Lipid biomarker evidence for determining the origin and distribution of organic matter in surface sediments of Lake Taihu, Eastern China

Lipid biomarker evidence for determining the origin and distribution of organic matter in surface sediments of Lake Taihu, Eastern China

Ecological Indicators 77 (2017) 397–408 Contents lists available at ScienceDirect Ecological Indicators journal homepage: www.elsevier.com/locate/ec...

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Ecological Indicators 77 (2017) 397–408

Contents lists available at ScienceDirect

Ecological Indicators journal homepage: www.elsevier.com/locate/ecolind

Lipid biomarker evidence for determining the origin and distribution of organic matter in surface sediments of Lake Taihu, Eastern China Yongdong Zhang a,∗ , Yaling Su a , Zhengwen Liu a,b,∗∗ , Jinlei Yu a , Miao Jin a a b

State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography & Limnology, Chinese Academy of Sciences, Nanjing 210008, China Department of Ecology and Research Center of Hydrobiology, Jinan University, Guangzhou 510632, China

a r t i c l e

i n f o

Article history: Received 16 December 2016 Received in revised form 18 February 2017 Accepted 20 February 2017 Available online 8 March 2017 Keywords: Biomarker Lake Taihu Sediment Organic matter Cyanobacteria

a b s t r a c t Lipid biomarkers from surface sediments of Lake Taihu (Eastern China) were analyzed in order to determine the origin and spatial distribution of sediment organic matter (OM), which is necessary to understand the regional carbon cycles and design environmental management strategies for lake systems. The results indicated significant heterogeneity in the distribution of autochthonous (algae-, photosynthetic bacteria- and macrophyte-based) and allochthonous (terrestrial plant-based) OM in sediments across the lake. Allochthonous OM inputs, indicated by long-chain n-alkane and long-chain n-alkanol biomarkers, generally declined in abundance from northwestern (Zhushan Bay and Meiliang Bay) to southeastern (East Bays) parts of the lake, suggesting a critical influence of hydrology, and in particular of inflowing rivers, which mainly enter the lake from the west and drain from the east. Autochthonous OM, on the other hand, appeared to reflect variations in overall nutrient status and habit type across the lake. Cyanobacterial OM inputs, identified by short-chain n-alkanes, were most abundant in sediment from the most severely polluted zones in Lake Taihu, namely Zhushan Bay and Meiliang Bay. OM derived from diatoms, indicated by brassicasterol and highly branched isoprenoids (HBIs), was most abundant in sediments from the East Bays, a clear-water zone with relatively low levels of nutrient input. Macrophyte OM input, indicated by the middle-chain n-alkanes and Paq ((n-C23 + n-C25)/(n-C23 + nC25 + n-C29 + n-C31)), was only identified in sediments from the East Bays. The lowest recorded inputs for both autochthonous and allochthonous OM were in sediments from open areas with significant sediment resuspension, including Gonghu Bay, Central and Western Region. This finding might reflect degradation mineralization of OM in the water column during sediment resuspension. © 2017 Elsevier Ltd. All rights reserved.

1. Introduction Lake sediments have been considered to play an important role in the terrestrial carbon cycle because they accumulated a significant fraction of OM produced by the biosphere (Anderson et al., 2013; Wang et al., 2015). The lake sediment is also a significant site for OM breakdown and nutrient regeneration (Xu et al., 2015). OM preserved in lake sediments could origin from production within the aquatic system, including phytoplankton and macrophytes, terrestrial OM input from the catchment and bacteria production within the sediment (Prartono and Wolff, 1998; Meyers, 2003). The abundance and chemical nature of OM in lake sediment

∗ Corresponding author. ∗∗ Corresponding author at: State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography & Limnology, Chinese Academy of Sciences, Nanjing 210008, China. E-mail addresses: [email protected] (Y. Zhang), [email protected] (Z. Liu). http://dx.doi.org/10.1016/j.ecolind.2017.02.031 1470-160X/© 2017 Elsevier Ltd. All rights reserved.

varies considerably with local conditions (Woszczyk et al., 2011), and in turn exerts a different impact on the environment and the biological communities in the sediments and the overlying water column (Dunn et al., 2008). High levels of OM stimulate microbial metabolism and increase sediment oxygen demand and nutrient regeneration within the surface sediment (Dunn et al., 2008). Previous studies suggest that phytoplankton-based sediment OM is more effectively biodegraded than that derived from terrestrial plants (Muri et al., 2013; Xu et al., 2015) probably because increased availability of nitrogen (N) and phosphorus (P) in the former enhances the efficiency of nutrient recycling (Meyers and Ishiwatari, 1993; Muri et al., 2013). Ecological restoration might be needed to reduce N and P release from sediment to overlying water when the sediment was dominated by phytoplankton OM (Smol, 2008). Thus, assessing the composition, origin and distribution of lake sediment OM is necessary to understand the local biogeochemical cycles for carbon and nutrients and design environmental management strategies for lake systems (Prartono and

