soil organic carbon decomposition and carbon pools in

7/30/2019 Soil Organic Carbon Decomposition and Carbon Pools In

1/6

Journal of Environmental Management 85 (2007) 690695

Soil organic carbon decomposition and carbon pools in

temperate and sub-tropical forests in China

L. Yanga,b,c, J. Pana,, Y. Shaoa, J.M. Chend, W.M. Jud, X. Shie, S. Yuanf

aCollege of Resources and Environment of Nanjing Agriculture University, Nanjing 210095, PR ChinabNanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, PR China

cGraduate School of Chinese Academy of Sciences, Beijing 100039, PR ChinadDepartment of Geography, University of Toronto, 100 St. George St., Room 5047, Toronto, Ont., Canada M5S 3G3

eInstitute of Soil Science, Chinese Academy of Sciences, Nanjing 210008, PR ChinafLand Institute of College of Public Management, Zhejiang Gongshang University, Hangzhou 310035, PR China

Received 4 December 2005; received in revised form 31 August 2006; accepted 19 September 2006

Available online 14 November 2006

Abstract

Decomposition of soil organic carbon (SOC) is a critical component of the global carbon cycle, and accurate estimates of

SOC decomposition are important for forest carbon modeling and ultimately for decision making relative to carbon sequestration and

mitigation of global climate change. We determined the major pools of SOC in four sites representing major forest types in

China: temperate forests at Changbai Mountain (CBM) and Qilian Mountain (QLM), and sub-tropical forests at Yujiang (YJ) and

Liping (LP) counties. A 90-day laboratory incubation was conducted to measure CO2 evolution from forest soils from each site, and

data from the incubation study were fitted to a three-pool first-order model that separated mineralizable soil organic carbon into active

(Ca), slow (Cs) and resistant (Cr) carbon pools. Results indicate that: (1) the rate of SOC decomposition in the sub-tropical zone was

faster than that in the temperature zone, (2) The Ca pool comprised $13% of SOC with an average mean residence time (MRT) of 219

days. The Cs pool comprised $2565% with an average MRT of 78 yr. The Cr pool accounted for $3580% of SOC, (3) The YJ site inthe sub-tropical zone had the greatest Ca pool and the lowest MRT, while the QLM in the temperature zone had the greatest MRT for

both the Ca and Cs pools. The results suggest a higher capacity for long-term C sequestration as SOC in temperature forests than in sub-

tropical forests.

r 2006 Elsevier Ltd. All rights reserved.

Keywords: Soil organic carbon decomposition; Carbon pool; Active carbon pool; Slow carbon pool; Resistant carbon pool

1. Introduction

Soil organic carbon (SOC) represents the largest carbon

reservoir in terrestrial ecosystems, and is estimated

at about 1500Pg C globally, or $2 times that of theatmosphere and 2.3 times that of the total terrestrial

vegetation (Schimel, 1995). Approximately 70% of the

global soil C inventory resides in forest ecosystems

(Hudson et al., 1994). A small change in forest soil C

inventories can thus result in a large change in atmospheric

CO2 concentration (Raich and Schlesinger, 1992). The

study of dynamic changes and mechanisms of forest SOC is

thus essential in understanding and mitigating global

climate change (Fang et al., 1996). The chemical

components of SOC are complex, involving a wide array

of organic constituents (Sollins et al., 1999) with mean

resistant times (MRT) that range over three orders ofmagnitude (Goh et al., 1989; Paul et al., 2001a). In general,

SOC can be divided into an active pool (turnover time

0.14.5 a), a slow pool (turnover time 550 a) and a passive

pool (503000 a) (Parton et al., 1987). Prior research

suggests that the three-pool first-order model can

accurately predict dynamic changes in forest SOC (Deans

et al., 1986; Gregorich et al., 1989; Cabrera, 1993).

Accurate assessment of the different carbon pools of forest

SOC is an important step in understanding mechanisms of

soil C cycling and dynamic change of carbon pools.

