DOI: 10.5061/dryad.fxpnvx0w1
title: Data from: Uncorrected soil water isotopes through cryogenic vacuum distillation may lead to a false estimation of plant water sources

description: Successful use of stable isotopes (δ2H and δ18O) in ecohydrological
 studies relies on the accurate extraction of unfractionated water from
 different types of soil samples. Cryogenic vacuum distillation (CVD) is a
 common laboratory-based technique used for soil water extraction; however,
 the reliability of this technique in reflecting soil water δ2H
 and δ18O is still of concern. This study examines the reliability
 of a newly developed automatic cryogenic vacuum distillation (ACVD) system
 through a set of pure water extraction. The impacts of extraction
 parameters (i.e., extraction time, temperature, and vacuum) and soil
 properties on the recovery of soil water δ2H and δ18O were further
 assessed for the ACVD and traditional extraction systems (TCVD) systems.
 Finally, the potential influences of the CVD technique on the prediction
 of plant water uptake were investigated through a sensitivity
 analysis. We demonstrated that the ACVD system was reliable for
 recovering the isotopic composition of pure water, with negligible biases
 of − 0.1 ± 0.3‰ for δ2H and 0.04 ± 0.09‰ for δ18O. Both ACVD and TCVD
 similarly extracted water from the rewetted soils when the extraction time
 of the ACVD system reached 240 min, but none of the CVD systems
 successfully recovered the isotopic signatures of doped water from soil
 materials. Mean δ2H offsets of extracted soil water were − 2.6 ± 1.3‰ and
 − 2.4 ± 1.7‰ for ACVD and TCVD, respectively; while mean δ18O offsets were
 − 0.16 ± 0.14‰ and − 0.39 ± 0.37‰. The isotopic offsets of CVD systems
 were positively correlated with soil clay content, and negatively
 correlated with soil water content. The use of corrected soil data (with
 CVD offsets) could improve the prediction of plant water uptake based on
 its high correlation with environmental factors. This study identifies the
 isotopic offsets of CVD systems (i.e., ACVD and TCVD) and provides
 possible solutions for better-predicting plant water sources. Even so, the
 wide use of CVD techniques probably induces noticeable uncertainties in
 predicting plant water uptake depths. The dataset of soil water extraction
 in this study will have implications for the technological development of
 CVD techniques.
description: The isotopic data are collected from both the laboratory and the
 field. This study assessed the CVD approaches for stable isotope analysis
 and plant water source prediction through the following consecutive
 experiments. Experiment (Ⅰ): 56 pure water samples of known isotopic
 values were extracted using the newly designed ACVD system. Experiment
 (Ⅱ): 225 soil samples containing various rates of clay particles were
 oven-dried, doped with deionized water, and cryogenically extracted using
 ACVD and TCVD systems. Experiment (Ⅲ): a sensitivity analysis of plant
 water uptake under four types of input data was performed among seven
 sites in China.
description: # Data from: Uncorrected soil water isotopes through cryogenic vacuum
 distillation may lead to a false estimation of plant water sources Note on
 the data for the above experiments | Sheet1) Figure 2 Hydrogen and oxygen
 isotope offsets between deionized (DI) water and the same water
 cryogenically extracted from rehydrated soils | |
