Forest Ecology and Management 257 (2009) 2088–2097
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Forest Ecology and Management
journal homepage: www.elsevier.com/locate/foreco
Stand level estimation of root respiration for two subtropical plantations based on
in situ measurement of specific root respiration
Dima Chen a,b, Yang Zhang a,b, Yongbiao Lin a, Hua Chen c, Shenglei Fu a,*
a
Institute of Ecology, South China Botanical Garden, Chinese Academy of Sciences, Guangzhou 510650, China
Graduate University of the Chinese Academy of Sciences, Beijing 100049, China
c
Biology Department, University of Illinois at Springfield, IL 62703, USA
b
A R T I C L E I N F O
A B S T R A C T
Article history:
Received 25 September 2008
Received in revised form 10 January 2009
Accepted 18 February 2009
In this study, the stand level root respiration was estimated for two monoculture plantations: Acacia
crassicarpa and Eucalyptus urophylla, based on in situ measurement of specific root respiration using
simplified root chamber method. The respiration rates of fine roots (<5 mm) were significantly higher
than those of coarse roots (>5 mm) for both A. crassicarpa and E. urophylla species. The root respiration of
A. crassicarpa showed a clear seasonal pattern with a higher value in the wet season. For E. urophylla, the
seasonal pattern was observed for fine roots but not for coarse roots. After determining the biomass of
fine roots and coarse roots and their specific rates of respiration at different time points, root respiration
at the stand level (Ra) was estimated using a direct up-scaling model. We found that the Ra accounted for
14% and 19% of total soil respiration (Rs) for A. crassicarpa and E. urophylla, respectively. The fine (RTf) and
coarse (RTc) root respiration at the stand level accounted for about 47% and 53% of the Ra for A. crassicarpa,
and accounted for 58% and 42% for E. urophylla. This suggests that coarse root respiration cannot be
ignored when estimating the root respiration at the stand level. Our results showed that the Q10 values
were more accurate in representing the temperature dependence when the confounding effect of soil
moisture was considered. This study introduces an alternative approach to estimate stand level root
respiration, but its reliability is largely dependent on the accuracy of root biomass quantification.
ß 2009 Elsevier B.V. All rights reserved.
Keywords:
Acacia crassicarpa
Eucalyptus urophylla
Rhizosphere respiration
Fine roots
Coarse roots
Q10
1. Introduction
Forest ecosystems have been the focus of many studies
worldwide because of the critical role they play in global carbon
(C) cycling. Forests comprise a major portion of the terrestrial C
sink and regulate C cycling between the terrestrial ecosystem and
the atmosphere. Soil respiration is the major pathway of carbon
loss in forest ecosystems (Goulden et al., 1996; Law et al., 1999),
accounting for over 70% of the respiration in some ecosystems
(Raich and Schlesinger, 1992). Forest plantations occupy an area of
approximately 0.20 billion ha worldwide and support the
increasing local and global demand for wood (FAO, 2007). These
forest plantations have been considered as potential fast-response
carbon sinks that may mitigate the rise of atmospheric CO2
concentrations (Hoen and Solberg, 1994; Sands et al., 1999;
Hunter, 2001). Fast-growing species such as Acacia crassicarpa and
Eucalyptus urophylla have been extensively planted and managed
* Corresponding author. Tel.: +86 20 37252592 fax: +86 20 37252615.
E-mail address: [email protected] (S. Fu).
0378-1127/$ – see front matter ß 2009 Elsevier B.V. All rights reserved.
doi:10.1016/j.foreco.2009.02.018
for pulpwood production in many tropical and subtropical regions
due to their high productivity with short rotations (Attiwill, 1994).
The potential for forest plantations to serve as a large C sink can
be evaluated by net ecosystem productivity (NEP), which can be
simply estimated by the difference between net primary productivity (NPP) and heterotrophic respiration (Rh) (Odum, 1969;
Gower et al., 2001; Chapin et al., 2002). Accurate prediction of NEP
in forest ecosystem requires accurate assessment of both NPP and
Rh. Yet one of the challenges involved in the experimental
validation of accurate assessment of NEP is the separation of soil
respiration (Rs) into heterotrophic (Rh, respiration of microbes
decomposing litter and soil organic C) and autotrophic (Ra,
respiration of roots and associated rhizospheric microbes)
components (Epron et al., 2001; Bond-Lamberty et al., 2004;
Scott-Denton et al., 2006). The determination of partitioning
between Ra and Rh must therefore be attempted with as much
accuracy as possible. This has been the objective of a number of
studies. There is a variety of techniques for separation of Rs but
each with their own drawbacks and underlying assumptions
(Hanson et al., 2000; Baggs, 2006; Kuzyakov, 2006; Binkley et al.,
2006). In addition, the contribution of each component needs to be
understood because Rh and Ra may respond differently to
D. Chen et al. / Forest Ecology and Management 257 (2009) 2088–2097
environmental variables, microbial community composition and
climate change (Boone et al., 1998; Widen and Majdi, 2001;
Bhupinderpal et al., 2003; Lavigne et al., 2003).
Most of the respiration partitioning methods are indirect and
rely heavily on soil respiration measurements, whose accuracy and
precision are an ongoing matter of debate (Longdoz et al., 2000;
Janssens et al., 2001; Yim et al., 2002; Ngao et al., 2006). In order to
validate the estimates of autotrophic and heterotrophic respiration, all possible approaches allowing the independent estimation
of the two components must be explored. Plot trenching approach
is commonly used because of its simplicity and low cost (Hanson
et al., 2000). However, plot trenching severs the structural integrity
of roots and fungal hyphae (Bhupinderpal et al., 2003), modifies
biophysical conditions and substrate supply for microbial respiration (Lee et al., 2003), and may change the soil microbial
population or composition (Högberg and Högberg, 2002).
Nevertheless, there have been several reports about direct
measurement of Ra using root-excision method (Nakatsubo et al.,
1998; Law et al., 2001; Widen and Majdi, 2001; Irvine and Law,
2002; Burton et al., 2004; Fahey et al., 2005); this technique relies
on the measurement of the CO2 produced by roots shortly after
being retrieved from a fresh soil core. Subke et al. (2006) estimated
the root contribution to Rs after measuring root respiration, root
density in the stand and undisturbed Rs. Unfortunately, only fine
roots were considered in their study. Marsden et al. (2008) also
estimated the root respiration at stand level (Ra) by measuring the
fine root respiration using ‘‘root-excision’’ method and the coarse
root respiration by ‘‘root-chamber’’ method. One of the drawbacks
of the root-excision method is the disturbance and wounding
effects on roots caused by excision. In addition, the root respiration
decreased rapidly within several minutes after root excision due to
the decrease of substrate supplies (Rakonczay et al., 1997; Yi et al.,
2007).