ARTICLE IN PRESS

www.elsevier.com/locate/jenvman

0301-4797/$ - see front matterr 2006 Elsevier Ltd. All rights reserved.

doi:10.1016/j.jenvman.2006.09.011

Corresponding author. Tel.: +8625 84395329; fax: +8625 57714759.

E-mail address: [email protected] (J. Pan).
http://www.elsevier.com/locate/jenvmanhttp://localhost/var/www/apps/conversion/tmp/scratch_6/dx.doi.org/10.1016/j.jenvman.2006.09.011mailto:[email protected]:[email protected]://localhost/var/www/apps/conversion/tmp/scratch_6/dx.doi.org/10.1016/j.jenvman.2006.09.011http://www.elsevier.com/locate/jenvman


2/6

While there are recent studies on total SOC stocks of

forests in China, estimates of sizes and turnover rates of the

three SOC pools have not been reported in forest soils of

China. The objectives of this work were: (a) to describe

SOC decomposition by incubation analysis of different

soils under constant temperature (25 1C) and water content

(60% WHC) for major forest types in China, and (b) to

determine SOC pool sizes and turnover rates for these

forest types according to the three-pool first-order model.

2. Materials and methods

2.1. Study sites

The Liping (LP) site is located in the Guizhou Province,

China (1091100E, 261200N) with a mean annual tempera-

ture (MAT) of 15 1C and rainfall of 1321 mm. The site is in

the sub-tropical zone of China, with plantation standsof Chinese fir (Cunninghamia lanceolata). Soil type

corresponds to Perudic Ferrosols in the CST classification

(Chinese Soil Taxonomy, 2001). The Yujiang (YJ) site, also

in the sub-tropical zone, is located in the Jiangxi Province,

China (1161410E, 281040N) with a MAT of 18.1 1C and

1741 mm of rainfall annually. Ferralsols were formed

under Chinese fir (Cunninghamia lanceolata) and evergreen

broadleaf forests (Wu et al., 1997). The Changbai

Mountain (CBM) site is located in the southeast of Jilin

province, northeast China (1271380E, 411420N), and the

elevation varies in the range from 720 to 2691 m above the

sea level. The climate belongs to the temperate continental

mountainous climate with a MAT of 5 1C and 1050 mm of

precipitation annually. The typical soil types in the area are

Boric Argosols and Udic Isohumosols. The site has

obvious vertical vegetation zones, including broad-leaved

Korean pine forest with an elevation from 500 to 1000 m,

dark coniferous forest with an elevation from 1100 to

1700 m, and Ermans birch forest with an elevation from

1700 to 2000 m. The broad-leaved Korean pine forest is the

dominating vegetation type (Wang et al., 2003a, b). The

Qilian Mountain (QLM) site is located in the Gansu

province, northwest China (991500E, 381300N) and has a

semiarid climate with a MAT of 0.3 1C and 440 mm of

precipitation annually. The typical soil types are Ustic

Isohumosols and Argosols in the CST classification with

main parent rock of calcareous rock. Influenced by the

topography and climate, vegetation type in the site is

mountainous pasture and forest, which includes Picea

crassisolia, Sabina przewalski and shrub forests (Chang

et al., 2005).

2.2. Samples and analysis methods

Soil samples from the four experimental sites were

collected using truck-mounted hydraulic soil probes in

2002 and 2003. Ten samples were collected according to

climate, soil and vegetation types, each of which included

three replicates (Table 1). Geographic coordinates and the

elevations of the four sites were obtained using a satellite

differential global positioning system (GPS).

Moist soil samples were air-dried and sieved to pass a

2 mm screen. Recognizable plant fragments were removedby hand picking. Soil carbonates were removed by adding

100 ml of 250 mM HCL to 20 g soil and shaking for 1 h.

Soils were washed with deionized water to remove excess

Cl (Collins et al., 2000). Total C was measured by wet

oxidation using dichromate in acid medium followed by

the FeSO4 Titration method (Nelson and Sommers, 1975),

and pH was measured in 0.01 M CaCl2 (1:5 Soil: Solution

by volume) using a glass electrode (Sparks, 1996).

