Diatom-based reconstruction of summer sea-surface salinity in theSouth China Sea over the last 15 000 years

HUI JIANG, MADS F. KNUDSEN, MARIT-SOLVEIG SEIDENKRANTZ, MEIXUN ZHAO, LONGBIN SHA AND LIHUA RAN

Jiang, H., Knudsen, M. F., Seidenkrantz, M.-S., Zhao, M., Sha, L. & Ran, L. 2014 (January): Diatom-basedreconstruction of summer sea-surface salinity in the South China Sea over the last 15 000 years. Boreas, Vol. 43,pp. 208–219. 10.1111/bor.12031. ISSN 0300-9483.

We present a new reconstruction of summer sea-surface salinity (SSS) over the past 15 000 years based on adiatom record from piston core 17940, located on the northern slope of the South China Sea (SCS). Thereconstructed diatom-based summer SSS values for the modern period are in accord with instrumental observa-tions of summer SSS in the area. Here, the modern summer SSS is primarily controlled by river runoff, inparticular from the Pearl River. The reconstruction presented in this study shows that the summer SSS variedbetween 33.3 and 34.2 psu over the past 15 000 years. The long-term summer SSS trend closely followed the trendof the orbitally controlled solar insolation at 20°N, suggesting that orbital forcing was the dominant driver ofchanges in summer SSS in this area. Comparisons to speleothem δ18O data and studies of surface hydrography inthe region suggest that changes in solar insolation affected the summer SSS through changes in the East AsianMonsoon and sea-level changes associated with the last deglaciation. Univariate spectral analyses indicate thatcentennial-scale oscillatory variations in summer SSS were superimposed on the long-term trend. During thedeglacial period (c. 12 000–9000 cal. a BP), the dominant periodicity was centred around 230–250 years, whereasa ∼350-year oscillation dominated in the period 2200–4500 cal. a BP. The balance of evidence suggests that thesecentennial-scale changes in summer SSS may have been driven by solar-induced changes in the East AsianMonsoon, but further evidence is needed to firmly establish this relationship.

Hui Jiang (hjiang@geo.ecnu.edu.cn) and Longbin Sha, Key Laboratory of Geographic Information Science, EastChina Normal University, Shanghai 200062, China; Mads F. Knudsen and Marit-Solveig Seidenkrantz, Centre forPast Climate Studies, Department of Geoscience, Aarhus University, DK-8000 Aarhus C, Denmark; Meixun Zhao,Key Laboratory of Marine Chemistry Theory and Technology of the Ministry of Education, Ocean University ofChina, Qingdao 266100, China; Lihua Ran, The Second Institute of Oceanography, SOA, Hangzhou 310012, China;received 21st February 2013, accepted 30th May 2013.

In recent years, central and eastern China have experi-enced severe droughts whereas other parts of Asia havereceived extreme amounts of rainfall during themonsoon season, leading to frequent floods in denselypopulated areas (e.g. IPCC 2007). The monsoon activ-ity is also known to exert a strong influence on surfacecirculation in the western Pacific (e.g. Wyrtki 1961).Rainfall, and especially monsoon intensity, thus repre-sents a highly significant component of the climatesystem, which is the main reason why we need toimprove our understanding of this phenomenon. Pastvariations in the hydrological cycle may be studiedbased on e.g. speleothems, loess sequences, lake levels,etc. (e.g. Huang et al. 2000; Dykoski et al. 2005; Morrillet al. 2006; Guan et al. 2007; Long et al. 2010).However, another approach is to assess the river runoffreaching the sea by studying changes in sea-surfacesalinity (SSS; Zong et al. 2006, 2010). Such study offersthe potential to define the combined effect of monsoon-driven variations in both precipitation and ocean-surface circulation patterns.

In this context, the South China Sea (SCS; Fig. 1) isparticularly important as it receives river runoff from alarge catchment area including that of the Pearl River,the second largest river in China with respect to waterdischarge of 320 km3 a−1 and a modern catchment areaof about 442 600 km2 (Fig. 2). This river runoff is not

only a significant indicator of regional precipitationand monsoonal activity, but the resulting variations inSSS also strongly influence regional ocean circulation,and thus potentially also the oceanography and climateof the western Pacific region. Detailed knowledge ofvariations in the SSS of the SCS is thus essential forobtaining a better understanding of the temporal vari-ability of both the East Asian monsoon (EAM) andwestern Pacific ocean currents.

