CARBON DIOXIDE FLUX IN A SUBTROPICAL AGRICULTURAL SOIL OF CHINA YUNSHENG LOU1∗ , ZHONGPEI LI2 and TAOLIN ZHANG2 1 College of Natural Resources and Environmental Sciences, Nanjing Agricultural University, Nanjing 210095, China; 2 Institute of Soil Science, the Chinese Academy of Sciences, Nanjing 210008, China (∗ author for correspondence, e-mail:
[email protected]; fax: +86-25-4396450)
(Received 27 May 2002; accepted 21 May 2003)
Abstract. Red soils, one of the typical agricultural soils in subtropical China, play important roles in the global carbon budget due to their large potential to sequester C and replenish atmospheric C through soil CO2 flux. Soil CO2 emission was measured using a closed chamber method to quantify year-round soil flux and to determine the contribution of soil temperature, dissolved organic carbon (DOC) and soil moisture content to soil CO2 flux. Soil flux was determined every 10 d during the experiment from August 1999 to July 2000, at the Ecological Station of Red Soil (the Chinese Academy of Sciences). In addition, diurnal flux measurements for 24 hr were made on August 5 and November 5, 1999 during this experiment. The average soil fluxes from 2 hr measurements between 9:00 and 11:00 can be regarded as the representative of daily averages. Soil CO2 fluxes were generally higher in summer and autumn than in winter and spring, averaged 7.16 and 0.86 g CO2 m−2 d−1 for the former and latter two seasons, and had a seasonal pattern more similar to soil temperature and DOC than soil moisture. The annual soil CO2 flux was estimated as 1.65 kg CO2 m−2 yr−1 . Regressed separately, the reasons for soil flux variability were 86.6% from soil temperature, 58.8% from DOC, and 26.3% from soil moisture, respectively. Regressed jointly, a multiple equation was developed by the above three variables that explained 85.2% of the flux variance, but only soil temperature was the dominant factor affecting soil flux, with significant partial correlation coefficient (r2 = 0.804, p ≤ 0.05), through stepwise regression analysis. Based on the exponential equation using soil temperature, the predicted fluxes were calculated and were essentially equal to the measured ones throughout the experiment. No significant difference was detected between the predicted average and the measured one. The exponential relationship describing the response of soil CO2 flux to the changes in soil temperature should accurately predict soil CO2 flux from red soils in subtropical China. Keywords: DOC, red soils, soil CO2 flux, soil moisture, soil temperature
1. Introduction Carbon dioxide (CO2 ), concentration of which is increasing at 0.5% annually, is the most important greenhouse gas causing global warming (Lal and Kimble, 1995). Soil CO2 evolution from soils is one of the important sources of atmospheric CO2 as well as a main output pathway of soil organic carbon pool (SOC) (Eswaran et al., 1993; Batjes, 1996; Mosier, 1998). Apart from contributing C to the atmosphere, Water, Air, and Soil Pollution 149: 281–293, 2003. © 2003 Kluwer Academic Publishers. Printed in the Netherlands.
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soil CO2 evolution can also be used as an index of underground processes, and of the C cycling capacity of soil ecosystems. Soil CO2 evolution generally exhibits diurnal and seasonal variations, and its magnitude is ecosystem-specific. For example, average annual soil CO2 emission fluxes were estimated to range from 1.5 to 5.9 kg CO2 m−2 yr−1 for grassland, 4.8 kg CO2 m−2 yr−1 for tropical forests and 0.73 kg CO2 m−2 yr−1 for deserts (Raich and Schlesinger, 1992; Larionova et al., 1998; Mielnick and Dugas, 2000). Average daily fluxes for grasslands, forest and arable soils were measured as 1.7–60.4 g CO2 m−2 d−1 , 5.1–28.9 g CO2 m−2 d−1 and 1.8–31.8 g CO2 m−2 d−1 , respectively (Jensen et al., 1996; Bremer et al., 1998; Knapp et al., 1998; Kudeyarov et al., 1998). Although many studies on soil CO2 emission are found around the world, most of them were conducted in temperate or tropical regions (Yang et al., 1989; Jiang and Huang, 1997; Wu et al., 1997; Mosier, 1998; Lal and Kimble, 1995). So far, few reports on soil CO2 emission have been available in subtropical regions, therefore, the lack of reliable data in the soils of this regions has hampered an accurate estimate of the global soil C fluxes and balance. Red soils are one of the important typical arable soils in subtropical regions of China, which covers about 1.13 million km2 or 11.8% of the country land surface, produces 80% of the rice and supports 22.5% of the population. However, with the rapid economic and social development, red soils are subject to degradation as characterized by low organic carbon content and low crop productivity. Therefore, it is necessary to investigate soil CO2 evolution from red soils for better understanding the mechanisms that regulate C storage and loss processes. There are several factors and mechanisms for the formation