Since roots are a critical component of ecosystem nutrient
stock and an important sink of plant primary productivity
(Jackson et al., 1997), there is much research focused on this
‘‘hidden half’’. Fine root respiration is always emphasized because
it is the primary pathway for water and nutrient uptake by plants
(Gill and Jackson, 2000). However the function of coarse root has
often been overlooked (Gansert, 1994; Ryan et al., 1996;
McDowell et al., 2001; Widen and Majdi, 2001; Desrochers
et al., 2002; Hamilton et al., 2002; Marsden et al., 2008), despite
the fact that the coarse root biomass accounts for about 95% of the
total root biomass (Edwards and Norby, 1998). The respiration
rates of coarse roots are usually assumed to be the same as those of
branches and stems, and are extrapolated to the stand level using
biomass derived from published allometric equations (Widen and
Majdi, 2001; Hamilton et al., 2002), but this approach has been
rejected by others (Vose and Ryan, 2002). Recently, Fu et al. (2008)
introduced a simplified root-chamber system to measure
respiration of fine roots and coarse roots in situ. After estimating
the biomass of both fine roots and coarse roots, the root
respiration at stand level (Ra) could be directly estimated using
this simplified approach.
The primary goals of this study were to: (1) estimate the
contribution of fine root and coarse root respiration to stand
level root respiration; (2) illustrate the seasonal patterns and soil
temperature sensitivity of root respiration and soil respiration;
(3) introduce a model to estimate stand level root respiration
based on the soil temperature and soil moisture. Plantations
might play an important role in C sequestration and C cycling.
The dominant plants of monoculture plantations in China
include Acacia, Eucalyptus, Pinus and Populus. A. crassicarpa
and E. urophylla plantations are representative species of Acacia
and Eucalyptus and were selected as test plants in the present
study.
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2. Methods
2.1. Site description
The study was conducted in A. crassicarpa and E. urophylla
monoculture plantations at the Heshan Hilly Land Interdisciplinary
Experimental Station (1128500 E, 228340 N), Chinese Academy of
Sciences (CAS). The field station is located in Heshan County,
Guangdong province, which is a subtropical hilly land region of
South China. The plantations were established in 2005 and occupy
an area of 50 ha. The site is characterized by the typical southern
climate of subtropical monsoon with lateritie soil. There is a distinct
difference between wet season and dry season. The wet season starts
in March and ends in September, and dry season starts in October
and ends in February. The annual mean precipitation was 1295 mm
between 1984 and 2006 and 80% of the precipitation occurred
during the wet season. Annual precipitation in 2007 was 1180 mm
which was lower than the annual mean precipitation recorded over
22 years. The precipitation was mainly distributed in April to
September with the highest in August and lowest in November. The
mean annual temperature is 21.7 8C. The A. crassicarpa and E.
urophylla saplings were planted at 3 m 2 m spacing. The mean soil
temperature at 5 cm soil depth under A. crassicarpa (22.9 1.3 8C)
was higher than that under E. urophylla (21.2 1.3 8C), and the highest
soil temperature was in July and lowest in January or February. In
January of 2008, the average height and diameter at breast height (DBH)
of A. crassicarpa were around 6.3 m and 6.4 cm, and those of E. urophylla
were 11.9 m and 9.1 cm, respectively. Understory vegetation was
dominated by Dicranopteris dichotoma (Thunb.) Bernh, but was mowed
before the field apparatus installations and measurements.
2.2. Fine root and coarse root biomass
In November of 2006, seven representative trees from each
stand were cut down at the base, the coarse roots (diameter
>5 mm) were excavated manually and fresh weights were
recorded. All fresh samples were collected and oven-dried
(65 8C) to constant weight and weighed. The diameter at breast
height (DBH) and height of the plantations were measured at the
time when root respiration was determined from February 2007 to
February 2008 (eight times in total). The allometric relationships
were established between coarse root biomass (Bc) and DBH and
height of the plants based on direct measurements.
In February 2007 and February 2008, the fine root biomass (Bf)
was measured using a sequential soil coring method. Briefly, 17
soil cores (8 cm in diameter, 40 cm in depth) were taken randomly
under each plantation using a steel corer. Each soil core was
divided into four sections based on horizon (0–10, 10–20, 20–30,
and 30–40 cm). Each soil section was soaked and carefully sieved
through a 0.5 mm mesh sieve to isolate roots, which were sorted by
size (<5, or >5 mm diameter) and vitality (live or dead, assessed
visually based on color, elasticity and resilience). The weights of
root samples were recorded after the roots were oven-dried at
65 8C to a constant mass (Burton et al., 2004). We hypothesized
that variation of fine root biomass is proportional to coarse root
biomass because it was reported there was a positive correlation
between the two components (Ruess et al., 1996). The Bf was
estimated using the following relationship:
DBc
ðB Bf1 Þ
DBc f2
Bf ¼ Bf1 þ P
(1)
where Bf is fine root biomass at the time when root respiration is
measured (seven times in total), and Bf1 and Bf2 are fine root
biomass estimated in February 2007 and February 2008, respectively. The Bc is coarse root biomass calculated by the previous
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D. Chen et al. / Forest Ecology and Management 257 (2009) 2088–2097
allometric relationships based on the data of DBH and height of the
plants, and the data were collected at the time when root
respiration was determined from February 2007 to February 2008.
The DBc is the net increment of coarse root biomass between two
P
consecutive samplings. DBc is the sum of the net increment of
coarse root biomass (DBc), which is equivalent to the annual net
increment of coarse root biomass from February 2007 to February
2008.
2.3. Measurement of fine root and coarse root respiration
In A. crassicarpa and E. urophylla plantations, eight replicate
trees in each stand were randomly selected in early February for
four sequential measurements of root respiration (February 7, May
5, June 5 and July 4 of 2007). Another eight replicate trees in each
stand were randomly selected in later July for measurements at
three times (August 3, September 21 and November 28 of 2007).
