Influence of water availability in the distributions of branched glycerol dialkyl glycerol tetraether in soils of the Iberian Peninsula

The combined application of the MBT (degree of methylation) and CBT (degree of cyclization) indices, based on the distribution of branched glycerol dialkyl glycerol tetraethers (brGDGTs) in soils, has been proposed as a paleoproxy to estimate mean annual temperature (MAT). CBT quantifies the degree of cyclization of brGDGTs and relates to soil pH. MBT and the simplified version MBT’ quantify the degree of methylation of brGDGTs and relate to MAT and soil pH. However, other factors such as soil water availability have also been suggested to influence MBT’ and possibly restrict the combined application of the MBT’ and CBT indices as a paleotemperature proxy. To assess the effect of hydrological conditions on MBT’ and CBT, a set of 23 Iberian Peninsula soil samples, covering a MAT range from 10 to 18C and a mean annual precipitation (MAP) range of 405 mm to 1455 mm, was analyzed. We found that the CBT was indeed significantly correlated with soil pH in our sample set. In contrast, MBT’ was not correlated with MAT but had a significant correlation with the aridity index (AI), a parameter related to water availability in soils. The AI can explain 50 % of the variation of the MBT’, and 70 % of the residuals of MAT estimated with the MBT/CBT proxy as compared to instrumentally measured MAT. We propose that, in arid settings, where water may be an ecologically limiting factor, MBT’ is influenced by hydrological conditions rather than temperature. Thus, our results suggest that the combination of MBT’ and CBT indices should be applied with caution in paleotemperature reconstructions in soils from dry subhumid to hyperarid environments.


Introduction
Reconstruction of past temperatures beyond the time period covered by instrumental records is required to understand the natural modes of climate variability.However, the reconstruction of continental temperature is particularly challenging as there are few quantitative proxies.There are a number of studies that have used microfossil assemblages based on pollen, diatoms or chironomids preserved in lake sediments to estimate past air or lake water temperatures (e.g., Colinvaux et al., 1996;Lotter et al., 1997;Kurek et al., 2009).A molecular proxy initially developed to estimate past sea surface temperatures has also been shown to be applicable in lake settings, i.e., the long-chain alkenone unsaturation index (e.g., Marlowe et al., 1984;Zink et al., 2001;Toney et al., 2010).In addition, the glycerol dialkyl glycerol tetraethers (GDGTs) have also been applied in marine as well as continental records for the same purpose (e.g., Powers et al., 2004Powers et al., , 2010;;Blaga et al., 2009).
The GDGTs are cell membrane lipids of Archaea and Bacteria that are used in paleoenvironmental studies to track, for example, changes in archaeal abundance or terrestrial organic matter input into aquatic systems, as well as for estimating past water/air temperatures and soil pH.Two major types of GDGTs are currently used -isoprenoidal (i) and branched (br) -that differ in their alkyl chain structures.iGDGTs are synthesized mainly by aquatic, mesophilic Archaea, while branched glycerol dialkyl glycerol tetraethers (brGDGTs) have been predominantly found in terrestrial settings such as peat bogs and soils (Weijers et al., 2006a), but also in sedimentary settings receiving significant terrestrial input (e.g., Hopmans et al., 2004).The glycerol stereochemistry of the brGDGTs indicates a bacterial provenance (Weijers et al., 2006b), and a brGDGT could be identified in two cultures of Acidobacteria (Sinninghe Damsté et al., 2011).However, brGDGTs are found in a wide range of environments, which can be interpreted as an indication that brGDGTs may be synthesized by different phyla of Bacteria (Sinninghe-Damsté et al., 2011).
