Holocene ENSO-related cyclic storms recorded by magnetic minerals in speleothems of central China

Soil-Derived Magnetic Minerals in Stalagmite HS4 and Their Hydrological Implication

Magnetite, goethite, and hematite/maghemite were identified in our samples. Coercivity unmixing analyses were conducted on specimens from stalagmite HS4 by alternating field (AF) demagnetization of an isothermal remanent magnetization (IRM_1.15T) induced by a 1.15-T direct current (dc) field (Methods). For each sample, ∼90% of the IRM_1.15T is carried by a mineral population with an ∼20-mT median destructive field (MDF) and a dispersion parameter (DP) of ∼0.4 (Fig. 2). A small proportion (<4%) of the total remanence is carried by a lower coercivity, or magnetically very “soft,” component with an MDF < 5 mT (Fig. 2), which is likely to be coarse, multidomain magnetic particles. Magnetic particles were extracted from stalagmite HS4 for more detailed mineralogical analyses, including low-temperature magnetic measurements and electronic microscopy (Methods). The presence of magnetite in HS4 was confirmed in all of the magnetic extracts by observation of an abrupt decrease in magnetization at ∼120 K, identified as the Verwey transition, during low-temperature cycling of thermal remanent magnetization (TRM) (Fig. S1). Low-temperature magnetometry also provided evidence for the presence of high-coercivity goethite and hematite/maghemite in the Heshang specimens (Fig. S1).

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Fig. 2.

Magnetic components in soil and stalagmites. Shown are d+ex, detrital magnetite transported by flowing water and organically formed extracellular, ultrafine magnetite (13) (gray squares); P, pedogenic magnetite observed in the United States (13) and China and Switzerland (13, 14) (blue squares and triangles); the “soft” component from stalagmite BCC-010 (11) (green circles); and the “soft” component from stalagmite HS4 (red circles) and soil capping Heshang Cave (orange squares) (this study). Horizontal and vertical axes represent the MDF and DP, respectively.

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Fig. S1.

Low-temperature behavior of magnetic extracts from stalagmite HS4 specimens. We used a four-stage protocol that allows distinguishing of remanence held by goethite and hematite from that held by magnetite (51). In the first stage, a TRM was imparted to each specimen at a 2.5-T dc field during a circle warming from 300 K to 400 K and then cooling from 400 K to 300 K. Then the remanence of each specimen was measured during thermal cycling in a zero field environment from 300 K to 10 K and back to 300 K (“TRM_Cooling” and “TRM_Warming”). This remanence represents the combined contributions from goethite, hematite, and magnetite. In the second stage, the sample was removed from the MPMS and demagnetized using an AF with a peak intensity of at 200 mT to remove nearly all of the remanence carried by magnetite. In the third stage, the specimen was inserted into the MPMS again, and its remanent magnetization was measured during thermal cycling in a zero-field environment from 300 K to 10 K, and then warmed to 400 K (“Magnetite off_Cooling” and “Magnetite off_Warming”). This stage measures the remanence of goethite and hematite, and then ultimately demagnetizes any goethite in the sample by warming from 300 K to 400 K. In the fourth stage, the specimens were measured at zero field during cooling from 400 K to 10 K and then warming to 300 K (“Goethite off_Cooling” and “Goethite off_Warming”). M_magnetite, M_goethite, and M_{hematite (maghemite)} indicate the magnetic remanence carried by magnetite, goethite, and hematite (probably company with maghemite), respectively. Strong particles extracted from the sample with (A) high, (B) low, and (C) medium IRM_soft-flux values.