Before measurement, we carefully removed the litter layer and top
soil under each replicate tree, and selected the roots of A.
crassicarpa or E. urophylla by hand to ensure that roots were not
damaged. Since the plantations are monocultures, it was not
difficult to identify the target tree roots. The criteria for fine roots
were root diameters not over 5 mm and with as many branching
orders as possible. The roots were considered to be coarse roots
when the diameter was over 5 mm. In general, the coarse roots
were straight with few sub-order branches. Under each replicate
tree, three root chambers were installed including ‘‘fine roots and
soil’’ treatment, ‘‘coarse roots and soil’’ treatment and ‘‘soil alone’’
treatment (Fig. 1). The soil used in the three treatments was taken
from the same place where roots were, and soil was sieved with a
4 mm sieve to get rid of the rocks and residues. The details were
described in Fu et al. (2008), here are the brief descriptions:
(1) ‘‘Soil alone’’ treatment: 500 g of the native soil was refilled into
the root chamber, which was made of PVC tube with an inner
diameter of 7 cm and a length of 37 cm, but without the
presence of roots.
(2) ‘‘Fine roots and soil’’ treatment: After a fine root was identified
and selected, the end section was carefully inserted into the
root chamber. The root chamber was sealed immediately with
a silicon stopper and 500 g of native soil was filled into the root
chamber. The opening of the root chamber was then sealed
with another silicon stopper where a small hole was made for
root-insertion; later the joint of roots and the small hole was
sealed with silicon glue.
(3) ‘‘Coarse roots and soil’’ treatment: One section of the coarse
root was placed into the root chamber from the slot made on
the lateral side of the chamber. The slot was sealed with silicon
glue after the placement of coarse root and 500 g of native soil.
The two ends of the root chamber were then closed with
perforated silicon stoppers and finally sealed with silicon glue.
Before the measurement took place, an acclimatization period
of one week was allowed for all roots inside the chambers under
field conditions. We did not attempt to install temperature probe
inside root chamber, because Cheng et al. (2005) measured the
inside temperature of the root chamber using a temperature sensor
and found it was not significantly different from soil temperature
at the same depth where root chamber was installed. The soil
inside the chamber showed no signs of drying in our study because
the circulating air had been through a water bottle before entering
the root chamber so that the air was moist enough to offset any
water loss of soil inside the chamber. The dry weight and diameter
of the roots were determined after taking them out of the
chambers at the last measurement. The maximum diameter of the
root in chamber was assessed as ‘‘root diameter’’ and it actually
was a branching network of roots in the present study. Root
diameter was measured at the end of each experiment. Root
respiration was defined as the difference between CO2 evolved
from ‘‘roots with soil’’ and ‘‘soil alone’’ treatments, and expressed
on a dry root weight basis. To minimize the potential influence of
the CO2 accumulation on root respiration (Qi et al., 1994; Burton
et al., 1997), three consecutive measurements were made on each
sampling day (9:00–13:00, 13:00–17:00 and 17:00–9:00 h). The
Fig. 1. Diagram of the modified root-chamber system for measuring root respiration (modified from Fu et al., 2008). This root-chamber system consists of three components:
(1) an air-flush unit; (2) root-chamber including ‘‘soil alone’’ treatment (A), ‘‘fine roots and soil’’ treatment (B), and ‘‘coarse roots and soil’’ treatment (C); and (3) CO2 sampling
apparatus (D).
D. Chen et al. / Forest Ecology and Management 257 (2009) 2088–2097
CO2 accumulated in the root chamber was sampled using a 60 ml
syringe and measured using a gas chromatograph (HP 6890,
Agilent). The siphon apparatus was used to flush the residue gases
in the root chamber after each CO2 sampling or before the next
incubation period. The principle and operational procedure for the
system were described in detail by Fu et al. (2008).
In order to estimate the maintenance respiration of roots, the fine
roots of the two tree species were selected to measure the root
respiration before and after the roots were excised in August of 2008.
Root respiration rates before excision was recorded as the initial root
respiration (R0) and measured 10 min after excision was represented
as R10. Although the R10 might not be the true maintenance
respiration, we consider the R10 as the relative predictor of fine root
maintenance respiration because the root respiration stabilizes
10 min after root excision (R10) based on our pilot study. Similarly,
respiration rate after root excision was used as maintenance
respiration although the stabilization time was longer (Chapin and
Slack, 1979). Since CO2 concentration around roots could affect root
respiration significantly (Burton et al., 1997), the concentration of
CO2 supplied into root chamber was 2000 ppm, which was similar to
the mean CO2 concentrations at the same soil depth where the root
chambers were installed (Yi et al., 2007).
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reported to be close to daily means (Tang et al., 2006a). Before
sampling, we push and pull the syringes five times to mix the air
inside the chambers. 60 ml gas samples were collected every
10 min from each chamber using 100 ml plastic syringes and four
samples were taken consecutively within 30 min (0, 10, 20 and
30 min). CO2 concentrations in the samples were analyzed in the
laboratory within 24 h (a preliminary test showed that the CO2
concentrations in the syringes did not change within 36 h) after
sampling using gas chromatography (HP 6890, Agilent). The gas
chromatography configurations for CO2 analysis and the methods
for CO2 efflux calculation were the same as those described by
Wang and Wang (2003). The CO2 efflux was calculated based on
the rate of change in CO2 concentration within the chamber, which
was estimated as the slope of linear regression between
concentration and time. All the coefficients of determination (r2)
of the linear regression were greater than 0.95. We monitored the
soil temperature at the depth of 5 cm with temperature probes in
two plots for each plantation and data were recorded as hourly
means. Gravimetric water content (%) was measured for all
samples collected at each sampling by oven drying at 105 8C for
24 h (15 samples for each plantation each time). Precipitation was
measured continuously with a tipping bucket rain gauge and data
were stored as hourly totals (Fig. 2).
2.4. Estimation of stand level rhizosphere respiration
2.6. Statistical analyses
Based on direct root respiration measurement using simplified
root-chamber system (Fu et al., 2008), the stand level Ra on specific
measurement day was extrapolated using the following equation:
X
X
Ra ¼ Rf Bf þ Rc Bc
(2)
where Rf and Rc are respiration rate of fine roots and coarse roots
per unit dry weight on a specific day. Bf and Bc are biomass of fine
roots and coarse roots per unit area.
Based on the measurement of Ra, soil temperature and soil
moisture under the two plantations, the regression between Ra and
two biophysical parameters can be established using the following
equation (Xu and Qi, 2001; Tang et al., 2006b):
Ra ¼ b0 eb1 T W b2
(3)
where T is soil temperature (8C) at 5 cm depth, W is gravimetric
water content (%) of topsoil (0–20 cm), and b0, b1, and b2 are
constants fitted with the least-squares technique. After consecutively monitoring the two biophysical parameters, the annualbased stand level Ra can be estimated with this model.
