ARTICLE IN PRESS
Journal of
Arid
Environments
Journal of Arid Environments 71 (2007) 12–28
www.elsevier.com/locate/jaridenv
Isotopic carbon composition and related characters
of dominant species along an environmental gradient
in Inner Mongolia, China
S. Chen, Y. Bai, G. Lin, J. Huang, X. Han
Key Laboratory of Vegetation and Environmental Change, Institute of Botany,
The Chinese Academy of Sciences, Beijing 100093, China
Received 13 January 2005; received in revised form 5 January 2007; accepted 24 February 2007
Available online 20 April 2007
Abstract
Carbon isotope composition (d13C value) provides a useful measure of integrated water-use
efficiency (WUE) of plants and can be used to rank the drought tolerance of different species. We
determined the d13C values, leaf water content (LWC) and free proline content of 52 plant species
selected from eight plant communities along a moisture gradient in the Xilin River Basin, Inner
Mongolia. The d13C values and WUE of C3 plant species tended to increase as the occurrence
frequency and relative biomass of the species increased in the entire basin. The mean foliage proline
concentration of all species in a community was higher when the habitat was drier and the mean
LWC of plants decreased with increasing soil aridity. Significantly positive relationships existed
between the foliar proline concentration and occurrence frequency and relative biomass of the
species, respectively. Our results indicated that inter- and intra-species variations in WUE might
significantly influence the outcome of competitive interactions and played a large role in determining
species composition of plant communities. In addition, proline accumulation in leaves might
strengthen competitive ability of plants growing in drought prone habitats.
r 2007 Elsevier Ltd. All rights reserved.
Keywords: d13C values; Leaf water content (LWC); Osmotic adjustment; Proline; Soil moisture gradient; Wateruse efficiency (WUE)
Corresponding author. Tel.: +86 10 62836279; fax: +86 10 62599059.
E-mail addresses: [email protected] (S. Chen), [email protected] (X. Han).
0140-1963/$ - see front matter r 2007 Elsevier Ltd. All rights reserved.
doi:10.1016/j.jaridenv.2007.02.006
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13
1. Introduction
Plant responses to water scarcity are complex, involving stress avoidance and adaptive
changes (Chaves et al., 2002). Early responses to water stress would aid the survival of
plants and improve plant functioning under stress (Bohnert and Sheveleva, 1998). The
water-use efficiency (WUE) is an important indicator for the evaluation of adaptive
capability to water resource scarcity. WUE is traditionally defined either as the amount of
carbon biomass produced per unit water transpired by the plant or the ratio of net
photosynthesis to stomatal conductance over a period of seconds or minutes (Wright et al.,
1988). Recently, Carbon isotope composition (d13C) has been developed as a tool to
measure WUE, because a strong positive correlation is found between d13C and WUE
(Farquhar et al., 1989). d13C is partly determined by Ci/Ca, the ratio of CO2
concentrations in the leaf intercellular spaces to that in the atmosphere (Farquhar et al.,
1982, 1989; Farquhar and Richards, 1984). This ratio differs among plants because of the
variation in stomatal opening (affecting the supply rate of CO2), and the variation in the
chloroplast demand for CO2. Therefore, the d13C value not only integrates physiological
and environmental properties that influence the interplay among all aspects of plant
carbon and water relations over the period of growth, but also have been instrumental in
revealing how species adjust their gas exchange metabolism and strategies of resource
acquisition and use to ensure competitiveness and survival in a given habitat (Dawson
et al., 2002; Ehleringer, 1993; Smedley et al., 1991). In general, it appears that species
native to arid or semi-arid environments show either no change or an increase in WUE
with decreasing water supply, that is, their water-use pattern can become more
conservative during drought (Cohen, 1970; Toft et al., 1989).
Proline accumulates in many plant species under a broad range of stress conditions such
as water shortage, salinity, extreme temperatures, and high light intensity (Chang and Lee,
1999; Delauney and Verma, 1993; Maggio et al., 2000; Treichel et al., 1984). The
accumulation of proline may be beneficial for several reasons. Researchers have been
proposed that it may act as a compatible osmotic solute (Handa et al., 1986), as a proteinstabilizing or solubilizing factor under limited cell water conditions (Blackman, 1992), and
as a source of reduced nitrogen and carbon (Xie et al., 1997). The beneficial role of proline
in plant stress tolerance as suggested by early correlative studies was recently confirmed by
genetic as well as transgenic studies, which demonstrated that proline could increase the
tolerance of plants to abiotic stress (Bajaj et al., 1999; Hong et al., 2000; Nanjo et al., 1999;
Xiong and Zhu, 2002). Drought is the most frequent abiotic stress factor limiting plant
growth and ecosystem productivity in arid and semi-arid Inner Mongolia steppe (Bai et al.,
2004; Li and Li, 1991). However, we still did not know whether proline plays an important
role in the adaptation of plant species to arid habitats in this area.
