Last Day On Earth Quartz
Oleta Blaylock
Among various monsoon proxy records, oxygen isotope records of stalagmites (δ18Oc) from South China have been widely used because of the precise dating of the records using U-series method and its quantitative nature with high time resolution (Wang et al. 2001, 2005; Hu et al. 2008; Cheng et al. 2006). Early works interpret stalagmite δ18O signals as representing changes in the summer/winter precipitation ratio (Wang et al. 2001) whereas later works interpret it as a proxy for regional precipitation of the EASM, with higher EASM precipitation corresponding to depleted (more negative) δ18Oc (Wang et al. 2005). Namely, shifts in δ18Oc largely reflect changes in the oxygen isotope ratio of precipitation (δ18Op) at the site, which in turn reflect changes in the amount of precipitation (the so-called amount effect) and thus characterize the EASM precipitation intensity (Wang et al. 2005). However, these interpretations have been recently questioned. For example, Maher and Thompson (2012) suggested that changes in the oxygen isotope ratio of these stalagmites in South China do not necessarily represent the amount effect but rather represent changes in the source of water vapors. Furthermore, when stalagmites occur along the edge of monsoonal belts, their oxygen isotope ratios could be impacted by both the EASM and Indian summer monsoon (ISM). One needs to carefully consider regional, geographical, and seasonal effects and in particular consider the amount-weighted δ18O (Maher 2008; Maher and Thompson 2012).
By using the δ18O and Mg/Ca of planktonic foraminifera, Kubota et al. (2010, 2015, 2019) reconstructed the δ18O of surface water (δ18Osw) in the northern East China Sea (ECS), which is an indirect indicator of the sea surface salinity (SSS). Using the relationship between the SSS in the northern ECS and the Yangtze River discharge during summer, Kubota et al. (2010, 2015) reconstructed temporal changes in the Yangtze River summer discharge during the Holocene, which they consider as the proxy of EASM precipitation in South China. They argued that their result inferred from δ18Osw is not consistent with δ18Oc records of stalagmites in South China that implied the early Holocene EASM precipitation maximum. Thus, they suggested that it is not appropriate to explain orbital-scale changes in stalagmite δ18Oc in South China during the Holocene by changes in the EASM precipitation amount, but more appropriate to explain the changes by other factors such as changes in the moisture source (Kubota et al. 2015).
The inner shelf of the ECS is of primary importance owing to the massive inputs of terrestrial materials from the Yangtze River, among the largest rivers in the world in terms of sediment load and freshwater discharge (Milliman and Meade 1983; Milliman et al. 1985; Milliman and Syvitski 1992), and its complex oceanic circulation on the shallow (
Two major types of sediments have been recognized as Yangtze-River-derived sediments on the inner shelf of the ECS system: mud-dominated sediments and the relict sandy sediments deposited during the Late Pleistocene low-sea-level stands (Qin 1979; Qin et al. 1987). The mud-dominated sediments predominantly discharged from the Yangtze River as SPM were mainly carried by the Zhejiang-Fujian Coastal Current (ZFCC) flowing south to southwestward along the Chinese coast, forming the mud belt on the inner shelf of the ECS. The warm and saline Taiwan Warm Current (TWC), which partly originates as an offshoot of the Kuroshio Current, flows northeastward between the 50 and 100 m isobaths of the ECS and intrudes into the submerged river valley off the Yangtze River mouth. The warm and saline Kuroshio Current (KC) enters the ECS along the eastern coast of Taiwan and the mainstream flows northeast along 200 m isobaths (Fig. 1) (Yang et al. 1992; Chen et al. 1994; Chang and Isobe 2003; Liu et al. 2007; Wang et al. 2014).
When the ESR signal intensity in the fine silt and coarse silt fractions are compared, the former is higher and more variable than that of the latter from 10 to 4.1 kyr BP, while both are similar from 4.1 to 2.0 kyr BP. The ESR signal intensity in the fine silt fraction becomes higher than that in the coarse silt fraction again from 1.8 to 0.9 kyr BP, while both are similar again beginning at 0.9 kyr BP.
The CI of quartz in the coarse silt fraction shows values similar to those in the fine silt fraction from 10 to 6.0 kyr BP. The CI of quartz in the coarse silt fraction is greater than that in the fine silt fraction and CI of the two fractions shows an opposite variation trend from 6.0 to 0 kyr BP at a millennial time scale. Compared to the temporal changes in the ESR signal intensity of quartz, the temporal variation patterns of the CI of quartz in the two fractions does not show obvious changes at 4.1 and 3.5 kyr BP. The CI of quartz in the coarse silt fraction shows a sudden decrease at 2.0 kyr BP that lasts until 1.2 kyr BP.
When the CI of quartz in the fine silt fraction and that in the coarse silt fraction are compared, both vary from 10.0 to 6.0 kyr BP; the former is relatively stable compared to the latter from 6.0 kyr BP to the present. The CI of quartz in the fine silt fraction maintains a higher value than that in the coarse silt fraction from 10.0 to 0 kyr BP.
