Interactive comment on “ Dependence of the cyclization of branched tetraethers ( CBT ) on soil moisture in the Chinese Loess Plateau and the adjacent areas : implications for palaeorainfall reconstructions ”

In their manuscript, Wang et al determined the environmental controls on the CBT index, i.e. the degree of cyclisation of branched GDGTs, in arid soils from the Chinese Loess Plateau (CLP) and its near vicinity. The authors find that soil moisture is the most important factor controlling the CBT index in their sample set, and propose to use the CBT index as a proxy for paleoprecipitation. This is tested on three loess-paleosol sequences from the literature.


Introduction
The deposits of wind-blown dust (i.e.loess) on the Chinese Loess Plateau (CLP, Fig. 1) are some of the key nature archives of past climate changes.Characteristically, the plateau consists of a sequence of alternating loess and paleosol layers, which have accumulated at least since 2.6 Ma BP (Liu, 1985;Liu and Ding, 1998), with the records at places extending back to late Oligocene (Heller and Liu, 1982;Guo et al., 2002;Qiang et al., 2011).The cyclic alternation of loess and paleosol provides highly visible records of regional climate resulted from changing monsoon intensity on glacialinterglacial time scales (An, 2000 and references therein;Porter, 2001).For the past three decades, numerous proxies have been shown indicative of monsoon intensities in loess-paleosol sequences (LPSs), including: the traditional pedogenic magnetic susceptibility (Liu, 1985;Zhou et al., 1990;Maher et al., 1994) and grain size distributions (Ding et al., 1994, Sun et al., 2006), the geochemistry of iron oxides (Ding et al., 2001), the δ 18 O of rhizoconcretions and land snail shells (Li et al., 2007), the δ 13 C of total organic matter (An et al., 2005;Liu et al., 2005a, b;Ning et al., 2008;Rao et al., 2013) or carbonate (Liu et al., 2011), the δ 13 C and δD of leaf wax n-alkanes (Zhang et al., 2003(Zhang et al., , 2006;;Liu and Huang, 2005;Liu et al., 2005b), phytolith (Lu et al., 2006(Lu et al., , 2007)), and trace mental ratios (Li and Li, 2014).The development of new palaeoclimatic proxies may further aid in the validation and explanations of the aforementioned proxies in the LPSs and the understanding of palaeoclimatic variations in monsoonal East Asia, and therefore, is still necessary for this climatologically important region.

Back Close
Full  , 2009;Peterse et al., 2009aPeterse et al., , b, 2012;;Loomis et al., 2011;Tierney et al., 2012;Yang et al., 2012Yang et al., , 2014a;;Wang et al., 2013;Liu et al., 2013).They are presumed to origin from the cell membrane of unknown bacterial species (Weijers et al., 2006b;Sinninghe Damsté et al., 2011) with a heterotrophic lifestyle (Pancost and Sinninghe Damsté, 2003;Oppermann et al., 2010;Weijers et al., 2010).By the study of bGDGT distributions in > 130 globally soils, Weijers et al. (2007a) founded that the relative extent of cyclopentane moieties, expressed as the cyclisation ratio of bGDGTs (CBT), is negatively related to soil pH, whereas the degree of methylation for the nine bGDGTs, expressed as the methylation index of bGDGTs (MBT), is positively correlated with the mean annual air temperature (MAAT) and to some extent to soil pH.Therefore, paleo soil pH and MAAT can be quantified using CBT and the combination of MBT and CBT (MBT-CBT), respectively (Weijers et al., 2007a).An extended survey of 278 globally distributed surface soils further confirmed that CBT relates best to soil pH, while the simplified form of MBT (i.e.MBT' based on the seven most common bGDGTs) and CBT were shown correlating with MAAT (Peterse et al., 2012).Recently, Yang et al. (2014a) investigated the distribution of GDGTs in > 100 surface soils across a large climatic gradient of China, and proposed an alternative transfer function for MAAT reconstruction based on the fractional abundances of bGDGTs for use in semiarid and arid regions.This calibration has a markedly higher determination factor and lower root mean square error (RMSE) than the MBT/CBT proxy in alkaline soils (Yang et al., 2014a).
The sensitivity of soil bGDGT distributions to environmental variables offers new tools for quantitatively inferring past continental climate change in LPS studies.Initial application of the bGDGT paleothermometer to LPSs from the Mangshan (Peterse et al., 2011(Peterse et al., , 2014)), Lantian (Gao et al., 2012), Yuanbao (Jia et al., 2013), and Weinan (Yang et al., 2014a, b) sections on the CLP indicates that bGDGTs might have recorded past changes in air temperature driven by local solar insolation.Unexpectedly, however, the CBT-reconstructed pH is higher for paleosol than for loess (Jia et al., 2013;Peterse et al., 2014), in contradiction with the well-accepted view that paleosol formed under wetter climate conditions.In fact, Xie et al. (2012)  observed a negative correlation between CBT and soil pH when pH < 7, but a slightly positive correlation or a flattening off when pH > 7, implying that some other factor(s) might have played an important role on CBT variations in alkalescent soils.
In the present study, we analyzed the CBT index in ca. 100 surface soils in the CLP and the adjacent arid/semi-arid areas with different climatic conditions.The aim of this work was to understand the environmental controls on soil CBT in the modern arid/semi-arid central China, in order to see if CBT can be used as a quantitative proxy specific for a certain environmental parameter in paleoclimate reconstructions in LPS studies.

