PUBLICATIONS Geophysical Research Letters RESEARCH LETTER 10.1002/2014GL062004 Key Points: • Leaf water δD could “inherit” the precipitation δD values far better 18 than δ O • Leaf water δD values were apparently modified by RH outside of the rainy season • Leaf water δD values were affected by monsoon precipitation in the rainy season
Influences of relative humidity and Indian monsoon precipitation on leaf water stable isotopes from the southeastern Tibetan Plateau Wusheng Yu1,2, Baiqing Xu1, Chun-Ta Lai3, Yaoming Ma1, Lide Tian1, Dongmei Qu1, and Zhiyong Zhu1 1 Key Laboratory of Tibetan Environment Changes and Land Surface Processes, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, China, 2CAS Center for Excellence in Tibetan Plateau Earth Sciences, Beijing, China, 3Department of Biology, San Diego State University, San Diego, California, USA
This project report results of the first leaf water δ18O and δD time series of the woody plant Quercus aquifolioides undertaken on the southeastern Tibetan Plateau (STP). The data show that δD of leaf water underwent less enrichment than δ18O relative to precipitation and soil water, and could “inherit” the δD value characteristics of precipitation far better than δ18O. The leaf water δD values were strongly modified by evaporative enrichment in response to lower and more drastically changing relative humidity observed outside of the rainy season. In comparison, leaf water δD values more closely tracked those observed in the monsoon precipitation (acted as source water) in the rainy season. Our findings suggest that leaf water δD values from the STP were sensitive to the Indian monsoon activities, and the effects of relative humidity and the Indian monsoon precipitation should be considered for stable isotopes in tree ring cellulose or other biomarkers studies on the STP.
Abstract
Supporting Information: • Readme • Figure S1 Correspondence to: W. Yu,
[email protected]
Citation: Yu, W., B. Xu, C.-T. Lai, Y. Ma, L. Tian, D. Qu, and Z. Zhu (2014), Influences of relative humidity and Indian monsoon precipitation on leaf water stable isotopes from the southeastern Tibetan Plateau, Geophys. Res. Lett., 41, 7746–7753, doi:10.1002/ 2014GL062004. Received 25 SEP 2014 Accepted 20 OCT 2014 Accepted article online 22 OCT 2014 Published online 12 NOV 2014
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1. Introduction Known as the “third pole,” the Tibetan Plateau region provides a key study area to examine past climate variability using, for example, palaeoclimate records preserved in ice cores [Yao et al., 1996; Thompson et al., 2000], speleothems [Cai et al., 2010], tree rings [Treydte et al., 2006], and lake sediments [Mügler et al., 2008; Zech et al., 2014]. In recent decades, some scientists have launched projects on stable isotopes in precipitation to better understand atmospheric moisture transport to the Tibetan Plateau and the surrounding regions [Yao et al., 1996, 2013; Tian et al., 2001, 2007; Yu et al., 2008, 2014]. These and other studies of precipitation-stable isotopes [Araguás-Araguás et al., 1998; Vuille et al., 2005] have emphasized the importance of understanding the key influences that control δ18O and δD variations in order to interpret paleoclimatic and paleoenvironmental records. Previous studies have found that precipitation-stable isotope variations in the southern region of the Tibetan Plateau differ distinctly from those in the northern region [Tian et al., 2007; Yu et al., 2008]. Studies of δ18O and δD in water vapor [Yu et al., 2005], river water [Hren et al., 2009], and lake water [Yuan et al., 2011] have also been conducted. However, a gap exists in the studies of δ18O and δD variations in plant’s leaf water on the Tibetan Plateau. During biosynthesis, leaf water serves as medium water between source water (precipitation/soil water) and cellulose or leaf wax lipid δD values or other biomarkers and contributes to δ18O and δD of plant organic matter [Epstein and Yapp, 1977; Yakir, 1992]. Hence, an improved understanding of δ18O and δD of plant organic matter requires detailed knowledge of the isotope compositions of leaf water. In particular, interpretation of the isotope data in tree ring cellulose on the Tibetan Plateau can be confusing without considering the effect of Indian monsoon. For example, in Zech et al. [2014], the authors related variability in δ18O of the lake sediment from the southern slope of the central Himalayan mountains (28°02′N, 85°43′E, 4050 m above sea level (asl)) to the activity of the Indian monsoon. In this case, the interpretation of stable isotope records in sediment archives should be based on the knowledge of variations of stable isotopes in plant’s water (medium water between source water and cellulose or other biomarkers) and their relationships with meteorological conditions. Shi et al. [2011] found that the tree ring δ18O record from the southeastern Tibetan Plateau (STP) (95°33′E, 29°52′N, 2759 m asl) appears significantly anticorrelated with summer precipitation amount, regional cloud cover, and relative humidity and suggested that the tree ring cellulose δ18O is a promising proxy to reconstruct regional summer moisture variability prior to the instrumental period. Xie et al. [2012]
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Figure 1. Map of the sampling site at Lulang (red dot) on the STP. The location of Lhasa (white dot) is also shown.