The distribution of brGDGTs in soils has been put forward as a means to estimate past continental mean annual temperatures (MATs) and pH (Weijers et al., 2007).The proxy is derived from measuring two indices that calculate the degree of methylation (MBT and its simplified form MBT') and cyclization (CBT) of brGDGTs (Weijers et al. 2007;Peterse et al., 2012), where (3) Biogeosciences, 11, 2571-2581, 2014 Roman numerals refer to chemical structures in Fig. 1a.MBT and MBT' have been described to correlate with air temperature and soil pH, while CBT has been found to depend mainly on soil pH.Thus, using the values of CBT and MBT', one can estimate MAT as follows (Peterse et al., 2012): The calibration equation to estimate MAT by Peterse et al. (2012), based on MBT' (Eq.5), has a slightly lower correlation coefficient than the original calibration by Weijers et al. (2007) using MBT.The error of the calibration from both studies is similar, being 5.0 The combination of the MBT or MBT' and CBT indices has been applied in a variety of marine and freshwater sites to estimate continental MAT (e.g., Weijers et al., 2007;Rueda et al., 2009;Peterse et al., 2012).In these applications the underlying assumption is that brGDGTs in sediments have an allochthonous origin, and the estimated temperatures correspond to those from the nearby continental regions.However, there is circumstantial evidence that brGDGTs are also biosynthesized within lake and ocean basins, not just in soils (e.g., Sinninghe Damsté et al., 2009;Blaga et al., 2010;Tierney et al., 2010;Fietz et al, 2011;Sun et al., 2011).Furthermore, the relatively large scatter in the original MAT calibration data sets (Weijers et al., 2007;Peterse et al., 2012) suggests that other parameters may influence brGDGT indices besides air temperature and soil pH (e.g., Loomis et al., 2011;Dirghangi et al. 2013;Wang et al., 2013).For instance, brGDGT distributions in geothermally heated soils and in a Spodosol in France were linked to oxygen availability or moistness (Peterse et al., 2009a;Huguet et al., 2010a).Two studies on surface soils from North America showed no correlation between MBT values and MAT, but found a correlation between MBT and mean annual precipitation (MAP) when MAP < 200 mm (R 2 = 0.75) (Peterse et al., 2009b) or when MAP < 800 mm (Dirghangi et al., 2013).This was interpreted as evidence that in arid regions MAP rather than MAT may drive the MBT index variability (Peterse et al., 2009b;Dirghangi et al. 2013).To evaluate further the effect of hydrological conditions on the MBT/CBT proxy, we have analyzed soil samples from locations across the Iberian Peninsula, which represents a range of mainly arid to subarid settings with moderate differences in MATs.

Samples and sites' environmental conditions
A suite of 23 surface soil samples was collected in October 2010 across the Iberian Peninsula (Fig. 1b).Each soil sample was obtained from the combination of three subsamples taken at least 4 m apart from each other and within a 10 m radius area.Subsamples were retrieved after removing the litter and loose gravel if present, scooping the soil from a depth of approximately 10 cm within a 20 cm × 20 cm square surface area, and transferring it into an aluminum tray.The soil samples were homogenized and air dried.A subsample of 500 g was then sieved (2 mm mesh size) removing vegetation remains and small stones.
Sample sites display moderate differences in MAT (10-18 • C), but cover a wide range of MAP (405-1455 mm) (Fig. 1b, Table 1; Ninyerola et al., 2005).In the Iberian Peninsula, the highest precipitation and cooler temperatures occur generally in the northwest, especially at high elevation, while the driest and warmest areas are in the southeast.A value of the aridity index (AI = MAP/mean annual potential evapotranspiration) was calculated for each site using the approach proposed by the Consortium for Spatial Information (CGIAR-CSI) based on UNEP (1997) criteria (Tables 1 and 2; Trabucco and Zomer, 2009).For each site, soil moisture regimes were established according to Soil Survey Staff (2010).In general, the eastern Iberian Peninsula is dominated by soils developed on calcareous parent material or with a significant accumulation of calcium carbonate within the soil profile, while western soils are usually silicic, developed on magmatic or metamorphic rocks, or acidified by leaching.Soils were classified according to the Soil Taxonomy System (Soil Survey Staff, 2010) at group level, as only the surface mineral soil material was collected.The sample set includes a wide range of soil types, belonging to 5 orders and 14 groups, covering a wide range of parent materials, and climatic and geographic conditions (Table 1).

Ancillary measurements
Total organic carbon (TOC) content was determined on finely ground soil samples using a Thermo Flash 1112 elemental analyzer in combustion mode with a Thermo Delta V Advantage mass spectrometer as a detector via a Thermo Conflo III interface, after Werner et al. (1999).A reference compound IAEA 600 was used for external calibration, and to calculate the TOC % standard deviation, which was ±0.25.
Soil pH was measured in a soil : de-ionized water suspension (1 : 5) by vigorous shaking the mixture for 1 min, and leaving it to settle for 30 min.(Thomas, 1996).A triplicate measurement was taken using a pH meter (GLP22, Crison Instruments) after calibration of the electrode with standard solutions at pH 4 and 7.