Regional setting and sample collection
The CLP is the largest region of loess deposits in the world.It is characterized by temperate semi-arid and semi-humid climate, modified by latitude, longitude, and terrain.Both the mean annual air temperature (MAAT) and the mean annual precipitation (MAP) show a clear northwestward decrease (Fig. 1).Dominated by the strength of the East Asian summer monsoon (EASM) system, the precipitation occurs mostly in the summer months (from May to September), which accounts for approximately 68-87 % of the total annual precipitation (Ding, 1994;Liu et al., 2005a).The present-day CLP is mainly covered by shrub (e.g., Sophuora viciifolia and Vitex chinensis) and grasses (e.g., Artemisia and Gramineae) (Liu, 1985).In general, the vegetation progressively becomes sparser and less dense from southeast to northwest, resulting from increasing dryness (Liu et al., 2005c).
A total of 97 samples were collected from 33 sites (i.e., 2-5 samples which are tens to hundreds of meters away for each site, except for site DengkouB with only one sample) in the CLP and the surrounding areas (Fig. 1).Samples for the CLP were collected from well-drained natural grassland (or to say the least, grassland restoration for > 10 years), Figures

Back Close
Full and therefore are typical for local soils.For each sample, three randomly collected subsamples were pooled and mixed to make one composite sample representing that location.Most samples were collected from the uppermost layer of soil profiles with a depth of less than 5 cm and they were transported to the laboratory immediately after collection and stored at −20 • C. The detailed information of the samples is indicated in Supplement Table 1.

Environmental parameters
The SWC value for the sampling time was obtained by measuring sample weight before and after freeze drying.Sample pH was measured following Wang et al. (2012): ca. 4 g freeze dried sample was added in 10 mL distilled water; the mixture was stirred for 1 min, left to stand for 30 min, and pH value of the supernatant was measured with a Sartorius PB-10 pH meter.The standard deviation for triplicate measurements was ± 0.03.The meteorological data for our sampling sites were obtained from the China Meteorological Data Sharing Service System (http://cdc.cma.gov.cn/).MAP, MAAT, mean annual ground surface temperature (MAGST), mean annual relative humidity (RH), and mean annual evaporation (MAE) for each sampling site were estimated from the nearest climate stations.If there are 2-3 nearest stations for one sampling site, the meteorological data of them was averaged to generate an integrated meteorological data.Moreover, a further correction to the meteorological MAGST and MAAT values for each sample was made according to a lapse rate of −0.6 • C 100 m −1 .