One-hundred g of each sample were incubated in 250 ml

glass jars in the dark at 25 1C and 60% water holding

capacity for 90 days. Water holding capacity was estimated

by a volumetric soil water method (Elliott et al., 1994). The

jars were normally closed but opened periodically to

maintain aerobic conditions. Water loss in the jars was

monitored by weight and replenished after opening. No

leaching occurred during the course of incubation. The

evolved CO2 was trapped in 25 ml, 0.4 N NaOH. Control

jars contained no soil. Evolved CO2 was precipitated by the

addition of BaCl2 and measured by titration of residual

NaOH to pH 7.0 with 0.4 N HCL. The evolved CO2 was

measured daily during the first week and every 34 days in

the following 2 weeks till the end of the incubation period.

The size of the resistant C pool (Cr) (Leavitt et al., 1997)

was determined by the residue of acid hydrolysis. Acid

hydrolysis consisted of refluxing 1 g soil in hot, 6 M HCL

ARTICLE IN PRESS

Table 1

Properties of soil samples in LP, CBM, YJ and QLM sites

Sample Depth (cm) Organic carbon (g k g1) pH (%) Clay (%) Soil type (CST) Vegetation

LP3 020 21.17 4.84 17.9 Perudic Ferrosols Cunninghamia lanceolata

LP7 015 24.73 4.42 22.9 Perudic Ferrosols Evergreen broadleaf

YJ1 015 30.76 4.35 28.40 Udic Ferralsols Evergreen broadleaf

YJ2 018 26.59 4.33 35.6 Udic Ferralsols Cunninghamia lanceolata

CBM0 011 57.72 5.04 9.39 Udic Isohumosols Pteridophyta

CBM14 011 74.41 5.07 8.69 Boric Argosols Spruce-fir

CBM22 07 120.34 5.24 7.18 Udic Isohumosols Poplar and Birch

QLM2 030 89.03 8.11 13.70 Ustic Argosols Picea crassifolia

QLM7 030 71.93 8.31 12.50 Ustic Isohumosols Sabinaprezew alskii

QLM8 030 70.18 8.24 13.30 Ustic Isohumosols Shrub

L. Yang et al. / Journal of Environmental Management 85 (2007) 690695 691


3/6

for 18 h. The soluble materials were separated by filtration

followed by repeated evaporation to remove the HCL. The

residue of hydrolysis was rinsed with deionized water and

dried at 55 1C and ground to pass a 180 mm screen. The

total soil and the residue of hydrolysis were combusted to

CO2 (Paul et al., 2001a, b).

2.3. Model description

The three-pool first-order model (Paul et al., 2001a, b)

separates the mineralizable organic carbon into active, slow

and resistant C pools and can be presented as:

Ct CaeKat Cse

Kst CreKr t, (1)

where Ct is total organic carbon at time t, Ca and Cs are the

sizes of the active and slow pools; and Ka and Ks are

decomposition rate constants for the active and slow pools.

Cr is the size of the resistant carbon pool as estimated by

acid hydrolysis. Mean residence time (MRT) for each

component was calculated as the reciprocal of the

decomposition rate constant in the three-pool first-order

model. Radiocarbon dating of the residue of the acid

hydrolysis may be used to determine MRT for Cr. Carbon

dating is relatively expensive and therefore C dates are

often unavailable, and the MRT of Cr is commonly

assumed to be 1000 yr (Paul et al., 2001a, b). The

laboratory-derived values were scaled to the field according

to mean-annual temperature (MAT) by assuming a Q10 of

225MAT=2 (Collins et al., 2000). The size of the slow pool

is defined as Cs CSOC Ca Cr with CSOC representing

the total SOC at time of sampling.

