Geoderma 120 (2004) 283 – 295
www.elsevier.com/locate/geoderma
Simulating trends in soil organic carbon of an Acrisol under
no-tillage and disc-plow systems using the Century model
Luiz Fernando Carvalho Leite a, Eduardo de Sá Mendoncßa b,*,
Pedro Luiz Oliveirade de Almeida Machado c, Elpı́dio Inácio Fernandes Filho b,
Júlio César Lima Neves b
a
Empresa Estadual de Pesquisa Agropecuária da Paraı́ba-EMEPA, Rua Eurı́pedes Tavares, 210, 58013-290 João Pessoa, Paraı́ba, Brazil
b
Departamento de Solos, Universidade Federal de Vicßosa, 36571-000 Vicßosa, Minas Gerais, Brazil
c
Embrapa Solos-EMBRAPA, Rua Jardim Botânico 1024, 22460-000 Jardim Botânico, Rio de Janeiro, Brazil
Received 22 October 2002; received in revised form 22 July 2003; accepted 17 September 2003
Available online 10 December 2003
Abstract
Soil organic matter (SOM) and its different pools have key importance in nutrient availability, soil structure, in the flux of trace
gases between land surface and the atmosphere, and thus improving soil health. This is particularly critical for tropical soils. The
rates of accumulation and decomposition of carbon in SOM are influenced by several factors that are best embodied by simulation
models. However, little is known about the performance of SOM simulation model in an acid tropical soil under different tillage
systems including no-tillage (NT). Our objective was to simulate soil organic matter dynamics on an Acrisol under no-tillage and
different plowed systems using Century model. Tillage systems consisted of no-tillage, disc plow, heavy disc harrow followed by
disc plow, and heavy disc harrow. Soil C stocks simulated by Century model showed tendency to recovery only under no-tillage.
Also, simulated amounts of C stocks of slow and active pools were more sensitive to management impacts than total organic C.
The values estimated by Century of soil C stocks and organic carbon in the slow and passive pools fitted satisfactorily with the
measured data. Thus fitted, except for the active pool, Century showed acceptable performance in the prediction of SOM dynamics
in an acid tropical soil.
D 2003 Elsevier B.V. All rights reserved.
Keywords: Acidic tropical soils; Soil carbon fractions; Long-term experiments; Century model
1. Introduction
Soil organic matter (SOM) is an important component of acid tropical soils and its significance can be
seen on the positive effects on Ferralsol cation exchange capacity, size and stability of aggregates,
* Corresponding author.
E-mail address: [email protected] (E. de Sá Mendoncßa).
0016-7061/$ - see front matter D 2003 Elsevier B.V. All rights reserved.
doi:10.1016/j.geoderma.2003.09.010
improved moisture and soil structure for plant growth
(Goedert et al., 1997). Also, SOM has large influence
on the flux of the trace greenhouse gases between land
surface and the atmosphere (Batjes, 1996). Soil cultivation often leads to diminution of SOM content
(Castro Filho et al., 1991), but conservation tillage
such as no-tillage can improve soil conditions to those
found in forest soils (Machado and Silva, 2001).
Because of cost reductions and soil erosion control,
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L.F. Carvalho Leite et al. / Geoderma 120 (2004) 283–295
no tillage is widely used in Brazil over an area of 14
million ha (Pereira, 2002).
No tillage, combined with crop rotation involving
cover crops, favors the accumulation of plant residues
on the soil surface (Machado and Silva, 2001). In a
large study conducted in the USA, Kern and Johnson
(1993) reported that the widespread conversion of
major field crop production from conventional tillage
(mouldboard plow) to conservation tillage would
change the soil system from a source to a sink of
atmospheric carbon. Similar observations were also
reported later for European soils (Smith et al., 1997a).
These findings show the potential for agriculture to
contribute to global carbon mitigation, particularly
through no-tillage.
The ability to predict the effects of environment
(e.g. climate and atmospheric composition) and landuse change on SOM dynamics is of utmost importance in formulating environmental and agricultural
policies (Smith et al., 1997b). Modeling is a powerful
means to simulate a range of intricate processes and
predict soil organic matter changes for long time
periods (Paustian et al., 1992).
