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

富营养化 高原(数学) 中国 环境科学 有机质 溶解有机碳 生态学 海洋学 环境化学 自然地理学 地质学 地理 营养物 化学 生物 考古 数学分析 数学
作者
Yuying Guan,Gongliang Yu,Nannan Jia,Ruiming Han,Da Huo
出处
期刊:Ecological Informatics [Elsevier BV]
卷期号:82: 102703-102703 被引量:4
标识
DOI:10.1016/j.ecoinf.2024.102703
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 tyrosine-like 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) (R2 = 0.762, p < 0.01) and Fn(355) (R2 = 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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