Tree Physiology 34, 966–980
doi:10.1093/treephys/tpu067
Research paper
Tree growth and intrinsic water-use efficiency of inland riparian
forests in northwestern China: evaluation via δ13C and δ18O
analysis of tree rings
Xiaohong Liu1,3, Wenzhi Wang1,2, Guobao Xu1,2, Xiaomin Zeng1,2, Guoju Wu1,2, Xuanwen Zhang1,2
and Dahe Qin1
1State
Key Laboratory of Cryospheric Sciences, Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, No. 320 Donggang
West Road, Lanzhou 730000, China; 2University of the Chinese Academy of Sciences, Beijing 100049, China; 3Corresponding author ([email protected])
Received May 18, 2014; accepted July 9, 2014; published online August 21, 2014; handling Editor Marc Abrams
The rising atmospheric CO2 concentration (Ca) has increased tree growth and intrinsic water-use efficiency (iWUE). However,
the magnitude of this effect on long-term iWUE and whether this increase could stimulate the growth of riparian forests in
extremely arid regions remain poorly understood. We investigated the relationship between growth [ring width; basal area
increment (BAI)] and iWUE in a riparian Populus euphratica Oliv. forest to test whether growth was enhanced by increasing
CO2 and whether this compensated for environmental stresses in the lower reaches of the inland Heihe River, northwestern
China. We accomplished this using dendrochronological methods and carbon (δ13C) and oxygen (δ18O) isotopic analysis. We
found an increase in BAI before 1958, followed by a decrease from 1958 to 1977 and an increase to a peak around 2000.
Tree-ring carbon discrimination (Δ) and δ18O indicated significant negative overall trends from 1920 to 2012. However, the
relationship shifted in strength and direction around 1977 from significantly negative to a weak connection. The seasonal
minimum temperature in April to July showed strong influence on Δ, and δ18O was controlled by relative humidity (negatively correlated) and temperature (positively correlated) in June and July. The patterns of internal to atmospheric CO2 (Ci/Ca)
suggest a specific adaptation of tree physiology to increasing CO2. Intrinsic water-use efficiency increased significantly (by
36.4%) during the study period. The increased iWUE explained 19.8 and 39.1% of the observed yearly and high-frequency
(first-order difference) variations in BAI, respectively, after 1977. Our results suggest significant CO2 stimulation of riparian
tree growth, which compensated for the negative influences of reductions in river streamflow and a drying climate during the
study period.
Keywords: CO2 fertilization, stable isotopes.
Introduction
It is widely acknowledged that modifications in gas exchange
and growth are among the primary responses of trees to
the current rise in atmospheric CO2 concentrations (Huang
et al. 2007). During the past 100 years, the atmospheric
CO2 concentration has been rising at an unprecedented rate
(McCarroll and Loader 2004), from 303 μmol mol−1 in 1920
to 391 μmol mol−1 in 2011 (IPCC 2013). Growth chamber
experiments have confirmed that the intrinsic water-use efficiency (iWUE) of trees, which represents the ratio of carbon
uptake to water loss through transpiration, increases with
decreasing stomatal conductance in response to elevated CO2
(Ainsworth and Long 2005, Battipaglia et al. 2013). Based
on simulations using a terrestrial model, further increases of
the atmospheric CO2 concentration will significantly increase
water-use efficiency throughout China by the end of the 21st
© The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please email: [email protected]
Riparian forest growth and iWUE 967
century, especially in forest areas, and the effects on wateruse efficiency will vary among geographical regions (Zhu et al.
2011).
At present, our knowledge of the long-term effects of rising CO2 concentrations on natural tree growth remains incomplete. Most studies from around the world that used tree-ring
stable carbon isotope ratios (δ13C) under natural conditions
have shown that trees vary in their responses to increasing
atmospheric CO2, suggesting the possibility of different adaptation strategies by different species, as well as the existence
of one or more interactions with other environmental factors
(Liu et al. 2008, Martinez-Vilalta et al. 2008, Silva et al. 2010,
Peñuelas et al. 2011, Wang and Feng 2012, Wang et al. 2012).
Despite the greater atmospheric CO2 concentration and the
expected increase in iWUE during the last century (Saurer
et al. 2004, Waterhouse et al. 2004, Liu et al. 2007, 2008,
Wang et al. 2012, Keenan et al. 2013), tree growth has not
always increased as expected; on the contrary, it has remained
stable or even declined in some areas, suggesting that local
stress factors have overridden the expected CO2-induced
growth increase (Peñuelas et al. 2011, Silva and Anand 2013,
Lévesque et al. 2014, Wu et al. 2014). To date, variation in
the relationship between iWUE and growth has been interpreted as evidence of warming-induced water stress, which
could explain both the reduced productivity and the enhanced
water-use efficiency (Nock et al. 2011, Peñuelas et al. 2011).