Century is a model of terrestrial C, N, P, and S
dynamics that use a four pool SOM submodel. Century has been successfully used in temperate ecosystems (Parton and Rasmussen, 1994; Kelly et al., 1997;
Del Grosso et al., 2001), but in spite of some studies
about modeling tropical agroecosystems (Parton et al.,
1989; Motavalli et al., 1994), no information is
available on the use of mathematical models on the
dynamics of soil organic carbon in Acrisol under notillage. Our objective was to simulate soil organic
matter dynamics on an Acrisol under no-tillage and
different plowed systems commonly used in Brazil
using Century model.
2. Material and methods
2.1. Experimental site
Simulations with the version 4 of the Century
model were carried out for an experimental site
established in 1985 at the Experimental Station of
the Federal University of Vicßosa, in Coimbra, State of
Minas Gerais, Brazil (20j45S and 42j51W; 700 m
asl). The mean annual temperature is 19 jC and
average rainfall is 1350 mm, and roughly two-thirds
of this rain falls in the warmer season of the year from
October to April.
The area was covered by Atlantic Forest until 1930
and was cultivated for 54 years with subsistence
crops, such as maize (Zea mays L.) and common
bean species. The soil in the experimental area is a
loamy Acrisol (Argissolo Vermelho-Amarelo, Brazilian Classification System; Typic Kandiudult, US Taxonomy) and some chemical and physical characteristics are shown in Table 1.
The experiment started at 1985 and consisted of
four soil management systems, arranged in a complete
randomized block design, with four replications. Plots
were 4 11 m under maize/fallow/soybean succession. The tillage treatments were:
1. No tillage (NT)—no disturbance to the soil other
than sowing operation;
2. Disk plowing (DP)—plowing at 20 to 25 cm depth
with a three-fixed disk plow, in a single pass;
3. Heavy disk harrow + disk plowing (HHDP)—one
single pass at 0– 15 cm using a heavy disk harrow
with 20 disks followed by disk plowing at 20– 25
cm depth, with a three-fixed disk plow;
4. Heavy disk harrow (HH)—one harrowing at 10 to
15 cm depth with a heavy disk harrower of 20
disks weighing approximately 2 t;
In addition, as a reference, samples were taken
from an area under secondary Atlantic Forest (AF),
adjacent to the experiment, (100 m away) in the same
soil type. At the middleslope, four areas (4 4 m)
Table 1
Chemical and physical characteristics of an Acrisol (0 – 20 cm layer)
under different tillage systems from the State of Minas Gerais,
Brazil
Treatmenta pH
TOC
TN
Clay
Bulk
(H2O) (dag kg 1) (dag kg 1) (dag kg 1) density
(mg m 3)
NT
DP
HHPD
HH
AF
4.97
5.05
5.05
5.00
5.48
1.46
1.28
1.28
1.26
2.83
0.12
0.10
0.10
0.11
0.22
41
38
39
37
46
1.32
1.22
1.21
1.24
1.13
TOC: total organic carbon, TN: total nitrogen.
a
NT: no tillage; DP: disk plow; HHDP: heavy disk harrow + disk plow; HH: heavy harrow; AF: secondary Atlantic Forest.
L.F. Carvalho Leite et al. / Geoderma 120 (2004) 283–295
were placed along a 100-m transect in which soil
samples were collected.
2.2. Chemical analysis
Soil samples were collected, in April 2000, just
after the harvest period. In each plot, eight topsoil
samples (0 – 20 cm) were collected and combined
into one composite sample. In the area under Atlantic Forest, 15 samples were collected from each
sampling area (n = 4) and bulked into one sample.
The samples were ground to pass a 2-mm sieve.
An aliquot of 100 g was separated and kept refrigerated at 4 – 8 jC before microbial biomass analysis. For all remaining analyses, the soil samples
were air-dried.
