use of the rothc model to estimate the carbon sequestration potential of organic matter application...

ORIGINAL ARTICLE

Use of the RothC model to estimate the carbon sequestrationpotential of organic matter application in Japanese arable soils

Masayuki YOKOZAWA, Yasuhito SHIRATO, Toshihiro SAKAMOTO,Seiichirou YONEMURA, Makoto NAKAI† and Toshiaki OHKURANational Institute for Agro-Environmental Sciences, Tsukuba, Ibaraki 305-8604, Japan

Abstract

We estimated the carbon (C) sequestration potential of organic matter application in Japanese arable soils at a

country scale by applying the Rothamsted carbon (RothC) model at a 1-km resolution. After establishing the

baseline soil organic carbon (SOC) content for 1990, a 25-year simulation was run for four management scenar-

ios: A (minimum organic matter application), B (farmyard manure application), C (double cropping for paddy

fields) and D (both B and C). The total SOC decreased during the simulation in all four scenarios because the C

input in all four scenarios was lower than that required to maintain the baseline 1990 SOC level. Scenario A

resulted in the greatest depletion, reflecting the effects of increased organic matter application in the other sce-

narios. The 25-year difference in SOC accumulation between scenario A and scenarios B, C and D was 32.3,

11.1 and 43.4 Mt C, respectively. The annual SOC accumulation per unit area was similar to a previous esti-

mate, and the 25-year averages were 0.30, 0.10 and 0.41 t C ha)1 year)1 for scenarios B, C and D, respectively.

The system we developed in the present study, that is, linking the RothC model and soil spatial data, can be use-

ful for estimating the potential C sequestration resulting from an increase in organic matter input to Japanese

arable soils, although more feasible scenarios need to be developed to enable more realistic estimation.

Key words: agricultural soil, mitigation, Rothamsted carbon model, soil carbon.

INTRODUCTION

Implementing efficient agronomic practices to change the

amount of soil organic carbon (SOC) stored in agricul-

tural soil can serve to mitigate climate change (Paustian

et al. 1997; Smith et al. 2008). The fourth assessment

report of the Intergovernmental Panel on Climate Change

(IPCC AR4) included details of the agricultural sector’s

mitigation potential (Smith et al. 2007a) through prac-

tices such as carbon sequestration by soil management.

The Kyoto Protocol allows carbon emissions to be offset

by demonstrable removal of carbon from the atmosphere;

this removal includes improved management of agricul-

tural soils, as well as afforestation and reforestation (Inter-

governmental Panel on Climate Change 2000).

It is essential for countries to estimate mitigation poten-

tial at a national scale. Several countries have published

details of the mitigation potential of cropland manage-

ment (e.g. Canada; Boehm et al. 2004). Such estimates,

however, have not yet been published for Japan.

The most well-known agricultural practice that

increases the sequestration of carbon in soils is no-tillage

or reduced-tillage farming (Paustian et al. 1997). No-till-

age techniques, however, would be difficult in many parts

of Japan, as well as in other regions with humid climates,

primarily because of problems with weeds. In these

regions, other practices, including the application of com-

post and the use of ‘‘green manure’’ or multi-cropping,

must be used to increase carbon input to soils and thus

increase SOC storage.

Recently in Japan, the Ministry of Agriculture, Forestry

and Fisheries (MAFF) calculated the potential carbon

sequestration by compost application (Ministry of Agri-

culture, Forestry and Fisheries 2008). The MAFF roughly

estimated that the application of compost at 10 and

15 t ha)1 year)1 (fresh weight) to all of Japan’s paddy

soils and arable upland soils, respectively, would accumu-

late more SOC (by approximately 2 Mt C year)1) than if

Correspondence: Y. SHIRATO, National Institute for Agro-Environmental Sciences, Kan-nondai 3-1-3, Tsukuba, Ibaraki305-8604, Japan. Email: [email protected] address: †Kan-nondai 1-3-11, Tsukuba, Ibaraki 305-0856, Japan.

Received 22 June 2009.Accepted for publication 31 August 2009.

� 2010 Japanese Society of Soil Science and Plant Nutrition

Soil Science and Plant Nutrition (2010) 56, 168–176 doi: 10.1111/j.1747-0765.2009.00422.x

no compost were applied. This estimate was not, how-

ever, presented in a scientific paper and MAFF (2008) sta-

ted that further investigation was needed to develop a

more reliable estimate.

There are several methods of estimating changes in

SOC at a national scale. The IPCC Guidelines (Intergov-

ernmental Panel on Climate Change 2006) provided a

three-tiered approach. Tiers 1 and 2 are regression based.