Exceptions to this general trend are expected in cold regions,
where low temperatures limit productivity. Seibt et al. (2008)
suggested that plant δ13C alone is not a sufficiently reliable
indicator of changes in plant water-use efficiency without independent estimates of gas exchange or environmental conditions. Recently, Silva and Horwath (2013) concluded that the
increase in iWUE estimated from tree-ring δ13C occurs independently of the changes in 13C discrimination that characterize
physiological responses to elevated CO2, and they suggested
that complementary methods should be used in combination
with iWUE analysis to discern the real effects.
The oxygen isotope ratio (δ18O) in tree rings can provide different insights into the causes of variation of iWUE (Battipaglia
et al. 2013, Gómez-Guerrero et al. 2013, Liu et al. 2014). Treering δ18O records both δ18O of meteoric source water and leaf
transpiration, which is controlled dominantly by vapor pressure
deficit (McCarroll and Loader 2004). Therefore, δ18O is often
negatively correlated with stomatal conductance (gs), because
changes in gs and transpiration with humidity alter leaf temperature and evaporation enrichment (Barbour and Farquhar
2000). Thus, combined analyses of carbon and oxygen isotopes in tree rings is probably the best way to investigate
changes in tree physiological responses (McCarroll and Loader
2004, Kruse et al. 2012, Lévesque et al. 2014, Liu et al. 2014),
and can reveal whether stomatal conductance or photosynthetic rate contributed most strongly to the variation of iWUE in
response to elevated CO2 (Scheidegger et al. 2000, Lévesque
et al. 2014).
In arid regions, the riparian forest is one of the key vegetation
components and performs crucial functions such as denitrification of run off, sediment control, reducing the damaging effects
of flooding and stabilizing stream banks, but it is also significant
for maintaining biodiversity and supporting the development
of oases (Zhang et al. 2012). Thus, the responses of riparian
trees to increasing atmospheric CO2 and local environmental
stresses will have important implications for characterizing the
vulnerability and development of riparian forests. In the present
study, we focused on the dominant riparian species Populus
euphratica Oliv. (Euphrates poplar), a natural desert tree that
grows along the lower reaches of Heihe River in northwestern China. We combined dendrochronological and isotope data
(δ13C and δ18O) to provide an integrated analysis of the changes
in radial growth, iWUE and stomatal conductance of the poplar.
Our specific objectives were to investigate the riparian growth
of Euphrates poplar during the past century, test the climatic
significance of tree-ring δ13C and δ18O data and determine how
changes in iWUE are related to changes in tree growth rates
based on the combination of tree-ring width and basal area
increment (BAI), tree-ring δ13C and tree-ring δ18O. The results
obtained from this study have broad implications for the dynamics of riparian forest under changing environmental stresses
and will inform government management decisions for riparian
forest ecosystems in water-limited regions.
Materials and methods
Study site
Our sampling site was located in the lower reaches of the Heihe
River, close to the Langxinshan mountains of northwestern China
(100.18°E, 40.95°N); it is the second largest inland river in China
(Figure 1). The region's climate is characterized by extremely
low precipitation (<40 mm) and strong evaporation (3746–
4213 mm) (Liu and Zhao 2003). During the instrumental period
for which data are available (1960–2012), mean monthly temperatures ranged from −11.5 °C in January to 27.0 °C in July, with
an annual average of 8.9 °C (Figure 2). Total precipitation averages 34.9 mm per year, of which 49.5% falls between July and
August. The monthly relative humidity is lowest in April and May
(∼22%) and averages 33.9% for the year. The dominant riparian
forest species is P. euphratica, which grows in sandy soil and is
part of a crucial natural desert forest ecosystem in northwestern
China. The species can survive extreme temperatures, as well
as drought and salt stress, and is therefore an important plant
species to study the mechanisms by which woody plants survive
under heat and drought stress. The main shrub species in the
study area include Tamarix ramosissima Ledeb. and Sophora alopecuroides L. The main soil type at the study site is a semi-fixed
aeolian sandy soil (Liu and Zhao 2003).
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968 Liu et al.
only on the changes of ring width. To overcome this problem,
we derived an annual BAI series, calculated forward from pith
not considering the bark, from the raw ring widths based on
the assumption of concentrically distributed tree rings (Phipps
and Whiton 1988):
BAI = π × (Rn2 − Rn2−1), (1)
where R is the tree radius and n is the year of tree-ring
­formation.
Isotopic analyses
Figure 1. Map of the location of the tree-ring sampling site, meteorological station and stream flow gauge used in this study.
