Bias and association of sediment organic matter source apportionment indicators: A case study in a eutrophic Lake Chaohu, China
Graphical abstract
Introduction
Lake sediment cores are high-resolution information databases that record ecosystem evolution, climate change and human activities (Haworth and Lund, 1984). With the study of sediment cores, the history of pollution and eutrophication of a lake ecosystem could be reconstructed, and the response of the lake ecosystem to human activities could also be explored (Yang et al., 2008, Zhang et al., 2010, Chen et al., 2011). Although water analysis a conventional and real-time way of monitoring eutrophication currently, its history data is often missing (Kong et al., 2016). To disclose the eutrophication of a lake, long-term monitoring not only provides convincing results, but also tells us what influencing factors lead to the eutrophication and gives early warning signals of a critical transition (Wang et al., 2012). Furthermore, sediment buries algal-derived organic matter from dissolved phase to particle phase and some biomarkers preserves intact information (Yang et al., 2008, Zhang et al., 2010, He et al., 2016a).
Some traditional methods, including elemental (Chen et al., 2002), pigment (Reuss et al., 2005) and pollen analyses (Xiao et al., 2007), are widely used for sediment organic matter (SOM) source apportionment. During recent years, new technical methods such as lipid monomer molecular biomarkers and stable isotope fingerprinting substantially contributed to SOM source apportionment. Thus, it is possible to study the environmental change and biological evolution of an aquatic ecosystem from the macro-level into molecular level (Fu and Sheng, 1996, Waterson and Canuel, 2008). The lipid compounds, including n-alkanes, fatty acids, ketones, alcohols, aldehydes, sterols, and terpenes, are typical biomarkers of SOM and are widely used in source apportionment (Meyers and Ishiwatari, 1993, Sheng et al., 1999, Zhang et al., 1999, Ficken et al., 2000, Meyers, 2003, Muri et al., 2004, Lin et al., 2005). For example, n-alkanes from plankton and bacteria are characterized by low carbon number and non-discernable parity advantage, whereas n-alkanes from terrestrial high-grade plants are characterized by high carbon number and appreciable parity advantage (Eglinton and Hamilton, 1967, Cranwell, 1973, Grimalt and Albaigés, 1987, Yao and Sheng, 2002). A high ratio of short to long carbon chains (L/H) of the homologous biomarkers (such as n-alkanes) is often indicative of the dominant inputs of algae and bacterial organic matter (Zhang et al., 1999). The predominance of monocarboxylic acids and dicarboxylic acids in the fatty acids of sediment indicates aquatic plankton as the primary SOM source and the lipids as the main component, respectively (Volkman et al., 1980, Xiang et al., 1997). Some lipid biomarkers are only from certain organisms. For instance, the dinoflagellate sterols (phytosterone and androstenol derivatives) are biomarkers of dinoflagellates in SOM (Fu and Sheng, 1996, Schubert et al., 1998). The stable isotope composition of lipid biomarker monomers substantially increases resolution and decreases deviation for source apportionment (Hayes et al., 1990, Hayes, 1993a, Lin et al., 2005). Sometimes, those indicators could cause confusion and contradiction because SOM sources were very complex and controlled by multiple factors. It is wise to simultaneously use a variety of indicators for the comprehensive and accurate apportionment of SOM sources. Then, some statistical analysis such as principle component analysis could be employed to simplify those indicators into one or two, to unravel each indicator and reduce the confusions, and to select those consistency indicators.
Lake Chaohu (30°58′ ~ 32°06′N/116°24′ ~ 118°00′E) is the fifth largest freshwater lake in China (Fig. 1), with an area of 760 km2 and an average depth of 3 m. With the rapid development of the social economy in the catchments, it has become one of the most hypereutrophic lakes in China since the 1980s (Xu et al., 1999, Xu et al., 2003). Our studies during recent years have shown that Lake Chaohu also suffers from severe contamination by persistent organic pollutants (POPs) such as organochlorine pesticides (OCPs) (Kong et al., 2013), polycyclic aromatic hydrocarbons (PAHs) (Qin et al., 2013), phthalate esters (PAEs) (He et al., 2013b), and polybrominated diphenyl ethers (PBDEs) (He et al., 2013a). The severe eutrophication and associated algal bloom in Lake Chaohu would have important effects on its SOM that would further impact the residues and distributions of lipophilic POPs in the sediment (Xu et al., 2003, Liu et al., 2012). Therefore, the study of SOM sources would also have an important implication to the environmental effects of the lake water eutrophication and to the POPs in the sediment. The objectives of this study were to: (1) identify the source of SOM based on the multiple indicators, including the contents of total organic carbon (TOC) and total nitrogen (TN), the C/N ratio, lipid molecular biomarkers and isotope fingerprinting, and (2) compare those SOM source apportionment results to make a suggestion on the use of multiple indicators.
Section snippets
Sample collection and pretreatment
The sampling locations and methods were referred in previous study (He et al., 2013a). In brief, fourteen sediment samples were collected by a stainless steel Ponar grab sampler (< 15 cm based on the angle of that system) from Lake Chaohu on August 8th and 9th, 2009. To minimize the sampling error caused by that tool, a composite sampling, which was mixed thoroughly with the sub-sample, were finally collected. The locations of the sampling sites are shown in Fig. 1. The sampling sites EL1, EL2,
Element composition
The TN and TOC in lake sediments are mainly controlled by the primary productivity of the lake, terrestrial input and the preservation of organic debris in the sediment (Meyers, 2003, He et al., 2016a, He et al., 2016b). There was a significantly positive correlation between TOC and TN contents in the Lake Chaohu sediment (p = 0.013 < 0.05), indicating that TN strongly associated with organic carbon matter. Sediment organic matter sources can be divided into endogenous and exogenous. The former is
Conclusions
Based on the comparison study of multiple indicators of SOM from Lake Chaohu, we concluded that: (1) Elemental analysis together unraveled the high primary productivity of Lake Chaohu. The differences between the eastern and western parts could be discriminated by SOM content as well as contribution of algae. (2) The n-alkane congeners' relative patterns of all samples had a bimodal distribution with the 1st peak at C17 and the 2nd predominant peak at C29. Its parity advantage index and Paq
Acknowledgments
The funding for this study was provided by the National Science Foundation of China (NSFC) (41271462, 41030529), and Project funded by China Postdoctoral Science Foundation (2016M600009, 2016T90010). This work is also supported by a grant from the 111 Project (B14001) and from the undergraduate student research training program of the Ministry of Education. F.L. Xu also thanks the China Scholarship Council for supporting his study at the University of Massachusetts, Amherst.
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