Giant clams (Tridacna) are the largest marine bivalves, and their carbonate shells
can be used for high-resolution paleoclimate reconstructions. In this
contribution, δ18Oshell was used to estimate climatic
variation in the Xisha Islands of the South China Sea. We first evaluate sea
surface temperature (SST) and sea surface salinity (SSS) influence on the
modern resampled monthly (r-monthly) resolution of Tridacna gigasδ18Oshell. The results obtained reveal that δ18Oshell seasonal variation is mainly controlled by SST and
appears to be insensitive to local SSS change. Thus, the δ18O
of Tridacna shells can be roughly used as a proxy of local SST: a 1 ‰ δ18Oshell change is roughly equal to
4.41 ∘C of SST. The r-monthly δ18O of a 40-year-old
Tridacnasquamosa (3673±28 BP) from the North Reef of the Xisha Islands was analyzed
and compared with the modern specimen. The difference between the average
δ18O of the fossil Tridacna shell (δ18O=-1.34 ‰) and the modern Tridacna specimen (δ18O=-1.15 ‰) probably implies a warm climate, roughly
0.84 ∘C, 3700 years ago. The seasonal variation 3700 years ago
was slightly lower than that suggested by modern instrumental data, and the
transition between warm and cold seasons was rapid. Higher amplitudes of
reconstructed r-monthly and r-annual SST anomalies imply an enhanced climate
variability during this warm period. Investigation of the El
Ninõ–Southern Oscillation (ENSO) variation (based on the reconstructed
SST series) indicates reduced ENSO frequency but increased ENSO-related
variability and extreme El Ninõ winter events 3700 years ago.
Introduction
The carbonate skeletons of marine organisms, such as corals, foraminifers,
and mollusks, have been widely used to reconstruct environmental variation
(Aharon,
1983; Batenburg et al., 2011; Ourbak et al., 2006; Schöne et al., 2005;
Wanamaker et al., 2011; Yamanashi et al., 2016; Yu et al., 2005a, b). Due to
their high sensitivity to the surrounding environment and the fact that they preserve
high-resolution biochemical variations in their skeleton, these marine
biogenic carbonates can shed light on past climate dynamics. Bivalves, which
are considered to be high-resolution records, can give us more precise
details on environmental variation. Giant clams (Tridacna), as they are the largest
bivalves and usually live in tropical coral reefs, have received increasing
scientific attention in recent decades
(Pätzold
et al., 1991; Watanabe et al., 1999, 2004; Elliot et al.,
2009; Ayling et al., 2015; Agbaje et al., 2017). This is because their
shells have many favorable properties for recording local environmental
changes: they have dense and well-preserved aragonite shells, fast growth
rates (up to 1 cm yr-1) with clear annual growth lines, and a longevity
of several decades to about 100 years. These characteristics allow
Tridacna to provide ideal material for high-resolution reconstruction of
interannual, seasonal, or even subseasonal climatic variations.
Previous studies indicate that Tridacna species grow their shells in oxygen isotopic
(δ18O) equilibrium with the surrounding seawater
(Aharon,
1991; Aharon and Chappell, 1986; Pätzold et al., 1991; Romanek and
Grossman, 1989; Watanabe et al., 1999). The reliability of reconstructing
temperature and seawater δ18O variability is not reduced and
does not show obvious increasing or decreasing trends due to Tridacna's ontogenetic
growth (Welsh et al., 2011).
These studies imply that δ18Oshell can be used to
reconstruct Late Quaternary sea-level and climatic changes. Indeed, the
δ18O of marine biogenic carbonates is influenced not only by
sea surface temperature (SST) but also by surrounding seawater δ18O. Meanwhile, seawater δ18O has a close correlation
with sea surface salinity (SSS), which is affected by tropical evaporation
and the precipitation balance. Nonetheless, the influence of SST and SSS on
δ18Oshell is unclear due to the distinct variation of
temperature and salinity in different areas. For example, the δ18Oshell of Tridacna from southwestern Japan can be directly used as a
proxy of SST (Yamanashi
et al., 2016), while the δ18Oshell of Indonesian
Tridacna has been interpreted to be a contribution of 71.4 % from SST and 28.6 % from SSS (Arias-Ruiz et
al., 2017). Thus, local calibration from modern Tridacna is important in determining
the relationship of δ18Oshell, SST, and SSS.
Climatic variation in the Meghalayan (which began 4200 BP in the Late
Holocene) has significant impacts on human society and ecosystem
development. However, early Meghalayan climatic conditions in SE Asia around
the South China Sea still remain poorly understood. Shi (1994) reviewed data
from various sources (such as ice cores, inland lakes, paleosols in loess
and eolian sands, sea-level fluctuations, palynological and botanical
studies) in China and found that the early Meghalayan is a part of the Holocene
megathermal period (8 to 3 kyr BP). Sediments in the South China Sea also
imply that the temperature might have been relatively higher in the early
Meghalayan than in the present
(Ouyang
et al., 2016). However, these studies are low-resolution, and
high-resolution records under interannual climate variation are rare. With
global warming and numerous climatic disasters happening in recent decades,
climatic conditions in the early Meghalayan could serve as an analogue to modern
problems and have received increasing scientific attention
(Schirrmacher
et al., 2019; Scuderi et al., 2019; Toth and Aronson, 2019; Zhang et al.,
2018). Recent studies of bivalve mollusk specimen (Arctica islandica) oxygen isotopes show
high-resolution data with seasonal signals
(Schöne
et al., 2005; Wanamaker et al., 2011). High-resolution isotopic geochemical
data from Tridacna may also provide detailed insight into climatic variations in
the early Meghalayan.