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Wolff, 1998; Kumar Das et al., 2009; Carreira et al., 2011; Woszczyk et al., 2011). Lipid biomarkers are widely used as tools for assessing the origin and distribution of OM in sediments of aquatic ecosystem because they are source specific and more resistant to bacterial degradation than many other biological compounds (Pinturier-Geiss et al., 2002; Hu et al., 2009; Xu and Jaffé, 2009; Xing et al., 2011; Lammers et al., 2013). Compared to geochemical proxies such as the relative abundance of total organic carbon to total nitrogen (TOC/TN), lipid biomarkers can provide detailed information about the origins of sediment OM (Hu et al., 2009; Xing et al., 2011). It is widely accepted that the short-chain lipids (C15–C20 n-alkanes and C16–C20 n-alkanols) in sediments indicate inputs from algae (and/or photosynthetic bacteria), while long-chain lipids (C27–C33 n-alkanes and C24–C32 n-alkanols) are derived from higher plants (Meyers, 1997). Middle-chain n-alkanes (C21–C25 n-alkanes) can indicate origins of OM from submerged and floating aquatic macrophytes (Meyers and Ishiwatari, 1993; Ficken et al., 2000). Moreover, some lipids in sediment can indicate input from more specific phytoplankton taxa. For example, dinosterol and brassicasterol are associated with dinoflagellate and diatom inputs from the overlying water column (Volkman et al., 1998; Schubert et al., 1998; Zimmerman and Canuel, 2002). Highly branched isoprenoids (HBI) compounds, especially C25HBI, can indicate input of OM from diatoms (Volkman et al., 1998). Lake Taihu is the third largest freshwater lake in China. The lake is important for aquaculture, tourism and recreation, transportation, and provides drinking water for cities including Shanghai, Suzhou, Wuxi and Huzhou (Qin et al., 2007). The lake is surrounded by the most industrialized and urbanized area of China and exhibits great heterogeneity in water quality (Qin et al., 2007). Northern

parts of the lake have undergone serious deterioration in recent decades and in the summer of 2007 cyanobacterial blooms (Microcystis spp.) lead to a water supply crisis in the region (Dong et al., 2014). The southeastern reaches of the lake are generally less polluted and are dominated by clear water habit (Qin et al., 2007; Qin, 2008; Dong et al., 2014). This spatial heterogeneity in water quality and habit might be reflected in the origin and distribution of OM in surface sediment. For example, in eutrophic areas, sediments tend to receive a large fraction of OM from phytoplankton, whereas the OM in relatively oligotrophic areas derives mainly from aquatic macrophytes (Qin et al., 2007; Dong et al., 2014). Fatty acid biomarkers have previously been used to assess the sources of sediment OM in the western part of Lake Taihu (Xu et al., 2015), but as yet there has been no attempt to map the type and distribution of OM in sediments across the entire lake. In this study, the abundance and composition of lipid biomarkers (including n-alkanes, HBIs, n-alkanols and sterols) in the surface sediments of Lake Taihu were analyzed in order to identify the origins of sediment OM in different sites. The mechanisms controlling OM distribution are discussed, based on hydrology and observed variations in physical and chemical parameters within and around the lake. 2. Materials and methods 2.1. Study area and sampling Lake Taihu is located in the delta of Yangtze River (30◦ 55 40 –31◦ 32 58 N and 119◦ 52 32 –120◦ 36 10 E) (Fig. 1). The lake has an area of about 2338 km2 , a catchment area of about 36, 500 km2 , a mean depth of 1.9 m and water retention time of approximately 5 months. Local hydrology of the lake

Fig. 1. Locations of the water and sediment sampling sites in Lake Taihu.

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is complex, with 117 connecting rivers and tributaries, largely flowing into the lake from the west and draining it to the east (Qin et al., 2007). Heavy pollution of some inflowing rivers has lead to strong gradients in water environment and ecosystems across the lake. For example, the water monitoring program conducted in 2012 by Taihu Laboratory for Lake Ecosystem Research (TLLER) reveals clear variations in total phosphorus (TP), total nitrogen (TN), suspended solids (SS) and chlorophyll a (Chl a) in the water column (Fig. 2). Abundances of both TP and TN are highest in the northwest, especially in Zhushan Bay. Levels are moderate in Gonghu Bay, Central region and Western region and lowest in the East Bays (Fig. 2a and b). Levels of SS, however, are highest in Central region and Western region, intermediate in Meiliang Bay, Gonghu Bay and Zhushan Bay, and lowest in the East Bays (Fig. 2d). Chl a abundance shows a trend similar to that of TP and TN across the lake (Fig. 2c), declining from northwest to southeast. Cyanobacteria are the major constituents of the phytoplankton community in Lake Taihu, with green algae, diatoms, dinoflagellates and cryptophytes present at much lower levels

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(Chen et al., 2003). The northern bays (Meiliang Bay and Zhushan Bay) are subject to severe seasonal blooms of cyanobacteria (Cai et al., 2012; Dong et al., 2014). Aquatic macrophytes (dominated by Potamogeton spp., Vallisneria natanus, Nymphoides peltatum, Hydrilla verticillata, and Trapa incise) are mostly restricted to the East Bays (Dong et al., 2014). For this study, sediment samples were collected in November 2013 from 30 stations regularly monitored by TLLER as part of the Chinese Ecosystem Research Network (CERN) (Fig. 1). Sediment samples (0–3 cm) were taken using a gravity corer with a 90-mmdiameter coring tube, and then stored in 250 mL glass bottles. Upon arrival in the laboratory, the sediments were frozen at −20 ◦ C until processing for geochemical analysis. Physical parameters including dissolved oxygen (DO), pH and electrical conductivity (EC), were measured in the lake water overlying each sampling site at a depth of 0.5 m using a Yellow Springs Instruments (YSI) 6600 multi-sensor sonde. Secchi depth (SD) was measured by Secchi disk in the lake water overlying each sampling site.

Fig. 2. Variation of TP (mg/L), TN (mg/L), Chla (␮g/L) and SS (mg/L) in water column of Lake Taihu.

