Low-latitude hydroclimate changes related to paleomagnetic variations during the Holocene in coastal southern China

Abstract

The variations in precipitation have displayed a complex pattern in different regions since the mid-to-late-Holocene. Cloud formation processes may have a significant impact on precipitation, especially during the tropical marine processes and summer monsoon which convey abundant water vapor to coastal southern China and inland areas. Here, we use two 7500 year sedimentary records from the Pearl River Delta and the closed Maar Lake, respectively, in coastal southern China to reconstruct the mid-to-late-Holocene humidity variability and explore its possible relationship with cloud cover modulated by the Earth’s magnetic fields (EMF). Our proxy records document an apparent increase in wetness in coastal southern China between 3.0 and 1.8 kyr BP. This apparent increase in humidity appears to be consistent with the lower virtual axial dipole moments and, in turn, with a lower EMF. This correlation suggests that the EMF might have been superimposed on the weakened monsoon to regulate the mid-to-late-Holocene hydroclimate in coastal southern China through the medium of galactic cosmic rays, aerosols, and cloud cover. However, further investigations are needed to verify this interaction.

Graphical abstract

Keywords

hydroclimate variations / Earth’s magnetic field / coastal southern China / the Holocene epoch

1 Introduction

Coastal southern China, which receives the oceanic moisture signal earlier when the Asian summer monsoon (ASM) blows inland toward China, has more complex hydroclimate patterns due to the superposition of the ASM and other low-latitude drivers. In particular, its hydrological conditions have differed significantly from the East Asian monsoonal precipitation variations since the Holocene. For example, the hydrologic conditions in coastal southern China showed a two-step increase in wetness during the middle to late Holocene (Yang et al., 2014), while most parts of the Chinese monsoon region showed a continuous decline in precipitation (Wang et al., 2005; Hu et al., 2008; Cai et al., 2010; Tan et al., 2018). The wet Little Ice Age in southern China is another major difference from the drier climate in central-northern China (e.g., Zhang et al., 2008; Yan et al., 2011; Zhang et al., 2018). These cases have led to the long-standing question of what drives the hydrological variability of coastal southern China to differ significantly from that of the East Asian monsoon region.

Recent studies have shown a significant positive correlation between aerosol, clouds, and precipitation (Pierce and Adams, 2007; Li et al., 2011; Campuzano et al., 2018; Jalihal et al., 2019; Liu et al., 2019). This is a fact that water vapor, whether carried by ASM or other drivers, inevitably forms clouds before falling to the ground as precipitation. Therefore, investigating the variation in cloud cover may help us more clearly to understand the mechanisms of hydroclimate change and the relationship between different driving forces. The process of cloud formation in the natural environment is affected by two factors, one is the content of water vapor and the other is the content of cloud condensation nuclei (CCN). The former is mainly transported by convection (e.g., ASM, ITCZ (intertropical convergence zone), ENSO (El Niño-Southern Oscillation)), while the latter is not only related to convection, but also contributes from some non-convective components. On the annual-decade scale, short-term wildfires and volcanic eruptions will release a large number of aerosol particles into the atmosphere (Robock and Outten, 2018; Jiang et al., 2020; Stenchikov, 2021). These aerosol particles increase the content of CCN in the atmosphere, which will increase precipitation after condensing with water vapor into raindrops. This also explains why heavy rainfall occurs after wildfires and volcanic eruptions. In addition, the variation of the non-convective CCN component may be related to the changes in the Earth’s magnetic field (EMF). The EMF can indirectly influence the content of non-convective components in the CCN and cloud formation process by regulating the flux of galactic cosmic rays (GCRs) entering Earth’s atmosphere (Dergachev et al., 2007; Kirkby, 2007; Knudsen and Riisager, 2009). Increased GCRs flux leads to increased atmosphere ionization and the nucleation rates of nanoscale particles, which can influence cloud formation when these nano-aerosols grow into CCN size (Carslaw et al., 2002; Kirkby et al., 2016; Svensmark et al., 2016; Svensmark et al., 2017; Cooper et al., 2021). However, the EMF modulation of climate on geological time scales has not been demonstrated and has long been debated due to the uncertainty of the forcing mechanism between them (Courtillot et al., 2007; Kirkby, 2007; Kerton, 2009; Knudsen and Riisager, 2009). Resolving Holocene hydroclimatic variations in coastal southern China will provide valid insights into the potential links among the EMF, cloud cover, and climate variation.