Studies of foraminifera (Pflaumann & Jian 1999),radiolarians (Chen & Tan 1997), pollen (Sun et al.1999), corals (Yu et al. 2005), and planktonic for-aminiferal δ18O (Wei et al. 2003) have been carried outto reconstruct millennial- to centennial-scale climatechanges in the SCS area. Some high-resolution studiesfocusing on Holocene climate and precipitationchanges have also been performed in this area (Sun &Li 1999; Higginson et al. 2003). Wang et al. (1999)calculated changes in local SSSs by subtracting pastvariations in sea-surface temperatures and globalice volume from the planktonic δ18O signal ofGlobigerinoides ruber (white) to study variations in theAsian monsoon intensity.

In the SCS, the Pacific and Indian Ocean waterscarry oceanic planktonic diatoms into the SCS,whereas the less saline coastal current combined withriver discharge, mainly from the Pearl River, result in

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DOI 10.1111/bor.12031 © 2013 The AuthorsBoreas © 2013 The Boreas Collegium

the deposition of brackish and freshwater species in theregion (Jiang et al. 2004). A calibration data set is avail-able from the western Pacific marginal seas, which con-sists of diatom data from surface sediments and fourenvironmental variables, including summer and wintersea surface temperature (SST) and SSS (Huang et al.2009a). Detrended correspondence analysis (DCA)suggested unimodality in the species data (gradient

length >4.0 standard deviation units of species turno-ver). Hence, canonical correspondence analysis (CCA)was used to determine if each variable has a uniqueinfluence on the diatom distribution. For this purpose,the variance inflation factor (VIF) of each variable wascalculated (ter Braak & Smilauer 2002). The VIF valueof all four variables is less than 20, suggesting that themulticolinearity amongst these four variables is low.

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Summer sea-surface salinity in the South China Sea, the last 15 000 years 209BOREAS

The results of the forward selection of the environmen-tal variables and associated Monte Carlo permutationtests of the statistical significance of each variablefurther show that all of the four variables above areindividually significant (p=0.001, 999 permutations).Marginal effects indicated the variability of eachexplanatory variable without considering other envi-ronmental factors. Conditional effects denoted theinfluence of each variable after removing the confound-ing effect of one or more of the other covariables.Amongst them, winter SST and summer SSS capturemost of the canonical variance (winter SST, 0.36;summer SSS, 0.34; summer SST, 0.13; winter SSS,0.09), suggesting that summer SSS is one of the twomost important environmental factors controlling thedistribution of diatoms in the surface sediments(Huang et al. 2009a). Consequently, changes in diatomassemblages may reflect variations in the summer SSSof the SCS, which underlines the potential for obtain-ing an independent record of past changes in SSS basedon a new proxy from this region.

Here, we present a diatom-based summer SSS recordof the Late Pleistocene to Holocene from a marinesediment core (piston core 17940) located in the north-ern SCS. The objective of this paper is twofold, first toquantitatively reconstruct Holocene summer SSS in thenorthern SCS, and secondly to discuss possible forcing

mechanisms underlying the summer SSS variability andthe possible relation to Asian monsoon intensity.

Regional setting

The SCS is a large, semi-enclosed marginal sea ofthe West Pacific (Fig. 1), which covers an area of3.5×106 km2 with an average water depth of about1250 m. The deep central basin, with maximum depthsexceeding 5000 m, represents 52% of the total area of theSCS. It is bordered by two broad shelves with an averagewater depth of less than 200 m. The SCS lies within theinfluence of the West Pacific Warm Pool and the EastAsian Monsoon, and its location between the EastAsian landmass and the West Pacific makes it particu-larly sensitive to both terrestrial and marine climaticchanges. It receives river runoff from a large catchmentarea including that of the Pearl River (Fig. 2) to thenorth and the Mekong River in the south.