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Fig. 3. Variation of TOC (%) and clay content (%) in the sediment.

2.2. Sediment analyses Sub-samples for analysis of TOC were leached with dilute HCl to dissolve carbonate and rinsed copiously with distilled water to remove remaining chlorides. Sediment concentrations of TOC were determined using a CHNS Vario E1 III elemental analyzer. The relative standard deviation for this analysis was less than 2%. Grain size was measured with a laser particle size analyzer (GSL-101B). Clay (grain size < 4 ␮m) content was determined using the clay percentage in the sand (grain size > 63 ␮m), silt (grain size 4–63 ␮m) and clay. Sediment samples for biomarker analyses were Soxhlet extracted for 72 h with dichloromethane/methanol (9:1 v/v) after adding known quantities of internal standards (n-tetracosane-d50 , C13 n-alkanol and 5␣-androstan-3␤-ol). Sulfur was removed by addition of activated copper. The extracts were saponified with 5% KOH–methanol solution. The neutral fraction was isolated by extraction with hexane and fractionated using silica gel column chromatography. Aliphatic hydrocarbons and n-alkanol/sterols (OLs) were eluted with hexane and dichloromethane/methanol (9:1), respectively. The OL fractions were silylated (70 ◦ C, 60 min) with N,O-bis(trimethylsilyl)trifluoroacetamide before being analyzed by gas chromatography–mass spectrometry (GC–MS). Aliphatic hydrocarbon and OLs were analyzed by GC–MS using an Agilent 5975 mass spectrometer coupled to an Agilent 7890A gas chromatograph with DB-5MS column (30 m × 0.25 mm × 0.25 ␮m). To determine aliphatic hydrocarbon fractions, the GC oven temperature program started at 80 ◦ C (2 min), followed by an increase to 300 ◦ C at 3 ◦ C/min then held at this temperature for 30 min. For the OL fractions, the temperature program started at 80 ◦ C (2 min), then increased to 220 ◦ C at 6 ◦ C/min, then to 250 ◦ C at 3 ◦ C/min and to 310 ◦ C at 2 ◦ C/min. The final temperature was maintained for 15 min. Helium was used as the carrier gas at a flow rate of 1.0 mL/min. The ion source was operated at 250 ◦ C and 70 eV, in electron impact mode. Compounds were identified by comparison with previously reported mass spectra, and by interpretation of fragmentation patterns and chromatographic retention behavior. Quantification data was determined by comparing peak areas of the internal standard with compounds of interest in reconstructed total ion current (TIC) chromatograms. Biomarker concentrations were normalized to the weights of dry sediment (␮g g−1 sediment). A precision test performed by analyzing five replicates of each sam-

ple revealed a deviation of less than 20% for hydrocarbon and OL compounds. 3. Results 3.1. TOC and clay content in the surface sediment TOC in the sediment of Lake Taihu varied from 0.44% to 1.31% (Fig. 3a). The East Bays (sites 12, 24, 25, 26, 27 and 30) and Zhushan Bay (sites 10, 16 and 17) were richest in TOC, averaging 0.99% (range 0.60–1.31%) and 0.97% (range 0.59–1.24%), respectively. TOC abundance was slightly reduced in Meiliang Bay (sites 0, 1, 3, 4, 5, 6, 9, 15 and 32), averaging 0.91% (range 0.61–1.27%). Lowest TOC levels were recorded in Gonghu Bay, Central and Western Region (sites 7, 8, 11, 13, 14, 18, 19, 20, 21, 22, 23 and 31), with an average value of 0.63% (range 0.44–0.81%). The clay percentage in the sediment varied from 3.92% to 13.09%, but unlike TOC, did not show a regular pattern across the lake (Fig. 3b). 3.2. Lipid biomarkers in the sediment 3.2.1. n-Alkanes and HBI Surface sediments from Lake Taihu yielded n-alkanes ranging from C15 to C34 (Fig. 4a), characterized by a bimodal distribution. In the low carbon number (C21) fraction, Cmax occurred at n-C29 in most cases, and at n-C25 or n-C27 in samples from the East Bays (Fig. 4a). The East Bays samples also contained abundant n-alkanes with moderate carbon numbers (n-C21, n-C23 and n-C25). Ratios of (n-C23 + n-C25)/(nC23 + n-C25 + n-C29 + n-C31), defined as Paq by Ficken et al. (2000), ranged from 0.49 to 0.62, much higher than in samples from elsewhere (0.27–0.47) (Fig. 4a). Moreover, the CPI values (CPI = 1/2[(n-C25 + n-C27 + n-C29 + n-C31 + n-C33)/(n-C24 + nC26 + n-C28 + n-C30 + n-C32) + (n-C25 + n-C27 + n-C29 + n-C31 + nC33)/(n-C26 + n-C28 + n-C30 + n-C32 + n-C34)]) in the East Bay samples ranged from 3.50 to 4.96, also somewhat higher than in other samples (2.25–3.46) (Fig. 4a). The TAR ratios ((n-C27 + nC29 + n-C31 + n-C33)/(n-C15 + n-C17 + n-C19)) were generally high in the East Bay samples (average 6.43, range 4.31–10.60) and low in Meiliang Bay material (average 3.16, range 1.69–6.90). High values were also observed in Zhushan Bay (average 5.10, range

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Fig. 4. The distribution of n-alkanes (a) and n-alkanols (b) by carbon number, and the sterol variation (c) in the represent samples of different region in Lake Taihu. In (c), 1: cholesta-5, 22 -dien-3␤-ol; 2: 5␣-cholest-22-en-3␤-ol; 3: cholest-5-en-3␤-ol (cholesterol); 4: 24-methylcholesta-5, 22-dien-3␤-ol (brassicasterol); 5: 24-methyl5␣-cholest-22-en-3␤-ol; 6: 24-methylcholest-5-en-3␤-ol (campesterol); 7: 24-ethylcholesta-5, 22-dien-3␤-ol (stigmasterol); 8: 24-ethyl-5␣-cholest-22-en-3␤-ol; 9: 24ethylcholest-5-en-3␤-ol (sitosterol); 10: 4␣,23,24-trimethyl-5␣-cholestan-3␤-ol (dinosterol).

