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\begin{document}

\title{Interrelation of soil water and plant water revealed by hydrogen-oxygen
isotopes across alpine shrub and grassland in northern Qinghai-Tibet
Plateau}



\author[1]{Jing Li}%
\author[1]{Fawei Zhang}%
\author[1]{Yunying Wang}%
\author[1]{Yangong Du}%
\author[1]{Huakun Zhou}%
\author[2]{Bin Wang}%
\author[1]{Guangmin Cao}%
\author[1]{Xiaowei Guo}%
\affil[1]{Northwest Institute of Plateau Biology Chinese Academy of Sciences}%
\affil[2]{Wagga Wagga Agricultural Institute}%


\vspace{-1em}



  
  \date{May 20, 2024}


\begingroup
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\selectlanguage{english}
\begin{abstract}
The alpine grassland shrubbization of the northern Qinghai-Tibet Plateau
on the background of global change and overgrazing, is a prominent and
serious problem. However, the water competition ability of shrubs and
alpine grasslands is rarely reported. Here, we tracked the \selectlanguage{greek}δ
\selectlanguage{english}\textsuperscript{18}O and \selectlanguage{greek}δ \selectlanguage{english}\textsuperscript{2}H of soil water, plant
water, precipitation, and groundwater, analysed sources of water use in
shrub and grassland by Mix SIAR model. Our results showed that both \selectlanguage{greek}δ
\selectlanguage{english}\textsuperscript{18}O and \selectlanguage{greek}δ \selectlanguage{english}\textsuperscript{2}H in soil, precipitation,
and plant varied significantly over time, groundwater remained
relatively stable in \emph{P. fruticosa} shrub and alpine grassland
sites during observation. Considering groundwater, precipitation, soil
water, and plant water, a progressive enrichment in \selectlanguage{greek}δ
\selectlanguage{english}\textsuperscript{18}O or \selectlanguage{greek}δ \selectlanguage{english}\textsuperscript{2}H existed from groundwater
and precipitation to soil water to plant water for each month. Alpine
grassland was more susceptible to drought stress, had a stronger
partitioning effect in dynamic transport than shrub. The \emph{P.
fruticosa} shrub displayed more flexible water utilisations, and was
more competitive for water than grasslands. Furthermore, the plants in
alpine shrub and grassland reached water use balance in August. Shrubs
degraded from alpine grassland changed water use pattern of grassland,
thereby changing soil water storage. These results contribute to
in-depth understanding the alpine grassland shrubbization from water use
patterns of grassland and shrub plants on the northern Qinghai-Tibet
Plateau.%
\end{abstract}%



\sloppy


Interrelation of soil water and plant water revealed by hydrogen-oxygen
isotopes across alpine shrub and grassland in northern Qinghai-Tibet
Plateau

Jing Li \textsuperscript{1,2}, Fawei Zhang \textsuperscript{1,3},
Yunying Wang \textsuperscript{1,2}, Yangong Du \textsuperscript{1,3},
Huakun Zhou\textsuperscript{1,3}, Bin Wang\textsuperscript{4}, Guangmin
Cao\textsuperscript{1,3*}, Xiaowei Guo\textsuperscript{1,3*}

1 Key Laboratory of Adaptation and Evolution of Plateau Biota, Northwest
Institute of Plateau Biology, Chinese Academy of Sciences, Xining, China

2 College of Resources and Environment, University of the Chinese
Academy of Sciences, Beijing, China

3 Qinghai Provincial Key Laboratory of Restoration Ecology for Cold
Regions, Xining, Qinghai, China

4 New South Wales Department of Primary Industries, Wagga Wagga
Agricultural Institute, Wagga Wagga 2650, Australia

\textbf{*} Correspondence: Xiaowei Guo and Guangmin Cao, Key Laboratory
of Adaptation and Evolution of Plateau Biota, Northwest Institute of
Plateau Biology, Chinese Academy of Sciences, Xining,810008, China;
Email: \emph{guoxw@nwipb.cas.cn}; Tel \& fax: +86 09716123010

\textbf{Abstract:}

The alpine grassland shrubbization of the northern Qinghai-Tibet Plateau
on the background of global change and overgrazing, is a prominent and
serious problem. However, the water competition ability of shrubs and
alpine grasslands is rarely reported. Here, we tracked the
\selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{18}O and \selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{2}H of soil water, plant
water, precipitation, and groundwater, analysed sources of water use in
shrub and grassland by Mix SIAR model. Our results showed that both
\selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{18}O and \selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{2}H in soil, precipitation,
and plant varied significantly over time, groundwater remained
relatively stable in\emph{P. fruticosa} shrub and alpine grassland sites
during observation. Considering groundwater, precipitation, soil water,
and plant water, a progressive enrichment in \selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{18}O or
\selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{2}H existed from groundwater and precipitation to soil
water to plant water for each month. Alpine grassland was more
susceptible to drought stress, had a stronger partitioning effect in
dynamic transport than shrub. The \emph{P. fruticosa} shrub displayed
more flexible water utilisations, and was more competitive for water
than grasslands. Furthermore, the plants in alpine shrub and grassland
reached water use balance in August. Shrubs degraded from alpine
grassland changed water use pattern of grassland, thereby changing soil
water storage. These results contribute to in-depth understanding the
alpine grassland shrubbization from water use patterns of grassland and
shrub plants on the northern Qinghai-Tibet Plateau.

\textbf{Keyword:} Stable isotopes, Alpine meadow water, \emph{P.
fruticosa} shrub water, Soil water, Mix SIAR model, Northern
Qinghai-Tibet Plateau

\textbf{Introduction}

Water is one of the most crucial limiting factors determining the
community dynamic trends and productivity of plant in arid and semiarid
ecosystems (Li et al., 2013). The primary water sources, such as soil
water and groundwater, absorbed by plants determine the growth status of
plants, the distribution and growth status of plants affect the
ecological structure and functions of the soil-plant system
(White\&Smith, 2013; Wu et al., 2019). Additionally, the interaction of
soil and plant water is a vital component of eco-hydrological processes
(Dawson\&Ehleringer, 1991; Chang et al., 2019).