The surface circulation of the SCS is strongly gov-erned by the seasonally reversing monsoonal regime(Wyrtki 1961). When the NE monsoon wind pre-vails during the Northern Hemisphere winter, ananticlockwise gyre is formed with strong coastal cur-rents flowing south along the western margin ofthe SCS. During summer, the SCS is dominated by a

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Fig. 2. The modern distribution of summer sea surface salinity (psu) in front of the Pearl River mouth (after Sarnthein et al. 1994).

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generally clockwise current system driven by the SWmonsoon. This results in warm Indian Ocean surfacewater flowing northwards over the Sunda Shelf into theSCS, whereas SCS water flows into the western Pacificand the East China Sea (ECS) through the Bashi Straitand the Taiwan Strait, respectively.

The modern SSSs in the SCS range between 32.8 and34.2 psu during winter, but enhanced precipitationlinked to summer monsoonal activity lowers the SSSduring the summer months throughout the entire basin.Owing to the inflow of low-salinity water from riversystems, the lowest summer SSS values are found in thenorthern and southern parts of the basin (32.3–33.0 psu), whereas the highest summer value is found inthe central part of the basin (around 33.6 psu) (Guoet al. 2004).

Material and methods

Diatom data and diatom-based summer SSStransfer function

Diatom data were extracted from piston core 17940(20°07′N, 117°23′E; Fig. 1). This 13.30-m-long corewas obtained from the northern slope of the SCS at awater depth of 1728 m during the Sonne-95 cruise in1994 (Sarnthein et al. 1994). The site is located at adistance of 400 km from the present freshwater plumeof the Pearl River mouth, but it was considerably closerto the shoreline of southern China during the late Pleis-tocene and early Holocene (Fig. 2).

Diatom samples were prepared following Håkansson(1984) and the relative abundance, calculated as apercentage of the total diatom assemblage, was basedon counts of at least 300 diatom valves (excludingChaetoceros resting spores). A total of 164 samples,each representing a 1-cm-thick slice of sediment, cov-ering the last 14 700 years, were analysed for theirdiatom contents. Huang et al. (2009b) published a rela-tively low-resolution diatom record with a samplinginterval of 10 cm during the Holocene and 5 cm beforethe Holocene. Our new diatom record used for thereconstruction of summer SSS variability has a highertime resolution with a sampling interval of 5 cm for thewhole period. The mean sample resolution is about 90years for the entire record.

A revised modern calibration data set from thewestern Pacific marginal seas (Supporting InformationTable S1) was used to generate a diatom-based transferfunction for quantitative reconstruction of summerSSS (Li et al. 2012). The computer program C2(Juggins 2007) was used for the summer SSS recon-struction. Seven numerical reconstruction methodswere tested in order to find the optimal diatom-basedsummer SSS transfer function (Supporting Informa-tion Table S2; Fig. S1).

The modern analogue technique (MAT (4 analogues))yields the lowest root mean squared error of prediction(RMSEP(Jack)) (0.43) and the highest squared correla-tion (r2

(jack)) (0.87) (Table S2). However, a plot of thedifferences between the jack-knife inferred and theobserved summer SSSs against observed summer SSSsshows that inferred summer SSSs are always over-estimated when observed summer SSSs are lower than32.5 (psu) and usually under-estimated when observedsummer SSSs are higher than 33.8 (psu) (Fig. S1B). Italso gives a very high maximum bias (Max_Bias(Jack))(0.66).

The weighted averaging partial least squares (WA-PLS) method with three components results in a lowRMSEP(Jack) (0.54), a low Max_Bias(Jack) (0.44), and ahigh r2

(Jack) (0.79) (Table S2). Furthermore, plots ofjack-knife inferred summer SSSs against observedsummer SSSs show a good linear correlation (Fig. 3A)and the residuals are randomly scattered (Fig. 3B).Therefore, the WA-PLS with three components wasused for reconstructing summer SSSs.

The diatom-based summer SSS values (∼33.9 psu)calculated for the youngest part of the record (top ofcore 17940) correspond to the present-day summer SSS(∼33.7 psu) (Fig. 2; Guo et al. 2004), suggesting that thediatom-based summer SSS reconstruction presentedhere may be suitable for reconstructing millennial- tocentennial-scale climate events in the SCS.

