The study areas were located in the ECS (Figure 1), a typical river-dominated continental margin sea that has been deeply influenced by riverine inputs from terrestrial soil in the Yangtze River (YR) catchments. The ECS received about 12 Mt/yr of organic matter (OM) as the largest continental margin in the Western Pacific realm (Wu et al., 2003). The muddy areas on the Yangtze River subaqueous delta and the Zhe-Min coastal mud area are formed by terrestrial inputs. As a result, the ECS shelf is an important target for paleoclimate reconstruction and understanding the role of the continental marginal sea in global carbon cycling.

Between 2013 and 2015, surface sediments (0–2 cm) were collected from 53 study locations in the ECS using a box corer (Figure 1). Samples were immediately placed in pre-cleaned polyethylene bags, sealed, and stored in a −20°C freezer until further analysis. Samples were freeze-dried for more than 48 h in a Christ Delta 1–24 LSC Laboratory freeze dryer (Christ, Germany). The dried samples were ground using a pre-cleaned agate mortar and pestle for further analysis.

Lipid extraction and GDGT analysis were conducted following the protocol described by Hopmans et al. (2016) and Zhang et al. (2018). Then 5 g of freeze-dried samples were weighed, ground, mixed with a quantified standard (C₄₆GDGT) (Huguet et al., 2006), and analyzed using an Agilent 1200 high-performance liquid chromatography system coupled to an Agilent 6460A triple-quadrupole mass spectrometer (HPLC-MS/MS) with atmospheric pressure chemical ionization (APCI) (Hopmans et al., 2004; Hopmans et al., 2016). The GDGTs were separated using two silica columns in tandem at 40°C. The elution gradients were n-hexane/ethyl acetate (84:16; v:v) for the first 5 min, n-hexane/ethyl acetate (82:18; v:v) for another 60 min, and then ethyl acetate for 21 min and kept for 4 min, followed by n-hexane/ethyl acetate (84:16; v:v) for 30 min at a flow rate of 0.2 ml/min. The MS conditions were given as follows: nebulizer at 60 psi, vaporizer at 400°C, N₂ flow at 6 L/min and temperature at 200°C, the capillary voltage 3500 V, and corona current at 5 μA (3200 V). Selected ion monitoring (SIM) was used for monitoring at m/z 1,292, 1,050, 1,048, 1,046, 1,036, 1,034, 1,032, 1,022, 1,020, 1,018, and 744. The quantification of GDGTs was performed by comparing the peak area of each compound with that of the C46 GDGT internal standard. The average relative standard deviation (RSD%) was lower than 10%.

BIT (a ratio of the branched and isoprenoid tetraether) index was calculated according to Hopmans et al. (2004): B I T = ( I a + I I a + I I I a + I I a ′ + I I I a ′ ) ( I a + I I a + I I I a + I I a ′ + I I I a ′ + C r e n ) . (1)

MBT′ 5ME, CBT′ 5ME, and pH were calculated according to De Jonge et al. (2014): M B T 5 M E ´ = ( I a + I b + I c ) ( I a + I b + I c + I I a + I I b + I I c + I I I a ) , (2) C B T 5 M E ´ = − l o g ( I b + I I b ) ( I a + I I a ) ,  and (3) p H = 7.84 − 1.73 × C B T 5 M E ´ (4)

The weighted average number of cyclopentane moieties (#Rings_tetra) was calculated for the tetramethylated brGDGTs according to Sinninghe Damsté (2016): # R i n g s t e t r a = ( I b + 2 × I c ) ( I a + I b + I c ) . (5)

MAAT was calculated according to Russell et al. (2018): M A A T = 23.81 − 31.02 × I I I a − 41.91 × I I b − 51.59 × I I b ' − 24.70 × I I a + 68.8 × I b  and (6) M A A T = − 1.21 + 32.42 × M B T 5 M E ´ . (7)

IIIa/IIa as calculated according to Xiao et al. (2016): ∑ I I I a ∑ I I a = I I I a + I I I a ′ I I a + I I a ′ (8)

In ECS, the brGDGT contents in the sediments ranged from 19.7 ng/g to 158.7 ng/g (avg. 66.59 ng/g), as shown in Figure 2A. From the subaqueous delta of the Yangtze River and the Zhe-Min coastal mud area to the outer shelf, the brGDGT contents showed a decreasing trend with water depth. The Cren contents varied from 36.1 ng/g to 814.9 ng/g (avg. 312.15 ng/g) in ECS (Figure 2B). In comparison with brGDGTs, the spatial distribution of Cren exhibited an opposite spatial distribution (Figure 2B).

