Journal of Applied Ecology 2016, 53, 1787–1799
doi: 10.1111/1365-2664.12730
Can intercropping with the world’s three major
beverage plants help improve the water use of rubber
trees?
Junen Wu1,2, Wenjie Liu1* and Chunfeng Chen1,2
1
Key Laboratory of Tropical Forest Ecology, Xishuangbanna Tropical Botanical Garden, Chinese Academy of
Sciences, Menglun, Yunnan 666303, China; and 2University of Chinese Academy of Sciences, Beijing 100049, China
Summary
1. The dramatic expansion of rubber plantations in mainland South-East Asia and south-
west China has caused many eco-environmental problems, especially negative hydrological
consequences. These problems have gradually worsened and pose formidable threats to rubber agriculture, especially in the light of increasingly frequent extreme weather events.
Although rubber-based agroforestry systems are regarded as the best solution for improving
the sustainability of rubber agriculture and environmental conservation, plant water use and
related interactions have rarely been examined in such systems.
2. We primarily used stable isotope (dD, d18O and d13C) methods to test whether intercropping could improve the water use and extreme weather tolerance (extreme cold and drought
in our study) of rubber trees in three types of promising agroforestry systems (i.e. rubber with
tea, coffee and cocoa) in Xishuangbanna, China.
3. We found that the rubber tree is a drought-avoidance plant with strong plasticity with
respect to water uptake. This characteristic is reflected by its ability to cope with serious seasonal drought, allowing it to avoid interspecific competition for water. The rubber trees
showed wasteful water behaviour unless they were intercropped with tea or coffee. However,
these intercropped species exhibited drought-tolerance strategies and maintained lower water
use efficiencies to strengthen their competitive capacity for surface soil water. The stable d13C
values of the intercrop leaves indicated that all the agroforestry systems have stable internal
microclimatic environments or higher resistance.
4. Synthesis and applications. This study suggests that interspecific competition for water can
enhance the water use efficiency of drought-avoidance plants (i.e. rubber trees) and lead to
complementarity between the root distributions of plants in rubber agroforestry systems (i.e.
rubber with tea, coffee and cocoa). All agroforestry systems have higher resistance, but tea
was the most suitable intercrop in terms of water use because the interspecific competition for
water was moderate and the agroforestry system retained much more soil water and improved
the water use efficiency of the rubber tree. Considering the root characteristics of the tea
trees, we suggest that the crops selected for intercropping with rubber trees should have a
relatively fixed water use pattern, short lateral roots and a moderate amount of fine roots that
overlap with the roots of the rubber trees in the shallow soil layer.
Key-words: agroforestry system, cold event, intercropping, interspecific competition, plant
water use, rubber plantations, seasonal drought, South-East Asia, stable isotope, water use
efficiency
Introduction
Rubber trees (Hevea brasiliensis) have great economic and
social value throughout South-East Asia. Though they are
*Correspondence author. E-mail: [email protected]
native to the tropical rain forest of the Amazon Basin,
approximately 97% of the global supply of natural rubber
today comes from South-East Asia (Fox et al. 2014). As
demand for natural rubber increases due to the development of tyre manufacturing, rubber plantations are rapidly
expanding at the expense of natural South-East Asian
© 2016 The Authors. Journal of Applied Ecology © 2016 British Ecological Society
1788 J. Wu, W. Liu & C. Chen
ecosystems (Xu 2011). Indeed, rubber has generated considerable prosperity. Even the Golden Triangle, the border
region of Thailand, Laos and Myanmar, long infamous for
opium poppy production, has become known for rubber
cultivation instead (Mann 2009). Farmers, especially smallholders who produce 80% of the global supply of latex,
have extended rubber trees to higher latitudes and altitudes
(Fox et al. 2014). By 2050, rubber plantations are predicted
to more than double or triple in land-use area, largely at
the expense of evergreen forests (Ziegler, Fox & Xu 2009;
Fox et al. 2014). In Yunnan Province in China, rubber
monoculture has expanded to cover more than 400 000 ha
in 2009, or 20% of the Xishuangbanna prefecture (Li et al.
2008; Qiu 2010). Rubber trees have become an agricultural
juggernaut (Ziegler, Fox & Xu 2009) that dominates both
the economy and land of this region.
Relative to primary tropical forests, rubber monocultures exhibit significantly low biodiversity (Warren-Thomas, Dolman & Edwards 2015), low total biomass carbon
stocks (Ziegler, Fox & Xu 2009) and negative hydrological consequences (Liu et al. 2007; Fox et al. 2014). Additionally, current planting patterns, especially those at high
latitudes and elevations, are also bad for rubber quality
and yield. Due to their low genetic diversity, rubber trees
are also vulnerable to plant diseases (e.g. powdery mildew
and leaf blight), pests and environmental conditions
(Mann 2009). Unfortunately, increasingly frequent
extreme weather events (e.g. drought in the dry season,
low temperatures in the foggy cool season and gales) since
the 1960s (Zhang 1986) have posed a growing threat to
rubber agriculture. For example, a devastating low-temperature event occurred in 1974 that destroyed nearly half
of the rubber plantations in Xishuangbanna (Feng 2007).
The outlook for rubber agriculture appears to have
become unfavourable. However, rubber agroforestry systems, which combine agricultural and forestry techniques
to create more diverse, productive, healthy and sustainable land-use systems, provide promising solutions (Feng
2007; Fox et al. 2014). In addition, multilayered structures
of agroforestry, which can reduce wind speed and maintain the stability of internal microclimates, are strong
assets for extreme weather adaption. Moreover, these systems can facilitate the diversification of agriculture and
promote faster returns on investment, as rubber prices are
notoriously volatile (Snoeck et al. 2013). Thus, the resistance and resilience ability after a disturbance (e.g. natural disaster or market failure) is improved by agroforestry
systems because of diversified temporal and spatial management options (Verchot et al. 2007).