2.4. Model fitting and statistical analysis

Eq. (1) was fitted with a non-linear regression (SPSS

10.5) that uses the Marquardt algorithm and an iterative

process to find the parameter values that minimize the

residual sum of squares. The resultant pool sizes and their

mineralization rate constants could be sensitive to the

initially assigned parameter values and the iterative step

size. Generally, the automatically estimated initial para-

meters resulted in acceptable parameter values. In some

cases, initial parameter values and the iterative steps size

were adjusted by hand to obtain results in reasonable

ranges; for example, rate constants could not be negative,

and the sum of active, slow and resistant carbon pools

should not exceed total SOC.

The standard deviations of the parameters, the residual

mean square (RMS) and the F-values of the curve fits were

calculated (Little and Hills, 1975).

3. Results

3.1. Characteristic of SOC decomposition

Although the rates of SOC decomposition were different

in different forests, qualitative trends were similar with

rapid decomposition in the initial incubation stages and

gradually which gradually reached a steady state. During

the SOC decomposition process, the amount of decom-

position in the first week accounted for 1441% of total

decomposition.

In the LP and YJ sites, which belong to the sub-tropical

zone, rates of SOC decomposition differed substantially.The decomposition rates in the LP site from Cunninghamia

lanceolata forest were faster than those in the YJ site. There

was the same trend under evergreen broadleaf forest.

Comparing the decomposition rates between the Cunning-

hamia lanceolata and evergreen broadleaf forests, the

maximum decomposition rate of the former was higher

than that of the latter (Fig. 1).

In the CBM and QLM sites, which belong to the

temperate zone, the rates of SOC decomposition varied

greatly (Fig. 2). During the incubation period, the

maximum SOC decomposition rate occurred during the

second day of incubation. After the initially high decom-

position rate, there was a gradual decrease in all samples.

There were only small differences in the rates of SOC

decomposition. In the CBM site, SOC decomposition rates

from different types of vegetations varied and followed the

order spruce-fir4poplar and birch4Pteridophyta. In the

QLM sites, SOC decomposition rates from different types

of vegetation followed the order Picea crassifolia4

Sabinaprezew alskii4shrub forests.

3.2. SOC pools and dynamics

The distributions of the three pools of SOC have distinctdifferences in different forests mainly because chemical

components of litterfall vary greatly which could cause

different effects on SOC decomposition rate. Although the

sizes of the SOC pools in the study areas were different,

ARTICLE IN PRESS

0

2

4

6

8

10

12

14

16

18

20

0 10 20 30 40 50 60 70 80 90

Incubation time (days)

CO2-Cevolved(mg

Ckg-1day-1)

Cunninghamia lanceolata(LP)

Cunninghamia lanceolata(YJ)

Evergreen broadleaf(LP)

Evergreen broadleaf(YJ)

Fig. 1. Decomposition rates of SOC from two vegetations under sub-

tropical zone.

L. Yang et al. / Journal of Environmental Management 85 (2007) 690695692


4/6

there was a commonality in that the sizes of Ca were

smaller (Table 2). The Ca pool comprised $13% of SOC

with an average MRT of 219 days. Because Ca is active, a

small change in pool size can cause a marked change in

atmospheric CO2 concentration and cause a sharp effect on

the global climate. Therefore, it is vital to take measures to

decrease the loss of Ca and increase the stock of the stabileC pool. The Cs pool comprised $2565% with an average

MRT of 78 yr. The Cr pool accounted for $3580%. There

was a greater retention of C in the forests. These results are

consistent with the existence of at least a small, labile

carbon pool and a much larger, more recalcitrant pool

(Collins et al., 2000).

The proportion of Ca in the YJ site was greater than in

the other study sites and this site had the lowest MRT for

both the Ca and Cs pools. This indicated that the soil in the

YJ site was active. The QLM site had the most stable pool,

and the CBM site had the second most stable pool (Table

2). So the stable C pools followed the order

QLM4CBM4LP4YJ which was consistent with the

temperature change in the study sites.

4. Discussion

Our data indicated that SOC decomposed rapidly during

the early incubation stages and gradually slowed down to a

comparative steady state. During the early stages of

incubation, the decomposed SOC consisted mostly of

accumulations of Ca, presumably derived from vegetation.