In our study, species composition was surveyed in eight different communities along a
soil moisture gradient in the Xilin River Basin, Inner Mongolia and the d13C values, leaf
water content (LWC) and free proline concentrations of dominant steppe species were
determined. Our objectives were: (1) to determine the variations in d13C values and WUE
of dominant species from the steppe; (2) to examine changes in LWC and proline content
among these plant species; and (3) to identify physiologically adaptive strategies of steppe
species associated with different habitats, in particular, with regards to soil moisture, by
comparing the changes in WUE, LWC and proline concentration along the soil moisture
gradient.
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2. Materials and methods
2.1. Study site and plot selection
The Xilin River Basin (431260 N–441290 N, 1151320 E–1171120 E) is located within the
typical steppe zone of the Inner Mongolia Plateau, which covers an area of about
10 000 km2, and ranges in elevation from 900 to 1500 m. The Xilin River Basin experiences
a semi-arid continental temperate steppe climate with dry springs and moist summers.
Annual mean temperature increases from southeast to northwest, ranging from 0.5 to
2.1 1C. Annual precipitation decreases gradually from 400 mm in the southeast to 250 mm
in the northwest. More than 70% of annual precipitation occurs from May to August
(Chen, 1988). Chestnut and dark chestnut soils are the zonal soil types (Wang and Cai,
1988).
This study was conducted in the vicinity of the Inner Mongolia Grassland Ecosystem
Research Station (IMGERS), the Chinese Academy of Sciences, which is located at the
middle reach of the Xilin River. The most frequently found plant community types in the
region were selected for this study including swamp meadow, saline meadow, meadow
steppe, typical steppe, degraded typical steppe and sand dune communities. Detailed
information on the natural conditions of the eight plots was shown in Table 1. The eight
plots were ordered according to their soil moisture status in our study and from plots 1 to 8
represent a decreasing soil moisture gradient. The plots were significantly different in
floristic composition, soil moisture, soil nitrogen content, and community productivity
(Table 2). The plots 4, 5 and 6 in our study were permanent experiment plots (fenced in
1979 and 1983) set up by the IMGERS, which represent the typical Leymus chinensis
Table 1
Plant community description and location of each study plot in the Xilin River Basin, Inner Mongolia, China
Plot no.
Vegetation type
Location
0
Altitude (m)
Soil type
Land-use type
1
Swamp meadow
N 43137.460
E 116140.3470
1150
Swamp meadow soil
Fenced plot
2
Saline meadow
N 43144.9250
E 116140.6290
1190
Saline meadow soil
Grazing pasture
3
Meadow steppe
N 43129.4180
E 116149.6430
1380
Dark chestnut soil
Mowing field
4
Typical steppe
N 43132.8950
E 116140.7080
1250
Chestnut soil
Fenced plot
5
Typical steppe
N 43132.3220
E 116133.1170
1180
Chestnut soil
Fenced plot
6
Restoring degraded steppe
N 43135.7480
E 116144.4190
1210
Chestnut soil
Fenced plot
7
Degraded steppe
N 43137.9670
E 116139.3970
1180
Chestnut soil
Heavily grazed
8
Fixed sand dune complex
N 43139.1890
E 116139.8920
1220
Sandy soil
Fenced plot
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Table 2
Main characteristics of eight plant communities in the Xilin River Basin, Inner Mongolia, China
Plot
no.
Soil water
content (%)
0–20 cm
Soil
nitrogen
content (%)
0–20 cm
Average
canopy
height
(cm)
Community
density
(individual m2)
Species
richness
Aboveground
biomass
(g DW m2)
Dominant species
1
135.3754.8a
0.770.3a
28.479.5a
22187315a
47
558.9724.4a
Blysmus
sinocompressus,
Carex spp.,
Agrostideae spp.,
etc.