Soft magnetic components in our samples were demonstrated to be of soil origin, on the basis of their mineralogy, magnetic coercivity distribution, and morphological characteristics. The coercivity distribution of the dominant soft magnetic component (MDF ≈ 20 mT and DP ≈ 0.4) is characteristic of pedogenic magnetite (13, 14), which is commonly transported into caves via drip water and preserved in stalagmites (9, 11) (Fig. 2). The pedogenic magnetite and very soft magnetic component that together dominate the HS4 stalagmite samples were also identified in the soil samples collected immediately above the cave, contributing more than 80% and less than 1.5% of the total IRM_1.15T, respectively. The ratio of the remanence held by the very soft component to that held by pedogenic magnetite is the same in both stalagmite HS4 and the soil samples (∼0.2), supporting a soil origin for the soft magnetic minerals in HS4. In contrast, the remanence properties of the carbonate rock that hosts Heshang cave were dramatically different. Less than 20% of the IRM_1.15T of the host rock was demagnetized after a 100-mT AF demagnetization. The bedrock is therefore dominated by higher coercivity, magnetically “hard” magnetic minerals with MDF > 100 mT, such as goethite and/or hematite, and is unlikely to be a primary source of soft magnetic minerals to the speleothems in Heshang cave. Furthermore, most of the extracted magnetite grains show evidence of transport and weathering processes, including partially rounded shapes, and etch pits, with an absence of euhedral magnetic grains (Fig. S2), indicating that the magnetite preserved in stalagmite HS4 is likely allochthonous rather than precipitating in situ (9, 15, 16). In addition, based on the past 9 y of in situ monitoring, the pH value of the drip water is always lower than 8.5, and the air temperature of the cave is constantly higher than 15 °C, conditions that are unfavorable for the formation of authigenic magnetites (ref. 16 and references therein). Together, these lines of evidence strongly suggest that the soft magnetic components (mainly magnetite) preserved in stalagmite HS4 are soil-derived.

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Fig. S2.

SEM and TEM micrograph of magnetic minerals extracted from stalagmite HS4. (A−D) SEM micrographs and EDS spectrums of extracted magnetite particles with etch pits and plumose textures. No evidence of shrinkage cracks associated with maghemitization are present. (E−H) TEM micrographs. (E) Needle-like particles with absorbed, nanometer-scale, Fe-oxide minerals. (F) Needle-shaped goethite and irregularly shaped nanometer particles. (G) An ∼1-μm, rounded magnetite with ∼200-nm minerals adhering to its surface. (H) Irregularly shaped, <100-nm particles in a clay-rich matrix.

Increased rainfall can enhance the production of pedogenic magnetite in soil (17), and it promotes the transportation of soil magnetite into the cave via drip water. Discrete intervals with enhanced concentrations of soil-derived particles, including magnetite, in speleothems can be associated with episodic enhanced rainfall (18). We therefore interpret variations in the concentration of soil-derived magnetite identified in the HS4 stalagmite to be indicative of rainfall variability. The amount of soil-derived, soft magnetic minerals (i.e., magnetite and its partially oxidized equivalents) in HS4 can be assessed by measuring |IRM_soft| [defined as 0.5 × (|IRM_1T|+|IRM_-0.3T|); Methods]. This measurement excludes the portion of IRM_1T contributed by hard magnetic minerals that originated from the surrounding rocks and authigenic goethite, because hard magnetic minerals such as hematite and goethite are unlikely to be remagnetized by a 300-mT dc field (8). We use the parameter IRM_soft-flux, whereby |IRM_soft| values are normalized by the growth duration of each sample, to trace the variation in the flux of the soft, soil-derived magnetite particles per year.

Although IRM_soft-flux can be a proxy for long-term paleoprecipitation, where higher values are associated with increased rainfall and wetter intervals, it may also record discrete high-intensity precipitation events. In contrast to pedogenic processes that slowly increase the amount of pedogenic ferrimagnetic minerals within soils, large storms can dramatically increase the energy of groundwater in karst regions within a very short time, causing an abrupt increase in the transportation of heavy minerals to the cave system and, in turn, an abrupt increase in the amount of allochthonous particles preserved in stalagmites. We therefore relate abrupt enhancements in IRM_soft-flux to increases in magnetite flux resulting from an increased frequency of extreme precipitation events such as storms.

