Wang et al. Progress in Earth and Planetary Science
https://doi.org/10.1186/s40645-019-0319-5(2020) 7:5

Progress in Earth andPlanetary Science

RESEARCH ARTICLE

Open Access

Provenance changes in fine detrital quartz
in the inner shelf sediments of the East
China Sea associated with shifts in the East
Asian summer monsoon front during thelast 6 kyrs
Ke Wang1,2*, Ryuji Tada1,2,3, Hongbo Zheng2, Tomohisa Irino4*, Bin Zhou5 and Keita Saito1

Abstract
The inner shelf sediments of the East China Sea (ECS) preserve valuable information regarding climatic changes onland through detrital material discharged from large rivers, particularly the Yangtze River. In this paper, we examine
the provenance changes of fine-grained detrital quartz preserved in the sediment of the MD06-3040 core retrieved
from the mud belt on the inner shelf of the ECS during the last 6 kyrs. The provenance of the fine silt fraction (4–16 μm) of the sediments, which is considered to represent the suspended particulate matter (SPM) from the
Yangtze River, is estimated based on the electron spin resonance (ESR) signal intensity and crystallinity index (CI) of
quartz. By comparing the ESR signal intensity and CI of quartz in the fine silt fraction of sediments to those fromdifferent parts of tributaries in the modern Yangtze River drainage, we can discriminate the SPM sourced from thenorthwestern and southeastern tributaries of the Yangtze River. Shifts in the East Asian summer monsoon (EASM)
front are monitored by changes in the main precipitation areas which are manifested as changes in source rockages and types implied from the ESR signal intensity and CI of quartz in the fine silt fraction of the studied
sediments discharged from the Yangtze River. Temporal changes in provenance of the fine silt fraction throughtime suggest that shifts in the main location of EASM precipitation (most likely representing the EASM front)
occurred at a multi-centennial-to-millennial scale with the deepest northwestward penetration of the EASM
precipitation front (an enhanced EASM) occurring during the period 3.5–2.0 kyr BP and a southeastward retreat (aweak EASM) occurring during the periods 6.0–4.1 and 2.0–0 kyr BP.
Keywords: Electron spin resonance, Crystallinity index, East Asian summer monsoon, The Yangtze River drainage,
The East China Sea

Introduction
The East Asian summer monsoon (EASM) is a distinctive
component of the Asian climatic system due to uniqueorographic forcing and huge thermal contrast between theworld’s largest continent, Eurasia, and the largest ocean,the Pacific (Zhou et al. 2009). It is also strongly influenced
by the world’s highest land feature, the Tibetan Plateau* Correspondence: wangke@eps.s.u-tokyo.ac.jp; irino@ees.hokudai.ac.jp
1
Department of Earth and Planetary Science, The University of Tokyo, Tokyo,
Japan
4
Faculty of Environmental Earth Science, Hokkaido University, Sapporo, Japan
Full list of author information is available at the end of the article(Wang and Lin 2002; Wang et al. 2002; Ding and Chan
2005; Tada et al. 2016). Meteorological data suggest thatmodern EASM precipitation shows significant spatiotemporal variability in eastern and southern China at a seasonal timescale, which has been attributed to the seasonal
northwestward migration of its precipitation front (Zhang
et al. 2008; Yim et al. 2014; Tada et al. 2016). Comparisonof the observational precipitation amount to the strengthof convection over East Asia suggests that summer precipitation increases (decreases) in North China and decreases (increases) in South China when convection overEast Asia strengthens (weakens) (Wang et al. 2002; Ding

© The Author(s). 2020 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0
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Wang et al. Progress in Earth and Planetary Science(2020) 7:5

and Chan 2005). As the trend of precipitation derived
from observational data represents a limited length of timeand spatial extent, the main purpose of this study was toreconstruct spatiotemporal variations of the main locationof EASM precipitation within the Yangtze River drainage
during the middle and late Holocene.
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 havebeen recently questioned. For example, Maher andThompson (2012) suggested that changes in the oxygenisotope ratio of these stalagmites in South China do notnecessarily represent the amount effect but rather represent changes in the source of water vapors. Furthermore,when stalagmites occur along the edge of monsoonalbelts, their oxygen isotope ratios could be impacted byboth the EASM and Indian summer monsoon (ISM).
One needs to carefully consider regional, geographical,
and seasonal effects and in particular consider theamount-weighted δ18O (Maher 2008; Maher andThompson 2012).
By using the δ18O and Mg/Ca of planktonic foraminifera, Kubota et al. (2010, 2015, 2019) reconstructed theδ18O of surface water (δ18Osw) in the northern East
China Sea (ECS), which is an indirect indicator of thesea 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 Chinathat 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).

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The provenance of sediment as well as
paleoenvironmental changes on the inner shelf of the
ECS have been well studied (Zheng et al. 2010; Wanget al. 2014; Liu et al. 2014; Yang et al. 2015; Bi et al.
2017; Fang et al. 2018; Liu et al. 2018). In this study, we
conducted provenance discrimination using the electron
spin resonance (ESR) signal intensity and crystallinity
index (CI) of quartz, which has been successfully applied
to modern surface samples to trace eolian dusts fromvarious deserts in western China (Sun et al. 2007, 2013),
to core sediment recovered from the Japan Sea to trace
dust provenance changes in association with the southward–northward shifts of the Westerly Jet (WJ) (Nagashima et al. 2007, 2011, 2012, 2013) and to characterizesuspended particulate matter (SPM) collected from various segments of the Yangtze River drainage (Saito et al.
2017). Saito et al. (2017) established a new method toevaluate relative contribution of sediment discharge
from different parts of the Yangtze drainage basin basedon the provenance of quartz in the fine silt fraction (4–16 μm) of riverbed sediments collected from all the
major tributaries of the Yangtze River using ESR signal
intensity and CI of quartz as a provenance tracer. They
concluded that the changes in provenance of the fine silt
fraction of detrital material are caused by changes in thehigh-precipitation area between the upper reaches andthe middle–lower reaches (Saito et al. 2017). The Yangtze River drainage basin occupies the major part ofSouth China in the middle of the present EASM region.
The annual precipitation ranges from 500 mm in thewest to 2500 mm in the east, and greater than 60% of
the annual precipitation is concentrated during summer(June, July, and August) (Xu et al. 2008). Because SPM
constitutes more than 95% of the sediment load discharged from the Yangtze River (Chen et al. 2001), anda strong positive relationship (R2 = 0.81) exists between
sediment load and fresh water discharge (Xu et al. 2010),
fresh water discharge of the Yangtze River could reflect
precipitation amounts in the drainage (Chen et al. 2014).
Consequently discharge of SPM from the Yangtze River
could reflect precipitation amounts in the drainage.
Based on these observations, changes in the SPM provenance reflect changes in the distribution of highprecipitation areas (Saito et al. 2017). The SPM discharged from the Yangtze River, whose grain size isdominantly a fine silt size, is distributed on the innershelf of the ECS extending southwestward from the
Yangtze River estuary along the southeastern coast ofSouth China, forming mud belts (Qin 1979; Qin et al.
1987; Liu et al. 2007). Based on this reasoning, we applied the provenance discrimination method of Saito
et al. (2017) to the MD06-3040 core retrieved from the
mud belt on the inner shelf of the ECS to reconstructspatiotemporal variations in the EASM precipitation area

Wang et al. Progress in Earth and Planetary Science(2020) 7:5

within the Yangtze River drainage during the middle andlate Holocene by examining provenance changes of finedetrital quartz (4–16 μm) derived from the Yangtze
River.
Regional setting

The inner shelf of the ECS is of primary importanceowing to the massive inputs of terrestrial materials fromthe Yangtze River, among the largest rivers in the worldin 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 (< 130 m) and broad (500 km) shelf(Qin 1979; Qin et al. 1987). Although annual sedimentload decreased from 0.48 × 109 t/year during the 1960s
to 0.34 × 109 t/year during the 1990s due to dam construction and water consumption, the Yangtze River remains the predominant sediment supplier to the delta
and coastal areas (Milliman and Meade 1983; Milliman
et al. 1985; Milliman and Syvitski 1992). In contrast,
sediment contribution from the Qiantang, Min, Ou, andJiao rivers to the coastal areas is only 0.007 × 109,
0.006 × 109, 0,003 × 109, and 0.001 × 109 t/year, respectively (Deng et al. 2006).

