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author:

Liu, Lin (Liu, Lin.) [1] | Xin, Yu (Xin, Yu.) [2] | Guang, Shan-Bin (Guang, Shan-Bin.) [3] | Lin, Guo-Fu (Lin, Guo-Fu.) [4] | Liu, Chao-Xiang (Liu, Chao-Xiang.) [5] | Zeng, Li-Qin (Zeng, Li-Qin.) [6] | He, Shao-Qin (He, Shao-Qin.) [7] | Zheng, Yu-Ming (Zheng, Yu-Ming.) [8] | Chen, Guan-Yu (Chen, Guan-Yu.) [9] | Zhao, Quan-Bao (Zhao, Quan-Bao.) [10]

Indexed by:

EI

Abstract:

To understand the dynamics of planktonic microbial community and its metabolism processes in subtropical drinking water river-reservoir system with lower man-made pollution loading, this study selected Dongzhen river-reservoir system in Mulan Creek as object to investigate spatial-temporal characteristics of community profile and functional genes involved in biological metabolism, and to analyze the influence of environmental factors. The results indicated that Proteobacteria and Actinobacteria were the most diverse phyla with proportion ranges of 9%–80% in target system, and carbohydrate metabolism (5.76-7.12 × 10−2), amino acid metabolism (5.78-7.21 × 10−2) and energy metabolism (4.07-5.17 × 10−2) were found to be the dominant pathways of biological metabolism. Although there were variations in biological properties both spatially and temporally, seasonal variation had a greater influence on microbial community and biological metabolism, than locational differences. Regarding the role of environmental factors, this study revealed that microbial diversity could be affected by multiple abiotic factors, with total organic carbon, total phosphorus and temperature being more influential (absolute value of standardized regression weights >2.13). Stochastic processes dominated the microbial community assembly (R2 of neutral community model = 0.645), while niche-based processes differences represented by nutrients, temperature and pH level played secondary roles (R > 0.388, P © 2023 Elsevier Inc.

Keyword:

Dissolved oxygen Metabolism Microorganisms Nitrogen Organic carbon Potable water Random processes Reservoirs (water) River pollution Rivers Stochastic models Stochastic systems Tropics

Community:

  • [ 1 ] [Liu, Lin]Key Laboratory of Urban Pollutant Conversion, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen; 361021, China
  • [ 2 ] [Liu, Lin]University of Chinese Academy of Sciences, Beijing; 100049, China
  • [ 3 ] [Xin, Yu]Key Laboratory of Urban Pollutant Conversion, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen; 361021, China
  • [ 4 ] [Xin, Yu]University of Chinese Academy of Sciences, Beijing; 100049, China
  • [ 5 ] [Guang, Shan-Bin]Key Laboratory of Urban Pollutant Conversion, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen; 361021, China
  • [ 6 ] [Guang, Shan-Bin]College of Environment and Safety Engineering, Fuzhou University, Fuzhou; 350108, China
  • [ 7 ] [Lin, Guo-Fu]Putian River Management Center, Putian; 351100, China
  • [ 8 ] [Liu, Chao-Xiang]Key Laboratory of Urban Pollutant Conversion, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen; 361021, China
  • [ 9 ] [Liu, Chao-Xiang]College of Environment and Safety Engineering, Fuzhou University, Fuzhou; 350108, China
  • [ 10 ] [Zeng, Li-Qin]Dongzhen Reservoir Administration, Putian; 351100, China
  • [ 11 ] [He, Shao-Qin]Dongzhen Reservoir Administration, Putian; 351100, China
  • [ 12 ] [Zheng, Yu-Ming]Key Laboratory of Urban Pollutant Conversion, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen; 361021, China
  • [ 13 ] [Chen, Guan-Yu]Dongzhen Reservoir Administration, Putian; 351100, China
  • [ 14 ] [Zhao, Quan-Bao]Key Laboratory of Urban Pollutant Conversion, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen; 361021, China

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Source :

Environmental Research

ISSN: 0013-9351

Year: 2023

Volume: 237

7 . 7

JCR@2023

7 . 7 0 0

JCR@2023

JCR Journal Grade:1

CAS Journal Grade:1

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 0

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