The red curve in Fig. 3c shows the temporal changes in the QC in the fine silt fraction which varies between 0.2 and 0.6 with an average of 0.4 and a standard deviation of 0.08 with a slight decreasing trend from 10 to 3.5 kyr BP. It suddenly increases from 0.3 at 3.5 kyr BP to 0.6 at 2.9 kyr BP, and then maintains a more or less constant value between 0.4 and 0.7 with an average of 0.5 and a standard deviation of 0.1 from 3.5 to 0 kyr BP.
The blue curve in Fig. 3c shows the temporal changes in the QC in the coarse silt fraction which varies between 0.3 and 0.8 with an average of 0.5 and a standard deviation of 0.1 over the last 10 kyrs. The QC in the coarse silt fraction varies between 0.3 and 0.6 with an average of 0.5 and a standard deviation of 0.1 from 10 to 6.0 kyr BP, and then varies between 0.4 and 0.6 with an average of 0.5 and a standard deviation of 0.06 from 6.0 to 3.5 kyr BP. The QC in the coarse silt fraction increases to 0.7 at 3.3 kyr BP, and then varies between 0.1 and 0.8 with an average of 0.6 and a standard deviation of 0.1 from 3.5 to 0 kyr BP.
The QC in both the fine silt and coarse silt fractions show similar temporal trends; the QC in the coarse silt fraction is slightly larger than that that in fine silt fraction from 10.0 to 0.6 kyr BP.
Based on the temporal variation patterns in ESR signal intensity, the CI and QC for both fine and coarse silt fractions, as previously described, were divided into the five intervals that are supposed to reflect changes in provenance. Namely, interval 1 (from 10 to 6.0 kyr BP) is characterized by a high ESR signal intensity, moderate quartz CI, and variable QC in both fractions. Following interval 1, the ESR signal intensity and QC in both fractions become moderately variable, and the CI of quartz in the fine silt fraction remains constant. Interval 2 (from 6.0 to 4.1 kyr BP) is characterized by a relatively high and moderately variable ESR signal intensity of quartz and a moderate CI and low QC in both fractions. Interval 3 (from 4.1 to 3.5 kyr BP) is characterized by a similar, moderately variable ESR signal intensity of quartz and a moderate CI and low QC in both fractions. Interval 4 (from 3.5 to 2.0 kyr BP) is characterized by a similar low ESR signal intensity of quartz with low variability, a moderate and variable CI, and an increasingly high QC with high variability in both fractions. Interval 5 (from 2.0 to 0 kyr BP) is characterized by a low to moderate ESR signal intensity of quartz with a low variability in the fine silt fraction, a low to moderate ESR signal intensity of quartz with high variability in the coarse silt fraction, a moderate and more or less constant CI in the fine silt fraction and a variable CI in the coarse silt fraction, and a high QC in both fractions.
Interval 1 corresponds to lithostratigraphic unit 2 in addition to the basal part of unit 3, which is equivalent to a TST. Intervals 2 to 5 correspond to lithostratigraphic unit 3, which is composed of mud deposits characteristic of the mud belt and represents a HST, whose deposition began when the contribution of fine-grained SPM derived from the Yangtze River became significant with rare tidal influence at 6 kyr BP (Wang et al. 2014).
The Yangtze River annually delivers a huge SPM load into its estuarine system and the ECS, resulting in a great impact on sedimentation in the inner shelf of the ECS, particularly in the mud belt during the Holocene (Liu et al. 2006, 2007; Zheng et al. 2010; Wang et al. 2014; Liu et al. 2014; Yang et al. 2015; Bi et al. 2017; Liu et al. 2018). Therefore, the inner shelf sediments deposited as the mud belt are the most appropriate sediments to study the provenance changes of SPM delivered via the Yangtze River.
Figure 5 shows a comparison of the ESR signal intensity and CI of quartz in the fine silt fraction of MD06-3040 core sediments in intervals 2 to 5 to those of the four major source areas in the modern Yangtze River drainage shown in Fig. 4. On the ESR signal intensity versus CI diagram, most of the fine silt fraction samples from the MD06-3040 core plotted within the area of the fine silt fraction of riverbed sediments from the entire Yangtze River drainage, suggesting that they can be explained by mixing of the sediments from the four major source areas in the modern Yangtze River drainage classified by Saito et al. (2017). Notably, this result is consistent with the idea that the Yangtze River has been a predominant source of fine-silt-sized sediments on the inner shelf of ECS over the last 6 kyrs (Zheng et al. 2010; Wang et al. 2014; Yang et al. 2015; Fang et al. 2018).
The authors sincerely thank all crews of MD155-Marco Polo II IMAGES XIV cruise on board for retrieving MD06-3040 core, researchers and staffs at the University of Tokyo, Tongji University, Institute of Geochemistry in Guangzhou, Chinese Academy of Sciences (CAS), and Peking University for laboratory assistance. We also would like to express our gratitude to Prof. Hodaka Kawahata, Mr. Hiroto Kajita from the University of Tokyo for cooperatively establishing the age model, as well as Prof. Shouye Yang from Tongji University, Prof. Masanobu Yamamoto from Hokkaido University, PEPS editor Dr. Ken Ikehara, Dr. Kana Nagashima from Japan Agency for Marine-Earth Science and Technology, Dr. Yoshimi Kubota from National Museum of Nature and Science, and two reviewers for constructive comments and suggestions greatly improving this manuscript.
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