Liu et al. Progress in Earth and Planetary Science
https://doi.org/10.1186/s40645-020-00349-9(2020) 7:30

RESEARCH ARTICLE

Progress in Earth andPlanetary Science

Open Access

Reconstruction of monsoon evolution insouthernmost Sumatra over the past 35 kyrand its response to northern hemisphereclimate changes
Shengfa Liu1,2* , Hui Zhang1, Xuefa Shi1,2*, Min-Te Chen1,2,3, Peng Cao1, Ziye Li4, Rainer Arief Troa5, Rina Zuraida6,
Eko Triarso5 and Hendrizan Marfasran7,8

Abstract
Reconstruction of monsoon evolution in the tropical Indian Ocean and evaluation of its influence on large-scaleocean circulation and sea-air interaction processes can help us understand climate driving mechanisms. Herein, weused a gravity core SO184-10043 to present the marine sedimentary record from the southernmost Sumatra,
spanning the past 35 kyr. The age model is well constrained by 12 accelerator mass spectrometry (AMS)
radiocarbon dates determined in mixed planktic foraminifera. We also measured sediment grain size and major andtrace elements to reconstruct the variations in hydrodynamic conditions and chemical weathering intensity. These
data were then used to reveal the evolution of the northwest (Indonesian) monsoon system over the past 35 kyr.
The results showed that both monsoon current and chemical weathering coincided with summer insolation in the
Northern Hemisphere and responded to glacial-interglacial climate changes in the northern Atlantic. Higher grainsize values of sensitive components, increased chemical index of alteration (CIA), and Ba/Sr ratios, together withlower CaO/MgO ratios, reflect a stronger monsoon current and chemical weathering during the late marine isotope
stage 3 and Holocene. Higher intensity of chemical weathering might be attributed to a stronger northwest
monsoon carrying warm and moist air from the Asian continent to Indonesian waters. Lower values of sensitive
components, CIA, and Ba/Sr, along with higher CaO/MgO values, reveal a weaker monsoon current and lower
intensity of chemical weathering during the last glaciation-deglaciation phase, which was controlled by a weakermonsoon system. At a millennial timescale, cold events occurred during the following intervals: 30–26 ka BP,
Heinrich Stadial 1 (HS1; 18–15 ka BP), Last Glacial Maximum (LGM; 23–18 ka BP), Younger Dryas (YD; 11–10 ka BP),and 8.2 ka BP. The same cold events were identified from core SO184-10043, indicating a perfect match withclimatic cooling in the Northern Hemisphere. We also observed periodicities of ~ 7.9 ka, 3.0–3.1 ka, 2.2–2.3 ka, and ~1.0 ka in our core records. These periodicities are coincident with solar-induced climate changes and support the
hypothesis that monsoon evolution in the tropical Indian Ocean during the late Pleistocene coincided with theclimate change in the Northern Hemisphere.
Keywords: Late Pleistocene, Hydrodynamic conditions, Chemical weathering, Indian monsoon, Paleoclimate,
Sumatra* Correspondence: liushengfa@fio.org.cn; xfshi@fio.org.cn
1
Key Laboratory of Marine Geology and Metallogeny, First Institute of
Oceanography, Ministry of Natural Resources, Qingdao 266061, China
Full list of author information is available at the end of the article© The Author(s). 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License,
which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give
appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate ifchanges were made. The images or other third party material in this article are included in the article's Creative Commonslicence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commonslicence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain
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Liu et al. Progress in Earth and Planetary Science(2020) 7:30

