/j.jhydrol.2020.124938

Cited by 62 publications

(25 citation statements)

References 45 publications

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“…Long-term changes related to environmental factors have been shown to influence shifts in the taxonomic community of phytoplankton (Richardson and Schoeman 2004;Edwards and Richardson 2004;Leterme et al 2005), which were first demonstrated in relation to the Shannon-Wiener diversity index, Pielou's evenness index, and Simpson's dominance index in Nansi Lake. Responses of phytoplankton diversity to water diversion in aquatic ecosystems have been reported in previous studies, the majority of which found an increase in phytoplankton diversity (Fornarelli et al 2013;Dai et al 2020). In contrast, our study revealed that the diversity in 2014 was lower than that before the water diversion.…”

Section: Seasonal Responses Of the Phytoplankton Community: Communitysupporting

confidence: 55%

“…Nansi Lake is located on the east route of SNWDP, which serves as a vital water-storing lake. Since the east route of SNWDP has been operated from November 2013, the aquatic ecosystem has been affected in Nansi Lake (Dai et al 2020;Yu et al 2020). The water diversion since 2013 provides an opportunity to determine the differences in the phytoplankton community before and after water diversion in Nansi Lake.…”

Section: Introductionmentioning

confidence: 99%

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Diverse drivers of phytoplankton dynamics in different phyla across the annual cycle in a freshwater lake

et al. 2021

Journal of Freshwater Ecology

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An understanding of the annual variations in the phytoplankton community in freshwater lakes, and of the drivers responsible for these variations, is essential for lake management. In this study we collected and analyzed seasonal samples of phytoplankton and assessed environmental variables in Nansi Lake from 2011 to 2015, in order to identify the seasonal dynamics of the phytoplankton community and the main drivers in each phylum. The results showed that phytoplankton diversity in Nansi Lake followed annual cycles, which were interrupted by a water diversion in 2013. The disruption of equilibrium was clearly demonstrated by the Shannon-Wiener diversity index, Pielou's evenness index, and Simpson's dominance index, whereas the species richness and abundance showed resilience, maintaining regular annual cycles. The dominant species were frequently Synedra acus K€ utz (Bacillariophyta), Closterium gracile Br eb (Chlorophyta), and Scenedesmus quadricauda Br eb (Chlorophyta) in summer and autumn. Non-metric multidimensional scaling (NMDS) analysis suggested that the phytoplankton was most widely distributed in summer, when conditions were more conducive to phytoplankton growth and reproduction. Redundancy analysis (RDA) indicated that the main drivers for the phytoplankton community varied in different taxonomic units. Specifically, the NP ratio and permanganate index (COD Mn ) had significant effects on Chlorophyta, whereas pH, dissolved oxygen (DO), and transparency significantly influenced Bacillariophyta. This study highlights the importance of seasonal phytoplankton succession and the need for identification of the main drivers in each phylum in order to achieve more effective control of phytoplankton blooms in freshwater lakes.

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Section: Seasonal Responses Of the Phytoplankton Community: Communitysupporting

confidence: 55%

Section: Introductionmentioning

confidence: 99%

Diverse drivers of phytoplankton dynamics in different phyla across the annual cycle in a freshwater lake

et al. 2021

Journal of Freshwater Ecology

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“…As a water conservancy project for mitigating water scarcity and improving water quality, water transfer projects are of great significance in alleviating the uneven distribution of water resources to relieve regional water crises and to promote regional socio-economic development and ecological environment improvement [1,2]. However, transferred water can change the hydrologic and hydrodynamic characteristics of receiving reservoirs and disturb the water environment system of receiving reservoirs, which causes variations in water environmental factors and the potential risk of eutrophication [3,4]. With increasing project implementation time, negative effects on the water quality of receiving reservoirs are likely to accumulate and may lead to unexpected water quality deterioration.…”