However, the associations of water use between rubber
tree and other intercropped species are poorly documented
(Ziegler, Fox & Xu 2009). As far as we know, rubber trees
have a strong ability to absorb water because of their large
xylem vessels (Ayutthaya et al. 2011). They are referred to
as ‘water pumps’ because they can deplete water sources at
a basin scale (Tan et al. 2011). Although the annual mean
latex yield of rubber trees in our study area was
approximately 1500 kg ha1 (Liu, Li & Duan 1997), their
roots absorb considerable quantities of water – roughly
5000 kg ha1 annually to replace the lost latex (Mann
2009). And soil water storage during the rainy season is not
sufficient to maintain high evapotranspiration rates in the
rubber monoculture plantations, resulting in zero flow and
water shortages during the dry season (Tan et al. 2011).
Decades of rubber cultivation in Xishuangbanna have
reduced streamflow and dried up wells in many villages
(Qiu 2009). Additionally, the soil moisture in the rubber
monoculture plantations approaches the permanent wilting
point during the dry season, leading to potentially large
effects on the growth and survival of the rubber trees
(Vogel, Wang & Huang 1995). Accordingly, direct observation of plant water use patterns and strategies in rubber
agroforestry and related improvement is currently and
urgently needed (Qiu 2009; Ziegler, Fox & Xu 2009;
Guardiola-Claramonte et al. 2010).
‘Big-leaf’ tea (Camellia sinensis var. assamica) is the most
famous ancient product in Yunnan Province (Mann 2009).
The other two of the three major beverage crops in the
world are Arabica coffee (Coffea arabica) and cocoa (Theobroma cacao). All three have previously been demonstrated
as optimal cash crops for intercropping with rubber trees
based on both ecological and economic profitability (Feng
2007; Righi et al. 2008; Snoeck et al. 2013; Xiao et al.
2014). To understand how rubber trees benefit from
intercropping, especially the water use benefits, we selected
the following three promising agroforestry systems as
observation groups: H. brasiliensis–C. sinensis agroforestry
system (CSAs), H. brasiliensis–C. arabica agroforestry system (CAAs) and H. brasiliensis–T. cacao agroforestry
system (TCAs). One rubber monoculture (Rm) was monitored as a control group. We measured the dD and d18O
values of water in the soil and plant xylem to trace plant
water sources. We also measured leaf d13C values, shoot
water potential and the soil water content (SWC) over the
course of the 2013–2014 rainy–dry season cycle to compare
the interspecific and intraspecific differences in water use
efficiency (WUE), plant ecophysiological functions and
moisture conservation abilities at all sites. We hypothesized
that (i) different species in rubber agroforestry systems
extract water from different soil layers to reduce interspecific competition for water; (ii) such competition decreases
soil water availability, thereby improving the WUE of the
rubber trees; and (iii) rubber agroforestry systems have
higher ecological resistance (i.e. the capacity to weather a
disturbance without loss) and maintain substantially more
soil water than rubber monocultures because of the various
functions of the understorey (i.e. the intercrops).
Materials and methods
STUDY SITE
The study sites are located in the Xishuangbanna Tropical Botanical Garden (XTBG; 21°550 39″N, 101°150 55″E) in Yunnan,
© 2016 The Authors. Journal of Applied Ecology © 2016 British Ecological Society, Journal of Applied Ecology, 53, 1787–1799
Plant water use in rubber agroforestry
south-western China. Local climate is dominated by tropical
southern monsoons from the Indian Ocean between May and
October and by subtropical jet streams between November and
April (Zhang 1988). Three seasons are apparent in this area:
rainy season, foggy cool season and hot dry season (Fig. 1).
Rainfall during the rainy season (mean temperature 25 °C)
accounts for approximately 84% of the annual total. The foggy
cool season is the coldest period, with dense fog in the morning
and night. The hot dry season is a transitional period, with less
rainfall and higher air temperature (exceeding 38 °C). The foggy
cool and hot dry seasons are collectively referred to as the dry
season owing to the lack of rainfall.
Observations were conducted in a typical catchment (193 ha)
covered with 25-year-old rubber trees (clone PB86) arranged in
double rows spaced 2 m apart. Within the rows, the trees are
spaced 45 m apart, and each set of double rows were separated
by an 18-m-wide gap (Fig. S1, Supporting information). The
mean diameters at breast height of the rubber trees in Rm, CSAs,
CAAs and TCAs were 7042 1162 m, 8585 1667 m,
8891 734 m and 9219 1594 m (mean SD), respectively.
With the exception of Rm, the rubber tree diameters at breast
height of the other sites exhibit no significant differences.
Four planting patterns were selected for this study: Rm, CSAs,
CAAs and TCAs. The intercrops were planted in the 18-m-wide
gaps between rows of rubber trees in 2005. In CSAs, the tea trees
reached heights of approximately 2 m and were planted in seven
1789
rows, each spaced 2 m apart, with 05 m between the plants in
each row. In CAAs, the coffee trees reached heights of approximately 22 m and were planted in five rows, with rows and plants
spaced 25 m apart. In TCAs, the cocoa trees reached heights of
approximately 23 m and were planted in four rows, each 4 m
apart and containing plants spaced 3 m apart. The planting
strategies of the intercrops were based on field surveys and were
designed based on planting experience and on the suitability of
the terrain for the growth of the intercrops (Feng 2007). All the
selected sites had a common north-facing slope with an aspect
ranging from 85° to 94°. The distances among the sites were all
less than 300 m and the differences in altitude were negligible.
The rubber trees were tapped every other day from the end of
March to mid-November, and the annual mean latex yield was
approximately 1500 kg ha1 (Liu, Li & Duan 1997).
SAMPLING AND MEASURING METHODS
Rainwater samples were collected from a rain gauge immediately
after rain ceased in the dry season and were collected weekly in
the early morning when rain fell overnight in the rainy season.
Rainwater samples were stored in 2 mL screw-cap plastic vials,
wrapped in parafilm and frozen until analysis. In total, 25 rain
samples were collected during the study period.