3.42–6.56) and some areas of Central and Western Region (Fig. 5d). Besides the n-alkanes, we also identified three HBIs in samples from the East Bays, namely a monoene C25HBI, a monoene C20HBI and saturated C20 HBI (Fig. 6). Identification was based on mass spectra data, chromatographic retention time and the results of previous authors (Jaffé et al., 2001; Xu et al., 2006; Belt et al., 2007), and these markers were not found elsewhere in Lake Taihu. Short-chain n-alkane abundance (sum of n-C15, n-C17 and n-C19) varied from 0.06 to 1.43 ␮g g−1 and displayed some notable patterns in spatial distribution (Fig. 5a). Abundance was greatest (average 0.44 ␮g g−1 , range 0.09–1.43 ␮g g−1 ) in Meiliang Bay, somewhat lower in Zhushan Bay (average 0.35 ␮g g−1 , range 0.21–0.49 ␮g g−1 ) and lowest (average 0.12 ␮g g−1 , range 0.06–0.18 ␮g g−1 ) in regions including the East Bays, Gonghu Bay,

Central and Western Region (Fig. 5a). Long-chain n-alkanes (sum of n-C27, n-C29, n-C31 and n-C33) varied in abundance from 0.28 to 2.61 ␮g g−1 , with the highest values recorded in Zhushan Bay (average 1.74 ␮g g−1 , range 1.19–2.61 ␮g g−1 ), followed by Meiliang Bay (average 1.09 ␮g g−1 , range 0.62–2.45 ␮g g−1 ). Unlike the shortchain n-alkanes, long-chain n-alkanes were also abundant in the East Bays, reaching 0.74 ␮g g−1 on average (range 0.28–0.96 ␮g g−1 ) (Fig. 5b). The abundance of middle-chain n-alkanes (sum of n-C21, n-C23 and n-C25) was high in Zhushan Bay and the East Bays, averaging 0.68 ␮g g−1 (range 0.42–1.00 ␮g g−1 ) and 0.61 ␮g g−1 (range 0.15–0.90 ␮g g−1 ), respectively (Fig. 5c). Abundance values for the HBI biomarker recorded within the East Bays showed notable variation, with monoene C25HBI ranging from 0.001 to 0.099 ␮g g−1 (average 0.023 ␮g g−1 ), monoene C20HBI from 0.005

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Fig. 5. Spatial distribution of the concentrations of short-chain n-alkanes (a), long-chain n-alkanes (b), middle-chain n-alkanes (c) and the variation of TAR (d) across the lake.

to 0.845 ␮g g−1 (average 0.237 ␮g g−1 ) and saturated C20HBI varying from 0.037 to 0.913 ␮g g−1 (average 0.342 ␮g g−1 ). 3.2.2. n-Alkanols and sterols The n-alkanols detected in surface sediment from Lake Taihu ranged from C14 to C30 with obvious even carbon preference in abundance (Fig. 4b). Abundance values exhibited a bimodal distribution whereby for the lower carbon number (C22) fraction, Cmax occurred at C24 at site 0 and in samples from the East Bays, and at C26 or C28 elsewhere. Shortchain n-alkanol abundance (sum of n-C14, n-C16, n-C18 and n-C20) varied from 2.2 to 14.8 ␮g g−1 , with notably low values in Central and Western Regions (average 2.7 ␮g g−1 , range 2.2–3.5 ␮g g−1 ), and high values elsewhere, especially in the East Bays (average 7.4 ␮g g−1 , range 3.6–14.8 ␮g g−1 ) (Fig. 7a). Abundance of longchain n-alkanols (sum of n-C22, n-C24, n-C26, n-C28 and n-C30) varied from 5.7 to 21.2 ␮g g−1 . The highest values were recorded in

samples from Zhushan Bay, reaching 16.1 ␮g g−1 on average (range 11.3–21.2 ␮g g−1 ). Abundance for this group was reduced in Meiliang Bay (average 12.3 ␮g g−1 , range 9.7–19.3 ␮g g−1 ) and in the East Bays (average 11.2 ␮g g−1 , range 5.7–17.0 ␮g g−1 ), and lowest in Gonghu Bay, Central and Western Region (average 7.5 ␮g g−1 , range 6.2–9.8 ␮g g−1 ) (Fig. 7b). A series of C27 to C29 4-des-methyl sterols and a C30 4␣methyl sterol (dinosterol) were also detected (Fig. 4c). C27 sterols accounted for 18–52% of the total C27 to C29 4-des-methyl sterols. The ratios were much lower in the East Bays (18–31%, average 22%) than in other regions (33–52%, average 41%). C28 sterols accounted for 24–37% of the total C27 to C29 4-desmethyl sterols, with no significant spatial variation across the lake. C29 sterols accounted for 23–56% of the total C27 to C29 4-des-methyl sterols. The ratios in the East Bays varied from 40% to 56% (average 51%), compared to only 22–40% (average 28%) elsewhere (Fig. 4c). There was a distinct variation in sterol abundance across the lake. Cholesterol (cholest-5-en-3␤-ol) abundances were highest in Zhushan Bay (average 9.70 ␮g g−1 , range

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ethylcholesta-5, 22-dien-3␤-ol), campesterol (24-methylcholest5-en-3␤-ol) and sitosterol (24-ethylcholest-5-en-3␤-ol) levels varied similarly to brassicasterol across the lake (Fig. 7f). Dinosterol abundance was much lower than for other common sterols, ranging from 0.03 to just 0.71 ␮g g−1 , with its greatest abundance in the East Bays (average 0.40 ␮g g−1 , range 0.12–0.71 ␮g g−1 ) (Fig. 7e).