Furthermore, El Ninõ–Southern Oscillation (ENSO) is widely accepted as
the main source of interannual climatic variability in the Pacific Ocean.
Previous studies suggest that the impacts of ENSO activity are not limited
to tropical areas but might also apply to global atmospheric circulation
through the heating-up of the tropical atmosphere
(Cane, 2005). Thus, reconstructing ENSO is
very important for understanding its dynamics and predicting future change.
Many early studies on ENSO behaviors were constructed with low-resolution
proxy data using deposition events (Rodbell et al., 1999; Koutavas and
Joanides, 2012) or ice cores (Thompson et al., 1995) in order to reveal
ENSO variance over thousands of years. However, the periodicity of ENSO is
short, making it difficult to use these low-resolution data to precisely
determine the strength and variability of ENSO activity. Recent studies
focus on seasonal or monthly data to examine precise variation of ENSO
activity
(Arias-Ruiz
et al., 2017; Ayling et al., 2015; McGregor et al., 2013; Welsh et al.,
2011; Yan et al., 2017), but those fragmental data cannot fully explain the
Holocene ENSO dynamics. Therefore, fragments from different times according
to different high-resolution samples are needed and can provide an
integrated framework for examining ENSO theory and models of the Holocene.
In addition, studies on the Middle to Late Holocene ENSO evolution yield
controversial findings: coral records show a reduced ENSO variability around
the early Meghalayan
(Tudhope
et al., 2001; McGregor et al., 2013; Cobb et al., 2014; Woodroffe et al.,
2003). Other carbonate species like fossil mollusk shells suggest that ENSO
variance was severely damped ∼4000 years ago
(Carré et al., 2014). Yet other studies indicate
strengthening ENSO activity at 4 to 3 ka
(Duprey et al., 2014; Yang
et al., 2019). Thus, this further points to the importance of
high-resolution isotopic geochemical data such as from Tridacna in unraveling the
dynamics of ENSO.
This study aims to evaluate seasonality, climate variation, and ENSO
activity in the Xisha Islands of the northern South China Sea, based on two
high-resolution δ18Oshell profiles of modern and fossil
Tridacna. The study area is situated in the northwest margin of the west Pacific
warm pool (WPWP), and the local climate is widely accepted to be directly
responsive to ENSO activity
(Mitsuguchi
et al., 2008; Yan et al., 2010). A modern Tridacnagigas shell was first used to estimate
the extent of environmental control (SST and SSS) on δ18Oshell, and a new SST–δ18Oshell linear
regression was proposed. Subsequently, a fossil Tridacnasquamosa (which lived to 40 years)
was used to reconstruct seasonality and climatic variation, and the obtained
results are compared with the modern species and meteorological
observations. Finally, ENSO activity and extreme El Ninõ winter events
were discussed, using the re-established SST anomalies.
The South China Sea is located in the northwest of WPWP (Fig. 1a), and its
interannual climate is closely related to ENSO activities
(Mitsuguchi
et al., 2008; Yan et al., 2010). The Xisha Islands in the northern South
China Sea are substantially influenced by two contrasting Asian monsoons from
opposite directions: the Asian summer monsoon from the southwest and the
Asian winter monsoon from the northeast. These two monsoons provide distinct
seasonal SST for the Tridacna populating the coral reefs of the Xisha Islands. Our
sample (Tridacnasquamosa A5) was collected in the North Reef (17∘05′ N, 111∘30′ E), whilst the modern
Tridacna gigas sample YX1 (studied previously by Yan, 2013) was acquired from Yongxing
Island (16∘50′ N, 112∘50′ E), which is about 90 km away from the North Reef (Fig. 1b).
Meteorological observations (atmosphere temperature, AT; SST; SSS; rainfall)
were obtained from the Institute of Meteorology of China, which has taken
records for the Xisha Islands since 1958. In order to compare geochemical
analyses with monthly environmental data, isotopic records and
meteorological observations were resampled according to the method suggested
by Schöne and Fiebig (2009). They used bivalve shells (Arctica islandica) to reconstruct
the climate, examining that seven points per year would minimize the influence of
different growth rates throughout the year; meanwhile, only the annual
sample number for which more than or equal to seven existed could be used.