2.5. Measurements of soil respiration
The soil respiration (Rs) was measured about every month
during 2007, including seven times when root respiration was also
determined. The Rs was measured in three replicate plots
(10 m 10 m) of each plantation using static chamber and gas
chromatography techniques (Wang and Wang, 2003). The static
chamber consisted of two parts, a steel collar (20 cm in diameter
and 5 cm in height) attaching with a circular sink (18 cm of inner
diameter, 22 cm of outer diameter and 4 cm of bottom width) and a
removable PVC chamber (20 cm in diameter and 20 cm in height,
with a top but without a bottom). Five steel collars were randomly
anchored 5 cm into the soil in each plot during measurement, and
the removable chamber was placed onto the sink of the collar and
sealed with water during sampling. We did not install any fan
inside the chamber because using a fan may alter the concentration
gradients of CO2 effluxes and cause a bias in measurements
(Davidson et al., 2002). In fact, a fan may not be needed for our
small chamber. The soil CO2 effluxes were sampled during 09:00–
10:00 h because soil respiration rate during this time interval was
Analysis of variance was performed to test for a significant
difference in respiration rates between root size classes (two) or
between tree species (two). Least significant difference (LSD)
procedure was used for comparison of treatment means.
Significance level was set at p 0.05. Statistical analyses for all
data were performed using SPSS 15 (SPSS, Inc, Chicago, IL).
Relationships between respiration (R) and biophysical factors
were examined using regression models. The root respiration
included Rf, Rc, Ra, and Rs, three types of regression models were
used. The first model is exponential and involves only soil
temperature, referred to as the T model (Boone et al., 1998):
R ¼ b0 eb1 T
(4)
where T is soil temperature (8C) at 5 cm depth, and b0, b1, and b2
are constants fitted with the least-squares technique. The second
model is linear, where soil moisture (W) was used as the indicator
variable, and is referred to the W model (Burton et al., 1998):
R ¼ b2 þ b3 W
(5)
where W is gravimetric water content (%) of topsoil (0–20 cm), and
b2 and b3 are constants fitted with the least-squares technique.
Fig. 2. Monthly sum of precipitation and monthly mean of soil temperatures from a
depth of 5 cm of 2007.
D. Chen et al. / Forest Ecology and Management 257 (2009) 2088–2097
2092
Fig. 3. Root respiration (Rr) of A. crassicarpa and E. urophylla of different root diameter (D) (A–B). The Rr was measured and modeled with equations, the solid and dashed lines
were the dividing lines of fine root and coarse root (5 mm). (A) The regression for A. crassicarpa (Rr = 11.74(D)1.68, r2 = 0.54, p < 0.001, n = 101); (B) the regression for E.
urophylla (Rr = 3.62(D)1.24, r2 = 0.43, p < 0.001, n = 102).
The third model considered both soil temperature and soil
moisture since root respiration was regulated by these two
parameters, and is referred to the T/W model (Xu and Qi, 2001;
Burton and Pregitzer, 2003; Burton et al., 2004):
32 6 g DW m2 for A. crassicarpa and E. urophylla, and 107 25
and 163 42 g DW m2 in February 2008, respectively.
R ¼ b0 eb1 T W b2
For A. crassicarpa, fine root diameter in the chamber ranged
from 1.5 to 4.8 mm with the mean value of 3.6 0.2 mm, coarse
root ranged from 6.1 to 17.0 mm with the mean value of
11.1 0.5 mm. For E. urophylla, fine root diameter ranged from 2.2
to 4.8 mm with the mean value of 3.3 0.2 mm, coarse root ranged
from 5.3 to 18.3 mm with the mean value of 10.0 0.5 mm (Fig. 3).
The root respiration of A. crassicarpa and E. urophylla decreased
significantly with increasing root diameter (D) (Fig. 3). Fine root
respiration rates were significantly higher than coarse root respiration (Tables 1 and 2). The root respiration was relatively stable when
the diameter was greater than 5 mm for both A. crassicarpa and E.
urophylla, therefore, the root with diameter great than 5 mm was
considered as coarse root in the present study.
The root respiration ranged from 0.57 to 4.65 nmol
CO2 g root1 s1 for fine roots and from 0.13 to 0.72 nmol
CO2 g root1 s1 for coarse roots of A. crassicarpa. The highest
respiration rate of fine roots occurred in July and in May for coarse
roots. The lowest rate occurred in November for both root size
classes (Table 1). The fine root (Rf) and coarse root (Rc) respiration
rates of A. crassicarpa showed a significant exponential relationship
with soil temperature (Table 3). The Rf was significantly correlated
with soil moisture but the Rc did not show this pattern (Table 3).
The T/W model incorporated both soil temperature and soil
moisture (Eq. (6)) yielded higher r2 values than univariate T or W
model alone (Table 3). T/W models explained 64% and 33% of the
variation in Rf and Rc under A. crassicarpa plantation, which were
much higher than T or W Model. The Q10 values based on the T/W
(6)
where T is soil temperature (8C) at 5 cm depth, W is gravimetric
water content (%) of topsoil (0–20 cm), and b0, b1, and b2 are
constants fitted with the least-squares technique.
The Q10 values were calculated as follows:
Q 10 ¼ e10b1
(7)
where b1 is taken from the T model (Eq. (4)) or the T/W model
(Eq. (6)).
3. Results
3.1. Fine root and coarse root biomass
In December of 2006, the mean heights of the plantations were
3.60 and 5.45 m, and the mean DBHs were 2.59 and 4.09 cm for A.
crassicarpa and E. urophylla. The allometric relationships used to
estimate coarse root were Bc = 21.42(D2H)0.50 (r2 = 0.60, p = 0.04,
n = 7) and Bc = 44.49(D2H)0.48 (r2 = 0.72, p = 0.01, n = 7) for A.
crassicarpa and E. urophylla, respectively. The coarse root biomass
was 107 15 and 456 30 g DW m2 for A. crassicarpa and E.
urophylla. In January of 2008, the mean heights of the plantations
were 6.42 and 9.07 m, the mean DBHs were 6.3 and 11.9 cm and the
coarse root biomasses were 351 and 1351 g DW m2 for A. crassicarpa
and E. urophylla, respectively. The fine root biomasses (Bf) determined
using the soil coring method in Feb 2007 were 43 4 and
3.2. Fine root and coarse root respiration
Table 1
Root biomass, root respiration, and major components of soil respiration (Rs) of A. crassicarpa.