Total organic carbon (TOC) was obtained by wet
digestion with a mixture of potassium dichromate and
sulfuric acid, under heating (Yeomans and Bremner,
1988). Total N was measured in the soil samples with
a sulfuric digestion followed by determination in the
Kjedahl distillation (Bremner, 1996). Measurement of
microbial biomass was conducted by the irradiation –
extraction method—using microwave (Islam and
Weil, 1998), 0.5 mol l 1 K2SO4 as extractant and
the biomass C was determined by wet combustion
(Yeomans and Bremner, 1988). The factor (KC) used
to convert the flow of C for the microbial biomass C
(CMB) was 0.33 (Sparling and West, 1988). The CMB
was used as an estimate of the active C pool (Paul,
1984; Motavalli et al., 1994). The free-light organic
carbon fraction (CLF) was determined by flotation in
NaI solution (d = 1.8 g cm 3) as proposed by Sohi et
al. (2001). The isolated material was dried at 105 jC
for 72 h. The CLF, quantified by dry combustion
(Perkin Elmer 2400 CHNS/O elemental analyzer),
was further used as an estimate of the slow C pool.
Passive C pool was calculated using the following
equation:
Passive C ¼ TOC ðCMB þ CLF Þ
Bulk soil density was determined on nondeformed
soil samples collected from a single field replicate.
The values of bulk soil density were used to calculate
SOM pools based on an equivalent soil mass (Angers
et al., 1997; Peterson et al., 1998).
285
2.3. Model parameterization
The Century SOM model was originally developed
and tested on data sets mainly from grassland and
wheat – fallow agriculture in the US Great Plains
(Parton et al., 1987, 1988). All parameter values
determined from these previous studies were initially
left unchanged to provide more criterious evaluations
of the simulations. As given by Paustian et al. (1992),
these general or non-site specific parameters include
the maximum specific decomposition rates for each
compartment, the constants that splits the flows of
decomposition products and the parameters that control the effects of soil texture, lignin/N ratios, temperature, and moisture on decomposition rates.
Site-specific parameters and initial conditions, such
as soil texture (sand, silt and clay content), bulk
density, soil depth and total soil C and N content,
were given values obtained from the field experiment
at Coimbra. Monthly precipitation and mean maximum and minimum monthly temperatures from 1967
to 2000 were obtained from the weather station at the
Vicßosa Federal University. The parameter determining
potential crop productivity was based on the maximum production level observed during the course of
the field experiment in each treatment and temperature
curve, C/N ratios and lignin contents of biomass pools
were obtained through default crop parameterizations
distributed with Century model. The main input data
for the model are in Table 2.
Some model adjustments were made to improve
the tillage effects on SOM decomposition. First, the
plowing option was adjusted to increase its effect on
decomposition (Six et al., 1998). All clteff values
(cultivation’s effect on decomposition) for the DP,
HHDP and HH were changed from 1.6 to 5 (Table
2). The second change was added to increase the
length of time which plowing effects decomposition.
Since Century uses a monthly time-step each action
only affects SOM dynamics for that specific month
although some studies have shown that plowing
affects decomposition for several months (Metherell
et al., 1995). Thus, an option called ‘‘Additional
plowing effect’’ was used in the months following
plowing in order to keep the decomposition rates at
higher levels (Manies et al., 2000).
To initialize the percentage of total SOM in each of
the three pools (active, slow and passive) used indirect
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Table 2
Model input for simulation of tillage systems using version 4 of the
Century model
Value
Soil variables
Texture (% sand,
% silt, % clay)
Bulk density (mg m 3)
Initial SOM
(g C m 2; C/N)
Active surface
Active soil
Slow soil
Passive soil
Monthly weather variables
Mean total precipitation
(cm month 1)
Mean maximum
temperature (jC)
Mean minimum
temperature (jC)
Cultivation variables
Multiplier for increased
decomposition
Active pool
Slow pool
Passive pool
38, 16, 46
1, 13
50, 12,5
159, 9
1776, 22
4460, 12
14
14.8
26.4
1.0
(NT); 1,8 (DP);
2.0 (HHDP); 1.6 (HH)
1.0 (NT); 4.0 (DP);
5.0 (HHDP); 3.0 (HH)
1.0 (NT); 1.8 (DP);
2.0 (HHDP); 1.6 (HH)
Carbon pool values were obtained from direct method. NT: no
tillage; DP: disc plow; HHDP: heavy disk harrow + disk plow; HH:
heavy harrow.
methods involving simulation of steady state organic
matter levels and direct methods using analytical
techniques. In the indirect method, Century model
parameterized all data including carbon pools for a
long term (6000 years) by equilibrium simulation.