The Ca pool comprised $13% of the SOC with an average

MRT of 219 days. The Cs pool comprised about 2565%

with an average field MRT of 78 yr. The Cr pool accounted

for $3580%. The sizes of the Cs and Cr pools indicatedthat the SOC in the cold arid QLM site was the most

stable. Among the different forests sampled, the SOC

contents followed the order CBM4QLM4YJ4LP. The

ratio of the Ca pool to the CSOC contents followed the

order YJ4LP4CBM4QLM, with MRT showing the

inverse order YJ (MRT 8 days)4LP (MRT 47

days)4CBM (MRT 56 days)4QLM (MRT 80 days).

These orders correspond closely to the rank order of mean

annual temperature (MAT) across the study areas: YJ

(18.1 1C)4LP (15 1C)4CBM (5 1C)4QLM (3 1C). Our

results are thus consistent with the conclusion that

temperature is the most important environmental factor

that affects microbial processes in soils and consequently

SOC decomposition dynamics. Although a significant

correlation between soil temperature and SOC decomposi-

tion is well established (Singh and Gupta, 1977; Raich and

Schlesinger, 1992; Lloyd and Taylor, 1994; Kirschbaum,

1995; Katterer et al., 1998), there is no agreement about

which function to use to describe this relationship.

Litterfall properties could also affect SOC decomposi-

tion under the same environment. In particular, the lignin

concentration and lignin/N ratios of litterfall, both

generally higher in conifers than in broadleaved trees

(Perry et al., 1987; Petersen et al., 1997), are expected to be

negatively related to decomposition rates. Our resultsindicate that SOC decomposition rate in Cunninghamia

lanceolata plantations was actually faster than that in

evergreen broadleaf forests in the sub-tropical zone,

contradicting some other researchers conclusions (Wu

et al., 1996). The relationships between the decomposition

rate and litterfall properties need to be studied further.

Soil texture, especially soil clay content, is also an

important factor influencing SOC dynamics under the

same climatic conditions. It was apparent that the fine

texture of clay soil reduced the amount of SOC miner-

alization which contributed to accumulation of SOC. Clay

ARTICLE IN PRESS

0

5

10

15

20

25

0 10 20 30 40 50 60 70 80 90

Incubation time (days)

CO2-Cevolved(mgCkg

-1d

ay-1) Spruce-fir(CBS)

Poplar and birch(CBS)

Pteridophyta(CBS)

Picea crassifolia(QLS)

Sabinaprezew alskii(QLS)

shrub(QLS)

Fig. 2. Decomposition rates of SOC from different vegetations under

temperate zone.

Table 2

Pool sizes and laboratory mean residence times (MRT) of soil for the active, slow and resistant carbon pools from LP, YJ, CBM and QLM sites

Sample Depth (cm) Ca (gkg1) MRTLab (days) Ca/SOC (%) Cs (gkg

1) MRTLab (yr ) Cs/SOC (%) Cr (gkg1) MRTLab (yr) Cr/SOC (%)

LP3 020 0.21 47 0.99 11.6 3 54.79 9.36 500 44.22

LP7 015 0.31 50 1.25 12.55 27 50.75 11.87 500 50.00

YJ1 015 0.47 8 1.53 6.65 2 21.61 23.64 620 76.86

YJ2 018 0.48 7 1.81 5.24 2 19.71 20.87 620 78.48

CBM0 011 0.65 56 1.13 36.54 12 63.32 20.52 250 35.55

CBM14 012 0.69 11 0.93 18.75 4 25.20 54.97 250 73.87

CBM22 07 1.38 35 1.15 64.08 25 53.25 54.88 250 45.61

QLM2 030 1.33 45 1.49 36.5 16 41.00 52.53 173 59.00

QLM7 030 1.73 161 2.41 27.56 33 38.31 44.38 173 61.70

QLM8 030 0.65 47 0.92 28.81 3 41.05 41.37 500 58.95



5/6

content affected the turnover of active carbon pools and

the stabilization efficiency of slow carbon pools (Sorenhen,

1981; Hassink, 1994). In our observations, there was no

significant correlation between the rate of SOC decom-

position and soil clay content (Fig. 3). Similarly, Gregorich

et al. (1991) found that soil texture had no significant effect

on the decomposition rate of SOC. However, Wang et al.

