lou 2004

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CO2 emissions from subtropical arable soils of China

Yunsheng Loua,b,*, Zhongpei Lic,1, Taolin Zhangc, Yongchao Lianga

aCollege of Natural Resources and Environmental Sciences, Nanjing Agricultural University, Nanjing, Jiangsu 210095, Chinab Institute of Applied Ecology, The Chinese Academy of Sciences, Shenyang 110016, China

c Institute of Soil Science, The Chinese Academy of Sciences, P.O. Box 821, Nanjing 210008, China

Received 19 February 2003; received in revised form 23 April 2004; accepted 18 May 2004

Abstract

CO2 efflux plays a key role in carbon exchange between the biosphere and atmosphere, but our understanding of the mechanismcontrolling its temporal and spatial variations is limited. The purpose of this study is to determine annual soil CO 2 flux and assess its

variations in arable subtropical soils of China in relation to soil temperature, moisture, rainfall, microbial biomass carbon (MBC) and

dissolved organic carbon (DOC) using the closed chamber method. Soils were derived from three parent materials including granite (G),

tertiary red sandstone (T) and quaternary red clay (Q). The experiment was conducted at the Ecological Station of Red Soil, The Chinese

Academy of Sciences, in a subtropical region of China. The results showed that soil CO2 flux had clear seasonal fluctuations with the

maximum value in summer, the minimum in winter and intermediate in spring and autumn. Further, significant differences in soil CO2 flux

were found among the three red soils, generally in the order of G>T>Q. The average annual fluxes were estimated as 2.84, 2.13 and

1.41 kg CO2 mK2 yearK1 for red soils derived from G, T and Q, respectively. Soil temperature strongly affects the seasonal variability of soil

CO2 flux (85.0–88.5% of the variability), followed by DOC (55.8–84.4%) and rainfall (43.0–55.8%). The differences in soil CO2 flux among

the three red soils were partly explained by MBC (33.7–58.9% of the variability) and DOC (23.8–33.6%).

q 2004 Elsevier Ltd. All rights reserved.

Keywords: Dissolved organic carbon; Microbial biomass carbon; Parent material; Soil CO2 flux; Soil temperature

1. Introduction

The atmospheric CO2 concentration has increased at the

rate of 0.5% annually and the major increase has occurred

since the 1850s (Lal and Kimble, 1995). The fossil fuel

combustion and land use changes are two principal human

activities attributed to the increase. A global flux of soil CO2emission from soils accounts for 68–75 pg CO2–C year

K1

(Eswaran et al., 1993; Mosier, 1998; Raich and Potter,

1995). There are a large number of documents on soil CO2emission around the world. However, most of the

observations have been found in the temperate or tropical

regions (Lal and Kimble, 1995; Mosier, 1998), very few

studies have addressed soil CO2 emissions in subtropical

regions. Red soils, one of the typical subtropical soils of

China, are widely distributed in southeast of China (on the

north bound by the Yangtze River and on the west bound by

the Yun-Gui Plateau). Red soils cover about 1.13

million km2 or 11.8% of the country’s land surface, and

support 22.5% of the nation’s population (Zhao, 2002).

However, with rapid economic and social development,

these soils have been degraded due to long-term unsustain-able land use. Consequently, most fields have had low

organic carbon content and low crop productivity. The

dynamics of soil carbon pool depends on the balance

between inputs and outputs of organic carbon in soils.

Therefore, it is essential to assess the CO2 emission in the

southeast extensive regions of China for better under-

standing of the roles of soil management and mechanisms

regulating the carbon storage and CO2 emission processes in

the regions.

0038-0717/$ - see front matter q 2004 Elsevier Ltd. All rights reserved.

doi:10.1016/j.soilbio.2004.05.006

Soil Biology & Biochemistry 36 (2004) 1835–1842

www.elsevier.com/locate/soilbio

* Corresponding author. Address: College of Natural Resources and

Environmental Sciences, Nanjing Agricultural University, Nanjing, Jiangsu

210095, China. Tel.: C86-25-84396393; fax: C86-25-86881000.