Analysis of bGDGTs
The freeze dried and homogenized samples (30-50 g) were extracted (4 × 10 min) with dichloromethane (DCM) : methanol (9 : 1, v/v) using an accelerated solvent extractor (ASE 350, Dionex) at 100 • C and 1500 psi.The total extract was dried under N 2 in a wa- then added to the extract, which was redissolved in DCM : methanol (9 : 1, v/v) and divided into two halves.One half was dried under N 2 , re-dissolved in hexane/isopropanol (99 : 1 v/v) and filtered over a 0.45 µm PTFE filter.
An aliquot (10 µL) of sample (100 or 600 µL, depending on GDGT concentration) was injected for HPLC-atmospheric pressure chemical ionization (APCI)-MS analysis according to a procedure slightly modified from Schouten et al. (2007) and Zhang et al. (2012).Separation of bGDGTs was achieved on an Alltech Prevail Cyano Column (150 mm × 2.1 mm, 3 µm).The elution gradient was: isocratic (5 min) at 99 % hexane/1 % isopropanol followed by a linear gradient to 1.8 % propanol in 45 min.After each analysis, the column was cleaned by back-flushing using 90 % hexane/10 % propanol.The flow rate was set at 0.2 mL min range of 7.5-9 (Fig. 3; R 2 = 0.25, N = 97; p < 0.01).This seems different from the significant negative CBT-pH relationship observed regionally (Peterse et al., 2009b) and globally (Weijers et al., 2007a;Peterse et al., 2012).However, we note that the proportion of alkalescent soils (especially for soils with pH > 8) is much small in each calibration of the aforementioned studies.This consequently can modify the deviation of CBT values at higher pH values, if any, in the context of a large amount of soils with pH < 7.In fact, by extending the pH to > 9, Xie et al. (2012) and Yang et al. (2014a) have recently pointed out that the CBT index appears unable to distinguish pH variations in neutral to alkalescent soils, due to the weak positive CBT-pH relationship or a flattening-off of CBT when the pH is > 7, despite that the CBT values still exhibit a significant negative correlation with soil pH when pH < 7 (Fig. 3).The flattening-off of CBT at higher pH values was also observed by Peterse et al. (2010), who analyzed bGDGTs in long term soil pH manipulation plots in Scotland.Moreover, in lacustrine systems, a seemingly similar pattern was also obvious in the surface sediments of 23 lakes in China and Nepal (Sun et al., 2011), as well as in suspended particulate matter (SPM) from 23 lakes in the USA (Schoon et al., 2013).The weak correlation between CBT and pH under alkalescent conditions suggests that, variations in CBT might also be insensitive to changing pH in the alkalescent CLP soils.
The absence of a clear CBT-pH relationship under alkalescent conditions possibly reflects that a certain threshold is reached for bGDGT-producers in adapting their membrane lipids to pH.For the negative CBT-pH relationship, Weijers et al. (2007a) have proposed two likely mechanisms.Firstly, it is important for the microbes to maintain the internal pH within the cell constant, and therefore the bGDGT-producing bacteria tend to reduce the production of cyclopentyl moieties (causing higher CBT) at lower pH for better membrane packing and lower membrane permeability, which helps to protect cells against low pH (Weijers et al., 2007a).When pH is > 7, however, there seems no need for soil bacteria to overcome the inhibition of acidity.Secondly, the proton permeability (i.e., the pH gradient) of the cell membrane plays a crucial role in driving energy reactions over the cell membrane (e.g.Booth, 1985).

Conclusions References
Tables Figures

Back Close
Full moieties would enable more water molecules to get trapped in the membrane and consequently increases the membrane proton permeability, whereas a steeper proton gradient (thus lower ambient pH) is counteracted by a more impermeable membrane resulting from fewer cyclopentyl moieties and thus higher CBT (Weijers et al., 2007a).Under alkalescent conditions, however, further adaptation of the cell membrane would not be needed to overcome H + leakage (Schoon et al., 2013), if the bGDGT-producers turn to use Na + for energy transduction as neutrophiles and alkaliphiles, which are able to perform energy transduction by establishing a Na + gradient in combination with an H + gradient (Speelmans et al., 1995;Schoon et al., 2013).Overall, these could possibly explain the apparent insensitivity of CBT to pH in alkalescent conditions theoretically, and for the alkalescent CLP soils therefore, variations in CBT values should be attributed as a response to some factor(s) else.

