Fungal communities as dual indicators of river biodiversity and water quality assessment

被引:1
|
作者
Siriarchawatana, Paopit [1 ]
Harnpicharnchai, Piyanun [1 ]
Phithakrotchanakoon, Chitwadee [1 ]
Kitikhun, Supattra [1 ]
Mayteeworakoon, Sermsiri [1 ]
Chunhametha, Suwanee [1 ]
Huong, Vu Thi Lan [2 ]
Eurwilaichitr, Lily [3 ]
Jiang, Chengying [4 ]
Cai, Lei [4 ]
Ingsriswang, Supawadee [1 ,5 ]
机构
[1] Natl Sci & Technol Dev Agcy NSTDA, Thailand Bioresource Res Ctr TBRC, Natl Ctr Genet Engn & Biotechnol BIOTEC, Khlong Luang, Pathumthani, Thailand
[2] Vietnam Natl Univ Ho Chi Minh City, Univ Sci, Ho Chi Minh City, Vietnam
[3] Natl Sci & Technol Dev Agcy NSTDA, Natl Energy Technol Ctr ENTEC, Khlong Luang, Pathumthani, Thailand
[4] Chinese Acad Sci, Inst Microbiol, Beijing, Peoples R China
[5] Natl Sci & Technol Dev Agcy NSTDA, Natl Ctr Genet Engn & Biotechnol BIOTEC, 113 Thailand Sci Pk,Phahonyothin Rd, Khlong Luang 12120, Pathum Thani, Thailand
关键词
Bioindicators; Water quality indices; Physicochemical properties; Fungal taxa; River ecosystem; BIOINDICATORS;
D O I
10.1016/j.watres.2024.121252
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Given their ecological importance, bioindicators are used for the assessment of the health of river ecosystems. This study explored the fungal compositions and the potential of fungal taxa as bioindicators for indicating the water quality of the Mekong River, as the use of fungal indicators of the Mekong River was not previously well characterized. The Mekong River exhibited dynamic variations in both physicochemical/hydrochemical properties and fungal communities according to seasons and locations. The results revealed the dominance of alkaline earth metal ions and weak acids in the water. The magnesium-bicarbonate water type was found in the dry season, but the water became the chloride-calcium type or mixed type of magnesium-bicarbonate and chloridecalcium in the rainy season at downstream sites. Fungal composition analysis revealed the dominance of Chytridiomycota in the dry season and intermediate periods, and Ascomycota and Basidiomycota in the rainy season. The fungal communities were influenced by stochastic and deterministic assembly processes, mainly homogeneous selection, heterogeneous selection, and dispersal limitation. The extent of environmental filtering implied that some fungal taxa were affected by environmental conditions, suggesting the possibility of identifying certain fungal taxa suitable for being bioindicators of water quality. Subsequently, machine learning with recursive feature elimination identified specific fungal bins mostly consisting of Agaricomycetes (mainly Polyporales, Agaricales, and Auriculariales), Dothideomycetes (mainly Pleosporales), Saccharomycetes (mainly Saccharomycetales), Chytridiomycota, and Rozellomycota as bioindicators that could predict ambient and irrigation water quality with high selectivity and sensitivity. These results thus promote the use of fungal indicators to assess the health of the river.
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页数:14
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