Leaf Waxes and Hemicelluloses in Topsoils Reflect the δ2H and δ18O Isotopic Composition of Precipitation in Mongolia

Compound-specific hydrogen and oxygen isotope analyzes on leaf wax-derived n-alkanes (δ²H_n–alkane) and the hemicellulose-derived sugar arabinose (δ¹⁸O_ara) are valuable, innovative tools for paleohydrological reconstructions. Previous calibration studies have revealed that δ²H_n–alkane and δ¹⁸O_ara reflect the isotopic composition of precipitation, but – depending on the region – may be strongly modulated by evapotranspirative enrichment. Since no calibration studies exist for semi-arid and arid Mongolia so far, we have analyzed δ²H_n–alkane and δ¹⁸O_ara in topsoils collected along a transect through Mongolia, and we compared these values with the isotopic composition of precipitation (δ²H_p–WM and δ¹⁸O_p–WM, modeled data) and various climate parameters. δ²H_n–alkane and δ¹⁸O_ara are more positive in the arid south-eastern part of our transect, which reflects the fact that also the precipitation is more enriched in ²H and ¹⁸O along this part of the transect. The apparent fractionation ε_app, i.e., the isotopic difference between precipitation and the investigated compounds, shows no strong correlation with climate along the transect (ε_{2H n–C29/p} = −129 ± 14‰, ε_{2H n–C31/p} = −146 ± 14‰, and ε_{18O ara/p} = +44 ± 2‰). Our results suggest that δ²H_n–alkane and δ¹⁸O_ara in topsoils from Mongolia reflect the isotopic composition of precipitation and are not strongly modulated by climate. Correlation with the isotopic composition of precipitation has root-mean-square errors of 13.4‰ for δ²H_n–C29, 12.6 for δ²H_n–C31, and 2.2‰ for δ¹⁸O_ara, so our findings corroborate the great potential of compound-specific δ²H_n–alkane and δ¹⁸O_ara analyzes for paleohydrological research in Mongolia.

Introduction

Leaf wax-derived n-alkanes and hemicellulose-derived sugars are produced by higher terrestrial plants and stay well-preserved in soils and sediments, because of their resistance against biochemical degradation (Eglinton and Hamilton, 1967). These compounds and their compound-specific stable hydrogen (δ²H_n–alkane) and oxygen (δ¹⁸O_sugar) isotopic composition get incorporated into soils through above-ground and root litter, abrasion, as well as grazing (dung), and they have a mean residence time of ∼40 years (leaf wax n-alkanes), while pentoses (including the hemicellulose-derived sugar arabinose) average over ∼20 years (Schmidt et al., 2011). Since δ²H_n–alkane and δ¹⁸O_sugar are not strongly affected by degradation effects (Zech et al., 2011, 2012), they are increasingly used for paleohydrological reconstructions (Aichner et al., 2015; Hepp et al., 2015, 2019; Thomas et al., 2016; Rach et al., 2017; Schäfer et al., 2018; Bliedtner et al., 2020). Usually, they are interpreted to record the isotopic composition of precipitation (Sachse et al., 2006, 2012; Tuthorn et al., 2015; Hou et al., 2018; Hepp et al., 2020), which in turn is long acknowledged as a valuable proxy for paleoclimate reconstructions and controlled by e.g., the temperature and amount effect, continentality, and altitude (Dansgaard, 1964). The isotopic signal of precipitation can be altered by isotopic fractionation at the soil-plant-atmosphere interface, including evaporative enrichment of soil water (ε_SW), transpirative enrichment of leaf water (ε_Et) and biosynthetic fractionation (ε_bio) (Schimmelmann et al., 2006; Sachse et al., 2012; Liu et al., 2016; Cormier et al., 2018; Liu and An, 2019).