demonstrated that precipitation amount and δD in precipitation are both important in determining δD values of terrestrial n-alkane in the sediments from Lake Chen Co on the southern Tibetan Plateau (28°58′N, 90°33′E, 4420 m asl). However, both studies did not consider the impacts of the Indian monsoon. With this background, we first launched a project in 2007 to collect different water samples (precipitation/soil water/plant water) at Lulang on the Tibetan Plateau, especially samples from plant Quercus aquifolioides leaves. We surveyed the seasonal changes and isotope fractionations in δ18O and δD of the different water samples and revealed the relationships between the isotopic compositions of the different water samples and different atmospheric circulation systems. In this case, our study provided a possible new route for the reinterpretation of stable isotopes in tree ring cellulose or in other biomarkers on the STP and adjacent regions.
2. Sampling Sites, Materials, and Methods 2.1. Study Area Our sampling site lies at the Southeast Tibet Station for Alpine Environment Observation and Research (STSAEOR), Chinese Academy of Sciences (CAS), located at Lulang on the STP, China (Figure 1). Lulang (94°44′E, 29°46′N, 3335 m asl) sits in a narrow south-north trending river valley, located north of the Yarlung Tsangpo River, with an average annual air temperature of 5.5°C, an annual precipitation of 800–1000 mm, and an average annual relative humidity of 73.5%. The main vegetation types are subalpine dark coniferous forest, alpine temperate coniferous, and broad-leaved mixed forest [Wang et al., 2010]. This unique broadleaf evergreen species Quercus aquifolioides found at the highest altitude in the world is one of the dominant tree species in the study area. 2.2. Sampling and Measurement During the sampling period from January 2007 to November 2008, each leaf sample was collected semimonthly from Quercus aquifolioides. Each sampling procedure was done at midday [Helliker and Ehleringer, 2002]. The leaves, which were approximately 1 year old at the time of sampling, were collected from three replicate trees of the same species [Kahmen et al., 2008]. Five to six leaves were collected from each tree. Leaf samples were removed from the plant and immediately inserted into a glass tube, which was then sealed with caps and wrapped with parafilm. The leaf samples were then frozen (15°C) until water was extracted. Soil samples were collected at a depth of 40 cm below the soil surface using a soil drill for each treatment [Yakir et al., 1990] at the same time (midday) and then they were processed using the same procedure as for the leaf samples. Water was extracted from the leaf and soil samples using a cryogenic vacuum distillation apparatus and collected in traps cooled continuously with liquid N2 [Farris and Strain, 1978]. The distillation temperature was 95°C, and the process took up to 4 h [Pendall et al., 2005]. Extracted water was stored in cryogenic vials. Rainfall from each precipitation event was collected immediately and sealed in clean and dry plastic bottles. Snow and other solid precipitation were collected on clean porcelain plates, put into clean plastic bags, and sealed. After the samples had melted at room temperature, they were processed by the same procedure as for the rainfall samples. All the water samples including the extracted leaf water and soil water were sealed with parafilm and
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stored at 15°C until analyzed. Unfortunately, the xylem water samples were not available for this project. The STSAEOR, CAS measured the daily temperature, relative humidity, and precipitation amount. Measurements of the isotopic compositions of all samples were performed in the Key Laboratory of Tibetan Environment Changes and Land Surface Processes, Institute of Tibetan Plateau Research (Chinese Academy of Sciences), using a high-temperature conversion elemental analyzer coupled with a Delta V Advantage isotope ratio mass spectrometer with a precision of 0.2‰ for oxygen and 1‰ for hydrogen. The measured isotope ratios (δ18O and δD) were expressed as parts per mil (‰) of their deviations relative to the Vienna standard mean ocean water. 