Plant and soil samples were collected separately in the rainy
season (August 24, 2013), the foggy cool season (November 23,
Fs
Fr
Rainy
Ds
Ls Lf Le
Foggy cool
Hot dry
Fp
Fs
Rainy
MP
His-MP
Month
2013
2014
10
δ value (‰)
Fig. 1. Monthly precipitation distribution
and monthly mean temperature during the
investigation period (historical data from
Xishuangbanna Station for Tropical Rain
Forest Ecosystem Studies). The first stippled bar at the top of the panel indicates
the phenophases for rubber trees: Fs represents fruit setting; Fr, fruit ripening; Ds,
dormant stage; Ls, leaf shedding; Lf, leaf
flushing; Le, leaf expansion; and Fp, flowering phase. The second stippled bar indicates the season. MT represents monthly
mean temperature, and His-MT represents
historical monthly mean temperature from
1969 to 2014. MP represents monthly precipitation, and His-MP represents historical monthly precipitation from 1969 to
2014. The black arrows indicate sampling
dates.
Temperature (°C)
Precipitation (mm)
MT
His-MT
Rain water δD
Rain water δ18O
Rain water d-excess
© 2016 The Authors. Journal of Applied Ecology © 2016 British Ecological Society, Journal of Applied Ecology, 53, 1787–1799
1790 J. Wu, W. Liu & C. Chen
2013), the late foggy cool season (January 19, 2014), the hot dry
season (March 10, 2014) and the early rainy season (May 5,
2014). At midday on each sampling date, plant xylem samples
were obtained by extracting small cylinders of wood from three
tree trunks with an increment borer for rubber trees and by cutting suberized mature stem segments from three trees for the
intercrop trees (i.e. three plant xylem samples were collected from
each species at each site). Then, they were immediately placed in
10-mL screw-cap glass vials, sealed with parafilm and frozen until
water extraction. Because the feeder roots of the rubber trees are
mostly found in the upper 30 cm of the soil and the density of
the roots varied little among the inter-rows in mature plantations
(Priyadarshan 2011), soil samples were collected from six
unequally spaced soil layers (i.e. depths of 0–5, 5–15, 15–30, 30–
50, 50–80 and 80–110 cm) via a hand-operated bucket auger
(4 cm in diameter) at three randomly chosen locations at each
site. Each soil sample was then divided into two parts. One was
collected in LDPE zip-lock bags and then stored to measure the
gravimetric SWC via oven-drying method. The other was stored
in 10-mL screw-cap glass vials to determine the soil water isotopic composition. Xylem and soil water samples were extracted
using a cryogenic vacuum distillation system.
Predawn and midday leaf water potentials (i.e. Ψpd and Ψmd)
were measured using a pump-up pressure chamber (Pump-Up;
PMS, Albany, OR, USA). In situ measurements were performed
after cutting 3–5 shoots with leaves from three randomly sampled
trees (for each species at each site) between 4:00 and 6:30 for Ψpd
and between 12:30 and 14:30 for Ψmd. We cut the leaves of the
rubber trees from the sunny slope of the canopy edge using tree
pruners (10 m) because of the remarkable height of the rubber
trees (15–25 m). For the intercropped plants, we cut the leaves
from the canopy top using normal pruners. We collected mature
leaves when we measured the Ψpd. Only leaves with a healthy
appearance were collected, avoiding yellow-to-brownish leaves.
Three plant leaf samples were collected for each species at each
site and were dried to a constant mass and homogenized to a
fine powder with an 80-mesh sieve to determine their d13C
compositions.
The dD and d18O values of the water samples and the d13C values of the leaf samples were measured using a stable isotope ratio
mass spectrometer (IsoPrime100; Isoprime, Stockport, UK) at the
Central Laboratory, XTBG. Each isotope ratio is expressed in
parts per thousand relative to V-SMOW for D and 18O and relative to V-PDB for 13C. The d-excess was calculated using the following formula: d-excess = dD8d18O (Dansgaard 1964).
CALCULATIONS AND STATISTICAL ANALYSES
Differences in the xylem water isotopic composition, leaf d13C
composition and water potential of rubber trees among all the
sites were analysed using general linear models (GLMs) with ‘season’ and ‘site’ as fixed effects. Similarly, the differences between
rubber trees and the intercrops at the same site were analysed by
GLMs with ‘season’ and ‘species’ as fixed effects. To analyse the
differences among the seasons at each species, the GLMs were
also run with ‘season’ as a fixed effect separately for each site
and species. Differences among seasons, sites and water sources
(soil layers) in the soil water isotopic composition and SWC were
analysed by residual maximum likelihood (REML) models with
‘season’, ‘site’ and ‘soil layer’, respectively, as fixed factors. All
the REML models included ‘individual’ as a random factor to
account for spatial autocorrelation and repeated-measures effects.
When the results were significant, differences among groups were
compared using a post hoc Tukey’s test. When the interaction
effect was significant, a simple-effects analysis was performed. All
data in our study were normally distributed (as assessed by normal quantile plots with Lilliefors 95% confidence bounds).
Homogeneity of variances was checked using Levene’s test.
The relative water-absorbing proportion of each water source
was estimated using the Bayesian mixing model MIXSIAR (Parnell
et al. 2013). This model can incorporate uncertainty in source
means/variances, and the ranges of solutions can be interpreted
as probabilities. In this study, we estimated the water-absorbing
proportion (i.e. the water uptake from different soil layers) for
each plant species at each site with two isotopic values (dD and
d18O), one fixed effect (season), an individual effect and zero discrimination. The MCMC (i.e. Markov chain Monte Carlo) run
length was set as ‘long’ (i.e. ‘Chains’ = 3, ‘Chain Length’ =
300 000, ‘Burn-in’ = 200 000, ‘Thin’ = 100 and ‘calcDIC’ =
TRUE). All statistical analyses were performed in R 3.2.0 (R
Core Team 2014).
For WUE, many studies (Farquhar, Ehleringer & Hubick
1989; Ehleringer, Roden & Dawson 2013) have noted a strong
relationship between d13C values and WUE, especially among C3
photosynthesis plants. A particular advantage of using d13C to
estimate WUE is its long integration time. Carbon isotope analysis provides an estimate of WUE integrated over the period (i.e.
neglects the leaf-to-air vapour difference, which is not always
constant) during which the carbon in the plant was fixed, often
weeks to months, and can do so for large numbers of independent samples (Marshall, Brooks & Lajtha 2007). Since the d13C
value of atmospheric CO2 is nearly constant (8&) within a
given year for field-grown plants (Farquhar, Ehleringer & Hubick
1989), such as the four plantations without closed canopy in our
study (Fig. S1), the gradients in atmospheric CO2 concentrations
under the canopy are normally very small and could be safely
ignored. Therefore, we can compare the long-term WUE of the
C3 photosynthesis plants in our study by comparing their leaf
d13C values.