Sensitivity of CBT to soil moisture in alkalescent soils
Notably in our dataset, we observed strong correlations of CBT with SWC (Table 1 and Fig. 4a; R 2 = 0.46, N = 96, p < 0.01) and MAP (Table 1 and Fig. 4b; R 2 = 0.52, N = 97, p < 0.01), which have much higher correlation coeficients than that for the CBT-pH relationship (R 2 = 0.25).The negative relationship between CBT and local MAP in our alkalescent soils is in accord with the results of Xie et al. (2012), at the MAP range of 200-800 mm (Fig. 5a).These empirical results imply that, in alkalescent soils, moisture conditions might have played an important role on CBT instead of soil pH.Contrarily, however, soil pH could have controlled CBT in acid to neutral soils, and therefore the positive correlation of MAP with CBT in Xie et al. (2012) when MAP > 800 is most likely a result of covariance with pH (Fig. 5b), which does not necessarily point to a direct causal relationship.The most likely explanation for the negative CBT-SWC and CBT-MAP relationships in alkalescent soils might be that the formation of cyclopentane moieties could result in a loosening of the packing of the membrane lipids (Weijers et al., 2007a), whereas a dense packing of membrane lipids is needed to avoid over-evaporation of intracel-Introduction

Conclusions References
Tables Figures

Back Close
Full lular water from the membrane under dry conditions.However, as the exact biological source of bGDGTs is unknown, the reason why CBT correlates with soil moisture in alkalescent soils still remains speculative.Further studies of manipulation experiment would provide deeper insight into the exact physiological mechanism responsible for the observed moisture dependence of the CBT index.
We should note that our measured SWC is an instantaneous value that is liable to be affected by differences in the time of short-term local rainfall, and may not accurately stand for an average soil moisture condition during the growth of bGDGT producers.This might be an important factor causing the large scatter in the CBT-SWC relationship.For instance, typical soils in site Yongdeng (MAP: 284 mm) should be drier than those in the adjacent site Gulang (MAP: 352 mm).However, the measured SWC values for soils in Yongdeng (13, 13, and 12 %) collected immediately after a rainfall (according to our field note) were much higher than those for Gulang (3, 6, and 3 %).In such a case, the use of SWC at this sampling time could lead to an overestimation of the averaging soil moistures for bGDGT producers for Yongdeng (Fig. 4a).Omitting the Yongdeng samples, the CBT-MAP relationship was improved as expected (R 2 = 0.56).For extensive surface soil investigations therefore, variations in the SWC values at the time of sampling can only roughly reflect differences in mean soil moisture conditions.
MAP would be more representative for the mean soil moisture condition than the instantaneous SWC value, especially when local continuous observation data was not available for each sampling site.For the total dataset, however, CBT only correlates slightly better with MAP than with SWC.This is possibly because that the diversity in soil texture (e.g., desert sandy soils vs. CLP soils) can lead to different responses of soil moisture conditions to local MAP, causing the large scatter in the CBT-MAP relationship.Indeed, when further relevance analysis of CBT and MAP was performed only for the CLP soils, the positive CBT-MAP correlation exhibits a significant improvement (R 2 = 0.87, N = 37, p < 0.01).This might imply that soil texture should be taken into consideration when using meteorological MAP data for modern surface soil investigations.

Conclusions References
Tables Figures

Back Close
Full The influence of temperature might not be a primary reason for the variations in CBT values.For the total dataset, we observed that CBT correlated substantially weakly (R 2 = 0.02, N = 97, p = 0.13) with mean annual ground surface temperature (MAGST).
For the CLP samples, despite the significant correlation (R 2 = 0.59, n = 37, p < 0.01) observed for CBT with MAGST, the correlation is likely indirect since MAGST is also correlated with MAP (R 2 = 0.62, n = 37, p < 0.01) while the correlation coefficient of the CBT-MAP relationship is much higher than that of the CBT-MAGST relationship.
Hence, the main factor controlling the CBT is suggested to be soil moisture (or MAP) for surface soils in the CLP and the adjacent arid/semi-arid areas.