ε_SW and ε_Et can lead to more positive δ²H_n–alkane and δ¹⁸O_sugar values relative to precipitation and/or the plants source water. ε_SW is probably of minor importance under semi-arid and arid conditions because most plants (especially perennial plants) exploit deeper water sources that are not isotopically affected by evaporation (Feakins and Sessions, 2010; Kahmen et al., 2013a; Berke et al., 2015), while ε_Et has a significant influence on δ²H_n–alkane and δ¹⁸O_sugar (Hou et al., 2008; Feakins and Sessions, 2010; Tuthorn et al., 2014, 2015; Berke et al., 2015; Cernusak et al., 2016; Liu et al., 2017). During biosynthesis, ε_bio leads to ²H depletion of ∼−160‰ in δ²H_n–alkane values and ¹⁸O enrichment of ∼+27‰ in δ¹⁸O_sugar values. At the same time, it is reported that ε_bio can vary among plant life forms and plant physiological metabolisms, for different environmental conditions and latitudes, as well as through relative contributions of the strongly depleted NADPH pool (Sessions et al., 1999; Kahmen et al., 2013b; Newberry et al., 2015; Liu et al., 2016; Sessions, 2016; Lehmann et al., 2017; Cormier et al., 2018; Griepentrog et al., 2019; Liu and An, 2019). The apparent fractionation (ε_{2H n–alkane/p}, ε_{18O sugar/p}), i.e., the difference between the isotopic signature of precipitation/source water (δ²H_p and δ¹⁸O_p) and δ²H_n–alkane and δ¹⁸O_sugar, respectively, basically integrates over ε_SW, ε_Et and ε_bio and results in ²H-depleted leaf wax-derived n-alkanes but ¹⁸O-enriched hemicellulose-derived sugars relative to δ²H_p and δ¹⁸O_p (Sachse et al., 2012; Tuthorn et al., 2015; Daniels et al., 2017; Liu and An, 2019; Strobel et al., 2020).

While some studies suggest that ε_{2H n–alkane/p} in plants and topsoils remains relatively constant over latitudinal distances (Liu et al., 2016, Liu and An, 2019; Vogts et al., 2016), many others show correlations of ε_{2H n–alkane/p} with relative humidity, mean annual precipitation (MAP) and the aridity index (AI) (Hou et al., 2008, 2018; Douglas et al., 2012; Tipple and Pagani, 2013; Berke et al., 2015; Herrmann et al., 2017; Li et al., 2019). This can be related to more evapotranspirative enrichment under more arid conditions, but plant physiological adaptations might also play a role, as well as changes in vegetation, as e.g., monocotyledons have more negative δ²H_n–alkane values than dicotyledons (Sachse et al., 2012; Kahmen et al., 2013b; Hepp et al., 2020). For relatively arid regions in the United States and South Africa, Hou et al. (2008), Feakins and Sessions (2010), and Strobel et al. (2020) found no correlations of ε_{2H n–alkane/p} with climate, and they reported constant, but quite different values (−94 ± 21‰, -99 ± 8‰, and −133 ± 12‰, respectively).

So far, only very few calibration studies applied compound-specific δ¹⁸O_sugar analyzes (Tuthorn et al., 2015; Hepp et al., 2016, 2020; Strobel et al., 2020). For semi-arid and arid regions in South America and South Africa, Tuthorn et al. (2015) and Strobel et al. (2020) suggest enhanced evapotranspirative enrichment and higher ε_{18O sugar/p} values with increasing aridity.

By now, δ²H_n–alkane and δ¹⁸O_sugar topsoil calibration studies on modern reference material do not exist for semi-arid and arid Mongolia, so it is not clear whether δ²H_n–alkane and δ¹⁸O_sugar reflect the isotopic composition of precipitation and/or are strongly modulated by evapotranspirative enrichment and climate conditions. Therefore, the aim of this study is to evaluate the influence of different climatic factors on the isotopic composition of leaf wax-derived n-alkanes (δ²H_n–alkane) and the hemicellulose-derived sugar arabinose (δ¹⁸O_ara) in topsoils from semi-arid and arid Mongolia. More specifically, we addressed the following research questions:

(1) Do δ²H_n–alkane and δ¹⁸O_ara reflect the isotopic composition of precipitation along the investigated transect?

(2) Do ε_{2H n–alkane/p} and ε_{18O ara/p} indicate a variable and climate-dependent fractionation on δ²H_n–alkane and δ¹⁸O_ara?

Our study will provide the necessary basis for using δ²H_n–alkane and δ¹⁸O_ara for paleohydrological and -climatological reconstructions in semi-arid and arid Mongolia and similar regions.