As the yearly minimum number of δ18OYX1 is seven, 1 year
includes 7 resampled months (r months). Figure 1d shows the r-monthly
average time series of AT, SST, SSS, and rainfall, and their standard
deviations (SDs). The mean SST is 27.77 ∘C, and AT shows a highly
positive correlation with SST (r=0.98), but it is about 0.7 ∘C
lower. The SST seasonality is 5.33 ∘C, with the lowest value and
highest value occurring in first and fourth r months, respectively. It is
excluded that river runoff effects on SSS as the Xisha Islands are about 300 km away from the continent (Hainan Island). SSS varies from 33.25 ‰ to 33.81 ‰, and the change is mainly dominated by rainfall:
higher SSS in dry winters and lower SSS in wet summers (Fig. 1e).
The SST data in the North Reef are acquired from NOAA HadISST, a global
monthly SST data with a spatial resolution of 1×1∘
(data grid cell includes both the North Reef and Yongxing Island) from 1982
to 2017. Ninõ 1+2 SST data are obtained from NOAA monthly data
between 1982 and 2017 (http://www.cpc.ncep.noaa.gov/data/indices/sstoi.indices; last access:
31 December 2017).
Shell descriptions and sample preparation
The original fossil Tridacna was cut from the umbo to the ventral (red line in Fig. 1b), where the thickness of the inner layer is the greatest. From the slice
we cut, the fossil Tridacna has three different zones (Fig. 1c): the inner layer,
the outer layer, and the hinge. A recent study investigating the architecture
of Tridacna shells shows a crossed lamellar microstructure with a strong fiber
texture with optimized mechanical performance (Agbaje et al., 2017), and the
mineralization of inner layer and outer layer is independent of each other
(Gannon et al., 2017). The inner layer is chosen for the analyses because of
its clear growth layer and well-preserved shell. Published data also reveal
that inner layer δ18O values are unaffected by ontogeny
(Welsh et al., 2011) and could better
reflect actual δ18O than the outer layer or the hinge
(Pätzold et al., 1991;
Elliot et al., 2009).
The determination of radiocarbon age was performed at the Institute of Earth
Environment of Chinese Academy of Sciences. The 14C accelerator mass
spectrometry data revealed that the fossil Tridacnagigas age is 3437±28 yr BP.
Due to the lack of an obvious “reservoir effect” in the dating results of
modern Tridacna shells, the atmospheric 4C yield model is used for
calibration (Liu et al., 2019). The calibrated date (2σ) ranges from 3733 to 3613 cal BP, with the median date is 3691 cal BP by
using the IntCal13 of Radiocarbon Calibration Program CALIB 7.10
(http://calib.org, last access: 31 December 2018). Both X-ray diffraction (XRD) and laser Raman
spectrometers results show aragonite, and no other substances are found.
Stable isotopes
Each stable isotope sample was micromilled parallel to the growth layer with
1 mm long and 100 µm deep under a micro-drill automated system
(Micro-Drill New Wave Research, Olympus SZ 61) in the Isotope Laboratory of
Xi'an Jiaotong University, China. Four intervals were used according to the
growth rates: 100 µm (n=1 to 268), 150 µm (n=269 to 481),
200 µm (n=482 to 657), and 300 µm (n=658 to 765)
in a transect from adult to ontogenetically younger shell, respectively (Fig. 2a).
The δ18O of the Tridacna was analyzed in the Isotope Laboratory of
Xi'an Jiaotong University, using the Thermo Finnigan MAT-253 mass
spectrometer fitted with the Kiel IV Carbonate Device. All results were
reported in per mil (‰), relative to the Vienna Pee Dee
Belemnite (VPDB) standard. The standard GBW04405, which has been compared
with international standard NBS-19, was added to the analyses every 10 to 20
samples to check reproducibility. The average value of standard powder in
δ18O is -8.49±0.14 ‰. Duplicate
measurements of GBW04405 standards and samples showed long-term
reproducibilities (1σ) of less than 0.14 ‰ and
0.05 ‰, respectively.
Published data of the modern Tridacnagigas shell YX1 were used to investigate the
relationship between Tridacnaδ18O and the local climate
(Yan et al., 2013). YX1 was collected
from Yongxing Island, 90 km ESE of the North Reef (Fig. 1b). The internal
carbonate standard of modern Tridacna YX1 δ18O (VPDB) was also
GBW04405; the standards and samples had reproducibilities (1σ) of
better than 0.08 ‰ and 0.06 ‰,
respectively.
Data processing and analyses
PearsonT3 (Version 2.2, January 2017) was used to test the correlation
coefficient. Successive sets of 100 years' length were calculated to
estimate monthly insolation using the software AnalySeries 2.0.8
(Laskar et al., 2004),
which contained the probable life span of Tridacna (A5) considering 2σ
confidence intervals of corrected age. The timescale of modern insolation
ranges from 1918 to 2017, while the past ranges from 3722 to 3623 BP.
Statistical analyses were performed with the software Origin 2018 and PAST
(Paleontological Statistics) 3.18. The isotopic records, meteorological
observations, and insolation data were resampled for seven points per year
using the software AnalySeries 2.0.8, as used for other studies in
sclerochronology
(Schöne
and Fiebig, 2009; Wanamaker et al., 2011).