GDGT analysis
Samples of approximately 1 g of dry soil were spiked with an internal standard (GR, Rethoré et al., 2007) and extracted using a microwave (MARS 5-CEM) and dichloromethane (DCM) : methanol (MeOH) (3 : 1, v/v).The temperature of the microwave vessels containing the soil aliquots was increased to 70 • C over 5 min, held at 70 • C for 5 min and then decreased to 30 • C. The organic extract was concentrated under a stream of nitrogen, and separated into three fractions of different polarity according to the method in Huguet et al. (2010b).In short, the lipid extract was eluted in a column filled with activated silica using n-hexane, DCM and MeOH.The MeOH fraction, which contained the GDGTs, was then evaporated under nitrogen, redissolved in n-hexane : n-propanol (99 : 1, v/v) and filtered through 0.45 µm PTFE (polytetrafluoroethylene) filters prior to analysis by high-performance liquid chromatography-mass spectrometry (HPLC-MS).The instrumental analysis was performed using a Dionex P680 HPLC system coupled to a Thermo Finnigan Quantum Discovery Max triple sector quadrupole MS with an atmospheric pressure chemical ionization (APCI) interface set in positive mode.Instrumental and chromatographic conditions were adapted from Schouten et al. (2007), Escala et al. (2009) and Fietz et al. (2011).Extracts were eluted using a Prevail Cyano column (2.1 × 150 mm, 3 mm; Alltech) fitted with a guard column.The flow rate was set at 0.6 mL × min −1 , and the HPLC program was as follows: 98.5 % hexane and 1.5 % npropanol for 4 min, increasing the proportion of n-propanol to 5 % in 11 min, then to 10 % over 1 min and held constant for 4 min, finally lowered to 1.5 % in 1 min and held constant for a further 9 min prior to injecting the next sample.
The parameters of the APCI were set as follows to generate positive ion spectra: corona discharge 3 mA, vaporizer temperature 400 • C, sheath gas pressure 49 mTorr, auxiliary gas (N 2 ) pressure 5 mTorr, and capillary temperature 200 • C. GDGTs were detected in selected ion monitoring (SIM) mode of [M+H] + ± 0.5 m/z units.Absolute abundances of brGDGTs were quantified by comparison of the corresponding peak areas with those of the internal standard GR and correcting for the response factor (cf. Huguet et al., 2006).
Samples were extracted and measured once.Due to low abundances of brGDGTs IIIb and IIIc (Fig. 1a), we decided to calculate the MBT' rather than MBT index (Peterse et al., 2012).The reproducibility of the measurement of MBT' and CBT was 0.006 and 0.022, respectively, obtained from the repeated analysis (six times) of a reference soil sample (sample X-Ref in Fig. 1b).The possibility of an apparent correlation between the abundances of GDGTs with MBT' and CBT due to an increased analytical error at low abundances was discarded after recalculating the MBT' and CBT while removing all peak areas below a threshold value.The original and the recalculated MBT' and CBT values did not reveal substantial differences (i.e., their lineal correlation yielded R 2 = 0.96, R 2 = 0.99, respectively).Temperature residuals were calculated by subtracting brGDGT-estimated values for MAT (i.e., MAT est , using MBT'/CBT) from instrumental values of MAT derived from a climatic atlas (MAT im ; Table 1; see Ninyerola et al., 2005).The residuals of pH values were calculated by subtracting brGDGT estimates (i.e., pH est , using CBT) from soil pH values measured in the laboratory with a pH meter (pH im ).Throughout the manuscript, the use of the subscript "est" denotes estimated values using GDGT indices, while the subscript "im" refers to values measured with instruments (Table 1, Sect.2.2).

BrGDGT abundances and distribution
The concentrations of brGDGTs in the soils ranged between 1.3 µg g −1 TOC and 17.5 µg g −1 TOC (Table 2).The predominant brGDGT is GDGT IIa, followed by IIIa and Ia (Table 2).The brGDGTs IIIb and c, IIc as well as brGDGT Ic are only present in minor amounts.In eight of the samples (35 % of the total), none of these brGDGTs were detected (Table 2), which is a similar percentage as reported in globally distributed soils (Peterse et al., 2012).