To explore potential links between low-latitude hydroclimate changes and the EMF during the Holocene, we constructed the mid-to-late-Holocene hydroclimate history. We did this at centennial-scale using the ratios of the relative content of hematite to the sum of hematite and goethite (I_Hm/(I_Hm + I_Gt) ratio) from the sediments deposited in the different environment. The formations of hematite and goethite in sediment are sensitive to hydrological variations and can reflect net precipitation (Long et al., 2011; Hyland et al., 2015; Zhang et al., 2020b). Therefore, the 7500 year I_Hm/(I_Hm + I_Gt) ratio profile in this study can fundamentally reveal the connections between EMF and hydroclimate at low latitudes.

2 Materials and methods

2.1 Materials and sampling

The Pearl River Delta stretches along the coastline of southern China between 21°40′ N and 23° N, and 112° E and 113°20′ E (Fig.1(a)). It is shaped by the interactions between rivers and the South China Sea during the Late Quaternary. The West River and North River deltas occupy 93.4% of the area. From its catchment, the West River carries a large amount of sediment, mainly terrestrial detritus, into the South China Sea. Huguangyan Marr Lake, situated ~340 km to the south-west of the Pearl River Delta, is 2.3 km² in area, and ~20 m deep. It is surrounded by a high tephra wall with a shoal extending from north to south in the middle. With no natural inflows or outflows, its water balance is primarily controlled by precipitation and groundwater.

The Da Ao (DA) core (22°26.08′ N, 113°13.81′ E, total core length of 37.73 m, Fig.1(b)) and Huguang Maar Lake (HML) core (21°9′ N, 110°17′ E, water depth of 11.5 m, total core length of 23 m, Fig.1(c)) were obtained from the lower West River Delta and Huguangyan Maar Lake by using a modified Livingstone piston corer in 2015 A.D. and 2012 A.D., respectively. Two cores were retained inside PVC tubes and transported to the laboratory after drilling and preserved at a low temperature (~4°C) until sampling. The two cores were both split into halves, and one half from each core was continuously sampled by pushing cubic plastic boxes (2 cm× 2 cm× 2 cm) into the split surface for environmental magnetism analysis. Paired powder samples were also collected for additional analysis after the box samples were collected. A total of 880 and 786 samples were obtained from the DA and HML cores, respectively. Samples for diffuse reflectance spectroscopy analysis were collected at 5 cm and 7 cm intervals from the DA core (543 samples) and the HML core (110 samples of the upper 5 m), respectively.

Dating samples of multiple materials (e.g., tree branches, leaves, plant fragments) were collected from the two cores and sent to three laboratories for accelerator mass spectrometry (AMS) radiocarbon dating. We also collected seven optically stimulated luminescence (OSL) samples and sent them to Qinghai Institute of Salt Lakes, Chinese Academy of Sciences, for OSL dating.

2.2 Experimental methods

Diffuse reflectance spectroscopy (DRS) was used to obtain the relative concentration of hematite (I_Hm) and goethite (I_Gt) and the I_Hm/(I_Hm + I_Gt) ratio. The DRS was conducted at the Geophysical Laboratory, Sun Yat-sen University, conducted on a PerkinElmer Lambda 950 spectrophotometer with a diffuse reflectance attachment (reflectance sphere) following the analytical protocols described in Zhang et al. (2020b). The data processing procedure followed Torrent and Barrón (2008) and Scheinost (1998).