Materials and Methods

Study Area and Sampling

The semi-arid and arid regions of Mongolia are influenced by three major atmospheric circulation systems (Figure 1A). Summer climate is mainly dominated by the Westerlies and the East Asian summer monsoon (EASM) (Wang and Feng, 2013; Rao et al., 2015). Winter climate is dominated by the Siberian high blocking the Westerlies and thus moisture supply during winter (Yamanaka et al., 2007; Liu et al., 2009). This results in short and hot summers and long, cold, and dry winters and overall harsh conditions (Dashkhuu et al., 2015). Especially the vegetation period, during which biosynthesis can take place, is very short and corresponds with the summer months June, July, and August, when ∼75% of the annual precipitation occurs (Figures 1D,E, 2H; Lang et al., 2020).

FIGURE 1

Figure 1. (A) Map of Mongolia showing δ¹⁸O_p–OIPC (Bowen, 2019) and the sampling locations. Black circles indicate samples which were analyzed for δ²H_n–alkane only, whereas black/white circles indicate samples which were analyzed for δ²H_n–alkane and δ¹⁸O_ara. (B) Submap showing a closeup of (A). (C) Map of Mongolia showing mean annual precipitation (Fick and Hijmans, 2017). (D,E) Climate diagrams illustrating the seasonal variability of precipitation and temperature (1970–2000; Fick and Hijmans, 2017), as well as the variability of δ¹⁸O_p–OIPC (Bowen, 2019) for (D) western Mongolia and (E) southern Mongolia.

FIGURE 2

Figure 2. δ²H and δ¹⁸O signatures of leaf wax-derived n-alkanes and the hemicellulose sugar arabinose as well as their apparent isotope fractionation (ε_app), compared to environmental and climatic parameters along the transect. (A) Compound-specific δ²H of the leaf wax-derived n-alkane n-C₂₉ (black) and n-C₃₁ (green) (this study), (B) compound-specific δ¹⁸O_ara (this study), (C) ε_{2H n–C29/p} (black) and ε_{2H n–C31/p} (green) (this study), (D) ε_{18O ara/p} (this study), (E,F) OIPC isotopic composition of precipitation (black line) and amount-weighted isotopic signature of precipitation (blue line): δ²H_p (E), and δ¹⁸O_p (F), respectively (Bowen et al., 2005; IAEA/WMO, 2015; Fick and Hijmans, 2017; Bowen, 2019), (G) the potential evapotranspiration (Et₀) (Trabucco and Zomer, 2019), (H) mean annual temperature (MAP) (Fick and Hijmans, 2017), (I) averaged summer temperature of June, July, and August (T_JJA), (J) black line shows the mean annual precipitation (MAP), blue shaded area the summer precipitation amount (P_JJA) (Fick and Hijmans, 2017), (K) the aridity index (AI) (Trabucco and Zomer, 2019), and (L) the altitude (Jarvis et al., 2008).

The climate in Mongolia is characterized by increasing mean annual temperature (MAT) and decreasing mean annual precipitation (MAP) toward the south-east (Figure 1C). This climate gradient is mirrored in regional vegetation biomes, well-adapted to the semi-arid and arid conditions of Mongolia. Northern and central Mongolia are characterized by taiga, mountain- and forest steppe biomes, whereas steppe and desert steppe biomes are dominant in southern Mongolia (Hilbig, 1995; Klinge and Sauer, 2019). The precipitation shows a distinct ²H_p–OIPC and ¹⁸O_p–OIPC enrichment in southern and eastern arid Mongolia (Figure 1A; Bowen, 2019), and the seasonal pattern is characterized by isotopically ²H- and ¹⁸O-depleted precipitation during winter and ²H- and ¹⁸O-enriched precipitation during summer (see Figures 1D,E for δ¹⁸O_p–OIPC).

For this study, topsoils (0–5 cm) were sampled in LDPE plastic bags in June/July 2017 (ID: 1–33) and June 2016 (ID: 34–42). To prevent molding, samples were stored open and dark during the 2-week field campaigns. Our sampling sites were dominated by different Poaceae and Cyperaceae species (grasses) as well as herbaceous and shrubby growth forms of Artemisia spp. and the woody shrub Caragana spp. Larix sibirica occurred at a few sites (for more details, see Struck et al., 2020). The investigated transect follows a west-east and north-south gradient with increasing aridity and ²H_p and ¹⁸O_p enrichment toward eastern and southern Mongolia (Figures 1A,B, 2 – all sampling sites and respective climate parameters are listed in the Supplementary Material).