2
16.772.9b
0.270.0b,c
18.476.3a,b
5967323b,c
18
148.4756.2c
Achnatherum
splendens,
Leymus chinensis
3
15.671.2b
0.270.1b,c
16.371.7b
7387128b
54
159.9726.3c
Filifolium
sibiricum,
Stipa baicalensis
4
11.471.4c
0.270.0b
22.572.4a
4807126c
16
150.2723.2c
Leymus chinensis,
Stipa grandis
5
9.570. 7d
0.270.0b,c,d
16.372.1b
3747105c
24
81.5714.0d
Stipa grandis,
Leymus chinensis
6
7.872.8d,e
0.170.0c,d
22.773.8a
5427127c
33
240.2734.2b
Caragana
microphylla,
Leymus chinensis
7
7.170.6e
0.170.0c,d
9.072.1c
4387104c
19
113.4715.1c,d
Artemisia frigida,
Potentilla acaulis
8
4.472.4f
0.170.1d
45
264.17144.7b
Ulmus pumila,
Armeniaca
sibirica,
Cleistogenes
polyphylla
ND
ND
Data within columns are mean7SD (n ¼ 15 or n ¼ 10). Significant difference between plots was determined by
one-way ANOVA (Po0.05). Different letters indicate significantly different means (Po0.05, Duncan multiple
comparisons test). ND: Not determined.
steppe, Stipa grandis steppe and restored steppe. The areas of plots 4, 5 and 6 were 24, 25
and 27 ha, respectively, and no replicate plots were designed. And it is impossible to find
other similar plots in the Xilin River Basin due to heavy overgrazing. Thus, no replicate
plots were arranged for different community types in our study, so we have to be cautious
when the results were extrapolated to larger spatial scale.
2.2. Survey on vegetation composition
We analyzed the plant species composition from 93 quadrats (1 1 m in size) sampled in
eight plots (with 5–19 quadrats per community) from August 10–12, 2001. Over 22 years of
monitoring, we have found that this is within the time period when plants reach a
maximum in aboveground biomass. In most cases, 10 quadrats were sampled per plot.
Exceptions included the more heterogeneous habitats (sand dunes and meadow steppe),
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where we sampled 19 quadrats, and the more homogeneous meadow community, where we
sampled 5 quadrats. In each quadrat, the aboveground portion of each plant species was
collected and taken back to the lab for analysis. Fresh plant samples were oven-dried at
70 1C for about 48 h, and then weighed to determine their aboveground biomass.
Occurrence frequency of each species was determined based on the ratio of the number
of quadrat in which species occurred to the total number of quadrats (93 quadrats).
Similarly, relative biomass of each species was obtained by calculating the average ratio of
the biomass of each species to the total biomass in that quadrat.
2.3. Sampling and analyses
About 6–12 plant species were sampled from each plot for LWC, foliar d13C and proline
content analysis from 8:00 am to 17:00 pm, August 23–25, 2001. The sampling location was
close to the vegetation composition survey quadrats in each plot. The selected species were
dominant or common species in their respective community, and they represented more
than 80% of the total biomass (excluding plot 1). The classification based on
photosynthetic pathway, life form and water ecological group of all plant species was
shown in Table 3 according to their classification in Flora of Inner Mongolia (Editorial
Committee of Flora of Inner Mongolia, 1994).
Fully expanded leaves from at least 10 individuals of each plant species were collected as
one sample and five replicates were sampled. After sampling, the foliar samples were put in
a cooler immediately to avoid water loss. The leaf samples were then divided to two subsamples. One sub-sample was weighed immediately and quickly killed at 105 1C, and then
dried at 70 1C to constant weight for proline analysis. The other was dried at 70 1C, and
then ground to 80-mesh by a mill for isotopic analysis. LWC was calculated by the
following equation:
LWC ð%Þ ¼ ½ðfresh dry leaf weightÞ=fresh leaf weight 100.
(1)
At the same time, soil cores were sampled at 0–20 cm depths with a 5 cm diameter soil
sampling gauge, and 15 replicates were sampled at each plot. Soil water content (SWC) of
each sample was determined by the difference between moist and oven-dried (105 1C to
constant weight) samples according to the following equation:
SWC ð%Þ ¼ ½ðwet dry soil weightÞ=dry soil weight 100.
(2)
About 0.1 g plant samples were weighted and wrapped into a tin capsule (diameter 4 mm
and height 6 mm) to determine the carbon isotope composition. Carbon isotope
composition of leaf samples was measured with a Finnigan MAT251 mass spectrometer
in the Center of Soil and Environment Analysis, Institute of Soil Science, the Chinese
Academy of Sciences. The stable isotopic ratios of the leaves were expressed as follows:
d13 C ð%Þ ¼ ½ð13 C=12 CÞl ð13 C=12 CÞs =ð13 C=12 CÞs 1000,
(3)
where d13C is the foliar d13C value, and (13C/12C)l and (13C/12C)s are the carbon abundance
ratios of the leaf and the standard PDB, respectively. The analysis error of d13C value was
70.5%.