Page 3 of 15

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 andsaline 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 andIsobe 2003; Liu et al. 2007; Wang et al. 2014).
According to previous stratigraphic and seismic profiling studies (Liu et al. 2006, 2007; Liu et al. 2014; Wanget al. 2014), the depositional sequence in the tidedominated Yangtze delta and mud belt areas is composed of a post-glacial transgressive surface (TS) and

Fig. 1 Map (a) showing the Yangtze drainage (yellow area), the location of the MD06-3040 core used in this study, and two Holocene stalagmite
δ18O sites. The modern EASM limit is shown by the black dashed line according to Chen et al. (2015). Map (b) showing the regional oceanic
circulation pattern in the East China Sea (ECS) and Yellow Sea (YS). CDW, Changjiang Dilute Water; ZFCC, Zhejiang-Fujian Coastal Current; JCC,
Jiangsu Coastal Current; YSWC, Yellow Sea Warm Current; TWC, Taiwan Warm Current; KC, Kuroshio Current. The gray shaded areas represent the
mud belts distributed from the Yangtze River estuary to the southwest along the shoreline of South China on the inner shelf of the ECS (Wanget al. 2014)

Wang et al. Progress in Earth and Planetary Science(2020) 7:5

transgressive systems tract (TST) that are overlain by
the subsequent highstand systems tract (HST) with the
maximum flooding surface (MFS) at its base (Liu et al.
2007).

Methods
Materials

The MD06-3040 core was recovered from the central
mud belt off the Zhejiang-Fujian coast on the inner shelfof the ECS (27° 43.36′ N, 121° 46.88′ E) at a water depthof 47 m during the IMAGES MD155-Marco Polo cruise
II by R/V Marion Dufresne in 2006 (Wang et al. 2014).
The division of lithostratigraphic units of the MD063040 core is described in Wang et al. (2014). Stratigraphic correlation between the two neighboring coresMD06-3039 (27° 43.36′ N, 121° 46.91′ E) and MD063040 was conducted based on visual pattern matching
and cross-correlation of the magnetic susceptibility profiles, which enabled us to project the age-controlling datums of the MD06-3039 core to the MD06-3040 core
(Wang et al. 2014). Using this common stratigraphic
framework established between the MD06-3039 andMD06-3040 cores, the age model for MD06-3040 core
was constructed using nine AMS14C dates of bivalve
shells, five shell samples obtained from MD06-3039
core, and four from the MD06-3040 core (Wang et al.
2014). To increase the precision of the age model, an
additional four well-preserved shells from the MD063040 core were analyzed at Paleo-Labo Co., Ltd., to revise the previous age model (Kajita et al. 2018). All
AMS14C dates were converted to calendar years using
the Oxcal v 4.2.4 software (Ramsey and Lee 2013) with
the Marine 13 dataset (Reimer et al. 2013), which includes a constant average global reservoir age of 400
years (Kajita et al. 2018, Table 1).

Page 4 of 15

One-hundred and thirty samples at a stratigraphic
interval of 4 cm (sometimes 8 or 16 cm due to sample
deficiency) from the MD06-3040 core were analyzed for
the ESR signal intensity and CI of quartz in the fine silt
fraction to reconstruct provenance changes of the SPM
discharged from the Yangtze River at a 40-year interval
on average. The analyzed samples include 84 samples
analyzed by Wang et al. (2014), who used the ESR signal
intensity and CI of quartz to distinguish between
Yangtze-derived sediment and sediments derived fromother local rivers. The remaining 86 samples are newly
analyzed in this work.

ESR signal intensity analysis

The ESR signal intensity of the E1′ center in the quartz reflects the number of unpaired electrons accompanied byoxygen vacancies (Feigl et al. 1974; Toyoda and Ikeda
1991; Toyoda and Naruse 2002). As oxygen vacancies areformed mainly by α, β, or γ rays emitted by natural radiation of radioactive elements contained in the host rock,the ESR signal intensity increases with an increase in theage of the host rock (Toyoda and Naruse 2002). The ESR
signal intensity of the bulk sample was normalized by theweight percent of quartz in the sample to obtain the ESR
signal intensity of the quartz per unit weight, whose unit
is 1.3 × 1015 spins/g (Toyoda and Hattori 2000).
Prior to ESR signal intensity measurement, a pretreatment sequence for the sample is necessary to concentrate quartz grains and remove elements such as Mn
that interfere with E1′ center signal. Details of the chemical pretreatment procedure are described in Wang et al.
(2014). Following these pretreatments, samples wereseparated into a clay fraction (< 4 μm), fine silt fraction(4–16 μm), and coarse silt fraction (16–63 μm) using a

Table 1 Table caption
Lab
code

Depth
(cm)
MD063039

Depth
(cm)
MD063040

Conventional14
C age(yr BP)

Calibrated age (Marine13)
Intercept

Range

61–62

580 ± 20220

148–271

GZ819

140–141(154–155)627 ± 21275

255–293

GZ820

210–211(231–232)

1217 ± 22752

716–783

298–299

1765 ± 30

1309

1277–1338

509–5103490 ± 25

3375

3339–3410

GZ825

723–7243917 ± 25

3896

3850–3940

GZ20181151–1152

4992 ± 34

5351

5294–5396

GZ20191363–1364

5788 ± 41

6211

6179–6262

1457–1458

6120 ± 23

6551

6505–6600

GZ2022

1611–1612

7205 ± 36

7666

7616–7704

GZ826

1912–1913

9479 ± 33

10324

10251–10369

Wang et al. Progress in Earth and Planetary Science(2020) 7:5

Page 5 of 15

settling method based on Stokes law; the latter two fractions were used in this study.
Prior to the ESR signal intensity measurements, 2 g ofpretreated samples was irradiated with γ-radiation (atotal dose of 2.5 kGy) using a 60Co source at the Takasaki Advanced Radiation Research Institute, National Institutes for Quantum and Radiological Science andTechnology, Takasaki, Japan, following the method of
Toyoda and Hattori (2000). After irradiation, approximately 1 g of pretreated samples was heated at 300 °C
for 15 min to convert the oxygen vacancies of quartz toE1′ centers (Toyoda and Ikeda 1991). The ESR signal intensity measurements were conducted using a JEOL JESFA100ESR spectrometer at the University of Tokyo atroom temperature under 0.01 mW of microwave power,
0.1 mT of magnetic field modulation (100 kHz), 5 mT ofscan range, 2 min of scan time, and a time constant of
0.03 s (Wang et al. 2014). The reproducibility of the ESR
signal intensity was ± 1.0 spin unit.

crystallinity based on the method of Isozaki (2009). The
reproducibility of the QC was ± 3%.
According to our previous study, the fine silt fraction(4–16 μm) of the detrital sediment is considered as
mainly representing SPM (Saito et al. 2017) whereas thecoarse silt fraction (16–63 μm) represents suspension
particles under high water discharge and/or saltation
particles transported by bottom currents (Wang et al.
2011). The grain size distribution of the MD06-3040
core sediments showed a modal size of the major grain
size population at 4–8 μm and modal sizes of minor
grain size populations at 0.8–4 μm and 16–22 μm (Fig. 2).
The fine silt fraction (4–16 μm) of the MD06-3040 coresediments, and its proportion during the period 6–0 kyr
BP, is 64.5% on average except for the coarse silt tosandy sediment at a depth interval of 2.7–2.9 m (1.1–
1.2 kyr BP), enabling representation of the SPM fromthe Yangtze River. Therefore, our provenance study
mainly focuses on quartz in the fine silt fraction (4–16 μm).