E-mail addresses: [email protected] (Y. Lou), [email protected]

(Z. Li).1 Tel.: C86-25-86881323; fax: C86-25-86881000.

http://www.elsevier.com/locate/soilbiohttp://www.elsevier.com/locate/soilbio

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Soil CO2 emission is the sum of root respiration and

microbial respiration. Most studies have focused on the

effects of temperature and soil moisture content on soil CO2flux (Davidson et al., 1998; Frank et al., 2002; Mielnick and

Dugas, 2000; Raich and Potter, 1995). This relationship

between soil CO2 flux and soil temperature was described

using an exponential equation (Davidson et al., 1998;Mielnick and Dugas, 2000). Soil moisture content directly

affects roots and microbial activities, or indirectly influ-

ences soil physical and chemical properties (Raich and

Schlesinger, 1992; Schimel and Clein, 1991). In addition,

soil CO2 emission is also correlated with other soil

properties such as carbon content, cation exchange capacity

and free iron content (La Scala et al., 2000). Dissolved

organic carbon (DOC) has also been used as an indicator of

carbon availability to soil microorganisms (Boyer and

Groffman, 1996). However, observations on the effects of

DOC on microbial activity are inconclusive. For example,

Burford and Bremner (1975) suggested that DOC was

related to heterotrophic microbial processes such as

respiration and denitrification, while Cook and Allan

(1992) observed that soil respiration rates declined during

a 210-d incubation, but DOC content remained constant or

increased.

Effects of vegetations on CO2 emissions have been

extensively studied (Kudeyarov and Kurganova, 1998;

Frank et al., 2002), but little attention has been paid to the

effects of soil parent materials on CO2 emission. The red

soils investigated in this study are derived from three parent

materials including quaternary red clay (Q), tertiary red

sandstone (T) and granite (G). Soil properties are largely

controlled by soil parent materials and pedogenic processes(well-developed or less-developed soils) (Miller and

Donahue, 1990). For instance, the red soil derived from

quaternary red clay generally contains higher clay content

than that derived from tertiary red sandstone or granite.

This may be related to the desilicification, one important

process of red soil formation, following the order QOTOG

(Xi, 1998; Zhao, 2002). Soil properties affect soil CO2emissions (La Scala et al., 2000; Mielnick and Dugas, 2000;

Raich and Schlesinger, 1992) and therefore CO2 emissions

from red soils may vary with the parent materials. The

objective of this study was to assess the dynamics of soil

CO2 flux as affected by soil temperature, moisture, and DOC

in subtropical red soils of China derived from three kinds of

parent materials.

2. Materials and methods

2.1. Site description

Field experiments were located at the Ecological Station

of Red Soil, The Chinese Academy of Sciences, Yingtan,

Jiangxi Province, China (28815 030 00N, 116855030 00E). Soil

CO2 emissions were measured from August 1999 to July

2000. The region has a typical subtropical monsoon climate

with an annual precipitation of 1795 mm, annual evapor-

ation of 1318 mm and a mean annual temperature of

17.6 8C. Based on mean monthly temperature, clear four

seasons can be distinguished as spring (February to April),

summer (May to July), autumn (August to October) and

winter (November to January).

The field study was conducted on three upland agro-

ecosystems. The soils were sandy loam soil, clay soil, and

sand soil, derived from tertiary red sandstone (T),

quaternary red clay (Q) and granite (G), respectively.

Relevant physical and chemical properties of soils are

listed in Table 1. The experimental fields were planted

with foxtail millet (Setaria italica L.) and barley

( Hordeum vulgare L.) from June 5 to October 15 and

from November 5 to May 15, respectively. During the

growing seasons, each crop was fertilized with the same

amounts of fertilizers (60N, 40P and 60K kg haK1). The

millet–barley rotation is a popular crop system distributedin upland arable soils of this region.