Biomarker Extraction and Chromatography

Total lipids of 42 topsoils (∼10–35 g) were extracted with dichloromethane:methanol (9:1, v/v) over three cycles using accelerated solvent extraction and ultrasonic extraction. Total lipid extracts were separated over aminopropyl pipette columns (Supelco; 45 μm), n-alkanes were eluted with hexane and additionally cleaned over coupled silver-nitrate (AgNO₃) coated silica gel (Supelco, 60–200 mesh) and zeolite (Geokleen Ltd.) pipette columns. n-Alkane identification and quantification were performed on an Agilent 7890B gas chromatograph equipped with an Agilent HP5MS column (30 m × 320 μm × 0.25 μm film thickness) and a flame ionization detector (GC-FID). For identification and quantification, external n-alkane standards (n-alkane mix n-C₂₁ – n-C₄₀, Supelco) were measured with each sequence.

While the n-alkanes had been extracted and quantified in a previous study (Struck et al., 2020) and were available and ready for compound-specific δ²H analyzes, we have selected 28 sampling sites for additional sugar analyzes. Hemicellulose-derived sugars were hydrolytically extracted from 0.1 to 1.4 g topsoil material using 10 ml of 4M trifluoroacetic acid at 105°C for 4 h according to Amelung et al. (1996). Thereafter, samples were vacuum-filtrated over glass fiber filters and the extracted sugars were cleaned over XAD-7 and Dowex 50WX8 columns to remove humic-like substances and cations (Zech and Glaser, 2009). The purified sugar samples were rotary-evaporated and derivatized with methylboronic acid (4 mg in 400 μl pyridine) at 60°C for 1 h. α-Androstane and 3-O-Methyl-Glucose were used as internal standards (Zech and Glaser, 2009).

Stable Isotope Analyzes

The compound-specific hydrogen isotopic composition of the most abundant n-alkanes (n-C₂₉, n-C₃₁) were measured on an Isoprime Vision isotope ratio mass spectrometer (IRMS) (Elementar, Langenselbold, Germany) coupled to an Agilent 7890B GC (Agilent, Santa Clara, United States) via a GC5 pyrolysis/combustion interface (Elementar, Langenselbold, Germany). The GC5 was operating in pyrolysis mode with a Cr (ChromeHD) reactor at 1050°C. The GC was equipped with a split/splitless injector and an Agilent HP5GC fused silica column (30 m × 320 μm × 0.25 μm film thickness). Samples were injected in splitless mode and measured as triplicates. For normalization, n-alkane standards (n-C₂₇, n-C₂₉, and n-C₃₃) with known isotopic composition (Schimmelmann standard, Indiana) were measured as duplicates after every third sample triplicate. All measurements were drift-corrected relative to the standards in each sequence. The H${}_3^{+}$-correction factor was checked regularly throughout the sequence and yielded stable values of 3.9 ± 0.02 (n = 4). The standard deviation of the sample triplicates was on average 1.2 and 1.0 for n-C₂₉ and for n-C₃₁, respectively, and not worse than 3.6 and 4.7‰. The standard deviation for all standards was better than 2‰ (n = 36). The hydrogen isotopic composition is given in delta notation (δ²H) vs. Vienna Standard Mean Ocean Water (VSMOW).

The compound-specific oxygen isotope measurements were performed on a Trace GC 2000 coupled to a Delta V Advantage IRMS using an ¹⁸O-pyrolysis reactor (GC IsoLink) and a ConFlo IV interface (all devices from Thermo Fisher Scientific, Bremen, Germany). Samples were injected in splitless mode and measured in triplicates. For normalization, derivatized sugar standards with known isotopic composition were measured repeatedly at different concentrations within every sequence. Measured δ¹⁸O values were drift- and amount-corrected and corrected for the oxygen from the carbonyl group within the sugar molecules that became introduced during the hydrolysis according to Zech and Glaser (2009). The standard deviation of the sample triplicates was on average 0.4‰, and not worse than 1.2‰. The standard deviation of the arabinose standard was 1.8‰ (n = 24, average over four concentrations). Fucose and xylose concentrations were too low for robust isotope measurements; we therefore refrained from further evaluation of those data. The oxygen isotopic composition is given in delta notation (δ¹⁸O) vs. VSMOW.