and distribution of CO2 in soils (Wood et al., 1984). CO2 production in soils is related to biological activities including root respiration and decomposition of soil organic matter (SOM) by microbial and other activities (Amundson et al., 1990). The microbial activities depend on soil temperature. For example, soil CO2 production rate and emission flux increase by between 1.5 and 3 times for every 10 ◦ C increase in temperature from 0 to 50 ◦ C (Parada et al., 1983; Norstadt et al., 1984). Soil moisture also affects CO2 production and distribution through its influence on gas diffusion and microbial activity. Increasing soil moisture between the permanent wilting point and 60 to 80% of saturation increases the rate of CO2 emission from soil (Solomon et al., 1987). Apart from soil temperature and moisture, energy supply (active carbon) is an important factor in regulating microbial activity or soil respiration because heterotrophic microorganisms are dominant in soil microbial communities. Dissolved organic carbon (DOC) has been used as an indicator of C available to soil microorganisms (Boyer and Groffman, 1996), however, the relationship of DOC to microbial activity or soil respiration is not well understood. Although several reports on the relations between DOC and microbial processes are available, the results are contradictory. For instance, Burford and Bremner (1975) suggested that DOC content was related to heterotrophic microbial processes like
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respiration and denitrification, while Cook and Allan (1992) confirmed that soil respiration rates declined during a 210-d incubation, but DOC content remained constant or increased. Although several researchers have proposed models or equations to predict soil CO2 flux on a large - scale, only a few variables such as soil temperature and soil water have been used in building the models or equations, but not DOC which also could affect soil CO2 evolution (Howard, 1993; Lloyd et al., 1994; Davidson et al., 1998; Knapp et al., 1998). The objectives of this research were to quantify yearround soil CO2 fluxes, and to develop a model on the basis of soil temperature, soil moisture and DOC for predicting soil fluxes in subtropical arable soils of China.
2. Materials and Methods 2.1. S ITE DESCRIPTION The field experiment was conducted from August 1999 to July 2000 in the Ecological Experimental Station of Red Soil, the Chinese Academy of Sciences, located in Yingtan, Jiangxi Province, China (28◦ 15 30 N, 116◦ 55 30 E). This region has a typical subtropical monsoon climate with an annual precipitation of 1795 mm, annual evaporation of 1318 mm and a mean annual temperature of 17.6 ◦ C. Based on mean monthly temperatures, four seasons can be distinguished as spring (February to April), summer (May to July), autumn (August to October) and winter (November to January). The cropped site was an unfertilized arable soil with foxtail millet (Setaria italica L.) and barley (Hordeum Vulgare L.) grown from June 5 to October 15 and from November 5 to May 15, respectively. The millet-barley rotation system is widely distributed in upland arable soils of this region. The soil of the experimental location was red soil, a typical subtropical arable soil, derived from quaternary red clay. Relevant physical and chemical properties of the soil were as follows: total organic carbon 7.3 g · kg−1 (by dichromate oxidation method); total N 0.79 g· kg−1 (by Kjeldahl method); clay content (< 0.001 mm) 370 g · kg−1 (by the pipette method) and pH 5.15 (H2 O). The test methods for soil properties mentioned above were described by Page et al. (1982). 2.2. M EASUREMENTS OF SOIL CO2 EMISSION AND DOC Soil carbon dioxide emissions were measured with a portable infrared analyzer (LI-6262, LICOR Inc., Lincoln, NE, USA) to determine CO2 accumulation in sealed chambers, which were made of lightproof material to avoid the effect of sunlight on the measurements. The chambers, 25.5 cm in diameter and 31.0 cm high, were settled on circular collars that had been inserted about 3–5 cm into the soil between the growing plants at the beginning of the experiment. When
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necessary, green vegetation was physically removed from inside the collars before a scheduled measurement was taken. The measurements were carried out at 8 locations (5–10 m apart) every 10 days during the whole experiment (from August 5, 1999 to July 5, 2000). The total number of measurements was 37. To avoid extremely high temperatures at noon, soil CO2 fluxes were determined in the morning (09:00–11:00) at 8 locations (each with 1–2 chambers), the data in 2 hr were used for 10 days average. In addition, on August 5 and November 5, 1999, soil CO2 fluxes were measured once every two hours during 24 hr periods at each location, but the measurements for 2 hr (9:00– 11:00) were made in duplicate. In this experiment, the equipment for measuring soil CO2 