Introduction
Monsoonal climate dominates over the northern Indian
Ocean, and marine records have revealed its close relationship with global climate changes during the late
Pleistocene (Mohtadi et al. 2014; Li et al. 2016). Coastal
waters of Sumatra span the equator in the northeastern
Indian Ocean and are influenced by seasonal rhythms,
i.e., by the southeast Malaysian-Australian monsoon andnorthwest Indonesian monsoon. These monsoon systems
show a biennial alternation between central Asia andAustralia (Tomczak and Godfrey 2001; Lückge et al.
2009). During boreal winter (from November to March),
the northwest monsoon carries warm and moist air fromthe Asian continent, causing heavy rainfall over Indonesia
in response to the southward migration of the Intertropical Convergence Zone (ITCZ) (Qu et al. 2005). In contrast, precipitation in Indonesia is relatively low between
June and September, when the dominant southeast monsoon carries warm and dry air from Australia (Gingele
et al. 2002; Spooner et al. 2005; Lückge et al. 2009). Driven
by the dominant seasonal monsoon system, the ocean currents along the southernmost coast of Sumatra are highly
dynamic in relation to monsoon winds. The northwest
monsoon drives the South Java Current (SJC), which is adownstream branch of the Indian Monsoon Current(IMC), and the Equatorial Counter Current (EEC) fromthe north (Wyrtki 1961; Wijffels et al. 1996). During thesoutheast monsoon season, the SJC weakens and may
even turn back to the west, feeding the South Equatorial
Current (SEC) (Wyrtki 1962; Murgese et al. 2008).
To date, most of the monsoon records in the Indian
Ocean come from the western side of the South Asian
Peninsula, where the abundance of Globigerina bulloides
represents the intensity of upwelling and serves as an alternative indicator of the rise and fall of the Indian monsoon (Prell and Curry 1981; Kroon et al. 1991;
Sijinkumar et al. 2011). In the northeast Indian Ocean,the Bay of Bengal and the Andaman Sea have no evident
upwelling activity, but river runoff supplies profuse
amounts of freshwater and debris (Kroon et al. 1991;
Clemens et al. 1991; Prell et al. 1992; Colin et al. 1999;
Dahl and Oppo 2006). Great monsoon changes are often
indicated by changes in salinity caused by increased
freshwater input, which is reflected in the oxygen isotope values of the planktonic foraminiferal shells (Cullen
1981; Rashid et al. 2007; Mohtadi et al. 2014; Li et al.
2016). A number of recent studies of sediment coresfrom the southwestern Sumatra showed that upwelling
along the islands of Indonesia is significant, and thechanges in coastal productivity levels are controlled bymonsoon (Li et al. 2016) and the Indonesian Throughflow (ITF) (Xu et al. 2017). The seasonally reversing,open-ocean monsoon currents control the Sumatra
coastal sedimentary processes, which are still poorly

Page 2 of 13

understood, especially its hydrodynamic conditions andchemical weathering. Moreover, a reliable age model has
yet to be put forward.
In this study, we present new sedimentological andgeochemical records of well-dated sedimentary archives
from the southernmost Sumatra waters spanning thepast 35 kyr. Several hydrodynamic conditions and chemical weathering processes are discussed herein to reveal
the evolution of the monsoon system during the late
Pleistocene. Our goal is to understand the relationshipbetween the local monsoon system, the Northern Hemisphere, and global climate changes.

Material and methods
Gravity core SO184-10043 (07° 18.57′ S, 105° 03.53′ E)with a total length of 382 cm was collected from a water
depth of 2171 m at the continental margin off the southernmost Sumatra waters (Fig. 1). The core was taken on
a cruise of R/V “Sonne” in August 2005. The core lithology was described in detail after opening the core tube.
A total of 74 samples were obtained every 5 cm along
the length of the core with a sample depth of 1 cm.
The pre-treatment samples for the grain size analysis
were treated with 15 mL of the H2O2 solution (30%) toremove organic matter. Afterward, the samples werebathed in 5 mL of the HCl solution (3 mol/L) for 24 h toremove calcareous cements and shell material. All samples were fully desalted and dispersed before the measurements. The sediment grain size was analyzed by
Malvern Mastersizer 2000 (UK) at the Key Laboratory ofMarine Geology and Metallogeny, Ministry of Natural
Resources (MNR), China. Malvern Mastersizer 2000 allows measurements of particle size distribution in therange of 0.02–2000 μm, with a resolution of 0.01 Φ. The
error based on repeated measurements was determined
to be less than 3%.
Geochemical elements were identified within the sediment samples using an inductively coupled plasma optical emission spectrometer (ICP-OES, Thermo Fisher
Scientific iCAP 6300) and inductively coupled plasma
mass spectrometer (ICP-MS, Thermo Fisher Scientific X
Series II) at the Key Laboratory of Marine Geology and
Metallogeny, MNR, China. The homogenized sediment
samples were dried in an oven with a temperature of lessthan 50 °C and were ground to the mesh size of less than
200 mm using an agate mortar. Next, approximately
0.05 g of each sample was dissolved in 1.5 mL of HNO3
and 1.5 mL of HF at 190 to 200 °C for 48 h, respectively.
Then, 50 g of the liquor was prepared for the measurements. The SiO2, Al2O3, Fe2O3, MgO, CaO, Na2O, K2O,
TiO2, P2O5, and MnO contents were measured using
ICP-OES, while the Cu, Ba, Sr, V, Zn, Cr, Zr, Pb, Co,
and Ni contents were quantified using ICP-MS. The
standard sediment reference materials (Chinese National

Liu et al. Progress in Earth and Planetary Science(2020) 7:30

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Fig. 1 Location of the sediment core SO184-10043 (red star) with seasonality of surface currents, SST, and salinity in the eastern Indian Ocean(revised from Mohtadi et al. 2014). Seasonal changes in SST (color shading), salinity (dashed lines; psu), and surface currents (arrows) in the study
area during boreal summer (top) and winter (bottom). The meridional Ekman transport (ME) is also indicated with arrows. Seasonal SST isaveraged for the period between 2002 and 2010 (http://oceancolor.gsfc.nasa.gov/cgi/l3). Salinities are averaged for the period between 1960
and 2004

Standard GSD-9 and GSD-10) and parallel samples wereanalyzed for quality control. Statistical results showedthat relative standard deviations (RSDs) were less than
3% for major elements and less than 5% for trace elements, compared to the previous studies.
AMS14C dating was carried out on 12 samples of
mixed planktonic foraminifera (~ 15 mg) (Table 1). Agedating was conducted at the Woods Hole Oceanographic Institution, Massachusetts, USA. Raw AMS14C
dates were converted to calendar ages using the CALIB
7.1 and Marine13 calibration curves (Reimer et al. 2013).
Local reservoir age ΔR of 42 ± 70 years was chosen for
calibration from the online marine reservoir correction
database (https://calib.qub.ac.uk/marine) based on themarine reservoir effect of 362 years observed in the Indian Ocean (Southon et al. 2002).