Long-Term Hydrological Variation and Storms

The mean IRM_soft-flux is relatively low (5.3 × 10⁻¹⁰ Am²⋅y⁻¹) between 6.7 ky and 3.4 ky, compared with higher values (14.9 × 10⁻¹⁰Am²⋅y⁻¹) before 6.7 ky and after 3.4 ky (Fig. 3A). This three-interval pattern is in good agreement with local water levels recorded by the accumulation rate of aerobic hopanoids in Dajiuhu peatland, a site about 120 km north of Heshang cave (7) (Fig. 3C). The two wet periods (before 6.7 ky and after 3.4 ky) also agree well with the highest lake water level in the middle and lower reaches of Yangtze River, which occurred between 8.0 ky and 7.0 ky and after 3.0 ky (19). The carbon isotope composition of the soil-derived acid-soluble organic matter (δ¹³C_ASOM) in the HS4 stalagmite (Fig. 3B and ref. 20) also records a pattern comparable to IRM_soft-flux on a millennial scale, with less negative δ¹³C_ASOM values during the two wet periods. These consistencies between the three different records suggest that IRM_soft-flux is a reliable and accurate indicator of regional hydrological changes in central China throughout the Holocene.

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Fig. 3.

Hydrological conditions in central China and ENSO strength. (A) IRM_soft-flux in stalagmite HS4. Peaks in IRM_soft-flux indicate intervals with increased extreme precipitation events (this study), numbers 1 through 10 indicate the flooding events reported near the research area (23⇓⇓⇓⇓–28). U−Th dating errors (12) are shown on the top of IRM_soft-flux curve as red line segments. (B) The carbon isotope composition of the acid-soluble soil-derived organic matter (δ¹³C_ASOM) of HS4 stalagmite. Although affected by multiple factors, more (less) negative δ¹³C_ASOM was correlated with dry (wet) climate (20). (C) Hopanoid accumulation rate in Dajiuhu peatland. High (low) accumulation rates correlate with dry (wet) intervals (7). (D) Simulated ENSO amplitude in 100-y window based on observation data [shown as SD of Nino3.4 (a region bounded by 5°N to 5°S, from 170°W to 120°W) interannual (1.5 y to 7 y) sea surface temperature variability] (39). (E) Observed ENSO variability from stalagmite BA03 (open squares) (33) and foraminiferal δ¹⁸O (open circles) (34). BA03 δ¹⁸O values are calculated based on the SD of the 2- to 7-y band in overlapping 30-y windows and indicate the ENSO variance in WPWP region. Foraminiferal δ¹⁸O is retrieved from deep-sea sediments in core V21-30 located at EEP region (cold tongue of ENSO activity), and is established on single tests in each 1-cm stratum with an age uncertainty of several hundred years (34). The question mark indicates a questionable δ¹⁸O value at 7.0 ky (mentioned in ref. 34). Comparison of peaks in IRM_soft-flux and ENSO variance are indicated by gray bars. Vertical yellow bar indicates the regional dry period (6.7–3.4 ky).

A detailed comparison of the magnetic signals and oxygen compositions of carbonate from the HS4 stalagmite is shown in Fig. S3 and does not show any significant correlation. It is well known that δ¹⁸O in cave sediments is controlled by a variety of factors, including rainfall amount, cave temperature, local evaporation, the δ¹⁸O of the sources (the Indian Ocean or/and the West Pacific Ocean), and the transport distance from the sources (21, 22). Models and modern observations have shown that variations in vapor sources rather than in the precipitation amount (1) dominated the speleothems δ¹⁸O records in the East Asian monsoon (EAM) area (2⇓⇓⇓–6). Consequently, converting stalagmite δ¹⁸O records into a quantitative assessment of past rainfall amount, including that arising from typhoon sources, is very difficult in the EAM region (12), and it is therefore unsurprising that there is no significant correlation between the δ¹⁸O records and our magnetic signal.