Data Analysis

Apparent fractionation (ε_app) of hydrogen- and oxygen isotopes were calculated after Sauer et al. (2001) to test for climatic/environmental controls on δ²H_n–alkane (Eq. 1) and δ¹⁸O_ara (Eq. 2).

$${\mathrm{\epsilon }}_{2\mathrm{H}\mathrm{n}\text{-}alkane/\text{p}}=\left(\left[{\displaystyle \frac{{\mathrm{\delta }}^2{H}_{\mathrm{n}\text{-}\mathrm{alkane}}+1000}{{\mathrm{\delta }}^2{H}_{\text{p}}+1000}}\right]-1\right)\mathrm{x}\mathrm{\hspace{0.33em}1000}[\text{‰}](1)$$

$${\mathrm{\epsilon }}_{18\mathrm{O}\mathrm{ara}/\text{p}}=\left(\left[{\displaystyle \frac{{\mathrm{\delta }}^{18}{O}_{\text{ara}}+1000}{{\mathrm{\delta }}^{18}{O}_{\text{p}}+1000}}\right]-1\right)\mathrm{x}\mathrm{\hspace{0.33em}1000}[\text{‰}](2)$$

δ²H_p–OIPC and δ¹⁸O_p–OIPC were extracted from The Online Isotopes in Precipitation Calculator (OIPC, Version 3.1)¹, the uncertainty estimates (95% confidence interval) range from 1 to 8‰ for δ²H_p–OIPC, and from 0.2 to 0.8‰ for δ¹⁸O_p–OIPC, respectively (Bowen et al., 2005; IAEA/WMO, 2015; Bowen, 2019). Since ∼75% of the annual precipitation occurs during the vegetation period in June, July, and August, an amount-weighted mean (δ²H_p–WM and δ¹⁸O_p–WM) was used to calculate ε_{2H n–alkane/p} and ε_{18O ara/p} (Eqs. 1, 2). MAT and MAP, as well as the temperature and precipitation of June, July and August (T_JJA, P_JJA) were extracted from the WorldClim 2.0 dataset (1970–2000, 30 s resolution: Fick and Hijmans, 2017)². The AI and the potential evapotranspiration (Et₀) were derived from the Global Aridity Index and Potential Evapotranspiration Climate Database v2 (1970–2000, 30 s resolution: Trabucco and Zomer, 2019)³. The altitude was extracted from the Shuttle Radar Topography Mission (SRTM) data (Jarvis et al., 2008).

Correlations of δ²H_n–alkane and δ¹⁸O_ara with δ²H_p–WM and δ¹⁸O_p–WM, respectively were tested using weighted linear regressions. Correlations of ε_{2H n–alkane/p} and ε_{18O ara/p} with climate were tested using unweighted linear regressions. Goodness of fit can be assessed using R², and the accuracy using root-mean-square errors (RMSE). Differences between the arid part of the transect (ID: 34–42) compared to the rest were analyzed using a t-test. For data sets with unequal variance, the Welsh-corrected t-test was used. Statistical analyzes were done using the statistical software Origin 2019b.

Results

Along our investigated transect, δ²H_n–C29 ranges from −215 to −143‰, with an average of −189 ± 16‰. In comparison to δ²H_n–C29, the δ²H_n–C31 values tend to be more ²H-depleted and range from −228 to −154‰ with an average of −205 ± 15‰ (Figure 2A). The δ¹⁸O_ara values range from +31‰ to +41‰ with an average of +35 ± 3‰ (Figure 2B). All compounds show the same trend as the isotopic composition of precipitation (Figures 2E,F), and are significantly more positive in the arid part of the transect (ID: 34 – 42) compared to the rest (δ²H_n–C29: p = 0.02, δ²H_n–C31: p = 7.08e^–4, δ¹⁸O_ara: p = 2.95e^–5). This reflects the ²H and ¹⁸O enrichment of the isotopic composition of precipitation, with values ranging from −101 to −53‰ for δ²H_p–OIPC and from −14 to −7‰ for δ¹⁸O_p–OIPC, respectively. The amount-weighted mean values are more positive and range from −78 to −46‰ for δ²H_p–WM and −11 to −6‰ for δ¹⁸O_p–WM, respectively. Like the biomarkers, the precipitation is significantly more positive in the arid part of the transect (δ²H_p–WM: p = 1.39e^–15, δ¹⁸O_p–WM: p = 1.32e^–17, Figures 2E,F).