2.2. Soil CO2 flux, soil temperature and soil

moisture content

Soil carbon dioxide emissions were measured using a

portable infrared analyzer (LI-6262, LICOR Inc., Lincoln,

NE, USA) by determining CO2 accumulation in closed

chambers. The chambers had a diameter of 25.5 cm and a

height of 31.0 cm. At the beginning of the experiment, the

chambers were placed on circular collars that had been

Table 1

Selected physico-chemical properties of the soils (0–20 cm)

Parent

material

Total C (g kgK1) Total N (g kgK1) Clay (g kgK1) pH (H2O) Bulk density

(g cmK3)

Main clay

mineral

(!1 mm) (!2 mm)

Tertiary 6.77G0.08b 0.51G0.01b 216G4.3b 239G7.2b 6.28G0.02b 1.26G0.01b Kaolinite,

montmorillonite

Quaternary 7.35G0.12a 0.79G0.02a 370G5.5a 415G9.5a 5.15G0.01a 1.35G0.02a Kaolinite,

hydromicas

Granite 4.96G0.09c 0.34G0.01c 81.0G3.1c 92.0G5.7c 6.30G0.02b 1.19G0.01c Kaolinite

Means in a column followed by the same letter were not significantly different (P%0.05) by Duncan’s test method. Values are the meanGSE (standard error).

Y. Lou et al. / Soil Biology & Biochemistry 36 (2004) 1835–18421836

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inserted 5 cm into the soil between plants. Plants were

grown approximately 30 cm away from the collars to

minimize or avoid plant roots’ possibly penetrating into

the soils below the collars, which affects CO2 fluxes. During

the whole experiment, the soil surface within the collars was

kept free of any live vegetation and residue by pulling out

seedlings with roots.In each field, the measurements were made at eight

locations (each 5–10 m apart) every 2 weeks over the whole

experiment. To avoid extremely high temperatures at noon,

all measurements were conducted in the morning

(09:00–11:00 a.m.). We have previously found that soil

CO2 fluxes in the morning generally well represented the

mean daily fluxes (Lou et al., 2003). Gas samples were

collected from the chambers using a 50 ml gas-tight syringe

and then injected into evacuated bags made of inert

aluminum-coated plastic. Soil CO2 fluxes were calculated

from the rate of increase in CO2 concentration (ml mK3) in

the chamber during a 45-min period in warm seasons or60-min in cold seasons.

Soil temperatures (at depth 0–5 cm) and moisture content

(0–10 cm) in the upper soil layer were also determined. Soil

temperatures were measured using soil thermometers

inserted to a depth of 5 cm inside the chambers. Soil

moisture content was estimated by the relative water content

as the percentage of water-filled pore space (WFPS). The

water mass content of soil (g gK1) was determined by

gravimetry with oven drying at 105 8C for 24-h. Soil WFPS

was calculated based on the equation (Franzluebbers, 1999):

WFPSZðSWC!BDÞ = ½1K ðBD = PDÞ, where SWC is the

soil water content (g gK1), BD is the bulk density (g cmK3),

and PD is the particle density. Daily precipitationwas recorded at a meteorological station nearby the

experimental location.

2.3. Crop biomass

At maturity, foxtail millet or barley was cut from 0.25-m2

quadrats with five replicates, and soil cores were sampled

for measurements of root biomass. Green plant materials

were separated from the dead and oven-dried (70 8C). The

total aboveground biomass was calculated by summing the

green and dead biomass. For the measurement of ground

biomass, five soil cores at the depth of 0–30 cm (10 cm in

diameter) were taken. Roots were washed with water, and

oven-dried (70 8C).

2.4. Soil sampling and analysis

Before fertilizer applications, background soil samples

(0–20 cm) were collected, air-dried, ground and sieved forthe analyses of total C and N, clay content and pH. Total

carbon was determined with dichromate oxidation method,

total N with Kjeldahl method, pH (1:1 soil–water paste)

with electrometry (pH electrode), and clay content with

pipette method (Page et al., 1982). Each measurement was

replicated five times.