X-ray powder diffraction analysis

Results

The CI of quartz was originally defined by Murata andNorman (1976) on the basis of the degree of resolutionof the d (212) reflection of quartz at 1.3820 Å on the Xray diffraction (XRD) profile. The CI of quartz reflects
physical conditions during quartz formation and is typically the highest for quartz formed under high temperatures and/or formed at a slow crystallization rate. In thisstudy, measurement of the CI of quartz was conductedusing a PANalytical X’Pert PRO X-ray diffractometer at
the University of Tokyo with a CuKα beam generated at
a voltage of 45 kV and a current of 40 mA with a divergence slit 1.52 mm in width and an anti-scatter slit 3
mm in width. The CI values were calculated as the degree of the quartz peak split at 67.74° 2θ, based on thedefinition of Murata and Norman (1976). The CI ofquartz was also used to constrain the provenance ofquartz. The reproducibility of the CI for five repeated
XRD measurements was ± 0.25.
The quartz content (QC) was determined using the internal standard method (Klug and Alexander 1974) withsilicon (Wako Co., Ltd.) as an internal standard. Measurement for QC was also conducted using the PANalytical X’Pert PRO X-ray diffractometer at the University ofTokyo with a CuKα beam generated at a voltage of 45
kV and a current of 40 mA with a divergence slit1.52
mm in width and an anti-scatter slit 3 mm in width. The
QC was calculated by the ratio of the quartz peak heightat 20.9 °2θ and silicon peak height at 27.9 °2θ measured
on the XRD profile; the peak height ratio between thequartz and silicon was translated to the QC in weightpercent using a predetermined calibration equation. The
quartz peak height was corrected for the effect ofTemporal changes in the ESR signal intensity of quartz inthe fine silt fraction (4–16 μm) and coarse silt fractions(16–63 μm)

The red curve in Fig. 3a shows the temporal changes inthe ESR signal intensity of quartz in the fine silt fraction(4–16 μm) of the MD06-3040 core samples during thelast 10 kyrs, which ranges between 3.5 and 24.0 with anaverage of 8.9 and a standard deviation of 3.2. From 10
to 6.0 kyr BP, the ESR signal intensity is high and highlyvariable, ranging between 3.8 and 23.7 with an averageof 12.3 and a large standard deviation of 5.0. From 6.0 to
4.1 kyr BP, the ESR signal intensity remains relatively
high ranging from 7.3 to 24.0 with an average of 10.8
and a moderate standard deviation of 3.2. During thisinterval, the ESR signal intensity rapidly decreased to 7.3
at 5.8 kyr BP, then gradually increases to ca. 15 at
4.5 kyr BP, and then decreased again to 4.6 at 4.1 kyr
BP. From 4.1 to 3.5 kyr BP, the ESR signal intensity
slightly increases and remains relatively low between 4.6
and 12.1 with an average of 7.9 and a small standard deviation of 1.9. From 3.5 to 2.0 kyr BP, the ESR signal intensity is low, ranging from 3.5 to 12.6 with an averageof 6.0 and a small standard deviation of 1.9. The ESR
signal intensity rapidly decreases to 4.1 at 3.5 kyr BP andthen gradually increases to 5.6 at 2.0 kyr BP. From
2.0 kyr BP to the present, the ESR signal intensity
slightly increases, ranging from 12.1 to 5.4 with an average of 8.4 and a small standard deviation of 1.6. It showsa higher value of 9.8 at 1.5 kyr BP and lower values ofless than 6.0 at 0.6 and 0.3 kyr BP.
The blue curve in Fig. 3a shows temporal changes inthe ESR signal intensity in the coarse silt fraction (16–Wang et al. Progress in Earth and Planetary Science(2020) 7:5

Page 6 of 15

Fig. 2 Typical grain size distributions of the MD06-3040 core sediments at a depth interval of 1 m (0.2 kyr BP) and 3 m (1.2 kyr BP)

63 μm) during the last 10 kyrs, which varies between 3.0
and 13.4 with an average of 6.8 and a standard deviationof 2.1. From 10 to 6.0 kyr BP, the ESR signal intensity ismore or less constant ranging from 5.9 to 10.2 with anaverage of 7.4 and a small standard deviation of 1.5.
From 6.0 to 4.1 kyr BP, the ESR signal intensity ranges

from 3.0 to 10.0 with an average of 5.8 and a standard
deviation of 1.8. During this interval, the ESR signal intensity continues to be constant until 4.4 kyr BP. From
4.1 to 3.5 kyr BP, the ESR signal intensity ranges from
3.3 to 9.8 with an average of 7.0 and a standard deviationof 1.6. During this interval, it rapidly decreases to 3.3 at

Fig. 3 Temporal changes in the (a) ESR signal intensity, (b) CI, and (c) quartz content in the fine silt fraction (4–16 μm; red) and coarse silt fraction(16–63 μm; blue) of the MD06-3040 core sediments. The calibrated 14C dates of the MD06-3040 core are presented with 2σ errors at the top of
the figure. Lithostratigraphic units with HST and TST are presented at the bottom of the figure. The vertical dotted lines divide the temporalsequence into five intervals based on the temporal variation patterns of the ESR signal intensity, CI, and QC for the fine and coarse silt
fractions, respectively

Wang et al. Progress in Earth and Planetary Science(2020) 7:5

4.1 kyr BP and then gradually increases to 8.1 at 3.5 kyr
BP. From 3.5 to 2.0 kyr BP, the ESR signal intensity
ranges from 3.9 to 11.2 with an average of 6.1 and asmall standard deviation of 1.5. During this interval, it
rapidly decreases to 5.0 at 3.3 kyr BP and remains stable
at approximately 7.0 until 2.0 kyr BP. From 1.5 to 0 kyr
BP, the ESR signal intensity ranges from 3.1 to 13.4 withan average of 7.3 and a standard deviation of 2.5, decreases to its lowest value of 3.1 at 1.5 kyr BP, and thengradually increases to 13.4 at 0.15 kyr BP.
When the ESR signal intensity in the fine silt andcoarse 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.
Temporal changes in the CI in the fine silt fraction (4–16 μm) and coarse silt fractions (16–63 μm)

The red curve in Fig. 3b shows the temporal changes in
the CI of quartz in the fine silt fraction (4–16 μm) of the
MD06-3040 core samples during the last 10 kyrs. During
this interval, it varies between 7.7 and 9.0 with an average of 8.5 and a standard deviation of 0.3. From 10 to
6.0 kyr BP, the CI of quartz in the fine silt fraction ismore or less constant between 7.7 and 8.8 with an average of 8.2 and a standard deviation of 0.3. It slightly increases, but remains more or less constant, between 8.0
and 9.0 with an average of 8.5 and a smaller standard deviation of 0.2 from 6.0 to 0 kyr BP.
The blue curve in Fig. 3b shows the CI of quartz inthe coarse silt fraction (16–63 μm) that ranges between
7.0 and 8.7 with an average of 8.0 and a standard deviation of 0.32 during the last 10 kyrs. The CI of quartz inthe coarse silt fraction is more or less constant between
8.3 and 7.7 with an average of 8.0 and a standard deviation of 0.2 from 10 to 6.0 kyr BP and ranges between
7.0 and 8.7 with an average of 8.1 and a standard deviation of 0.3 from 6.0 to 2.0 kyr BP. The CI of quartz inthe coarse silt fraction ranges between 7.0 and 8.5 withan average of 7.8 and a relatively large standard deviation of 0.5 from 2.0 to 1.2 kyr BP and is relatively variable between 7.3 and 8.6 with an average of 7.9 and astandard deviation of 0.3 from 1.2 to 0 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 isgreater than that in the fine silt fraction and CI of thetwo fractions shows an opposite variation trend from 6.0
to 0 kyr BP at a millennial time scale. Compared to thetemporal changes in the ESR signal intensity of quartz,
the temporal variation patterns of the CI of quartz in the