Previous studies about interrelation of soil and plant mostly focused on
exploiting different hydrological niches (Walker et al., 1981), soil
moisture--vegetation feedbacks and their possible effects (D'Odorico et
al., 2007), and functional differences (Ryel et al., 2008) by modeling.
Precipitation patterns (D'Odorico, et al., 2007), soil water utilization
(Gow et al., 2018; Lanning et al., 2020) and roots distribution (Wang et
al., 2021a) affect the plant water use patterns. They were all based on
traditional situ observations. Subsequently, some scholars found that
isotopic variation of both plant water and soil water provide an
effective and powerful way to reveal and partition the different
potential water sources used by plants (Vargas et al., 2017; Che et al.,
2019; Rothfuss\&Javaux, 2017).

The Qinghai-Tibet Plateau (QTP) is known as ''Chinese Water Tower'' and
is an essential component of ''three screens and two belts'' ecological
security strategic pattern (Li et al., 2022), that both show the
important role of QTP in the construction of ecological civilization.
However, QTP is particularly vulnerable under overgrazing and climate
change (He et al., 2020). Data observed from 2001 to 2018 indicated that
both soil water storage declined over that period. Shrub
(\emph{Potentilla fruticosa} ) meadows and alpine grasslands are the
dominant vegetation types in the QTP. They have important water
conservation functions (Dai et al., 2021), and play an important role in
maintaining the water-heat balance and ecological barrier function of
the QTP (Dai et al., 2019). However, on the background of global change
and overgrazing, the problems of grassland shrubs and the decline of
water conservation functions caused by grassland degradation, are
threatening the national strategic position of water resources in the
Qinghai-Tibet Plateau (Guo et al., 2020). Grassland degradation changes
carbon accumulation rate (Sun et al., 2020), soil nutrients (Wu et al.,
2020), evapotranspiration (Ji et al., 2022), and plant water use
efficiency (Wang et al., 2021b), but the interrelation of water
competition from shrubs and alpine grasslands are not well understood,
and little research on water-use patterns and relationships between
\emph{P. fruticosa} shrubs and alpine grasslands has been conducted on
the northern QTP.

To fill the gaps, we compared \selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{18}O and
\selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{2}H from different water sources in a pair of
neighboring sites, combined with field observations, and distinguished
water use sources of \emph{P. fruticosa} shrubs and alpine grassland
plants on different seasons through Mix SIAR model to in-depth
understand the interaction of soil water and plant water for \emph{P.
fruticosa} shrubs and alpine grasslands. Our results provided a
theoretical basis for the alpine grassland shrubbization, and made
contribution to restoration of the alpine grassland in the northern QTP
under global climate change.

\textbf{2. Materials and methods}

\textbf{2.1. Site description}

This study was conducted in Ganchaitan, close to Haibei station
(101\selectlanguage{ngerman}°19\selectlanguage{english}'E, 37deg37\selectlanguage{english}'N, 3335 m), and included two neighboring sites (i.e.,
shrubs site and grassland site, the distance between them was 460 m) in
the northeastern Qinghai-Tibet Plateau, located in Qinghai Province,
China, (Figure 1). The region is in a semiarid, cold, high-altitude
climate zone (Dai et al., 2019b). The mean annual precipitation is
approximately 562 mm. Almost 80\% of the annual precipitation falls
during the growing season (i.e., from May to September). The mean annual
air temperature is approximately -1.7\selectlanguage{english}, with the maximum temperature
occurring in July (9.8 \selectlanguage{english}) and the minimum temperature occurring in
January (-14.80\selectlanguage{english}) (Dai, et al., 2021). The soil type in the study area
was classified as Mollic Gryic Cambisols based on the classification of
soil systems in China (Liu et al., 2018). Vegetation characteristics of
the sampling sites were investigated and shown in Table 1.

Table1 Vegetation characteristics of the sampling sites.\selectlanguage{english}
\begin{longtable}[]{@{}lll@{}}
\toprule
\begin{minipage}[b]{0.30\columnwidth}\raggedright\strut
Community characteristics\strut
\end{minipage} & \begin{minipage}[b]{0.30\columnwidth}\raggedright\strut
Experimental sites\strut
\end{minipage} & \begin{minipage}[b]{0.30\columnwidth}\raggedright\strut
Experimental sites\strut
\end{minipage}\tabularnewline
\midrule
\endhead
\begin{minipage}[t]{0.30\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.30\columnwidth}\raggedright\strut
Shrub\strut
\end{minipage} & \begin{minipage}[t]{0.30\columnwidth}\raggedright\strut
Grassland\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.30\columnwidth}\raggedright\strut
Density (plants/5 m \selectlanguage{ngerman}× 5 m)\strut
\end{minipage} & \begin{minipage}[t]{0.30\columnwidth}\raggedright\strut
5.23\selectlanguage{ngerman}±1.22\strut
\end{minipage} & \begin{minipage}[t]{0.30\columnwidth}\raggedright\strut
29.11\selectlanguage{ngerman}±1.89\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.30\columnwidth}\raggedright\strut
Height (cm)\strut
\end{minipage} & \begin{minipage}[t]{0.30\columnwidth}\raggedright\strut
97.02\selectlanguage{ngerman}±4.62\strut
\end{minipage} & \begin{minipage}[t]{0.30\columnwidth}\raggedright\strut
30.41\selectlanguage{ngerman}±3.26\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.30\columnwidth}\raggedright\strut
Coverage (\%)\strut
\end{minipage} & \begin{minipage}[t]{0.30\columnwidth}\raggedright\strut
10.89\selectlanguage{ngerman}±0.98\strut
\end{minipage} & \begin{minipage}[t]{0.30\columnwidth}\raggedright\strut
82.21\selectlanguage{ngerman}±1.23\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.30\columnwidth}\raggedright\strut
Root biomass (g/m\textsuperscript{3})\strut
\end{minipage} & \begin{minipage}[t]{0.30\columnwidth}\raggedright\strut
2447\selectlanguage{ngerman}±349\strut
\end{minipage} & \begin{minipage}[t]{0.30\columnwidth}\raggedright\strut
1656\selectlanguage{ngerman}±640\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.32\columnwidth}\raggedright\strut
Dominant species composition and plant community description\strut
\end{minipage} & \begin{minipage}[t]{0.32\columnwidth}\raggedright\strut
\emph{Potentilla fruticosa L.} \emph{Kobresia humilis,Double-stigma
Bulrush,} \emph{Polygonum viviparum L.,} and \emph{Elymus nutans
Griseb.}\strut
\end{minipage} & \begin{minipage}[t]{0.32\columnwidth}\raggedright\strut
\emph{Elymus nutans Griseb., Polygonum viviparum L., Double-stigma
Bulrush, Poa prsten, Kobresia humilis}\strut
\end{minipage}\tabularnewline
\bottomrule
\end{longtable}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image1/image1}