4. Discussion 4.1. Lipid biomarker evidence of autochthonous OM input in the sediment

Fig. 6. Partial total ion chromatogram of aliphatic hydrocarbon fraction in the surface sediment of East Bays (a), and the mass spectrum of C20:1HBI (b), C20HBI (c) and C25:1HBI (d).

5.49–14.90 ␮g g−1 ) and lowest in Gonghu Bay, Central and Western Region (average 2.48 ␮g g−1 , range 1.74–3.38 ␮g g−1 ), with sites in Meiliang Bay and the East Bays, exhibiting intermediate values averaging 5.66 ␮g g−1 (range 2.02–10.33 ␮g g−1 ) and 4.63 ␮g g−1 (range 2.25–7.66 ␮g g−1 ), respectively (Fig. 7c). Brassicasterol (24-methylcholesta-5, 22-dien-3␤-ol) abundance was highest in the East Bays, reaching 2.97 ␮g g−1 on average (range 1.06–4.90 ␮g g−1 ). Values for brassicasterol were slightly lower in Zhushan Bay (average 2.07 ␮g g−1 , range 1.07–3.28 ␮g g−1 ) and Meiliang Bay (average 1.89 ␮g g−1 , range 0.94–3.68 ␮g g−1 ), and lower still in Gonghu Bay, Central and Western Region (average 0.95 ␮g g−1 , range 0.74–1.22 ␮g g−1 ) (Fig. 7d). Stigmasterol (24-

The lipid biomarkers constitute less than 1% of the total sedimentary OM and may not be representative of the total material (Meyers, 1997). However, the lipid composition can provide important details about changes in origins of the OM (Hu et al., 2009; Xing et al., 2011). Short-chain n-alkanes are commonly used as indicators of OM input from algae and aquatic photosynthetic bacteria (Cranwell et al., 1987) and in particular, n-alkanes exhibiting a Cmax at C17 or C19 are thought to be cyanobacterial in origin (Santos Neto et al., 1998). The n-alkanes identified in the current study exhibited a Cmax at C17, coupled with abundant n-C19 (Fig. 4a). This, along with the known distribution and the predominance of cyanobacteria in the phytoplankton community (Chen et al., 2003; Yu et al., 2013) suggest that cyanobacteria contribute to OM in Lake Taihu sediments. C20HBI alkane and its monounsaturated alkene were not directly acquired from algae; instead, they were found in epiphytes of the green macroalgaa Enteromorpha prolifera (Volkman et al., 1998). The major contributors of the C20HBI were attributed to diatoms, green algae, cyanobacteria and desmids (Jaffé et al., 2001). C25HBI, on the other hand is known exclusively from diatoms, including Navicula, Pleurosigma, Rhizosolenia, and Berkeleya (Saunders et al., 2014; He et al., 2016). Abundant C25 HBI compounds have previously been found in periphyton and floc associated with macroalgae and higher plants in wetland settings (He et al., 2016). The current study identified C20 and C25HBIs only in sediments from the East Bays (Fig. 6), suggesting an origin in the diatoms and green algae known to be abundant in the macrophyte periphyton of this part of Lake Taihu (Yuan et al., 2006). Sterols originate from a variety of eukaryotic organisms, including phytoplankton, zooplankton and vascular plants (Volkman, 1986). Cholesterol is abundant in zooplankton, diatoms and cyanobacteria (Volkman, 1986; Volkman et al., 1998). In contrast, in Lake Taihu, dinosterol and brassicasterol can be regarded as highly specific biomarkers for dinoflagellate and diatom respectively (Volkman et al., 1998, 2008; Schubert et al., 1998; Li et al., 2014), because other source organisms for brassicasterol, such as the coccolithophores Emiliania huxleyi and Gephyrocapsa oceanica are generally absent from the lake (Chen et al., 2003). Stigmasterol, campesterol and sitosterol have been found in land plants, but also in phytoplankton, including green algae, diatoms and haptophytes (Volkman, 1986; Killops and Killops, 2005; Pearson et al., 2007; Volkman et al., 2008). However, the ratio of campesterol/stigmasterol/sitosterol abundance in sediments from Lake Taihu (Fig. 4c) differs from that in higher plants (1:1.6:6.6) (Volkman, 1986; Grimalt and Albaigés, 1990; Carreira et al., 2002). Sitosterol (and/or campesterol, stigmasterol) exhibited a positive abundance gradient from Zhushan Bay and Meiliang Bay to the East Bays (Fig. 7f), against the trend for terrestrial plant biomarkers (discussed below), resulting in a weak correlation between the sterol and long-chain n-alkanols (R2 = 0.43, n = 30) that are generally derived from terrestrial plants (Meyers, 2003). Instead, the greater abundance of sitosterol in the East Bays coincided with the local distribution of HBI compounds. A strong correlation was established between abundances of sitosterol and brassicasterol (R2 = 0.92,