Foliar proline content was measured with a photometric method according to Bates
et al. (1973) and three replicates were determined for each species.
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Table 3
The carbon isotope composition (d13C value), LWC, proline content and descriptive characteristics of dominant
species in the Xilin River Basin
Family
Species
Life
form
Water
ecotype
d13C value (%)
LWC (%)
Proline
content
(mg g1DW)
Chenopodiaceae
Corispermum spp.
Kochia prostrata
Suaeda corniculata
A
S
A
X
X
HM
26.8170.23
14.8270.51
27.0471.17
79.071.4
63.672.6
86.471.0
297731
169716
233715
Compositae
Artemisia eriopoda
Artemisia frigida
Artemisia pubescens
Cirsium esculeutum
Filifolium sibiricum
Inula britanica
Leontopodium
leontopodioides
Leontopodium
longifolium
Ligularia sibirica
Serratula
centauroides
PF
S
PF
PF
PF
PF
PF
MX
X
X
M
MX
M
X
27.9170.45
25.0970.25
26.2070.38
27.9770.85
25.4770.25
27.3170.21
27.2170.51
72.370.6
73.5710.6
71.770.8
86.271.6
61.273.3
75.872.8
62.171.4
3757191
5497195
238777
115735
ND
112732
2697158
PF
XM
29.7570.13
80.172.2
6479
PF
PF
HM
MX
28.1570.31
27.4370.45
81.471.3
68.570.7
82712
6497246
Cyperaceae
Carex korshinskyi
Carex spp.
Scirpus spp.
PF
PF
PF
MX
M
H
26.4270.92
27.4670.44
28.0170.41
53.574.3
61.475.8
64.271.8
11079
72717
68715
Elaeagnaceae
Stellera chamaejasme
PF
X
26.2170.53
64.972.0
221755
Gramineae
Achnatherum
sibiricum
Achnatherum
splendens
Afropyron cristatum
Cleistogenes
polyphylla
Koeleria cristata
Leymus chinensis
Psammochloa villosa
Stipa baicalensis
Stipa grandis
PG
MX
25.9570.20
50.173.2
174717
PG
XM
26.8670.23
56.571.2
114723
PG
PG
X
X
26.7270.39
15.2670.51
55.573.8
51.576.0
304767
421730
PG
PG
PG
PG
PG
X
X
X
MX
X
28.7670.35
26.4170.27
26.8870.31
25.7070.41
25.5170.51
58.172.0
56.272.9
52.873.2
42.170.9
46.072.3
169742
174717
148722
135722
241747
Iridaceae
Iris lactes Pall. var.
chinensis Koidz.
PF
M
26.7370.31
70.571.9
219740
Juncaginaceae
Triglochin maritimum
PF
H
28.9070.24
81.571.1
ND
Leguminosae
Caragana
microphylla
Hedysarum
fruticosum var.
lignosum
Oxytropis
myriophylla
S
X
27.0470.27
53.073.2
10537157
S
MX
26.3170.88
61.473.9
257737
PF
X
25.6870.51
59.271.9
188723
PF
PF
MX
MX
25.7370.41
25.0170.62
83.970.4
68.071.0
286719
225729
Liliaceae
Allium ramosum
Anemarrhena
asphodeloides
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Table 3 (continued )
Family
Species
Life
form
Water
ecotype
d13C value (%)
LWC (%)
Proline
content
(mg g1DW)
Polygonaceae
Polygonum
divaricatum
PF
XM
26.9871.09
75.274.2
217738
Ranunculaceae
Caltha palustris
Pulsatilla
turczaninovii
Ranunculus japonicus
Thalictrum
petaloideum
Thalictrum
squarrosum
PF
PF
HM
MX
26.7971.52
25.3170.58
80.171.0
59.470.7
76713
7175
PF
PF
HM
XM
25.3070.35
27.8370.07
79.873.6
67.071.5
63713
3417138
PF
MX
26.9070.62
67.173.1
5817312
S
S
XM
M
28.5870.48
27.6170.14
52.273.1
54.272.3
160714
ND
PF
PF
PF
X
M
MX
28.2771.39
28.2570.12
26.9170.50
58.773.8
64.975.6
61.172.4
10276
8578
127719
T
M
27.3870.62
56.170.8
ND
S
XM
28.2070.55
48.573.2
ND
Rosaceae
Armeniaca sibirica
Cotoneaster
mongolicus
Potentilla acaulis
Potentilla anserina
Potentilla
tanacetifolia
Prunus padus L. var.
