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Use the predictive models to explore the key factors affecting phytoplankton succession in Lake Erhai, China
Zhu, Rong1,2; Wang, Huan1,2; Chen, Jun1; Shen, Hong1; Deng, Xuwei1
2018
Source PublicationENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
ISSN0944-1344
Volume25Issue:2Pages:1283-1293
AbstractIncreasing algae in Lake Erhai has resulted in frequent blooms that have not only led to water ecosystem degeneration but also seriously influenced the quality of the water supply and caused extensive damage to the local people, as the lake is a water resource for Dali City. Exploring the key factors affecting phytoplankton succession and developing predictive models with easily detectable parameters for phytoplankton have been proven to be practical ways to improve water quality. To this end, a systematic survey focused on phytoplankton succession was conducted over 2 years in Lake Erhai. The data from the first study year were used to develop predictive models, and the data from the second year were used for model verification. The seasonal succession of phytoplankton in Lake Erhai was obvious. The dominant groups were Cyanobacteria in the summer, Chlorophyta in the autumn and Bacillariophyta in the winter. The developments and verification of predictive models indicated that compared to phytoplankton biomass, phytoplankton density is more effective for estimating phytoplankton variation in Lake Erhai. CCA (canonical correlation analysis) indicated that TN (total nitrogen), TP (total phosphorus), DO (dissolved oxygen), SD (Secchi depth), Cond (conductivity), T (water temperature), and ORP (oxidation reduction potential) had significant influences (p < 0.05) on the phytoplankton community. The CCA of the dominant species found that Microcystis was significantly influenced by T. The dominant Chlorophyta, Psephonema aenigmaticum and Mougeotia, were significantly influenced by TN. All results indicated that TN and T were the two key factors driving phytoplankton succession in Lake Erhai.
SubtypeArticle
KeywordWater Bloom Phytoplankton Succession Predictedmodels Lake Erhai
DOI10.1007/s11356-017-0512-2
WOS HeadingsScience & Technology ; Life Sciences & Biomedicine
Indexed BySCI ; ISTP
Funding OrganizationNational Key Research and Development Program of China(2017YFA0605201) ; National Key Research and Development Program of China(2017YFA0605201) ; State Key Laboratory of Freshwater Ecology and Biotechnology(2016FBZ08) ; State Key Laboratory of Freshwater Ecology and Biotechnology(2016FBZ08) ; Major Science and Technology Program for Water Pollution Control and Treatment(2012ZX07105-004) ; Major Science and Technology Program for Water Pollution Control and Treatment(2012ZX07105-004) ; National Key Research and Development Program of China(2017YFA0605201) ; National Key Research and Development Program of China(2017YFA0605201) ; State Key Laboratory of Freshwater Ecology and Biotechnology(2016FBZ08) ; State Key Laboratory of Freshwater Ecology and Biotechnology(2016FBZ08) ; Major Science and Technology Program for Water Pollution Control and Treatment(2012ZX07105-004) ; Major Science and Technology Program for Water Pollution Control and Treatment(2012ZX07105-004)
Language英语
WOS Research AreaEnvironmental Sciences & Ecology
WOS SubjectEnvironmental Sciences
WOS KeywordHARMFUL ALGAL BLOOMS ; CYANOBACTERIA DOMINANCE ; CLIMATE-CHANGE ; PHOSPHORUS LIMITATION ; GLOBAL EXPANSION ; FRESH-WATER ; NITROGEN ; EUTROPHICATION ; COMMUNITY ; MICROCYSTIS
WOS IDWOS:000419944100028
Funding OrganizationNational Key Research and Development Program of China(2017YFA0605201) ; National Key Research and Development Program of China(2017YFA0605201) ; State Key Laboratory of Freshwater Ecology and Biotechnology(2016FBZ08) ; State Key Laboratory of Freshwater Ecology and Biotechnology(2016FBZ08) ; Major Science and Technology Program for Water Pollution Control and Treatment(2012ZX07105-004) ; Major Science and Technology Program for Water Pollution Control and Treatment(2012ZX07105-004) ; National Key Research and Development Program of China(2017YFA0605201) ; National Key Research and Development Program of China(2017YFA0605201) ; State Key Laboratory of Freshwater Ecology and Biotechnology(2016FBZ08) ; State Key Laboratory of Freshwater Ecology and Biotechnology(2016FBZ08) ; Major Science and Technology Program for Water Pollution Control and Treatment(2012ZX07105-004) ; Major Science and Technology Program for Water Pollution Control and Treatment(2012ZX07105-004)
Citation statistics
Cited Times:1[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ihb.ac.cn/handle/342005/50645
Collection淡水生态学研究中心
Affiliation1.Chinese Acad Sci, Inst Hydrobiol, State Key Lab Freshwater Ecol & Biotechnol, Donghu Expt Stn Lake Ecosyst, Wuhan 430072, Hubei, Peoples R China
2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
Recommended Citation
GB/T 7714
Zhu, Rong,Wang, Huan,Chen, Jun,et al. Use the predictive models to explore the key factors affecting phytoplankton succession in Lake Erhai, China[J]. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH,2018,25(2):1283-1293.
APA Zhu, Rong,Wang, Huan,Chen, Jun,Shen, Hong,&Deng, Xuwei.(2018).Use the predictive models to explore the key factors affecting phytoplankton succession in Lake Erhai, China.ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH,25(2),1283-1293.
MLA Zhu, Rong,et al."Use the predictive models to explore the key factors affecting phytoplankton succession in Lake Erhai, China".ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH 25.2(2018):1283-1293.
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