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Fig. 7. Spatial distribution of the concentrations of short-chain n-alkanols (a), long-chain n-alkanols (b), cholesterol (c), brassicasterol (d), dinosterol (e) and sitosterol (f).

n = 30). Thus, it appears that sediment sitosterol (and/or campesterol, stigmasterol) represents OM input from algae, especially diatoms (Pearson et al., 2007). Short-chain n-alkanols are regarded as less accurate indicators of biotic sources than short-chain n-

alkanes and sterols owing to their ubiquitous nature (Pearson et al., 2007; Woszczyk et al., 2011). Short-chain n-alkanol levels exhibited a relatively weak correlation with brassicasterol, dinosterol and short-chain n-alkanes (R2 = 0.59, 0.54 and 0.34, n = 30), sug-

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gesting a mixed input from cyanobacteria, diatoms, dinoflagellates and others. Submerged and floating macrophytes are reported to contain abundant n-C21, n-C23 and n-C25 alkanes (Cranwell, 1984; Ficken et al., 2000). In the East Bays of Lake Taihu, Paq values ranged between 0.49 and 0.62 (Fig. 4a), placing them within the range reported for submerged/floating macrophytes (0.48–0.94), indicating a macrophyte origin for the middle-chain (n-C21, n-C23 and n-C25) n-alkanes (Ficken et al., 2000). The geochemical records are consistent with the results of field investigations in this region where the abundant submerged macrophytes growth includes Potamogeton malaianus and Vallisneria natans (Dong et al., 2014). Thus, the middle-chain n-alkanes (n-C21 + n-C23 + n-C25 alkanes) detected in sediments of the East Bays most likely represent OM derived from submerged and floating macrophytes. Elsewhere, however, Paq values lower than 0.48 (Fig. 4a) indicate an alternative source of middle-chain n-alkanes, such as terrestrial plants or phytoplankton. The abundance of lipid biomarkers in sediment is generally dependent on the quantity of OM entering the sediment and the extent of in situ preservation (Meyers, 2003). Previous authors report that sediment grain size may influence total OM and biomarker abundance due to the greater absorption capacity of fine sediments with relatively large surface areas (Meyers and Lalliervergés, 1999; Dunn et al., 2008; Xing et al., 2011). In the current study, however, we found no correlation between lipid biomarkers (including n-alkane, n-alkanol and sterol) abundances and clay percentage and conclude that lipid biomarker abundance is mainly representative of OM input from the overlying water column (Hu et al., 2009). The distribution of lipid biomarkers in Lake Taihu sediments indicates a marked variation in autochthonous OM input across the lake. Significant accumulations of cyanobacterial OM were recorded in Zhushan Bay and Meiliang Bay, while the greatest input of diatoms was in sediments of the East Bays. Diatom-derived OM was present in sediments from Zhushan Bay and Meiliang Bay at relatively low levels. Input of dinoflagellates was much higher in the East Bays than elsewhere (Fig. 7e). Submerged and floating macrophyte OM accumulated only in the East Bays; and inputs of phytoplankton-derived OM were lowest in Gonghu Bay, Central and Western Region. The lack of species-specific biomarkers for green algae and cryptophytes makes it difficult to quantify inputs of OM from these taxa. 4.2. Lipid biomarker evidence of allochthonous OM input in the sediment Terrestrial higher plants are commonly regarded as the major contributor of allochthonous OM to lake sediment. The presence of long-chain n-alkanes with a strong predominance of odd carbon numbers can indicate OM input from terrestrial higher plants (Eglinton and Hamilton, 1967; Meyers, 2003). In Lake Taihu sediment, the CPI values calculated for long-chain n-alkanes were higher in the East Bays than other regions (Fig. 4a). Moreover, the long-chain n-alkanes in sediments from the East Bays have Cmax at C27, rather than at C29 as seen elsewhere (Fig. 4a). Longchain n-alkanols (>C22) from the East Bays have Cmax at C24 while those from elsewhere peak at C26 or C28 (Fig. 4b). These results indicate different sources for the long-chain n-alkanes and long-chain n-alkanols in sediment in different parts of the lake. Because submerged and floating macrophytes are distributed in the East Bays, the compounds in this region might reflect a mixed input from macrophytes and terrestrial higher plants (Ficken et al., 2000). In contrast, the compounds in other regions of the lake are derived mainly from terrestrial plants, although a possible contribution from petroleum contamination cannot be excluded in consideration of the low CPI values (Qu et al., 2007; Hu et al.,