Results
Lithology

Visual inspection of core SO184-10043 indicates thatthe sediments are composed of olive to dark olive-grayclayey silt. The sediment color, composition, sedimentary structures, and grain size gradually change along thelength of the core. For instance, the sediment color
changes from olive in the top section (0–105 cm, including some missed length at the top), to olive-gray in the
middle section (105–280 cm), and dark olive-gray in thebottom section (280–382 cm). Shell debris and foraminifera were observed at specific intervals (i.e., 34 and
270–370 cm), which coincided with the presence ofcoarser sandy material. Moreover, two significant tephra
layers were identified at 10–12 and 370–382 cm,
respectively.

Table 1 AMS14C dating of SO184-10043 determined from planktonic foraminifer Globigerinoides ruber shells, and the14C ages wereconverted to calendar age by using CALIB7.1 (Reimer et al. 2013)
Lab ID

Depth (cm)Raw AMS 14 C data

Calibrated age (year B.P.)

Mean calibrated age (year B.P.)

Corrected error

OS-112616

25–262100 ± 25

1534–1714

1624

± 90

OS-112617

30–31

2380 ± 20

1867–2050

1959

± 92

OS-112618

40–41

2790 ± 20

2349–2575

2462

± 113

OS-112619

95–96

4800 ± 25

4875–5123

4999

± 124

OS-112621

105–106

5110 ± 25

5315–5490

5403

± 88

OS-112622

165–166

7880 ± 30

8217–8373

8295

± 124

OS-112625

180–1818310 ± 35

8697–8945

8821

± 124

OS-112626

230–231

11,950 ± 55

13,280–13,449

13,365± 85

OS-112627

240–241

12,950 ± 50

14,488–15,000

14,744± 256

OS-112628

290–291

18,350 ± 100

21,521–21,854

21,688± 167

OS-112629

310–311

20,200 ± 120

23,607–23,961

23,784± 177

OS-112630

350–351

27,700 ± 310

30,995–31,378

31,187± 192

Liu et al. Progress in Earth and Planetary Science(2020) 7:30

The changes in core lithology indicate variations in
sedimentary environments through time. Considering
the current sea level, presence of shells, whelks, and foraminifera, which are characteristics of the marine environment (Qin et al. 1987; Liu et al. 2014), the sedimentsof core SO184-10043 were likely deposited in a marine
environment. Overall, the sediments are distinguished byfiner grain size and negligible compositional changes,
suggesting a relatively stable depositional environment.
Chronology

Planktic foraminiferal shell samples were collected from
12 sedimentary layers to build the age model for the sediments of core SO184-10043. The dating results showedthat the core sediments were accumulated over the past
35 kyr. The sedimentation rates increased gradually up
to the present moment and varied between 5 and 29 cm/
kyr, with an average of 10 cm/kyr (Table 1). A rapid increase in sedimentation rates is attributed to the flooding of the Sunda Strait in response to global sea-levelrise, which might have caused intensified erosion anddownslope transport of terrigenous material to the sea(Li et al. 2016). Based on this version of the age model, asampling interval of 1 cm provided an average resolutionof 100 years in this study.
Grain size

We measured the variations in grain size for the sediments of core SO184-10043, including the mean grainsize, sorting coefficient, skewness, and kurtosis (Fig. 2).
Consistent with the lithology of core SO184-10043, grain
size characteristics were described as follows:
The bottom section (280–382 cm) is predominantly
characterized by silt (73.22%) with a lesser amount ofPage 4 of 13

