Estimating sedimentary organic matter sources by multi-combined proxies for spatial heterogeneity in a large and shallow eutrophic lake

The multiple proxies involving elemental and stable isotope ratios (C/N, δ¹⁵N and δ¹³C) 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, δ¹⁵N and δ¹³C), n-alkanes and fatty acids (FA). More depleted δ¹³CTOC 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, δ¹⁵N and δ¹³C 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.