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2009). The biomarkers indicative of terrestrial higher plant input indicate the greatest allochthonous OM input in Zhushan Bay, a moderate contribution in Meiliang Bay, and lowest values in Gonghu Bay, Central and Western Region (Figs. 5b and 7b). The lipid biomarkers indicated a moderate input of allochthonous OM at sites in the East Bays. However, this value should be much smaller because long-chain n-alkanes and long-chain n-alkanols in this region might reflect input mainly from aquatic macrophytes rather than terrestrial plants. Variation in TAR values across the lake provides a snapshot of allochthonous versus autochthonous OM inputs (Fig. 5d). In Meiliang Bay, allochthonous OM input was relatively high, but this region had the lowest TAR, indicating significant concomitant loading with autochthonous OM. By contrast, the high TAR values in the East Bays suggest that autochthonous OM makes a small contribution to gross OM compared to that of macrophytes (including partial contribution from terrestrial plants). The Central and Western Region exhibited high TAR values in some sites (Fig. 5d), reflecting a relatively high proportion of allochthonous OM in the sediment, although both autochthonous and allochthonous OM were less abundant in this part of the lake than elsewhere. 4.3. Factors controlling the spatial distribution of OM in the sediment Lipid biomarkers in the sediments of Lake Taihu demonstrate significant spatial variation in the distribution of autochthonous and allochthonous OM. The biomarker evidence for the OM distribution describes three distinct zones in the lake, corresponding well to previously documented differences in physical, chemical and biological conditions (Qin et al., 2007; Cai et al., 2012; Dong et al., 2014). Zone I includes Zhushan Bay and Meiliang Bay. Both bays receive water from polluted rivers, the Yincungang River, Chendonggang River and Hongcheng River into Zhushan Bay and the Liangxihe River, Wujingang River and Zhihugang River into Meiliang Bay (Fig. 8). All six rivers have carried significant pollution since the 1960s, including chemical fertilizers, industrial waste and domestic sewage from the cities of Wuxi, Changzhou and Yixing (Duan et al., 2009). Riverine inputs of TN and TP account for 72% and 77% of the total TN and TP entering Lake Taihu (Jin, 1995) and these two northern bays are the most polluted areas (Wu et al., 2007; Xu et al., 2010; Cai et al., 2012). TP levels in the lake increased by 2.7 times from 1981 to 1998 (Qin et al., 2007) and the western part of the lake has been regarded as hypertrophic since 1987 (Chen et al., 2003). In 2012, TP reached 0.29 mg/L in Zhushan Bay and 0.21 mg/L in Meiliang Bay, while TN levels were 4.82 mg/L and 3.20 mg/L, respectively (Fig. 2a and b). Besides nutrients, the inflowing rivers also deliver terrestrial plant OM to the lake (Liu et al., 2009). This resulted in greatest accumulations of allochthonous OM in this zone, especially for Zhushan Bay. Meanwhile, the influx of nutrients has lead to changes in the species composition of the phytoplankton community (Qin, 2008). Blooms of the toxin-producing cyanobacterium Microcystis spp. have occurred in these bays every summer since the mid-1980s (Qin et al., 2007; Xu et al., 2010), and in 1988 cyanobacteria replaced diatoms as the dominant form of phytoplankton (Chen et al., 2003; Qin, 2008). In May 2007, a very large cyanobacterial mat in Meiliang Bay caused the drinking-water plant of the nearby city (Wuxi) to fail, leading to a highly publicized drinking water crisis (Xu et al., 2010). The elevated productivity of cyanobacteria in summer leads to a significant accumulation of cyanobacterial OM in the sediments of Zone I. By contrast, TP levels of 0.08–0.29 mg/L in this zone are much higher than the 0.01–0.03 mg/L thought to be optimal for diatoms (such as Aulacoseira spp. and Cyclotella spp.) (Kalff, 2001), which therefore exhibit much lower productivity than cyanobacteria (Chen et al., 2003).

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Fig. 8. A sketch map of environmental and ecosystem variation within and around Lake Taihu, including the major inflowing and outflowing rivers (indicated as arrows in direction of flow) and the annual runoff between 2001and 2002 (108 m3 /y).

Diatom productivity peaks in late autumn or early winter when TP in the water decreases to its annual minimum (Song et al., 2007). Allochthonous OM accounted for a higher proportion of total OM in sediment of Zhushan Bay than in Meiliang Bay due to its greater riverine input (Fig. 8) and the larger quantity of terrestrial plant OM imported (Qin, 2008; Liu et al., 2009). Zone II comprises the East Bays. This part of the lake is drained by two significant outflows (Xijiang River and Taipu River) (Fig. 8) but has no inflowing rivers, so terrestrial OM and nutrients from the watershed cannot be transferred directly into this zone by river transport. The lack of direct inflow might partially account for the low nutrient abundance (TP < 0.05 mg/L; TN < 1.4 mg/L, Fig. 2a and b) and the low levels of allochthonous OM recorded in this zone. The water depth, soft-sediment depth and nutrient conditions of Zone II are suitable for the growth of submerged and floating macrophytes (Dong et al., 2014) and 14 species representing six families of submerged macrophytes were identified, dominated by an abundance of P. malaianus and V. natans (Dong et al., 2014). Submerged and floating macrophytes cover 73.6% and 18.3% of the water surface respectively (Gu et al., 2005) and the biomass of submerged macrophytes can reach 2882 g/m2 in September (He et al., 2008). This resulted in a significant accumulation of macrophyte-based OM in the sediment, as evidence by the high abundance of lipid biomarkers associated exclusively with macrophyte input (Figs. 4a and 5c), as well as the high TOC abundances (Fig. 3a). Besides the occurrence of macrophytes, predominance of C29 over C27 sterols (Fig. 4c) reveals a marked variation of phytoplankton structure compared to zone I. Most obviously, diatoms exhibited the greatest productivity because the mesotrophic water (TP: 0.03–0.05 mg/L) approached the optimal condition for their growth (Kalff, 2001). The high abun-