sand (~ 12.63%) and clay (20.14%). The sand fraction increases towards the top of the section along with themean grain size, with an average of 5.88 Φ, influenced
by the composition of sand and clay. The sorting coefficient is an indicator of the degree of sorting in response
to hydrodynamic conditions and averages 2.01. It showsno significant changes in the section, indicating relatively
poor sorting. Skewness and kurtosis present similar
trends and decrease upwards with insignificant
fluctuations.
The middle section (105–280 cm) is the most variable.
All of the parameters show noticeable changes. Silt fraction is predominant (64.62%), while sand fraction
reaches its most representative value in this section(48.15%) at a depth of ~ 206 cm. The mean grain size
also showed a similar trend with the silt, has an averagevalue of 5.95 Φ, and is consistent with stronger bottomhydrodynamic conditions. The sorting coefficient varies
from 1.70 to 2.21, reflecting various sedimentary environments. Skewness decreases upwards from − 0.78 to
1.62, indicating a complex sedimentary composition.
Kurtosis reaches its highest value in this section (~ 2.82).
The upper section (0–105 cm) represents an opposite
trend from the bottom section, where the average valuesof sand, silt, and clay fractions are determined to be
15.34%, 64.95%, and 19.72%, respectively. Silt remains
the main fraction and reaches its lowest value at a depthof ~ 60 cm. Sand and clay fractions show a similar distribution trend in this section, being the most variable between 50 and 70 cm of depth. All of the grain-size
parameters show substantial changes. The mean grain
size gradually decreases upwards, with an average valueof 5.8 Φ, and is consistent with stronger bottom hydrodynamic conditions. The sorting coefficient, skewness,

Fig. 2 Vertical distributions of grain size parameters of core SO184-10043; red dashed lines represent the boundary of three sections

Liu et al. Progress in Earth and Planetary Science(2020) 7:30

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and kurtosis start to vary from a depth of 105 cm to the
top of the section.
Geochemistry

Major and trace element components are presented inTable 2. Among 10 major elements measured for the entire profile, SiO2 is the dominant component, averaging
65.72%, followed by Al2O3 with an average of 14.33%
and CaO with an average of 8.59%. These three elements
amount to more than 85% of all the elements present.
Other elemental proportions include 4.95% of TFe2O3,
3.50% of Na2O, 1.66% of K2O, 1.87% of MgO, 0.61% of
TiO2, 0.11% of P2O5, and 0.05% of MnO. Trace element
concentration also fluctuates, ranging from 5.20 × 10−6
to 556.64 × 10−6 in the order of Ba > Sr > Zr > V > Pb >Zn > Cu > Cr > Ni > Co.
Throughout the length of the core, most elements display similar or reciprocal distribution patterns (Fig. 3).
Three horizons (0–12.0 cm, 200–222 cm, and 350–370cm) serve as important boundaries, where the elemental
composition changes. As such, SiO2, MnO, Na2O, P2O5,
and Zr reach relatively high values at these horizons,
whereas Al2O3, MgO, Ba, Cr, Co, and Ni are characterized by the lowest content. Other portions of the coredemonstrate little compositional changes.

Discussion
Hydrodynamic condition

Sediment grain size is widely used to reconstruct past
sedimentary environments and paleoclimate evolution. It
also serves as a direct proxy of hydrodynamic conditions(Xiao et al. 2006; Cao et al. 2015). However, the transportation of marine sediments depends on a multitude of factors, which result in selective transportation and variablesediment compositions under different hydrodynamic
conditions (Xiao et al. 2005; Liu et al. 2010). As marine
sediments usually form mixtures of sediments in complex
sedimentary environments and their constituent

components can be delivered from different provenances,meaningful fraction selection from the bulk grain-size distribution is required to infer their significance for specificdepositional conditions. In recent years, several mathematical and statistical methods have been developed, suchas the Weibull function (Sun et al. 2002), end-member
modeling of grain-size distributions (Stuut et al., 2002a, b;
Prins et al. 2007), and analysis of grain-size populations
with environmentally sensitive terrigenous components(Boulay et al. 2002; Sun et al. 2003). All these methods
have been widely used to extract typical fractions to reveal
a hydrodynamic evolution in the marginal sea settings.
Herein, we applied a mathematical method “grain size vs.
standard deviation” to extract the environmentally sensitive
components, which reflect the variability in grain size in asample group using each grain-size class. High standard deviation values tend to indicate high-frequency variability ingrain-size classes in a sample group and vice versa. We
used a standard deviation vs. grain-size class plot to identify
the number of grain-size components and size range ofeach grain-size component in a sample group, where thecomponents are closely related to the sedimentary environment (Stuut et al., 2002a, b; Xiang et al. 2006). We calculated the standard deviation of each grain-size grade using
the terrigenous components in 74 samples of core SO18410043 and defined two components sensitive to the sedimentary environment: 3.28–15.63 μm and 52.6–105.1 μm,
with the boundary at 26.28–31.25 μm (Fig. 4).
Previous studies have shown that two sensitive components in a sedimentary environment are characteristics
of continental margins and adjacent coastal areas controlled by normal hydrodynamic conditions (e.g., coastal
currents, warm currents) and unstable hydrodynamic
conditions (e.g., storm currents, earthquakes, waves)(Xiao et al. 2005; Xiang et al. 2006). Each of the two
grain-size classes represents a population of grains withthe highest variability through time (Xiao et al. 2006),
while the boundary of these two populations isTable 2 Composition of major and trace elements of sediment from core SO184-10043
Major
element

Maximum value(%)

Minimum value(%)

Average value
(%)

Trace
element

Maximum value(10−6)