Cubic samples (2 cm× 2 cm× 2 cm) were analyzed for the low-field magnetic volume susceptibility (κ) by using a Kappabridge MFK1-FA with a frequency of 976 Hz. A total of 880 and 230 were measured for the DA core and the upper 5 m of the HML core, respectively. Natural remanent magnetization (NRM) was stepwise demagnetized with 2G-760 system using peak fields of 0−80 mT (total of 12 steps). Anhysteretic remanence (ARM) was then imparted with a 0.05 mT steady field and an 80 mT alternating field. ARM was demagnetized and measured in 40 mT field. Isothermal remanence was imposed using a DC field of 1 T (SIRM) and 100 mT (IRM_−100mT). ARM and IRM were measured using JR6A Spinner Magnetometer. ARM and IRM were measured for all cubic subsamples of the DA core. Representative samples of the DA core (n = 4) were selected to perform rock magnetism analysis. Temperature-independent susceptibility (χ-T) curves were measured using the same Kappabridge magnetometer from room temperature to 700°C in an argon environment. The hysteresis loops and first-order reversal curves (FORCs) were measured using a Princeton Measurements Corporation vibrating sample magnetometer (MircoMag 3900). Hysteresis loops were obtained between −1 to 1 T with a field increment of 10 mT. The saturation magnetization (M_s), saturation remanence (M_rs), and coercivity (B_c) were obtained from the hysteresis loops. The coercivity of the remanence (B_cr) was determined using the demagnetized curve of M_rs. FORC measurements were conducted by 150 hysteresis loop curves with a 1 s averaging time and a field step of 2 mT and then processed with the FORCinel software v3.06 (Harrison and Feinberg, 2008). Natural remanent magnetization was performed at the Paleomagnetism and Geochronology Laboratory, Institute of Geology and Geophysics, Chinese Academy of Sciences, China. The other rock magnetism measurements were conducted at the Geophysical Laboratory, Sun Yat-sen University.

The bulk organic matter (δ¹³C) was also measured for the upper 27.3 m of the DA core (232 samples). After treatment with 5% HCl to remove carbonates, the bulk organic matter δ¹³C value was measured using a Finnigan MAT Delta Plus mass spectrometer coupled with a Flash EA 1112 elemental analyzer at State Key Laboratory of Organic Geochemistry, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, China. The isotopic values are presented in the standard δ-notation in per mil (‰) deviation from the Pee Dee Belemnite (PDB). Replicate analyses indicated that the analytical precision was better than 0.1‰.

2.3 Meteorological data and analytical methods

A variety of meteorological data are used in this paper. Monthly long-term mean temperature (CMA_tmp) and precipitation (CMA_pre) data (1981–2010) of Zhanjiang and Xinhui meteorological stations were obtained from the CMA Meteorological Data Centre (available at CMA website). The monthly long-term mean wind data (1981–2010) were obtained from the NCEP/DOE Reanalysis II data set with a 2.5-degree spatial resolution and 17 vertical levels (Kanamitsu et al., 2002). The long-term mean of monthly total precipitation (GPCC_pre) data (1981–2010) were obtained from the Global Precipitation Climatology Centre (GPCC) monthly precipitation data set (V2018) with a 0.5-degree spatial resolution (Schneider et al., 2018). The global monthly mean precipitation (CRU_pre), self-calibrating Palmer drought severity index (CRU_scPDSI), and cloud (CRU_cld) data (1901–2010) were obtained from CRU TS V4.03 climatic data sets, which have a 0.5-degree spatial resolution (Harris et al., 2020).

Air-mass back-trajectory analyses of the HML and DA cores in summer (June–July–August) were performed using the HYSPLIT V4.8 model and based on the NCEP/NCAR Reanalysis data set from 2009 to 2019 (Kalnay et al., 1996). The back trajectories were computed for a time period of 96 h (sampled four times per day at 00 UTC, 06 UTC, 12 UTC, and 18 UTC) and started at 1500 m above ground level. Similar trajectories were merged through cluster analysis.

3 Results

3.1 Modern climatology

The instrumental data show that the lower reaches of the Pearl River Delta and Huguangyan Marr Lake have a typical monsoonal climate, and approximately 75% of the annual precipitation is supplied between May and September (Fig.2(a) and 2(b)). Modern precipitation is mainly influenced by the East Asian summer monsoon (EASM) and the Indian summer monsoon (ISM; Fig.2(c)). The ocean-atmospheric circulations such as the Hadley circulation and the Walker circulation also have a significant influence on the region (Zhang et al., 2020a). The Air-mass back-trajectory analysis results for the HML and DA cores show that the water vapor of coastal southern China in summer is mainly transported from the South China Sea, the Indian Ocean, and the Western Pacific area by the EASM and the ISM (Fig.2(c)). The profiles of vertical velocity and meridional wind at 112.5°E show that there is an updraft over coastal southern China in summer due to the increased temperature of land (Fig.2(d) and Fig.2(e)). This updraft will impede most of the water vapor which is carried by ASM and other forcing, and force the remaining water vapor to rise higher and then migrate to inland regions. Therefore, the total precipitation in coastal southern China is higher than that in inland areas (Fig.2(c)). The pointwise correlation results between cloud cover and precipitation and scPDSI show that clouds play a non-negligible role in regulating precipitation in the monsoon region (Fig.2(f) and Fig.2(g)). The following connection can explain the relationship between cloud cover and precipitation: water vapor combines with cloud condensation nuclei (CCN) to form raindrops → large numbers of raindrops gather together and form clouds → raindrops fall to ground when the raindrops grow large (heavy) enough such that the clouds cannot carry them. Therefore, when there are more clouds, precipitation increases, and vice versa.