\end{center}
\end{figure}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image2/image2}

\end{center}
\end{figure}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image3/image3}

\end{center}
\end{figure}

\textbf{Figure 1. Location of sample sites (a), shrub site (b) and
grassland site (c).}

\textbf{2.2. Sample collections and isotope analysis}

2.2.1 Sample collection

We collected the samples, including the plant, soil, precipitation and
groundwater. All the samples were frozen at -10\selectlanguage{ngerman}°C prior to vacuum
distillation, for consistent handling while avoiding the effects of
fractionation. In addition, our preliminary experimental results showed
that the isotope ratio spectrometer had more stable operating state
after extraction of precipitation and groundwater.

The plant and soil samples were collected from the shrub and grassland
sites during the re-green season, growing season, and withering season
in 2021 (20 May, 15 June, 16 July, 16 August, 7 September, and 12
October). Plant species were randomly chosen on the sampling date in the
two sites. The whole plants of herbs were used for experiments after
removing leaves. Whereas, the stem sections were removing the outer bark
from \emph{P. fruticosa} were used for isotope analysis (Martín-Gómez et
al., 2017). The soil samples were collected around the selected plants
within 2 m by soil cores, the soil cores were divided into 10 layers
(0--5 cm, 5--10 cm, 10--15 cm, 15--20 cm, 20--30 cm, 30--40 cm, 40--50
cm, 50--60 cm, 60--80 cm, and 80--100 cm), each soil samples were
analyzed as separate samples. Three replicates for each of the soil
layers and plants samples were collected in the two experimental sites.
A total number of 72 and 360 samples of plants and soils, respectively,
were sealed for isotopic analysis.

Precipitation and groundwater were sampled concurrently from May to
October in 2021. The event-based precipitations were sampled using
bottles at herder's home, 2 km away from our sampling sites during the
sampling period, the number of replicates (one, two or three) from every
event-based precipitation were determined according to the amount of
precipitation. Groundwater were sampled once a week from a well 2 km
away from our sites, three replicates were collected. The well had a
depth of 2 m, and was commonly used for groundwater monitoring. A total
of 162 and 72 samples from precipitation and groundwater, respectively,
were all transferred into clean polyethylene bottles.

The soil water content (SWC) was determined by an automatic soil
moisture monitoring system (CR800; Campbell, USA) with sensors installed
at depths of 5 cm, 10 cm, 15 cm, 20 cm, 30 cm, 40 cm, 50 cm, 60 cm, 80
cm, and 100 cm below the soil surface. Precipitation measurements were
collected using a precipitation gauge (52,203, RM Young, USA) at a
height of 0.5 m. Temperatures were obtained from a meteorological
station (Molis 520; Vaisala, Finland). All data were recorded every 30
min.

2.2.2. Isotopic analysis

Precipitation, groundwater, plant water, and soil water samples were all
extracted by the cryogenic vacuum distillation technique (LI-2100pro,
Lica United Technology Limited, Beijing, China) in order to avoid the
influence of high salinity moisture on the accuracy of the instrument.
After all samples were equilibrated to room temperature, extraction was
started, setting 3 h for plant water and soil water, 2 h for
precipitation and groundwater samples according to West et al. (2006).
All of the extracted water was transferred into 2 ml vials, then
analyzed stable isotopes (\selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{2}H and
\selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{18}O) using an isotope ratio spectrometer
(LGR-TLWIA-912, Los Gatos Research, San Jose, CA, USA). The instrument
was equipped with an autosampler (PAL-LSI) for sample injection, and
post-processing software (LWIA Post Analysis Full Installer v4.4.1) for
test diagnosis, checking, and quantifying problems in the analysis
(e.g., interference from organic pollutants, injection volume error)
through detailed analysis of high-resolution absorption spectra. The
measurement precision was 0.3%0 for \selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{2}H and 0.1%0 for
\selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{18}O. The organic contamination on plant water need
correction procedures to eliminate the influence (Schultz et al., 2011).
The isotopic compositions of \selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{18}O and
\selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{2}H were expressed as an isotope ratio:

\begin{equation}
\delta sam(\%0)=\left(\frac{R\text{sam}}{R\text{std}}-1\right)\times 1000\%0\nonumber \\
 \end{equation}

where \selectlanguage{greek}δ\selectlanguage{english}sam was the isotopic difference, Rsam was the
abundance ratios (\textsuperscript{18}O/\textsuperscript{16}O
and\textsuperscript{2}H/\textsuperscript{1}H) of samples, Rstd was the
abundance ratios of standard.

2.2.3. Statistical analysis

All statistical analyses were conducted using R (software version 4.0.3,
https://www.r-project.org/), and all figures were plotted using Origin
9.1(https://www.originlab.com/). One-way analysis of variance (ANOVA)
followed by the post hoc Turkey's test at p = 0.05 was used to assess
hydrometeorological parameters of sampling date and sites. Two-way ANOVA
was performed to examine the significant effects of hydrometeorological
parameters and their interactions. Pearson's correlations were tested at
the p = 0.05 level.

The Bayesian mixing model Mix SIAR (http://conserver.iugo-cafe.org/user/
brice.semmens/Mix SIAR) was used for identifying the proportions of
contributions from each water source according to the
\selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{2}H and \selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{18}O, which were considered
as the mixture data of the potential water sources (Dawson\&Ehleringer,
1993; Beyer et al., 2018). The inputs of original data (for example, the
0-20 cm soil layer data was input as 0-10 cm and 10-20 cm isotope data),
the discrimination data (the TDF data in the model), the running time of
Markov Chain Monte Carlo (MCMC), and the diagnosis method of the model
results were according to (Zhou et al., 2021). The average value was
output from the model. Three potential soil water sources were
identified to facilitate subsequent analysis (i.e., shallow soil water
(0--20 cm), middle soil water (20--60 cm), and deep soil water (60-100
cm)), according to the variability in the soil water content and the
impacts of precipitation pulse.