The tier 3 approach, with a dynamic model and spatially

explicit data, is better if the data and model are available.

The Rothamsted Carbon Model ([RothC] Coleman and

Jenkinson 1996) is a leading model that is widely used, as

are the CENTURY (Parton et al. 1987) and DNDC

(Li et al. 1992) models. The RothC model has also been

used for nation-scale estimation of carbon sequestration

(Falloon et al. 2006; Smith et al. 2005, 2007b; van Wese-

mael et al. 2005).

The RothC model has been tested against data from

long-term experiments in Japan. The model was modified

for Andosols (Shirato et al. 2004) and for paddy soils

(Shirato and Yokozawa 2005) so that changes in SOC

with time can be well simulated at a plot scale. In addi-

tion, the spatial distribution of SOC in arable land in

1990 was recently calculated for Japan. By combining the

modified RothC models and the spatial SOC distribution

data, we attempted to estimate the country-scale changes

in SOC that would result from the use of different soil

management practices.

Specifically, our objective was to use the RothC model

at a 1-km resolution to conduct a country-scale estimation

of potential carbon sequestration through the application

of organic matter to Japanese arable soils.

MATERIALS AND METHODS

Model description

The current version of RothC, RothC-26.3, is derived

from earlier versions developed by Jenkinson and Rayner

(1977). It separates incoming plant residues into decom-

posable plant materials (DPM) and resistant plant materi-

als (RPM), both of which undergo decomposition to

produce microbial biomass (BIO) and humified organic

matter (HUM) and to release CO2 (Coleman and Jenkin-

son 1996). The clay content of the soil determines the pro-

portions of decomposed carbon allocated to CO2 and to

BIO + HUM. The BIO and HUM fractions both undergo

further decomposition to produce more CO2, BIO and

HUM. The model also includes a pool of inert organic

matter (IOM). Each compartment, except for IOM,

undergoes decomposition by first-order kinetics at its own

characteristic rate, which is determined by using modifiers

for soil moisture, temperature and plant cover. The input

parameters include monthly average air temperature,

monthly precipitation, monthly open-pan evaporation,

soil clay content, monthly C input from plant residues

and ⁄ or farmyard manure (FYM), and monthly informa-

tion on soil cover (whether the soil is bare or covered with

vegetation).

Study area

We conducted a simulation by prescribing datasets

required for running the RothC model, such as weather,

soil and management data, on a 1-km grid basis. Grids in

which 40% or more of the area was occupied by arable

land were subjected to calculation. The percentage of ara-

ble land was derived from the 100-m-grid soil map of the

Fundamental Soil Survey for Soil Fertility Conservation

from 1953 to 1978 (Ministry of Agriculture, Forestry and

Fisheries 1980). Concretely, if there were 40 or more 100-

m-grids of arable soil within the 1-km grid, the 1-km grid

was subjected to calculation. If the dominant soil in a grid

was organic soil (locally known as muck soil or peat soil,

corresponding to Histosols in the World Reference Base

system; International Society of Soil Science et al. 1998),

the grid was excluded from the calculation because the

RothC model is not currently applicable to organic soils

(Coleman and Jenkinson 1996).

Weather data

Monthly mean air temperature and monthly precipita-

tion data were obtained from the gridded Automated

Meteorological Data Acquisition System (AMeDAS) pro-

vided by the National Institute for Agro-Environmental

Sciences. The original AMeDAS data were observed by

the Japan Meteorological Agency. The station data were

interpolated to grids of 45¢ in longitude and 30¢ in lati-

tude (approximately 1 km · 1 km) on the terrain of

Japan following the procedure developed by Seino

(1993). Because open-pan evaporation data are not

widely available in Japan, we instead estimated potential

evapotranspiration from the air temperature (Thorn-

thwaite 1948).

Soil data

Data from the dominant soil series in each 1-km grid were

used for the simulation for simplicity, although there was

often more than one soil series in a 1-km grid. The domi-

nant soil series in each grid was derived from the 100-m-

grid soil maps from MAFF’s Fundamental Soil Survey for

Soil Fertility Conservation (1953–1978).