(a) The δ18O profiles of A5. (b) The δ18OA5 profiles chronology scale after resampling the data; the
dotted lines indicate the average annual maximum and minimum.
Seasonal cycles are distinct in the δ18OA5 profile (Fig. 2, Table S2), which indicate that this Tridacna lived for 40 years. The δ18OA5 range from -2.07‰ to -0.14‰ (mean -1.35‰, n=765). After resampling into seven points per year,
δ18OA5 varied from -1.98‰ to -0.29‰
(mean -1.34‰, n=281).
Sclerochronology
From the shell section, dark–bright line couples (each couple represents 1
year) can be seen clearly (Fig. 3a). Following the δ18OA5
profiles, these short, dark lines (transparent) correspond to higher δ18OA5 values, which means that Tridacna grew in lower temperature (cold
seasons such as December to February). In contrast, lower δ18OA5 values lie in the long bright lines (opaque), corresponding
to the higher temperatures (warm seasons such as March to November). Annual
growth rates can be calculated with the δ18OA5 seasonal
cycles and interval distance (Fig. 3c). The results show that growth rates
were higher when Tridacna A5 was young, reaching 5 mm yr-1. The growth then
slowed down and stabilized to 1–2 mm yr-1 after the Tridacna had matured (Fig. 3c). Furthermore, daily increments visible as pairs of dark and bright
increments can be seen under the microscope (Fig. 3b). A fragment was chosen
where δ18O values were nearly the highest in a particular year.
This period fell during the cold season, when the daily growth increment was
about 4.5 µm. When the temperature rose as warm season began,
Tridacna grew faster, with daily growth increment reaching up to 8 µm. This
situation occurred throughout the Tridacna's life (Yan et al., 2020). In general,
Tridacna A5 grew faster in warm seasons and slower in cold seasons.
(a) Dark–bright lines consistent with δ18OA5
profiles. The blue line represents the sampling line. Dark and bright lines
correspond to high δ18O (cold seasons) and low δ18O (warm seasons), respectively. The distance between the dashed
lines represents one year, during which the Tridacna grew. (b) Under the microscope,
daily increments (a dark coupled with a bright increment) are smaller when
temperature is cold but larger when temperature is higher. (c) Growth rates
(line 2 in Fig. 1c) in fossil Tridacna A5.
The SST observation in the Xisha Islands suggested that the first r month
nearly corresponds to the lowest SST. Thus, the highest δ18O of
each cycle was chosen as the beginning of a year.
DiscussionRelation of SST, SSS, and <inline-formula><mml:math id="M132" display="inline"><mml:mrow class="chem"><mml:msup><mml:mi mathvariant="italic">δ</mml:mi><mml:mn mathvariant="normal">18</mml:mn></mml:msup><mml:mi mathvariant="normal">O</mml:mi></mml:mrow></mml:math></inline-formula> of modern <italic>Tridacna</italic>
Previous studies have demonstrated that Tridacna is in oxygen isotopic equilibrium
with the surrounding seawater (Aharon, 1983;
Watanabe et al., 1999), which also holds true for Tridacna in the South China Sea
(Yan et al., 2013). Biogenic carbonate
δ18O values show linear correlations with SST and seawater
δ18Owater
(Aharon
and Chappell, 1986; Pätzold et al., 1991; Romanek and Grossman, 1989).
The δ18Oshell–SST–δ18Owater Eq. (1) of
Grossman and Ku (1986) is adopted, as it is widely used in calculations for
tropical aragonite mollusk species. Meanwhile, δ18Owater
has a positive relationship with SSS, and Eq. (2), which was established
using seawater in the northern South China Sea (Hong et al., 1997), is
chosen for the calculation. We merge Eqs. (1) and (2) into δ18Oshell–SST–SSS (Eq. 3) to roughly simplify the environmental
control on the δ18Oshell.
1SST(∘C)=21.8-4.69(δ18Oshell-δ18Owater)2δ18Owater(‰)=0.23×SSS-7.583SST(∘C)=-13.75-4.69×δ18Oshell+1.08×SSS
The δ18Oshell reflects a combination of SST and SSS
variation. In order to quantify more precisely the relation between those
factors and δ18Oshell, two δ18O profiles are
calculated (Fig. 4a): δ18OSST (constant SSS but varying
SST) and δ18OSSS (constant SST but varying SSS). For the
purpose of minimizing the influence of extreme values, mean r-monthly
δ18O profiles (δ18OYX1, δ18OSST, and δ18OSSS) are used for the comparison. The
results show that δ18OYX1, δ18OSST, and
δ18OSSS profiles are in the range of -0.57‰ to -1.52‰, -0.48‰ to -1.58‰, and -1.07‰ to
-1.19‰, respectively. It is obvious that δ18OYX1 and δ18OSST show the same trend and are
highly correlated (r=0.91, n=7; r=0.78, n=77), but the
variation range in δ18OSSS is only 14 % of δ18OYX1. Therefore, this indicates that the δ18Oshell in the Xisha Islands corresponds predominantly to
seasonal SST variation. In addition, the calculated δ18Opredicted (by using both local actual SST and SSS) was used to
compare with δ18OYX1 (Table S1 in the Supplement). The δ18OYX1 and δ18Opredicted profiles have nearly
the same mean value (1.15 ‰ and 1.14 ‰, respectively), and their positive correlation (r=0.81, n=77) indicates that the local Tridacna precipitates its shell in oxygen
isotopic equilibrium.