Implications for palaeorainfall reconstruction on the CLP
The significant correlation between CBT and MAP in 37 surface soils on the CLP (Fig. 6a) indicates that this index may be a useful tool for palaeorainfall reconstruction in this region.The residual errors of the estimated MAP are < 127 mm, with a RMSE of 50 mm, and without following a clear trend with MAP (Fig. 6b).Analytically, the standard deviation for CBT is 0.01, equivalent to 6 mm of MAP, indicating that palaeorainfall estimates can be obtained with high analytical reproducibility.
In order to test the CBT index as a palaeorainfall proxy on the CLP, we applied it to three LPSs with published bGDGT data covering the past 70 kyr.Located from west to east on the southern CLP, the three LPSs are the Yuanbao (Fig. 7a, Jia et al., 2013), Lantian (Fig. 7b, Gao et al., 2012), andMangshan (Fig. 7c, Peterse et al., 2014) sections, respectively.The CBT-derived MAP records exhibit pronounced precessiondriven variations in rainfall amount at the three sites.Within dating uncertainties, the fluctuations of each record resembles the speleothem δ 18 O record from the Hulu (Wang et al., 2001) and Sanbao (Wang et al., 2008) caves in southeast China (Fig. 7d), which are widely regarded as a robust record for the EASM intensity, predominantly for monsoon precipitation (Peterse et al., 2014).All these records indicate that rainfall amount was highest during Marine Isotope Stage (MIS) 1, relatively higher during MIS 3, and lowest during MIS 2 and probably MIS 4. In addition, the magnetic susceptibility 10025 Introduction

Conclusions References
Tables Figures

Back Close
Full (MS) in LPSs has also been linked with climate, mainly through rainfall, by numerous investigators (Balsam et al., 2011 and references therein).For each section, the reconstructed rainfall history inferred from CBT is in general accord with the fluctuations of measured MS (Fig. 7a-c).Overall, the consistency of the CBT-inferred MAP records with other records of independent monsoon rainfall proxies (i.e., the speleothem δ 18 O and MS records) strongly supports the CBT index as a palaeorainfall proxy on the CLP.
According the preliminary modern CBT-MAP calibration, the minimum MAP values for the three sites (559 mm, 726 mm, and 616 mm for Yuanbao, Lantian, and Mangshan, respectively) since the last glacial occurred at the Last Glacial Maximum (LGM), while the maximum values (780 mm, 834 mm, and 858 mm for Yuanbao, Lantian, and Mangshan, respectively) were reached during the Holocene, showing an overall ca.200 mm enhancement in MAP on average during the transitional Deglacial period in the southern CLP.Moreover, the maximum and minimum values of reconstructed MAP for the Yuanbao LPS are much lower than those of Lantian and Mangshan LPSs, in agreement with the modern isohyets pattern of a decreasing MAP from east to west CLP (Fig. 1).However, these quantitative results based on CBT data measured by different laboratories should be interpreted with caution, since recent round-robin studies with dozens of laboratories have shown that GDGT indicies may vary significantly due to differences in inter-laboratory instrumental characteristics (Schouten et al., 2013b).
In view of the great potential of bGDGTs in reconstructing continental air temperature (Weijers et al., 2007a;Peterse et al., 2012;Yang et al., 2014a), the application of the CBT index derived from the same suite of lipids as a palaeorainfall proxy is particularly promising on the CLP.Recently, Peterse et al. (2014) proposed that the direct comparison of CBT-derived pH (likely precipitation-induced) and bGDGT-derived temperature might enable us to further assess the relative timing and magnitude of hydrological and thermal changes in continental east Asia, independent of potential biases associated with age model uncertainties.However, the reconstructed pH is unexpectedly higher in paleosol and weak paleosol (Peterse et al., 2014), which is in contrast to the presumption of Weijers et al. (2007b) that higher paleo-soil pH is related to drier conditions.In Introduction