pubescens Regel et
Tiling
Spiraea aquilegifolia
Rutaceae
Haplophyllum
dauricum
PF
X
27.3170.35
63.472.9
ND
Saxifragaceae
Ribes diacanthum
S
M
26.7570.86
62.473.2
ND
Scrophulariaceae
Odontites serotina
Pedicularis striata
A
PF
M
M
28.0470.64
28.0770.27
74.572.4
68.371.3
152767
158721
Ulmaceae
Ulmus pumila
T
XM
26.9970.39
54.371.5
365793
Umbelliferae
Cicuta virosa
PF
HM
27.7770.27
77.670.4
101717
T, S, SS, PF, PG, and A represent trees, shrubs, sub-shrubs, perennial forbs, perennial grasses and annuals,
respectively.
X, MX, XM, M, HM, and H represent xerophytes, mesoxerophytes, xeromesophytes, mesophytes,
hygromesophytes and hygrophytes, respectively.
The classifications of life form and water ecological group of all of species in the table were obtained from the
Flora of Inner Mongolia (Editorial Committee of Flora of Inner Mongolia, 1994).
d13C value and LWC values are expressed as mean7SD and those of proline as mean7SE, n ¼ 3–34. ND:
not determined.
Kochia prostrate and Cleistogenes polyphylla are C4 species and the others are C3 species.
2.4. Statistic analysis
Statistical analysis was performed using SPSS 10.0 software (SPSS Inc.). Multiple
comparisons were made on the mean d13C values, LWC and proline content of C3 plants
and SWC among different communities. One-way ANOVA (Duncan test) was performed
to determine whether means were significantly different at the Po0.05 level. The same
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method was also used to separate the differences in SWC, soil nitrogen content, canopy
height, community density, and aboveground biomass of different plots. Correlation
analysis was performed to detect any relationship between mean d13C values, LWC and
proline content of C3 plants and SWC in different communities. The same analyses also
were used to determine the relationship between d13C values and proline content of C3
plants with the occurrence frequency and relative biomass of each species, respectively.
Because lots of species with lower occurrence frequency and relative biomass gathered
together, and logarithmic function transforms of occurrence frequency and relative
biomass were made to show all of data more clearly.
3. Results
3.1. Carbon isotope compositions of major plant species in the Xilin River Basin
A total of 372 plant samples representing 17 families, 43 genera and 52 species were
measured for stable carbon isotopic composition (d13C) (Table 3). We found that most of
these species were C3 plants based on their d13C values, which ranged from 29.8% to
25.0% (mean –27.1%). Out of the 52 species sampled, only two were C4 plants,
Cleistogenes squarrosa (a perennial grass) and Kochia prostrata (a sub-shrub), with a mean
d13C of –15.0%. Significantly positive correlation was found between plant d13C value and
natural logarithm of occurrence frequency for all of C3 plant species (r ¼ 0.528,
Po0.0001) (Fig. 1a). A similar pattern was found between plant d13C values and the
relative biomass of different C3 plant species (r ¼ 0.610, P ¼ 0.002) (Fig. 1b).
Average d13C values of all C3 plants were pooled for each plot to allow comparisons
between soil moisture regimes. We found that significant difference existed in average d13C
values of C3 plants among different community types along soil moisture gradient
(Fig. 2a). Correlation analysis showed that average d13C values of C3 plants increased with
decreasing soil water content (y ¼ 0.412x26.27, r ¼ 0.814, P ¼ 0.014, n ¼ 8).
3.2. Leaf water content (LWC) of major plant species in the Xilin River Basin
There were apparent differences in LWC of major plant species in the Xilin River Basin
(Table 3) and mean LWC of plants changed significantly along the soil moisture gradient
(Fig. 2b). From swamp, saline meadow, meadow steppe to typical steppe, mean LWC of
plants decreased significantly. However, higher mean LWC was found in the restoring
steppe, degraded steppe and sand dunes, which might be due to the increase of shrubs and
sub-shrubs. A significant negative correlation existed between LWC and d13C values of
different C3 plant species. That is, d13C values of C3 plants increased with decreasing in
LWC (Po0.001, n ¼ 42) (Fig. 3). Significantly positive correlation was also found between
mean LWC and SWC in different plots (Fig. 4).