Age model

The age model of core 17940 is based on 38 acceleratormass spectrometry (AMS) 14C measurements carri-ed out on the planktonic foraminiferal speciesGlobigerinoides ruber and Globigerinoides sacculifer(Wang et al. 1999). Radiocarbon ages were convertedto calendar ages using the CALIB98 program (Stuiveret al. 1998). A 402-year correction was applied for thereservoir age of seawater for the last 11 000 years. Priorto the last 11 000 years, AMS 14C ages were correctedfor reservoir ages of 900–1000 years, as 14C plateausand reversals are common to all regions of the oceanand pervasive during the last deglacial interval(Sarnthein et al. 2007). Calendar ages were interpolatedbetween age-calibrated 14C plateau boundaries andlinear interpolation was used between the data points(Table S3). This age model shows that core 17940covers the age interval 0–14 700 cal. a BP.

Spectral analyses

Univariate spectral analyses were applied to thediatom-based SSS proxy data from core 17940 to iden-tify the presence of statistically significant oscillationsin summer SSS throughout the studied record. Theuntuned SSS proxy data were initially detrended tosuppress spectral leakage from low-frequency harmon-ics. The spectra were subsequently estimated using the

Summer sea-surface salinity in the South China Sea, the last 15 000 years 211BOREAS

Lomb-Scargle Fourier transform for unevenly spaceddata, combined with the Welch-Overlapped-Segment-Averaging procedure, and a Welch I data taper. Fivesegments with 50% overlap were used for the full SSSproxy record, covering almost 15 000 years, whereasthree segments were used for the truncated Holocenerecord, covering the last 10 000 years. The univariatespectra were bias-corrected using 1000 Monte-Carlosimulations. This was carried out by use of the pub-licly available REDFIT program (Schulz & Mudelsee2002), which automatically produces first-orderautoregressive (AR1) time series with sampling timesand characteristic time scales matching those of thereal climate data. To assess the statistical significanceof a spectral peak, REDFIT estimates the upper con-fidence interval of the AR1 noise for various signifi-cance levels based on a χ2 distribution. Standard testsshowed that the climate data series could in fact beapproximated sufficiently well by an AR1 model. Sub-sequently, the SSS proxy data were grouped in sliding4000-year windows, with a spacing of 50 years, beforethe spectrum and associated red-noise false-alarmlevels were calculated for all individual windows. Theindividual spectra, based on data grouped in each4000-year time window, were then aligned accordingto their age, given by the mid-point of the timewindow, and the frequencies for which the spectralpower exceeded red-noise false-alarm levels of 90, 95,and 99% were then colour-coded. A window size of4000 years was chosen to obtain optimal balancebetween spectral smoothing and temporal resolution.This approach relies on the same methods used in

numerous earlier palaeoclimatological studies toevaluate the statistical significance of spectral peaks(e.g. Knudsen et al. 2011).

A bivariate analysis was performed to estimate thecoherency between centennial-scale changes in summerSSS in the SCS, past solar variability, and past changesin rainfall over SE China by using the software SPEC-TRUM (Schulz & Stattegger 1997).

Results and discussion

Reconstruction of past variations in summer SSS

We applied the same diatom-based SSS transfer func-tion as in Li et al. (2012) to the diatom data from core17940, thus allowing us to establish a new SSS recordfrom the northern SCS reaching back approximately15 000 years. The reconstructed summer SSSs varybetween 33.3 and 34.2 psu during this time period(Table S4) and exhibit a relatively distinct long-termtrend, which roughly follows variations in the summer(June) insolation at 20°N (Fig. 4). The summer SSSswere generally below the mean value for the recordbefore 9000 cal. a BP and a relatively distinct minimumin summer SSS occurred between 10 000 and11 000 cal. a BP. This minimum was followed by agradual increase in summer SSS until about 4500 cal. aBP, at which point the SSS reached relatively stablehigh values. The summer SSS experienced a relativelyweak declining trend from about 1500 cal. a BPtowards the present. Superimposed on these long-term

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212 Hui Jiang et al. BOREAS

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Fig. 4. Diatom-based summer SSSs of the last 14 700 years from core 17940 in the northern SCS (A) compared to records of fresh and littoralwater diatoms from core 17940 (B), the δ18O records from Dongge Cave (C) and the planktic δ18O-based SSS record from core 17940 (D).