\textbf{3. Results}

\textbf{3.1. Temperature, precipitation and its isotopes}

A unimodal distribution was exhibited by temperature and precipitation
amount in 2021, respectively (Figure 2a). Temperature peaked at the end
of July (16.61) and decreased monotonically to the end of October
(-6.62) during the observation. Precipitation activities were
concentrated in the same time, accounting for 86.10\% (465 mm) to the
annual precipitation (540 mm). The \selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{18}O and
\selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{2}H of precipitation showed large variations, the
degree of enrichment and evaporative fractionation in May and October
was more than in June to September, seasonal conditions are important
factors that affect the isotope characteristics of precipitation,
however, precipitation amount had little influence to
\selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{18}O and \selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{2}H in precipitation
(Figure 2b), temperature explained 49\% to \selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{18}O,
whereas, 42\% to \selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{2}H (Figure 2c).\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image4/image4}

\end{center}
\end{figure}

Note: the \selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{18}O and \selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{2}H in
precipitation, precipitation amount and temperature in the figure were
all daily means.

\selectlanguage{greek}\textbf{Figure 2. The δ\textsuperscript{18}O and δ\textsuperscript{2}H
in precipitation, precipitation amount and temperature in 2021 (a), the
δ\textsuperscript{18}O and δ\textsuperscript{2}H of different
precipitation amount (b) and different temperature (c) during the
sampling period}\selectlanguage{english}

\textbf{3.2. Isotopic compositions in precipitation, plant water, soil
water, and groundwater}

The \selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{18}O and \selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{2}H values in the two
sites varied greatly between water sources and months (Figure 3).
Generally, the average values of \selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{2}H were -53.86%0,
-52.25%0, -45.95%0, and -38.48%0 for groundwater, precipitation, soil
water, and plant water, respectively. The respective average values of
\selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{18}O were -8.83%0, -8.65%0, -6.93%0, and -2.96%0.
Considering groundwater, precipitation, soil water, and plant water, a
progressive enrichment in \selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{18}O or
\selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{2}H existed from groundwater and precipitation to soil
water to plant water for each month. The \selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{18}O and
\selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{2}H in precipitation water enriched initially and then
depleted significantly from May to October (p \textless{} 0.05).
Moreover, the trends of \selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{18}O and \selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{2}H
in plant water responded well to the trends of precipitation from May to
July, but not well from August to October. Likewise, significant
differences were observed for \selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{18}O in plant water
between shrub and grassland sites (p \textless{} 0.05), but
non-significant differences were observed for \selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{2}H (p =
0.06\textgreater{}0.05). There were no significant differences in the
\selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{18}O and \selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{2}H of soil water and
across months for the two sites (p>0.05). Groundwater isotopes remained
relatively stable during the sampling period.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image5/image5}

\end{center}
\end{figure}

Precipitation Plant water Ground water Soil water

\selectlanguage{greek}\textbf{Figure 3. Variation of δ\textsuperscript{18}O and
δ\textsuperscript{2}H of precipitation, soil water, plant water, and
groundwater between shrub (a) and grassland (b) sites}\selectlanguage{english}

\textbf{3.3. Comparisons of SWC and isotopes in shrub and grassland
sites}

Soil water content, variations of \selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{2}H and
\selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{18}O of shrub and grassland sites were shown in Figure
4. There was a significant difference in SWC of the same soil layers
between shrub and grassland sites (p \textless{} 0.05), the SWC of shrub
site ranged from 15.13 \selectlanguage{ngerman}± 0.06\% to 49.87 ± 0.29\%, whereas ranged from
19.25 ± 0.02\% to 39.76 ± 0.24\% in grassland site during the sampling
period (Figure 4a and 4d). However, \selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{2}H in soil water
showed no significant difference between the two sites (p
\textgreater{}0.05) (Figure 4b and 4e), in contrast to
\selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{18}O (p \textless{} 0.05) (Figure 4c and 4f). Both
\selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{18}O and \selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{2}H in shallow soil water
(0--20 cm) were more highly variable than deeper soil layers. The
isotopic values in surface soil water were enriched in June and July,
depleted in August and September. The \selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{18}O and
\selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{2}H values in the grassland soil were enriched than in
the shrubs from May to September, but almost the same in October,
indicating that grassland is more sensitive to environmental changes,
plant water has a stronger partitioning effect in dynamic transport
comparing with shrub plant water.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image6/image6}

\end{center}
\end{figure}

\selectlanguage{greek}\textbf{Figure 4. Soil water content (a), variations of
δ\textsuperscript{2}H (b) and δ\textsuperscript{18}O (c) in shrub, soil
water content (d), variations of δ\textsuperscript{2}H (e) and
δ\textsuperscript{18}O (f) in grassland sites}\selectlanguage{english}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image7/image7}

\end{center}
\end{figure}

The \selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{18}O and \selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{2}H showed significant
correlations in plant water, precipitation, and soil water during the
study period (Figure 5). The local meteoric water line (LMWL) was
described by equation, \selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{2}H =7.89 \selectlanguage{ngerman}×
\selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{18}O +17.79 (R\textsuperscript{2} = 0.97; p
\textless{} 0.05) , its slope was smaller than the global meteoric water
line (GMWL), \selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{2}H = 8.17 \selectlanguage{ngerman}× \selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{18}O +
10.35; (Rozanski et al., 1993), indicating that evaporation is a main
reason of arid climate and kinetic fractionation in the research sites.
The linear relationships of \selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{18}O and
\selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{2}H in soil water were significantly indicated that
the different evaporation effect between shrub and grassland sites.
Additionally, their slopes and intercepts at the two sites were smaller
than those of the LMWL, for the ongoing evaporation influence soil water
(Yang\&Fu, 2017). Moreover, Soil water, plant water and LMWL laid at an
angle on the both sites, indicating that these water types contained
water that had been recycled through terrestrial evaporation and
precipitation.