Results
PRECIPITATION AND TEMPERATURE
The total precipitation during the study was 15945 mm,
exceeding the long-term mean (14543 mm; Fig. 1) but
showing no significant difference (t = 0472, P = 0646).
However, the monthly mean temperature significantly
exceeded the long-term mean (t = 2340, P = 0039). A
sustained low-temperature event (lasting for more than a
week with the minimum temperature falling to 59 °C,
which was the lowest level since 2000) and strong storms
occurred in December 2013. Subsequently, rubber tree
foot disease (i.e. a cold injury to the basal trunk of rubber
trees; Fig. S2) was found in Rm. This was followed by a
dry spell of more than 2 months without any rainfall. The
rainwater dD, d18O and d-excess values varied seasonally
(with dD values ranging from 10742& to 225&, d18O
values ranging from 1459& to 126& and d-excess
values ranging from 595& to 1695&). In this study, precipitation and rainwater isotopic values were significantly
© 2016 The Authors. Journal of Applied Ecology © 2016 British Ecological Society, Journal of Applied Ecology, 53, 1787–1799
Plant water use in rubber agroforestry
1791
correlated (the correlation coefficients were 0802 for dD
and 0803 for d18O; P < 0001).
in TCAs, the soil layers at 15–80 cm depth did not differ
significantly.
SOIL WATER CONTENT
ISOTOPIC COMPOSITION OF SOIL WATER AND PLANT
In general, the SWC significantly differed among all the
sites (F = 40785, P < 0001). The order of sites from high
to low was as follows: CSAs, CAAs, Rm and TCAs
(Fig. 2). The SWC also exhibited pronounced seasonal
variation (F = 34498, P < 0001), with lower and higher
values observed in the dry and wet seasons, respectively.
The SWC decreased gradually from surface to deep soil
layers, but each site differed in performance. In Rm and
CAAs, the soil layer SWC did not significantly differ
across the 30-cm-depth boundary; in CSAs, the soil layers
at 5–50 cm depth did not differ significantly in SWC; and
(a) Rm
XYLEM WATER
The soil water dD and d18O values differed significantly
among seasons, sites and depths (P < 001; see Table 1).
TCAs exhibited significantly low isotopic values for soil
water (a = 005), while the other sites showed small
differences. The soil water dD and d18O values
decreased gradually from the surface to the deeper soil
layers, and for all sites, the soil layers at 15–50 cm
depth and 50–110 cm depth showed inconspicuous differences (P > 005), but each site behaved differently
(Fig. 3).
(b) CSAs
50
50
40
SWC (%)
SWC (%)
40
30
20
10
a
0
Aug
2013
Nov
b
b
Jan
b
Mar
Month
a
May
2014
c
20
a 0–5 cm
a 5–15 cm
ab 15–30 cm
bc 30–50 cm
bc 50–80 cm
10
b
b
0
Aug
2013
80–110 cm
Nov
Depth
a 0–5 cm
5–15 cm
15–30 cm
b 30–50 cm
c 50–80 cm
d
80–110 cm
b
b
Jan
b
b
Mar
a
May
Month
2014
(c) CAAs
Depth
(d) TCAs
50
50
40
SWC (%)
40
SWC (%)
30
30
20
a
10
0–5 cm
5–15 cm
a
15–30 cm
b 30–50 cm
b
50–80 cm
b
80–110 cm
a
a
0
Aug
2013
Nov
a
a
Jan
Month
b
Mar
a
May
2014
Depth
30
20
10
a
a
0
Aug
2013
Nov
ab 0–5 cm
5–15 cm
15–30 cm
b 30–50 cm
b 50–80 cm
c 80–110 cm
b
b
Jan
Month
b
Mar
c
a
May
2014
Depth
Fig. 2. Soil water content (SWC) of each soil layer and seasonal variation for (a) rubber monoculture (Rm), (b) Hevea brasiliensis–
Camellia sinensis agroforestry systems (CSAs), (c) Hevea brasiliensis–Coffea arabica agroforestry systems (CAAs) and (d) Hevea brasiliensis–Theobroma cacao agroforestry systems (TCAs). Different lowercase letters indicate significant differences among seasons in the isotopic composition after post hoc Tukey’s tests (a = 005).
© 2016 The Authors. Journal of Applied Ecology © 2016 British Ecological Society, Journal of Applied Ecology, 53, 1787–1799
1792 J. Wu, W. Liu & C. Chen
Table 1. Results of a general linear model testing the spatial and temporal effects on dD and d18O values of soil water and plant xylem
water, as well as leaf d13C, Ψpd and Ψpd values (by a repeated-measures ANOVA)
Soil water
Tested effects
(A)
Season
Site
Depth
Season 9 Site
Season 9 Depth
Site 9 Depth
Season 9 Site 9 Depth
(B)
Season
Depth
Species
Season 9 Depth
Season 9 Species
(C)
Season
Depth
Species
Season 9 Depth
Season 9 Species
(D)
Season
Depth
Species
Season 9 Depth
Season 9 Species
Xylem water
Leaf
d.f.
dD
F
d18O
F
dD
F
d18O
F
d13C
F
Ψpd
F
Ψmd
F
4
3
5
12
20
15
60
22046**
1733**
2638**
160
2093**
106
093
9981**
1057**
1780**
173
1138**
073
095
9585**
1266**
4443**
596*
1589**
3457**
2162**
426*
7051**
308*
157
162
200*
184
722**
4
5
1
20
4
11238**
1764**
4003**
1179**
3121**
1781**
765**
902**
1747**
1719**
921*
705*
702*
1526**
763**
416**
359*
199
198
290*
792**
4
5
1
20
4
7833**
668**
3404**
48**
7514**
3308**
059
833**
2228**
1794**
565*
3451**
1045**
1258**
76**
333**
618**
540**
210
476**
836**
4
5
1
20
4
3426**
586**
2831**
42**
4775**
2932**
468**
2440**
1555**
2472**
920**
273
3316**
256
525**
383**
722**
722**
188
1743**
832**
F-values and significance are reported. The results include the following: (A) the effects on rubber trees at all sites; (B) the effects on all
plants in CSAs; (C) the effects on all plants in CAAs; and (D) the effects on all plants in TCAs. *P < 005, **P < 001.