In addition, the brGDGT contents were dominated by brGDGTs without cyclopentane moieties including brGDGT-Ia (16.6 ± 4.7%), IIa (19.3 ± 3.1%), II´a (8.7 ± 2.9%), IIIa (11.3 ± 4.5%), and III´a (10.8 ± 3.1%), which accounted for between 60.1 and −70.2% of the total brGDGT content, while brGDGTs with 1-2 cyclopentane moieties accounted for between 29.8 and 39.9%. Besides, tetra-, penta- , and hexamethyl-brGDGTs accounted for 32.3 ± 1.3%, 46.3 ± 1.2%, and 26.4 ± 1.1% of the total brGDGT content, respectively (Figure 3).

In ECS sediments, the MBT′ 5ME value ranged between 0.30 and 0.48 (avg. 0.38 ± 0.11), and the MBT′ 5ME value showed a decreasing trend from the subaqueous delta of the Yangtze River and inner shelf to the outer shelf (Figure 2C). The CBT′ 5ME value ranged between 0.23 and 0.49 (avg. 0.31 ± 0.13, Figure 2D). Compared with the CBT′ 5ME in the inner shelf, the brGDGTs in the subaqueous delta of the Yangtze River showed stronger cyclization. The CBT′ 5ME-derived pH ranged from 7.0 to 7.45 (avg. 7.3 ± 0.2) in the ECS. The calibration for MAAT by Russell et al. (2018a) ranged from 11.9°C to 19.7°C (avg. 15.4 ± 2.4°C, Figure 2E) and was consistent with the measured annual MAAT in mid-lower reaches of the Yangtze River (14.7°C–16.9°C, avg.15.4 ± 1.8°C) (Li et al., 2015). The MAAT based on MBT′ 5ME ranged from 8.6°C to 14.5°C (avg. 11.2 ± 2.1°C) and was 4°C lower than the measured annual MAAT in mid-lower reaches of the Yangtze River. The BIT values ranged from 0.02 to 0.71 (avg. 0.12 ± 0.13), which showed a decreasing trend from the inner shelf to the outer shelf (Figure 2F). The #Rings_tetra and IIIa/IIa values ranged from 0.40 to 0.79 (avg. 0.59 ± 0.15) and 0.35 to 0.78 (avg. 0.58 ± 0.13), respectively, which also showed an increasing trend from the inner shelf to the outer shelf (Figures 2G,H).

In comparison to the calibration (based on worldwide soil) for MAAT by De Jonge et al. (2014), the calibration (based on the aquatic environment) for MAAT by Russell et al. (2018a) had a lesser variance with the measured annual MAAT in the Yangtze River’s mid-lower reaches. This finding was most likely attributable to the aquatic environment, yet Russell et al. (2018a)’s MAAT was still a deviation applied to ECS sediments. In the inner shelf, the MAAT was more consistent with the recorded air temperature in the mid-lower reaches of the Yangtze River (Supplementar Figure S1 in the Supplementary Materials). This supports the previous report that most of the riverine inputs deposited and accumulated to form the subaqueous delta and inner shelf (Liu et al., 2006). Therefore, the MAAT of the subaqueous delta-brGDGTs closely matched the recorded air temperature of mid-lower catchments of the Yangtze River. Compared with the inner shelf, the MAAT based on MBT′ 5ME in the outer shelf indicated a lower level temperature than the recorded air temperature in the mid-lower reaches of the Yangtze River. In membrane lipid simulations, decreasing the degree of methylation leads to a more ordered and compact membrane with reduced membrane fluidity, providing a mechanistic foundation for widespread observation from natural samples that the degree of methylation of brGDGTs decreases with increasing temperature (Naafs et al., 2021). This explains why marine sediments contained fewer tetramethylated brGDGTs than soil (Sinninghe Damsté., 2016). Moreover, the presence of marine in situ brGDGTs resulted in a lower degree of tetramethylation brGDGTs in marine sediments than in the soil.