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Fig. S3.

Comparison of IRM_soft-flux (red curve) and oxygen isotope sequences (blue curve, from ref. 12), both from stalagmite HS4. Error (2σ) of U−Th dating is shown as separate red segments at the top of the figure.

The IRM_soft-flux record shows pulses of abrupt, centennial-scale enhancement throughout the HS4 stalagmite. These abrupt enhancements are particularly strong during the two wet intervals (after 3.4 ky and before 6.7 ky), and are subdued during the dry interval between them. We interpret these pulses of enhanced IRM_soft-flux to represent intervals of increased storm frequency/strength. For comparison, we compiled previously published histories of flood deposits preserved in the middle reaches of Yangtze River, and 10 paleoflood events could be recognized during the past 9.0 ky, occurring at 9,000–8,400 y B.P. (23, 24), 7500–7200 y B.P. (25), 5500–5000 y B.P. (26), 4200–4000 y B.P. (23, 27), 3200–2800 y B.P. (23⇓–25), 2600–2200 y B.P. (28), 1900–1700 y B.P. (23, 27), 1200 y B.P. (28), 1000–800 y B.P. (26, 28), and 590 ± 50 y B.P. (28), respectively. These paleoflood events are identified in peaks in IRM_soft-flux in Fig. 3A and indicate periods of elevated precipitation (23, 25, 28). Extreme paleofloods became more frequent after 2.2 ky and reached a maximum frequency between 1.0 ky and the present day (29), coincident with the two highest pulses of the IRM_soft-flux value of HS4 stalagmite. In contrast, the pronounced aridity event induced by the abrupt cooling event in the North Atlantic region at 8.2 ky (30) is coincident with the weak IRM_soft-flux value of HS4 stalagmite. The δ¹³C_ASOM exhibits a similar variance to IRM_soft-flux on a millennial scale, but not on a centennial scale; this may be due to the effects of temperature and vegetation on δ¹³C_ASOM in addition to precipitation (20).

Close Correlation Between El Niño−Southern Oscillation and Storms in Central China

The occurrence of modern-day storms in the middle reaches of Yangtze River is related to the strength of El Niño−Southern Oscillation (ENSO) (31), especially the El Niño events (32). Although paleo-ENSO records are difficult to reconstruct, particularly in the early Holocene (33−35), our IRM_soft-flux record appears to be consistent with paleo-ENSO proxies available for the Holocene. Geological data and climate models document a mid-Holocene reduction in ENSO intensity and fewer El Niño-related flood events (33, 34, 36⇓–38) (Fig. 3 D and E). This finding is consistent with lower IRM_soft-flux values, which indicates fewer storms between 6.7 ky and 3.4 ky. Although the Holocene ENSO might show different spatial patterns (36), δ¹⁸O variances of foraminifera (34) (open circles in Fig. 3E) and stalagmite BA03 (33) (open squares in Fig. 3E) support strong ENSO activity in both the eastern equatorial Pacific (EEP) and western Pacific warm pool (WPWP) regions during the early and later Holocene, which is broadly consistent with the frequent storms before 6.7 ky and after 3.4 ky indicated by the IRM_soft-flux record. Of particular importance is that, during the relatively strong ENSO periods (the early and later Holocene), IRM_soft-flux shows an increased frequency of enhancement pulses, and the peaks of IRM_soft-flux during those periods broadly correspond to the peaks of the observed and modeled ENSO variances in the EEP region (33, 39) (Fig. 3 D and E). This would suggest that stronger ENSO can increase the frequency of extreme precipitation events, such as storms, in central China.