3.2 Chronology

The AMS dating results of the two cores are shown in Tab.1. All of the dates were calibrated using the IntCal 13 data set in the CALIB 7.04 program (Stuiver et al., 2020). In the DA core, six of seven OSL ages are in good agreement with the AMS ¹⁴C ages (Table S1), which further demonstrates the reliability and accuracy of the AMS ¹⁴C dating. The OSL ages were not considered when reconstructing the age-depth model. We assumed that −65 yrs. BP (2015 A.D.) and −62 yrs. BP (2012 A.D.) are the ages of the tops of DA and HML cores, respectively. The detailed age controls for cores DA and HML are based on a series of 14 AMS ¹⁴C ages and 4 AMS ¹⁴C ages, respectively. The age-depth models of two cores were developed using a Bayesian approach with the Bacon program (Blaauw and Christen, 2011). The age models show continuous sedimentation records without hiatuses in two cores, reaching back to 7.5 kyr BP and 8 kyr BP for the DA core and the upper 5 m of the HML core, respectively (Fig.3).

Age offsets arising from the radiocarbon reservoir effect in the different deposition environment is negligible to the chronology of two cores. In HML, the good agreement of AMS ages from multiple materials at the same depth is observed (the deviation is less than 100 years), indicating a negligible reservoir effect in this freshwater lake (Wu et al., 2012). In Pearl River Delta regions, a relatively low marine reservoir effect (∆R = −128 ± 40 years) is reported based on the average radiocarbon age of modern corals from Hong Kong, which indicate that the source waters entering the South China Sea are rather well equilibrated with atmospheric ¹⁴C (Southon et al., 2002). Therefore, the radiocarbon reservoir effect is minor and ignorable in two cores and does not affect the variation of climate proxies we discussed later at the centennial-scale.

3.3 Downcore variations of environmental proxies

Downcore variations of the κ, δ¹³C, I_Hm, I_Gt, and the I_Hm/(I_Hm + I_Gt) ratio of two cores are shown in Fig.4. The magnetic susceptibility of two cores was characterized by a two-stage change: a low value stage and a high value stage. The δ¹³C_TOC record from the HML lake (Liu et al., 2019) and δ¹³C record from the DA core show a consistent trend during the overlapping time interval. The relative hematite (I_Hm) and goethite (I_Gt) concentrations in two cores showed an increasing trend over the past 7.5 kyr BP (Fig.4), and a substantial increase was particularly displayed since ~2 kyr BP. The I_Hm/(I_Hm + I_Gt) profiles of the two cores also show consistent variations at the centennial-scale, which is supported by the results of the correlation analysis between the first principal component of two cores (Fig.1). The high value of magnetic susceptibility and the good positive correlation of I_Hm/(I_Hm + I_Gt) records in two cores during the past 2 kyr indicate that the influence of human activities on the amount of terrestrial input and the ratio of magnetic minerals in the sediments is negligible compared to natural processes.