The rubber tree xylem water dD and d18O values differed significantly among sites and seasons (P < 001),
and increased gradually at all sites during the study
(Fig. 4a–c). The xylem water isotopic values of intercrops
differed significantly from those of rubber trees (Table 1),
but their values were significantly correlated (the correlation coefficients all exceeded 089; P < 005) with those of
the rubber trees, except in TCAs.
Except for the water in the 0- to 5-cm and 5- to 15-cm
soil layers, the diagnostic matrix of correlations indicates
that the MIXSIAR model can readily differentiate the water
sources for each plant species at each site (Fig. S3).
Therefore, we identified the 0- to 15-cm-layer soil water as
the surface soil water. Similarly, using a posteriori method
(Phillips et al. 2005), we identified the 15- to 50-cm- and
50- to 110-cm-depth soil water as the intermediate soil
water and deep soil water, respectively, considering the
similar isotopic signatures of these depths (see above and
Fig. 3). The MIXSIAR model indicated that rubber trees in
Rm heavily relied on water from the surface and intermediate soil layers (representing an average of 745% of the
water absorbed by the rubber trees during the study), but
the water-absorbing proportion from the deep soil layers
gradually increased during the study period (Fig. 5a). In
CSAs, the rubber trees heavily absorbed water (767%)
from the intermediate and deep soil layers, and seasonal
changes in the absorbed proportion were considerable in
this area (Fig. 5b). The tea trees mainly relied on surface
soil water (53%), and the proportions of water they
absorbed from each soil layer showed no significant seasonal variation (Fig. 5c). In CAAs, the rubber trees also
absorbed most of their water (76%) from the intermediate
and deep soil layers, with significant seasonal changes in
the absorbed proportions from the surface and intermediate soil layers (Fig. 5d). In contrast, the coffee trees
absorbed most of their water (665%) from the surface
soil layer, and the absorbed proportions from each soil
layer varied greatly among the seasons (Fig. 5e). In
TCAs, the rubber trees absorbed most of their water
(764%) from the intermediate and deep soil layers, but
the absorbed proportion from each soil layer (except for
the 50- to 80-cm soil layer) exhibited no significant seasonal variation (Fig. 5f). The cocoa trees absorbed most
of their water (735%) from the surface soil, and seasonal
changes in the absorbed proportion only occurred in the
5- to 15-cm soil layer (Fig. 5e).
© 2016 The Authors. Journal of Applied Ecology © 2016 British Ecological Society, Journal of Applied Ecology, 53, 1787–1799
Plant water use in rubber agroforestry
Soil water δD
Soil water δ18O
(a) Rm
Rubber xylem water δD
Rubber xylem water δ18O
(b) CSAs
δ value (‰)
1793
Intercropped species xylem water δD
Intercropped species xylem water δ18O
(c) CAAs
δ value (‰)
(d) TCAs
δ value (‰)
δ value (‰)
Depth (cm)
Aug.2013
Depth (cm)
Nov.2013
Depth (cm)
Jan.2014
Depth (cm)
Mar.2014
Depth (cm)
May.2014
Fig. 3. Isotopic composition of soil water and its gradient variations within soil profiles of (a) Rm, (b) CSAs, (c) CAAs and (d) TCAs.
Data are expressed as means SE. See Fig. 2 for abbreviations.
PLANT LEAF d13C VALUES AND SHOOT WATER
POTENTIAL
The mean leaf d13C values of rubber trees were 3181&,
3096&, 2959& and 3167& in Rm, CSAs, CAAs
and TCAs, respectively. Additionally, the mean leaf d13C
values were 3158& for tea trees in CSAs, 3124& for
coffee trees in CAAs and 3207& for cocoa trees in
TCAs. These values are consistent with C3 photosynthesis
plants, as leaf d13C values range from 20& to 34&
(Farquhar, Ehleringer & Hubick 1989). The leaf d13C values of rubber trees differed significantly among the sites
(Table 1) and were ranked among studied sites, in
descending order, as CAAs, CSAs, TCAs and Rm. However, there was no significant difference between TCAs
and Rm. The leaf d13C values of rubber trees in the agroforestry systems other than TCAs were significantly higher
than those of the intercropped species, especially during
the rainy and hot dry seasons (Table 1; Fig. 4d,e). The
leaf d13C values of the intercropped species from each
agroforestry system, as well as rubber trees from CAAs,
showed little seasonal variation (P > 005).
Both the Ψpd and Ψmd results for the rubber trees
showed significant differences among seasons and sites
(P < 005; Table 1). For the rubber tree Ψpd, the highest
values were found within CSAs. At all sites, both Ψpd and
Ψmd of the rubber trees differed significantly from those
of their intercrops (except the Ψmd of rubber trees and
cocoa in TCAs). The interaction effect of season with species was significant (P < 001; see Table 1), and the simple-effects analysis showed that the intercrop values in
each agroforestry system changed less among seasons
than those of the rubber trees (Fig. 4j).