Page 7 of 15

two fractions does not show obvious changes at 4.1 and3.5 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 thatin the coarse silt fraction are compared, both vary from10.0 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.
Temporal changes in the QC in the fine silt fraction (4–16 μm) and coarse silt fractions (16–63 μm)

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 thecoarse silt fraction varies between 0.3 and 0.6 with anaverage 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 anaverage 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 deviationof 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.
Recognition of each interval and relationship with thelithostratigraphic unit

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 thefive intervals that are supposed to reflect changes inprovenance. Namely, interval 1 (from 10 to 6.0 kyr BP)
is characterized by a high ESR signal intensity, moderatequartz CI, and variable QC in both fractions. Followinginterval 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Wang et al. Progress in Earth and Planetary Science(2020) 7:5

quartz and a moderate CI and low QC in both fractions.
Interval 3 (from 4.1 to 3.5 kyr BP) is characterized by asimilar, moderately variable ESR signal intensity ofquartz and a moderate CI and low QC in both fractions.
Interval 4 (from 3.5 to 2.0 kyr BP) is characterized by asimilar 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 tomoderate 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 thecoarse silt fraction, a moderate and more or less constant CI in the fine silt fraction and a variable CI in thecoarse silt fraction, and a high QC in both fractions.
The sedimentary facies and lithostratigraphic unit division of the MD06-3040 core have been reported by
Wang et al. (2014). Three lithostratigraphic units were
defined as follows: unit 1 (19.3–18.3 m depth, 10.5–
9.6 kyr BP) consisting of dark gray, moderately sorted
coarse silt interbedded with 1.5–2.0-cm layers of coarse
sand rich in bivalve shell fragments; unit 2, (18.3–15.86
m depth, 9.6–7.5 kyr BP), consisting of dark graymedium silt interbedded with a few thin layers of finesand showing ripples with rare bioturbation; and unit 3(15.86–0 m depth, 7.5 kyr BP–present), dominated byyellow to olive gray silty clay and fine silt. In brief, units
1 and 2 are interpreted as TST which represent a transition from the nearshore subtidal environment to thenearshore shelf environment with rare tidal influence in
response to the postglacial sea-level rise. Unit 3 wasinterpreted as possibly an HST (Wang et al. 2014).
Interval 1 corresponds to lithostratigraphic unit 2 inaddition 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).

Discussion
Temporal changes in the provenance of fine detrital
quartz in the MD06-3040 core sediments

The EASM is characterized by a seasonal northwestward
migration of its precipitation front, of which the timing
and extent is controlled by migration of the WJ axis
(Sampe and Xie 2010). Such migration of the main precipitation area would also have occurred at longer timescales (Tada et al. 2016). The ESR signal intensity and
CI of quartz have been used to estimate the mixing ratios of the fine silt fraction of sediments from the different tributaries in the Yangtze drainage (Saito et al.
2017). Saito et al. (2017) suggested that if migration ofPage 8 of 15

the main precipitation area occurred within the Yangtze
River drainage, it would have been manifested aschanges in the provenance of SPM discharged from the
Yangtze River. If correct, the centennial-to-millennialscale variations in the main position of the EASM precipitation front could have been recorded as changes in
the provenance of the fine-silt-sized sediment corresponding to SPM discharged from the Yangtze River.
Saito et al. (2017) subdivided the entire drainage of the
Yangtze River into the upper Jinshajiang, western tributaries, northeastern tributaries, and southeastern tributaries, respectively, based on the ESR signal intensity and
CI of quartz of the fine silt fraction in each tributary(Fig. 4). The result enables discrimination of the sediment contributions from the upper–middle reaches(northwestern part of the drainage) versus the lower
reaches (southeastern part of the drainage) of the Yangtze River drainage.
The Yangtze River annually delivers a huge SPM load
into its estuarine system and the ECS, resulting in agreat 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; Liuet 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.
The proportion of clay, fine silt, and coarse silt fraction in the bulk samples of the MD06-3040 core during
the period 6.0–0 kyr on average is 17.3%, 64.5%, and18.1%, respectively. The geochemical compositions andclay mineral assemblages of MD06-3040 core sedimentssuggests that most of the terrigenous sediments originated from the Yangtze River (Zheng et al. 2010; Yanget al. 2015; Bi et al. 2017), with minor contribution from
Taiwan island during the entire Holocene (Fang et al.
2018). However, sediments deposited at the MD06-3040
site during the period from 7.5 to 6 kyr BP occasionallyshow quasi-bimodal grain size distributions, which issimilar to that of typical modern sediments from theinner margin of the mud belt (Liu et al. 2006). Thisquasi-bimodal grain size distribution of MD06-3040 coresediments can be explained by occasional contributionof coarse silt to sand sediments supplied from local rivers such as the Qiantang, Min, and Ou rivers. The ESR
signal intensity and the CI of quartz in the coarse silt
fraction (16–63 μm) of the MD06-3040 core sediments
also suggest potential contributions from these local rivers (Wang et al. 2014). Because the MD06-3040 core, inwhich fine silt is the relatively dominant faction derived
from the Yangtze River with lesser impacts from local
rivers and Taiwan island, is the longest continuous piston core collected from the central mud belt

Wang et al. Progress in Earth and Planetary Science(2020) 7:5

Page 9 of 15

Fig. 4 ESR signal intensity vs. CI plot of quartz in the fine silt fraction of the riverbed samples from the major tributaries of the Yangtze River from
Saito et al. (2017)

representing extensive sediment succession thus far, we
examined the provenance changes in the fine silt fraction of the MD06-3040 core sediments to reconstructspatiotemporal variability in the EASM precipitation
area (EASM front) within the Yangtze River drainage.
Figure 5 shows a comparison of the ESR signal intensity and CI of quartz in the fine silt fraction of MD063040 core sediments in intervals 2 to 5 to those of thefour major source areas in the modern Yangtze Riverdrainage 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 thefine 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 apredominant 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).
Regarding provenance changes, most of the samples
from interval 2 (from 6.0 to 4.1 yr BP, Fig. 5a) are plottedwithin or in between the areas of the southeastern tributaries, northeastern tributaries, and upper Jinshajiang(Fig. 5a), within an ESR signal intensity range of 7–24
and CI range of 8.0–8.9. The exception is one sample
characterized by a relatively high ESR signal intensity
and low CI, which possibly originated from local sources
such as the Qintang and Ou rivers (Wang et al. 2014).
Thus, we infer that the quartz in the fine silt fraction(4–16 μm) of the sediments deposited during this interval is a mixture of quartz derived from the southeasternand northeastern tributaries of the Yangtze River andthe upper Jinshajiang with a possible rare contribution
from the Qiantang and/or Ou rivers. Fang et al. (2018)
examined the clay mineralogy of the MD06-3040 core
and tentatively concluded that kaolinite content (%) represented the contribution of the Fujian-derived source,
illite content (%) was a contribution from the Taiwanesesource, and the contribution from the Yangtze River was
the sum of its smectite proportion (%) and illite content(%). They also suggested that most fine-grained (< 2 μm)
terrigenous sediments originated from the Yangtze
River, with a minor contribution from Taiwan islandand the nearby Zhejiang and Fujian provinces during theentire Holocene (Fang et al. 2018). However, using clay
mineral analyses of sediments from the MZ02 core retrieved from the mud belt area of the inner ECS, Liuet al. (2014) suggested that the increased strength of the
TWC might have played an important role in sediment