Wood core sampling
We obtained 44 increment cores from 22 P. euphratica
trees, all of which were large mature trees and were growing along the river bank of the lower reaches of the Heihe
River (Figure 1, see Table S1 available as Supplementary Data
at Tree Physiology Online) using a 12-mm-diameter increment
borer (Haglöf, Mora, Sweden). The cores were processed for
measurement (at a resolution of 0.01 mm) and cross-dated
using standard dendrochronological techniques. For all samples, cross-correlations were checked with the COFECHA software (Holmes 1983), and the ultimate chronologies for the
tree-ring-width indices were detrended by fitting a negative
exponential or linear regression curve to remove long-term
growth trends using the ARSTAN software (Cook and Holmes
1986). The statistical characteristics of the cross-dating are
presented in Table S1 available as Supplementary Data at Tree
Physiology Online.
Basal area increment
Tree-ring width decreases with age in mature trees. If a decline
in growth caused by environmental factors is suspected, the
age trend may make it impossible to detect this effect based
Tree Physiology Volume 34, 2014
One core from each of the five trees with no evident growth
disturbance was ultimately selected for isotope analysis. We
removed the first 20 years of each core before pooling the
woody material to avoid juvenile age effects on the treering isotopes. Annual rings were cut from each core with a
scalpel under a binocular microscope, and for each year, the
corresponding rings from each of the five cores were carefully pooled (Wang et al. 2012, Liu et al. 2014). Each pooled
sample was ground in a ball mill (Pulverisette 23, Fritsch,
Idar-Oberstein, Germany) prior to extracting the α-cellulose
according to standard procedures. The pooling method saves
time and resources and has been successfully used to extract
climate information in northwestern China (Liu et al. 2009,
Wang et al. 2012).
The α-cellulose was extracted using a modified version of
the method of Loader et al. (1997). To obtain better homogenization of the cellulose, we used an ultrasonic water bath
(JY92-2D, Scientz Industry, Ningbo, China) to break the cellulose fibers. The α-cellulose was then freeze-dried for 72 h
using a vacuum freeze dryer (Labconco Corporation, Kansas
City, MO, USA) prior to isotope analysis.
We packed 0.10–0.12 mg of α-cellulose for δ18O analysis in silver capsules, then conveyed each capsule into a
High-Temperature Conversion Element Analyzer linked to a
gas stable-isotope mass spectrometer (MAT-253, Thermo
Electron Corporation, Bremen, Germany) to determine the
δ18O values for each sample. The analysis was performed at
the State Key Laboratory of Cryospheric Sciences, Chinese
Academy of Sciences. The δ13C values were measured by
an element analyzer (Flash EA 1112) linked to a gas stableisotope mass spectrometer (Delta-plus, Thermo Electron
Corporation) at the Key Laboratory of Western China's
Environmental Systems, Lanzhou University. Each sample
was analyzed three times to determine the stability and the
mean values. The precision of the analysis was ≤0.3‰ for
δ18O and ≤0.05‰ for δ13C.
Carbon isotope discrimination and iWUE
The carbon isotope discrimination (Δ) in C3 plants can be
expressed as follows (Farquhar et al. 1982):
Riparian forest growth and iWUE 969
Figure 2. (a) Monthly climatic data at the Ejina meteorological station (Figure 1) for the region near the sampling site. Temporal changes for (b)
mean temperature, (c) precipitation, (d) relative humidity and (e) river streamflow of Langxinshan hydrological station.
Tree Physiology Online at http://www.treephys.oxfordjournals.org
970 Liu et al.
∆ = (δ13Ca − δ13Cp ) / (1 + [δ13Cp /1000]),
(2)
where Δ is the carbon isotope discrimination by the plant, and
δ13Ca and δ13Cp are the stable carbon isotopic values of ambient air and plant cellulose, respectively. Δ can also be calculated as follows to connect carbon isotope discrimination with
physiological responses:
∆ = a + (b − a)(Ci /Ca ), (3)
where a (∼4.4‰) represents the isotopic discrimination that
results from diffusion of CO2 from the atmosphere into the
intercellular space of cells, b (∼27‰) represents the isotopic
discrimination caused by discrimination of RuBP carboxylase
against 13CO2 (McCarroll and Loader 2004), and Ci and Ca are
the CO2 concentrations in the intercellular space of leaves and
in the atmosphere, respectively.
Intrinsic water-use efficiency is defined as the ratio of the
CO2 assimilation rate (A) to stomatal conductance (gs) for
water vapor (Ehleringer et al. 1993), which quantifies the
amount of carbon assimilated per unit leaf area per unit time,
and thus represents the cost of assimilation per unit of water. It
is calculated as follows:
iWUE = A/gs = Ca × (1 − [Ci / Ca ])/1.6.
