[Environmental Driving Factors and Assessment on the Aquatic Ecosystem of Periphytic Algae of Six Inflow Rivers in Yangtze River Basin]

Huan Jing Ke Xue. 2023 Apr 8;44(4):2072-2082. doi: 10.13227/j.hjkx.202206095.
[Article in Chinese]

Abstract

Phytoplankton is frequently utilized in the assessment of water ecological health, and a great number of related studies have been conducted in China; however, most of them are limited in scope. A phytoplankton survey was carried out at the basin scale in this study. A total of 139 sampling sites were set up in crucial locations of the main stream, from the Yangtze River's source region to the estuary, as well as the eight primary tributaries and the Three Gorges' tributaries. In the Yangtze River Basin, phytoplankton was found in seven phyla and 82 taxa, with Cryptophyta, Cyanophyta, and Bacillariophyta being the dominant species. To begin, the composition of phytoplankton communities in various sections of the Yangtze River Basin was studied, and LEfSe was utilized to identify highly enriched species in different regions. The association between phytoplankton communities and environmental factors in different sections of the Yangtze River Basin was then investigated using CCA. The generalized linear model demonstrated that TN and TP were strongly positively linked with phytoplankton density at the basin scale, whereas TITAN analysis identified the environmental indicator species and their corresponding optimal growth threshold range. Finally, the study assessed each Yangtze River Basin Region in terms of biotic and abiotic factors. Although the results of the two aspects were incongruent, the analysis of all indicators using the random forest method can yield comprehensive and objective ecological evaluation results for each section of the Yangtze River Basin.

Keywords: Yangtze River Basin; ecological evaluation; environmental drivers; phytoplankton; random forest algorithm.

Publication types

  • English Abstract

MeSH terms

  • China
  • Ecosystem
  • Environmental Monitoring*
  • Phytoplankton
  • Rivers*