ε_{2H n–C29/p} ranges from −165 to −95‰ with an average of −129 ± 14‰ (Figure 2C). In comparison, ε_{2H n–C31/p} is more negative, ranging from −171 to −100‰ with an average of −146 ± 14‰ (Figure 2C). ε_{18O ara/p} ranges from + 39‰ to + 48‰ with an average of + 44 ± 2‰ (Figure 2D). ε_app is not statistically different in the arid part of the transect (ε_{2H n–C29/p}: p = 0.79, ε_{2H n–C31/p}: p = 0.554, ε_{18O ara/p}: p = 824).

Discussion

Differences in Compound-Specific δ²H

Along the investigated transect δ²H_n–C29 is on average ∼15‰ more positive than δ²H_n–C31. As described previously by Struck et al. (2020), n-C₂₉ is the most abundant homolog in the woody shrubs Caragana spp. and Artemisia spp., whereas n-C₃₁ is the most abundant homolog in grasses. Since shrubs and dicotyledonous plants in general are more sensitive to evapotranspirative enrichment than grasses (Sachse et al., 2012; Kahmen et al., 2013b; Hepp et al., 2020), the observed offset might indicate (i) plant-physiological differences affecting the evapotranspirative enrichment of different plants, and (ii) plant-physiological differences affecting ε_bio.

Grasses grow via the intercalary meristem, where the leaf water is isotopically not as ²H-enriched due to transpiration compared to the exposed part of grasses (Helliker and Ehleringer, 2000, 2002; Lehmann et al., 2017; Liu et al., 2017). The leaf wax n-alkanes, which are produced in the intercalary meristem, do therefore not incorporate the full leaf water enrichment signal (Barbour et al., 2004; Ripullone et al., 2008; Sachse et al., 2012; Kahmen et al., 2013b; Cernusak et al., 2016; Holloway-Phillips et al., 2016). This can be referred to as “dampening effect”.

δ²H_n–alkane and δ¹⁸O_ara Against the Isotopic Composition of Precipitation

The δ²H_n–alkane and δ¹⁸O_ara values correlate significantly with the δ²H_p–WM and δ¹⁸O_p–WM values (Figure 3, R² = 0.30, p = 3.22e^–4 for δ²H_n–C29; 0.11 and 0.03 for δ²H_n–C31; and 0.36 and 1.60e⁻³ for δ¹⁸O_ara). Significant correlations between compound-specific biomarker isotopes and the isotopic composition of precipitation have been observed previously for different regions (a.o.: Sachse et al., 2006; Feakins and Sessions, 2010; Hou et al., 2018; Li et al., 2019; Strobel et al., 2020). In comparison to transects covering larger climate gradients (a.o. Hou et al., 2018), our determination coefficients are small and explain only up to ∼30% of the variability. However, this is due to the fact that our transect covers only a small climate gradient. The RMSE is 13.4‰ for δ²H_n–C29, 12.6‰ for δ²H_n–C31 and 2.2‰ for δ¹⁸O_ara (Figure 3) and thus indicates that the biomarkers accurately record the isotopic composition of precipitation along our transect. There are several possible explanations for the observed scatter, including: (i) uncertainties related to the modeled OIPC-based isotopic composition of precipitation and the WorldClim 2.0 reanalysis dataset, (ii) the analytical errors of the δ²H_n–alkane and δ¹⁸O_ara measurements, (iii) micro-climatic effects along the investigated transect, and (iv) metabolic differences affecting ε_bio (Sachse et al., 2012; Fick and Hijmans, 2017; Cormier et al., 2018; Hou et al., 2018; Bowen, 2019; Strobel et al., 2020; Struck et al., 2020).

FIGURE 3

Figure 3. δ²H signatures of the leaf wax-derived n-alkanes (A) n-C₂₉ and (B) n-C₃₁, as well as (C) δ¹⁸O_ara signatures from the topsoil transect through Mongolia plotted against the amount-weighted δ²H and δ¹⁸O signature of precipitation (δ²H_p–WM/δ¹⁸O_p–WM). Red trend lines illustrate linear regressions, gray shaded areas the 95% confidence interval. Bold R²/p-values indicate the level of significance (α = 0.05).