(a) Predicted r-monthly δ18O profiles under constant
SSS (blue line) and constant SST (green line) conditions, and δ18O of YX1 (red line). Dotted lines represent the maximum and minimum
of the r-monthly δ18O profiles. (b)r-monthly δ18OYX1 and δ18Opredicted. The (c)r-monthly δ18OYX1 and δ18OA5, and the dotted lines
represent mean values. (d) Different insolation 3700 years ago and in the
past 100 years. (e) Mean seasonal cycles of reconstructed SSTA5 and
North Reef SST. (f) Different SST profiles: predicted SST with varied SSS
(blue line), constant SSS (green line), and actual SST (red line),
respectively.
Moreover, the comparison of predicted SST (under constant SSS and actual SSS
with δ18OYX1) further confirms that the SSS variation has
no significant effect on the local reconstructed SST (Fig. 4f). The two
predicted SST values were highly similar (r=0.93), and they are well
correlated with the actual SST (rvary=0.79, rconstant=0.78). Thus, we can use δ18Oshell to roughly estimate the
seasonal local SST variation and to establish a new SST–δ18Oshell linear regression: SST (∘C) =22.69-4.41×δ18Oshell (or δ18Oshell
(‰) =-0.136×SST+2.634). A 1 ‰ change of δ18Oshell is roughly equal
to 4.41 ∘C of SST. Yu et al. (2005b) summarized many published δ18O–SST slopes for another marine carbonate species, Porites lutea coral, and
suggested that the slopes could range from -0.134 to -0.189. Corals from
Hainan Island revealed good δ18O vs. SST correlation, with a
linear regression slope of -0.137 (Su
et al., 2006), very similar to our result (-0.136). Consequently, use of the
new linear regression for reconstructing the past SST with the fossil
δ18Oshell is a valid approach.
Indication of seasonal variation in modern <italic>Tridacna</italic>
According to δ18OYX1 (-0.60 ‰ to -1.52 ‰) and δ18Opredicted (-0.47 ‰ to -1.57 ‰) profiles (Fig. 4b), seasonality is shown with the lowest value occurring
in the first r month (cold season) and the highest value in the fourth
r month (warm season). The difference in seasonality between δ18OYX1 and δ18Opredicted is 0.18 ‰, which accounts for 19 % of δ18OYX1. This situation may be due to the different growth rates
and equidistance sampling mode. In each year, the analyzed Tridacna grew faster in
warmer seasons than in colder seasons; thus, specimens under equidistance
sampling mode have more samples in the warm seasons. Fewer points in the
cold seasons decrease the values and lead to a lower δ18Oshell in the first r month, but the higher number of points
makes δ18Oshell close to δ18Opredicted in
the warm seasons (nearly identical in the fourth r month). Moreover,
throughout the life of the analyzed Tridacna, the δ18Oshell yearly
amplitude increasingly approaches the actual δ18Opredicted when using a greater number of points (fast growth
rate) before reaching maturity. After the Tridacna reached maturity, the fewer
points obtained under equidistance mode in a year yielded a lower amplitude.
This can explain the minor discrepancy between δ18Oshell
and δ18Opredicted. As a result, δ18Oshell slightly reduced the actual seasonal variation. However,
the correlation between them is high (r=0.81, n=77), and the mean
δ18OYX1 (-1.15‰) and mean δ18Opredicted (-1.14‰) values are similar.
Therefore, δ18Oshell can also be used to estimate the
actual seasonal variation, with caution regarding the slightly reduced
variation.
The fossil Tridacna lived 3700 years ago during the early Meghalayan. The 40 δ18OA5 cycles reveal that Tridacna A5 had probably lived for at least 40 years. After calculating data into r-monthly average profiles, the extreme
seasonal variation effects were minimized. The mean δ18OA5
is -1.34 ‰, with a minimum and maximum of -1.66 ‰ and
0.66 ‰, respectively (Fig. 4c). Contrasting with the
mean value of YX1 (-1.15 ‰), the lower δ18OA5 mean value may have reflected the higher temperature that
Tridacna A5 experienced during the warmer season. To translate into SST (without
considering the SSS changes), the temperature was estimated to be roughly
0.84 ∘C higher than the present. This agrees with other lines of
evidence that suggest a higher temperature during that period
(Ouyang
et al., 2016), considered to be part of the Holocene megathermal in China
(Shi et al., 1994).
Reconstructed SST around 3700 years ago (red), compared with the
North Reef SST from 1982 to 2017 (blue). Dotted lines represent the average
maximum and minimum SST. The gray field represents extreme El Ninõ
winter events.