Moist soil (0–20 cm) was taken from each location (eight

replicates per experimental field) on each sampling date.

The moist soil samples were sieved (2 mm) to remove the

root materials. Before biochemical analysis, soils were

adjusted to 60% of water holding capacity (WHC) and

incubated at 25 8C for 10 days. WHC was determined

according to Choudhary et al. (1995). Microbial biomass

carbon (MBC) was measured using the fumigation–extrac-

tion method (Vance et al., 1987). Briefly, after 10-d

incubation, one portion of moist soils (20 g oven-dried

equivalent) was extracted immediately with 50 ml of 0.5 M

K 2SO4 by shaking for 30 min, filtered through Whatman

No. 42 paper, and frozen at K20 8C until analyzed.

Simultaneously, another portion of soil samples was

fumigated with ethanol-free chloroform for 24 h at 25 8C

and then extracted as above. MBC was calculated as the

difference between the total organic carbon in the fumigated

and non-fumigated extracts using a K EC factor of 0.38. DOC

was extracted with 0.5 M K 2SO4 from the non-fumigatedsoils (Ross et al., 1999; Hogberg and Hogberg, 2002)

and measured by dichromate oxidation (Jenkinson and

Powlson, 1976).

2.5. Data statistics

SPSS software (SPSS Inc., 2000) was used for data

analyses. All data were expressed as meansGstandard

errors and tested by Duncan’s method at the 5 or 1%

probability level. Simple and multiple regression pro-

cedures were used to describe the correlation between

soil flux and soil temperature, soil moisture, rainfall,

MBC and DOC.

Table 2

Biomass production in the soils under millet–barley rotation system

Parent material Foxtail millet Barley

Aboveground (kg haK1) Ground (kg haK1) Aboveground (kg haK1) Ground (kg haK1)

Tertiary 2015G83.1a 423G17.5a 2215G85.3a 343G13.2a

Quaternary 1988G67.5a 377G12.8a 2142G61.9a 321G12.4a

Granite 1895G64.4a 367G12.5a 1996G57.6a 307G8.89a

Mean in a column followed by the same letter were not significantly different (P%0.05) by Duncan’s test method. Values are the meanGSE (standard error).

The biomass data were measured at maturity stage. Foxtail millet and barley were grown from June 5 to October 15 and from November 5 to May 15,

respectively.

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3. Results and discussion

3.1. Biomass production

No significant differences in both aboveground and

ground biomass were found among the three red soils. The

aboveground biomass for foxtail millet and barley averaged1895–2015 and 1996–2215 kg haK1, respectively. There

were also no significant differences in ground biomass

(Table 2).

3.2. Changes of soil CO2 flux and related factors

Seasonal soil CO2 fluxes are shown in Fig. 1. Fluxes

declined from the beginning of the experiment in August to

the winter period, followed by a gradual increase in their

highest values in summer, and then a decrease until the end

of this study (July). Soil CO2 fluxes differed among the three

red soils derived from various parent materials, following

the order of G>T>Q. Based on soil CO2 fluxes, the average

annual soil CO2 fluxes were estimated as 2.84G0.34,

2.13G0.31 and 1.41G0.29 kg CO2 mK2 yearK1 for red

soils derived from G, T and Q, respectively. These were

calculated by summing up the products of the 26 daily

averages multiplied by 14-d (the interval time).

Seasonal changes in soil temperature followed the order

of summerOautumnOspringOwinter, which corresponded

to seasonal variations in soil CO2 flux described above

(Fig. 1). However, no significant differences in soil

temperature were observed among the three red soils

(Fig. 2). Soil moisture content (expressed as % of WFPS)

in autumn was lower than in other three seasons (Fig. 3).No significant changes in soil moisture were found among

the seasons except for winter and spring.