Samples with the highest absolute brGDGT abundances were located in the northern Iberian Peninsula, the area with the highest rainfall and cooler temperatures.Towards the drier and warmer south, the brGDGT abundances gradually decreased (Table 2).The highest brGDGT abundance was found in an Endoaquoll soil (sample code CAR, Tables 1 and 2), a relative singular soil with aquic moisture regime, formed on an alluvial delta with a high TOC content (15.9 %), and relatively high MAP im in our data set (886 mm; Tables 1 and 2).Soil types Hapludoll (one sample) and Dystrudept (four samples) also had relatively high brGDGT abundances.These soils are also characterized by high MAP im (866-1455 mm) and TOC contents that range between 3.5 and 10 %.Therefore, our data suggest that  brGDGT abundance is partly controlled by both precipitation and to a lower extent by TOC in agreement with previous studies.For instance, a positive correlation was found between soil water content and brGDGT abundances in marsh soils of the Qinghai-Tibetan Plateau (Wang et al., 2013).Soil water content was suggested to have a direct effect on brGDGTs and/or an indirect effect on other factors such as oxygen and TOC content (Wang et al., 2013).Water saturation was also suggested to play a significant role for brGDGT abundance in African soils (Loomis et al., 2011).BrGDGT source organisms have been suggested to be heterotrophic (e.g., Weijers et al., 2010;Huguet et al., 2012;Opperman et al., 2012;Ayari et al., 2013), which could explain the higher brGDGT abundances coupled to high TOC.Earlier studies showed that brGDGT abundances are usually high in water-saturated soils and peat bogs, thus potentially providing an ideal environment for brGDGT source organisms that have been proposed to be anaerobic (Weijers et al., 2006).However, so far, brGDGTs have been identified in only two aerobic Acidobacteria species, suggesting that brGDGTs are synthesized by a range of bacterial communities (Sinninghe Damsté et al., 2011).Hence, the impact of soil redox conditions on brGDGT abundance from diverse bacterial communities has yet to be ascertained.
Our data also indicated that pH is not a driving factor for brGDGT abundance as, despite covering a pH range from 4.8 to 8.7, we did not observe an increase in brGDGTs with lower pH.This contrasts with earlier findings (e.g Peterse et al., 2010;Sinnghe-Damsté et al., 2011;Yang et al., 2011) again suggesting that brGDGTs are produced by a range of bacterial communities.

CBT and MBT' relationship with pH and temperature
In the soils studied, the CBT values range from 0.23 to 1.71 with an average of 0.81 (Table 1).Even though this is a regional study, our CBT values span almost 70 % of the range of values published in the global calibration set (Weijers et al. 2007).CBT values and pH im of the Iberian soils are linearly  2a).However, CBT values are not correlated with MAT im or MAP im (Fig. 2b and c).Our results would then confirm the CBT relationship with pH.This is in contrast to previous studies that suggested that the calibration of soils above pH 7 needed to be revised (Loomis et al. 2011;Weijers et al. 2007).We also observed a significant correlation between pH im and MBT' values (R 2 = 0.71, p < 0.0001), which is even higher than the one observed in the global data set (Fig. 2d).As previous studies indicated that the variation in the MBT index is mostly explained by differences in soil pH and temperature (Weijers et al., 2007), we further compared MBT' of our samples to MAT im (Fig. 2e).
The range in MBT' values in the Spanish data set is similar to the one observed for the global data set (Peterse et al., 2012) despite a much narrower range of MAT im in our Iberian samples (10-18 • C; Table 1 and Fig. 2e).However, the relative abundance of methyl brGDGTs increases at higher temperatures in the Iberian samples.Thus, MBT' and MAT im show a weak but significant negative correlation within the Spanish sample set (R 2 = 0.21; p = 0.02) in contrast to the positive correlation between MBT and MAT observed by Weijers et al. (2007) and Peterse et al. (2012) for a global data set (Fig. 2e).
