Jing Zhang

Jing Zhang


Research Focus & Metrics

Academic Career Length

6Years (2021-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 February 2021 in Journal of Environmental Management
Verified
Journal Article
Closed access
YDYang Ding
Yang Ding
JZJinyong Zhao
Jinyong Zhao
WPWen-Qi Peng
Wen-Qi Peng
JZJing Zhang
Jing Zhang
QCQuchang Chen
Quchang Chen
DMDuan Maoqing
Duan Maoqing

9 January 2025 in Sustainability
Verified
Journal Article
Open access
PDF file
SFShuo Feng
Shuo Feng
HWHongtao Wang
Hongtao Wang
JZJing Zhang
Jing Zhang
XZXianfu Zhao
Xianfu Zhao
Jinyong ZhaoJinyong Zhao
Jinyong Zhao
QCQuchang Chen
Quchang Chen
Tributaries flowing naturally play an important role in maintaining the biodiversity of aquatic organisms in dammed rivers. The Chishui River is currently the only undeveloped first-level tributary and an important habitat for aquatic organisms in the upper reaches of the Yangtze River. Understanding the distribution of the community structure of macrobenthos in the Chishui River and its influencing factors is crucial for the conservation and restoration of aquatic biodiversity in both the Chishui River and the Yangtze River. This study analyzes the community structure characteristics of macrobenthos in the Chishui River using four indicators, i.e., Margalef richness index, EPT taxon richness (the number of taxa in the pollution-sensitive Ephemeroptera, Plecoptera, and Trichoptera), Simpson dominance index, and Shannon diversity index, examining differences among different types of environmental factors (physical, chemical, and biological) in the upper, middle, and lower reaches. Subsequently, RDA (Redundancy Analysis) is used to analyze the main influencing factors of different types of environmental factors on macrobenthic community structure. VPA (Variance Partitioning Analysis) is employed to assess the relative importance of different types of environmental factors and their joint effects on the characteristics of macrobenthic community structure. The results indicate that physical environmental factors explain 68.7% of the variation in macrobenthic community structure indicators, chemical environmental factors explain 79.3%, and biological environmental factors account for 36.2%. The interaction among chemical, biological, and physical factors is the most significant explanatory variable, accounting for 41.7% of the variation in macrobenthic community structure characteristics. For EPT taxon number and Shannon diversity index, the interaction among chemical, biological, and physical factors is also the most important explanatory variable, accounting for 42.1% and 42.5% of the variation. For the Margalef richness index and Simpson dominance index, the interaction between chemical and physical factors is the most significant, accounting for 45.0% and 85.3% of the variation. Therefore, the impact of multiple environmental factors on aquatic organisms should not be overlooked, and attention should be paid to the contributions of various environmental factors in the conservation of macrobenthos in the Chishui River Basin.