Minimum value(10−6)

Average value(10−6)

SiO2

65.72

39.00

47.30

Ba

556.64288.63430.48

Al2O3

16.42

11.04

14.33

Cr

57.42

7.01

39.78

CaO

15.66

2.50

8.59

Sr

525.90162.54338.00TFe2O3

6.91

2.96

4.95

V

122.0032.00

104.30

K2O

2.85

1.27

1.66

Zn

103.51

69.15

88.67

MgO

2.42

0.93

1.87

Zr

229.7991.13

119.24

MnO

0.12

0.03

0.05

Co

14.91

5.20

12.03

Na2O

5.12

2.82

3.50

Ni

38.75

7.11

30.62

P2O5

0.23

0.09

0.11

Cu

79.46

9.04

28.27

TiO2

0.96

0.40

0.61

Pb

104.43

10.55

24.45

Liu et al. Progress in Earth and Planetary Science(2020) 7:30

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Fig. 3 Vertical distributions of major and trace elements of core SO184-10043; gray belts (at the depth of 0–12.0 cm, 200–222 cm, and 350–370cm) represent the layers with largest geochemical fluctuation

Fig. 4 Grain size vs. standard deviation curve of core SO184-10043

Liu et al. Progress in Earth and Planetary Science(2020) 7:30

characterized by the lowest standard deviation value andimplies negligible changes within this proportion of thegrain-size population in the siliciclastic fraction. Hence,
we can infer that these two grain-size populations ofcore SO184-10043 were mainly controlled by coastal
currents driven by monsoon systems and by wave currents driven by storms or tsunami. Considering that thenorthwest (Indonesian) monsoon current is stronger than thesoutheast Malaysian-Australian monsoon current (Fig. 1), wesuggest that the finer population (sensitive component I 3.28–
15.63 μm) was mainly transported by the stronger Indonesianmonsoon current. A large-amplitude fluctuation of the mean
grain size and content further confirms its response being sensitive to sedimentary variation (Fig. 5). The coarser grain-size
population (sensitive component II 52.6–105.1 μm) shows aslight temporal change that might reflect a stronger current.
Regardless, as fraction II appears continuously in the core, its
origin may be related to normal sedimentation driven by alocal wave system. Consequently, sensitive component I ischosen to reflect the evolution of the hydrodynamic conditions in this study. As shown in Fig. 5, we were able to distinguish between the glacial-interglacial responses ofhydrodynamic intensity within the study area. During the latemarine isotope stage (MIS) 3 and Holocene, a higher mean
grain size of sensitive component I is interpreted to reflect astronger monsoon current, probably associated with a stronger northwest monsoon reconstructed by paired SST andδ18Osw (Govil and Naidu 2011). Limited by the quantity andresolution of the analyzed data, we obtained less detailed core
information for MIS 3. However, the resolution for the Holocene portion of the core was not compromised. The mean

Page 7 of 13

grain size of sensitive component I changed from 8 to 8.8 μm,
revealing incremental hydrodynamic conditions coherent withthe record from the Andaman Sea and the Bay of Bengal(Cao et al. 2015; Li et al. 2019), where larger sediment fractions could be transported from the adjacent continent to thesea. On the contrary, the mean grain-size value of sensitive
component I was lower during the last glaciation-deglaciation
phase, revealing weak hydrodynamic conditions, controlled byweaker monsoon systems (Mohtadi et al. 2014; Gebregiorgis
et al. 2016). The lowest value of sensitive component I was observed at 15 ka BP and coincided with the weakest monsoon
record in the northeastern Indian Ocean (Rashid et al. 2007;
Govil and Naidu 2011). On a millennial time scale, a numberof significant grain-size fluctuations were identified by examining a sensitive grain-size curve, such as the Heinrich Stadial 1(HS1), B/A, and Younger Dryas (YD) deglaciation events,
which corresponded to larger climate and environmental
changes (Li et al. 2016).
Chemical weathering intensity

Elemental geochemistry composition is related to sediment source, grain size, and dynamic conditions, which
are essential to reveal a sedimentary environment andclimate intensity in the past epochs (Tao et al. 2006).
Climatic and environmental changes contribute to theconcentration, transportation, and deposition of certain
elements (Young and Nesbitt 2001). Thus, the content
and assemblage of specific elements may be a good indicator of the past climates and depositional environments(Liu et al. 2010), especially for the weathering andpaleoclimatic processes recorded in sediments (Yan et al.