The average r-monthly seasonal range of this period (1 ‰) is similar to that yielded from YX1 (0.92 ‰). The SDs
of δ18OA5 (0.38 ‰, n=281) and
δ18OYX1 (0.35 ‰, n=77) are also
similar. These results show similar climate change 3700 years ago and in the
present. However, the life of Tridacna YX1 (11 years) was much shorter than the
fossil Tridacna (which lived for at least 40 years), and YX1's location is in the
south of A5's location; thus modern observation data from the North Reef were used
to do the climatic comparison. After translating δ18OA5
into SST (Fig. 5), the reconstructed SST shows an average maximum and
minimum of 30 and 25.61 ∘C, respectively, with a
seasonal variation of 4.39 ∘C (Fig. 4e). Comparatively, the
r-monthly average range of modern observation is 29.33 to 23.99 ∘C (from 1982 to 2017), with a seasonal variation of 5.34 ∘C (Fig. 4e). The warmer climate in the past, associated with seasonality variance,
is about 0.95 ∘C lower. Considering the seasonality discrepancy
between δ18Oshell and δ18Opredicted, the
δ18Oshell has a 19 % lower seasonal variation than
δ18Opredicted. Therefore, the actual seasonal variation of
A5 (roughly 5.23 ∘C) is still below present seasonality.
In addition, the discrepancy between mean δ18OA5 and mean
δ18OYX1 is 0.19 ‰; the lower mean
δ18OA5 is because of more r months in lower values. This
reveals a possible prolonged high-temperature period 3700 years ago: warm
seasons may have been longer, while cold seasons may have been shorter. This
agrees with a comparison between 3700 years ago (3722 to 3623 BP) and the
past century (1918 to 2017), which indicates Tridacna A5 lived in more insolation.
This occurs from the second to fifth r month (warm seasons); however, less
insolation occurs in the rest of the months (Fig. 4d). Thus, the prolonged
high temperature in the past might be attributed to more insolation. In
addition, although a higher sampling density obtained in the warm seasons
enlarges the high-temperature period (from the second to sixth r month), a
cold-to-warm transition could still be recognized in A5 and YX1 δ18O profiles (Fig. 4c). Comparison of each r-monthly value with the
average value shows that between the first and second r month, there was a larger
deviation with a greater slope 3700 years ago. This illustrates a fast
transition between cold and warm seasons 3700 years ago. As δ18Opredicted has stronger seasonal variation than δ18Oshell, the slope should be sharper, which means more
significant actual seasonal transition.
Overall, the climate around 3700 years ago had slightly lower seasonality
than the present, and the transition between cold and warm seasons was
starker.
SST anomalies of modern instrumental data and reconstructed SST
anomalies of Tridacna A5 under r-monthly (a) and r-annual (b) resolution. Dotted
lines represent a standard deviation (1σ) of SST anomalies.
Climate variation comparison between 3700 years ago and present
A comparison was performed between the modern instrumental observations
(from 1982 to 2017) in the North Reef and the reconstructed SST anomalies of
Tridacna A5. The r-monthly resolution data were first compared, obtained by
subtracting the r-monthly SST with the mean value of each r month. In terms
of long-term climatic variation, the SST anomalies are markedly different
between the 36-year modern instrumental data and the 40-year reconstructed
data (Fig. 6a). The SST anomalies (3700 years ago) have sharper peaks and a
greater amplitude than in those of recent years, and the SD in the past is
much larger (0.68 ∘C) than in the present (0.42 ∘C),
suggesting more severe climate conditions in the past. However, the
deviation should be noted alongside the different growth rates during
Tridacna's life span and in equidistant sampling mode. For example, Tridacna may have
different annual growth rates; hence an r-monthly value may not represent
the corresponding actual r-monthly value under equidistant sampling mode. In
this respect, the r-annual SST anomalies are estimated to reduce the
deviation (Fig. 6b). The SD of modern observation SST anomalies is 0.30 ∘C, and the SD of reconstructed SST anomalies is 0.41 ∘C. This illustrates that the modern-to-past ratios of the r-monthly
resolutions or r-annual resolutions are almost the same (0.65 and 0.73,
respectively); thus the SD of r-monthly SST anomalies of Tridacna is likely a
reliable measure. As a result, the enhanced climate variability 3700 years
ago probably indicates increased ENSO-related variability in this region.
This conclusion contradicts data from samples (deep-sea sediments and fossil
mollusk shells) collected in the eastern tropical Pacific at the same time
period (Koutavas et al., 2012, Carré et al., 2014). More data should be
analyzed from long, successive time periods to understand more about the
dynamics of ENSO on a large scale.
ENSO activity recorded by <italic>Tridacna</italic> <inline-formula><mml:math id="M353" display="inline"><mml:mrow class="chem"><mml:msup><mml:mi mathvariant="italic">δ</mml:mi><mml:mn mathvariant="normal">18</mml:mn></mml:msup><mml:mi mathvariant="normal">O</mml:mi></mml:mrow></mml:math></inline-formula>
As ENSO is the strongest contributor to global interannual climate
variation, a better understanding of its fundamental properties will allow
us to better unravel past climate change episodes and to make more accurate
predictions for the future. Interannual climate changes in the Xisha Islands
were likely dominated by ENSO activity. The local accumulated positive
percentage of monthly SST anomaly threshold responds to 76.47 % El
Ninõ and 79.41 % La Niña events in the Ninõ 3.4 region
(Liu et al., 2016). Previous studies demonstrate
that marine biogenic carbonate-based SST reconstructions in the northern
South China Sea likely responded to ENSO activity
(Sun et al., 2005; Yan et al., 2017).