2.3. Statistical Analysis All statistical analyses were performed on IBM SPSS Statistics version 19.0 (IBM Corp. Armonk, NY, USA). Least squares linear regression was used to determine if there was a linear correlation between (precipitation/soil/ leaf) isotopic composition and measured variables (air temperature and relative humidity) and the Indian monsoon index (IMI). Relationships between variables were assessed using standard bivariate procedures. Parameter p < 0.01 was considered very significant for all analyses; p < 0.05 was considered significant; p < 0.1 (but >0.05) was considered marginally significant; and p > 0.1 was considered not significant. 2.4. Calculation of Indian Monsoon Index and Wind/Water Vapor Flux Field In this study, we calculated the Indian monsoon index (IMI) to analyze the relationship between the index and the δD value variations of different samples using the method from Wang et al. [2001], which defined a dynamic index for the Indian monsoon by using the difference of the 850 hPa zonal winds between a southern region of 5°N–15°N, 40°E–80°E and a northern region of 20°N–30°N, 70°E–90°E. In addition, based on a monthly averaged reanalysis of data sets from the National Centers for Environmental Prediction (NCEP), we calculated the wind field at 500 hPa and the water vapor flux field at 300–500 hPa over Lulang and adjacent regions. A subset of the results of January, May, July, and October 2007 concisely represented winter, the premonsoon period, the active monsoon period, and the postmonsoon period conditions, respectively. 2.5. Modified Craig–Gordon Model and Deuterium Excess Value The isotopic composition of leaf water (δDl) can be described by the modified Craig–Gordon model [Farquhar et al., 1989], given by δDl ¼ δDsw þ εk þ ε þ ðδDv δDsw εk Þea =ei
(1)
where δDsw and δDv represent the δD in the source water taken up by roots (~δDs) and atmospherical water vapor, respectively. Parameter ε* is the equilibrium fractionation factor (ε* = 52.612 × 103 76.248/(T + 273.16) + 24.844/(T + 273.16)2 × 103) [Majoube, 1971], and εk is the kinetic fractionation factor, 25.1‰ for diffusion through stomata [Merlivat, 1978]. Assuming that atmospheric water vapor is isotopically equilibrated with precipitation, δDv can be equal to δDp ε*. Parameter ea/ei is the ratio of ambient vapor pressure to intercellular vapor pressure, which can be assumed to be equal to the relative humidity of the ambient air [Dongmann et al., 1974]. Then the modified Craig–Gordon model can be simplified further as δDl = δDp × RH + (δDs + ε* + εk) (1 RH). The deuterium excess value (d = δD 8 × δ18O) [Dansgaard, 1964] in precipitation at a given locality reflects the rate of evaporation in the source area, which depends on relative humidity (RH) in the source region [Dansgaard, 1964; Rozanski et al., 1993]. Low d values of precipitation are expected during times of high RH over the primary source region.
3. Results and Discussion 3.1. Seasonal Changes in δ18O and δD of Leaf Water In general, the changes in the δ18O and δD values of leaf water and soil water were similar, and the trends of those water samples were consistent with those of precipitation (Figures 2a and 2b). A significant positive correlation between the δ18O (and δD) values of leaf/soil water and of precipitation exists (Figures 3a and 3b). Before the rainy season (January–April), the δ18O and δD values of different water samples increased gradually; in the rainy season (May–September), they decreased rapidly, and after the rainy season (October–December), the δ18O and δD values increased gradually again. With the exception of the halophytic plants [Lin and Sternberg, 1993], there is no fractionation against δ18O (or δD) by the roots during water uptake, until the water reaches the leaves undergoing water loss YU ET AL.
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18
Figure 2. Semimonthly variations of (a) δ O and (b) δD in (c) precipitation (P), soil water (S), leaf water (L), and d of precipitation and (d) the daily changes in air temperature, (e) relative humidity, (f) IMI (the green curve represents the semimonthly mean IMI, and the blue curve shows the climate mean), and (g) precipitation amount at Lulang during the observation period in 2007–2008. Note that the dashed line inFigure 2c shows the global means of d excess (~10‰).
[Ehleringer and Dawson, 1992]. Leaf water becomes enriched in heavy isotopes during transpiration [Farquhar and Gan, 2003] due to equilibrium and kinetic effects [Flanagan et al., 1991]. As a result, compared to precipitation, the δ18O and δD values of plant’s leaf water were higher in this study (Figure 2a), and the leaf water fell off the global/local meteoric water line (GMWL/LMWL) (Figure 3c).