Date
Bf
(g m2)
Bc
(g m2)
Rf (nmol CO2 g
root1 s1)
Rc (nmol CO2 g
root1 s1)
Ra (nmol CO2
m2 s1)
Rs (nmol CO2
m2 s1)
RTf/Ra (%)
RTc/Ra (%)
Ra/Rs (%)
7 February
10 May
5 June
4 July
3 August
21 September
28 November
43.0
57.9
63.0
69.4
75.1
86.0
97.9
136.0
180.6
195.9
215.0
232.4
264.8
300.6
1.46
2.11
2.28
4.65
4.37
0.86
0.57
0.50
0.72
1.59
0.64
0.62
0.33
0.13
131
252
455
460
472
161
95
1085
2345
1907
3192
2221
2169
1134
48.0
48.4
31.6
70.1
69.5
45.8
58.8
52.0
51.6
68.4
29.9
30.5
54.2
41.2
12.1
10.8
23.9
14.4
21.3
7.4
8.4
Mean
70.3 (6.9)
217.9 (20.6)
2.33 (0.61)
290 (64)
2008 (277)
53.2 (5.2)
46.8 (5.2)
14.0 (2.4)
(0.32)
(0.39)
(0.19)
(0.51)
(0.96)
(0.38)
(0.28)
(0.11)
(0.25)
(0.37)
(0.21)
(0.13)
(0.08)
(0.04)
0.65 (0.17)
(98)
(221)
(176)
(284)
(205)
(220)
(106)
Note: Bf and Bc are biomass of fine roots and coarse roots; Rf and Rc are respiration of fine roots and coarse roots; Ra and Rs are root respiration at stand level and soil
respiration; RTf and RTc are respiration of fine roots and coarse roots at stand level. Values in parentheses are standard errors (n = 8).
D. Chen et al. / Forest Ecology and Management 257 (2009) 2088–2097
2093
Table 2
Root biomass, root respiration, and major components of soil respiration (Rs) of E. urophylla.
Date
Bf
(g m2)
Bc
(g m2)
Rf (nmol CO2 g
root1 s1)
Rc (nmol CO2 g
root1 s1)
Ra (nmol CO2
root1 s1)
Rs (nmol CO2
root1 s1)
RTf/Ra (%)
RTc/Ra (%)
Ra/Rs (%)
7 February
10 May
5 June
4 July
3 August
21 September
28 November
31.7
57.8
67.1
79.0
90.2
111.3
134.7
456.2
617.0
674.5
747.5
816.6
946.0
1090.6
0.85
2.11
0.72
2.66
2.59
2.14
1.01
0.37
0.25
0.21
0.41
0.26
0.16
0.11
196
276
190
517
446
389
256
907
1973
2584
3359
2015
1730
905
13.8
44.2
25.4
40.7
52.4
61.1
53.2
86.3
55.9
74.6
59.3
47.6
38.9
46.9
21.6
14.0
7.4
15.4
22.1
22.5
28.3
324 (48)
1925 (332)
41.5 (6.3)
58.5 (6.3)
18.8 (2.6)
Mean
81.7 (13.0)
764.0 (79.8)
(0.15)
(0.48)
(0.20)
(0.43)
(0.66)
(0.20)
(0.45)
1.73 (0.32)
(0.12)
(0.06)
(0.03)
(0.09)
(0.06)
(0.07)
(0.03)
0.25 (0.04)
(142)
(264)
(209)
(269)
(18)
(288)
(76)
Note: Bf and Bc are biomass of fine roots and coarse roots; Rf and Rc are respiration of fine roots and coarse roots; Ra and Rs are root respiration at stand level and soil
respiration; RTf and RTc are respiration of fine roots and coarse roots at stand level. Values in parentheses are standard errors (n = 8).
During the whole year of 2007, soil respiration (Rs) ranged from
802 to 3192 nmol CO2 m2 s1 for A. crassicarpa, with the highest
and lowest occurring in July and April, respectively. For E.
urophylla, Rs ranged from 478 to 3359 nmol CO2 m2 s1, with
the highest and lowest occurring in July and January (Fig. 4). Soil
respiration under both A. crassicarpa and E. urophylla plantations
increased exponentially (p < 0.001, n = 16) with soil temperature
(Tables 3 and 4). The Q10 was 2.2 for A. crassicarpa and 2.9 for E.
urophylla based on the T/W models (Tables 3 and 4). Soil
respiration rates under the two plantations were not significantly
different.
Fine root respiration at the stand level (RTf) accounted for about
53% and coarse root respiration (RTc) accounted for 47% of total root
respiration (Ra) under A. crassicarpa plantation. The Ra at stand
level ranged from 95 to 472 nmol CO2 m2 s1. The highest Ra
value was detected in July and the lowest in November. The
contribution of Ra to Rs ranged from 7.4% in September to 23.9% in
June (Table 1). Ra at stand level was significantly correlated with
soil temperature (p = 0.012, n = 7) (Table 3 T). The T/W model
explained 88% of the variation in Ra and yielded higher r2 values
than univariate T model. The Q10 value based on the T/W models
was 4.1 for Ra (Table 3), which was lower than that based on the
univariate T model (5.5). Based on the T/W model (Eq. (3)), we
simulated annual-based stand level Ra by the soil temperature
(5 cm) and gravimetric water content (%) which were consecutively measured during year of 2007. Simulation results showed
that Ra ranged from 50 to 563 nmol CO2 m2 s1 with a mean value
of 252 nmol CO2 m2 s1, accounting for 5.5–25.4% of Rs with a
mean value of 13.3%. The total annual Ra of 2007 at stand level was
96 kg C m2 y1 (Fig. 4A).
Table 3
Regression models for the relationship between respiration rate, soil temperature
(T) and gravimetric water content (W) of A. crassicarpa.
Table 4
Regression models for the relationship between respiration rate, soil temperature
(T) and gravimetric water content (W) of E. urophylla.
models were 4.2 and 2.1 for Rf and Rc (Table 3 T/W), which were
lower than that based on the univariate T model (Table 3, T).
For E. urophylla, root respiration rates ranged from 0.72 to
2.59 nmol CO2 g root1 s1 for fine roots and from 0.11 to
0.41 nmol CO2 g root1 s1 for coarse roots. The highest rate
occurred in July for both root size classes. The lowest rate occurred
in June for fine roots, and in November for coarse roots (Table 2).