Fig. 5 Content and mean grain size of two sensitive components from core SO184-10043

Liu et al. Progress in Earth and Planetary Science(2020) 7:30

2002; Tao et al. 2006; Zhao et al. 2008; Liu et al. 2011).
Chemical weathering appears to drive relatively mobile
elements, such as Na, Ca, and Sr, to migrate in theiraqueous form (Tao et al. 2006), while conservative elements, such as Ti and Al, remain stable in the sediments(Yang et al. 2006). The differential mobility allows us to
use the ratios of these elements in order to infer past climatic conditions. The following ratios of elements are
the most commonly used in the vicinity of the Asian
marginal seas: Al2O3/Na2O, K2O/Na2O, CaO/K2O,
CaO/MgO, CaO/Sr, and Rb/Sr (Young and Nesbitt
2001; Tao et al. 2006; Ye et al. 2010; Liu et al. 2011). In
addition, the Chemical Index of Alteration (CIA =[Al2O3/(Al2O3 + CaO* + Na2O + K2O)] × 100) (Nesbitt
et al. 1980; Nesbitt and Young 1989, 1996; Delaney et al.
1993; Nyakairu and Koeberl 2000; Young and Nesbitt
2001; Yan et al. 2002) is frequently used to estimate theintensity of weathering (Yang et al. 2004), where CaO* is
CaO in a silicate fraction calculated by the Honda andShimizu’s formula: [CaO* = 0.35 × 2(Na2O%)/62] (Nesbitt and Young 1982).
The Sumatra offshore waters are situated within theseasonal features of the following monsoon systems: thesoutheast Malaysian-Australian monsoon and northwest
Indonesian monsoon. These monsoon systems determine Sumatra’s regional precipitation and temperaturepatterns. In this study, we utilized the CIA, CaO/MgO,
and Ba/Sr proxies for the reconstruction of chemical
weathering intensity to deduce the monsoon evolution
process further. These geochemical proxies are regarded
as synchronous with changes in the oxygen isotope
stages since the last glacial period, reflecting rapid sediment deposition and the influence of climate (Fig. 6).

Fig. 6 Distributions of CIA, CaO/MgO, and Ba/Sr from core SO184-10043

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Four phases were identified from the core bottom to top
as follows: MIS 3, last glaciation, deglaciation, and theHolocene. The geochemical proxies during MIS 3 andthe Holocene showed similar features, with higher ratios
of CIA and Ba/Sr and lower ratios of CaO/MgO, indicating increased weathering and erosion rates in the sourceareas, dominated by a warm and humid climate during
these periods. Higher precipitation and temperatures
tend to be accompanied by active chemical weathering(Yang and Li 1999). Our results are supported by theδ18O values of planktonic foraminifera and SST reconstruction in the Andaman Sea (Rashid et al. 2007), where
intense precipitation and high temperatures were reported for MIS 3 and the Holocene (Marzin et al. 2013).
Such climatic conditions caused higher river runoff,reflected in a high Ba/Ca ratio from the planktonic foraminifera G. sacculifer shells (Gebregiorgis et al. 2016;
Sijinkumar et al. 2016). On the contrary, lower CIA and
Ba/Sr values and higher CaO/MgO ratios during the lastglaciation-deglaciation indicate weaker chemical weathering intensity, controlled by low precipitation and decreased temperatures. The reduced chemical weatheringand erosion rates were also reported from the Andaman
Sea during MIS 2 (Colin et al. 1998; Miriyala et al.
2017). Similar to the sensitive grain-size proxy, the decreasing CaO/MgO, and increasing CIA, Ba/Sr during
the deglaciation period also changed sharply, revealing awarm and moist climate generated after the last glaciation. Some minor variations in the chemistry proxies
were identified from the following intervals: 12.5–12,
17–15, and 34–32 ka BP. These variations imply the instability of chemical weathering intensity on a millennial
time scale. Similar trends were found for the sea surface

Liu et al. Progress in Earth and Planetary ScienceFig. 7 (See legend on next page.)(2020) 7:30

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Liu et al. Progress in Earth and Planetary Science(2020) 7:30

Page 10 of 13(See figure on previous page.)
Fig. 7 Paleoclimatic proxies and referenced data plotted as a function of age (ka B.P.): (a) mean grain size of sensitive component I from core
SO184-10043 (this study); (b) CaO/MgO from core SO184-10043 (this study); (c) CIA from core SO184-10043 (this study); (d) Ba/Sr from core
SO184-10043 (this study); (e) records of speleothem δ18O from Dongge Cave in the southern China (Yuan et al. 2004) and Hulu Cave in theeastern China (Wang et al. 2001); (f) records of ice core (NGRIP) δ18O from Greenland (Andersen et al. 2006; Rasmussen et al. 2006); (g) integrated
summer insolation variations at 30° N over June, July, and August (Berger 1978). Grey, yellow, and orange bars in this figure represent global cold
events recorded in our core SO184-10043

temperature and seawater salinity proxies (Mohtadi et al.
2014; Li et al. 2016).
Paleoclimate reconstruction for the past 35 kyr