4 Discussion

4.1 The paleoclimate significance of the ratio of hematite and goethite contents

The formation of hematite and goethite in soil and sediments varies with climate (Schwertmann, 1988). The formation of goethite and hematite is closely related to hydroclimate, with warm, dry climates favoring hematite formation and wet, cold climates favoring goethite formation (Schwertmann, 1988; Ji et al., 2004; Zhang et al., 2007). Therefore, ratios related to their concentration, such as Hm/Gt and I_Hm/(I_Hm + I_Gt), are often used as indices of hydrological variations (e.g., Ji et al., 2004; Zhang et al., 2020b). However, the dissolution of magnetic minerals in a reducing environment needs to be considered for lake sediment (Robinson et al., 2000; Abrajevitch and Kodama, 2011; Duan et al., 2014). There was a reduction environment in the HML record before 6.0 kyr BP and dissolution is partially responsible for the phenomenon of weak magnetism with coarser grain size (Duan et al., 2014). The magnetic susceptibility of the DA core is lower before ~2 kyr BP (Fig.4 and Fig.2), indicating lower concentrations of magnetic minerals. Nevertheless, the rock magnetic results of representative samples show that the magnetic minerals in the lower κ layers have finer grain sizes than those in the higher κ layers, inconsistent with the notion that dissolution leads to weak magnetism (Fig.2). In addition, the magnetic minerals in the DA core are dominated by low-coercivity minerals (Fig.3). The dissolution effect of magnetic minerals cannot be ruled out; however, this process may have a relatively minor impact, and the lower κ value during the interval before 2.0 kyr BP could mainly result from a decreased terrigenous material flux. In addition, HML I_Hm/(I_Hm + I_Gt) profile shows high consistency with its δ¹³C_TOC record, which is controlled by effective precipitation and finally by EASM and ISM (Liu et al., 2005; Fig.2). The δ¹³C and I_Hm/(I_Hm + I_Gt) trends in the DA core are also generally consistent over the past 4.0 kyr (Fig.2). The I_Hm/(I_Hm + I_Gt) record from the DA core is highly consistent with the Palmer drought severity index (PDSI) records, which represent the precipitation in south-eastern China during the period of 1620−2000 A.D. (Liu et al., 2019; Fig.5). The I_Hm/(I_Hm + I_Gt) trends of the two cores show a good comparison at the centennial scale (Fig.1). These results suggest that the I_Hm/(I_Hm + I_Gt) ratios in the HML and DA cores can be indicative of effective rainfall in coastal southern China. The decreased (increased) precipitation is beneficial for the environment of hematite (goethite) formation, and the corresponding decreasing (increasing) terrigenous flux. Ultimately, this climate process would induce the high (low) I_Hm/(I_Hm + I_Gt) ratios.

4.2 Hydroclimate variations in coastal southern China and changes in Earth’s magnetic field

The most profound feature of our I_Hm/(I_Hm + I_Gt) records is that a significant decline from 3.0 to 1.8 kyr BP superimposed on the long-term increasing trend over the past 7.5 kyr BP (Fig.6(b) and Fig.6(c)). This signifies extreme wetness in coastal southern China over 3.0−1.8 kyr BP, approaching or even exceeding that of the mid-Holocene, which is notably inconsistent with the continuous weakening trend of ASM and Northern Hemisphere summer insolation (Wang et al., 2005; Laskar et al., 2011; Kathayat et al., 2016; Wang et al., 2016; Zhang et al., 2017; Xu et al., 2020). In addition, this centennial-scale increase in rainfall is also recognizable in the paleontology records of HML (Zhang et al., 2020a), peat records, and stalagmite records in central China (Xie et al., 2013; Zhu et al., 2017; Zhang et al., 2021). The different trends among different regions may be related to the complex precipitation patterns in East Asia (Hao et al., 2016). Moreover, previous studies demonstrated that the ocean-atmosphere variabilities, such as a southward migration of the ITCZ, strong ENSO activity, south-westward shift of WPSH, accounted for the late Holocene humidity of coastal southern China during the long-term weakened Asian monsoon trend (Yang et al., 2012; Yang et al., 2014; Xu et al., 2020; Zhang et al., 2020a). However, ITCZ displacement and ENSO activity are difficult to fully reconcile with the humidity conditions over 3.0−1.8 ka BP inferred from our records (Haug et al., 2001; Conroy et al., 2008; Fig.4). All of these results suggest that the humidity over 3.0−1.8 kyr BP inferred from our I_Hm/(I_Hm + I_Gt) records is unlikely to be ascribed to AM-coupled hydroclimate variations.