Wang et al. Progress in Earth and Planetary Science(2020) 7:5

Page 10 of 15

Fig. 5. a–d Comparison of the ESR signal intensity and CI of quartz in the fine silt fraction of MD06-3040 core sediments to those sedimentsfrom various parts of the modern Yangtze River drainage (Saito et al. 2017) for intervals 2 to 5 covering the last 6.0 kyr BP identified in this study.
The circles represent the average values of the ESR signal intensity and CI of quartz during each individual interval

dispersal and deposition on the inner shelf of the ECS
during the period 6.2–2.4 kyr BP, with a dominance ofgreater than 60% of the sediments transported from Taiwanese rivers (Liu et al. 2014). However, our result suggested that the fine silt faction was derived from thesoutheastern and northeastern tributaries of the Yangtze
River and the upper Jinshajiang with a possible rare contribution from the local Qiantang and/or Ou rivers during the period 6.0–4.2 kyr BP. We insist that different
grain sizes might show different results despite the same
original source due to hydrodynamic sorting and preferential mineral alteration (Clift et al. 2015). The previous
provenance studies focused on the clay-sized (< 2 μm)
fraction; we used the fine silt fraction (4–16 μm) whichis the predominate fraction of SPM discharged from the
Yangtze River and deposited at the MD06-3040 site.
The fine silt fractions of samples from interval 3 (from4.1 to 3.5 kyr BP, Fig. 5b) fall mainly within the area of thenortheastern tributaries with a relatively narrow ESR signal intensity range of 4–10 and CI range of 8.1–8.9. We

interpret that the quartz in the fine silt fraction of the sediments deposited during this interval is mostly derived
from the northeastern tributaries of the Yangtze River.
Most of samples from interval 4 (from 3.5 to 2.0 kyr
BP, Fig. 5c) fall within the areas of the western andnortheastern tributaries within an ESR signal intensity
range of 5–13 and CI range of 7.8–8.8. The exceptions
are two samples, one at 2.4 kyr BP and the other at
3.4 kyr BP, which fall near the southeastern tributaries.
Thus, we interpret that the quartz in the fine silt fractionof the sediments deposited during this interval is mainly
derived from the western and northeastern tributaries of
the Yangtze River.
Most of samples from interval 5 (from 2.0 to 0 kyr BP,
Fig. 5d) fall within the area of the northeastern tributaries within am ESR signal intensity range of 5–14 and a
CI range of 8.2–9.0. Some samples fall within the area ofthe upper Jinshajiang, suggesting potential contribution
from this area. We interpret that the quartz in the finesilt fraction of the sediments deposited during thisWang et al. Progress in Earth and Planetary Science(2020) 7:5

interval is mainly derived from the northeastern tributaries of the Yangtze River with a contribution from theupper Jinshajiang.
Hydrological data of a past 30-year time scale (1950–
1980) were collected from the upper, middle, and lower
Yangtze River (Chen et al. 2001) to examine the temporal and spatial distribution of discharge and sedimentload in the Yangtze drainage. Sediment load in the upperand middle Yangtze had been decreasing along with thedecreasing water discharge, which is possibly due towater diversion for intensive agriculture (Chen et al.
2001). Gao et al. (2019) analyzed the siltation and erosion state of the estuary-shelf depositional systems bycombining the spatial distribution of deposition rates,
types of vertical distribution profiles of 210Pb activity,and distribution of grain size composition in surficial
sediments and discussed the response intensity and timing of the depositional system in the Yangtze subaqueous delta and mud belt area. Their results showed thatthe abrupt reduction in the sediment discharge to theestuary disturbed the equilibrium among the estuarine,
coastal, and shelf depositional systems following operation of the Three Gorges Dam in 2003, modifying thesiltation–erosion balance and seabed sediment types(Gao et al. 2019). Regarding the Yangtze River-ECS
source-to-sink system, human impact during the late
Holocene, particularly recent decades, is of considerable
importance.
Changes in the heavy precipitation area within the
Yangtze River drainage during the last 6 kyrs

As mentioned in the introduction, SPM constitutes
greater than 95% of the sediment load discharged fromthe Yangtze River (Chen et al. 2001), and a strong positive relationship (R2 = 0.81) exists between the sedimentload and fresh water discharge (Xu et al. 2010), while
fresh water discharge of the Yangtze River could reflect
precipitation amounts in the drainage (Chen et al. 2014).
Thus, discharge of SPM from the Yangtze River shouldreflect precipitation amounts in the drainage. Based on
this, we hypothesized that changes in the SPM provenance reflect changes in the distribution of highprecipitation areas. Based on temporal changes in the
ESR signal intensity in the MD06-3040 core, we interpret that the ESR signal intensity increase during theperiod 6.0–4.1 kyr BP suggests retreat of the EASM precipitation front southeast in the Yangtze drainage (aweak EASM). In contrast, the ESR signal intensity decrease during the period 3.5–2.0 kyr BP suggests penetration of the EASM precipitation front northwestward(an enhanced EASM). The slight increase in the ESR signal intensity during the period 2.0–0 kyr BP suggests retreat of the EASM precipitation front toward thesoutheast in the Yangtze drainage again.

Page 11 of 15

EASM precipitation variability during the Holocene
has been discussed based on various reconstructions
using a variety of proxies. For example, Nagashima et al.
(2013) reported the relationship between spatial variations in EASM precipitation and the westerly jet (WJ)
path over East Asia during the Holocene using the provenance of eolian dust in the Japan Sea sediment core DGC-6 via ESR signal intensity and CI of quartz. The variation pattern of the eolian dust provenance manifested
as changes in the ESR signal intensity of the quartz in
the Japan Sea sediment core D-GC-6 (Fig. 6b) is similar
to that of our ESR signal intensity changes in the MD063040 core (Fig. 6a). Namely, migration of the WJ southward during the period 6.0–3.5 kyr BP and northwestward during the period 3.5–2.0 kyr BP inferred fromchanges in the eolian dust provenance in the sedimentsof the Japan Sea correlated well with our results of
EASM precipitation front movement with the retreat of
the EASM precipitation front southeastward during theperiod 6.0–4.1 kyr BP as well as the deepest northwestward penetration during the period 3.5–2.0 kyr BP (anenhanced EASM). This agreement argues for coupling
between the WJ and EASM precipitation front at a millennial time scale.
Kubota et al. (2010, 2015) reported changes in δ18Osw,
an indirect indicator of SSS, calculated from the Mg/Caand δ18O of the planktonic foraminifera Globigerinoides
ruber in KY07-04-01 core sediments retrieved from thenorthern end of the ECS, which they interpreted asreflecting changes in the summer SSS due to changes infresh water discharge from the Yangtze River thatreflected changes in EASM precipitation in South China
during the Holocene. Their higher δ18Osw peaks representing the lower Yangtze River discharge events at 6.1,
5.1 3.5, 2.1, and 0.8 kyr BP seem to correspond to our ESR
signal intensity minima of the MD06-3040 core at 5.8, 5.1,
3.5, 2.0, and 0.6 kyr BP (Fig. 6c), suggesting more contribution from the northwestern area of the Yangtze drainage during these events. This idea is further supported bystalagmite δ18Oc values that show positive peaks during
these periods suggesting lower EASM precipitation inSouth China (Dykoski et al. 2005; Hu et al. 2008, Fig. 6d,e). Furthermore, EASM precipitation front movement in
the Yangtze River drainage was inferred from the ESR signal intensity of quartz in the fine silt faction of the MD063040 core sediments, and water discharge from the Yangtze River reconstructed by Kubota et al. (2015) synchronously changed at multi-centennial scale during the periods
6–5.1, 5.1–4.1, 4.1–3.5, 3.5–2.1, and 2.1–0.8 kyr BP(Fig. 6c). This observation implies that northwestward
penetration of the EASM front (the increase in contribution from the northwestern area of the Yangtze drainage)at a multi-centennial time scale may have caused a significant decrease in local summer precipitation and water

Wang et al. Progress in Earth and Planetary Science(2020) 7:5

Page 12 of 15

Fig. 6 Comparison of temporal change patterns in between several EASM proxies. a ESR signal intensity in the fine silt fraction (4–16 μm) of
MD06-3040 core sediments (this study). b ESR signal intensity in the fine silt fraction (4–20 μm) of D-GC-6 core sediments (Nagashima et al. 2013).
c δ18Osw, an indicator of the sea surface salinity (SSS), at the KY07-04-01 site in the northern ECS during the Holocene based on paired analysesof Mg/Ca and δ18O of planktonic foraminifera (Kubota et al. 2010, 2015), where the black thin line represents the 3-point moving average. d δ18O
record of a stalagmite from Heshang Cave (Hu et al. 2008). e δ18O record of a stalagmite from Dongge Cave D4 (Dykoski et al. 2005). The
calibrated 14C dates of the MD06-3040 and KY07-04-01 cores are presented with 2σ errors on the top of the figures