(4)
Saurer et al. (2004) proposed that the isotope values in the tree's
annual growth rings result from three primary responses of gas
exchange to changes in Ca: (i) Ci = constant, (ii) Ci/Ca = constant
and (iii) Ca − Ci constant. The scenarios differ in the degree to
which the increase in Ci responds to the increase in Ca: either (i)
not at all, (ii) in a proportional way or (iii) at the same rate. Detailed
explanations of the three scenarios can be found in Saurer et al.
(2004) and Linares and Camarero (2012). Here, we use these
scenarios as guidelines for interpreting the observed tree-ring
carbon discrimination and iWUE trends.
Climatic data and statistical analyses
Based on instrumental records from the Ejina meteorological
station (41°57′N, 101°04′E, 941.3 m above sea level, 1960–
2012), which is near the sampling site, there has been a continuous and significant warming trend during the past 50 years.
Linear regression showed a rate of increase of 0.45 °C per
decade from 1960 onwards (Figure 2b). Annual precipitation over the 50-year period ranged between 7 (1983) and
101.1 mm (1969) (Figure 2c), and revealed no statistically
significant (−0.89 mm per decade, P > 0.1) long-term trend.
The relative humidity varied, but showed an overall decreasing
trend (−0.75% per decade) throughout the period (Figure 2d),
suggesting a gradual increase in evapotranspirational stress.
We used the observed streamflow data (Figure 2e) at the
Langxinshan hydrological gauge station (Figure 1), which is
Tree Physiology Volume 34, 2014
∼1 km downstream of the sampling site, to evaluate the influence of streamflow variability on poplar growth. Before 1990,
there was considerable interannual variation in river streamflow, but no long-term trend; after 1990, streamflow decreased
sharply, and then peaked in 2008 again. This decrease in
streamflow would potentially influence the riparian forest
growth.
We computed Pearson's correlation coefficient (r) to examine
the relationships between the observed climate data (temperature, precipitation and relative humidity) from 1960 to 2012 at
the Ejina meteorological station and the tree-ring-width index,
BAI, stable-isotope series (δ13C and δ18O), Δ and iWUE in the
corresponding years. The coherence of variability of tree-ring
δ13C and δ18O series was calculated by the 21-year moving
correlation analysis. We also calculated the response contrast
(RC) index according to the method of Silva and Anand (2013),
which equals the ratio of the cumulative change rates in growth
to iWUE. Correlation, linear regression and time-series analyses were conducted using the SPSS 11.0 statistical package
(SPSS, Chicago, IL, USA).
Results
Tree-growth trends and their climatic response
We detected a decrease in the tree-ring width from 1900 to
1980, followed by a slight increase in tree-ring width around
2000 in the past 30 years (Figure 3a). After removing the
potential long-term age effect (Figure 3b), the tree-ring-width
chronology revealed a maximum value in 1958, and a period
with relatively high tree growth from 1990 to 2000, as well as
a growth reduction from 1970 to 1980. Basal area increment
showed a continuous increase from 1900 to 1960, reaching a
peak in 1958, indicating that this riparian forest had matured
after ∼60 years of development. From 1960 to 2012, BAI and
tree-ring width showed similar variations (Figure 3c).
The climatic-response patterns of tree-ring-width index
and BAI were similar, and the strength of the moisture signal recorded in the ring-width index appeared to be slightly
stronger than the signal recorded in BAI (see Figure S1 available as Supplementary Data at Tree Physiology Online). The
temperature parameters had a strong positive influence on
BAI, and this relationship was generally stronger than that for
the ring-width index. However, the correlation coefficients of
tree growth for temperature, precipitation and relative humidity were not very strong (i.e., r < 0.4), although there were
some significant correlations between the growth parameters
(ring width and BAI) and the climatic parameters. However,
we found that the raw values for measured tree width and
stream runoff during the period when data were available for
all parameters followed a common trend, and were significantly
positively correlated (r = 0.266, P < 0.044; see Figure S2 available as Supplementary Data at Tree Physiology Online). There
Riparian forest growth and iWUE 971
Figure 3. Trends of (a) tree growth, (b) the standard ring-width index and (c) the basal area index (BAI) from 1900 to 2010. The dark lines represent the results of FFT filtering using an 11-year window to emphasize the low-frequency variations.
were obvious common peaks in growth and river streamflow in
1958. The correspondence of several peaks among the treegrowth proxies and streamflow suggests, to a certain degree,
the significant influence of variations in river runoff on growth
of the riparian forest. However, during the period 1978–80s,
the streamflow and tree growth had a clear divergence (see
Figure S2 available as Supplementary Data at Tree Physiology
Online), and the reason needs to be clarified further.