Monsoonal climate dominates over the northern Indian
Ocean. Its close relationship with global climate changes
during the late Pleistocene was revealed by marine sedimentary records (Schulz et al. 1998, Mohtadi et al., 2014).
The results of our study show that both monsoon current
and chemical weathering coincide with the glacialinterglacial changes in the Northern Hemisphere. During
the late MIS 3 and Holocene, higher values of sensitive
grain size, increased CIA, and Ba/Sr ratios, as well as lower
CaO/MgO ratios, reflect a stronger monsoon current andheightened chemical weathering intensity, which werelikely connected to a stronger northwest monsoon thatcarried warm and moist air from the Asian continent toIndonesia. Evidence from land precipitation (Wang et al.
2001), seawater salinity (Li et al. 2016), sea surface
temperature (Mohtadi et al. 2014), and paleoprodutivity(Xu et al. 2017) supports the suggested stronger northwest
monsoon. High temperature and increased precipitation
were able to accelerate weathering, erosion, and the terrestrial influx into the sea from the surrounding territories,
whereas a monsoon current was characterized by higher
energy that transported coarser sediments to the continental shelf. During the last glaciation-deglaciation phase,lower sensitive grain size, decreased CIA, and Ba/Sr ratios,
as well as higher CaO/MgO ratios, reveal a weaker monsoon current and diminished chemical weathering intensity, which were likely controlled by a weaker monsoon
system. Low precipitation and decreased temperaturesduring MIS 2 reduced the transport of the chemical
weathering and erosion products to the core location. We
also identified other processes for this period. For instance, the monsoon system was at its weakest point during the last glaciation, while a strong rebound occurredfrom 16 to 11 ka BP. Seawater δ18O was measured fromthe nearby cores, SO189-119KL and SO189-39KL, andpresented significantly decreased values (Mohtadi et al.
2014), which coincides with increased summer insolationin the Northern Hemisphere (Li et al. 2016).
The movement of rainfall belt in a monsoon area is controlled by the displacement of the ITCZ, which, in turn, isprincipally driven by orbital changes in solar insolation(Fleitmann et al. 2007; Goodbred 2003; Philander et al.

1996; Wang et al. 2005; Xie and Saito 2001). The almost
synchronous changes in the indices of sensitive component I and chemical weathering seem to be modulated by
the orbital-scale variations in 30° N July insolation, suggesting a prominent response to the Northern Hemisphere climate changes (Fig. 7). The highest CIA and Ba/
Sr ratios and the lowest CaO/MgO values were noted for
10–8 ka BP. The highest insolation values appeared between 12 and 11 ka BP. The opposite trend was observed
when insolation reached its minimum at 25 ka BP (Berger
and Loutre 1991; Laskar et al. 2004). Therefore, we inferthat orbital-scale changes in insolation influenced theglacial-interglacial paleoclimate changes over the past 35
kyr in the southernmost Sumatra waters.
On a millennial timescale, cold events occurred during thefollowing intervals: HS1 (18–15 ka BP), Last Glacial Maximum (LGM; 23–18 ka BP), YD (11–10 ka BP), and 8.2 ka
BP. The same events were identified in core SO184-10043,
indicating their co-occurrence with the Northern Hemisphere cold events. Hydrodynamic conditions and chemical
weathering intensity were weak during these events, whichwere observed in ice core records from the northern Atlantic(Andersen et al. 2006; Rasmussen et al. 2006). It should bepointed out that abnormal weakening of hydrodynamic conditions and chemical weathering from 30 to 26 ka BP was recorded in our core sediments. This period coincides with areduced-precipitation event in the Indian Ocean (Ali et al.
2015; Sijinkumar et al. 2016), revealing the predominant roleof monsoon systems in the sedimentary processes.
We used a power spectrum analysis (PSA) to investigate the periodicity of climate records and its possible
driving forces in core SO184-10043. The CIA and MgO/
CaO time series were analyzed using REDFIT35 (Schulz
and Mudelsee 2002), which have been shown to have ahigh performance in PSA for unevenly spaced timeseries. PSA of the CIA and MgO/CaO time series
showed maximum power at periodicities centered at
3.0–3.1 ka, 2.2–2.3 ka, and ~ 1.0 ka, all of which arecharacteristic of solar activity (Stuiver et al. 1995; Wanget al. 2005) (Fig. 8). Though the interpretation of our results is ultimately limited by the marine sediment coreresolution and age uncertainty of the AMS14C dating,our results suggest a possible influence of changes insolar activity on the Sumatra maritime climate on multidecadal and multi-centennial scales (Hong et al. 2001;
Xiao et al. 2006). These data further support theLiu et al. Progress in Earth and Planetary Science(2020) 7:30

Page 11 of 13

Fig. 8 Power spectrum analysis of CIA and MgO/CaO proxies from core SO184-10043

monsoon evolution in the tropical Indian Ocean during
the Late Pleistocene and its dependence on the Northern
Hemisphere climate changes.