Simulated values for carbon pools were used as input
variables for simulation of land use change. To each
treatment, the model simulated SOM dynamics for 54
years representing forest conversion into cropland
(e.g. maize and bean production) and later, for 66
years, representing different tillage systems. In the
direct method, the initial soil carbon pool sizes under
Atlantic Forest were estimated by laboratory analysis
and similarly used in the indirect method. All Century
estimates were based on a 20-cm depth. Both simulated and measured values for TOC, active, slow and
passive pools in 2000 were subjected to linear regression and Pearson’s correlation. An average of these
data sets was taken from each treatment and subjected
to a Student’s t-test to determine the significance of
the coefficients at the 0.05 and 0.01 probability levels.
Simulations for nitrogen pools were also done for NT
and HHDP systems.
3. Results and discussion
3.1. Estimates of carbon pools by equilibrium values
Century model simulated the equilibrium values of
total organic carbon (TOC) and carbon pools (active,
slow and passive) for 6000 years. Compared to the
initial values, storage of both TOC and passive C pool
increased while active and slow carbon pools
remained generally constant (Fig. 1). The increase in
the passive carbon pool, reflected by TOC, is probably due to carbon pools that are highly recalcitrant,
physically protected against microbial attack and less
prone to oxidation. After reaching equilibrium, stocks
of TOC (64 mg ha 1) and active carbon pool (1.60
mg ha 1) were similar to those measured in the soil
under Atlantic Forest (Table 3). The stocks of TOC
are 3.9% higher than the value (61.5 mg ha 1) found
by Silveira et al. (2000) in another soil under Atlantic
Forest in the Piracicaba river basin, Brazil. The
estimated value of the slow carbon pool (30.1 mg
ha 1) was 42% higher than the measured value in the
forest soil. On the other hand, the estimated value of
Fig. 1. Modeled stocks of soil organic carbon (TOC) and organic
carbon pools of an Acrisol (0 – 20 cm) under Atlantic Forest.
L.F. Carvalho Leite et al. / Geoderma 120 (2004) 283–295
Table 3
Measured values of total organic carbon (TOC) and carbon pools
(active, slow and passive) of an Acrisol under Atlantic Forest
(Brazil)
Pools
Stocks (mg ha 1)
Total organic carbon
Active
Slow
Passive
63.95
1.59
17.4
44.9
( F 4.25)
( F 0.02)
( F 1.23)
( F 4.01)
Values in parenthesis represent the standard error of the mean.
the passive carbon pool (32.3 mg ha 1) was lower
than the measured data (Table 3). Hence, model fit to
measured slow and passive carbon pool was not good,
probably due to sizes of the passive pool higher in
287
tropical soils than the assumption of the Century
model.
Starting at initial values of carbon pools obtained
from the equilibrium simulation, Century estimates
for the stocks of TOC and carbon pools after 120
years decreased after changing forest into agriculture
(Fig. 2). Parfitt et al. (1997) studying the effects of
clay minerals and land use on organic matter pools
obtained similar results, i.e. a decrease of the TOC and
C pools after forest clearance and subsequently land
use under pasture and maize in an Inceptisol. In 1984,
before setting up the experiment, TOC stock was 28
mg ha 1, which were 56% lower than the initial value
predicted by the model (64 mg ha 1). In 2000, 15
years after the introduction of the tillage systems,
Fig. 2. Time variation of the stocks of TOC (A) and active (B), slow (C) and passive (D) carbon pools simulated by Century based on the initial
values obtained from the equilibrium simulation in the no-till (NT), disc plow (DP), heavy harrow followed by disc plow (HHDP) and heavy
harrow (HH).
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stocks of TOC in the soil under NT (29 mg ha 1)
showed an increase compared to the stocks of TOC in
the NT soil at the beginning of the experiment. This
was in contrast with DP (24.5 mg ha 1), HSPD (23.4
mg ha 1), and HH (25.2 mg ha 1) (Fig. 2). In 2050,
stocks of TOC in the soils under NT and plowed
systems were estimated as 26 and 15 mg ha 1,
respectively, thus showing less soil organic matter
degradation under no tillage.