Discussion
Compared with the past, the seasonal distribution of precipitation during the study was exceptional (Fig. 1). The
strong ‘amount effect’ (Dansgaard 1964), as indicated by
the significant negative correlation between precipitation
and rainwater isotopic values, confirmed that the local
climate was dominated by monsoons (Zhang 1988). In
low-latitude monsoon regions, a d-excess exceeding 10&
indicates that most of the precipitation is derived from
© 2016 The Authors. Journal of Applied Ecology © 2016 British Ecological Society, Journal of Applied Ecology, 53, 1787–1799
1794 J. Wu, W. Liu & C. Chen
Xylem water isotopes (‰)
(a) CSAs
δD
(b) CAAs
δ18O
δD
(c) TCAs
δ18O
δD
δ18O
Rm-R
As-R
As-In
Rm-R
As-R
As-In
(e) CAAs
(f) TCAs
δ13C (‰)
(d) CSAs
Rm-R
As-R
As-In
Rm-R
As-R
As-In
Rm-R
As-R
As-In
(h) CAAs
(i) TCAs
Ψpd (Mpa)
(g) CSAs
Rm-R
As-R
As-In
Rm-R
As-R
As-In
(k) CAAs
Rm-R
As-R
As-In
(l) TCAs
Ψmd (Mpa)
(j) CSAs
Rm-R
As-R
As-In
Rm-R
As-R
As-In
Rm-R
As-R
As-In
Month
Rm-R
As-R
As-In
Month
Month
Fig. 4. Seasonal variation in (a–c) dD and d18O values for plant xylem water, (d–f) d13C values of plant leaves, (g–i) predawn leaf water
potential and (j–l) midday leaf water potential. Rm-R indicates rubber trees in rubber monoculture, As-R indicates rubber trees in agroforestry systems and As-In indicates various intercrops in agroforestry systems. See Fig. 2 for other abbreviations. Data are expressed as
means SE.
© 2016 The Authors. Journal of Applied Ecology © 2016 British Ecological Society, Journal of Applied Ecology, 53, 1787–1799
Plant water use in rubber agroforestry
100
(a) Rm-H.brasiliensis
c
Proportion (%)
80
c
c
60
40
1795
c
d
d
d
b
a
d
a
a
c
b
Depth
c
a
a
b
b
b
a
b
c
bc
80–110 cm
50–80 cm
30–50 cm
15–30 cm
5–15 cm
0–5 cm
a
b
20
a
a
b
a
0
Aug-13
Nov-13
Jan-14
Mar-14
May-14
Month
100
(b) CSAs-H.brasiliensis
b
b
100
b
b
a
80
60
b
a
b
b
b
bc
40
bc
a
b
Proportion (%)
80
Proportion (%)
(c) CSAs-C.sinensis
60
40
c
20
20
0
0
Aug-13
Nov-13
Jan-14
Mar-14
May-14
Aug-13
Nov-13
Month
100
(d) CAAs-H.brasiliensis
100
80
60
40
b
b
a
a
ab
ab
ab
b
ab
b
Proportion (%)
Proportion (%)
80
a
0
Aug-13
b
Nov-13
b
Jan-14
ab
Mar-14
b
b
ab
b
b
a
b
a
a
ab
b
ab
40
ab
a
ab
c
Aug-13
Nov-13
Jan-14
Mar-14
May-14
Month
a
40
(g) TCAs-T.cacao
80
ab
60
c
60
c
bc
ab
a
40
20
20
0
b
ab
60
100
b
b
ab
b
b
c
b
0
May-14
(f) TCAs-H.brasiliensis
b
May-14
ab
Proportion (%)
Proportion (%)
80
a
b
Month
100
Mar-14
(e) CAAs-C.arabica
20
20
Jan-14
Month
Aug-13
Nov-13
Jan-14
Month
Mar-14
May-14
0
Aug-13
Nov-13
Jan-14
Mar-14
May-14
Month
Fig. 5. Mean water-absorbing proportion of rubber trees (a, b, d and f) and the intercrops (c, e and g) from each soil layer. Shared patterns indicate that the differences in isotopic composition of each water source are not significant. Different lowercase letters indicate significant differences among seasons in the isotopic composition after post hoc Tukey’s tests (a = 005), while no letter indicates there was
no significant seasonal variation. See Fig. 2 for abbreviations.
© 2016 The Authors. Journal of Applied Ecology © 2016 British Ecological Society, Journal of Applied Ecology, 53, 1787–1799
1796 J. Wu, W. Liu & C. Chen
continental air masses instead of ocean water vapour. The
d-excess data therefore suggested that the Indian Ocean
monsoon, which dominated the local climate between
May and October (Zhang 1988), weakened during the
study period (see d-excess, Fig. 1). In fact, Asian monsoon decline has occurred, and become less certain in the
period of global warming since 1960. Anthropogenic forcing is thought to be the major driver (Verchot et al. 2007;
Zhang et al. 2008). Hence, climate change in this region
cannot be avoided. Indeed, local climate change has
occurred over several decades and has resulted in increasingly frequent extreme low-temperature and drought
events in the dry season (Zhang 1986). Because rubber
trees are highly sensitive to environmental conditions
(Priyadarshan 2011), the extreme weather events that
affected our study area provided an excellent opportunity
to improve our understanding of the responses of rubber
trees and the resistance of rubber agroforestry systems.
This understanding is imperative for effectively improving
the design of rubber plantations to meet these challenges.
Water potential is the key physiological index for representing water deficit in plants, and its fluctuations are
determined by transpiration and hydraulic conductance
when the soil water potential remains constant (Pallardy
2010). Specifically, Ψpd is often used as a reliable indicator of the average soil water potential, and Ψmd corresponds to the maximum transpiration (Richter 1997).
The soil water condition for rubber trees in CSAs was
the best, as the Ψpd was the highest, which is consistent
with the SWC result (Fig. 2). In TCAs, the cocoa tree
Ψmd did not significantly differ from rubber trees, indicating that the transpiration abilities of cocoa trees were
similar to rubber trees. The slight seasonal variation in
Ψmd in all the intercrops confirms that they are isohydric
species, which suffered little drought stress via strict control of transpiration through stomatal closure (Tardieu &
Simonneau 1998). In contrast, the obvious seasonal variation in rubber trees Ψmd indicates that they are anisohydric species (with less stringent stomatal control), as
previously demonstrated (Chandrashekar et al. 1990).
Additionally, the plants cope with drought stress via two
strategies: drought avoidance and drought tolerance
(Levitt 1980). Generally, the stomata of drought-avoidance plants are highly sensitive to drought stress and
have high water potential, but the water potential of
drought-tolerance plants is always low. Obviously, rubber
trees are drought-avoidance plants, but the intercrops,
especially tea trees, exhibited drought-tolerance behaviours. Hence, rubber trees in this area show defoliation
during the dry season (see phenophases in Fig. 1), which
can prevent excessive dehydration and drastically reduce
the total hydraulic conductance of leaves, thereby avoiding damage caused by drought stress (Bloom, Chapin &
Mooney 1985; Brodribb, Holbrook & Gutierrez 2002).