Summer sea-surface salinity in the South China Sea, the last 15 000 years 213BOREAS

trends are some relatively large centennial-scale varia-tions with amplitudes almost comparable to the ampli-tude of the long-term trends.

Spectral analysis of the diatom-based SSS data fromcore 17940 indicates the existence of distinct centennial-scale cyclicities, although the predominant cyclicityseems to change with time. When studying the fullsummer SSS record covering ∼15 000 years, the statis-tically most significant oscillation had a period of ∼230years (Fig. 5A). The most prominent periodicity in thepower spectrum of the data covering the last 10 000years of the record, however, had a period of ∼350 years(Fig. 5B). The temporal distribution of spectral power(Fig. 6) shows that the significant ∼350-year oscillationwas confined to the interval 2200–4500 cal. a BP,whereas the dominant oscillation in the pre-Holoceneinterval had a period of 230–250 years. The Holocenealso seems to have experienced a short interval with anoscillation of around 1100 years and two short intervalswith 195- and 205-year oscillations between 5000 and8000 cal. a BP. However, the oscillatory fluctuationswith periods close to ∼200 years should be regarded asuncertain, because these periodicities lie close to theNyquist frequency associated with the data. TheNyquist frequency (1/2Δt=1/180) is the maximum fre-quency that can be resolved based on the sample reso-lution of the summer SSS record (Δt=90 years).

Long-term summer SSS trends in the SCS

Our new diatom-based SSS record shows an overallpattern similar to that of Wang et al. (1999), whoreconstructed SSS based on the combined studies ofstable oxygen isotopes and alkenones from the same

core, with relatively low SSSs during the Late Pleisto-cene and early Holocene, and high SSSs during themid-late Holocene. However, the variability of the SSSrecord of Wang et al. (1999) is somewhat larger, reach-ing up to 2 psu, whereas our method suggests a vari-ability of only about 1 psu throughout the last 15 000years. Additionally, changes from low to high SSSs inthe early Holocene occurred much more graduallyaccording to our record compared to that of Wanget al. (1999), and we do not observe the distinctly lowSSS values prior to c. 13 500 cal. a BP recorded bythese authors.

The relative abundance of fresh-, brackish, andcoastal-water diatoms from core 17940 shows highvalues of these diatoms, e.g. Cyclotella spp., Diploneispp., and Paralia sulcata, prior to 9000 cal. a BP whenour reconstruction indicates low summer SSSs (Figs 4,7). Meantime, the abundance of marine planktonicdiatoms, e.g. Thalassionema nitzschioides var. parva,Fragilariopsis doliolus, and Rhizosolenia bergonii, isrelatively low, especially during the early Holocene.This combined evidence strongly indicates a high freshwater discharge and strong coastal water influencebefore 9000 cal. a BP, in particular during the earlyHolocene, as previously proposed by Huang et al.(2009b). Changes in the strength of the EAM areknown to exert a strong influence on the summer SSS inthe SCS. At millennial time scales, the strength of theEAM is mainly controlled by orbitally induced varia-tions in the summer insolation (e.g. Wang et al. 2005,2008). As changes in the EAM, and hence rainfall,strongly influence the amount of fresh water deliveredto the SCS through river systems, in particular the PearlRiver, it is not surprising that long-term changes in

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summer SSS broadly follow changes in summer insola-tion and rainfall (i.e. monsoon activity) reconstructedfrom speleothem δ18O records.

It has been shown that shifts in the oxygen isotoperatio (δ18O) of a stalagmite from the Dongge Cavelargely reflect changes in δ18O values of meteoric precipi-tation at the site, which in turn relate to changes in theamount of precipitation and thus characterize the EAMstrength (Dykoski et al. 2005). Comparison betweenmillennial-scale trends in the Dongge Cave δ18O records(Dykoski et al. 2005) and our summer SSS reconstruc-tion (Fig. 4) shows that increased summer precipitationis in general associated with low salinity in the SCS.Accordingly, the minimum in summer SSS in the SCScoincides with a maximum in EAM precipitation duringthe early Holocene. There are, however, some inconsist-encies between the two records, probably attributable toclimate-induced changes in sea level.