Tree-ring isotopes and their climatic responses
Tree-ring δ13C decreased significantly, at a rate of 0.041‰
per year, from 1960 to 2000, and followed the same trend
as the changes of atmospheric δ13C (Figure 4a). There was
no clear increase in δ13C from 1920 to 1960, suggesting
that the possible juvenile age effect on tree-ring δ13C was
avoided by removing the first 20 years of each core before
pooling the woody material. During the past 90 years, the
mean tree-ring Δ values generally showed a slight increasing trend (y = 0.0062x + 6.4, R2 = 0.143, P < 0.001), at a rate
of 0.062‰ per decade. From 1920 to 1980, tree-ring δ18O
decreased, and then increased sharply from 1980 to the
present (Figure 4b), suggesting a drying trend (decreasing
relative humidity; Figure 2d) and enhancing the dominance
of stomatal conductance in controlling isotopic discrimination.
We estimated changes in photosynthetic assimilation and in
the stomatal conductance of trees in the riparian forest by
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972 Liu et al.
Figure 4. Chronologies of (a) tree-ring δ13C and atmospheric δ13C (δ13Ca), (b) Δ and δ18O and (c) the correlation between tree-ring Δ and δ18O for
P. euphratica.
assessing the shift over time in the relationship between Δ
and δ18O. Overall, tree-ring Δ and δ18O were significantly negatively correlated (r = −0.295, P < 0.01). However, there was a
loss of this correlation after 1977, and when this period was
removed from the analysis, the overall correlation strengthened (r = −0.602, P < 0.001). The shift revealed by the 21-year
moving correlation (Figure 4c) indicates a divergence in the
factors that controlled Δ and δ18O.
The climatic-response patterns of Δ and δ18O differed both
temporally and in their signal strength (Figure 5). We found
a significant positive correlation between tree-ring Δ and the
mean minimum temperature in the current growing season
and in the current and previous fall, and negative but not significant correlations between Δ and the two moisture-related
Tree Physiology Volume 34, 2014
parameters, precipitation and relative humidity in July to August
(Figure 5a), suggesting a contrasting influence of the thermal
and moisture conditions on carbon discrimination. The strongest correlation between tree-ring Δ and the minimum temperature from April to September was 0.458 (P = 0.001). From
a comparison of the first-order difference (r = 0.129, P = 0.368),
we confirmed that the significant correlation between Δ and
the mean minimum temperature mostly resulted from low-­
frequency variations, not year-to-year variations (data not
shown), implying that the influence of the minimum temperature on carbon discrimination was not as strong as expected.
For tree-ring δ18O, the effects of temperature and moisture
conditions (precipitation and relative humidity) were clearly
in the opposite directions (Figure 5b). The most significant
Riparian forest growth and iWUE 973
Figure 5. Climatic response of tree-ring isotope ratios (a, tree-ring Δ; b, tree-ring δ18O) to mean temperature (Mean T), maximum temperature
(Max T), minimum temperature (Min T), precipitation and relative humidity. Horizontal dashed lines represent the 95% confidence interval. A p
before a month indicates that the month is in the previous year.
months for tree-ring δ18O were June to August of the growing season, with the highest correlation coefficients for mean
temperature (r = 0.544, P < 0.001) and relative humidity
(r = −0.564, P < 0.001) occurring during this period.
Overall, these results suggest that the influences of climate
on Δ were weaker than those on tree-ring δ18O. In addition,
comparing the tree-ring Δ and δ18O series with the streamflow record (see Figure S3 available as Supplementary Data
at Tree Physiology Online) revealed a strong and significant
correlation between δ18O and streamflow in 1954–2005
(r = −0.408, P = 0.003) but Δ (r = −0.155, P = 0.246). Clearly,
after 2005, tree-ring δ18O and river streamflow revealed similar trends.
Trends of Ci, Ci/Ca and iWUE
As expected, the intercellular CO2 concentration (Ci) increased
with increasing atmospheric CO2 concentration (Ca) rather than
exhibiting an adaptation to maintain constant Ci (Figure 6a).
The trend of Ci/Ca revealed a significant increase (0.003 per
decade) over the past 90 years, which is related to differences
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974 Liu et al.
Figure 6. Changes in tree physiological parameters over time. Trends for (a) Ci and Ca, (b) Ci/Ca and (c) iWUE. We calculated iWUE using Eq. (4) for
three scenarios based on the theoretical regulation of plant gas exchange in response to increasing atmospheric CO2 (Ca): (i) constant intercellular
CO2 (Ci), (ii) constant Ci/Ca and (iii) constant Ca − Ci.
in the timing and magnitude of the changes in Ci and Ca.
However, when we separated the overall study period into two
sub-periods, this revealed contrasting patterns: from 1920
to 1977, the ratio decreased, whereas from 1978 to 2012,
it increased (Figure 6b). This result suggests changes in the
physiological response to higher levels of atmospheric CO2.