The MBT'/CBT values in the Iberian soils translate (using Eq. 5) to a MAT est of −0.9 to 9.4 • C and an average of 4.7 • C (Table 1).These estimated values are lower than the climatic atlas temperatures, which yields monthly air temperatures in the sample sites from 3 to 23 • C and annual mean values (i.e., MAT im ) from 10 to 18 • C. It is also noteworthy that the residuals of MAT est are not randomly distributed, since MBT'/CBT-derived temperatures consistently underestimate MAT im in the Iberian data set (Fig. 3d).This deviation was observed previously in the global data set, but it is more pronounced in the Iberian soils (Fig. 3d).Thus, MBT'/CBT-derived temperatures (MAT est ) in 17 out of the 23 soil samples underestimate MAT im by more than the 5 • C proxy calibration error found by Peterse et al. (2012;Fig. 3c, Table 1).For example, a soil sample close to the Zarracatín lagoon in the south of Spain (sample code ZA, Table 2), where monthly mean temperatures never fall below 11 • C and MAT im is 18 • C, has a MAT est value of 1.9 • C (Table 1).Even if we were to attempt a regional temperature calibration of the MBT', the weak correlation between MBT' and MAT im (Fig. 2e) would result in an error much higher than the 5 • C reported for the global data set (Peterse et al., 2012).Moreover, local calibrations have already been proven not to improve MBT'/CBT-based MAT accuracy (Peterse et al., 2012).
These findings would suggest caution in the use of the MBT'/CBT for paleotemperature reconstructions in the Iberian Peninsula, and support previous studies that showed that environmental parameters other than temperature may control the distribution of brGDGTs (e.g., Weijers et al., 2011;Peterse et al., 2012;Dirghangi et al., 2013;Loomis et al., 2013).Some studies have attributed the lack of correlation between MAT im and MBT/CBT to factors such as vegetation change, soil type and changes in hydrologic regime (e.g., Weijers et al., 2011;Dirghangi et al., 2013;Loomis et al., 2013).

Potential control of hydrological conditions on MBT'
We observe significant correlations between MAP im and MBT' (R 2 =0.55, p < 0.0001; Fig. 2f).This is similar to the observation from the global data set (Weijers et al. 2007;Peterse et al. 2012) where the MBT/CBT vs. MAP im correlation was interpreted as the result of covariation between temperature and precipitation (Weijers et al. 2007).Indeed in tropical sites higher precipitation is often associated with higher temperatures, but in arid regions, such as the southern Iberian Peninsula, the highest temperatures are usually found in the driest areas, not the wettest.In fact, in the Iberian soil data set we find a weak inverse correlation between MAP im and MAT im (MAT im = −0.0004MAP im +16, R 2 = 0.32, p = 0.017).Thus, our results suggest that sitespecific water availability may influence MBT' in the Iberian soils.This would be in agreement with previous studies that also suggested an effect of either precipitation or water content on the MBT in North American and Tibetan soils (Dirghangi, 2013;Wang et al., 2013).Peterse et al. (2012) also suggested an effect of precipitation on the MBT' index because the addition of temperate soil data to the global data set increased the scatter of the original MBT/CBT calibration (Weijers et al., 2007).The global MBT' values from Peterse et al. (2012) show indeed a large scatter in the 8-20 • C range (Fig. 3c inset), and the R 2 of the MBT' vs. MAT im correlation is only 0.09, much lower than the R 2 of 0.58 observed for the full −8 to 28 • C range of the global data set (Fig. 3c).Therefore, MBT' correlates poorly with MAT im in the temperate range, in which the Iberian Peninsula soil samples fall (Fig. 3c), regardless of the study area, and this should be taken into account in future regional studies.
Interestingly, the brGDGT abundances normalized to TOC (Fig. 4a), the MBT' (Fig. 2f), and the MAT est residuals (Fig. 4c) are significantly correlated with MAP im .This may indicate that under water stress the brGDGT-producing organisms are less productive and may have to adapt their membranes to water availability rather than temperature, resulting in the observed underestimation of MAT (Fig. 3d).Our data show that brGDGT abundances are lower under dryer (Table 2) and potentially oxic conditions, as has been shown in previous studies (e.g., Dirghangi et al., 2013;Wang et al., 2013).The physiological influence of changes in hydrological conditions on the degree of methylation of the brGDGTs is not yet known.It is possible that precipitation has an indirect influence on MBT' as the amount of precipitation can affect soil pH due to increased leaching of calcium and magnesium (Brady and Weil, 2002).Additionally, rainwater has a slightly acidic pH of 5.7 due to the dissolution of atmospheric CO 2 (Brady and Weil, 2002).But no correlation was observed between CBT (or pH im ) and MAP im at the investigated sites (Fig. 2c).Hence, a possible effect of precipitation on soil pH cannot explain the correlation between MBT' or MAT est residuals and MAP im .Alternatively, as precipitation is only one expression of hydrological conditions at a site, MBT' may also be influenced by soil type, vegetation and water circulation through percolation and evaporation.