Also in both active and slow pools, carbon stocks
diminished with the change from forest to cropland.
After the introduction of tillage systems, it was
observed less significant changes in the carbon stock
of active and slow pools. However, the amount of
passive carbon stocks in the soils under NT was
significantly higher. In 2000, the amount of organic
carbon in the soil under NT was 5 mg ha 1 higher
than the soils under DP, HHDP and HH systems. This
difference increased with time and in 2050 the stocks
of TOC in the soil under NT (23 mg ha 1) were
estimated as two times higher than the amounts in the
soils under DP (12.8 mg ha 1), HHDP (10.6 mg
ha 1), and HH (13.2 mg ha 1). These results show
the effect of soil disturbance by plowing, which favors
higher SOM mineralization rate and thus leads to an
increase in humification and in the passive carbon
pool.
3.2. Estimates of carbon pools by the measured
values
In the beginning of the field experiment, the stock
of TOC had declined to 40 mg ha 1 (Fig. 3), a
decrease of 37%, compared to the 63.95 mg ha 1,
initial value measured in the soil under Atlantic
Forest. The measured stocks of TOC were 20% lower
than the Century model equilibrium estimates of TOC
stocks. This difference is probably due to the higher
proportion of passive carbon pool in measured TOC.
As Century was originally developed for temperate
soils it is unlikely to be adjusted to tropical environments because organic –mineral associations in the
tropics are different from that observed in the temperate grasslands.
Tillage systems did not change the trend to decreasing stocks of carbon. Fifteen years after setting
up the field experiment the stocks of TOC in the soils
under NT, DP, HHDP and HH were 38, 32, 31, and 34
mg ha 1, respectively (Fig. 3). This tendency continued mainly due to conventional plowed systems and
in 2050 the projected stocks of TOC will be 34 mg
ha 1 in the soil under NT, and approximately 20 mg
ha 1 in the soils under DP, HHDP and HH. Despite
these results, soils under NT system were the only
ones to show a slight recovery in long term. Our
results are corroborated by Smith et al. (2001) that
observed at several soils groups and cultures rotation
that no tillage resulted, in long term, in the rate of
TOC gain rising as high as 0.15 mg ha 1 C year 1 in
Black Chernozem and Gleysolic soil groups whereas
the conventional tillage showed a loss of TOC.
Apparently, crop succession involving fallow, even
with no tillage, will demand too long time to reach
new equilibrium. This situation, however, may be
changed if a crop rotation involving a cover crop to
improve mulching (e.g. millet) is included or a ley
farming system is adopted. Ley farming involving
grass such as Brachiaria may greatly increase the
stock of soil organic carbon.
In 1984, carbon stocks of the active, slow and
passive pools were 0.2, 2 and 36 mg ha 1. These
values, compared to those initial values in the soil
under forest, represented a decrease of 87%, 89%, and
19%, respectively (Fig. 3). This diminution trend was
still observed even after the adoption of NT system,
which shows that although the soil has been under NT
for 15 years, no soil disturbance without cover crop
management as pointed out by Machado and Silva
(2001) hardly help to improve an increase of TOC in
acidic tropical soils. As reported by Parton et al.
(1987), Metherell et al. (1993) and Del Grosso et al.
(2001) our results also indicate the high sensitivity of
the active and slow carbon pools to changes in soil
management parallel to a higher stability of the
passive carbon pool. In 2000, compared to the
amounts in the beginning of the experiment, the
carbon stocks of the active pool in the plowed soils
increased approximately 0.3 mg ha 1. However,
Century simulation for 50 years showed a decrease
in the carbon stocks even in the soil under NT (Fig. 3),
indicating that, as reported by Machado and Silva
(2001), no tillage without cover crop management
(e.g. millet, sun hemp, black oat) hardly improve TOC
content of an acid tropical soil. In 2000, the modeled
carbon stocks of the slow pool in the soils under NT,
DP, HSDP and HH were 2.3, 2.8, 2.9 and 2.7 mg
L.F. Carvalho Leite et al. / Geoderma 120 (2004) 283–295
289
Fig. 3. Time variation of organic carbon stocks (TOC) (A) and active (B), slow (C), and passive (D) pools simulated by Century based on the
initial values obtained from direct method in the no-till (NT), disc plow (DP), heavy harrow followed by disc plow (HHDP) and heavy harrow
(HH).
ha 1, respectively (Fig. 3). The passive carbon pool
showed higher differentiation in carbon content
among tillage systems than the active and slow pools.