Apparent Fractionation Against Climate

To check for potential climatic influences on δ²H_n–alkane and δ¹⁸O_ara, we correlated apparent fractionation against T_JJA, P_JJA, Et₀ and AI (Figure 4), as well as MAT, MAP, and altitude (Supplementary Figure 1). None of the correlations with climate is significant, except ε_{2H n–C29/p} and precipitation, which is only weak (R² = 0.20, p = 4.90e⁻³ for P_JJA, and R² = 0.12, p = 0.03 for MAP). However, if climatically-controlled one might expect that temperature, potential evapotranspiration and the degree of aridity also affect evapotranspirative enrichment and ε_app (Hou et al., 2018). Thus, this correlation should not be overinterpreted. We conclude that ε_app is nearly constant with ε_{2H n–C29/p} = −129 ± 14‰, ε_{2H n–C31/p} = −146 ± 14‰, and ε_{18O ara/p} = + 44 ± 2‰.

FIGURE 4

Figure 4. Apparent fractionation ε_{2H n–C29/p}, ε_{2H n–C31/p} and ε_{18O ara/p} from the topsoil transect through Mongolia plotted against T_JJA, P_JJA, Et₀, AI (Fick and Hijmans, 2017; Trabucco and Zomer, 2019). Red trend lines illustrate linear regressions, gray shaded areas the 95% confidence interval. Bold R²/p-values indicate the level of significance (α = 0.05). Black dashed lines illustrate values for the biosynthetic fractionation, and black arrows indicate the effect of evapotranspirative enrichment (biosynthetic fractionation factors of −160 and +27‰ are assumed for the n-alkanes and arabinose, respectively).

Assuming constant ε_bio values of −160‰ for leaf wax n-alkanes (Sessions et al., 1999; Hepp et al., 2020), evapotranspirative enrichment would be ∼31‰ for δ²H_n–C29 and ∼15‰ for δ²H_n–C31 (Figure 4). While n-C₂₉ is the most abundant homolog in shrubs, and n-C₃₁ is the most abundant homolog in grasses (Bliedtner et al., 2018; Struck et al., 2020) the observed offset in evapotranspirative enrichment most likely results from plant physiological differences described above, particularly the dampening effect. Assuming a constant ε_bio factor of +27‰ for arabinose (Lehmann et al., 2017; Hepp et al., 2020) evapotranspirative enrichment would be ∼17‰ for δ¹⁸O_ara. While we expect arabinose to be mainly synthesized by grasses (Mekonnen et al., 2019), we cannot quantify the contribution from other plants or roots (Schädel et al., 2010). Anyhow, for arabinose synthesized by grasses, we can expect a similar dampening effect as described above for leaf waxes, because leaf water in the leaf growth-and-differentiation zone is usually not as enriched as the exposed part of grasses (Lehmann et al., 2017; Liu et al., 2017; Hepp et al., 2020).

Comparison With Other Studies

While other calibration studies in relatively arid regions have also not found a strong climatic modulation of ε_{2H n–alkane/p}, our values (−129 ± 14‰ for ε_{2H n–C29/p} and −146 ± 14‰ for ε_{2H n–C31/p}) are only comparable to those from Strobel et al. (2020), i.e., −133 ± 12‰ for n-C31 and n-C33, which are much more negative than those reported by Hou et al. (2008) and Feakins and Sessions (2010), i.e., −99 ± 8‰ and −92 ± 21‰, respectively. Most likely, plant physiological and metabolic adaptations play an important role, as leaf waxes from C₄ plants are more enriched in ²H than leaf waxes from C₃ plants, and dicotyledons produce more enriched leaf waxes than monocotyledons (Sachse et al., 2012; Kahmen et al., 2013b; Hepp et al., 2020). Li et al. (2019) reported very similar ε_{2H n–C29/p} values as for Mongolia from the semi-arid and arid regions in China (−127 ± 10‰ compared to −129 ± 14‰), yet ε_{2H n–C31/p} is much less negative than in Mongolia (−133 ± 13‰ compared to −146 ± 14‰). We suggest that this reflects the fact that C₄ grasses are more dominant in China than along our transect that is dominated by C₃ grasses (Pyankov et al., 2000). Our ε_{2H n–C31/p} values are also very much comparable to those reported for C₃ grass sites along a transect in Europe (Hepp et al., 2020), and our ε_{2H n–C29/p} values are in very good agreement with their ε_{2H n–alkane/p} values for sites dominated by deciduous trees, which ones more highlights the dampening effect of C₃ grasses compared to dicotyledons.