DOC content varied seasonally. The maximum value of

DOC was observed in summer or autumn, and the minimum

in winter (Fig. 4). Furthermore, significant differences in the

content of DOC were found among the three red soils

(Q>G>T, P%0.05). Regarding the content of MBC, no

obvious seasonal fluctuation was observed (Fig. 5), butsignificant differences were found among the three red

soils, in general, with the sequence of GOTOQ (P%0.05,

Fig. 5).

3.3. Soil CO2 flux versus soil temperature, moisture content

and rainfall

Soil CO2 fluxes showed significant seasonal fluctuations

with the highest value in summer, the lowest in winter and

intermediate in spring and autumn (Fig. 1). Higher CO2fluxes during the summer may be attributed to increased

root respiration and activated microbial respiration. Active

root growth increases root respiration, while rapid organic

carbon transformation increases microbial respiration as

well. Both root growth and microbial respiration increased

in warm soil temperature (around 30 8C) and proper

precipitation (43% total annual rainfall) in summer

Fig. 1. Variations of soil CO2 flux in red soils derived from three parent

materials. T, Q and G represent red soils derived from tertiary red

sandstone, quaternary red clay and granite, respectively. Values are the

mean determined in the morning (09:00–11:00 a.m.) on sampling dates.

The study was from August, 1999 to July, 2000. Vertical bars indicate the

standard error of the averages.

Fig. 2. Changes in soil temperature in red soils derived from three parent

materials (0–5 cm). T, Q and G represent red soils derived from tertiary red

sandstone, quaternary red clay and granite, respectively. Values are the

mean determined in the morning (09:00–11:00 a.m.) on sampling dates.

The study was from August, 1999 to July, 2000. Vertical bars indicate the

standard error of the averages.

Fig. 3. Changes in soil moisture in red soils from three parent materials. T,

Q and G represent red soils derived from tertiary red sandstone, quaternary

red clay and granite, respectively. WFPS indicates water-filled pore space.

Values are the mean determined in the morning (09:00–11:00 a.m.) on

sampling dates. The study was from August, 1999 to July, 2000. Vertical

bars indicate the standard error of the averages.


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(Figs. 2 and 6). In contrast, lower fluxes in winter may be

connected with depressed root and microbial respiration

caused by low soil temperatures ((10 8C). Figs. 1 and 2

showed significantly positive correlation between soil CO2flux and soil temperature. Temperature accounted for

approximately 85–88.5% of the seasonal variability for

soil CO2 fluxes (Table 3). Our observation is in agreement

with other recent reports (McInerney and Bolger, 2000;

Mielnick and Dugas, 2000).

Soil moisture was another important factor influencing

soil CO2 production and emission (Solomon and Cerling,

1987). Linn and Doran (1984) found a close relationship

between microbial respiration and soil moisture content

with a peak of activity at 60% WFPS (soil water-filled pore

space). However, our study indicates that soil moisture hadweak effects on soil CO2 flux. These moisture effects also

depended upon soil types as found in other studies

(Davidson et al., 1998; Knapp et al., 1998; Kudeyarov and

Kurganova, 1998). A significant correlation between soil

CO2 flux and soil moisture was observed only for the red

soil derived from quaternary red clay (Q) (Table 3), that had

relatively higher soil moisture values than the other two

soils (Fig. 3). It has been reported that no significant

relationship was found between soil respiration and WFPS,

though soil WFPS varied from 45 to 60% in the sandy loam

and from 50 to 70% in the sandy clay (Chantigny et al.,1999). Several factors contribute to this poor relationship.

Firstly, the seasonal ranges of soil moisture content in the

field were small (Fig. 3) (Chantigny et al., 1999). Secondly,

soil moisture regimes depended on not only precipitation

but also evaporation, and were also affected by soil

properties and plant growth. Thirdly, in this study, soil

moisture was measured to a depth of only 10 cm which was

too shallow to reflect the potential capacities of deep roots

and microbial respiration. Wet soil at deep depth may

counteract the effects of near-surface soil moisture on soil

CO2 flux (Mielnick and Dugas, 2000; Singh et al., 1998).