BIT was used to track terrestrial OM in the sediments, where brGDGTs originated from terrestrial soil (Hopmans et al., 2004; Weijers et al., 2007, Kim et al., 2012). The BIT value decreased offshore in ECS sediments, and the peak area was controlled by the Changjiang River. Although the BIT value did not take into account the in situ production of brGDGTs in the ECS, but it still indicated the influence of terrestrial materials in the large estuary. When compared to soil and lake sediments in the Yangtze River Basin, ECS surface sediments showed significant differences among tetra-, penta-, and hexamethylated brGDGTs (Figure 3) (Xie et al., 2012; Yang et al., 2014; Dang et al., 2018). This is consistent with findings from previous studies (Zhu et al., 2011; Sinninghe Damsté, 2016; Zhang et al., 2020). The fractional abundance of tetramethylated brGDGTs in ECS surface sediments was lower than the soil and lake sediments of the Yangtze River Basin, and the pentamethylated brGDGT level was higher. Furthermore, the majority of the brGDGTs in the ECS surface sediments were pentamethylated brGDGTs, whereas the soil contained mostly tetramethylated brGDGTs. This result represents the aquatic environment was smaller than the soils in our study area due to the degree of temperature difference, and the degree of methylation of brGDGTs decreases with increasing temperature. In ECS sediments, the #Ringstetra values increased offshore, as other reports in shelf sediments (Sinninghe Damsté, 2016). Due to the #Ringstetra value controlled by pH (Weijers et al., 2007), we suggest that the low #Ringstetra values controlled by Changjiang River and Zhe-Min coastal rivers. The high #Ringstetra values indicated marine in situ brGDGTs on the outer shelf, which was consistent with previous reports results (Duan et al., 2019; Zhang et al., 2020). The IIIa/IIa value was a sensitive source indicator for brGDGTs, and it considerably increased offshore in ECS sediments, which is useful for accurate estimation of organic carbon.

These were also significant differences in the #Rings_tetra and IIIa/IIa values between soil and marine derived brGDGTs (Sinninghe Damsté, 2016; Xiao et al., 2016; Crampton-Flood et al., 2018; Warden et al., 2018; Cao et al., 2020; Zhang et al., 2020; Liu et al., 2021). In marine sediments, the #Rings_tetra values ranged from 0.79 to 1.12 (avg. 0.96), while the IIIa/IIa values ranged from 0.92 to 1.16 (avg. 1.04), as shown in Figure 4A (Zhou et al., 2014; Sparkes et al., 2015; Xiao et al., 2016; Crampton-Flood et al., 2018; Cao et al., 2020; Zhang et al., 2020; Liu et al., 2021). In Yangtze River Basin soil, the #Rings_tetra values ranged from 0.2 to 0.32 (avg. 0.29), whereas the IIIa/IIa values ranged from 0.22 to 0.45 (avg. 0.35) (Dang et al., 2018). The value of #Rings_tetra and IIIa/IIa in Yangtze River Basin soil was lower than that in the surface sediments in ECS (Yang et al., 2014; Dang et al., 2018). Therefore, the existence of marine in situ production of brGDGTs in ECS was shown by the distribution of #Rings_tetra and IIIa/IIa.