In 2000, the highest values of soil carbon stocks were
found in the soils under NT (36 mg ha 1) and HH (31
mg ha 1) and the lowest amounts were found in the
soils under DP (29.5 mg ha 1) and HHDP (28 mg
ha 1). This shows that, after setting up the field
experiment, only the carbon stocks of the soils under
NT did not decrease.
The highest proportion of soil TOC was found in
the passive pool (90%). Similar results were also
reported by Freixo et al. (2002) investigating tillage
and crop rotation interactions on organic carbon
fractions of a Ferralsol from southern Brazil. Increasing proportion of passive carbon pool with simulta-
neous decrease of active and slow carbon pools may
indicate soil organic matter degradation because the
latter pools are highly associated to microbial activity
and decomposition and are the most relevant pools to
nutrient cycling.
3.3. Nitrogen pools by the measured values
The replacement of the Atlantic Forest by agriculture also led to a decrease in the contents of total
nitrogen (TN). In 1984, TN stocks of the soil before
setting up the experiment were 3.34 mg ha 1. This
corresponds to a 32% decrease relative to the soil
under forest (Fig. 4). Similar to what was observed for
TOC, the stocks of TN decreased in the soils under
NT and HHDP systems. However, this decrease was
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L.F. Carvalho Leite et al. / Geoderma 120 (2004) 283–295
Fig. 4. Dynamics of stocks of total nitrogen (TN) (A) and active (B), slow (C) and passive (D) nitrogen pools simulated by Century model at 0 –
20 cm depth. NT: no-tillage; HHDP: heavy harrow followed by disc plow.
less pronounced in the soil under NT than under
HHDP. Although N losses in the soil under no-tillage
were lower than those observed under plowed systems, there is an apparent need to include legume
plants in the crop rotation as cover crops. This would
increase N inputs through biological N fixation in
addition to returning plant residues to the soil to
supplement soil fertilization. The use of cover crops
to improve mulching in the tropics is strongly recommended in a crop rotation system to increase soil
carbon stocks (Machado and Silva, 2001).
From 1930 to 1984, N stocks in the active, slow
and passive pools followed similar trend of what was
observed for C stocks. The close relationship between
C and N can be observed in the nitrogen mineralization. Nitrogen pools in the N submodel can only be
mineralized if CO2 is lost in the corresponding pool of
the C submodel, whose decomposition rate can be
regulated by N, P and S availability.
Soil tillage caused an increase of TN of the active
pool of both NT and HHDP systems. However, until
the end of the simulation period, TN stocks decreased
to the same levels found in the beginning of the
experiment. In the N submodel, the active pool
represents the microbial biomass N (Parton et al.,
1987) and it can be assumed that in a short run the
limited amount of available carbon substrates will not
support biomass in soil under NT and HHDP systems.
The slow pool N stocks were also decreased after
deforestation. In 1984, N stock estimated by Century
model was 0.1 mg ha 1, which is approximately 85%
lower than the amount found in the soil under Atlantic
Forest. In 2000, similarly to what was observed in the
active pool, the N stocks in the slow pool were higher
in the soil under HHDP (0.22 mg ha 1) than in the
soil under NT (0.1 mg ha 1). From 2000 to 2050, N
stocks in the soil under NT were projected to tend to
increase up to 0.16 mg ha 1 while in the soil under
HHDP, N stocks remained stable at 0.18 mg ha 1
(Fig. 4). Hence, the tendency in the short term is that
the nitrogen stocks in the soil under NT will be similar
or even higher than those found in the soil under HH.
In the passive pool, the decrease in the N stocks
after changing forest to agriculture was less pronounced than that observed in the active and slow
pool. This is probably due to the high recalcitrance of
the passive pool (Romanyá et al., 2000). For the
simulated period, contrary to the values observed in
L.F. Carvalho Leite et al. / Geoderma 120 (2004) 283–295
the active and slow pools, N stocks in the passive pool
were higher in the soil under NT than under HHDP.