(2003a, b) observed that there was a negative correlationbetween clay content and the rate of SOC decomposition,

consistent with the results of Franzluebbers et al.

(1999a, b). A common practice in modeling is to assume

that the rate of SOC decomposition decreases with

increasing clay content (Jensen et al., 1994; Coleman and

Jenkinson, 1996). Soil textural effects on SOC decomposi-

tion could be confounded by clay mineralogy, chemistry of

SOM, microbial composition, inhibiting or toxic factors

such as extreme pH or heavy metals, and other soil

properties that are related to the clay content of the soils

tested. Such confounding effects are more difficult to

discern when only a small number of soils are used (Wanget al., 2003a, b).

5. Conclusions

The dynamics of SOC decomposition followed a two-

phase pattern in which SOC was rapidly decomposed in the

initial incubation stages and its decomposition gradually

slowed down in a comparative steady stage. The reason

was that SOC was composed of two parts: active (easily

mineralizable) and slow and resistant carbon pools

(anti-mineralizable components). This could be described

by a three-pool first-order model. Many researchers have

shown that the three-pool first-order model could be used

to interpret the dynamics of forest SOC. Pool sizes and

MRT of the three pools were determined by the model. The

Ca pool comprised $13% of SOC with an average MRT

of 219 days. The C pool comprised $2565% with an

average MRT of 78 yr. The Cr pool accounted for

$3580%. The analyses of pool sizes and MRT give

accurate estimates of SOC dynamics that may be used in

decision making related to global climate change. However

the pool sizes and MRT of the three pools from different

forest soils had obvious differences which showed that

SOC decomposition was affected by the environment and

other factors. By analyzing the factors that control SOC

decomposition, it was found that temperature (MAT) was

a good predictor of SOC values and the active pool size,

but that other factors, such as vegetation type, may modify

SOC and pool composition. Further evaluation of the

relationships between SOC decomposition and environ-

mental factors is required.

Acknowledgements

This research was sponsored by the Canadian Interna-

tional Development Agency (CPR/00/G33/A/1G/99) and

the National Natural Science Foundation of China

(Project 40231016). Part of this work was completed while

the author was a visiting scholar at University of Toronto,

Canada. The authors thank Dr. Chen Minzhen, Prof. Tian

Qingjiu, Prof. Pan Genxing, Prof. Li Lianqing, Ms. Zhang

Yongqin, Dr. Li Zhiwei, Ms. Lu Xiongjie, Dr. Hui

Fengming, Dr. Jin Zhenyu, and Dr. Xia Xueqi for various

assistance.

References

Cabrera, M.L., 1993. Modeling the flush of nitrogen mineralization caused

by drying and rewetting soils. Soil Science Society of America Journal

57, 6366.

Chang, Z.Q., Shi, Z.M., Feng, Q., 2005. Effect of temperature in different

communities on soil respiration in Qilian Mountains. Chinese Journal

of Agrometeorology 26 (2), 8589.

Chinese soil taxonomy, 2001. Chinese Soil Taxonomy Research Group,

Institute of Soil Science, Academia Sinica, Cooperative Research

Group on Chinese Soil Taxonomy. Key to Chinese Soil Taxonomy,

third ed. Chinese Science and Technology University Press, [M]. Hefei,

pp. 1275.

Coleman, K., Jenkinson, D.S., 1996. RothC-26.3a model for theturnover of carbon in soil. In: Powlson, D.S., Smith, P., Smith, J.U.

(Eds.), Evaluation of Soil Organic Matter Models, NATO ASI Series,

Vol. I38. Springer, Berlin, pp. 237246.