In addition, rubber trees in Rm suffered more drought
stress than those in the agroforestry systems in the dry
season.
Because the understorey can serve as a windbreak,
overall water evaporation is predicted to be lower in the
agroforestry systems (Soderberg et al. 2012), and the
agroforestry systems are predicted to capture more rain,
run-off and condensation from fog (Liu et al. 2005). The
agroforestry systems should therefore hold more soil
water than Rm, as was true in CSAs and CAAs; however,
the SWC of TCAs was significantly lower than that of
Rm. So, the water scarcity caused by rubber trees has
been alleviated in CSAs and CAAs. Differences in the seasonal input of rainwater (causing isotopic depletion) as
well as evaporation in surface layers (causing isotopic
enrichment) produce gradients in the isotopic composition
of the water in the soil profiles. Based on the aforementioned functions of the understorey, the soil water isotopic
compositions in agroforestry systems should be more
depleted than those of Rm. However, they (except TCAs)
were more enriched relative to Rm, despite a lack of significant differences among them, perhaps because of the
input of condensation from fog. Our previous study in
the same region suggested that fog water, characterized
by more enriched isotopic values than rainwater (ranging
from 62 to +19& for d18O and 30 to +27& for dD),
is important for shallow soil water recharge (Liu et al.
2005). Therefore, the condensation water in TCAs is less
than that in other agroforestry systems, which may be the
result of the lower planting density of the cocoa trees.
Meanwhile, the d13C assays indicate there was no significant interspecific or intraspecific WUE difference in TCAs
and Rm, suggesting that the water use behaviour of the
rubber trees in TCAs was still the same as that in Rm
and that cocoa trees can also squander water like rubber
trees, as a low WUE can increase transpiration-induced
water loss (Bacon 2009). These findings explain why the
SWC in TCAs was lower than in the other sites. Cocoa
trees have a strong water-absorbing capacity because their
lateral roots can spread 4–6 m from the stem (Carr &
Lockwood 2011). Relatively speaking, the water-absorbing
capacity of tea trees and coffee trees was weaker because
their lateral roots were less than 1 m (Niranjana & Viswanath 2008) and 24 m (Kanten et al. 2005), respectively.
In addition, the WUEs of the rubber trees in CSAs and
CAAs were significantly higher than those in Rm; thus,
the SWCs in both CSAs and CAAs were significantly
higher than those in Rm.
Tracing plant water sources can help us better understand plant water use patterns. Although the fine roots of
rubber trees are mainly concentrated in the top 30 m of
soil, the deeper roots are not necessarily less efficient
water absorbers since their lateral roots extended over
9 m (Priyadarshan 2011). The MIXSIAR model indicates
that the rubber trees in Rm depended greatly on surface
and intermediate soil water but could increase the waterabsorbing proportion from deep soil in the dry season.
Furthermore, such plasticity is also reflected in the complementarity of plant water use patterns in rubber agroforestry. The Ψpd values of the intercrops and rubber
© 2016 The Authors. Journal of Applied Ecology © 2016 British Ecological Society, Journal of Applied Ecology, 53, 1787–1799
Plant water use in rubber agroforestry
trees differed significantly in each agroforestry system,
consistent with the significant differences in the xylem
water isotopic compositions. In other words, their roots
distributions were not the same; thus, their main water
sources ought to be different. Indeed, previous studies
indicate that approximately 47% of the fine roots of tea
trees were concentrated in the upper 45 cm, with lateral
roots no more than 1 m deep (Feng 2007; Niranjana &
Viswanath 2008). The lateral roots of coffee trees were up
to 24 m from the trunk, and approximately 58–65% of
their fine roots were concentrated in the top 20 cm of the
soil (Kanten et al. 2005). Almost all the fine roots (more
than 90%) of cocoa trees were located in the upper 10 cm
of the soil, and their laterals roots can spread 4–6 m from
the trunk forming a mat of fine roots that extend into the
decomposing litter layer (Carr & Lockwood 2011). Hence,
surface soil water was mainly occupied by the intercropped species, especially cocoa trees (Fig. 5g).
Complementarity between the root distributions of
plants, which reduces competition for water and nutrients,
is common in efficient agroforestry systems (Niranjana &
Viswanath 2008). For most plants, this can occur because
roots can detect and avoid neighbouring roots, thus segregating spatially within the soil (Callaway 2002). However,
interspecific competition in plants cannot be completely
avoided because plants depend on nearly identical
resources (Falik et al. 2003), and some plants can increase
root growth when they were forced to share growth space
with another plant (Callaway 2002). Competition can promote two types of evolutionary responses: increased competitive ability and minimized competitive interactions
(Falik et al. 2003). Obviously, the former was more consistent with the intercropped species, while the latter was
more consistent with the rubber trees in our study. In
CSAs and CAAs, the significant correlation between the
xylem water isotopic values of intercropped species and
rubber trees indicated that their water resources were
related; thus, the competition for water cannot be
avoided. Indeed, the opposite seasonal fluctuations in
d13C and Ψmd values of both coffee trees and rubber trees
in CSAs showed strong competition for water. The strong
seasonal variations in their water-absorbing proportion in
each soil layer (Fig. 5d,e) also demonstrate this. This
competition is because the root systems of coffee species
are also highly plastic. Thus, in dense plantings, coffee
roots can grow deeper to take up water and nutrients
from lower soil horizons (DaMatta et al. 2007). Meanwhile, previous studies have indicated that the feeder
roots of rubber and coffee trees in agroforestry system
were substantially overlapped (Feng 2007). Such intense
competition decreases water availability, thereby making
the WUE of rubber trees in CAAs the highest. Because
the fine roots overlapped less in CSAs and TCAs and the
deep soil water was stable, the seasonal variations in
water-absorbing proportions of the plants in both CSAs
and TCAs were less than those in CAAs and Rm. This
high degree of water uptake plasticity of rubber trees
1797
helps them to avoid water scarcity related to both seasonal drought and interspecific competition.