Water availability is critical in semiarid soils affecting osmotic status and abundance of microbial cells as well as nutrient cycling (Bustamante et al., 2012, and references therein).In order to better estimate water availability, we used the aridity index (AI), a measure for moisture availability in soils excluding the specific impact of soil condition to adsorb and hold water (Trabucco and Zomer, 2009).The AI is a ratio of MAP and mean annual potential evaporation, and increases with more humid conditions (see Trabucco and Zomer, 2009, for details).It was calculated for each site using the approach followed by the Consortium for Spatial Information (CGIAR-CSI) based on United Nations Environment Programme (UNEP) criteria (Tables 1  and 2; Trabucco and Zomer, 2009).In the Iberian soils the brGDGT abundance shows a weak, albeit significant correlation with the AI (R 2 = 0.30, p = 0.006; Fig. 4b), but the AI has a much higher correlation with the MAT est residuals (R 2 = 0.71, p < 0.0001; Fig. 4d).In fact, the AI can explain 71 % of the variance in the residuals (Fig. 4d), and 53 % of the variance in the MBT' index (MBT' = 0.38AI + 002, n = 22, R 2 = 0.53, p < 0.001; Fig. 4e).MAP im also explains 55 % of the variance in the MBT' index but only 60 % in the MAT est residuals (Fig. 4c).This suggests that it is the soil's capacity to retain water, or soil moisture, rather than just precipitation that drives MBT' besides temperature and pH.Correlations between the MBT' and MAP have already been reported (Huguet et al., 2010a;Loomis, 2011;Dirghangi et al., 2013), but the validity of the correlation between MBT' and AI (Fig. 4e) has to be confirmed by analyzing brGDGTs in a larger number of soils.As mentioned above, the AI cannot explain all the variation observed in the MBT' (only 53 %, Fig. 4e), and other factors such as vegetation type or soil water retention capacity that also affect water availability most probably play a role.In fact vegetation type has already been shown to affect the MAT est values in North American soils (Weijers et al., 2011).
Our results have significant implications for the interpretation of paleotemperature records derived from the combined MBT' and CBT indices.Based on our analysis, we urge caution in the application of the proxy in arid environments and areas with an aridity index lower than 0.8, as we observe that MAT est accuracy in such locations is likely to be low, and with an error larger than the one provided in the global MBT'/CBT vs. MAT calibration (Peterse et al., 2012).The exact hydrological threshold below which water availability exerts a stronger control on the MBT' index than temperature will have to be determined in future studies.We recommend that hydrological conditions should be evaluated in conjunction with MBT'/CBT paleotemperatures in paleoreconstruction studies, for example through known paleohydrological proxies such as compound-specific δD values, whose analysis can even be carried out on the same lipid extracts (e.g.Sachse et al., 2012).

Conclusions
In soils from the Iberian Peninsula, the CBT index was shown to co-vary with soil pH with sufficient accuracy to confirm its use as a proxy for estimating paleo-soil pH in the region.The MBT' index was also shown to relate to soil pH, but the expected relation between MBT' and mean annual air temperatures (MAT im ) was not apparent.Due to these results, the application of the combined MBT' and CBT indices to estimate air temperatures does not seem appropriate in the Iberian Peninsula.
In contrast, the MBT' index was coupled with instrumental mean annual precipitation (MAP im ) and the aridity index (a ratio of MAP and mean annual potential evaporation).We thus argue that, under moisture shortage, MBT' is not coupled to temperature and is instead controlled by soil water availability.The validity of the correlation between MBT' and AI as well as the AI threshold below which MBT' might be biased needs to be contrasted in other soil types and study areas.Nonetheless, we suggest that these findings should be taken into account when interpreting MBT'/CBT climatic records from arid areas.

Table 1 .
Sample code and coordinates, instrumentally measured mean annual temperature (MAT im ), instrumentally measured mean annual precipitation (MAP im ), aridity index (AI), instrumentally measured pH (pH im ) and TOC (%).Soils were classified according to Soil Taxonomy(Soil Survey Staff, 2010) at group level.The calculated CBT and MBT' values, as well as derived pH (pH est ) and MAT (MAT est ), are also included.