The general trend of our I_Hm/(I_Hm + I_Gt) records is highly similar to that of the virtual axial dipole moments (VADMs) from multiple global models, with higher I_Hm/(I_Hm + I_Gt) ratios corresponding to strong VADMs, and vice versa (Fig.6). This high similarity has been particularly evident over the past 3 kyr BP. It appears that greater precipitation in coastal southern China is associated with a lower Earth’s magnetic field and less precipitation with a higher Earth’s magnetic field. Further, a strong positive correlation was detected between the EMF records in southern China and our records from DA (r = 0.7503, p < 0.01; Fig.5) and HML (r = 0.6893, p < 0.01; Fig.5) during the past 3 kyr. This puts the hydrologic variations in coastal southern China over 3.0–1.8 ka BP to a possible connection with the EMF-GCRs-Aerosols-Cloud-Climate. The link between EMF and climate is complex and has been debated for decades. Researchers found that ozone and aerosol play an important role in climate change and their fluctuating are inextricably linked to the EMF variations (Carslaw et al., 2002; Kirkby, 2007; Channell and Vigliotti, 2019; Cooper et al., 2021). Based on the EMF-GCRs-climate interaction in Cooper et al. (2021) and Kirkby (2007), the EMF regulates the flux of GCRs particles entering Earth’s atmosphere, which then influences ionization in the troposphere, and then influences the production of new aerosol particles and the concentration of ozone in the atmosphere, which affects the formation of clouds and ultimately influences climate (Gallet et al., 2005; Dergachev et al., 2007; Kirkby, 2007; Kerton, 2009; Knudsen and Riisager, 2009; Cooper et al., 2021). The positive correlation between cloud cover and precipitation has been detected from modern observations (Fig.2). Notably, water vapor and CCN are two necessary conditions required for cloud formation. The increased CCN will reduce the threshold of the condensation reaction and result in more vapor condensing into droplets (Li et al., 2011; Sato et al., 2018; Williamson et al., 2019; Luo et al., 2021). In contrast, if too few CCNs (water vapor) are present, precipitation will not increase even if more water vapor (CCNs) is available (Li et al., 2011). As we mentioned above, the water vapor is abundant in coastal southern China, and a small increase in CCN may lead to significantly increased precipitation, and vice versa. During the weak EMF intervals, the weak shielding allows more GCRs to enter the Earth᾽s troposphere, and then produces an increasing number of small ions (charged molecules or small charged clusters of molecules) in the troposphere, which increases the nucleation rates of nanoscale aerosol particles and finally influences the formation process of clouds (Pierce and Adams, 2007; Svensmark et al., 2016; Pierce, 2017; Campuzano et al., 2018; Cooper et al., 2021). More importantly, weak EMF shielding also reduces the energy threshold for the particles to reach the lower latitude regions, increasing the concentration of ion and aerosol nucleation and CCN in the lower latitude atmosphere (Fig.7). Correspondingly, precipitation increased in coastal southern China. During the strong EMF intervals, fewer GCRs are allowed to enter the Earth’s troposphere and most of them can only cause nuclear reactions at the high geomagnetic latitudes. In the lower latitude regions, the climate effect by the GCRs modulated nanoscale aerosol particles is not expected to be more significant than weak EMF intervals. Moreover, the increased EMF is superimposed on the weakening summer insolation and ASM (e.g., 4.0–3.0 kyr BP and 1.8–1.4 kyr BP in Fig.6), which lead to decreased precipitation and drier hydroclimate conditions.

It is important to note that the forcing mechanisms of climate change are more complex than we mentioned above. The correlation between the I_Hm/(I_Hm + I_Gt) records and EMF variations does not imply that the EMF and cloud cover are the dominant force driving hydroclimate change in low-latitude regions. This is a superimposed result of multiple forcing mechanisms, such as ASM, ITCZ, ENSO, WPSH, human activities, and EMF-GCR-Aerosols-Clouds-Climate interactions.

5 Conclusions

We provide high-resolution I_Hm/(I_Hm + I_Gt) records revealing hydroclimate variations in coastal southern China during the mid-to-late-Holocene. The region experienced profound humidity during 3.0–1.8 kyr BP, which differs from the East Asian monsoon variability. The correlations between our I_Hm/(I_Hm + I_Gt) records and the virtual axial dipole moments, suggest that the Earth’s magnetic field played an indispensable role in regulating the mid-to-late-Holocene hydroclimate in coastal southern China, with the GCRs and aerosols and cloud cover as the medium. The Earth’s magnetic field may act in combination with other mechanisms. Although this work appears to provide support for the connection between the EMF and climate, future investigations are needed to further discuss this issue.

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