Estimating sedimentary organic matter sources by multi-combined proxies for spatial heterogeneity in a large and shallow eutrophic lake. (15th October 2018) - Li, Zhichun; Xu, Xiaoguang; Ji, Ming; Wang, Guoxiang; Han, Ruiming; Ma, Jie; Yan, Xingcheng; Liu, Jine
Abstract: The multiple proxies involving elemental and stable isotope ratios (C/N, δ 15 N and δ 13 C) and biomarkers are powerful tools for estimating sedimentary organic matter (SOM) sources. However, the systematic and reasonable evaluation of organic matter sources existing with serious spatial heterogeneity in large, shallow and eutrophic lakes is still far from clear. Samples of sediments, aquatic plants and particulate organic matter (POM) collected from different ecotype regions of Taihu Lake, China, including algae-type lakeshore, grass-type lakeshore, algae-grass-type lakeshore, inflow rivers and estuary, groove reed zone, offshore and central regions, were analyzed for their SOM sources via elemental and stable isotope ratios (C/N, δ 15 N and δ 13 C), n -alkanes and fatty acids (FA). More depleted δ 13 CTOC values (−26.3‰ to −25.4‰) and higher relative percentages of odd n -alkanes (C26 to C35 ) and long-chain FA (C24:0 to C32:0 ) clarified the influence of inflow rivers carrying terrestrial inputs on SOM. The higher relative percentages of n -alkanes from C14 to C20, FA (C16:0 ), and polyunsaturated FA (C18:2 and C18:3 ) in the reed belt of the groove demonstrated that some special terrain was important for the accumulation of algae-derived OM in sediments. Short-chain and middle-chain biomarker compounds revealed a large contribution from macrophytes in the grass-type region and an obvious algae-derived organic matter accumulation in the algae-type region, respectively. However, some overlapping ranges of C/N, δ 15 N and δ 13 C among aquatic plants, the ubiquity of lipid biomarkers compounds, anthropogenic influences, meteorological factors and lake topography caused some biased identification results for partial samples using different indicators. These biased identifications were mainly embodied in the source category and contribution difference based on principal component analysis and an end-member mixing model. Therefore, the estimation of SOM sources by multiple proxies cannot be uniformly applied in large freshwater lakes. The systematic investigation and comprehensive understanding of the different ecotypes and their surrounding environments are the important links in the identification of SOM sources via multiple indicators. Graphical abstract: Image 1 Highlights: Systematic investigation of SOM sources was performed in a large-shallow lake. SOM sources in different ecotype regions were estimated by multiple indicators. Stable carbon isotope models accurately calculated SOM source contribution rates. Partial samples presented some biased identifications by different indicators. Multi-combined proxies necessarily assess SOM sources in spatial heterogeneity.