Spectral characteristics of dissolved organic matter in Plateau Lakes: Identifying eutrophication indicators in Southwest China

被引:5
作者
Guan, Yuying [1 ,5 ]
Yu, Gongliang [2 ]
Jia, Nannan [3 ]
Han, Ruiming [4 ,6 ]
Huo, Da [2 ]
机构
[1] Nanjing Inst Geog & Limnol, State Key Lab Lakes Sci & Environm, Nanjing 210008, Peoples R China
[2] Chinese Acad Sci, Inst Hydrobiol, Key Lab Algal Biol, Wuhan 430072, Peoples R China
[3] Chinese Acad Sci, Inst Urban Environm, Key Lab Urban Environm & Hlth, Ningbo Urban Environm Observat & Res Stn, Xiamen 361021, Peoples R China
[4] Nanjing Normal Univ, Sch Environm, Nanjing 210023, Peoples R China
[5] Univ Chinese Acad Sci, Beijing 100049, Peoples R China
[6] Jiangsu Ctr Collaborat Innovat Geog Informat Resou, Nanjing 210023, Peoples R China
关键词
Dissolved organic matter; Trophic state index; Excitation -emission matrix; LASSO; TROPHIC STATE INDEX; FLUORESCENCE SPECTROSCOPY; ENVIRONMENTAL-FACTORS; PHYTOPLANKTON; BIOMASS; CARBON; ABSORPTION; EXCITATION; NITROGEN; ESTUARY;
D O I
10.1016/j.ecoinf.2024.102703
中图分类号
Q14 [生态学(生物生态学)];
学科分类号
071012 ; 0713 ;
摘要
Dissolved organic matter (DOM) acts as a chemical intermediary between terrestrial and lacustrine ecosystems and significantly affects the structure and function of lakes. The trophic state of lakes, driven by terrestrial input and phytoplankton biomass, alters the optical properties of DOM. From November 2018 to July 2019, we collected 119 water samples from the Erhai watershed and analyzed them using UV-Vis and EEM-PARAFAC to study the optical properties of DOM in relation to the trophic conditions. Our result indicated that the tyrosinelike protein (C1), tryptophan-like protein (C2), and humic-like compounds (C3) were among the mostly autochthonous components of the DOM. The percentage of the C3 was higher in eutrophic lakes than in mesotrophic and light-eutrophic lakes. The ultraviolet absorption coefficients at 254 nm (aCDOM(254)) and fluorescence intensity at 355 nm (Fn(355)) increased significantly (p < 0.01) with an increased trophic state. Our findings indicate that the influence of nutrients and environmental factors (such as pH and water temperature) on DOM varies with the trophic state. The development of novel predictive models for trophic state assessment was largely based on the significant correlations between TSI and aCDOM(254) (R-2 = 0.762, p < 0.01) and Fn (355) (R-2 = 0.705, p < 0.01). This neural network model facilitates the creation of a novel fast assessment tool by highlighting the connection between DOM features and the trophic state index. By enabling swift experimental measurements, this model offers a high-resolution monitoring solution for tracking the eutrophication of plateau lakes and rivers.
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页数:10
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