From 1920 to 2012, iWUE increased significantly (by 36.4%;
Figure 6c). Before 1978, the trend in iWUE was significantly
Tree Physiology Volume 34, 2014
related to the trend that would exist in a constant Ci scenario
(the scenario that assumed the strongest response to the
atmospheric CO2 concentration), and accounted for 25.9% of
the variation in iWUE. However, the iWUE values from 1978 to
2012 were more consistent with the values predicted under
a scenario with constant Ci/Ca. Thus, we hypothesize that
the increases in iWUE during the two periods may have been
driven by different physiological mechanisms.
Riparian forest growth and iWUE 975
Correlations between BAI and iWUE
We detected an overall positive correlation (r = 0.244, P = 0.018)
between BAI and iWUE since 1920 (Figure 7a). However, there
are some clear differences in the relative rates of increase
between BAI and iWUE. For instance, there is a lower BAI around
1978, whereas iWUE continued to increase at this time. The
first-order difference comparison between BAI and iWUE also
showed a significant positive correlation (r = 0.293, P = 0.005,
1920–2012; Figure 7b), suggesting a substantial interannual
linkage between BAI and iWUE. The 21-year moving correlations revealed a gradually increasing linkage between BAI and
iWUE under increasing atmospheric CO2 (Figure 7c); the correlation became significant in 1978 for the raw data, and in 1965
for the first-order difference. However, BAI and iWUE changed
in opposite directions from 2006 to 2012 (Figure 7a and b).
The average RC values were 0.292 from 1920 to 1977, 0.931
from 1978 to 2012 and 0.243 from 1920 to 2012.
Discussion
Climatic controls of tree growth, Δ and δ18O
The significant positive effects of the temperature in March
on tree growth and BAI indicate that warm spring benefits
the growth of P. euphratica (Liang et al. 2013). However, the
low correlation coefficients (r < 0.4) for the climatic controls
of tree-ring-width index and BAI (see Figure S1 available as
Supplementary Data at Tree Physiology Online) showed that
the climatic parameters did not strongly control tree radial
growth. In other words, other factors were responsible for
the observed variation in tree radial growth. In 1947, BAI
decreased dramatically, indicating that a stressful event may
have occurred. For trees growing beside a river, the variability
of streamflow is often a dominant factor that influences their
vulnerability to stress. This is consistent with the significant
relationship between the raw tree-ring width and river streamflow (see Figure S2 available as Supplementary Data at Tree
Physiology Online). However, there was no remarkable correlation among streamflow and the two growth parameters
(ring-width index and BAI). Our data show good peak-to-peak
correspondences between river streamflow and BAI, such as
in 1958, 1971, 1972, 1983, 1989, 1993, 1998 and 2002.
A previous streamflow reconstruction (Qin et al. 2010) for
the upper reaches of the Heihe River that was inferred from
an independent tree-ring-width chronology for Qilian Juniper
revealed lower values of runoff around 1928, 1934, 1971 and
2001 during the past century. However, the growth of poplars
in these 4 years was not always low (Figure 3), indicating the
possibility that human activities influenced variations of river
streamflow in the middle reaches of the river and that this, in
turn, influenced tree radial growth.
Our tree-ring δ13C values were consistent with those previously reported in western China (Liu et al. 2008, 2014,
Wang et al. 2012), and showed progressively lower values
over time. The tree-ring δ13C values changed simultaneously
with atmospheric δ13C (Figure 4a). After removing the lowfrequency variations in atmospheric δ13C, the overall increasing trend for tree-ring Δ revealed a specific response of Ci/Ca
and a temporal trend in plant carbon–water relations. Based on
the climatic response of tree-ring Δ, we found the influence of
minimum temperature mainly in April to July recorded on the
tree-ring carbon discrimination (Figure 5a), suggesting some
effect of minimum temperature on Δ which can be explained
by the linkage of increasing temperature and enhanced plant
evapotranspiration. The negative correlation between δ18O and
relative humidity is consistent with the physiological isotopic
responses (Barbour and Farquhar 2000, Roden et al. 2000).
Based on the combination of these results, we conclude that
stomatal conductance was the dominant factor that affected
δ18O and that tree-ring δ18O can be regarded as a proxy for
stomatal physiological responses (Barbour and Farquhar
2000). The patterns in the climatic response were similar to
those reported in previous tree-ring δ18O studies (An et al.
2012, Liu et al. 2014). The water source δ18O would also affect
the tree-ring δ18O, so the δ18O in tree rings can be used to infer
changes in the water source in certain regions and periods
(An et al. 2012, Brienen et al. 2013). Similar trends between
tree-ring δ18O and streamflow during the last decade (see
Figure S3a available as Supplementary Data at Tree Physiology
Online) suggest that tree-ring δ18O mainly reflected the variations of the river water, but this relationship was disturbed by
changes in the atmospheric environment, such as transpiration,
which were linked strongly to stomatal conductance.