Collins, H.P., Elliott, E.T., Paustian, K., Bundy, L.G., Dick, W.A.,

Huggins, D.R., Smucker, A.J.M., Paul, E.A., 2000. Soil carbon pools

and fluxes in long-term corn belt agroecosystems. Soil Biology &

Biochemistry 32, 157168.

Deans, J.R., Molina, J.A.E., Clapp, C.E., 1986. Models for predicting

potentially mineralizable nitrogen and decomposition rate constants.

Soil Science Society of America Journal 50, 323326.

Elliott, E.T., Burke, I.C., Monz, C.A., Frey, S.D., Paustian, K.H., Collins,

H.P., Paul, E.A., Cole, C.A., Blevins, R.L., Frye, W.W., Lyon, D.W.,

Halvorson, A.D., Huggins, D.R., Turco, R.F., Hickman, M.V., 1994.

Terrestrial carbon pools: Preliminary data from the Corn Belt and

Great Plains regions. In: Doran, J.W., Coleman, D.C., Bezdicek, D.F.,Stewart, B.A. (Eds.), Defining Soil Quality for a Sustainable

Environment. American Society of Agronomy, Madison, pp. 179191.

Fang, J.Y., Liu, G.H., Xu, S.L., 1996. Soil carbon pool in China and its

global significance. Journal of Environmental Science (China) 8,

249254.

Franzluebbers, A.J., Haney, R.L., Hons, F.M., 1999a. Relationships of

chloroform fumigationincubation to soil organic matter pools. Soil

Biology & Biochemistry 31, 395405.

Franzluebbers, A.J., Haney, R.L., Hons, F.M., Zuberer, D.A., 1999b.

Assessing biological soil quality with chloroform fumigationincuba-

tion: why substract a control? Canadian Journal of Soil Science 79,

521528.

Goh, K.M., Stout, J.D., OBrien, B.J., 1989. The significance of

fractionation in dating the age and turnover of soil organic matter.

New Zealand Journal of Science 27, 6972.

ARTICLE IN PRESS

0

10

20

30

40

50

60

0 10 20 30 40

Clay content (%)

Cr(gkg-1)

Fig. 3. The relationships between clay content and resistant carbon pool

from different study sites.

L. Yang et al. / Journal of Environmental Management 85 (2007) 690695694


6/6

Gregorich, E.G., Kachanoski, R.G., Voroney, R.P., 1989. Carbon

mineralization in soil size fractions after various amounts of aggregate

disruption. Journal of Soil Science 40, 649659.

Gregorich, E.G., Voroney, R.P., Kachanoski, R.G., 1991. Turnover of

carbon through through the microbial biomass in soils with different

textures. Soil Biology & Biochemistry 23, 799805.

Hassink, J., 1994. Effects of soil texture and grassland management on soil

organic C and N and rates of C and N mineralization. Soil Biology& Biochemistry 9, 12211231.

Hudson, R.J.M., Gherini, S.A., Goldstein, R.A., 1994. Modeling the

global carbon cycle: nitrogen fertilization of the terrestrial biosphere

and the missing CO2 sink. Global Biogeochemical Cycles 8,

307333.

Jensen, C., Stougaard, B., Ostergaard, H.S., 1994. Simulation of nitrogen

dynamics in farm land areas of Denmark (19891993). Soil Use and

Management 10, 111118.

Katterer, T., Reichstein, M., Andren, O., Lomander, A., 1998. Tempera-

ture dependence of organic matter decomposition: a critical review

using literature data analysed with different models. Biology and

Fertility of Soils 27, 258262.

Kirschbaum, M.U.F., 1995. The temperature dependence of soil organic

matter decomposition, and the effect of global warming on soil organic

C storage. Soil Biol Biochem 27, 753760.Leavitt, S.W., Paul, E.A., Pendall, E., Pinter, J.R., Kimble, B.A., 1997.

Field variability of carbon isotopes in soil organic carbon. Nuclear

Instruments and Methods in Physics Research B 123, 451454.