Plant leaf d13C value is a useful and extensively examined indicator of long-term WUE in C3 photosynthesis
plants, and the increased WUE which can be indicated by
leaf d13C value can be referred to as a response mechanism of plants to soil water deficits and drought tolerance
(Farquhar, Ehleringer & Hubick 1989). Thus, rubber trees
showed higher leaf d13C values in the dry season because
soil water deficits occurred during this season. However,
interspecific competition for water, which can decrease
soil water availability, is the main driver of WUE
increases (rather than soil water deficits) since the soil
water in CSAs and CAAs was much more abundant than
in Rm. Some studies have suggested that low WUE confers a competitive advantage when water is abundant
(Lucero, Grieu & Guckert 2000; Robinson et al. 2001).
Hence, the intercrops always occupy surface soil water
because of their lower WUE and root distributions. Additionally, the increased WUE of agricultural plants typically increases yield and decreases transpiration-induced
water loss (Bacon 2009). During the dry season, water
consumption is mostly governed by environmental variables; thus, a high WUE ensures normal growth of the
plant. Hence, the higher rubber tree WUE in CSAs and
CAAs is associated with higher productivity and less
water waste relative to Rm, thereby ensuring a higher
yield during the rainy season and normal physiological
activity during the dry season. This inference can be supported by previous studies that intercropping tea, coffee
or cocoa tree with rubber tree could increase rubber yields
and biomass (Feng 2007; Snoeck et al. 2013).
Moreover, environmental factors other than water, such
as temperature and photosynthetically active radiation,
can also greatly affect WUE or leaf d13C values (Bacon
2009). As we mentioned above, all the intercrops suffered
little drought stress, as indicated by the slight seasonal
variations in Ψmd, via strict control of transpiration
through stomatal closure. Thus, environmental factors,
mainly temperature (considering the design of our experiment), would more greatly affect their leaf d13C values.
However, the leaf d13C values of the intercrops in all the
agroforestry systems, as well as the rubber trees in CAAs,
during the study were stable despite the extreme cold in
December 2013. This observation confirmed that the
internal environmental conditions in the agroforestry systems were stable likely because of the windbreak function
and heating effect of the understorey (Feng 2003), especially in CAAs. Thus, the agroforestry systems had a
higher degree of resistance or ecosystem stability (i.e. the
ability of an ecosystem to maintain a steady state, even
after a stress or disturbance has occurred) compared with
Rm. As most rubber growers know, rubber tree foot disease, which was found only in Rm in our study, is a
destructive threat to the survival of rubber trees during
their wintering period. Stable internal microclimatic environments can ensure that rubber trees seldom suffer such
© 2016 The Authors. Journal of Applied Ecology © 2016 British Ecological Society, Journal of Applied Ecology, 53, 1787–1799
1798 J. Wu, W. Liu & C. Chen
injuries. Thus, less water waste, higher resistance and
higher yield are directly related to enhancing the adaptive
capacity of rubber agricultural systems to a disturbance.
Overall, rubber trees exhibited a drought-avoidance
strategy. In Rm, rubber trees relied heavily on surface
and intermediate soil water and employed wasteful behaviour with respect to water, leading to water scarcity.
However, rubber trees can adjust their water use strategy
(i.e. by increasing both deep soil water absorption and
WUE) to cope with drought stress. In our agroforestry
systems, rubber trees relied mainly on intermediate and
deep soil water to avoid intense competition for surface
water, as was also reflected in their strong plasticity in
water uptake. The rubber trees in TCAs still employed
water-wasteful behaviour, but the rubber trees in CSAs
and CAAs exhibited water-saving behaviour; thus, the
soil water in CSAs and CAAs was more abundant (i.e.
the water scarcity caused by rubber trees was alleviated
in CSAs and CAAs). These intercropped species were
drought-tolerance species, and they can increase their
competitive capacity for surface water by maintaining
low WUE and stable Ψmd. In TCAs, interspecific competition for water was the weakest, causing rubber trees in
TCAs to have similarly low WUE as rubber trees in Rm,
and because of the similar low WUE of cocoa trees,
TCAs depleted more soil water than Rm. In contrast, the
competition in CAAs was more intense so that the rubber
trees showed the highest WUE. However, such intense
competition may also greatly affect nutrient absorption
by roots, especially for coffee trees (Feng 2007). The
competition in CSAs was moderate, as tea trees have
shorter lateral roots and a moderate amount of fine roots
overlapping with those of rubber trees in the shallow soil
layer compared with coffee and cocoa trees. Therefore,
tea trees may be the most suitable intercrop since CSAs
could contain much more water, improve the WUE of
the rubber trees and maintain a moderate degree of interspecific competition for water. We also conclude that
interspecific competition for water can enhance WUE of
drought-avoidance plants (i.e. rubber trees). Additionally,
the resistance of all agricultural systems was stronger
than that of Rm in the face of extreme cold and drought.
Based on the features of tea trees, we advise that the
intercrops selected for intercropping with rubber trees
should have lower WUE compared with rubber trees,
stronger drought resistance, relatively fixed water use pattern, short lateral roots and a proper amount of overlapping fine roots with rubber trees in the shallow soil layer.
Acknowledgements
We thank Dr. Deng Y., Mr. Liu M.N., Prof. R.T. Corlett, Miss Zhao F.,
Xishuangbanna Station for Tropical Rain Forest Ecosystem Studies and
the Central Laboratory of XTBG for their help. This study was supported
by the National Natural Science Foundation of China (31570622,
41271051 and 31170447), Natural Science Foundation of Yunnan Province
(2013FA022 and 2014HB042) and the Chinese Academy of Sciences 135Project (KFJ-EW-STS-084).
Data accessibility
All data are available from the Dryad Digital Repository: http://dx.
doi.org/10.5061/dryad.cs1h4 (Wu, Liu & Chen 2016).
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Received 1 May 2016; accepted 23 June 2016
Handling Editor: Joseph Bennett
Supporting Information
Additional Supporting Information may be found in the online version
of this article.
Fig. S1. Planting patterns of the rubber plantation.
Fig. S2. Rubber tree foot disease.
Fig. S3. Diagnostic matrix plot for the Bayesian mixing model
(MIXSIAR) at the season level.
© 2016 The Authors. Journal of Applied Ecology © 2016 British Ecological Society, Journal of Applied Ecology, 53, 1787–1799