Wang et al. Progress in Earth and Planetary Science(2020) 7:5

discharge from the southeastern Yangtze River drainage
that exceeded the increase in the water discharge from thenorthwestern Yangtze River drainage.
Based on geological evidence including lake levels,
pollen assemblages, and magnetic susceptibility of a loesspaleosol sequence together with numerical modeling
results, An et al. (2000) summarized the spatiotemporal
distribution of summer monsoon precipitation during the
Holocene and proposed an “asynchronous Holocene
optimum” hypothesis assuming a stepwise latitudinal shiftof the maximum precipitation from northwestern China
during the early Holocene to southeastern China during
the late Holocene in response to progressively decreased
summer insolation. This interpretation is different fromour results of the ESR signal intensity of the MD06-3040
core, suggesting higher summer precipitation in thesoutheastern part of the Yangtze River drainage during
the period 6.0–4.1 kyr BP. Previous studies may have been
unable to obtain similar results because they were subject
to uncertainties in the age model, an asynchronous response pattern from a number of different proxies andpoor spatial coverage, particularly in the broad Yangtze
drainage.
However, our ESR signal intensity results from theMD06-3040 core suggest that southeastward retreat ofthe precipitation front (a weaker EASM) and higher
summer precipitation in the southeastern Yangtze Riverdrainage during the period 6.0–4.1 kyr BP is attributable
to weaker EASM convection (Zhou et al. 2009) rather
than enhanced EASM intensity as advocated by previous
works. Based on numerical meta-analysis of 92 proxy records (72 sites) of moisture and/or temperature changes
in monsoonal central Asia, the maximum moisture levels
in southeastern China occurred with a southeast–northwest moisture gradient during the period 6–4 kyr BP(Wang et al. 2010). High pollen percentages of evergreen
Quercus and Castanopsis as well as extremely low percentages of coniferous taxa suggested extensive growthof warm-temperate evergreen broadleaf forests supporting the prevalence of a wet climate in southeastern
China during the middle Holocene (Zhao et al. 2017).
Sedimentological and geochemical results of the core recovered from the Hangbu delta plain of Chaohu Lake inthe lower reaches of the Yangtze drainage suggested alake expansion from 7.4 to 4.3 kyr BP (Shi 2006). Theseprevious studies are consistent with our interpretationthat southeastward retreat of the precipitation front (aweaker EASM) and higher summer precipitation in thesoutheastern Yangtze River drainage occurred during
the period 6.0–4.1 kyr BP. Lake shrinkage occurred witha cold and dry sub-stage in the lower reaches of the
Yangtze River drainage during the period 4.3–2.7 kyr BP(Shi 2006), while flood events in the upper reach of the
Hanjiang River occurred during the periods 4.3–3.8 andPage 13 of 15

3.6–3.0 kyr BP (Tan et al. 2018), and frequent abrupt
flood events occurred in the upper Yangtze drainage
during the period 4.0–3.6 kyr BP (Jia et al. 2017). These
results are also consistent with our interpretation ofnorthwestward penetration of the EASM precipitation
front during the period 4.1–2.0 kyr BP.

Conclusion
We examined temporal changes in the provenance of
detrital quartz in the fine silt fraction of sediments from
the MD06-3040 core retrieved from the mud belt on the
inner shelf of the ECS, which are considered as representing the SPM derived from the Yangtze River. We
used the ESR signal intensity and CI of quartz in the finesilt fraction as provenance tracers to monitor shifts inthe main location of EASM precipitation (EASM front)
within the Yangtze River drainage. Our results suggest
northwest–southeast oscillations of the EASM precipitation front with the deepest northwestward penetration(an enhanced EASM) during the period 3.5–2.0 kyr BP
and a southeastward retreat (a weak EASM) during theperiods 6.0–4.1 and 2.0–0 kyr BP. This interpretation
does not agree with the prevailing view based on stalagmite δ18Oc in southeastern China, suggesting an early
Holocene EASM maximum and gradual decrease in
EASM intensity thereafter (Wang et al. 2001, 2005).
Higher summer precipitation occurred in the southeastern Yangtze River drainage during the periods 6.0–
4.1 kyr BP and 2.0–0 kyr BP due to weaker EASM convection and consequent southeastward retreat of the
precipitation front rather than an enhanced EASM intensity, which is consistent with the high precipitation
and abrupt climatic events in the lower Yangtze drainage
and southeastern China.
Abbreviations
CDW: Changjiang Diluted Water; CI: Crystallinity index; EASM: East Asiansummer monsoon; ECS: East China Sea; ESR: Electron spin resonance;
HST: Highstand systems tract; ISM: Indian summer monsoon; JCC: Jiangsu
Coastal Current; KC: Kuroshio Current; MFS: Maximum flooding surface;
QC: Quartz content; SPM: Suspended particulate matter; TS: Transgressive
surface; TST: Transgressive systems tract; TWC: Taiwan Warm Current;
WJ: Westerly jet; XRD: X-ray diffraction; YS: Yellow Sea; YSWC: Yellow Sea
Warm Current; ZFCC: Zhejiang-Fujian Coastal Current

Acknowledgements
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 inGuangzhou, Chinese Academy of Sciences (CAS), and Peking University forlaboratory 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 Natureand Science, and two reviewers for constructive comments and suggestions
greatly improving this manuscript.

Wang et al. Progress in Earth and Planetary Science(2020) 7:5

Authors’ contributions
RT proposed the topic and conceived and designed the study. KW carriedout the experiment, analyzed the data, and wrote the manuscript. HZ, TI, BZ,
and KS collaborated with the corresponding author in the development of
the manuscript. All authors read and approved the final manuscript.
Funding
This study was supported by the Japan Society for the Promotion of Science(JSPS) KAKENHI Grant Number 23221002 to Ryuji Tada, jointly supported by
the Second Tibetan Plateau Scientific Expedition and Research (STEP)(2019QZKK0704), the Strategic Priority Research Program of Chinese
Academy of Sciences (XDB26020301), and National Natural Science
Foundation of China (NSFC) (U1902208, 41991323) to Hongbo Zheng, by the
NSFC (41977378) to Bin Zhou, and by the JSPS grants JPMXS05R2900001 and
19H05595 to Masanobu Yamamoto.
Availability of data and materials
Available data are attached as Table 1. Please contact the corresponding
author for further data requests.
Competing interests
The authors declare that they have no competing interests.
Author details
1
Department of Earth and Planetary Science, The University of Tokyo, Tokyo,
Japan. 2Yunnan Key Laboratory of Earth System Science, Yunnan University,
Kunming, China. 3Planetary Exploration Research Center (PEPC), Chiba
Institute of Technology, Chiba, Japan. 4Faculty of Environmental Earth
Science, Hokkaido University, Sapporo, Japan. 5School of Earth Sciences andEngineering, Nanjing University, Nanjing, China.
Received: 4 May 2019 Accepted: 27 December 2019