Warm (cold) SST anomalies are related to El Ninõ (La Niña) events.
Coral has one of the earliest records revealing ENSO events
(Peng
et al., 2003; Sun et al., 2005; Wei et al., 2007), yet there are still some
technical limitations in using coral, such as those concerning
post-depositional diagenetic alteration between aragonite and calcite
(McGregor and Gagan, 2003).
Analyses of Tridacna species are performed to overcome this limitation by taking
advantage of their denser shells, lack of diagenetic alteration, and oxygen
isotopic equilibrium with seawater. Recently, Yan et al. (2014) proved that
Tridacna species in the Xisha Islands respond to ENSO activity, and then they used fossil
Tridacna δ18O on Dongdao Island (part of the Xisha Islands) to
reconstruct the ENSO variability around 2000 years ago (Yan
et al., 2017).
Spectral analysis of the North Reef SST anomalies (a), Ninõ 1+2 SST anomalies (b), and reconstructed SST anomalies according to
δ18OA5(c). Green lines indicate significance at the 90 % confidence level, and the area between the two dotted lines represents
the frequency of 3 to 7 years.
To acquire more precise ENSO reconstructions, modern observation data were
analyzed and compared with the SST in Ninõ 1+2 region. The SST
anomaly series were calculated by subtracting the r-monthly mean values. The
spectral analyses were performed to test periodicity among all SST anomalies
(Fig. 7), which indicate a spectral peak of 3 to 7 years. According to the
SST series, the North Reef SST has a 3-r-month time lag behind the Ninõ
1+2 SST (Fig. 8a), and thus 3 r months of the North Reef SST were
brought forward to eliminate the lag. To reconstruct the occurrence of ENSO
in the North Reef, 3–7 years of bandpass filtering was performed on the SST
anomalies, which yielded North Reef ENSO activity mostly consistent with the
Ninõ 1+2 SST anomalies (Fig. 8c). A threshold value was calculated
under 1σ SST anomalies for moderate El Ninõ–La Niña events.
A total of 7 El Ninõ and 10 La Niña events occurred in the past
36 years. In other words, El Ninõ–La Niña events occurred
successively at a 5.14-year frequency in the North Reef.
Relationship between Ninõ 1+2 SST and the North Reef SST:
(a) the North Reef SST (blue line) compared with Ninõ 1+2 SST
(yellow line); a clear time lag exists. (b) SST anomalies of two areas; the
lag is removed by forwarding the North Reef SST anomalies for 3 r months.
(c) The North Reef SST anomalies were performed with 3–7 years of bandpass
filtering, consistent with Ninõ 1+2 SST anomalies; the dashed lines
show the calculated threshold limits (1σ) for ENSO activity in the
North Reef. El Ninõ and La Niña events are represented by positive
and negative SST anomaly values, respectively.
(a) ENSO activity reconstructed by the fossil Tridacna 3700 years ago:
δ18O anomalies of fossil Tridacna A5. (b) The North Reef SST anomalies
calculated by δ18O anomalies, based on modern Tridacnaδ18O–SST equation (1 ‰ δ18Oshell≈4.41∘C SST). (c) ENSO activity according to the North
Reef SST anomalies after 3–7 years of bandpass filtering; the dashed lines
show the calculated threshold limits (1σ) for ENSO activity.
Spectral analysis revealed that δ18OA5 anomalies also have
a 3–7-year period (Fig. 7c). As discussed above, the Tridacnaδ18O
values are mainly dominated by SST in the Xisha Islands, and 1 ‰ δ18Oshell is roughly equal to 4.41 ∘C of SST. δ18OA5 anomalies were transformed
into the North Reef SSTA5 anomalies (Fig. 9b). After the 3–7 years of
bandpass filtering of the North Reef SSTA5 anomalies, six El Ninõ
and five La Niña events were estimated to occur over 40 years with a
1σ SSTA5 anomaly threshold (Fig. 9c), giving a 6.67- and
8-year frequency, respectively. The ENSO frequency is reduced when compared
with modern observation data. The lower frequency is supported in ENSO
reconstructions back to 7 ka, which suggest a notable reduction of ENSO
between 5 and 3 ka
(Liu
et al., 2013; McGregor et al., 2013; Tudhope et al., 2001; Emile-Geay et
al., 2016). However, implications drawn from a mere 40-year-long Tridacnaδ18O record are likely inconclusive. A collection of more similar-aged
Tridacna is needed to develop a more continuous climate and ENSO activity record in
Holocene.