\selectlanguage{greek}\textbf{Figure 5. Relationships of δ\textsuperscript{18}O and δ H of
different waters between shrub (a) and grassland(b)}\selectlanguage{english}

\textbf{3.4 Variation of plant water utilization}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image8/image8}

\end{center}
\end{figure}

Plants in different sites used different fractions of shallow, middle,
and deep soil waters during different growth periods (Figure 6). The
plant water utilization of shallow soil water ranged from 19\% to 52\%,
and the minimum value at the shrub site was on 16 July. In contrast, the
maximum value was observed at the grassland site on 15 June. The
proportional contributions of middle soil water and deep soil water
acquired by plant were 55\% and 50\%, respectively, at the shrub site.
At the onset of the growing season and fast-growing season from May to
July, plants at shrub and grassland sites extracted water from the
middle soil layer and the shallow soil layer, respectively. Water
utilization from shallow, middle, and deep soil water reached
equilibrium in August. The water contributions of the three layers
remained unchanged during the late growing season and withering season.
The plants at the shrub site had higher degree of flexible plasticity in
water use compared with the plants at the grassland site.

\textbf{Figure 6. Seasonal variations in water use proportions at shrub
site (a) and grassland site (b)}

\textbf{4. Discussion}

\textbf{4.1. Variations of the isotopic composition in different water}

The \selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{18}O and \selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{2}H in precipitation
initially enriched and then depleted significantly from May to October.
Some scholars have concluded that \selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{18}O and
\selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{2}H in precipitation are consequence of the effects of
temperature and precipitation amount. The consequence produce a dominant
factor for plant and soil waters, regarding the isotopic inheritance
from precipitation to plant water, and their studies conducted in Ordos
Plateau, where located in monsoon regions(Liu et al., 2021). There is a
clear difference between their conclusions and our results.
Precipitation amount had little influence to \selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{18}O and
\selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{2}H in precipitation, temperature explained 49\% to
\selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{18}O, whereas, 42\% to \selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{2}H. It may
be caused by air trajectory, which influence \selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{18}O and
\selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{2}H in precipitation (Wu et al., 2016) by influencing
moisture source. Our research sites located in south of Qilian
Mountains, which situated the intersection of the alpine regions, the
northwest regions, and the monsoon regions (Yang et al., 2019). They had
more frequency of transition times than Ordos Plateau, where influenced
by internal circulation and monsoon circulation (Gou et al., 2011),
influencing the moisture sources depleted atmospheric water vapor.

Plant water trends responded well to the trends of
\selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{18}O and \selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{2}H in precipitation from
May to July, but not well from August to October. Several studies have
previously documented the consistency of precipitation and plant water
(Phillips\&Ehleringer, 1995; Meinzer et al., 2006; Sprenger et al.,
2016; Plavcov\selectlanguage{ngerman}á et al., 2018). Our different results may be due to that
precipitation intensity exerts little effect on the soil water as almost
all rainfall returns to the atmosphere via evapotranspiration (Dai et
al., 2019a). Soil water is the primary source of plant water, soil
moisture meets the needs of plant growth from May to July. However,
during the rapid growth of plants (August and Septermber), fierce water
competition stimulates plants to use water in each soil layer in a
balanced manner. This is an adaptation mechanism established to promote
growth until October. Furthermore, soil water isotopic compositions
resulting from soil water evaporative differences influenced the plant
water uptake pattern of plants (Rothfuss\&Javaux, 2017).

The \selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{18}O, \selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{2}H and SWC displayed
larger variability in shallow soil depths, compared with deeper soil
depths from May to October for the both sites. Groundwater isotopes were
consistent in the deeper soil and remained relatively stable. This
result is consistent with previous studies of arid and semi-arid regions
(Fischer et al., 2017; Wang et al., 2019; Guo, et al., 2020). Both
\selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{18}O and \selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{2}H values were enriched in
June and July, depleted in August in the shallow soil layers. The
isotopically enriched soil water of shallow depths matched well with the
lower SWC, in contrast to the depleted to the higher, the results
probably attributable to less precipitation and intensive evaporation
(Gazis\&Feng, 2004) in July, and rainfall recharge with negative
isotopic values (Wang, et al., 2019) in August. The results indicate
that precipitation recharge, evaporation, and antecedent moisture all
influence soil water isotopic compositions (Brooks et al., 2015).

\textbf{4.2. Comparisons between \emph{P. fruticosa} shrub and alpine
grassland}

The \selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{18}O in soil water and plant water showed
significant differences between shrub and grassland sites (p \textless{}
0.05) in contrast to non-significant differences in
\selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{2}H, resulting in different slopes and intercepts for
the water line equations of soil water and plant water.
Isotope-fractionated differences were probably associated with local
microenvironment and heterogeneity differences of surroundings between
the grassland and shrub sites despite the same general conditions
(Ellsworth\&Williams, 2007).

The water line equations between \selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{18}O and
\selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{2}H were established. Soil and plant water samples
were well described by linear regressions, resulting of laying at an
angle to the LMWL, this is consistent with previous studies (Goldsmith
et al., 2012; Che, et al., 2019). Their slopes and intercepts from soil
water at the grassland site were slightly than those at the shrub site,
suggesting soil evaporation was slightly greater at the grassland site
than at the shrub site. This was probably because the shrub site had a
denser coverage shading the soil surface compared with the grassland
site, as daily evaporation rates were slightly lower than grassland
(Crawford et al., 2014; Schw\selectlanguage{ngerman}ärzel et al., 2020). Nevertheless, the
slopes and intercepts in plant water lines at the grassland site were
higher than the slope and intercept at the shrub site. The differences
resulted from substantial variabilities for plant water at shrub and
grassland sites, evaporative distinctions
of\textsuperscript{2}H/\textsuperscript{1}H
and\textsuperscript{18}O/\textsuperscript{17}O on the primary of leaf
water (Farquhar et al., 2007) , and the transpiration from an area of
grassland is greater than the transpiration from a similar area of
shrubs.