The mean value of each soil group (Table 1) was used to

determine the clay content for all soil series belonging to

the soil group because data were not available for all soil

series. The percentage of pyrophosphate-extractable Al

(Alp %), which is required for the modified model for

Andosols (Shirato et al. 2004), was calculated from the

total SOC concentration (%) as follows (Shoji et al. 1993):


Estimating carbon sequestration potential 169

Alpð%Þ ¼ ðSOC%� 0:95Þ=5:96 ð1Þ

The 1990 value of SOC (t ha)1) in the top 30 cm of soil

was calculated for each soil series and was used as the

baseline in the present study. Therefore, a soil depth of

30 cm was used for all models. The carbon concentration

and bulk density data for each soil series were obtained

from the Basic Soil–Environment Monitoring Project (Sta-

tionary Monitoring) conducted by MAFF, in which SOC

data were collected every 5 years from 1979 (e.g. first per-

iod, 1979–1982; second period, 1984–1987; third period,

1989–1992; fourth period, 1994–1997). The SOC data

collected during the third period (1989–1992) were used

to determine the 1990 value of SOC. Table 1 shows the

average, minimum and maximum SOC (0–30 cm) of all

soil series in each soil group.

Simulation procedure

In modeling each grid, we set the initial SOC content to

the 1990 value (Table 1) and then simulated the changes

in SOC with time for four management scenarios, which

will be described in detail later. For each 1-km grid, the

SOC of a dominant soil series in a grid in 1990 was set as

the baseline, and the RothC was run to reach equilibrium

with that baseline SOC under constant environmental

conditions. As described by Jenkinson et al. (1999),

assuming that the SOC content has reached equilibrium,

the RothC model can be run inversely to calculate how

much C needs to enter the soil annually to maintain a

specified level of SOC. In this calculation process, the allo-

cation of SOC into each of the five compartments (DPM,

RPM, BIO, HUM and IOM) is determined. Therefore, we

ran the model inversely to calculate the C input required

to maintain the SOC content at 1990 levels, and we then

set the SOC allocation in each of the five compartments to

this equilibrium value. Soils were assumed to be covered

with vegetation (summer crops) from May to October.

For simplicity, the C input required to maintain the 1990

SOC level was added in October, the harvest month, as a

single pulse because Coleman and Jenkinson (1996)

reported that it makes little difference in the calculation of

SOC content how the annual input is distributed, or even

if it is all added in a single pulse. The DPM : RPM ratio

was set at 1.44, a typical value for most agricultural crops

and grasses (Coleman and Jenkinson 1996). The values of

IOM were set by Eq. 2:

IOM ¼ 0:049� SOC1:139 ð2Þ

Falloon et al. (1998), except for the IOM of Andosols,

which was set to 0 because Andosols do not contain

organic carbon when formed from fresh volcanic ash,

although IOM is assumed to be present from the begin-

ning of soil formation (Shirato et al. 2004).

The SOC content (t ha)1 in the top 30 cm), which was

output by the model, was multiplied by the area (ha) of

arable land within the grid to produce the total amount of

SOC (t, 0–30 cm) in each grid. The area of arable land

used for this calculation was the sum of the 1997 Digital

National Land Information (land-use data) on the areas

of paddy fields and other arable land.

Selection of three versions of RothC

The RothC model has been tested against data from long-

term experiments in Japan, and has successfully simulated

changes in SOC over time for non-volcanic upland soils

(Shirato and Taniyama 2003). However, the original

model was not successful in simulating carbon turnover in

Table 1 Soil organic carbon and clay content in 1990 for each soil group used for the simulations

Name of the soil group

Corresponding soil name

in the WRB system No. soil series

SOC in 0–30 cm (t ha)1)

Clay (%)Average Minimum Maximum

Lithosols Leptsols 2 73.3 46.0 86.5 16.0

Sand-dune Regosols Arenosols 1 24.4 24.4 24.4 5.1

Andosols Andosols 61 111.9 58.4 212.7 14.0

Wet Andosols Andosols 48 133.3 75.1 283.1 16.1

Gley Andosols Andosols, Gleysols 14 115.4 56.3 162.7 13.3

Brown Forest soils Cambisols 23 69.5 50.6 108.3 23.1

Gray Upland soils Gleysols, Planosols 15 73.5 45.8 205.0 26.8

Gley Upland soils Gleysols, Planosols 11 56.5 49.0 80.7 40.0

Red soils Acrisols, Alisols 7 58.1 11.6 69.2 32.6

Yellow soils Acrisols, Alisols 23 59.2 39.4 166.5 21.0

Dark Red soils Acrisols, Alisols 6 45.2 36.5 50.2 34.1

Brown Lowland soils Fluvisols, Cambisols, Gleysols 19 54.8 24.0 87.1 16.6

Gray Lowland soils Fluvisols, Cambisols, Gleysols 38 62.4 44.2 92.2 18.5

Gley soils Fluvisols, Cambisols, Gleysols 37 66.1 37.6 97.6 25.3

SOC, soil organic carbon; WRB, World Reference Base for Soil Resources.