3.3. Foliar free proline content of major plant species in the Xilin River Basin
Foliar free proline content of 45 species was determined and there was a large range of
variation in proline content among species (Table 3). Correlative analysis showed that
foliar free proline content exponentially increased with an increase in the occurrence
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y = 0.4938x- 28.095
a
-23
R2 = 0.2787,P<0.0001, n = 43
-24
-25
-26
δ13C values of C3 species (‰)
-27
-28
-29
-30
0
2
1
4
3
5
Ln (Occurrence frequency)
y = 0.2703x- 26.645
b
-23
-24
R2
= 0.3723, P = 0.002, n = 44
-25
-26
-27
-28
-29
-30
-8
-10
-6
-4
-2
0
2
4
Ln (Relative biomass)
13
Fig. 1. Relationships between d C values (mean7SD) and (a) distribution frequency, and (b) relative biomass of
C3 species in the Xilin River Basin.
frequency and relative biomass of plants (Po0.01). Thus, the species with a wider
distribution and larger aboveground biomass had higher free proline content (Fig. 5).
Mean proline content of plants was significantly different among different plots
(Fig. 2c). With decreasing soil water availability, mean proline content of plants
significantly increased, with the exception of an unexpected lower content in the degraded
steppe species (plot 7). There were significant exponential negative correlations between
SWC and proline content of plants along a soil moisture gradient (Po0.05) (Fig. 4).
A significant exponential relationship was also found between the mean proline content
and LWC of plants in different plots (r ¼ 0.79, P ¼ 0.02, n ¼ 8).
4. Discussion
4.1. d13 C values and WUE of major plant species in the Xilin River Basin
C3 and C4 plants have distinctly isotopic composition because of the difference in their
primary carboxylating enzymes (Rubisco and PEP carboxylases for C3 and C4 plants,
respectively). The d13C values of C3 plants are approximately –28%, whereas those of C4
plants are approximately 14% (Farquhar et al., 1989; O’Leary, 1988). It is clear that all of
the communities that we examined in Xilin River Basin were overwhelmingly dominated by
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a
Average δ13C values (‰)
-23
-24
a
abc
-25
abc
abc
bc
ab
c
-26
-27
d
-28
-29
-30
1
2
3
4
5
e
de
4
5
6
7
8
bcd
bc
cde
6
7
8
b
100
a
b
LWC (%)
80
bcd
60
40
20
0
1
2
3
c
Proline content (µg g-1 DW)
600
a
500
ab
ab
400
bc
300
200
ab
b
b
c
100
0
1
2
3
4
5
6
7
8
Plot No.
Fig. 2. Average d13C values (a), LWC (b) and foliar proline content (c) of dominant plant species in eight
communities of the Xilin River Basin. Error bars are 1 SD. Different letters represent significant differences
among the means (Po0.05, ANOVA Duncan test).
C3 species and only two species had C4 photosynthetic pathways. These results were
consistent with those of other studies conducted in the Inner Mongolian steppe (Ni, 2003; Su
et al., 2000; Tieszen and Song, 1990) and in other similar geographical regions (Pyankov
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Foliar δ13C values (‰)
-23
y = -0.0527x- 23.482
2
R = 0.2831, P=0.0003, n=42
-24
-25
-26
-27
-28
-29
-30
30
40
50
60
70
80
90
100
LWC (%)
13
Fig. 3. Relationship between LWC and d C values of dominant plant species in the Xilin River Basin.
Proline
LWC
LWC
Proline
80
500
y = 49.936x0.0793
400
R2 =
300
0.6714, P=0.013, n=8
y = 690.67x-0.4206
200
70
R2 = 0.774, P=0.004, n=8
60
LWC (%)
Proline content (µg g-1 DW)
600
50
100
0
0
50
100
150
40
200
SWC (%)
Fig. 4. Relationships between SWC and mean proline content, between SWC and mean LWC of plants. Each
point represents an average by plot or community. Error bars represent 1SE.
et al., 2000). For example, Pyankov et al. (2000) found the percentage of C4 species in the
total Mongolian flora was only about 3.5% with a strong dominance by Chenopodiaceae.