\textbf{4.3. Implications for grassland shrubbization of alpine meadow}

The plants at alpine \emph{P. fruticosa} shrub extracted water from the
middle soil layer to deep soil water preferentially from May to June,
and extracted water from shallow, middle and deep soil in a balanced
manner from July to October. The results were different from the results
carried out on north of Qilian Mountains, where has a drier climate.
Their results had shown that \emph{P. fruticosa} used the shallow soil
water except for August, when used the middle soil water (Zhang et al.,
2022). This difference may be due to the different ages of plant (Wang,
et al., 2021a), the different geographical locations (Li et al., 2022),
or the different symbiotic species (Wu, et al., 2019). Additionally, the
different sources of the soil water from the eco-hydrological processes
maybe another reason.

Both \selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{18}O and \selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{2}H at the grassland
site were enricher than at the shrub site during the growing season, but
almost the same during the withering season. Grassland was more
susceptible to drought stress, plants at grassland site had a stronger
partitioning effect in dynamic transport, comparing with plants at the
shrub site displayed more flexible water utilisations. From the
perspective of plant water use patterns and evolution, alpine shrub on
the northern QPT were formed from the long-term encroachment of \emph{P.
fruticosa} . This result is consistent with the results published
previously by Klein et al. (2007) , who found that shrub populations are
a result of proliferation and expansion of woody plant, and that areal
expansion of shrubs is one of the most threatening forms of grassland
degradation (Eldridge et al., 2011) . The contrasting plant water use
patterns identified in our study provided theoretical basis for the
alpine grassland shrubbization, contributed to predict vegetation
functional dynamics and the ecohydrological process under current and
future climatic conditions should take species-specific plasticity and
responses to short-term water supply fluctuations into account.

\textbf{5. Conclusions and future directions}

The \selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{18}O and \selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{2}H values of
precipitation, soil water, and plant water varied significantly over
months at the alpine grassland and \emph{P. fruticosa} shrub sites on
the northern QTP, those of groundwater remained relatively stable during
the sampling period. Considering groundwater, precipitation, soil water,
and plant water, a progressive enrichment in \selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{18}O or
\selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{2}H existed from groundwater and precipitation to soil
water to plant water for each month. Alpine grassland was more
susceptible to drought stress, had a stronger partitioning effect in
dynamic transport than shrub. The \emph{P. fruticosa} shrub displayed
more flexible water utilisations, and was more competitive for water
than grasslands. Furthermore, the plants in alpine shrub and grassland
reached water use balance in August to October. Shrubs degraded from
alpine grassland changed water use pattern of grassland, thereby
changing soil water storage. These results contribute to understand the
alpine grassland shrubbization from water use patterns of grassland and
shrub plants on the northern Qinghai-Tibet Plateau, promote better
understanding of the interface between plant and surrounding soils from
the perspective of eco-hydrological processes on the QTP.

Our study explored the interaction of soil water and plant water at the
alpine grassland and \emph{P. fruticosa} shrub sites using stable
isotopes, drawn important conclusions in the process of alpine grassland
shrubbization. However, greater variety of species, more potential water
sources (dew, creek and deeper groundwater), multi-site continuous
observation, and longer time scales need to be took into consideration
to further examine in the future.

\textbf{ACKNOWLEDGEMENT}

We sincerely thank the anonymous invaluable comments provided for the
improvement of the manuscript. This work was supported by National
Natural Science Key Foundation of China (Y711641501), the Natural
Science Foundation of Qinghai (2021-HZ-811). We are grateful to Haihong
Gao, Jianshe Ge, Quande Yang, Peiling Ma and Ruxiong Qi for the
assistance in the experiments.

\textbf{DECLARATIONS}

Ethical Approval: The paper is not currently being considered for
publication elsewhere. All authors have been personally and actively
involved in substantial work leading to the paper, and will take public
responsibility for its content.

\textbf{Consent to Participate:} Informed consent was obtained from all
individual participants included in the study.

\textbf{Consent to Publish:} The participant has consented to the
submission of the case report to the journal.

\textbf{Conflict of Interest:} None.

\textbf{AUTHOR CONTRIBUTION}

J Li performed the research, wrote the paper; F Zhang analyzed data, and
G Cao, Y Du, Y Wang, H Zhou and B Wang verified the results; X Guo
conceived the study.

\textbf{DATA AVAILABILITY}

The data that support the findings of this study are openly available in
Dryad, https://doi.org/10.5061/dryad.h44j0zpnb.

\textbf{REFERENCES}

Beyer M, Hamutoko J, Wanke H, Gaj M, Koeniger P. 2018. Examination of
deep root water uptake using anomalies of soil water stable isotopes,
depth-controlled isotopic labeling and mixing models. \emph{Journal of
Hydrology} 566\textbf{:} 122-136.

Brooks P D, Chorover J, Fan Y, Godsey S E, Maxwell R M, McNamara J P,
Tague C. 2015. Hydrological partitioning in the critical zone: Recent
advances and opportunities for developing transferable understanding of
water cycle dynamics. \emph{Water Resources Research}
51\textbf{:}6973-6987.

Chang E, Li P, Li Z, Xiao L, Zhao B, Su Y, Feng Z. 2019. Using water
isotopes to analyze water uptake during vegetation succession on
abandoned cropland on the Loess Plateau, China.
\emph{Catena}181\textbf{:} 104095.

Che C, Zhang M, Argiriou A A, Wang S, Du Q, Zhao P, Ma Z. 2019. The
Stable Isotopic Composition of Different Water Bodies at the
Soil--Plant--Atmosphere Continuum (SPAC) of the Western Loess Plateau,
China. \emph{Water} 11\textbf{:} 1742.

Crawford J, Hughes C E, Lykoudis S. 2014. Alternative least squares
methods for determining the meteoric water line, demonstrated using GNIP
data. \emph{Journal of Hydrology} 519\textbf{:} 2331-2340.

D'Odorico P, Caylor K, Okin G S, Scanlon T M. 2007. On soil
moisture--vegetation feedbacks and their possible effects on the
dynamics of dryland ecosystems. \emph{Journal of Geophysical Research:
Biogeosciences} 112.

Dai L, Guo X, Ke X, Du Y, Zhang F, Cao G. 2021. The variation in soil
water retention of alpine shrub meadow under different degrees of
degradation on northeastern Qinghai-Tibetan plateau. \emph{Plant and
Soil} 458\textbf{:} 231-244.

Dai L, Guo X, Zhang F, Du Y, Ke X, Li Y, Cao G, Li Q, Lin L, Shu K.
2019a. Seasonal dynamics and controls of deep soil water infiltration in
the seasonally-frozen region of the Qinghai-Tibet plateau. \emph{Journal
of Hydrology} 571\textbf{:} 740-748.