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Although vegetation cover somewhat reduced evaporative enrichment by diminishing evaporation [Dubbert et al., 2013], soil water at 40 cm soil depth in this study still experienced apparent isotopic enrichment, and soil water samples fell off the GMWL/LMWL (Figure 3c). Previous studies examining water use by different plant species near Nam Tso on the central Tibetan Plateau also found that the δD values of upper soils were more enriched than those of the soils at lower depths [Hu et al., 2013]. In addition, in this study area, the rooting depth of Quercus aquifolioides is 0–50 cm [Zhu et al., 2010], and the groundwater table depth is 1.5–4 m. Hence, stable isotope variations in the upper part of the soil profile largely influence those of our plants. However, soil water was less enriched in δ18O and δD relative to leaf water in this study (Figures 2a and 2b and Figure 3c). Moreover, both the δ18O (δD) records of soil water and precipitation followed the same trend, similar to the results of the study at Nagqu in the middle part of the Tibetan Plateau [Tian et al., 2002]. Accordingly, the δ18O and δD variations of soil water directly reflected that of precipitation. Dubbert et al. [2013] also found that stable isotope variation of the soil in central Portugal was constant between 10 and 40 cm, which reflected rainwater isotopic composition, although it differed significantly across the soil depths between 0 and 10 cm. Interestingly, the δD values of leaf/soil water underwent less enrichment than the δ18O values, and were closer to those of precipitation (Figures 2a and 2b), despite the δD values in precipitation, 18 18 18 18 soil water, and leaf water correlated Figure 3. Correlations of (a) δ Ol–δ Op and δ Os–δ Op, (b) δDl–δDp and 18 remarkably well to the δ18O values at δDs–δDp, and (c) δ O–δD of various water samples at Lulang in 2007–2008. Note that the legends of Figure 3b are similar to Figure 3a but for δD. Lulang, with a positive correlation coefficient of 0.9 (n = 38, p < 0.01), 0.75 (n = 33, p < 0.01), and 0.87 (n = 44, p < 0.01), respectively (Figure 3c). The discrepancy was mainly caused by the different kinetic fractionation effects in the evapotranspiration process, which are larger for H218O relative to H216O than for DH16O relative to H216O [Dansgaard, 1964]. In that case, the δD values of the leaf water could “inherit” the δD value characteristics of precipitation far better than the δ18O values. These facts implied that precipitation is the main source of the leaf water, although fractionation processes could cause the leaf water isotope values
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Figure 4. The observed (down triangles) and simulated (open circles) δD of leaf water and the leaf water enrichment (crosses) at Lulang in 2007–2008.
to deviate from the precipitation input values and to fall off the GMWL/LMWL (Note: precipitation samples fall on the GMWL trend indicating that they are unaffected by significant evaporation.) (Figure 3c). Many environmental variables such as relative humidity and air temperature [Dongmann et al., 1974; Lai et al., 2008] might interact to influence the isotopic compositions of the water samples, especially for the plant’s leaf water. Although the δD values decreased (or increased) in (or after) the rainy season, with an inverse trend in the corresponding air temperatures (Figures 2b and 2d), the trends of leaf water δD and air temperatures (T) were similar before the rainy season (especially in February–April), with an increasing trend (Figures 2b and 2d). This indicates that in this study, the δD values of leaf water sometimes were partly dependent on the changes of air temperature. Relative humidity (RH) strongly influences the heavy isotope enrichment of leaf water [Dongmann et al., 1974]. It is easy to see an inverse tendency between the δD values of different water samples and relative humidity (Figures 2b and 2e). In particular, the negative δD-RH correlation of precipitation and leaf water is more significant than the δD-temperature relationship, with a correlation coefficient of 0.41 (n = 38, p < 0.05) and of 0.49 (n = 44, p < 0.01), respectively. At high humidity, both transpiration rates and leaf water isotopic enrichment decrease. Hence, the δD values of leaf water could be strongly modified by evaporative enrichment, thus effectively deviating from the δD values of its source water under dry conditions [Lai et al., 2008]. Based on the modified Craig–Gordon model [Farquhar et al., 1989], we calculated the δDl values and found that the tendencies of the simulated δDl values in the rainy season were coincident with those of the observed data (Figure 4). However, before (and after) the rainy season, the simulated δDl values apparently overestimated the observed data (Figure 4). We modeled steady state leaf water enrichment at the sites of evaporation (Δes) by Δes = ε* + εk + (Δv εk) RH, following Farquhar et al. [1989]. Our results also demonstrated that changes in the isotopic enrichment of leaf water outside the rainy season were intense, resulting from the impact of relative humidity, but were less variable and somewhat tracking the δD values of monsoon precipitation in the rainy season (Figure 4). 3.2. Relationship Between δD of Leaf Water and the Indian Monsoon The seasonal trends of the IMI and the δD variations from all leaf water samples are shown in Figure 2. The δD values of leaf water and precipitation over the entire sampling period were negatively correlated to the IMI. The regression equations were δDl = 0.09 IMI 5.37 (r = 0.55, n = 44, p < 0.01) and δDp = 0.05 IMI 3.99 (r = 0.41, n = 38, p < 0.05), respectively. In winter (for example, January, Figure S1a in the supporting information), the high water vapor flux appeared over the ocean, and the westerlies dominated at Lulang, and over the entire Tibetan Plateau, resulting in low water vapor flux and sparse precipitation, with high δD values in leaf water, soil water, and precipitation (Figure 2b). Before April, the IMI stayed below zero (Figure 2f), indicating that the monsoon had not yet occurred. At the onset of the Indian monsoon (May), the IMI began to change to