After 15 years, soil N stocks were 3.1 mg ha 1 for
NT system and 2.4 mg ha 1 for HHDP system.
Estimates for 2050 showed a significant decrease in
nitrogen stocks of soils under HHDP. In this year, N
stocks in the soil under NT were 2.7 mg ha 1, which
is approximately 47% higher than the N stocks in the
soil under HHDP (Fig. 4).
3.4. Comparison between measured and simulated C
pools using Century model
In 2000, the Century model simulated TOC in
different tillage systems showed similar patterns to
those observed in the measured TOC data, especially
in the soil under NT (Fig. 5). In the soils under DP,
HHDP and HH the stocks of TOC estimated by
Century were higher than those shown by measurements, but differences were 4%, 0.4% and 7%,
respectively. Similar trends were observed dividing
TOC into 70% passive carbon, 27% slow carbon and
3% active carbon. Falloon and Smith (2002), in their
modeling of the arable site at Martonvasar (Hungary)
divided TOC into similar proportions, but resulted in
an overestimation of measured TOC. A reasonable fit
to the measured data was found using 34% passive
carbon, 63% slow carbon and 2.6% active carbon. In
our study, the higher proportion of the passive carbon
pool than the other pools enabled an optimum fit
between measured and Century model values. Compared to labile carbon fractions, in tropical soils the
largest TOC stocks are humified soil organic matter
probably due climatic conditions favoring microbial
decomposition all over the year and also chemical and
physical stability (Bayer et al., 2002; Leite et al.,
2003). It is well known that caolinitic soils, such as
the Acrisol of our study, are originally well structured
with adequate aggregate size distribution to promote
drainage (El-Swaify, 1980). Furthermore, differences
between tropical/subtropical and temperate soils suggest the need for parameterization of the Century
model using regional data and measured carbon pools
thus contributing to more adequate modeling in the
tropics. However, reasonable Century model fit to the
measured TOC values were reported for both temperate (Mikhailova et al., 2000; Alvarez, 2001) and
tropical (Parton et al., 1989; Motavalli et al., 1994)
291
soils. This shows the potential of Century model to
simulate soil organic carbon changes in soils under
different tillage systems and its sensitivity to distinguish organic carbon changes due to different tillage
systems.
Compared to the measured data obtained by microbial biomass carbon, in all tillage systems, the C
stocks of the active pool simulated by the Century
model were underestimated (Fig. 5). The differences
between simulated and measured data of C stocks
were 70%, 52%, 52% and 51% for NT, DP, HHDP
and HH, respectively. Similarly, Motavalli et al.
(1994) studying forest soils from Colombia, Peru
and Brazil with varying mineralogy reported that the
values of dissolved and biomass carbon stocks were
larger than Century simulated values. In oxidic soils,
Motavalli et al. (1994) reported that the simulated
values were 45%, 51% and 39% higher than the
measured values in Valencß a, Ouro Preto e Una
(Brazil), respectively. In both studies, the results are
probably related to factors that control C to the active
pool. The Century model uses soil humidity, soil
temperature, soil texture and management as regulators of the active pool. However, besides environmental aspects, microbial growth is affected by substrate
availability (organic matter) and soil chemical properties (e.g. soil pH, N content) that are not taken into
account by the model. Also, the mechanisms that
describe C exudation by roots and its microbial
metabolism are not clearly defined by the model and
the lack of these mechanisms in the model may
contribute to its inaccuracy. Additionally, the decomposition rate of the active pool is likely to be overestimated or the kEC value needs to be calibrated for
acid tropical soils. Joergensen (1996) investigated the
effects of soil properties and different form of land use
on the calibration of the kEC value and found that a
kEC value of 0.38 can be recommended for C analysis
by dichromate consumption and a kEC value of 0.45
for that by UV-per sulfate or oven oxidation.
Compared to the measured data, apart from the soil
under HHDP, the C values of the slow pool simulated
by the Century model were underestimated (Fig. 5).