Conclusions
We conducted a paleoclimatic reconstruction for core
SO184-10043 collected from the southernmost coast of
Sumatra using sedimentological, geochemical, and elemental proxies in order to reconstruct the monsoon evolution and its response to the Northern Hemisphereclimate changes.
On a glacial-interglacial timescale, both monsoon
current and chemical weathering coincided with summer insolation in the Northern Hemisphere and showeda clear response to the glacial-interglacial changes.
Higher values of sensitive grain size, CIA, and Ba/Sr, as
well as lower CaO/MgO ratios, indicated a stronger
monsoon current and chemical weathering intensity inthe late MIS 3 and Holocene. Such climate conditions
were likely controlled by a stronger northwest monsoon
that carried warm and moist air from the Asian continent to Indonesia. Lower sensitive grain size, CIA, and
Ba/Sr ratio with higher CaO/MgO values revealed aweaker monsoon current and diminished chemical
weathering intensity during the last glaciationdeglaciation phase, which was predominantly controlled
by a weaker monsoon system.
On a millennial timescale, in core SO184-10043, wewere able to identify a number of global cold events,
such as the one at 30–26 ka BP, HS1 (18–15 ka BP),LGM (23–18 ka BP), YD (11–10 ka BP), and 8.2 ka BP,

which occurred simultaneously with the Northern
Hemisphere cold events. We also applied PS and identified periodicities of ~ 7.9 ka, 3.0–3.1 ka, 2.2–2.3 ka, and~ 1.0 ka in our core records. We related these periodicities to solar-induced climate changes, which further
support our findings of the monsoon evolution in thetropical Indian Ocean in the late Pleistocene and its coincidence with the Northern Hemisphere climatechanges.

Supplementary information
Supplementary information accompanies this paper at https://doi.org/10.
1186/s40645-020-00349-9.
Additional file 1. Data.
Acknowledgements
We would like to thank the crew of R/V “Sonne” for sample collection andalso all the Scientists on board on SO-184 PABESIA Cruise. We thank the Director of Marine Research Center, Agency of Research and Human Resources
for Marine and Fisheries of the Ministry of Marine Affairs and Fisheries of the
Republic of Indonesia (KKP), Dr. Budi Sulistiyo (former Director of Marine andCoastal Resources, Research Agency—KKP), Dr. Susilohadi (former Director of
Marine Geological Institute-KESDM), Dr. Haryadi Permana (former Director of
the Research Center for Geotechnology—LIPI) for their support of the initiation “BENTHIC” joint research project in 2013–2015. We thank Prof. Wahyoe
S. Hantoro who allowed us to analyze the core sample. We also thank Prof.
Xuchen Wang from the Ocean University of China and Woods Hole Oceanographic Institution for AMS14C measurements, Aimei Zhu, Jingjing Gao, andYing Zhu from First Institute of Oceanography, MNR, for grain size and elements analysis.
Authors’ contributions
SFL participated in the data analysis and research idea design andcompleted the main work of the paper. HZ participated in the analysis of theelements and drafted the manuscript. XFS conceived of the study andLiu et al. Progress in Earth and Planetary Science(2020) 7:30

participated in its design and coordination. MTC participated in its designand coordination and helped to draft the manuscript. PC participated in thedesign of the study and drafted the manuscript. ZYL participated in theanalysis of sediment particle size data and drafted the manuscript. RAT
participated in paleoclimate analysis. RZ participated in the applicability
analysis of research indicators. ET completed the spectrum analysis. HM
participated in the establishment of the chronological framework. All authors
read and approved the final manuscript.
Funding
This work was supported by the National Programme on Global Change and
Air-Sea Interaction (GASI-GEOGE-06-03), the National Nature Science Foundation of China (U1606401), China–Indonesia marine research cooperation project “BENTHIC”: “Benthic Records of Marine Environment, Climate, andEcosystem in the Eastern Indian Ocean since the Last Deglaciation”, andTaishan Scholar Program of Shandong.
Availability of data and materials
The dataset supporting the conclusions of this article can be found in the
supplementary files.
Competing interests
The authors declare that they have no competing interests.
Author details
1
Key Laboratory of Marine Geology and Metallogeny, First Institute of
Oceanography, Ministry of Natural Resources, Qingdao 266061, China.
2
Laboratory for Marine Geology, Qingdao National Laboratory for Marine
Science and Technology, Qingdao 266061, China. 3Institute of Earth Sciences,
Taiwan Ocean University, Keelung 20224, Taiwan. 4College of Marine
Geosciences, Ocean University of China, Qingdao 266100, China. 5Marine
Research Center, Agency of Research and Human Resources for Marine andFisheries, Ministry of Marine Affairs and Fisheries, Jakarta 14430, Indonesia.
6
Center for Geological Survey, Geological Agency, Ministry of Energy andMineral Resources, Bandung 40122, Indonesia. 7Research Center for
Geotechnology, Indonesia Institute of Sciences, Bandung 40135, Indonesia.
8
Graduate program in Earth Sciences, Faculty of Earth Sciences andTechnology, Institute of Technology Bandung, Bandung 40132, Indonesia.
Received: 23 April 2020 Accepted: 3 July 2020

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