Dai L, Ke X, Guo X, Du Y, Zhang F, Li Y, Li Q, Lin L, Peng C, Shu K.
2019b. Responses of biomass allocation across two vegetation types to
climate fluctuations in the northern Qinghai--Tibet
Plateau.\emph{Ecology and evolution} 9\textbf{:} 6105-6115.

Dai L; Guo X; Ke X; Du Y; Zhang F; Li Y; Li Q; Lin L; Cao G; Peng C.
2019c. Responses of plant communities to degenerate succession in a
shrub-meadow on the Qinghai-Tibet Plateau. \emph{Journal of Ecological
Environment} 28\textbf{:} 732.

Dawson T E, Ehleringer J R. 1991. Streamside trees that do not use
stream water. \emph{Nature} 350\textbf{:} 335-337.

Eldridge D J, Bowker M A, Maestre F T, Roger E, Reynolds J F, Whitford W
G. 2011. Impacts of shrub encroachment on ecosystem structure and
functioning: towards a global synthesis. \emph{Ecology
letters}14\textbf{:} 709-722.

Farquhar G D, Cernusak L A, Barnes B. 2007. Heavy water fractionation
during transpiration. \emph{Plant physiology} 143\textbf{:} 11-18.

Fischer B M, van Meerveld H I, Seibert J. 2017. Spatial variability in
the isotopic composition of rainfall in a small headwater catchment and
its effect on hydrograph separation. \emph{Journal of
Hydrology}547\textbf{:} 755-769.

Gazis C, Feng X. 2004. A stable isotope study of soil water: evidence
for mixing and preferential flow paths. \emph{Geoderma}
119\textbf{:}97-111.

Goldsmith G R, Mu\selectlanguage{ngerman}ñoz\selectlanguage{english}-Villers L E, Holwerda F, McDonnell J J, Asbjornsen
H, Dawson T E. 2012. Stable isotopes reveal linkages among
ecohydrological processes in a seasonally dry tropical montane cloud
forest. \emph{Ecohydrology} 5\textbf{:} 779-790.

Gou X, Hu Z, Cui G, He H, Sun J, Hao L, Gu L. 2011. Monsoon changes and
their correlation with summer precipitation on the Ordos
Plateau.\emph{Arid Zone Resources and Environment} 25\textbf{:} 79-83.

Gow L, Barrett D, O'grady A, Renzullo L, Phinn S. 2018. Subsurface
water-use strategies and physiological responses of subtropical eucalypt
woodland vegetation under changing water-availability
conditions.\emph{Agricultural and Forest Meteorology} 248\textbf{:}
348-360.

Guo X, Dai L, Li Q, Qian D, Cao G, Zhou H, Du Y. 2020. Light grazing
significantly reduces soil water storage in alpine grasslands on the
Qinghai-Tibet plateau. \emph{Sustainability} 12\textbf{:} 2523.

He J; Liu Z.; Yao T; Sun S; Lv Z; Hu X; Cao G; Wu X; Li L; Pu H. 2020.
Restriction factors and restoration techniques of degraded grassland
restoration on the Qinghai-Tibet Plateau. \emph{Science and Technology
Herald} 38\textbf{:} 66-80.

Ji Z, Pei T, Chen Y, Wu H, Hou Q, Shi F, Xie B, Zhang J. 2022. The
driving factors of grassland water use efficiency along degradation
gradients on the Qinghai-Tibet Plateau, China. \emph{Global Ecology and
Conservation} \textbf{:} e02090.

Klein J A, Harte J, Zhao X-Q. 2007. Experimental warming, not grazing,
decreases rangeland quality on the Tibetan Plateau. \emph{Ecological
Applications} 17\textbf{:} 541-557.

Lanning M, Wang L, Benson M, Zhang Q, Novick K A. 2020. Canopy isotopic
investigation reveals different water uptake dynamics of maples and
oaks. \emph{Phytochemistry} 175\textbf{:} 112389.

Li H, Wang Z, Zhang F, Yi L, Guo X, Li Y, Lin L, Cao G, Li Y, Zhou
H.2022. Characteristics of soil water-holding functions in alpine
grassland-dwarf tarragon meadows at the southern foot of the Qilian
Mountains. \emph{Soil and water conservation research}
29\textbf{:}135-141+146.

Li J, Zhang F, Si M, Lan Y, Li B, Lin L, Du Y, Cao G, Guo X. 2022.
Response of Soil Water Storage to Meteorological Factors in Alpine Shrub
Meadow on Northeastern Qinghai--Tibetan Plateau.
\emph{Diversity}14\textbf{:} 185.

Li X-Y, Zhang S-Y, Peng H-Y, Hu X, Ma Y-J. 2013. Soil water and
temperature dynamics in shrub-encroached grasslands and climatic
implications: results from Inner Mongolia steppe ecosystem of north
China. \emph{Agricultural and forest meteorology} 171\textbf{:} 20-30.

Liu H, Mi Z, Lin L, Wang Y, Zhang Z, Zhang F, Wang H, Liu L, Zhu B, Cao
G. 2018. Shifting plant species composition in response to climate
change stabilizes grassland primary production. \emph{Proceedings of the
National Academy of Sciences} 115\textbf{:} 4051-4056.

Liu J, Wu H, Cheng Y, Jin Z, Hu J. 2021. Stable isotope analysis of soil
and plant water in a pair of natural grassland and understory of planted
forestland on the Chinese Loess Plateau. \emph{Agricultural Water
Management} 249\textbf{:} 106800.

Li Z, Duan R, Ke H, Liu X, Xie G, Gao W, Song L, Zhang B, Gui J, Xue J.
2022. Research progress of ecohydrology in the source region of the
Yangtze River based on hydrochemical characteristics. \emph{Glacier
permafrost} 44: 288-298.

Martin-Gomez P, Serrano L, Ferrio J P. 2017. Short-term dynamics of
evaporative enrichment of xylem water in woody stems: implications for
ecohydrology. \emph{Tree physiology} 37\textbf{:} 511-522.