Little, T.M., Hills, F.J., 1975. Statistics Methods in Agricultural Research,

second ed. University of California, Davis, p. 242.

Lloyd, J., Taylor, J.A., 1994. On the temperature dependence of soil

respiration. Functional Ecology 8, 315323.

Nelson, D.W., Sommers, L.E., 1975. A rapid and accurate method for

estimating organic carbon in soil. Proceedings of the Indiana Academy

of Science 84, 456462.

Parton, W.J., Schimel, D.S., Cole, C.V., 1987. Analysis of factors

controlling soil organic matter levels in great plains grasslands.

Journal of Soil Science Society of America Journal 51, 11731179.

Paul, E.A., Morris, S.J., Bohm, S., 2001a. The determination of soil C

pool sizes and turnover rates: biophysical fractionation and tracers. In:Lal, R., Kimble, J.M., Follett, R.F. (Eds.), Assessment Methods for

Soil C Pools. CRC Press, Boca Raton, FL.

Paul, E.A., Collins, H.P., Leavitt, S.W., 2001b. Dynamics of resistant soil

carbon of Midwestern agricultural soils measured by naturally

occurring 14C abundance. Geoderma 104, 239256.

Perry, D.A., Choquette, C., Schroeder, P., 1987. Nitrogen dynamics in

conifer-dominated forests with and without hardwoods. Canadian

Journal of Forest Research 17, 14341441.

Peterson, E.B., Peterson, N.M., Simard, S.W., Wang, J.R., 1997. Paper

birch managers handbook for British Columbia. B.C. Ministry ofForests, Victoria, B.C. FRDA Report no. 271.

Raich, J.W., Schlesinger, W.H., 1992. The global carbon dioxide flux in

soil respiration and its relationship to vegetation and climate. Tellus

44B, 8199.

Schimel, D.S., 1995. Terrestrial ecosystems and the carbon cycle. Global

Change Biology 1, 7791.

Singh, J.S., Gupta, S.R., 1977. Plant decomposition and soil respiration in

terrestrial ecosystems. Botanical Review 43, 449526.

Sorenhen, L.H., 1981. Carbon-nitrogen relationships during the humifica-

tion of cellulose in soils containing different amounts of clay. Soil

Biology & Biochemistry 13, 313321.

Sollins, P., Gassman, C., Paul, E.A., Swanston, C., Lajtha, K., Hei, J.W.,

Elliott, E.T., 1999. Soil carbon and nitrogen: pools and fractions. In:

Robertson, G.P., Bledsoe, C.S., Coleman, D.C., Sollins, P. (Eds.),

Standard Soil Methods for Long-Term Ecological Research. OxfordUniversity Press, New York, pp. 89105.

Sparks, D.L., 1996. Methods of Soil Analysis, Part III. Soil Science

Society of America, American Society of Agronomy, Madison, WI.

Wang, M., Ji, L.Z., Li, Q.R., et al., 2003a. Effects of soil temperature and

moisture on soil respiration in different forest types in Changbai

Mountain. Chinese Journal of Applied Ecology 14 (8), 12341238.

Wang, W.J., Dalal, R.C., Moody, P.W., Smith, C.J., 2003b. Relationships

of soil respiration to microbial biomass, substrate availability and clay

content. Soil Biology & Biochemistry 35, 273284.

Wu, W.D., Huan, C.C., Liu, R.L., et al., 1996. A study on litter

decomposition and the dynamic state of nutrient release of different

types of forest in Jiangxi Province. Acta Agriculturae Universitatis

Jiangxiensis 18 (1), 6166.

Wu, W.D., Huang, C.C., Wang, J.M., et al., 1997. The status and

distribution of soil organic matter and N in the soil profiles underdifferent types of forest in Jiangxi. Acta Agriculturae Universitatis

Jiangxiensis 19 (3), 9095.

ARTICLE IN PRESS


soil organic carbon decomposition and carbon pools in

Documents