170 M. Yokozawa et al.

Andosols and paddy soils. Shirato et al. (2004) modified

the model for Andosols by changing the HUM decompo-

sition rate constant with concentration of pyrophosphate-

extractable Al, taking the strong stability of humus in An-

dosols into account. Similarly, for paddy soils, Shirato

and Yokozawa (2005) modified the model by tuning the

decomposition rate constant of all pools separately for

periods with and without submergence, on the basis of

the slower decomposition rates of organic matter in paddy

soils than in upland soils.

For grids in which the area of paddy fields was larger

than that of upland crop fields, we used the RothC version

modified for paddy soils (Shirato and Yokozawa 2005). If

the dominant soil series was the Andosols group (Ando-

sols, Wet Andosols and Gleyed Andosols), we used the

model modified for Andosols (Shirato et al. 2004). For all

other grids, the original version of the RothC model

(Coleman and Jenkinson 1996) was used. The areas of

paddy fields and upland crop fields were derived from

1997 Digital National Land Information (land-use data).

Soil management scenarios

Once the baseline SOC content had been established for

each 1-km grid, four management scenarios were modeled

for a 25-year period (Table 2).

Scenario A (minimum organic matter application)

A minimum amount of crop residue (roots and stubble),

0.46 t C ha)1 year)1 for paddy fields and 0.41 t C ha)1

year)1 for upland fields, enters the soils. This scenario was

compared with each of the other scenarios to assess the

effects of the other scenarios on carbon sequestration.

Scenario B (farmyard manure application)

In this scenario, in addition to the minimum organic mat-

ter application of scenario A, FYM is applied at a rate of

1.0 t C ha)1 year)1 for paddy fields and 1.5 t C ha)1

year)1 for upland areas. This scenario was chosen because

the application of FYM is regarded as a promising option

to increase SOC in the Japanese agricultural system. The

amount of FYM was set at the same level used by MAFF

(2008), in which 10 and 15 t (fresh weight) ha)1 year)1

of FYM was applied to paddy and upland soils, respec-

tively, and the carbon concentration of the fresh FYM

was assumed to be 10%.

Scenario C (double cropping for paddy fields)

In this scenario, in addition to the treatment in scenario A,

wheat residue (0.70 t C ha)1 year)1) from winter wheat

cropping in all paddy fields was assumed to be input into

the system. This scenario assesses the effects of increasing

the carbon input from crop residues by mulch cropping,

which is also considered to be an important option for

increasing SOC.

Scenario D

In addition to the minimum treatment in scenario A,

FYM is applied as described in scenario B and there

is double cropping in the paddy fields, as described in

scenario C.

The increase or decrease in SOC storage caused by each

treatment was estimated by calculating the differences

between scenarios B, C and D and scenario A.

The annual C inputs from crop residue and the applica-

tion of FYM in each scenario are shown in Table 2. The

parameters used to calculate the C inputs from crop resi-

dues are summarized in Table 3. The C input from crop

residues (roots and stubble) in paddy soils was calculated

from the average yield and the proportion of residue to

yield of paddy rice, derived from the work of Ogawa et al.

(1988). The C input from crop residue in upland soils was

calculated by using similar data for wheat and soybeans

(Ogawa et al. 1988), and the average of the two crops

was used (Table 3) for simplicity.

Again, for simplicity, the C input from plant residues

was added to the soils only in the month of harvest: Octo-

ber for summer crops and April for winter crops. A

DPM : RPM ratio of 1.44 was used for all types of plant

residues, and the recommended values for FYM

(DPM = 49%, RPM = 49% and HUM = 2%) were also

Table 2 Carbon input as crop residue and farmyard manure in the four management scenarios

Scenarios

Carbon input (t C ha)1 year)1)

Paddy Upland

Crop residue† FYM‡ Crop residue† FYM‡

A. Minimum organic matter application 0.46 0 0.41 0

B. FYM 0.46 1.0 0.41 1.5

C. Double cropping for paddy fields 0.46 + 0.70 0 0.41 0

D. FYM + double cropping for paddy fields 0.46 + 0.70 1.0 0.41 1.5

†Only roots and stubble enter the soil as residue. The amount was calculated from the yield as shown in Table 3; ‡Fresh farmyard manure (FYM) wasapplied at a rate of 10 t C ha)1 year)1 and 15 t C ha)1 year)1 to paddy fields and upland fields, respectively. The concentration of C in the fresh FYM wasassumed to be 10%.



used (Coleman and Jenkinson 1996). The months during

which soil was covered by vegetation were set as May–

October for summer crops and November–April for win-

ter crops.