Meinzer F C, Brooks J, Domec J C, Gartner B L, Warren J, Woodruff D,
Bible K, Shaw D. 2006. Dynamics of water transport and storage in
conifers studied with deuterium and heat tracing techniques.\emph{Plant,
cell \& environment} 29\textbf{:} 105-114.

Phillips S L, Ehleringer J R. 1995. Limited uptake of summer
precipitation by bigtooth maple (Acer grandidentatum Nutt) and Gambel's
oak (Quereus gambelii Nutt). \emph{Trees} 9\textbf{:} 214-219.

Plavcova L, Hronkova M, \selectlanguage{polish}Š\selectlanguage{english}imkov\selectlanguage{ngerman}á M, Kv\selectlanguage{polish}ě\selectlanguage{english}to\selectlanguage{polish}ň \selectlanguage{english}J, Vr\selectlanguage{ngerman}áblová M, Kubásek J,
\selectlanguage{polish}Š\selectlanguage{english}antr\selectlanguage{polish}ůč\selectlanguage{english}ek J. 2018. Seasonal variation of \selectlanguage{greek}δ\selectlanguage{english}18O and \selectlanguage{greek}δ\selectlanguage{english}2H in leaf water of
Fagus sylvatica L. and related water compartments. \emph{Journal of
Plant Physiology} 227\textbf{:} 56-65.

Rothfuss Y, Javaux M. 2017. Reviews and syntheses: Isotopic approaches
to quantify root water uptake: a review and comparison of
methods.\emph{Biogeosciences} 14\textbf{:} 2199-2224.

Rozanski K, Aragu\selectlanguage{ngerman}ás-Araguás L, Gonfiantini R. 1993. Isotopic patterns in
modern global precipitation. \emph{Geophysical Monograph-American
Geophysical Union} 78\textbf{:} 1-1.

Ryel R J, Ivans C Y, Peek M S, Leffler A J. 2008. Functional differences
in soil water pools: a new perspective on plant water use in
water-limited ecosystems. \emph{In} Progress in botany. Springer.
397-422.

Schultz N M, Griffis T J, Lee X, Baker J M. 2011. Identification and
correction of spectral contamination in 2H/1H and 18O/16O measured in
leaf, stem, and soil water. \emph{Rapid Communications in Mass
Spectrometry} 25\textbf{:} 3360-3368.

Schwärzel K, Zhang L, Montanarella L, Wang Y, Sun G. 2020. How
afforestation affects the water cycle in drylands: A process\selectlanguage{english}-based
comparative analysis. \emph{Global change biology} 26\textbf{:} 944-959.

Sprenger M, Leistert H, Gimbel K, Weiler M. 2016. Illuminating
hydrological processes at the soil\selectlanguage{english}-vegetation\selectlanguage{english}-atmosphere interface with
water stable isotopes. \emph{Reviews of Geophysics} 54\textbf{:}674-704.

Sun J, Zhou T C, Liu M, Chen Y C, Liu G H, Xu M, Shi P L, Peng F,
Tsunekawa A, Liu Y. 2020. Water and heat availability are drivers of the
aboveground plant carbon accumulation rate in alpine grasslands on the
Tibetan Plateau. \emph{Global ecology and biogeography}
29\textbf{:}50-64.

Vargas A I, Schaffer B, Yuhong L, Sternberg L d S L. 2017. Testing plant
use of mobile vs immobile soil water sources using stable isotope
experiments. \emph{New Phytologist} 215\textbf{:} 582-594.

Walker B H, Ludwig D, Holling C S, Peterman R M. 1981. Stability of
semi-arid savanna grazing systems. \emph{The Journal of Ecology}
\textbf{:} 473-498.

Wang J, Fu B, Jiao L, Lu N, Li J, Chen W, Wang L. 2021a. Age-related
water use characteristics of Robinia pseudoacacia on the Loess
Plateau.\emph{Agricultural and Forest Meteorology} 301\textbf{:} 108344.

Wang J, Fu B, Lu N, Wang S, Zhang L. 2019. Water use characteristics of
native and exotic shrub species in the semi-arid Loess Plateau using an
isotope technique. \emph{Agriculture, Ecosystems \&
Environment}276\textbf{:} 55-63.

Wang Y, Pei W, Cao G, Guo X, Zhou H, Du Y. 2021b. Moderate Grazing
Increases Water Use Efficiency for Environmental Health in Alpine
Meadows of the Tibetan Plateau. \emph{Frontiers in Ecology and
Evolution} 9.

White J C, Smith W K. 2013. Water sources in riparian trees of the
southern Appalachian foothills, USA: A preliminary study with stable
isotope analysis. \emph{Riparian Ecology and Conservation}
1\textbf{:}46-52.

Wu H, Li X-Y, Jiang Z, Chen H, Zhang C, Xiao X. 2016. Contrasting water
use pattern of introduced and native plants in an alpine desert
ecosystem, Northeast Qinghai--Tibet Plateau, China. \emph{Science of the
Total Environment} 542\textbf{:} 182-191.

Wu H, Zhao G, Li X-Y, Wang Y, He B, Jiang Z, Zhang S, Sun W. 2019.
Identifying water sources used by alpine riparian plants in a
restoration zone on the Qinghai-Tibet Plateau: Evidence from stable
isotopes. \emph{Science of the Total Environment} 697\textbf{:} 134092.

Wu J, Wang H, Li G, Ma W, Wu J, Gong Y, Xu G. 2020. Vegetation
degradation impacts soil nutrients and enzyme activities in wet meadow
on the Qinghai-Tibet Plateau. \emph{Scientific reports}
10\textbf{:}1-17.

Yang Y, Fu B. 2017. Soil water migration in the unsaturated zone of
semiarid region in China from isotope evidence. \emph{Hydrology and
Earth System Sciences} 21\textbf{:} 1757-1767.

Zhang F, Jia W, Zhu G, Zhang Z, Shi Y, Yang L, Xiong H, Zhang M. 2022.
Using stable isotopes to investigate differences of plant water sources
in subalpine habitats. \emph{Hydrological Processes} 36\textbf{:}e14518.

Zhou Y, Gao X, Wang J, Zhao X. 2021. Study on the source of water uptake
by roots of Lycium barbarum in irrigated area of Qaidam
Basin.\emph{Chinese Journal of Ecological Agriculture} 29\textbf{:}
400-409.

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