References
An ZS, Porter SC, Kutzbach JE, Wu XH, Wang SM, Liu XD, Li XQ, Zhou WJ (2000)
Asynchronous Holocene optimum of the East Asian monsoon. Quat Sci Rev
19:743–762
Bi L, Yang SY, Zhao Y, Wang ZB, Dou YG, Li C, Zheng HB (2017) Provenancestudy of the Holocene sediments in the Changjiang (Yangtze River) estuary
and inner shelf of the East China sea. Quat Int 441:147–161
Chang P, Isobe A (2003) A numerical study on the Changjiang diluted water in
the Yellow and East China Seas. J Geophys Res 108(C9):3299. https://doi.org/
10.1029/2002JC001749
Chen C, Beardsley RC, Limeburner R, Kim K (1994) Comparison of winter andsummer hydrographic observations in the Yellow and East China Seas andadjacent Kuroshio during 1986. Cont Shelf Res 14(7–8):909–929
Chen FH, Xu QH, Chen JH, Birks HJB, Liu JB, Zhang SR, Jin LY, An CB, Telford RJ,
Cao XY, Wang ZL, Zhang XJ, Selvaraj K, Lü HY, Li YC, Zheng Z, Wang HP,
Zhou AF, Dong GH, Zhang JW, Huang XZ, Bloemendal J, Rao ZG (2015) East
Asian summer monsoon precipitation variability since the last deglaciation.
Sci Rep 5:11186. https://doi.org/10.1038/srep11186
Chen J, Wu XD, Finlayson BL, Webber M, Wei TY, Li MT, Chen ZY (2014) Variability
and trend in the hydrology of the Yangtze River, China: annual precipitation
and runoff. J Hydrol 513:403–412
Chen ZY, Li JF, Shen HT, Wang ZH (2001) Yangtze River of China: historicalanalysis of discharge variability and sediment flux. Geomorphology. 41:77–91.
https://doi.org/10.1016/S0022-1694(02)00028-8
Cheng H, Edwards RL, Wang YJ, Kong XG, Ming YF, Gallup CD, Kelly MJ, Wang
XF, Liu WG (2006) A penultimate glacial monsoon record from Hulu Caveand two-phase glacial terminations. Geology. 34:217–220
Clift PD, Harff J, Wu J, Qui Y (2015) River-dominated shelf sediments of East Asian
Seas geological society special publication, p 429
Deng B, Zhang J, Wu Y (2006) Recent sediment accumulation and carbon burial
in the East China Sea. Glob Biogeochem Cycles 20:GB3014. https://doi.org/10.
1029/2005GB002559
Ding YH, Chan CL (2005) The East Asian summer monsoon: an overview.
Meteorog Atmos Phys 89:117–142
Dykoski CA, Edwards RL, Cheng H, Yuan DX, Cai YJ, Zhang ML, Lin YS, Qing JM,
An ZS, Revenaugh J (2005) A high-resolution, absolute-dated Holocene andPage 14 of 15

deglacial Asian monsoon record from Dongge Cave, China. Earth Planet Sci
Lett 233:71–86. https://doi.org/10.1016/j.epsl.2005.01.036
Fang J, Liu Z, Zhao Y (2018) High-resolution clay mineral assemblages in the
inner shelf mud wedge of the East China Sea during the Holocene:
implications for the East Asian Monsoon evolution. Sci China Earth Sci 61:
1316–1329. https://doi.org/10.1007/s11430-017-9208-1
Feigl FJ, Fowler WB, Yip KL (1974) Oxygen vacancy model for the E1 center in
SiO2. Solid State Commun 14:225–229
Gao JH, Shi Y, Sheng H, Kettnerc AJ, Yang Y, Jia JJ, Wang PY, Li J, Chen YN, Zou
XQ, Gao S (2019) Rapid response of the Changjiang (Yangtze) River and East
China Sea source-to-sink conveying system to human induced catchment
perturbations. Mar Geol 414:1–17
Hu C, Henderson GM, Huang J, Xie S, Sun Y, Johnson KR (2008) Quantification of
Holocene Asian monsoon rainfall from spatially separated cave records. Earth
Planet Sci Lett 266:221–232
Isozaki Y (2009) Characterization of eolian dust and its sources in the Tarim Basinand their temporal changes during Plio-Pleistocene based on the ESR signal
intensity and crystallinity index of quartz. Ph. D. thesis, The University ofTokyo, Tokyo, Japan
Jia JT, Ma CM, Zhu C, Guo TH, Xu JJ, Guan HC, Zeng MX, Huang M, Zhang Q(2017) Depositional evidence of palaeofloods during 4.0-3.6 ka BP at the
Jinsha site, Chengdu Plain, China. Quat Int 440:78–89
Kajita H, Kawahata H, Wang K, Zheng HB, Yang SY, Ohkouchi N, Utsunomiya M,
Zhou B, Zheng B (2018) Extraordinary cold episodes during the midHolocene in the Yangtze delta: interruption of the earliest rice cultivating
civilization. Quat Sci Rev 201:418–428
Klug HP, Alexander LE (1974) X-ray diffraction procedure, 2nd edn, p 966
Kubota Y, Kimoto K, Tada R, Oda H, Yokoyama Y, Matsuzaki H (2010)
Variations of East Asian summer monsoon since the last deglaciation
based on Mg/Ca and oxygen isotope of planktic foraminifera in thenorthern East China Sea. Paleoceanography. 25:PA4205. https://doi.org/
10.1029/2009PA001891
Kubota Y, Kimoto K, Tada R, Uchida M, Ikehara K (2019) Millennial-scale variabilityof East Asian summer monsoon inferred from sea surface salinity in thenorthern East China Sea (ECS) and its impact on the Japan Sea during
Marine Isotope Stage (MIS) 3. Prog Earth Planetary Sci 6:39
Kubota Y, Tada R, Kimoto K (2015) Changes in East Asian summer
monsoon precipitation during the Holocene deduced from a
freshwater flux reconstruction of the Changjiang (Yangtze River) basedon the oxygen isotope mass balance in the northern East China Sea.
Clim Past 11:265–281
Liu JP, Li AC, Xu KH, Velozzi DM, Yang ZS, Milliman JD, DeMaster DJ (2006)
Sedimentary features of the Yangtze River-derived along-shelf clinoform
deposit in the East China Sea. Cont Shelf Res 26:2141–2156
Liu JP, Xu KH, Li AC, Milliman JD, Velozzi DM, Xiao SB, Yang ZS (2007) Flux andfate of Yangtze River sediment delivered to the East China Sea.
Geomorphology. 85:208–224
Liu SF, Shi XF, Fang XS, Dou YG, Liu YG, Wang XC (2014) Spatial and temporal
distributions of clay minerals in mud deposits on the inner shelf of the East
China Sea: implications for paleoenvironmental changes in the Holocene.
Quat Int 349:270–279
Liu XT, Li AC, Jiang DJ, Lu J, Huang J, Wan SM (2018) Provenance discriminationof sediments in the Zhejiang-Fujian mud belt, East China Sea: implications
for the development of the mud depocenter. J Asian Earth Sci 151:1–15
Maher BA (2008) Holocene variability of the East Asian summer monsoon from
Chinese cave records: a re-assessment. The Holocene 18:861–866
Maher BA, Thompson R (2012) Oxygen isotopes from Chinese caves: records notof monsoon rainfall but of circulation regime. J Quat Sci 27:615–624
Milliman JD, Meade HR (1983) World-wide delivery of sediment to the oceans. J
Geol 91(1):1–21
Milliman JD, Shen H, Yang Z, Meade HR (1985) Transport and deposition of river
sediment in the Changjiang estuary and adjacent continental shelf. Cont
Shelf Res 4(1–2):37–45
Milliman JD, Syvitski J (1992) Geomorphic/tectonic control of sediment discharge tothe ocean: the importance of small mountainous rivers. J Geol 100(5):525–544
Murata K, Norman M (1976) An index of crystallinity for quartz. Am J Sci 276:
1120–1130
Nagashima K, Asahara Y, Fumi Y, Takeuchi F, Harada N, Toyoda S, Tada R (2012)
Contribution of detrital materials from the Yukon River to the continental
shelf sediments of the Bering Sea based on the electron spin resonancesignal intensity and crystallinity of quartz. Deep-Sea Res II 61-64:145–154