The root respiration rates of E. urophylla was not significantly
correlated to either soil temperature or soil moisture (Table 4).
However, the T/W model yielded higher r2 values than T or W
model alone (Table 4) and explained 64% and 24% of the variation
in Rf and Rc under E. urophylla plantation. The Q10 values based on
the T/W models were 2.8 and 2.1 for Rf and Rc (Table 4 T/W), which
were higher than that based on the univariate T model (Table 4, T).
3.3. Soil surface CO2 efflux and up-scaling root respiration to
the stand level
b0
Respiration
b1
r2
p
Q10
eb1 T
(T) R ¼ b0
Fine root (Rf)
Coarse root (Rc)
Stand level root respiration (Ra)
Soil respiration (Rs)
Respiration
b0
b1
p
r2
Q10
0.22
0.07
51.36
73.58
0.080
0.057
0.070
0.125
0.110
0.198
0.034
<0.001
0.09
0.06
0.50
0.66
2.21
1.77
2.01
3.50
eb1 T
0.05
0.04
2.91
170.51
0.153
0.106
0.170
0.094
0.45
0.17
0.80
0.63
<0.001
0.068
0.012
<0.001
4.61
2.88
5.47
2.57
(T) R ¼ b0
Fine root (Rf)
Coarse root (Rc)
Stand level root respiration (Ra)
Soil respiration (Rs)
Respiration
b2
b3
p
r2
Respiration
b2
b3
p
r2
(W) R = b2 + b3W
Fine root (Rf)
Coarse root (Rc)
Stand level root respiration (Ra)
Soil respiration (Rs)
4.49
1.19
600.55
757.14
0.324
0.087
41.86
113.34
0.041
0.196
0.059
0.089
0.60
0.31
0.54
0.19
(W) R = b2 + b3W
Fine root (Rf)
Coarse root (Rc)
Stand level root respiration (Ra)
Soil respiration (Rs)
1.27
0.07
10.63
2842.10
0.152
0.017
14.95
222.40
0.201
0.293
0.373
0.021
0.30
0.22
0.16
0.33
Q10
Respiration
b0
Respiration
b1
b2
p
r2
eb 1 T W b 2
(T/W) R ¼ b0
Fine root (Rf)
0.00089
Coarse root (Rc)
0.00074
Stand level root respiration (Ra)
0.559
Soil respiration (Rs)
97.83
b0
b1
b2
p
r2
Q10
0.62
0.24
0.66
0.68
2.75
2.10
2.27
2.85
eb1 T W b2
0.143
0.075
0.141
0.079
1.354
0.028
1.581
0.045
0.854
0.004
0.307 <0.001
0.64
0.33
0.88
0.64
4.17
2.12
4.10
2.21
Note: Rf and Rc are respiration of fine roots and coarse roots (nmol CO2 g root1 s1);
Ra and Rs are root respiration at stand level and soil respiration (nmol CO2 m2 s1); T
is soil temperature (8C) at 5 cm depth; W is gravimetric water content (%) of topsoil (0–
20 cm); Q10 was the multiplier to the respiration rate for a 10 8C increase in
temperature.
(T/W) R ¼ b0
Fine root (Rf)
0.135
Coarse root (Rc)
0.107
Stand level root respiration (Ra) 208.27
Soil respiration (Rs)
12.38
0.101
0.004
0.014
0.074 0.180
0.073
0.082 0.555
0.017
0.105
0.769 <0.001
Note: Rf and Rc are respiration of fine roots and coarse roots (nmol CO2 g root1 s1);
Ra and Rs are root respiration at stand level and soil respiration (nmol CO2 m2 s1); T
is soil temperature (8C) at 5 cm depth; W is gravimetric water content (%) of topsoil (0–
20 cm); Q10 was the multiplier to the respiration rate for a 10 8C increase in
temperature.
2094
D. Chen et al. / Forest Ecology and Management 257 (2009) 2088–2097
Fig. 4. Heterotrophic respiration (Rh) and root respiration at the stand level (Ra) simulated using T/M model which based on the soil temperature (T) and soil moisture (W)
under A. crassicarpa and E. urophylla plantations during the year of 2007 (A–B): The Ra was calculated by soil temperature (8C) at 5 cm depth and gravimetric water content (%)
of topsoil (0–20 cm) with the Eq. (3), all the constants showed in Tables 3 and 4; the Rh was the result of Ra subtracted from soil respiration.
Under E. urophylla plantation, the RTf accounted for about 42% and
RTc accounted for about 58% of Ra. The Ra at stand level ranged from
190 to 517 nmol CO2 m2 s1. The highest Ra value was detected in
July and the lowest in June. The contribution of Ra to Rs ranged from
7.4% in September to 28.3% in June (Table 2). Ra at stand level was
significantly correlated with soil temperature (p = 0.034, n = 7)
(Table 4 T). The T/W model explained 69% of the variation in Ra and
also yielded higher r2 values than univariate T model. The Q10 value
based on the T/W models was 3.3 for Ra (Table 4), which was higher
than that based on the univariate T model (2.0). The annual-based
stand level Ra of 2007 was estimated by the soil temperature and
gravimetric water content (Eq. (3)). Simulation results showed that
the Ra ranged from 147 to 462 nmol CO2 m2 s1 with a mean value
of 280 nmol CO2 m2 s1, which accounted for 11.1–35.2% of Rs with
a mean value of 18.4% during the year 2007. The total annual Ra of
2007 at stand level was 106 kg C m2 y1 (Fig. 4B).
4. Discussion
The biometric method is an alternative approach to estimate
forest NEP, and the accurate prediction of NEP not only relies on the
measurements of NPP but also relies on the separation of soil
respiration (Rs) into root respiration (Ra) and soil microbial
respiration (Rh). In the present study, the stand level root
respiration was estimated based on the measurements of biomass
of fine and coarse roots and their specific rates of respiration. We
found the specific root respiration was significantly different
between fine and coarse root for both A. crassicarpa and E. urophylla
specie. We also found that the contribution of root respiration to
soil respiration and the temperature sensitivity of root respiration
varied with plant species and root diameters. The reasons for these
differences were discussed in detail in the following sections.