Extreme winter El Ninõ records in fossil <italic>Tridacna</italic> <inline-formula><mml:math id="M391" display="inline"><mml:mrow class="chem"><mml:msup><mml:mi mathvariant="italic">δ</mml:mi><mml:mn mathvariant="normal">18</mml:mn></mml:msup><mml:mi mathvariant="normal">O</mml:mi></mml:mrow></mml:math></inline-formula> values
In recent decades, extreme El Ninõ has brought about many climatic
disasters, such as catastrophic flooding, bushfire and drought
(Ramírez
and Briones, 2017; Staupe-Delgado et al., 2018; Yu et al., 2018,
2019). With global warming persisting, the question of whether high
temperatures are related to extreme El Ninõ events is still
controversial. Therefore, records of extreme El Ninõ events in past warm
periods are important. Here, the winter SST is used to estimate extreme El
Ninõ events. Winters in the northern South China Sea are very dry, and
the SSS variation caused by rainfall is small. Thus, the SST determined from
δ18Oshell should be close to the actual value. The SST
calculated by δ18OYX1 reveals a warmer winter in 1998,
corresponding to a stronger El Ninõ that year. A comparison between the
reconstructed SST (calculated with δ18OA5) and modern
observation data from the North Reef (Fig. 5) suggested that the average
winter SST 3700 years ago was 25.62 ∘C. There are six distinctly
high SSTs within the 40 years (gray fields in Fig. 5), with anomalies ranging
from 0.73 to 2.00 ∘C. As for the SST of modern observations (from
1982 to 2017), the average of winter SST is 23.99 ∘C, and three
anomalously warm temperatures vary from 0.60 to 1.38 ∘C. It seems
that extreme El Ninõ winter events were very frequent in this past warm
period. However, this analysis still provides low confidence in answering
this controversial question about the relationship between El Ninõ
events and warm climate; more Tridacna in the past warm period should be analyzed in
future work. Nevertheless, our results still put forward high-resolution
data that make a contribution to future work on how El Ninõ events occur
in warm periods.
Conclusions
The δ18O values derived from Tridacna provide high-resolution data, useful to
unravel climatic variability and ENSO activity. In the Xisha Islands of the
northern South China Sea, the δ18Oshell of modern
Tridacna gigas can serve as a proxy for SST, while SSS has a minor effect on the δ18Oshell. Thus, a rough δ18O–SST linear regression
is established: SST (∘C) =22.69-4.41×δ18Oshell. Another Tridacna squamosa A5, which lived 3700 years ago, reveals 40
clearly dark–bright line couples consistent with δ18Oshell
profiles. Reconstructed SST implies a warmer climate 3700 years ago, 0.84 ∘C higher than the present. The seasonal variation slightly
decreased, and the transition among cold to warm seasons was faster. The
combinations of SST anomalies reconstructed at r-monthly–r-annual resolution
suggest enhanced ENSO-related variability during this past warm period. In
addition, the frequency of ENSO activity was less 3700 years ago than during
the recent 36 years of modern observations. El Ninõ–La Niña events
occurred alternatively at a frequency of every 6.67 and 8 years in the past,
compared to every 5.14 years in recent decades. Extreme El Ninõ winters
have been recorded by a fossil Tridacna with increased numbers and intense
variations. Our results imply an unstable climate 3700 years ago, although
more data are still needed to support this hypothesis.
Data availability
All data can be acquired in the Supplement. Some of meteorological data are deposited at the NOAA website (http://www.cpc.ncep.noaa.gov/data/indices/sstoi.indices, last access: 31 December 2017). The dating result of Tridacna is calibrated by CALIB 7.10 Radiocarbon Calibration (http://calib.org, Stuiver et al., 2018). Correspondence and requests for materials should be addressed to Xiaoming Sun (eessxm@mail.sysu.edu.cn) and Hong Yan (yanhong@ieecas.cn).
The supplement related to this article is available online at: https://doi.org/10.5194/cp-16-597-2020-supplement.
Author contributions
XS, HY, and YH designed the research and experiments; HY
collected the samples; HC and YH performed stable isotope
measurements. HY and YH did the data analyses. YH wrote the
manuscript, with the help of all co-authors.
Competing interests
The authors declare that they have no conflict of interest.
Acknowledgements
We are grateful to Yu Fu, Yang Lu, Jiaoyang Ruan, Chengcheng Liu, Tianjian Yang, and Jun Gu for their support in preparing the manuscript. Youfeng Ning, Hanying Li, Pengfei Duan, and Jingyao Zhao are thanked for their technical support in drilling and analyses at Xi'an Jiaotong University.
Financial support
This research has been supported by the National Key R&D Program of China (2018YFA0702605), the National 13th Five Year Plan project (DY135-R2-1-01, DY135-C1-1-06), National Nature Science Foundation of China (41876038, 41877399, 91128101, 41888101), State Key Laboratory for Mineral Deposits Research in Nanjing University (no. 20-15-07), Chinese Academy of Sciences (QYZDB-SSW-DQC001), and the Qingdao National Laboratory for Marine Science and Technology of China (QNLM2016ORP0202).
Review statement
This paper was edited by Denis-Didier Rousseau and reviewed by two anonymous referees.
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