Wang et al. Progress in Earth and Planetary Science(2020) 7:5

Nagashima K, Tada R, Tani A, Sun Y, Isozaki Y, Toyoda S, Hasegawa H (2011)
Millennial-scale oscillations of the westerly jet path during the last glacial
period. J Asian Earth Sci 40:1214–1220
Nagashima K, Tada R, Tani A, Toyoda S, Sun Y, Isozaki Y (2007) Contribution ofaeolian dust in Japan Sea sediments estimated from ESR signal intensity andcrystallinity of quartz. Geochem Geophys Geosyst 8(2):Q02Q04. https://doi.
org/10.1029/2006GC001364
Nagashima K, Tada R, Toyoda S (2013) Westerly jet-East Asian summer monsoon
connection during the Holocene. Geochem Geophys Geosyst 14:5041–5053.
https://doi.org/10.1002/2013GC004931
Qin YS (1979) A study on sediment and mineral compositions of the sea floor of
the East China Sea. Oceanic Selections 2(2):130–142
Qin YS, Zhao YY, Chen LR, Zhao SL (1987) Geology of the East China Sea. China
Science Press, Beijing
Ramsey CR, Lee S (2013) Recent and planned developments of the program
OXCAL report
Reimer PJ, Bard E, Bayliss A, Beck JW, Blackwell PG, Ramsey CB, Buck CE, Cheng H,
Edwards RL, Friendrich M, Grootes PM, Guilderson TP, Haflidason H, Hajdas I,
Hatte C, Heaton T, Hoffmann D, Hogg AG, Hughen KA, Kaiser KF, Kromer B,
Manning SW, Niu M, Reimer RW, Richards DA, Scott EM, Southon JR, Staff RA,
Turney CSM, Van der Plicht J (2013) IntCal13 and Marine13 radiocarbon age
calibration curves 0-50,000 years cal BP. Radiocarbon 55:1869–1887
Saito K, Tada R, Zheng H, Irino T, Luo C, He M, Wang K, Suzuki Y (2017) ESR signal
intensity of quartz in the fine-silt fraction of riverbed sediments from the
Yangtze River: a provenance tracer for suspended particulate matter. Prog
Earth Planetary Sci 4:4. https://doi.org/10.1186/s40645-017-0118-9
Sampe T, Xie SP (2010) Large-scale dynamics of the Meiyu-baiu rainband:
environmental forcing by the Westerly jet. J Clim 23(1):113–134. https://doi.
org/10.1175/2009jcli3128.1
Shi Y X (2006) Sedimentary and geochemical records of climate andenvironmental change for the Chaohu-Hangbu River Catchment in Anhui
Province. Ph.D. Thesis, Guangzhou Institute of Geochemistry, Chinese
Academy of Sciences, Guangzhou, China (in Chinese with English abstract)
Sun Y, Chen H, Tada R, Weiss D, Lin M, Toyoda S, Yan Y, Isozaki Y (2013) ESR
signal intensity and crystallinity of quartz from Gobi and sandy deserts inEast Asia: implication for tracing Asian dust provenance. Geochem Geophys
Geosyst 14:2615–2627. https://doi.org/10.1002/GGGE.20162
Sun Y, Tada R, Chen J, Chen H, Toyoda S, Tani A, Isozaki Y, Nagashima K,
Hasegawa H, Ji JF (2007) Distinguishing the sources of Asian dust based onelectron spin resonance signal intensity and crystallinity of quartz. Atmos
Environ 41:8537–8548
Tada R, Zheng H, Clift PD (2016) Evolution and variability of the Asian monsoon
and its potential linkage with uplift of the Himalaya and Tibetan Plateau.
Prog Earth Planetary Sci 3:4. https://doi.org/10.1186/s40645-016-0080-y
Tan LC, Cai YJ, Cheng H, Edwards LR, Gao YL, Xu H, Zhang HW, An ZS (2018)
Centennial to decadal scale monsoon precipitation variations in the upper
Hanjiang River region, China over the past 6650 year. Earth Planet Sci Lett
482:580–590
Toyoda S, Hattori M (2000) Formation and decay of the E1 center and of its
precursor. Appl Radiat Isot 52:1351–1356
Toyoda S, Ikeda M (1991) Thermal stabilities of paramagnetic defect and impurity
centers in quartz: basis for ESR dating of thermal history. Geochem J 25:437–
445
Toyoda S, Naruse T (2002) Eolian dust from the Asian deserts to the JapaneseIsland since the last glacial maximum: the basis for the ESR method,transactions. Jpn Geomorphological Union 23(5):811–820
Wang B, Lin H (2002) Rainy season of the Asian-Pacific summer monsoon. J Clim
15:386–396
Wang B, Wu RG, Lau KM (2002) Interannual variability of the Asian summer
monsoon: contrasts between the Indian and the Western North Pacific–East
Asian monsoons. J Clim 14:4073–4090
Wang K, Zheng H, Tada R, Irino T, Zheng Y, Saito K, Karasuda A (2014)
Millennial-scale East Asian Summer monsoon variability recorded in grain
size and provenance of mud belt sediments on the inner shelf of the East
China Sea during mid-to late Holocene. Quat Int 349:79–89
Wang MJ, Zheng HB, Xie X, Fan DD, Yang SY, Zhao QH, Wang K (2011) A 600year flood history in the Yangtze River drainage: comparison between a
subaqueous delta and historical records. Chin Sci Bull 56:188–195
Wang YB, Liu XQ, Herzschuh U (2010) Asynchronous evolution of the Indian andEast Asian summer monsoon indicated by Holocene moisture patterns inmonsoonal central Asia. Earth Sci Rev 103(3):135–153

Page 15 of 15

Wang YJ, Cheng H, Edwards RL, He Y, Kong X, An Z, Wu J, Kelly MJ, Dykoski CA,
Li X (2005) The Holocene Asian monsoon: links to solar changes and North
Atlantic climate. Science 308:854–857
Wang YJ, Cheng H, Edwards RL, Wu JY, Shen CC, Dorale JA (2001) A highresolution absolute-dated Late Pleistocene monsoon record from Hulu Cave,
China. Science 294:2345–2348
Xu J, Yang D, Yi Y, Lei Z, Chen J, Yang W (2008) Spatial and temporal variation of
runoff in the Yangtze River basin during the past 40 years. Quat Int 186:32–
42
Xu K, Milliman J, Xu H (2010) Temporal trend of precipitation and runoff in major
Chinese Rivers since 1951. Glob Planet Chang 73(3–4):219–232
Yang SY, Wang ZB, Dou YG, Shi XF (2015) Major sinks of the Changjiang (Yangtze
River)-derived sediments in the East China Sea during the late quaternary.
Geol Soc Lond, Spec Publ 429:137–152
Yang ZS, Guo ZG, Wang ZX (1992) Basic pattern of transport of suspended
matter from the Yellow Sea and East China Sea to the eastern deep seas.
Acta Oceanol Sin 14(2):81–90 in Chinese, with English summary
Yim SY, Wang B, Liu J, Wu ZW (2014) A comparison of regional monsoon
variability using monsoon indices. Clim Dyn 43:1423–1437. https://doi.org/10.
1007/s00382-013-1956-9
Zhang Q, Xu CY, Zhang Z, Chen YD, Liu CL, Lin H (2008) Spatial and temporalvariability of precipitation maxima during 1960-2005 in the Yangtze Riverbasin and possible association with large-scale circulation. J Hydrol 353:215–
227. https://doi.org/10.1016/j.jhydrol.2007.11.023
Zhao L, Ma CM, Leipe C, Long TW, Liu KB, Lu HY, Tang LY, Zhang Y, Wagner M,
Tarasov PE (2017) Holocene vegetation dynamics in response to climatechange and human activities derived from pollen and charcoal records fromsoutheastern China. Palaeogeogr Palaeoclimatol Palaeoecol 485:644–660
Zheng Y, Kissel C, Zheng HB, Laj C, Wang K (2010) Sedimentation on the innershelf of the East China Sea: magnetic properties, diagenesis and paleoclimate
implications. Mar Geol 268(1–4):34–42
Zhou TJ, Gong DY, Li J, Li B (2009) Detecting and understanding the multidecadal variability of the East Asian summer monsoon-recent progress andstate of affairs. Meteorol Z 18:455–467

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