The results above suggest that changes in the summerSSS in the SCS during the Late Pleistocene and earlyHolocene were driven by variations in the strength ofthe EAM, which may be attributed to variations insolar insolation. Lower salinity during the early Holo-cene (11 000–8000 cal. a BP) has also been found inthe southern SCS and it is presumably linked to thePreboreal–Early Holocene Maximum in summer

monsoon precipitation and river runoff in the Asianmonsoon region (Steinke et al. 2006). This is furthersupported by Liew et al. (2006), who studied a subal-pine pollen sequence from the Toushe Peat Bog depos-its in central Taiwan (23°49′N, 120°53′E) covering thelast 12 000 years. Based on changes in relative frequen-cies of fern spores, they identified intervals of highhumidity at 11 000–8000 and 7000−6000 cal. a BP. Thisis in agreement with our observations of low summerSSS in the SCS during the same periods.

Relatively low sea levels during the Late Pleistoceneand early Holocene presumably reduced the distancebetween the location of core 17940 and the coastline ofsouthern China, thereby increasing the influence offresh water from the Pearl River. During low sea-levelstands of the Pleistocene, the SCS was a semi-closedbasin and the palaeoenvironment was consequentlyhighly sensitive to sea-level induced changes in hydrog-raphy and oceanography. It is believed that an increasein sea level associated with the deglaciation thatmarked the onset of the Holocene led to a reconnectionof the ECS and the SCS, allowing low-salinity coastalwaters to enter the SCS (Huang et al. 2009b). This isconsistent with the observation of a general minimumin summer SSS in the SCS around 11 000 cal. a BP,which may partly be attributed to inflow of less salty

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Fig. 6. Spectrogram delineating the temporal distribution of highly significant (yellow: χ2>90%, red: χ2>95%, and dark red: χ2>99%) spectralpower of the diatom-based summer SSS proxy record from the SCS. The data were grouped in overlapping 4000-year windows, with a spacingof 50 years. The green rectangles delineate time intervals characterized by particularly prominent solar cycles with periods centred at ∼210 and350 years (Knudsen et al. 2009). To the left of the dashed blue line (c. 8300 cal. a BP), the information on past solar-cycle activity is based oncorroborating 14C data from tree rings and 10Be data from the GRIP ice core. Information on solar-cycle activity prior to c. 8300 cal. a BP reliessolely on 14C data and is therefore less reliable.

Summer sea-surface salinity in the South China Sea, the last 15 000 years 215BOREAS

waters from the ECS. The influence of sea-level changeson palaeoenvironmental conditions in the SCS declinedafter 9000 cal. a BP, as the sea level rose towardspresent-day levels.

Long-term changes in the summer SSS during theLate Pleistocene and early Holocene may therefore beattributed to a combination of changes in monsoonprecipitation and climate-induced changes in sea level.Summer SSS changes during the mid-late Holocene,characterized by more stable sea level and decreasinginsolation, however, were presumably primarily con-trolled by variations in precipitation linked to the EAM.

Centennial-scale oscillations in summer SSS andpotential links to solar variability

Given the similarity between the general trends of theEAM strength and the summer SSS during the Holo-cene, it is reasonable to assume that centennial-scalechanges in the EAM also exerted a strong influence onthe summer SSS. The reconstruction presented in this

study has made it possible to tentatively investigate thenature and origin of centennial-scale changes insummer SSS in the SCS. The distribution of the statis-tically significant oscillations in summer SSS showsthat the dominant oscillations centred around 200 and340 years coincide with the frequency of prominentsolar-cycle activity during the Holocene (Knudsenet al. 2009) (Figs 5, 6). The episodes characterized bysignificant ∼200- and ∼340-year oscillations in summerSSS were constrained to rather limited time intervals(Fig. 6). Knudsen et al. (2009) recently showed that the∼210-year (Suess) and ∼350-year solar cycles were par-ticularly prominent during certain time intervals,so-called burst intervals (green rectangles; Fig. 6). Fur-thermore, subtropical speleothem δ18O records showincreased variability during these burst intervals, indi-cating a link between solar irradiation and monsoonactivity (Knudsen et al. 2012). The significant summerSSS oscillations partly overlap these burst intervals, buta considerable fraction of the summer SSS oscillationsdo not coincide in time with the burst intervals, most

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lenia berg

onii

Age

(ca

l. a

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)

Percentage of diatom species (%)

Fig. 7. Percentage distributions of selected species and species groups of diatoms in core 17940.