Section: Introductionmentioning

confidence: 99%

Machine Learning-Based Prediction of Chlorophyll-a Variations in Receiving Reservoir of World’s Largest Water Transfer Project—A Case Study in the Miyun Reservoir, North China

Liao

Zang

Wang

et al. 2021

Water

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Although water transfer projects can alleviate the water crisis, they may cause potential risks to water quality safety in receiving areas. The Miyun Reservoir in northern China, one of the receiving reservoirs of the world’s largest water transfer project (South-to-North Water Transfer Project, SNWTP), was selected as a case study. Considering its potential eutrophication trend, two machine learning models, i.e., the support vector machine (SVM) model and the random forest (RF) model, were built to investigate the trophic state by predicting the variations of chlorophyll-a (Chl-a) concentrations, the typical reflection of eutrophication, in the reservoir after the implementation of SNWTP. The results showed that compared with the SVM model, the RF model had higher prediction accuracy and more robust prediction ability with abnormal data, and was thus more suitable for predicting Chl-a concentration variations in the receiving reservoir. Additionally, short-term water transfer would not cause significant variations of Chl-a concentrations. After the project implementation, the impact of transferred water on the water quality of the receiving reservoir would have gradually increased. After a 10-year implementation, transferred water would cause a significant decline in the receiving reservoir’s water quality, and Chl-a concentrations would increase, especially from July to August. This led to a potential risk of trophic state change in the Miyun Reservoir and required further attention from managers. This study can provide prediction techniques and advice on water quality security management associated with eutrophication risks resulting from water transfer projects.

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“…The heterogeneity is further deepened by the distinct seasonal changes. Previous studies have shown that bacteria in water bodies and sediments affected by water diversion have significant spatiotemporal changes [ 38 , 39 , 40 , 41 , 42 ]. However, the different responses of bacterial and archaeal communities in river sediments affected by both water diversion and seasonal changes are currently less known.…”

Section: Introductionmentioning

confidence: 99%

Different Responses of Bacterial and Archaeal Communities in River Sediments to Water Diversion and Seasonal Changes

Niu

Yuan

et al. 2021

Microorganisms

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In recent years, different responses of archaea and bacteria to environmental changes have attracted increasing scientific interest. In the mid-latitude region, Fen River receives water transferred from the Yellow River, electrical conductivity (EC), concentrations of Cl- and Na+ in water, total phosphorus (TP), and Olsen phosphorus (OP) in sediments were significantly affected by water transfer. Meanwhile, temperature and oxidation-reduction potential (ORP) of water showed significant seasonal variations. Based on 16S rRNA high-throughput sequencing technology, the composition of bacteria and archaea in sediments was determined in winter and summer, respectively. Results showed that the dominance of bacterial core flora decreased and that of archaeal core flora increased after water diversion. The abundance and diversity of bacterial communities in river sediments were more sensitive to anthropogenic and naturally induced environmental changes than that of archaeal communities. Bacterial communities showed greater resistance than archaeal communities under long-term external disturbances, such as seasonal changes, because of rich species composition and complex community structure. Archaea were more stable than bacteria, especially under short-term drastic environmental disturbances, such as water transfer, due to their insensitivity to environmental changes. These results have important implications for understanding the responses of bacterial and archaeal communities to environmental changes in river ecosystems affected by water diversion.

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Impacts of a large river-to-lake water diversion project on lacustrine phytoplankton communities

Cited by 62 publications

References 45 publications

Diverse drivers of phytoplankton dynamics in different phyla across the annual cycle in a freshwater lake

Diverse drivers of phytoplankton dynamics in different phyla across the annual cycle in a freshwater lake

Machine Learning-Based Prediction of Chlorophyll-a Variations in Receiving Reservoir of World’s Largest Water Transfer Project—A Case Study in the Miyun Reservoir, North China

Different Responses of Bacterial and Archaeal Communities in River Sediments to Water Diversion and Seasonal Changes

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