 :--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Column 1, three soil textures for rehydration treatments: sandy loam soil from Loess Plateau, loam soil from Northeast Plain, and clay soil from Yunnan-Guizhou Plateau | | Column 2, ACVD\_3h (ACVD: automatic cryogenic vacuum distillation) | | Column 3, Bias Delta 2H | | Column 4, Bias Delta 18O (‰) | | Column 5, WRR (water recovery rate, %) | | Column 6, ACVD\_4h (ACVD: automatic cryogenic vacuum distillation with 240 min) | | Column 7, Bias Delta 2H (‰) | | Column 8, Bias Delta 18O (‰) | | Column 9, WRR  (water recovery rate, %) | | Column 10, ACVD\_4ht (ACVD: automatic cryogenic vacuum distillation with 240 min and 105 °C) | | Column 11, Bias Delta 2H (‰) | | Column 12, Bias Delta 18O (‰) | | Column 13, WRR (water recovery rate, %) | | Column 14, TCVD\_1 (TCVD: traditional mode of cryogenic vacuum distillation) | | Column 15, Bias Delta 2H (‰) | | Column 16, Bias Delta 18O (‰) | | Column 17, WRR (water recovery rate, %) | | Column 18, TCVD\_2 (TCVD: traditional mode of cryogenic vacuum distillation) | | Column 19, Bias Delta 2H (‰) | | Column 20, Bias Delta 18O (‰) | | Column 21, WRR (water recovery rate, %) | | **Sheet 2) Figure 3 Soil water δ2H offsets as a function of soil water δ18O offsets (a) for two types of cryogenic vacuum distillation systems** | | Column 1, three soil textures for rehydration treatments: sandy loam soil from Loess Plateau, loam soil from Northeast Plain, and clay soil from Yunnan-Guizhou Plateau | | Column 2, ACVD\_4h (ACVD: automatic cryogenic vacuum distillation with 240 min) | | Column 3, Bias Delta 2H (‰) | | Column 4, Bias Delta 18O (‰) | | Column 5, SWC (soil water content, %) | | Column 6, TCVD\_1 (TCVD: traditional mode of cryogenic vacuum distillation) | | Column 7, Bias Delta 2H (‰) | | Column 8, Bias Delta 18O (‰) | | Column 9, SWC (soil water content, %) | | Column 10, TCVD\_2 (TCVD: traditional mode of cryogenic vacuum distillation) | | Column 11, Bias Delta 2H (‰) | | Column 12, Bias Delta 18O (‰) | | Column 13, SWC (soil water content, %) | | **Sheet 3) Figure 4 Dual-isotope (δ2H and δ18O) plots of xylem water at seven experimental sites and their potential sources of soil water corrected based on isotopic offsets of cryogenic vacuum distillation (CVD) techniques** | | Column 1, sites in Luancheng (LC) County, Duolun (DL) County, Taihe (TH) County, Zhangye (ZY) City, Ansai area, Xishuangbanna (BN) Autonomous Prefecture, and Jingdong (JD) County | | Column 2, soil clay contents (%) | | Column 3, soil water content (%) of topsoil | | Column 4, soil water content (%) of deep soil | | Column 5, sampling series | | Column 6, xylem Delta 2H (‰) | | Column 7, xylem Delta 18O (‰) | | Column 8, topsoil Delta 2H (‰) | | Column 9, topsoil Delta 18O (‰) | | Column 10, deep soil Delta 2H (‰) | | Column 11, deep soil Delta 18O (‰) | | Column 12, topsoil Delta 2H offsets (‰)  | | Column 13, topsoil Delta 18O offsets (‰) | | Column 14, deep soil Delta 2H offsets (‰) | | Column 15, deep soil Delta 18O offsets (‰) | | **Sheet 4) Figure 5 Variations of xylem water SW-excess at seven experimental sites** | | Column 1, sites in Luancheng (LC) County, Duolun (DL) County, Taihe (TH) County, Zhangye (ZY) City, Ansai area, Xishuangbanna (BN) Autonomous Prefecture, and Jingdong (JD) County | | Column 2, sampling series | | Column 3, SW-excess-raw (‰) | | Column 4, SW-excess-corrected (‰) | | **Sheet 5) Table 2 Parameter estimates of fixed effects and R squares of the generalized linear mixed models on source water contributions for each type of input data** | | Column 1, sites in Luancheng (LC) County, Duolun (DL) County, Taihe (TH) County, Zhangye (ZY) City, Ansai area, Xishuangbanna (BN) Autonomous Prefecture, and Jingdong (JD) County | | Column 2, sampling series | | Column 3, topsoil contribution (%) based on input data 1 | | Column 4, deep soil contribution (%) based on input data 1 | | Column 5, topsoil contribution (%) based on input data 2 | | Column 6, deep soil contribution (%) based on input data 2 | | Column 7, topsoil contribution (%) based on input data 3 | | Column 8, deep soil contribution (%) based on input data 3 | | Column 9, topsoil contribution (%) based on input data 4 | | Column 10, deep soil contribution (%) based on input data 4 | | Column 11, topsoil SWC (SWC: soil water content, %) | | Column 12, deep soil SWC (SWC: soil water content, %) | | Column 13, VPD (VPD: vapor pressure deficit, kPa) |