The ε_{18O ara/p} values for Mongolia (44 ± 2‰) are very similar to values reported by Strobel et al. (2020) for relatively arid regions in South Africa. There, the more humid regions have a significantly lower ε_{18O ara/p} (∼37‰), quite similar to the C₃ grass sites in Europe (Hepp et al., 2020). The deciduous tree sites in Europe, however, are again characterized by more enriched δ¹⁸O_sugar values (ε_{18O sugar/p} = ∼43‰). All this indicates that δ¹⁸O is more sensitive to evapotranspirative enrichment than δ²H, so that climate can more strongly modulate δ¹⁸O_sugar, and again that grasses show the signal dampening much more pronounced than dicotyledons.

Conclusion

This study investigated compound-specific δ²H_n–alkane and δ¹⁸O_ara values in topsoils collected along a transect through semi-arid and arid Mongolia in order to evaluate to which degree they reflect variations in the isotopic signature of precipitation and/or they are affected by climate and evapotranspirative enrichment. We therefore tested for correlations of δ²H_n–alkane and δ¹⁸O_ara with δ²H_p–WM and δ¹⁸O_p–WM, respectively, as well as ε_app with climate. We can conclude the following:

• Leaf wax-derived n-alkanes and the hemicellulose-derived sugar arabinose are significantly more enriched in ²H and ¹⁸O in the more arid southern and eastern parts of the transect. This reflects the changes in the isotopic composition of precipitation along the transect, and the correlations with δ²H_p–WM and δ¹⁸O_p–WM have RMSE of 13.4‰ for δ²H_n–alkane and 2.2‰ for δ¹⁸O_ara.

• The apparent fractionation remains mostly constant at −129 ± 14‰, −146 ± 14‰, and at + 44 ± 2‰ for ε_{2H n–C29/p}, ε_{2H n–C31/p} and ε_{18O ara/p}, respectively. There are no significant differences along the transect, nor strong correlations with climate.

Compound-specific δ²H_n–alkane and δ¹⁸O_ara analyzes on terrestrial biomarkers, preserved e.g., in lake sediments, have great potential for reconstructing past changes in the isotopic composition of precipitation and thus for paleoclimate and -hydrological reconstructions in Mongolia.

Data Availability Statement

The datasets presented in this study can be found in the article/Supplementary Material.

Author Contributions

JS, MB, PS, MZ, and RZ designed the study. MB and RZ collected the samples along transect I in 2016. JS and RZ collected the samples along transect II in 2017. JS carried out the major part of the laboratory analyzes in the laboratory of RZ and BG, assisted by LB, PS, and MB. EB, DA, and WZ organized the sample logistics in 2016 and 2017. JS wrote the manuscript with contributions of all coauthors. All authors contributed to the article and approved the submitted version.

Funding

This research was supported by the SNF (Grant No. PP00P2 – 150590).

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Acknowledgments

We thank the Swiss National Science Foundation (SNF) for funding. PS acknowledges the support by a fellowship from the state of Thuringia (Landesgraduiertenstipendium). DA gratefully acknowledges the support of the framework of Goszadanie no. AAAA-A17-117011810038-7. Furthermore, we greatly acknowledge M. Benesch (Martin Luther University Halle-Wittenberg) for compound-specific δ¹⁸O measurements and N. Ueberschaar (MS platform, Friedrich-Schiller-University Jena) for providing laboratory facilities. I. K. Schäfer (Agilent) and J. Wintel (Elementar) are acknowledged for support during δ²H measurements. We want to acknowledge H. Maennicke, C. Heinrich, T. Bromm, S. Polifka, M. Lerch (all Martin Luther University Halle-Wittenberg), M. Wagner, F. Freitag, I. Paetz, and N. Blaubach (all Friedrich-Schiller-University Jena) for laboratory support. We thank our logistic partners in Mongolia, especially G. Gereltsogt from Remote Mongolian Adventures and all field trip participants 2016 and 2017. We thank ML and M-AC for their valuable and helpful comments on this manuscript.

Supplementary Material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/feart.2020.00343/full#supplementary-material

Footnotes

1. ^ http://www.waterisotopes.org
2. ^ http://worldclim.org/version2
3. ^ https://cgiarcsi.community/data/global-aridity-and-pet-database/

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