RESULTS

Soil organic carbon storage in 1990

The total area of arable land subjected to the simulation

was 4.27 million ha: 2.39 million ha of paddy fields and

1.88 million ha of upland fields (Table 4). Gray Lowland

soils, Gley soils and Wet Andosols occupied 76% of the

area of paddy soils, and Andosols, Brown Forest soils and

Brown Lowland soils occupied 69% of the upland soils

area. These proportions are consistent with the findings of

MAFF’s Fundamental Soil Survey for Soil Fertility Con-

servation (1953–1978), implying that the procedure used

to represent a dominant soil series in a grid successfully

approximated the actual area proportions for the soil

types.

The total SOC of mineral soils in the top 30 cm of soil

in 1990 (the sum of all of the grids) was 341 Mt; paddy

soils and upland soils accounted for 173 Mt and 168 Mt,

respectively (Table 4). This value is close to the MAFF

(2008) estimate of 380 Mt, which included organic soils.

Organic soils were excluded from our study, but if organic

soils had been included then the total SOC would have

been approximately 370 Mt.

The average SOC of all mineral soils was 79.8 t ha)1,

and the average SOC for paddy soils and upland soils was

72.2 and 89.5 t ha)1, respectively. Soils in the Andosols

group (Andosols, Wet Andosols and Gleyed Andosols)

had high levels of C (>100 t ha)1).

Carbon input required to maintain the 1990 SOClevel

On average, 2.8, 5.1 and 5.7 t C ha)1 year)1 of crop resi-

dues were required to maintain the 1990 level of SOC in

paddy, upland (Andosols) and upland (non-Andosols)

soils, respectively (Table 5).

The C inputs to soils in scenario A were 0.46 and

0.41 t ha)1 year)1 for paddy and upland soils, respec-

tively (Tables 2,3). These values were much lower than

the required inputs shown in Table 5, and it was obvious

that SOC would decline (approximately 75 Mt C

declined during the 25 years of our simulation) under this

scenario.

Table 3 Calculation of the carbon input derived from cropresidue (roots and stubble)

Yield†

(t ha)1)

(Roots + stubble) ⁄yield‡

Roots + stubble

(t C ha)1)

Paddy rice 5.0 0.230 0.46

Wheat 3.7 0.473 0.70

Soybean 1.7 0.162 0.11

Average of

wheat and

soybean

0.41

†Recent average yield. Moisture concentrations were assumed to be 15%for rice and soybean and 12.5% for wheat. ‡Derived from the proportionsof dry matter produced from each part of the crop as reported by Ogawaet al. (1988). Rice: grain, 37.2%; chaff, 8.2%; leaves and stalks, 44.6%:stubble, 6.7%; roots, 3.3%. Wheat: grain, 32.3%; chaff, 9.7%; leavesand stalks, 40.6%; stubble 9.4%; roots 8.1%. Soybean: grain, 33.1%;pod, 17.9%; leaves and stalks, 42.7%; stubble, 3.3%; roots, 3.0%.The C concentration of the dry matter was assumed to be 40%.

Table 4 Total baseline (1990) area and soil organic carbon of each soil group used for the simulation

Soil groups

Area (·1000 ha) Total SOC (Mt C) in 1990

Paddy Upland Total Paddy Upland Total

Lithosols 0.6 4.2 4.8 0.04 0.32 0.37

Sand-dune Regosols 2.7 16.3 19.0 0.07 0.40 0.46

Andosols 120.7 844.1 964.8 13.96 93.90 107.86

Wet Andosols 212.0 107.4 319.3 26.61 16.19 42.79

Gley Andosols 24.2 8.9 33.1 2.69 1.12 3.81

Brown Forest soils 41.8 263.6 305.4 2.83 18.38 21.21

Gray Upland soils 60.9 90.1 151.0 3.94 7.25 11.19

Gley Upland soils 40.0 8.6 48.6 2.26 0.48 2.75

Red soils 4.0 29.5 33.5 0.23 1.71 1.94

Yellow soils 127.2 96.1 223.4 7.66 5.58 13.24

Dark Red soils 2.1 36.9 38.9 0.10 1.63 1.73

Brown Lowland soils 156.0 197.4 353.3 9.43 9.96 19.39

Gray Lowland soils 873.7 120.5 994.2 54.66 7.58 62.24

Gley soils 725.3 57.8 783.1 48.11 3.91 52.03

Total 2,391.1 1,881.4 4,272.4 172.60 168.40 341.00

SOC, soil organic carbon.