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positive values, the monsoon activities started transporting oceanic moisture from the Indian Ocean toward the southern Tibetan Plateau (Figure S1b in the supporting information), resulting in abruptly decreased δD values observed in leaf water (Figure 2b). However, the westerlies still dominated moisture input to the northern Tibetan Plateau, and water vapor flux remained low (Figure S1b in the supporting information). During the active monsoon period (as seen by the high IMI between July and September), the Indian monsoon prevailed at Lulang on the STP, where water vapor flux was very high (for example, in July, see Figure S1c in the supporting information), and intense precipitation events frequently occurred (Figure 2g). The δD values found in summer leaf water, soil water, and precipitation were coincidentally lower (Figure 2b). In this study, the low d values of precipitation suggested that air moisture was transported by the Indian monsoon from the humid regions during summer (Figure 2c), which can be seen by the connection between low d and high IMI values (Figure 2). After the Indian monsoon retreat (October), the IMI fell below zero, and the westerlies moved toward the southern Tibetan Plateau and dominated the moisture at Lulang again, resulting in low water vapor flux and low precipitation amounts (Figure S1d in the supporting information). Due to low precipitation amounts, intensive reevaporation occurred as raindrops fell under very dry conditions, contributing considerably to more enriched δD values in precipitation as a consequence of diffusive exchange between raindrops and the ambient vapor [Stewart, 1975]. Therefore, after the Indian monsoon retreat, the δD values in leaf water, soil water, and precipitation also increased gradually (Figure 2b). Clearly, the δD variations of leaf water at Lulang were sensitive to the Indian monsoon activities and were affected by Indian monsoon precipitation. During biosynthesis, the incorporation of leaf water isotope ratio values into organic compounds affects the δD values of plants [Hoefs, 2009], because isotopic fractionation can occur under reequilibrium exchange between the organic compounds and local medium water (e.g., leaf water) [Roden et al., 2000]. With regard to δD in the cellulose, it is a function of both δD of the substrate sucrose and of the medium water within the cell, which could be a leaf cell, a root cell, or a stem xylem cell as part of a tree ring [Roden et al., 2000]. As a result, the environmental impact on hydrogen isotope fractionation between source water and medium water and tree ring cellulose or other biomarkers is inevitable. Hence, the leaf water isotope study is essential to specify the evapotranspirative enrichment and the contribution to the δD of plant organic matter. Our findings suggest that RH and Indian monsoon precipitation strongly affect leaf water isotope values on the STP. We suggest that the impacts of the Indian monsoon need to be considered when stable isotopes in tree ring cellulose or other biomarkers are to be used for paleoclimate reconstruction on the Tibetan Plateau.
4. Conclusions
Acknowledgments We thank the Editors (M. Bayani Cardenas, Editor-in-Chief, and anonymous Associate Editor) for the constructive comments that considerably improved this paper. NCEP Reanalysis-derived data were provided by the NOAA/OAR/ESRL PSD, Boulder, Colorado, USA, from their website at http://www.esrl.noaa.gov/psd/. Some meteorological data were provided by the STSAEOR, CAS. This work was supported by CAS (grants XDA05080600 and XDB03030207) and NSFC (grants 41125003, 41371086, and 41025002). C.-T. Lai was supported by the U.S. National Science Foundation, Division of Atmospheric and Geospace Sciences under grant AGS-0956425. The Editor thanks two anonymous reviewers for their assistance in evaluating this paper.
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Our study found that the δD values in leaf water of Quercus aquifolioides at Lulang underwent less enrichment than the δ18O values of those plants’ leaf water. Accordingly, the δD values were closer to those measured in precipitation. Hence, the leaf water δD values could inherit the characteristics of the precipitation δD values far better than the leaf water δ18O values. Relative humidity significantly influenced the heavy isotope enrichment of leaf water, especially before (or after) the rainy season. Indian monsoon activities characterize the relatively low δD values in summer precipitation at Lulang, which was accurately reflected by the seasonal δD change observed in the leaf water. Therefore, monsoon precipitation plays an important role in determining the δD of leaf water in the rainy season. We suggest that the δD variation in leaf water at Lulang could serve as an indicator of the warm oceanic moisture transported by the Indian monsoon to this region.
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