4.1. Fine root and coarse root respiration
The classification of roots varies in different studies with no
fixed standard. 1 mm (Edwards and Norby, 1998), 2 mm (Jackson
et al., 1997; Vogt et al., 1996) or 5 mm (Gansert, 1994; Widen and
Majdi, 2001) has been considered as the dividing diameter
between fine roots and coarse roots in various studies (Desrochers
et al., 2002). However, fine roots are often referred to those with
diameter less than 2 mm because these roots have very different
physiological functions in C/N ratio, metabolic activity, and
nutrient uptake capacity compared to the roots with diameter
greater than 2 mm (Wells and Eissenstat, 2001; Pregitzer, 2002). In
the present study, the respiration rate was relatively stable when
the root diameter was greater than 5 mm for both A. crassicarpa
and E. urophylla species; therefore 5 mm was used as the dividing
diameter between fine roots and coarse roots for our root
respiration research.
Fine root respiration rate was higher than that of coarse roots,
which was consistent with the previous studies (Gansert, 1994;
Pregitzer et al., 1998; Widen and Majdi, 2001). It was reported that
the root respiration rate was positively related to tissue N content
(Pregitzer et al., 1998; Ryan et al., 1996; Burton et al., 2002), and this
was supported by our results. We found that the tissue N content of
fine roots was significantly higher than that of coarse roots for both
A. crassicarpa (14.4 0.8 g kg1 vs. 8.3 0.5 g kg1) and E. urophylla
(5.5 0.5 g kg1 vs. 4.4 0.5 g kg1). In addition, there were inherent
variations between the fine root and coarse roots in terms of nutrient
and water uptake or transport, resulting in different rates of metabolic
activities such as growth respiration between fine and coarse roots
(Lambers et al., 1996; Vose and Ryan, 2002). Overall, the root
respiration of E. urophylla was lower than that of A. crassicarpa, Which
can also be ascribed to the fact that the root tissue N content of
E. urophylla (4.7 0.4 g kg1) was significantly lower than that of
A. crassicarpa (11.1 0.1 g kg1).
Although specific respiration of coarse root (Rc) was much lower
than that of fine root (Rf). The stand level respiration of coarse root
(RTc) and fine root (RTf) almost equally contributed to total root
respiration (Ra) because the biomass of coarse root (Bc) was much
greater than that of fine root (Bf). However, the contribution of RTc to
RT decreased from February to November with plant growth,
indicating that the fine roots play a more important role in the
growing season. Overall, the contribution of coarse root respiration
in the present study was higher than the values reported in the
literature (Linder and Troeng, 1981; Ryan et al., 1996; Widen and
Majdi, 2001; Marsden et al., 2008). Marsden et al. (2008) estimated
fine root and coarse root respiration rates and extrapolated to the
stand level using biomasses from the literature on Eucalyptus
stands, and they found the contribution of RTc to Ra was about 30%,
which was much lower than our values. The different RTc
contribution to Ra reported in these studies can partly be ascribed
to difficulties in accurate estimation of fine root and coarse root
biomass (Vogt et al., 1998). The coarse root respiration at the stand
level accounted for a large portion of total root respiration for the
two plantations in the present study, demonstrating that the coarse
root respiration should be considered when estimating the root
respiration at the stand level.
4.2. Contribution of root respiration to soil respiration
Our up-scaling method provided an independent estimate of root
respiration at the stand level, which can be compared with other
D. Chen et al. / Forest Ecology and Management 257 (2009) 2088–2097
techniques. Using this direct up-scaling technique, we obtained the
estimates of 130–472 and 190–517 nmol CO2 m2 s1 for Ra of A.
crassicarpa and E. urophylla from February to November, which
accounted for 14% and 19% of soil respiration. We extrapolated the Ra
at the stand level to the whole year using the T/W model in which
both soil temperature and moisture were taken into account
(Eq. (3)). The Ra accounted for 13% and 18% of soil respiration after
extrapolation for A. crassicarpa and E. urophylla plantations,
respectively. To our surprise, the estimated contribution of Ra to
soil respiration using different approaches was very similar. At stand
level, total annual Ra of A. crassicarpa and E. urophylla were
96 kg C m2 y1 and 106 kg C m2 y1, respectively.
These estimates were at the lower end of the range (10–90%)
reported in the literature (Hanson et al., 2000; Subke et al., 2006)
and were lower than the mean of 46% for forest soil. Widen and
Majdi (2001) found that the percentage of soil CO2 efflux from
roots was 33–62% in May, but decreased to 12–16% in October for a
mixed pine and spruce forest. Epron et al. (2006) reported that root
respiration contributed 59% to total soil respiration for an
Eucalyptus stand using the root exclusion approach. Marsden
et al. (2008) found that root respiration contributed 70% or 48% to
total soil respiration of a Eucalyptus forest using the up-scaling
technique based on root-excision method or using the root
exclusion approach, respectively. We considered that the discrepancies in the proportion of root respiration to soil respiration
might not only vary with plant species but also vary with the
method used for root respiration estimation. As Rakonczay et al.
(1997) pointed out, the root respiration might be overestimated by
using root-excision method. We considered that the low values of
root respiration to soil respiration in the present study were
probably resulted from the following two reasons: (1) It is likely we
have underestimated the fine root biomass and its contribution to
total root respiration during the growing season. We hypothesized
that the variation of fine root biomass is proportional to coarse root
biomass. In fact, fine root does not simply increase with the
increment of coarse root biomass because fine root biomass
(especially <1 mm) can be highly dynamic seasonally (Hendrick
and Pregitzer, 1993a, 1993b, 1996; Burton et al., 2000; Tingey et al.,
2003; Comas et al., 2005). Jourdan et al. (2008) reported that the
fine root biomass was higher in wet season (105 g m2) than in dry
season (75 g m2) in another 1.5-year-old Eucalyptus stand in
Brazil. M’bou et al. (2008) also found that the elongation rate of fine
roots was higher in the rainy season (ca. 0.35 cm d1) than in the
dry season (ca. 0.26 cm d1) in a two-year-old Eucalyptus
plantation. Fine root biomass, particularly for those with diameter
less than 1 mm, could be underestimated using soil coring method
although this method was widely used in previous studies (Kurz
and Kimmins, 1987; Hendrick and Pregitzer, 1992). It was reported
that elutriating the residual soils could increase the recovery of fine
root biomass (<1 mm) to 150% of that obtained without elutriation
(Pregitzer et al., 2008). In addition, the sampling depth also affects
the root biomass estimation using the soil coring method (Vogt
et al., 1998). For example, Marsden et al. (2008) reported that fine
roots (<2 mm diameter) in the top 30 cm of soil revealed 46% of all
fine root biomass measured down to a depth of 1.2 m. In the
present study, we found that fine root (<5 mm diameter) biomass
including live and dead roots in the top 20 cm of soil accounted for
94% of total fine root biomass in 40 cm soil core for A. crassicarpa
plantation. For E. urophylla, fine root biomass in the top 20 cm
accounted for 60% of total fine root biomass measured to a depth of
40 cm. It will be helpful to use minirhizotron in future studies to
estimate the fine root production, mortality and longevity
(Hendrick and Pregitzer, 1992; Burton et al., 2000; Ruess et al.,
2003). (2) We might have underestimated the specific root
respiration because we probably overestimated the root biomass
inside the root chamber. In the present study, the root biomass was
2095
only measured at the end of experiment but the ingrowth of fine
roots was not monitored during the experiment. In future efforts,
an image of the root branching system taken at the beginning and
the end of the experiment can help to estimate the root ingrowth
inside the chamber during the experiment.