Conclusions References
Tables Figures

Back Close
Full this study, the CBT-MAP relationship in alkalescent soils provides an empirical basis for the direct reconstruction of palaeorainfall based on the CBT index on the CLP, filling the gap of the uninterpretable results of previous studies (Jia et al., 2013;Peterse et al., 2014).The application of CBT as a palaeorainfall proxy in the three LPSs (Fig. 7a-c) confirms that continental air temperature and monsoon precipitation in southern CLP were generally decoupled (Peterse et al., 2011;2014).The decoupling is more obvious for the past 30 kyr as the bGDGT results of each study exhibits an unambiguously lagged intensification of monsoon precipitation relative to Deglacial warming (Fig. 7ac).This supports the idea that factors controlling the onset of Deglacial atmospheric warming and the intensification of East Asian Summer Monsoon might have been different (Peterse et al., 2011).

Summary
In this study, we have investigated the environmental controls on the CBT index for surface soils on the CLP and in the adjacent arid/semi-arid areas.In contrast to most previous studies covering a large range of soil pH values, no significant relationship was observed between soil pH and CBT for our data set.Further examination of other environmental factors showed that CBT is best correlated with SWC and MAP, indicating that soil moisture might have played an important role on the cyclisation ratio of bGDGTs in the alkalescent soils.bGDGT temperature proxy derived from the same suite of lipids tells a similar story of the lag of monsoon precipitation relative to continental temperature (Peterse et al., 2011(Peterse et al., , 2014;;Jia et al., 2013), independent of chronology.Moreover, the maximum and minimum values of reconstructed MAP for the drier Yuanbao section on the eastern CLP are systematically lower than those of the more humid Lantian and Mangshan sections on the western CLP.These evidences collectively support the CBT index as a palaeorainfall proxy on the CLP.
In conclusion, the results of this study indicate that CBT is a promising new palaeorainfall proxy on the CLP, although further research on the exact physiological mechanism and the additional data for a more accurate surface soil CBT-MAP calibration are required.
The Supplement related to this article is available online at doi:10.5194/bgd-11-10015-2014-supplement.
Screen / Esc Printer-friendly Version Interactive Discussion Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | sell and Yang et al. (2014a) have recently Figures Back Close Full Screen / Esc Printer-friendly Version Interactive Discussion Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Screen / Esc Printer-friendly Version Interactive Discussion Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | ter bath.A known amount of C 46 GDGT internal standard (IS, Huguet et al., 2006) was Figures Back Close Full Screen / Esc Printer-friendly Version Interactive Discussion Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | −1 .In order to increase sensitivity and reproducibility, selective ion monitoring (SIM) mode of the [M + H] + (protonated molecular ion) of the different bGDGTs (Fig. 2) was used to detect and quantify them.Quantification of each bGDGT was achieved by calculating the peak area in the chromatogram and comparing it with that of the IS.Ionization efficiency for bGDGTs and the IS was assumed identical.The CBT index was calculated following Weijers et al. (2007a): CBT = − log Ib + IIb I + II Replicate analyses of 5 samples for CBT showed an averaging standard deviation of 0of CBT to soil pH variation in alkalescent soils Correlation of soil pH with CBT for surface soils in the CLP and the adjacent arid/semiarid areas shows that there is a slight positive relationship between them at the pH Introduction Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Screen / Esc Printer-friendly Version Interactive Discussion Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Screen / Esc Printer-friendly Version Interactive Discussion Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Screen / Esc Printer-friendly Version Interactive Discussion Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Screen / Esc Printer-friendly Version Interactive Discussion Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | A preliminary calibration of MAP and CBT was established by 37 well-drained local natural soils on the CLP (CBT = −0.0021• MAP + 1.7).With a RMSE of 50 mm for the estimated MAP, this correlation might be useful for inferring past rainfall variations in this climatologically important region.According to this regional calibration, variations in reconstructed MAP based on three sets of published bGDGT data on the CLP (Yuanbao: Jia et al., 2013; Lantian: Gao et al., 2012; Mangshan: Peterse et al., 2014) are in agreement with the speleothem δ 18 O record and the fluctuations of site-specific MS, within age model uncertainties.The combination of the CBT rainfall indicator with the Discussion Paper | Discussion Paper | Discussion Paper |