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Evaluation of water ecosystem health of Baihua Reservoir in Guizhou based on GIS and P-IBI.

XIONG Mei-jun1, LI Qiu-hua1*, CHEN Qian1, HE Yin1, MA Xin-yang1, HAN Meng-shu1, TANG Chong-li2, ZHANG Hua-jun3   

  1. (1Key Laboratory of Mountainous Environment Information System and Ecological Environment Protection of Guizhou Province, Guizhou Normal University, Guizhou 553000, China; 2College of Chemistry and Materials Science, Guizhou Normal University, Guizhou 553000, China; 3Guizhou Zhonghuan Technology Co., Ltd, Guiyang 550004, China).
  • Online:2019-10-10 Published:2019-10-10

Abstract: To understand the current health status of water ecosystem in the Baihua Reservoir in Guizhou Plateau, a phytoplankton community survey was carried out from January to December in 2017. The GIS spatial interpolation method was used for data analysis and ecological evaluation. The phytoplankton integrity method was applied to evaluate water ecological health of Baihua Reservoir. The results showed that: (1) A total of 40 species belonging to 32 genera within six phyla of phytoplankton were recorded, and the phytoplankton abundance was Yanjiaozhai (YJZ) (1.24×106 cells·L-1)> Huaqiao (HQ) (7.06×105 cells·L-1)> Guilǚshuichang (GLSC) (4.83×105 cells·L-1)> Maixihe (MXH) (4.41×105 cells·L-1)> Daba (DB) (3.25×105 cells·L-1). The abundance of top three dominant species were Pseudanabaenasp.>Synedra sp.>Cyclotella sp. (2) The four reference points were healthy. Among the 16 polluted points, however, six points in health, four points in subhealth, two points in general, six points in poor, and two points in very poor status. (3) The PIBI values were 18.75 in HQ, 21.75 in YJZ, 17.25 in MXH, 18 in GLSC and 17.25 in DB, of which the HQ, YJZ and GLSC belonged to the subhealth state, and the MXH and DB were classified as the general state. Overall, the ecological health of Baihua Reservoir was in a sub-health state in 2017. GIS interpolation analysis can accurately predict unknown areas, which provides ecological evaluation basis for ecological monitoring.

Key words: leaf stoichiometry, variation, provenance, Quercus acutissima.