Fig. 4. Changes in dissolved organic carbon (DOC) in red soils derived

from three parent materials. T, Q and G represent red soils derived from

tertiary red sandstone, quaternary red clay and granite, respectively. Values

are the mean determined in the morning (09:00–11:00 a.m.) on sampling

dates. The study was from August, 1999 to July, 2000. Vertical bars

indicate the standard error of the averages.

Fig. 5. Changes in microbial biomass carbon (MBC) in red soils derived

from three parent materials. T, Q and G represent red soils derived from

tertiary red sandstone, quaternary red clay and granite, respectively. Values

are the mean determined in the morning (09:00–11:00 a.m.) on sampling

dates. The study was from August, 1999 to July, 2000. Vertical bars

indicate the standard error of the averages.

Fig. 6. Dynamics of precipitation at a meteorological station near the

experimental location during this study (August, 1999 to July, 2000).

Values represent the average cumulative precipitation every 2 weeks

(14 days). Vertical bars indicate the standard error.

Table 3

Correlation analysis between soil CO2 flux and soil temperature, rainfall,

dissolved organic C, soil moisture and microbial C in soils as grouped

according to their parent materials

Parent

material

CO2 flux

versus

Correlation

coefficients ( R2)

Simple

regression

Partial by

stepwise

regression

Tertiary Soil temperature 0.885** 0.857**

Rainfall 0.514** NS

Dissolved organic C 0.558** NS

Soil moisture NS NS

Microbial C NS NSQuaternary Soil temperature 0.851** 0.714**

Rainfall 0.574** NS


Soil moisture 0.198* NS

Moicrobial C NS NS

Granite Soil temperature 0.850** 0.813**

Rainfall 0.430* NS


Soil moisture NS NS

Moicrobial C NS NS

*Significant at P%0.05; **significant at P%0.01; ns, not significant. The

correlation coefficients were calculated from the data of observations

during the entire duration of experiment.


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Soil temperature and plants played important roles in

regulating soil respiration (Table 3). Soil moisture content

in the subtropical regions seldom decreased to the levels that

would limit microbial activities and hence may not be a

limiting factor controlling soil CO2 flux (Fig. 3).

In this experiment, rainfall was the main input of water to

soils, and has been found to be one of the important climaticfactors controlling soil CO2 flux, though there was no clear

relationship between soil CO2 flux and soil moisture as

discussed above (Table 3). In contrast to soil moisture

(Fig. 3), the rainfall varied largely with seasons with the

maximum in summer, the minimum in winter and

intermediate in spring and autumn. About 43–57% of the

seasonal variability for soil CO2 flux could be explained by

rainfall (Table 3 and Fig. 6). This indicates that rainfall

played an important indirect role in controlling the seasonal

variations of soil CO2 flux (Table 3 and Fig. 2).

3.4. Soil CO2 flux versus DOC and MBC

Soil CO2 flux and DOC content showed clear and similar

seasonal fluctuations over the entire experiment. Both had

the maximum value in summer (autumn) and the minimum

in winter (Figs. 1 and 4). In arable soils, heterotrophic

organisms are the most dominant microbial community and

they rely on carbon availability (Burford and Bremner,

1975; Stevenson, 1986). A large proportion of plant root

carbon was released as soluble materials during growing

seasons (Barber and Martin, 1976), which would be the

major carbon source respired by soil microbes in cropped

soils (Xu and Juma, 1993).