In paddy soils, the total crop residue from a normal

yield was calculated to be 2.86 t C ha)1, which included

0.46 t C ha)1 in roots and stubble and 2.40 t C ha)1 in

leaves and straw (Table 5). This amount did exceed the

required input of 2.8 t C ha)1, implying that SOC in

paddy soils could be maintained or increased if all crop

residues (not just the roots and stubble) were incorporated

into the soils.

Conversely, the total amount of residue produced by

wheat was estimated to be 2.7 t C ha)1 and that of soy-

beans was 1.1 t C ha)1; these amounts were clearly much

lower than the required C inputs of 5.1 and 5.7 t ha)1,

respectively (Table 5). These large amounts of required C

input to maintain present SOC might result from the large

C input (net primary production [NPP]) from original nat-

ural vegetation, such as forest (Kira 1975) or grassland

(Caldwell 1975). For example, average annual above-

ground net primary production rates (dry matter) of vari-

ous types of Japanese forests of approximately 8–

20 t ha)1 year)1 (Kira 1975) and 45% C concentration

result in 3.6–9.0 t C ha)1 year)1 of C input. It is therefore

difficult to maintain the SOC level of upland soils even if

all residues are incorporated into the soils. In fact, the

topsoil C of upland crop fields has been gradually decreas-

ing recently, whereas that of paddy fields has remained

almost constant (Nakai 2006).

Soil organic carbon accumulation effects

The SOC decreased during the 25-year simulation period

in all four scenarios because the C inputs in all four sce-

narios (Table 2) were lower than the C inputs required to

maintain the SOC level (Table 5). The rates of decrease

were, however, different among the scenarios. As

expected, scenario A resulted in the greatest depletion in

SOC. The other scenarios had lower levels of depletion,

reflecting the effects of organic matter application. The

amount of SOC accumulated in scenario B (FYM applica-

tion; 32.3 Mt) was greater than that in scenario C (double

cropping in paddy fields; 11.1 Mt) as shown in Table 6.

The accumulation in scenario D (using both techniques)

was equal to the sum of the accumulations in B and C

(43.4 Mt).

These accumulations increased rapidly in the early years

of the simulation and then slowly increased toward equi-

librium (Fig. 1a), although they had not reached equilib-

rium by the 25th year. The annual accumulations in

scenarios B, C and D were 2.95, 0.93 and

3.88 Mt C year)1, respectively, for the first year, and

decreased to 0.73, 0.25 and 0.98 Mt C year)1 for the

25th year, respectively (Table 6). A similar declining trend

can be seen in the average accumulations for the first

10 years and the entire 25 years (Table 6).

The effects of SOC accumulation per hectare are pre-

sented in Table 7. For the 25-year period, the per-hectare

SOC accumulations in scenarios B, C and D were 7.55,

2.60 and 10.16 t ha)1, respectively. Again, there was a

rapid increase at the beginning, followed by a slower rate

of increase (Fig. 1b). Similarly, the annual SOC accumula-

tions per hectare were large at the beginning and declined

thereafter (Table 7; Fig. 1c).

Table 5 Amounts of carbon derived from crop residues and thecarbon inputs required to maintain the 1990 soil organic carbonlevel

Roots +

stubble†Other

residues†All

residues

Required

C input‡

t C ha)1 t C ha)1 year)1

Paddy rice 0.46 2.40 2.86 2.76

Wheat 0.70 2.00 2.70 5.06–5.66§

Soybean 0.11 1.00 1.11 5.06–5.66§

†Calculated from the yield data as shown in Table 3. ‡Calculated byRothC. §5.06 for upland (Andosols) and 5.66 for upland (non-Andosols)soils.

Table 6 Soil organic carbon accumulation under the three scenarios

Scenario Land use

Total accumulation

(25 years)

Annual accumulation

1st year 25th year 25-year average 1st 10-year average

Mt C Mt C year)1

B. FYM Paddy 18.3 1.49 0.41 0.73 1.04

Upland 14.0 1.46 0.32 0.56 0.83

All 32.3 2.95 0.73 1.29 1.87

C. Double cropping for

paddy fields

Paddy 11.1 0.93 0.25 0.45 0.63

Upland 0 0 0 0 0

All 11.1 0.93 0.25 0.45 0.63

D. FYM + double cropping for

paddy fields

Paddy 29.4 2.42 0.66 1.18 1.67

Upland 14.0 1.46 0.32 0.56 0.83

All 43.4 3.88 0.98 1.74 2.50

FYM, farmyard manure.