216 Hui Jiang et al. BOREAS

notably the 195-year oscillation around 7000 cal. a BPand the 340-year oscillation between 3200 and 4500 cal.a BP (Fig. 6). This indicates that the summer SSS vari-ability at these solar-like periodicities were not com-pletely in synchrony with the sun. The proximity to theNyquist frequency implies that interpretation of the195-year oscillatory fluctuations is problematic.

The ∼230-year SSS oscillation was remarkably dis-tinct during the pre-Holocene portion of the record, buta lower sea level and shorter distance between the coresite and the Pearl River could have enhanced the sen-sitivity to centennial-scale, solar-induced oscillationsin fresh water input. Interestingly, there are no indica-tions of significant ∼350-year oscillations in the pre-Holocene portion of the summer SSS reconstruction,but it is unknown whether the Sun oscillated at thisperiodicity during this time interval.

Coherency between summer SSS, solar variability, andAsian monsoon precipitation

Bivariate analysis was used to estimate the coherencybetween centennial-scale changes in summer SSS in theSCS, a reconstruction of the Holocene Total Solar Irra-diance (TSI; Steinhilber et al. 2009), and a high-resolution δ18O record from Dongge Cave (Wang et al.2005). Note that for this analysis, we focused on therecord from stalagmite DA (Wang et al. 2005), whichhas a higher resolution and features a more uniformgrowth rate compared to that of Dykoski et al. (2005).The bivariate analysis of the SSS proxy record and theTSI record indicates the presence of significant coher-

ent cycles centred at 240 and 350 years, i.e. the coher-ency of these periodicities exceeds the 90% false-alarmlevel (Fig. 8A). Significant coherency between the SSSproxy record and the Dongge δ18O record are observedfor oscillations with periods centred at 350 and 1450years (Fig. 8B). The coherency spectra therefore indi-cate that the SSS proxy record is coherent with the TSIrecord at frequencies that correspond to well-knownsolar cycles, and that it is coherent with the δ18O recordfrom Dongge Cave at one of these solar frequencies(∼350 years). This supports the notion that solarforcing may have played a key role in drivingcentennial-scale summer SSS variability in the SCS,most likely via the link between solar variability, Asianmonsoon precipitation (Wang et al. 2005), and, in turn,fresh water discharge into the SCS. However, furtherevidence is needed to firmly establish this relationship.

Conclusions

The summer SSS in the SCS is today strongly affectedby river runoff from a large catchment area (Fig. 2).This river-runoff is dependent on precipitation andmonsoonal activity in East Asia, and past summer SSSvariability may thus be used to study changes in Asianmonsoon activity.

We have produced a summer SSS record based onnew proxy data from sediment core 17940 in the north-ern SCS. The record reaches back approximately15 000 years and during this time period the recon-structed summer SSSs varied between 33.3 and

0.5 1 1.5 2 2.5 3 3.5 4 4.5 5

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Period (years)2505001000 333 200 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5

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A B

Fig. 8. Coherency spectra calculated for (A) the summer SSS record and Total Solar Irradiance (Steinhilber et al. 2009) and (B) the summerSSS record and the δ18O record from Dongge Cave (Wang et al. 2005). The coherency spectra (solid black lines) are compared against the 90%false-alarm-rate level (dashed red line). To bring the three records onto an equal footing, we re-sampled the TSI and Dongge δ18O records,which both have higher resolution than the summer SSS record, using the sample ages of the SSS record in the interval 0–9000 a BP. The TSIand δ18O data were then averaged half-way between neighbouring data points, which is the equivalent of a running average with slightlyirregular sampling intervals. The coherency spectra were calculated using the software SPECTRUM (Schulz & Stattegger 1997), a Welch I datataper, and no alignment.