Interaction of iWUE with physiological parameters
Elevated atmospheric CO2 is expected to affect plant carbon–
water relationships, as a decline in stomatal conductance is predicted when plants are exposed to elevated CO2 (Battipaglia
et al. 2013). If a decline in stomatal conductance occurs in
conjunction with an increase in carbon assimilation (owing to
the increased CO2 supply), this can change the Ca to Ci gradient, which will in turn determine the isotopic composition of the
assimilated carbon. From 1920 to 2012, Ca increased from 303
to 394 ppm (Figure 6). In consequence, the Ci of plants changed
greatly as a result of physiological responses to the environment
(from 195 ppm in 1920 to 247 ppm in 2012). The Ci/Ca ratio
reflects the balance between the net assimilation of CO2 (A)
and stomatal conductance (gs) according to Fick's law: A = gs
(Ca − Ci). Previous studies have found that Ci/Ca has remained
constant or increased during the past century (Ehleringer and
Cerling 1995, Feng 1998, Wang and Feng 2012), but Hietz et
al. (2005) found a slight decrease during the past 50 years in a
tropical forest. Over the entire study period, Ci/Ca showed a significant linear increasing trend (y = 0.0003x + 0.089, R2 = 0.143,
P < 0.001). However, from 1920 to 1977, Ci/Ca indicates a slight
Tree Physiology Online at http://www.treephys.oxfordjournals.org
976 Liu et al.
Figure 7. Comparison of tree BAI and iWUE from 1920 to the present: (a) yearly values, (b) first-order difference and (c) the 21-year moving
­correlation. The horizontal dashed line represents the 95% confidence level; negative correlations were not significant at P < 0.05.
Tree Physiology Volume 34, 2014
Riparian forest growth and iWUE 977
Figure 8. (a) Correlations between tree-ring δ18O and iWUE, and (b) the 21-year moving correlation between iWUE and δ18O (values above the
horizontal dashed line are significant at P < 0.05). (c) Relationships between iWUE and BAI at different periods.
decreasing trend, and after 1978, this parameter increased at a
rate of 0.004 per year, but this was not significant statistically
(Figure 6b). These results suggest a different response before
and after 1978 in the relationship between the increases in Ci in
response to the increase in Ca for different ranges of CO2 levels
(Saurer et al. 2004).
Tree Physiology Online at http://www.treephys.oxfordjournals.org
978 Liu et al.
The iWUE increased overall from 1920 to 2010 (Figure 6c),
which is consistent with the iWUE response by Qinghai spruce
in the Qilian mountains (Liu et al. 2011), but with different
rates of increase along a precipitation gradient from east to
west. However, changes in iWUE from 1920 to 1977 were
mostly close to the predicted changes in a scenario with constant Ci, which is related to the strong response to increasing
atmospheric CO2 (Saurer et al. 2004). From 1978 to 2012,
the changes in iWUE more closely followed the predicted values in a scenario with constant Ci/Ca, indicating that the tree
response to increasing CO2 became active. This change in the
physiological response to increasing CO2 would lead to differing contributions to the rate of increase in iWUE, and would
therefore lead to variations in tree growth.
Linkage of tree growth with iWUE
Even though the overall positive correlation between BAI and
iWUE since 1920 existed, there were some exceptions in several
short periods (e.g., from 1940 to 1950; from 1960 to 1978).
This is similar to the results from several previous investigations, which reported that increased water-use efficiency did
not necessarily translate into enhanced tree growth (Nock et al.
2011, Peñuelas et al. 2011, Silva and Anand 2013, Lévesque et
al. 2014). We note that, during this period, the relative humidity decreased (Figure 2d), which would increase the stomatal
effects of increasing iWUE. Climate-dependent δ18O signals can
provide a more complete picture of whether the changes in
iWUE were caused by differences in stomatal conductance or
by changes in photosynthetic capacity. In general, the correlation between δ18O and iWUE was significant from 1920 to 2012
(R2 = 0.186, P < 0.001; Figure 8a), and 18.6% of the variation
in iWUE could be explained by the variation in δ18O. The shift
in the correlations between tree-ring Δ and δ18O from negative
and non-significant to positive and significant (Figure 4c) indicates the decreasing importance of stomatal conductance for
determining tree-ring Δ after 1977, and therefore indicates the
minor contribution of the regulation of stomatal conductance
to iWUE. In other words, the increase in iWUE that occurred
after 1977 was mainly caused by the increasing CO2 concentration. The 21-year moving correlations revealed variations in
the impact of stomatal conductance on the changes in iWUE
(Figure 8b). From 1970 to 1990, the correlations between
iWUE and δ18O were weakest, suggesting that the contribution
of drought-induced iWUE during this period was not important.