DISCUSSION

Total potential of carbon sequestration inJapanese arable land

The estimated annual SOC accumulation in response to

the application of compost (scenario B) ranged from 0.73

to 2.95 Mt year)1 during the 25-year simulation, and the

averages for the entire 25-year period and for the first

10 years were 1.29 and 1.87 Mt year)1, respectively

(Table 6). These values are similar to MAFF’s (2008) esti-

mation of a potential 2 Mt C year)1. As mentioned previ-

ously, the application rate of compost was the same in

both estimates. The MAFF estimate was calculated on the

basis of the difference between plots with and without

compost and from continuous field observation datasets

longer than 8 years, whereas our estimation was based on

a 25-year model simulation. The two approaches are

quite different, but both approaches produced similar

estimates. The annual average for the first 10 years

(1.87 Mt C year)1) was closer to the MAFF estimate

(2.0 Mt C year)1) than was the 25-year average

(1.29 Mt C year)1).

Per-area potential of carbon sequestration

The IPCC AR4 (Smith et al. 2007a) provided values for

the per-area potential of mitigation technologies in agri-

culture. Its mitigation potentials for CO2 represent the net

change in SOC derived from approximately 200 studies,

primarily taken from the works of Ogle et al. (2005) and

Smith et al. (2008). Mean estimates of annual per-area

mitigation potentials for CO2 by agronomy, nutrient

management, tillage and residue management range from

0.51 to 0.88 t CO2 ha)1 year)1 in cool-moist and warm-

moist climate regions, which correspond to the Japanese

climate. These values are equivalent to 0.14–

0.24 t C ha)1 year)1. Our estimates (the 25-year average)

of 0.30 t C ha)1 year)1 for compost application and

0.19 t C ha)1 year)1 for double cropping for paddy fields

(Table 7) are similar to the IPCC AR4 estimates.

05

101520253035404550

0 5 10 15 20 25

Tota

l SO

C a

ccum

ulat

ion

effe

cts

(Mt C

)

Years

0

2

4

6

8

10

12

0 5 10 15 20 25S

OC

acc

umul

atio

n ef

fect

spe

r un

it ar

ea (

t C h

a–1)

0.00.10.20.30.40.50.60.70.80.91.0

0 5 10 15 20 25

D: FYM +doublecropping forpaddy fields

B: FYM

C: Doublecropping forpaddy fields

Ann

ual S

OC

acc

umul

atio

n ef

fect

spe

r un

it ar

ea (

t C h

a–1

year

–1)

(a) (b) (c)

Figure 1 Soil organic carbon (SOC) accumulation effects in scenarios B, C and D, expressed as the difference between the SOC in eachof the scenarios and that of scenario A (minimum organic matter application). (a) Total SOC accumulation effects, (b) SOC accumula-tion effects per unit area and (c) annual SOC accumulation effects per unit area. FYM, farmyard manure.

Table 7 Soil organic carbon accumulation (per ha) under the three scenarios

Scenario Land use

Accumulation ha–1

(25 years)

Annual accumulation ha–1

1st year 25th year 25-year average 1st 10-year average

t C ha)1 t C ha)1 year)1

B. FYM Paddy 7.66 0.62 0.17 0.31 0.43

Upland 7.43 0.78 0.17 0.30 0.44

All 7.55 0.69 0.17 0.30 0.44

C. Double cropping for

paddy fields

Paddy 4.66 0.39 0.10 0.19 0.26

Upland 0 0 0 0 0

All 2.60 0.22 0.06 0.10 0.15

D. FYM + double cropping for

paddy fields

Paddy 12.31 1.01 0.28 0.49 0.70

Upland 7.43 0.78 0.17 0.30 0.44

All 10.16 0.91 0.23 0.41 0.58

FYM, farmyard manure.



Trade-offs between soil carbon sequestration andCH4 or N2O emissions

In paddy soils, the increased C input to the soils with com-

post application causes increased CH4 emissions. MAFF

(2008) referred to this trade-off between SOC accumula-

tion and CH4 emissions and estimated that increased com-

post application (10 t ha)1 year)1; fresh weight) for all

paddy fields may increase CH4 emissions by approxi-

mately 0.2 Mt C year)1 in terms of global warming

potential (GWP), or approximately 10% of the SOC

accumulation (2.0 Mt year)1). This suggests that the SOC

accumulation effect of compost application vastly exceeds

the negative effects of CH4 emissions. The rate of compost

application was the same in our study, and we similarly

expect that the positive effects of SOC accumulation

will far outweigh the negative effects of increased CH4

emissions.