Summer sea-surface salinity in the South China Sea, the last 15 000 years 217BOREAS

34.2 psu. Our summer SSS record exhibits a long-termtrend, which roughly follows variations in the orbitallyforced summer insolation at 20°N with relatively lowsummer SSS before 9000 cal. a BP and a distinctminimum between 10 000 and 11 000 cal. a BP. Thiswas followed by a gradual increase in summer SSS untilabout 4500 cal. a BP, when SSS values reached a rela-tively stable maximum. After about 1500 cal. a BP, thesummer SSS shows a weak declining trend. This overalltrend suggests that orbital forcing has been the mostimportant overall driver of summer SSS in the regionthrough the Lateglacial and Holocene.

The distribution pattern of this diatom-based summerSSS record from core 17940 reflects the combined effectof the EAM strength and palaeoceanographic condi-tions. During the Late Pleistocene and the early Holo-cene, climate-induced sea-level change and a stronger-than-present EAM both influenced variations in thesummer SSS. However, during most of the Holocene,when the sea level reached the present coastline, thesummer SSS variations were probably primarily con-trolled by fluctuations in the EAM strength, withperiods of lower SSS corresponding to periods ofincreased EAM.

Spectral analyses indicate that significant centennial-scale variations are superimposed on the long-termorbital trend. The amplitude of these centennial-scalevariations is almost comparable to the amplitude of thelong-term trend. The dominant periodicity was centredon 230–250 years in the deglacial period (c. 12 000–9000 cal. a BP), whereas a ∼350-year oscillation domi-nated in the period 2200–4500 cal. a BP. Evidencesuggests that the 230–250-year and ∼350-year SSS oscil-lations may be linked to well-known solar cycles atthese frequencies, but it is currently impossible to estab-lish a firm causal relationship between centennial-scalechanges in summer SSS/EAM and solar variability.

Acknowledgements. − We would like to thank the GermanMinistry for Education and Research and the DeutscheForschungsgemeinschaft in Bonn for their generous support of theSonne-95 cruise. Our thanks also go to Captain Bruns and the crew ofRV Sonne, especially to Norbert Mühlhan for technical assistance inretrieving sediment cores, to Prof. Michael Sarnthein for kindly pro-viding diatom samples and the age model of core 17940, and to DrZong for diatom data from surface sediments in the Pearl RiverEstuary. This work was financed by NSFC (grants nos 40976115 and40676032), the National Basic Research Program of China (973Program 2010CB428903), the Carlsberg Foundation, the DanishCouncil for Independent Research|Natural Science (grant no.09-069833/FNU, TROPOLINK), and the EU FP7 (project no.243908, Past4Future). Finally, we are grateful to J. Reed and ananonymous reviewer as well as the Editor-in-Chief, Jan A.Piotrowski, for constructive and useful comments.

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Supporting Information

Additional Supporting Information may be found inthe online version of this article at the publisher’sweb-site:

Fig. S1. Plots of jack-knife inferred summer SSSs (psu)using MAT (four analogues) against observedsummer SSSs (psu) (A) and of the differencesbetween jack-knife inferred and observed summerSSSs against observed summer SSSs (psu) (B). Theinferred summer SSSs are always over-estimatedwhen observed summer SSSs are lower than 32.5(psu) and under-estimated when observed summerSSSs are higher than 33.8 (psu).

Table S1. Locations of the surface sediment diatomsamples. The data from deep seas were mainly fromWorld Ocean database 1998 (the NOAA NationalOceanographic Data Centre) and data from theChinese coasts and in the shallow water areas aremainly from Guo et al. (2004), who compiled thedata during 1982–2002.

Table S2. Test of seven numerical reconstructionmethods. Seven numerical reconstruction methodswere tested, including weighted averaging (WA),weighted averaging with tolerance down-weighting(WA(tol)), partial least squares (PLS), weighted aver-aging partial least squares (WA-PLS), and modernanalogue technique (MAT). Both inverse and classi-cal deshrinking regression were used in the WA andWA(tol) reconstruction procedures (Juggins 2007).The results are presented as root-mean squared errorof prediction based on the leave-one out jack-knifing(RMSEP(Jack)) test, maximum bias (Max_Bias(Jack)),and coefficient of determination between observedand predicted values r2

(Jack).Table S3. Calibrated ages of data points used for the

age model of core 17940. Linear interpolation hasbeen used between data points.

Table S4. Diatom-based summer SSS data from core17940.

Summer sea-surface salinity in the South China Sea, the last 15 000 years 219BOREAS