dance of HBI compounds in Zone II also suggests that diatoms are significant components of the epiphyte community. The relatively low levels of nutrient in this zone support high dinoflagellate productivity and significantly limit the productivity of cyanobacteria compared to Zone I (Schindler et al., 2008). Thus, the autochthonous OM in Zone II is characterized by a marked proportional increase in diatom input and a significant relative decline in cyanobacterial input. Zone III includes Gonghu Bay, Central and Western Region, which feature three inflowing rivers (Changxingang River, Xixin River and Xitiaoxi River) (Fig. 8). Compared to the rivers feeding Zone I, Zone III rivers are low in N and P (Yi et al., 2016), resulting in less extreme N and P loading (Fig. 2a and b). However, unlike in Zone I and II, wind-induced disturbance of sediment is very intense in zone III due to its long wind fetch and high dynamic ratio in this open area (Dong et al., 2014). From 1997 to 1999, daily maximum wind speeds higher than 5 m/s occurred 89.5% of the time, and wind speeds higher than 8 m/s occurred 34.2% of the time (Fan et al., 2004). Moderate winds (3.3–5.0 m/s) can cause strong mixing of the water and sediment and such resuspension can even occur in over two thirds of the year in this region (Cai et al., 2012). Indeed, the SS levels are higher in this zone than any other part of the lake (Fig. 2d). Wind-induced disturbance of water and sediment is likely to exert a strong negative influence on OM accumulation, because resuspended OM is likely to be mineralized in the water column before it can be buried in the sediment (Woszczyk et al., 2011). The fatty acid biomarkers in sediments from this zone indicated a significant degradation of algal OM in the water column, with sediment OM mainly reflecting input from terrestrial plants (Xu et al., 2015). Both autochthonous and allochthonous OM inputs

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were at their lowest levels for the entire lake in this zone, despite the relatively high phytoplankton productivity indicated by Chl a concentrations (Fig. 2c), and the significant import of terrestrial plant OM by inflowing rivers (Zhang et al., 2011). These inputs are counteracted by the degradation mineralization of OM in the water column while the relative enrichment of terrestrial plant OM in the sediment reflects its greater resistance to degradation (Xu et al., 2015). 5. Conclusion Lipid biomarker evidence demonstrates that the origin and distribution of OM in sediments of Lake Taihu are significantly influenced by environmental variables in and around the lake. The distribution of allochthonous OM was dependent on hydrological conditions in the watershed, because terrestrial plant OM is transported to the lake mostly by rivers. By contrast, the autochthonous OM distribution is closely related to the nutrient status in the lake. Cyanobacterial blooms promoted by the hypertrophic water in Zhushan Bay and Meiliang Bay induce a significant accumulation of cyanobacterial OM in the sediments of these regions. Under the mesotrophic condition in the East Bays, macrophytes and diatoms present a high productivity. Macrophytes can even provide sites for the growth of diatoms in epiphytes. This resulted in a significant accumulation of OM from macrophytes and diatoms in the sediment. The Gonghu Bay, Central and Western Region experience moderate nutrient loading and a relatively high input from inflowing rivers and yet receive the lowest inputs of both autochthonous and allochthonous OM in the sediment. This likely reflects extensive degradation mineralization of OM in the water column, made possible by strong wind-induced disturbance of water and sediment. Acknowledgments The suggestions of two anonymous reviewers and the associate editor improved the manuscript greatly. Special thanks go to Prof. Kuanyi Li for discussion of this manuscript. The study was supported by the National Natural Science Foundation of China (Grant Nos. 41673046, 41303036 and U1033602). References Anderson, N., Dietz, R., Engstrom, D., 2013. Land-use change, not climate, controls organic carbon burial. Proc. Biol. Sci. 280, 20131278. Belt, S.T., Massé, G., Rowland, S.J., Poulin, M., Michel, C., LeBlanc, B., 2007. A novel chemical fossil of palaeo sea ice: IP25. Org. Geochem. 38, 16–27. Cai, Y., Gong, Z., Qin, B., 2012. Benthic macroinvertebrate community structure in Lake Taihu, China: effects of trophic status, wind-induced disturbance and habitat complexity. J. Great Lakes Res. 38, 39–48. Carreira, R.S., Wagener, A.L.R., Readman, J.W., Fileman, T.W., Macko, S.A., Veiga, Á., 2002. Changes in the sedimentary organic carbon pool of a fertilized tropical estuary, Guanabara Bay, Brazil: an elemental, isotopic and molecular marker approach. Mar. Chem. 79, 207–227. Carreira, R.S., Araújo, M.P., Costa, T.L.F., Spörl, G., Knoppers, B.A., 2011. Lipids in the sedimentary record as markers of the sources and deposition of organic matter in a tropical Brazilian estuarine–lagoon system. Mar. Chem. 127, 1–11. Chen, Y., Qin, B., Teubner, K., Dokulil, M.T., 2003. Long-term dynamics of phytoplankton assemblages: microcystis-domination in Lake Taihu, a large shallow lake in China. J. Plankton Res. 25, 445–453. Cranwell, P.A., 1984. Lipid geochemistry of sediments from Upton Broad, a small productive lake. Org. Geochem. 7, 25–37. Cranwell, P.A., Eglinton, G., Robinson, N., 1987. Lipids of aquatic organisms as potential contributors to lacustrine sediments. Org. Geochem. 11, 513–527. Dong, B., Qin, B., Gao, G., Cai, X., 2014. Submerged macrophyte communities and the controlling factors in large, shallow Lake Taihu (China): sediment distribution and water depth. J. Great Lakes Res. 40, 646–655. Duan, H., Ma, R., Xu, X., Kong, F., Zhang, S., Kong, W., Hao, J., Shang, L., 2009. Two-decade reconstruction of algal blooms in China’s Lake Taihu. Environ. Sci. Technol. 43, 3522–3528. Dunn, R.J.K., Welsh, D.T., Teasdale, P.R., Lee, S.Y., Lemckert, C.J., Meziane, T., 2008. Investigating the distribution and sources of organic matter in surface

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