Emissions of N2O could also increase as the compost

application rate increases because compost contains nitro-

gen. In our scenario, however, we assumed that an

increase in the application rate of compost would coincide

with a reduction in the use of chemical fertilizers; thus,

total N2O emissions will not change.

Double cropping of paddy fields will cause an increase

in N2O emissions from the use of fertilizers for wheat. A

rough estimate of this increase is approximately

0.2 Mt C year)1, assuming an N fertilization rate of

100 kg N ha)1, an emission factor of 0.62 (Akiyama

et al. 2006), an area of 2.4 million ha (Table 4) and a

GWP of 298 (100-year time horizon; Forster et al. 2007).

Thus, this negative effect is lower than the SOC accumula-

tion (range, 0.25–0.93 Mt year)1; 25-year average,

0.45 Mt year)1).

Overall, the effect of SOC accumulation exceeded the

negative effects of increasing CH4 and N2O emissions

under all three scenarios.

Feasibility of the soil management scenarios

In scenario A, we assumed that only roots and stubble

entered the soil and that other residues (e.g. leaves and

stalks) were removed from the fields. Obviously, this

amount of C input was smaller than what actually occurs.

Hence this scenario was not business as usual because

some of the above-ground residues are generally incorpo-

rated into the soils. This scenario was created as a basis of

comparison with the other scenarios to assess the effects

of the other scenarios on carbon sequestration; it was not

set to simulate SOC under a business as usual scenario.

In scenario B (compost application), the rate of compost

application (1.0 t C ha)1 year)1 for paddy fields and

1.5 t C ha)1 year)1 for upland crop fields) was set to be

equal to the amount recommended by MAFF (2008).

Although this application rate is feasible, the assumption

that compost would be applied at the same rate to all ara-

ble soils is not realistic. The application rate has actually

been decreasing and has declined from 4.51 t ha)1 in

1970 to 0.88 t ha)1 in 2005 for paddy rice and from

3.90 t ha)1 to 0.89 t ha)1 for wheat, although the appli-

cation rate for vegetables has stayed relatively high

(19.0 t ha)1 from 1994 to 1999; Ministry of Agriculture,

Forestry and Fisheries 2008). A more realistic rate of com-

post application would be smaller than the rate used in

our scenario. In addition, the assumption of compost

application to all arable land is probably not realistic, and

a smaller area of application would result in a smaller

potential SOC accumulation. Our estimates of total C

sequestration potential with this scenario might be an

overestimate in terms of both the area of implementation

and per-unit-area potential.

In scenario C (double cropping for paddy fields) we

set the C input from winter wheat by assuming that

only roots and stubble entered the soil and that the

other residues were removed from the fields. The real

amount of C input from winter wheat cropping would

be much greater than the amount that we assumed

because some of the above-ground residues are incorpo-

rated into the soil; hence, the C input per unit area

would be greater than our scenario indicates. Con-

versely, we also assumed winter wheat cropping in all

paddy fields, which is clearly not realistic. Some paddy

fields are already double cropped, and winter cropping

is difficult in some regions because of the climate. In

this scenario, we may be underestimating the per-area

potential and overestimating the area of implementa-

tion. In addition, mulch cropping occurs not only in

paddy fields, but also in upland fields. From this per-

spective, our simulation should be considered as an

example of this type of analysis.

More feasible scenarios of compost and crop residue

application both for area of implementation and for rate

per unit area need to be developed to generate better esti-

mates of potential C sequestration. We conclude that,

regardless of the problems listed above, the system we

developed in the present study, that is, linking the RothC

model and soil spatial data, can be useful to estimate the

potential C sequestration resulting from an increase in

organic matter input to Japanese arable soils.

ACKNOWLEDGMENTS

We thank Mr Kevin Coleman (Rothamsted Research,

UK) for help and advice with the RothC model and Dr

Hiroko Akiyama (National Institute for Agro-Environ-

mental Sciences, Japan) for advice on calculating N2O

emissions. This work was financially supported by the

Ministry of Agriculture, Forestry and Fisheries, Japan



(Evaluation, Adaptation and Mitigation of Global Warm-

ing in Agriculture, Forestry and Fisheries).

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