4.3. Soil temperature sensitivity of root respiration
Soil temperature and moisture are considered to be the most
important biophysical parameters controlling the temporal variation of root respiration. Root respiration of A. crassicarpa showed a
clear seasonal pattern (Table 1), and it was higher in the wet season
(May, June, and August) than in the dry season (February, and
November). This seasonal pattern was clearly correlated with soil
temperature and soil moisture (Table 3). Burton and Pregitzer
(2003) reported that soil temperature and soil water availability
together explained 76% of the variation in root respiration rates in
the red pine plantation and 71% of the variation in the sugar maple
forest. In the present study, the T/W model explained higher
fraction of the variation in root respiration than that of the
univariate T model, suggesting not only soil temperature but also
soil moisture affects root respiration.
Recent studies have suggested that the Q10 values derived from
different models are different (Fang and Moncrieff, 2001; Xu and
Qi, 2001; Tang et al., 2006b). The Q10 values derived from T/W
models were lower for A. crassicarpa but higher for E. urophylla
compared to those calculated from T models (Table 3). Apparently,
taking soil moisture into consideration in the T/W models caused
the differences in the Q10 values, it is likely that the effect of soil
temperature on CO2 efflux is confounded by soil moisture since soil
moisture and temperature covaried across seasons. High moisture
occurring simultaneously with high temperature is common in
subtropical region. Therefore, Q10 values derived from the T/W
models, which included the confounding effect of soil moisture, are
more accurate in representing the temperature dependence of
respiration rates than those derived from T models without
considering soil moisture (Xu and Qi, 2001; Burton et al., 2004;
Tang et al., 2006b).
Burton et al. (2002) reported that the Q10 values of root
respiration were not significantly different among forest types.
However, the Q10 values of root respiration of A. crassicarpa were
higher than that of E. urophylla in the present study. It was reported
that root respiration can be partitioned into maintenance
respiration and growth respiration, and the maintenance respiration is more sensitive to temperature than growth respiration
(Amthor, 2000; Saxe et al., 2001). In other words, the proportion of
maintenance respiration or growth respiration could affect the Q10
values of root respiration, a higher proportion of maintenance
respiration or a lower proportion of growth respiration would
result in a higher Q10 value of root respiration. The ratio of
maintenance respiration of A. crassicarpa (68.4 0.1%) was
significantly higher than that of E. urophylla (46.2 0.1%) based on
our measurements, which might partially explain for a higher Q10
value of root respiration of A. crassicarpa. Coincidently, the growth
respiration of A. crassicarpa could be lower than that of E. urophylla
based on our measurements of plant biomass. Our results showed
that the annual increments of DBH and height of A. crassicarpa
(3.7 cm, 2.8 m) were significantly lower that that of E. urophylla
(7.8 cm, 3.6 m). It was reported that the growth respiration rate
would increase with the rate of biomass increment (Adu-Bredu et al.,
1997; Ceschia et al., 2002).
In contrast to root respiration (Ra), the Q10 values of soil
respiration (Rs) for A. crassicarpa was lower than that for E.
urophylla probably due to that the contribution of Ra to Rs of A.
crassicarpa (13.2 1.6%) was lower (p = 0.065, n = 16) than that of E.
urophylla (18.4 1.7%). It was reported that root respiration was
2096
D. Chen et al. / Forest Ecology and Management 257 (2009) 2088–2097
more sensitive to temperature than soil microbial respiration (Boone
et al., 1998).
4.4. Improve the accuracy of the direct up-scaling model
The accuracy of this direct up-scaling model has been hampered
by limited quantitative description of the dynamics of belowground biomass. Most existing techniques to measure fine root
biomass and production are labor intensive and controversial
(Vogt et al., 1998), which has resulted in a scarcity of accurate
estimation on roots compared to the aboveground components.
The estimates of root biomass increment, based on allometric
equations which were derived from limited numbers of whole tree
harvests, suggest that the root growth component is generally a
fairly small (<20%) fraction of above-ground increment (Perala and
Alban, 1994). In fact, the fine root carbon pool is the larger and
more variable component of below-ground productivity, but the
accuracy of estimation for this component and its turnover has
been a challenge to us. Numerous studies have indicated that the
soil coring approach yielded lower estimates of fine root
production compared to those estimated using minirhizotron
techniques (Hendrick and Pregitzer, 1993a, 1993b; Rytter, 1999;
Hendricks et al., 2006). As for the measurements of root respiration
in the present study, we only focused on two size classes of root
diameters (diameter < 5 mm and diameter > 5 mm) as an upscaling variable but neglected the variance of other diameters.
More detailed measurement of root respiration for other size
classes of root diameters and the structure of the root system for
the plantations would definitely produce a better estimation of
root respiration at the stand level.
Despite there are issues concerning the accuracy of measurements of root biomass and root respiration, the method employed
in the present study can be used as an alternative approach for
estimation of stand level root respiration of monoculture plantations. After we calculate the NPP of the plantation, this direct upscaling model can provide an approach to quantify NEP of the
monoculture forest. It is noteworthy to point out that the
plantations in this study were at the early developmental stage
and most of the roots had not been developed to large structural
roots. Therefore, the results of this study might be only meaningful
for young plantations, particularly when linking to estimation of C
sequestration and C cycling. The reliability of this approach needs
to be tested for other developmental stages of the monoculture
plantations and mixed-species plantations.
Acknowledgements
This work was financially supported by National Science
Foundation of China (30630015), Knowledge Innovation Program
and ‘‘100 Elites Program’’ of the Chinese Academy of Sciences
(KZCX2-YW-413). We thank the editor-in-chief and three anonymous reviewers for their insightful comments. We also thank
Prof. Murray B. McBride for polishing the language of the
manuscript.
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