However, differences between measured and simulated values were small: 13%, 14%, and 16% for NT, DP
and HH systems, respectively (Fig. 5). This suggests
that also in tropical soils, the carbon of the free-light
fraction may represent the slow pool as proposed by
292
L.F. Carvalho Leite et al. / Geoderma 120 (2004) 283–295
Fig. 5. Measured and simulated total organic carbon (TOC) (A), active (B), slow (C) and passive (D) carbon pool, and total nitrogen (TN) (E) in
different soil management systems. NT: no-tillage; DP: disk plow; HHDP: heavy disk harrow followed by disc plow and light harrowings; HH:
heavy disk harrowing (n = 4 for measured values).
Cambardella and Elliott (1992). On the other hand,
Motavalli et al. (1994) showed that measured stocks
of the free-light organic carbon fraction were lower
than Century simulated values. The discrepancies
between measured and simulated values varied in
soils showing 69% to 83% oxidic mineralogy. Motavalli et al. (1994) believed that the slow pool contains
substances other than free light organic carbon or the
extraction procedure is not efficacious to isolate all
free light organic carbon soils.
Underestimation of the Century active and slow
pool may be explained by the lack of important
chemical processes in acid tropical soils not considered
by the model. In tropical and subtropical acid soils, the
organic matter – Al complex is relevant in the control
of the Al toxicity and therefore in the soil organic
L.F. Carvalho Leite et al. / Geoderma 120 (2004) 283–295
matter mineralization (Haynes and Mokolobate, 2001;
Meda et al., 2001). High acidity and high soil aluminum content are also responsible for the stabilization
of organic matter in acid tropical soils (Mendoncßa and
Rowell, 1994; Mendoncßa, 1995). Thus, parameterization of simulation models should improve knowledge
about the effect of soil mineralogy, soil pH and soil
exchangeable aluminum on SOM formation and decomposition in acid tropical soils.
Thus more detailed investigations are needed to
identify the underlying differences between the theoretical requirements of the Century pools and those
analytically quantified. Century simulated C stocks of
the passive pool and those estimated by difference
showed similar patterns, especially in the soils under
NT and HHDP. In the soils under DP and HH,
293
differences between measured and simulated C stocks
were 7% and 10%, respectively. Apart from the soil
under NT, N stock contents estimated by Century
were higher (7 – 10%) than measured values (Fig. 5).
These trends were also reported by Fernandes (2002)
in an Acrisol from southern Brazil in the no and
conventional tillage as in the native grass.
Regression analysis showed that the Century simulated TOC stocks correlated well (R 2 = 0.91;
p < 0.05) with the measured values and a good 1:1
correspondence between simulated and measured values (Fig. 6). This indicates that Century model is able
to simulate the TOC dynamic from tropical soil under
different management systems. On the other hand,
correlations among simulated and measured C pools
indicated that only passive C pool correlated signifi-
Fig. 6. Relationship between measured and simulated total organic carbon (A), C active pool (B), C slow pool (C), C passive pool (D) and total
nitrogen (E). *, ** indicate significance at the 0.05 and 0.01 probability level, respectively; ns = not significant.
294
L.F. Carvalho Leite et al. / Geoderma 120 (2004) 283–295
cantly (R2 = 0.89; p < 0.05). Thus, it is essential to
conduct more studies on acid tropical soils to optimize
the relationship between the theoretical concepts of
the Century model pools and the measured fractions.
The regression coefficient of measured TN versus
simulated TN has an R2 value of 0.97, but here is
not a good 1:1 correspondence between measured and
simulated TN values.
4. Conclusions
Both active and slow carbon pools were more
sensitive to soil management systems than total organic carbon and passive carbon pool. This indicates
that active and slow pools can be used as early
warning indicators of soil organic matter degradation.
The Century model simulated changes in the total
organic carbon content and obtained an excellent fit to
measured data (only 5% contrast) and this shows the
high potential of the model to simulate soil organic
matter dynamics in the tropics.
Similarly to the total organic carbon, the Century
model simulated values of passive carbon pool showed
similar patterns to those observed in the measured
data. However, the Century model underestimated
stocks of slow and especially active carbon pool and
thus there is a need to include some important chemical process in the model in acid tropical soils.
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