The 13C natural abundance of C3 plants also provides a useful measure of integrated
carbon/water balance in plants over a longer time interval, and is generally well correlated
with plant WUE (Farquhar et al., 1982, 1989). A relatively wide variation existed in d13C
values of C3 plants, ranging from 29.8% to 25.0%, which indicated that there were
significant differences in WUE of C3 species in the Xilin River Basin. Our results were
consistent with a former study in the same area which showed that the d13C values of
major C3 plants ranged from 28.4% to 24.8% (mean 26.35%) (Tieszen and Song,
1990). Similar change range of d13C values was also reported in a study of desert plants
along a soil moisture gradient (Ehleringer and Cooper, 1988). Since a 1% change in d13C is
equivalent to approximately a 15 mmol mol1 difference in Ci (Ehleringer and Cooper,
1988), a range of about 5% (from 29.8% to 25.0%) among the C3 species we analyzed
would correspond to a difference of 75 mmol mol1 in average Ci. A decrease in the
operational Ci value indicated an increase in the stomatal diffusion limitation to
photosynthesis and also an increase in leaf WUE.
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a
1400
y = 108.42x0.2314
1200
2
R = 0.1726, P = 0.0077, n = 40
1000
800
600
Proline content (µg g-1 DW)
400
200
0
0
20
40
60
80
100
Occurrence frequency (%)
b
1400
y = 205.87x0.1084
1200
2
R = 0.1723, P = 0.0086, n = 39
1000
800
600
400
200
0
0
2
4
6
8
10
12
Relative biomass (%)
Fig. 5. Relationships between proline content (mean7SE) and (a) occurence frequency, and (b) relative biomass
of dominant plant species in the Xilin River Basin.
The Xilin River Basin is typical semi-arid grassland with an annual average rainfall of
about 350 mm. In such area, water availability is a limiting factor for plant growth
(Johnson and Asay, 1993). The variation in the competitive ability to take up water among
co-existing species could largely determine species composition of a community (Vilà and
Sardans, 1999). Plants that use water efficiently may have a competitive advantage, which
allows them to dominate in vegetation biomass (Ehleringer, 1993; Tsialtas et al., 2001). In
our study, the C3 species’ performances (including distribution frequency and biomass)
were positively correlated with d13C values, and therefore positively related with potential
WUE (Fig. 1). With decreasing soil water availability, C3 plants showed significantly more
positive d13C values and more efficient water use strategies in different community types.
Therefore, plants may compete effectively by increasing their potential WUE when water is
scarce, and the relative abundance and biomass of a particular species in a community are
regulated by the species’ ability to utilize water resources more efficiently.
Ehleringer and Cooper (1988) found that average carbon isotope ratio increased along a
soil moisture gradient from relatively wetter wash to a relatively drier slope. Stewart et al.
(1995) reported a linear increase in community-averaged carbon isotope composition with
decreasing annual rainfall in southeastern Queensland, Australia. In our study, large
variations in the mean 13C natural abundance existed among different community types.
Plants of the typical steppes had the highest d13C values and those of marsh meadow the
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lowest. Plant d13C value gradually increased with decreasing SWC, indicated that WUE
increased as soil water availability decreased. Plant communities overall had higher WUE
and employed more conservative water-use strategies to allow plant growth, survival and
maintenance in dryer habitats; while in wetter habitats, lower WUE and prodigal wateruse patterns enabled communities to attain higher productivity.
4.2. Variations in LWC and proline content of major plant species in the Xilin River Basin
Measurement of LWC allowed estimation of the degree of water shortage within each
plant. The LWC of major species in the Xilin River Basin was significantly different and
significantly negatively related to d13C values. That is, the species with lower LWC had
higher WUE and showed more conservative water use pattern. Along a soil water gradient,
mean LWC of plants decreased with decreasing SWC, and an obvious negative correlation
was also found between mean LWC and mean d13C values of C3 plants in habitats with
different water availability.
As reported by Hsiao (1973), leaf water deficit is mainly caused by soil water depletion,
which in turn affects many physiological processes, and eventually determines the biomass
production or survivorship of plants. Many of these changes represent adaptive responses
by which plants cope with water stress. The survival strategies of plants under waterlimited environment include tolerance and avoidance of tissue water stress. Generally,
stress avoidance involves stomatal closure, hydraulic conductance and root growth
patterns. Stress tolerance usually includes osmotic adjustment and changes in tissue
elasticity (Jones et al., 1981). Osmotic adjustment is the lowering of osmotic potential by
net solute accumulation in response to dehydration. It assists the maintenance of turgor at
lower water potentials, and is considered as a beneficial drought tolerance mechanism
(Bajji et al., 2001; Iannucci et al., 2002). Proline is an important osmoticum in higher
plants. Since the accumulation of free proline in water stressed leaves was first described by
Kemble and Macpherson (1954) in perennial ryegrass, this phenomenon has been
subsequently observed in many plants including crops, forage grasses and desert species
(Bajji et al., 2001; Gao et al., 1999). In our study, proline was present in all the plant
species examined and its content ranged from 1054 to 64 mg g1 DW. Higher proline levels
were associated with species of wider distribution range and higher biomass in the Xilin
River Basin (Po0.01). Our results indicated that proline exists in most steppe species
and it might be a determinant of their competitive ability in the semi-arid steppe in the
Xilin River Basin. A survey of plants growing in the southern Namib Desert indicated
that 61 species out of a total of 95 species in 26 families contained detectable amounts of
proline (Treichel et al., 1984). In Australia, Naidu et al. (2000) analyzed 125 Melaleuca
species in different habitats and found proline accumulation in all of the species.