The seasonal changes in DOC content may be attributedto the microbial utilization of readily available soluble

carbon through respiration. The reasons for high DOC

content during summer or autumn may be the rapid turnover

of soil organic matter due to high microbial activities, more

inputs of dissolved carbon from plant root exudates with

warmer soil temperature and fast growing plant, and/or high

evaporation, which caused upward movement of water and

concentrated DOC in the surface soil. Our current study

confirmed the previous observation that DOC content

changed with seasons and was correlated with soil

respiration (Cook and Allan, 1992; Lundquist et al.,

1999). Statistic analyses indicated that soil CO2 flux was

significantly correlated with DOC content (Table 3),

( R2Z0.558**–0.844**, P%0.01). In other words, the

DOC content accounted for approximately 55.8–84.4% of

seasonal variability of soil CO2 flux in the three soils.

Data analyses showed that DOC content was one of the

important factors in influencing soil CO2 flux among the red

soils (Figs. 1 and 4). The DOC content could explain about

23.8–33.6% of soil CO2 flux variability determined by

parent materials (Table 4). However, among the three soils

tested, the red soil derived from Q contained more DOC and

total organic C (Table 1 and Fig. 4), but the flux of CO2was significantly lower in this soil than in other two soils

(Fig. 1). This may be, in part, due to the fact that there was

more DOC adsorbed to soil clay particles, in particular,

DOC in micro-pores (!0.2 mm), which may be inaccessible

and unavailable to soil microorganisms (energy deficiency).

Oxygen supply may also have been depressed by poor soil

aeration (oxygen deficiency). Both, increased DOC adsorp-

tion and reduced aeration, may be associated with higher

clay content in the soil derived from Q (Table 1). Compared

to coarser-textured soils (T and G), clay soils (Q) have a

greater capacity to stabilize organic carbon by sorption on

clay surfaces or physical protection within stable aggregates

(Ladd et al., 1996).

Soil moisture content was also relatively high, especially

in summer, in the soil Q with high clay content compared to

the other two soils (Fig. 3). An increase in the soil water

content can result in oxygen diffusion becoming limiting for

microbial activity (Schjonning et al., 1999; Skopp et al.,

1990). Thus, despite higher DOC content in the red soil

from Q, available organic carbon or oxygen supply was not

enough to maintain microbial activity, leading to lower soil

CO2 flux.

For all three soils, there were no significant correlations

between soil CO2 flux and MBC over the experimental

period (Table 3). This shows that MBC content had no

effects on the seasonal variations of soil CO2 flux though

MBC was generally regarded as the size of soil microbial

communities (Stevenson, 1986). Low correlation between

Table 4

Correlation analysis between soil CO2 flux and soil temperature, rainfall,

dissolved organic C, soil moisture and microbial C in soils as grouped

according to their sampling seasons

Season CO2 flux versus Correlation

coefficients ( R2)

Simple

regression

Partial

stepwise

regression

Spring Soil temperature NS NS

Soil moisture NS NS

Dissolved

organic C

0.272* NS

Microbial C 0.589** 0.467**

Summer Soil temperature NS NS

Soil moisture NS NS

Dissolved

organic C

0.355* NS

Microbial C 0.548** 0.446**

Autumn Soil temperature NS NS

Soil moisture NS NS

Dissolvedorganic C

0.238* NS

Microbial C 0.483** 0.412**

Winter Soil temperature NS NS

Soil moisture NS NS

Dissolved

organic C

0.336* NS

Microbial C 0.337* 0.313*

*Significant at P%0.05; **significant at P%0.01; NS, not significant. The

correlation coefficients were based on the data in each season.


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soil CO2 flux and MBC may be due to the fact that MBC

content had no marked seasonal fluctuations (Fig. 5), or that

soil CO2 production and emission rates lagged behind or did

not correspond with the seasonal dynamics of MBC content

as reported by Dill et al. (1997).

Soil CO2 fluxes and the quantity of MBC were

significantly correlated and differed between the three redsoils (GOTOQ) (Table 4), suggesting that the quantity of

MBC controlled the dynamics of soil CO2 flux.