Some discrepancies do exist between the two ENSO records (simulated and observed) and the storms inferred by our magnetic record, which might arise from limitations inherent within the simulated and observed ENSO records. The simulated ENSO variability is based on modern observations, which means that the simulation becomes less reliable with increasing age. It might provide a good comparison for variations in frequency, but modeled changes in the amplitude become less reliable with increasing age. This tendency explains why our magnetic record shows similar cyclic variation to the simulated ENSO record (39), but shows inconsistent amplitude variation, particularly in the early Holocene (Fig. 3D). Further, the previously published data for the observed ENSO record display a comparatively low temporal resolution and a large uncertainty in age (33, 34). The observed ENSO record cannot provide a detailed comparison, but it does show the same three-interval features observed in the magnetic data (i.e., elevated during 9–6.7 ky, and 3.4–0 ky, but decreased during 6.7–3.4 ky) (Fig. 3E). Finally, the compilation of flooding events (23⇓⇓⇓⇓⇓–29) in central China confirms the robustness of our magnetic profile as an ENSO record within the age uncertainties denoted in Fig. 3.

Five-Hundred-Year Periodicity of Storms and Its Forcing

Spectral analysis of the detrended IRM_soft-flux record and modeled ENSO variance data (from ref. 39) reveal that they both exhibit a centennial cycle centered at ∼500 y with a confidence level of greater than 99% (Fig. 4 A and B). The 500-y cycle is a significant component of solar activity periodic variations (40, 41) (Fig. 4C), which can control Earth surface temperature variability and alter atmospheric and oceanic circulation (42⇓⇓–45). The 500-y cycle of storms in central China is generally in an antiphase relationship with solar activity, indicated by the residual atmospheric Δ¹⁴C from global tree ring records (46) during the past 8.6 ky, where higher IRM_soft-flux values (representing storms) are associated with low solar irradiation (larger Δ¹⁴C). The correlation between 500-y periodic storms and the ENSO variance is positive in the wet periods (the early and later Holocene), but it changes to a negative correlation in the dry period (the mid-Holocene) when the ENSO is damped and in a more La Niña-like state according to the observed data (33, 34).

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Fig. 4.

Power analysis of IRM_soft-flux of HS4, ENSO variance, and solar irradiance parameter [residual atmospheric Δ¹⁴C from global tree ring records (46)]. (A−C) Power spectra of (A) IRM_soft-flux (this study), (B) ENSO variance (39), and (C) residual atmosphere Δ¹⁴C (46). Red, orange, and green dashed lines are 99%, 95%, and 90% confidence level (CL) respectively. (D) IRM_soft-flux (black), ENSO variance (blue), and residual atmosphere Δ¹⁴C (red) after 500-y band-pass filtering. Higher Δ¹⁴C values correspond to periods of lower solar activity.

Our results show that strong/frequent storms in central China are broadly consistent with weak solar irradiation as well as strong ENSO activities. Solar activity can modulate the EAM system and thereby affect precipitation in central China. Decreased solar irradiance can weaken the Asian summer monsoon (41, 43), which, in turn, could cause the convergence zone, the Mei-yu Front, where warm−moist, tropical−subtropical air meets the cooler continental air mass, to move southward toward the Yangtze River valley (47) and hover around this area. This southward movement could move preexisting storm centers closer to Heshang cave or, alternatively, increase the frequency of storms regionally. Although there are multiple controls on ENSO (39), its long-term variability is closely related to secular solar activity variations, and both the intensity and frequency of El Niño events, which result in flooding in east and central China (32), are high at secular solar minimum and low at secular solar maximum (48). Thus, solar radiation, ENSO activity, and coupled atmospheric−oceanic variation may therefore control the occurrence of ENSO-related storms in central China. The delayed response of storms in central China to the mature ENSO (48), and/or the different age modes of those two data series, could probably result in the small phase shift between ENSO variations and storms shown in Fig. 4D. Reduced ENSO activity during the dry mid-Holocene was not strong enough to affect the storms in central China, which might explain their weak relationship during this interval.