Many studies have shown that the accumulation of proline could protect plant
macromolecules (Delauney and Verma, 1993; Xiong and Zhu, 2002; Xu et al., 2002)
and increase plant survival in stressful situations (Ain-Lhout et al., 2001; Chang and
Lee, 1999; Naidu et al., 2000), and thus may play an important role in the ecological
distribution of species.
In our study, greater accumulation of proline was found in plants living in the driest
habitats (mean 219 mg g1 DW) than in the wettest habitats (mean 45 mg g1 DW), and the
mean proline concentration of plants increased exponentially with declining mean LWC of
plants growing in different soil moisture conditions. This suggested that limited water
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25
availability in the soil could result in plant water deficit, and further lead to differentiating
proline levels. Treichel et al. (1984) studied the distribution of proline in the vegetation of
the Namib Desert over seven years. They observed that long-term proline accumulation
was caused by water shortage and plant water deficit but was fully reversible when the
water availability increased again after an abundant rainfall. In severely drought years,
proline of surviving species increased with increasing drought and decreasing plant water
content. Thus, it seemed likely that proline was involved in drought protection. Barker
et al. (1993) reported that proline accumulated exponentially in leaves of five forage grasses
as soil water content decreased during each dry-down period. Gao et al. (1999) showed
there was obvious accumulation of proline in Lolium perenne with decreasing SWC and
LWC. Those studies and our results both indicated that the proline content of plants could
clearly reflect the water availability in the soil. Water supply, and consequently, plant
water deficit is the main factor controlling the accumulation of proline. Proline is a
osmotically active compound and its accumulation would compensate further loss of cell
turgor induced by severe water stress. In addition, proline also plays a role in the
protection of enzymes, scavenging hydroxyl radicals and stabilizing the cell membrane
during water stress (Arndt et al., 2001; Pedrol et al., 2000; Rudolph et al., 1986; Solomon
et al., 1994). This allows the plant to take up more soil water and maintain turgor and cell
function for a longer time under drought conditions. In our study area, summer drought is
often accompanied by high temperature and strong irradiance (about 2000 mmol m2 s1),
plants tend to close stomata to avoid water loss by transpiration, and therefore CO2
uptake is prevented. Under these conditions it has been proposed that proline can act as an
electron acceptor, avoiding damage by photoinhibition (Ain-Lhout et al., 2001; Arndt
et al., 2001; Smirnoff et al., 1985).
There are some opposing viewpoints on the relationship between proline and WUE.
Some research has suggested that the accumulation of proline could enhance WUE of
plants under water stress condition (Karyudi and Fletcher, 1999; Naidu et al., 2000).
However, other studies have reported that the level of proline had no obvious effects on
WUE (Ludlow et al., 1990; McCree and Richardson, 1987; Morgan et al., 1986;
Santamaria et al., 1990). Our results showed a weakly positive correlation between proline
and WUE (r ¼ 0.25, P ¼ 0.10, n ¼ 43), indicating that proline did not directly improve the
water use of plants, but rather, it might have an indirectly positive effects on WUE by
controlling stomatal conductance, maintaining leaf area and facilitating water absorption
(Pedrol et al., 2000; Xiong and Zhu, 2002).
In conclusion, inter- and intra-species variations in WUE might significantly influence
the outcome of competitive interactions and play a large role in determining species
composition of the community in the Xilin River Basin, Inner Mongolia. Proline
accumulation in leaves might strengthen competitive ability of plants growing drought
habitats by enhancing their osmosis-regulating ability and drought tolerance.
Acknowledgments
We thank Dr. Amy Concilio for her helpful and intensive English language revision of
this manuscript. This research was supported by the ‘‘100 Talents’’ project and a
Knowledge Innovation Project (KSCX2-SW-127) of the Chinese Academy of Sciences to
G. Lin, and the projects sponsored by the National Natural Science Foundation of China
(30330150 and 90511001).
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