From 1978 to 2005, BAI recovered and iWUE increased
synchronously, and the yearly and high-frequency correlations between the two parameters became statistically significant (Figure 7c). Together with the shift in the correlations
between tree-ring Δ and δ18O, these results led us to conclude
that iWUE was driven by the biochemical demand for CO2 in
photosynthesis and that the increasing iWUE promoted tree
growth after 1978. The RC values from 1920 to 1977, 1978 to
Tree Physiology Volume 34, 2014
2012 and 1920 to 2012 were all positive, suggesting that the
net changes in iWUE and growth are likely to have had similar
causes, and that the increase in iWUE stimulated tree growth in
general, even though the CO2 fertilization effect on tree growth
was weak during some short periods.
Considering the obvious opposite trends followed by iWUE
and BAI after 2005 (Figure 7a and c), we focused on the correlations between the two parameters from 1920 to 2005.
During this period, iWUE explained ∼6% of the overall variation
in BAI. From 1920 to 1977, the correlation between iWUE and
BAI was not significant (R2 = 0.013, P = 0.400), even though
the slope was positive (Figure 8c). In contrast, the significant
positive correlation between iWUE and BAI from 1978 to 2005
(R2 = 0.455, P < 0.001) suggests a remarkable CO2 stimulation
of tree growth (Figure 8c), which is supported by the RC evaluation (RC = 0.93, 1978–2012) according to Silva and Anand
(2013). Our results contrast with Lévesque et al. (2014), who
reported no significant contribution of increased iWUE to tree
growth under xeric and mesic conditions.
Other factors, such as nutrient limitation, may shift treegrowth trends in certain periods when water stress is not
apparent. For example, forest productivity under elevated CO2
is mostly limited by nutrient availability, and particularly by
nitrogen (Fisher et al. 2012). Increases in nitrogen deposition
over China (Liu et al. 2013, Jia et al. 2014) are expected to
stimulate primary productivity (Wu et al. 2014), but may also
lead to soil acidification, resulting in the loss of other nutrients
and limiting productivity increase. The leaching of soil nitrogen
that accompanies agricultural activities in the middle reaches
of the Heihe River will increase the nitrogen concentration in
groundwater and river water in the river's lower reaches. This
contribution to the development of riparian forest in the lower
reaches of the river remains to be determined. The abundance
of 15N in tree rings (Marshall et al. 2007) could be used to
clarify this key factor. Therefore, in future research, it will be
necessary to combine multi-proxy records, including additional
isotopic tracers, to describe the distinct roles of resource limitation (e.g., water vs nutrients) in modulating the response of
riparian forest to changes in atmospheric CO2.
Conclusions
As we expected based on our review of the literature, iWUE
increased for the riparian forest in the extremely arid study
region, and this change was related to changes in Ca and climate. The increase of iWUE explained 19.8 and 39.1% of the
observed yearly and high-frequency (first-order difference)
variations in BAI after 1978, indicating that the increased
iWUE enhanced tree growth to some extent. Around 1977, the
relationship between carbon discrimination and δ18O in tree
rings shifted in strength and direction, from significantly negative to non-significant, and revealed the changes in stomatal
Riparian forest growth and iWUE 979
conductance and photosynthetic rate that occurred at this time.
Overall, our results suggest a benefit from CO2 stimulation of
tree growth in the riparian forests of arid regions, especially
during the past 30 years. This stimulation compensated for
the negative influence of a reduction of river streamflow. Our
study highlights the advantage of simultaneous measurements
of two isotopes (δ13C and δ18O) and growth, since this provides more insights into changes in tree physiology and productivity in response to elevated CO2. The approach outlined
in the present study has great potential as a means to evaluate
the productivity of riparian forests, which will support more
optimal management of the water resources of inland rivers in
water-limited areas. We also note that the present study only
used P. euphratica to accomplish the goals of linking climate
change with water-use efficiency and tree growth in a specific study site, and some uncertainties may have existed in a
range of study sites (riparian to upland) and other tree species. Therefore, the results may not be indicative of the broader
region or other tree species, even on riparian sites.
Supplementary data
Supplementary data are available at Tree Physiology online.
Acknowledgments
The authors thank Dr Liangju Zhao for assistance with our
fieldwork and Dr Jianhua Si and Prof. Jingjie Yu for providing
the river streamflow data. The authors also thank the journal's anonymous reviewers for their constructive comments to
improve the manuscript.
Conflict of interest
None declared.
Funding
This research was supported by the National Natural Science
Foundation of China (41171167 & 41121001), and by the
self-determination project of the State Key Laboratory of
Cryospheric Sciences (SKLCS-ZZ-2013-01-03).
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