Environmental Science and Pollution Research

, Volume 25, Issue 2, pp 1283–1293 | Cite as

Use the predictive models to explore the key factors affecting phytoplankton succession in Lake Erhai, China

  • Rong Zhu
  • Huan Wang
  • Jun Chen
  • Hong Shen
  • Xuwei DengEmail author
Research Article


Increasing 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.


Water bloom Phytoplankton succession Predicted models Lake Erhai 


Funding information

The research was financially supported by the National Key Research and Development Program of China (2017YFA0605201), the State Key Laboratory of Freshwater Ecology and Biotechnology (2016FBZ08), and the Major Science and Technology Program for Water Pollution Control and Treatment (2012ZX07105-004).

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflicts of interest.

Supplementary material

11356_2017_512_MOESM1_ESM.docx (19 kb)
ESM 1 (DOCX 18 kb)


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Copyright information

© Springer-Verlag GmbH Germany 2017

Authors and Affiliations

  • Rong Zhu
    • 1
    • 2
  • Huan Wang
    • 1
    • 2
  • Jun Chen
    • 1
  • Hong Shen
    • 1
  • Xuwei Deng
    • 1
    Email author
  1. 1.Donghu Experimental Station of Lake Ecosystems, State Key Laboratory of Freshwater Ecology and Biotechnology, Institute of HydrobiologyChinese Academy of SciencesWuhanPeople’s Republic of China
  2. 2.University of Chinese Academy of SciencesBeijingPeople’s Republic of China

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