3.5. Predominant factors controlling soil CO2 flux

In order to determine the dominant parameters control-

ling soil CO2 flux, multiple-variable procedures were

performed using soil CO2 flux against soil temperature,

moisture, rainfall, DOC and MBC, based on the data

collected during the entire experiment or each season

(Tables 3 and 4). As described above, simple regression

analyses showed that soil temperature, DOC, and rainfall

accounted for 85.0–88.5%, 55.8–84.4%, and 43.0–55.8%,

respectively, of the seasonal variability of soil CO2 flux. The

seasonal variability was maximum in summer, minimum in

winter and intermediate in spring and autumn (Table 3 and

Fig. 1). However, multiple stepwise regression analyses

indicated that, among the three variables, only soil

temperature dominantly controlled the seasonal variability

with a significant partial correlation coefficient

( R2Z0.714**–0.857**, P%0.01) (Table 3). The other two

variables (DOC and rainfall) could be excluded from the

multiple equations (not shown). These findings are consist-

ent with our previous results and other reports (Lou et al.,

2003; Lloyd and Taylor, 1994; Frank et al., 2002).Regression analyses indicates that DOC and MBC

played important roles in determining soil CO2 flux in the

three red soils (GOTOQ) as discussed above (Table 4).

Nevertheless, multiple stepwise regression analyses shows

that only MBC predominantly determined the variations

of soil CO2 flux in the three soils, with a significant partial

coefficient ( R2Z0.313*–0.467**, P%0.05 or 0.01)

(Table 4). The contribution of DOC to the variations of

soil flux in the three soils was, in general quite small

(not shown).

Generally, soil CO2 emission from soils, i.e. total soil

respiration, is the sum of roots and soil microbial

respirations. However, these two sources of soil respiration

are difficult to be determined separately under field

conditions (Fu et al., 2002). In the present study, the daily

and annual amounts of CO2 flux determined under natural

plant–soil system should represent the total soil CO2 flux

including plant root and microbial respirations, though some

measures were taken to minimize or avoid the effects of

plant roots possibly penetrating into the soils below the

collars. As we know, water movement and gas diffusion

naturally occurred in the field soils (Fu et al., 2002). The

DOC exuded from plant roots and CO2 from root respiration

may be transported through water movement and gas

diffuses from rhizosphere to ambient soils with a result of a

supply of DOC to soil microorganisms. In addition, no

significant differences in both aboveground and ground

biomass were observed among the three soils (Table 2). This

implies that root respiration possibly contributed equally to

the amount of soil CO2 flux in the soils. In contrast, there

were significant differences in soil CO2 fluxes among thetested soils with the order of GOTOQ (Fig. 1). Accord-

ingly, differences in soil CO2 flux among the three soils may

be caused by soil microbial respiration. This is in agreement

with the observation that MBC was the dominant variable

influencing soil CO2 flux among the three soils (Table 4). It

has been reported that root respiration contributed 16% of

total soil respiration for arable soils (Larionova et al., 1998),

which was lower than those for grassland and forest soils

(40–90 and 50%, respectively) (Kucera and Kirkham, 1971;

Dugas et al., 1999; Hanson et al., 1993). Thus, the

contribution of root respiration to total CO2 efflux was

less than that of microbial respiration. Moreover, soil CO2fluxes were higher in summer, autumn and spring (the

growing seasons), which coincided with the plant canopy

CO2 uptake and biomass production (Fig. 1). As a result, the

contribution of root respiration to the total soil CO2 flux may

be minimized since high canopy CO2 uptake and photosyn-

thesis fixation occurred.

Acknowledgements

This research was jointly supported by the grants from

the National Natural Science Foundation of China, the Key

Knowledge Innovation Project of the Chinese Academy of Sciences and the National Key Basic Research Support

Foundation of China. The authors are grateful to Dr

Jagadish Timsina from Department of Crop Production,

Institute of Land and Food Resources, University of

Melbourne, Australia, for correcting the language.

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