Thus, the source of brGDGTs is discriminated by the following equations: A C + A m a r i n e = 1 (9) # R C × A C + # R m a r i n e × A m a r i n e = # R s a m p l e (10) ( I I I a I I a ) C × A C + ( I I I a I I a ) m a r i n e × A m a r i n e = ( I I I a I I a ) s a m p l e (11) where A_C represents the contribution of brGDGTs in the Yangtze River soil, A_marine represents the contribution of marine in situ production of brGDGTs, #R_C represents the mean value of #Rings_tetra in the Yangtze River catchment soil (a mean of 0.29), and ( I I I a I I a ) C represents the mean of IIIa/IIa in the Yangtze River catchment soil (a mean of 0.35). Moreover, #R_marine and ( I I I a I I a ) m a r i n e are considered as the marine in situ production of brGDGTs in the marine environment, with averages of 0.96 and 1.04, respectively (Zhou et al., 2014; Sparkes et al., 2015; Xiao et al., 2016; Crampton-Flood et al., 2018; Cao et al., 2020; Zhang et al., 2020, Liu et al., 2021). As a result, the contributions of brGDGTs derived from Yangtze River catchment ranged from 34 to 91% (Figure 4B), while marine in situ production of brGDGTs ranged from 9 to 66% (Figure 4C). In general, the production of marine in situ brGDGTs in the ECS showed an increasing trend from the coast to the outer shelf. The majority of the soil brGDGTs were deposited in the estuary and coast, which was consistent with previous reports (Duan et al., 2019; Cao et al., 2020; Zhang et al., 2020).

Previous studies suggest that brGDGTs can be produced in situ in the water column or the sediments of an aquatic environment (Peterse et al., 2009; Kim et al., 2012; Sparkes et al., 2015; Sinninghe Damsté., 2016; Xiao et al., 2016; Crampton-Flood et al., 2018; Warden et al., 2018; Cao et al., 2020; Zhang et al., 2020, Liu et al., 2021). Acidobacteria have been proposed as a potential candidate group, and its subdivisions I, III, IV, and VI had produced the presumed building block of brGDGTs (Weijers et al., 2009; Sinninghe Damsté et al., 2018). Compared with the anaerobic zones, Acidobacteria increased from 2.80 to 4.69% of total bacterial RNA in sediments and increased from 0.05 to 4.91% in oxygen-saturated areas (Zimmermann et al., 2012). Acidobacteria preferred aerobic zones with an organically enriched environment. In addition, they had a feedback relationship with phototrophic communities dominated by cyanobacteria (Zimmermann et al., 2006; Zimmermann et al., 2012). The differences of methylation and cyclization of brGDGTs in microbial cultures of Acidobacteria were not only considered as physiological responses but also related to compositional changes (Sinninghe Damsté et al., 2018). As shown in Figure 4, the methylation of brGDGTs in ECS was similar to that of the lakes in the catchments when compared with the soils in the Yangtze River catchments. Moreover, in situ brGDGTs synthesis in water is associated with eutrophication and redox stratification. The high proportion of IIIa´ in total brGDGTs is a common phenomenon in marine environments, where in situ production of brGDGTs is significant (Xiao et al., 2016). Besides, it is predominantly biosynthesized in the lower part of the oxygenated water column (Weber et al., 2018), which imprints the redox transition zone at the subsurface water in the ocean. In membrane lipid simulations, the decreasing degree of methylation leads to a more ordered and compact membrane with reduced membrane fluidity (Naafs et al., 2021). Therefore, marine in situ brGDGTs are preferred to associate with subsurface water. In recent work, samples by the contribution rate of in situ production of brGDGTs for temperature reconstructions allowed the MBTʹ 5MEmarine to be separated from samples (Crampton-Floodet al., 2018). Thus, we calculated the MBTʹ 5MEmarine in low-latitude continental margin surface sediments and associated with the subsurface water. It showed good potential in paleoenvironment reconstruction and land–sea interactions. Moreover, earlier research had shown that pH has a significant impact on modifying the degree of cyclization to mix the sources of brGDGTs (De Jonge et al., 2014; Russell et al., 2018a; Naafs et al., 2021). Therefore, the effects of methylation and cyclization on keeping membranes fluid and permeable must be considered in brGDGTs paleothermometers. Overall, brGDGT paleothermometer is worth further research to understand its responses in climate changes.