emission was improved by combining a portable analyzer with the closed chamber method. Using this improved method, soil gas samples can be almost simultaneously collected from the closed chambers with 50 ml gas-tight syringes and plastic bags evacuated before sampling at different locations, and then, the CO2 concentration in the plastic bags was measured with the portable analyzer. The CO2 fluxes (expressed as mg CO2 m−2 h−1 ) were calculated from the rate of increase in CO2 concentration (mg kg−1 ) in the chamber during 45 min period in warm seasons or 1 hr in cold seasons. Soil temperature (0–5 cm) and moisture (0–10 cm) in the upper soil layer were also determined at each sampling date. Soil temperature was measured using soil thermometers by inserting the probes at 5 cm depth inside the chambers. Soil moisture was estimated by the water content expressed as the percentage of water holding capacity (% of WHC). The mass water content of soil (g g−1 ) was determined by weight loss upon drying at 105 ◦ C for 24 hr, and water holding capacity (WHC) was measured using plastic rings (30 mm in diameter and 40 mm in height) with 0.5 mm nylon meshes in the bottom. The rings were filled with the soil (approx. 30 g) collected from the experimental site and immersed to half in deionized water for 24 hr to obtain maximum saturation. The saturated soil was drained by keeping the covered rings over glass funnels. WHC was calculated with the equation: WHC = (S.-D)/D, where S = the mass of the saturated soil and D = the mass of the soil dried at 105 ◦ C for 24 hr (modified from Choudhary et al., 1995; Ilstedt et al., 2000). Fresh soil samples (0–20 cm) weighing about 250 g were taken from the eight locations at the same time of CO2 measurements, mixed and placed in plastic bags after manual removal of visible plant residues and roots. One portion of moist soil weighing 20 g was extracted immediately after sampling by shaking for 30 min with 50 ml of 0.5 mol · L−1 K2 SO4 . DOC was estimated by the quantity of 0.5 mol · L−1 K2 SO4 -extractable C and determined by dichromate oxidation (modified from Ross, 1992). Eight soil sub-samples collected from the eight locations were used for the above analyses.
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Figure 1. Comparison of average soil CO2 fluxes for 2, 12 and 24 hr measurements. Time 1, Time 2 and Time 3 represent the averages of soil flux for 2, 12 and 24 hr intervals measured on August 5, 1999; and Time 4, Time 5 and Time 6 determined on November 5, 1999, respectively. The columns with the same letter were not significantly different (p ≤ 0.05) by Duncan’s test method. Vertical bars represent standard error of the means.
2.3. DATA ANALYSIS SPSS software (SPSS Inc, 2000) was used for all data analyses. An equation was developed with a multiple regression procedure to predict soil CO2 flux from soil temperature, soil moisture and DOC. An exponential equation was used to predict flux against soil temperature as suggested by other researchers (Davidson et al., 1998; Mielnick and Dugas, 2000). In this study, the exponential equation was also suitable for predicting flux as a function of DOC or soil moisture, though the flux was negatively correlated with moisture.
3. Results and Discussion 3.1. R ELATIONSHIPS BETWEEN 2-H, 12-H AND 24-H FLUX AVERAGES Based on the diurnal flux measurements conducted on d 1 and 93 in 1999 (August 5 and November 5, 1999), the average soil fluxes for 2, 12 and 24 hr were compared to investigate whether 2 hr (9:00–11:00) measurements can be regarded as representative of daily fluxes. No significant differences were found between average soil fluxes calculated from 2, 12 and 24 hr measurements (Figure 1). However, the averages of 2, 12 or 24 hr flux were significantly different between the two days of measurements. Temperature may be one of the important factors affecting the relative magnitude of CO2 fluxes on the two days. In the present experiment, soil temperature on d 1 and 93 in 1999 (August 5 and November 5, 1999) were 32.0 ± 0.25 ◦ C and 15.0 ± 0.11 ◦ C, respectively (Figure 2). Obviously, soil temperature in August is higher than that in November, more organic matter was decomposed by higher
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microbial activities from beneficial soil temperature for microbial communities and more CO2 evolved in August. In contrast, lower temperatures in November limited soil microbial activities, thereby decreasing CO2 efflux. In addition, plant root respiration may be another factor resulting in the differences in soil fluxes between the two days. The crops grown on d 1 and 93 in 1999 (August 5 and November 5, 1999) were foxtail millet and barley (just sown), with the growing and dormant periods, respectively. Thereby, the greater fluxes on August 5 may have been partially due to higher root respiration and the additional nutrients returned to the soil through root exudates beneficial to the microbial respiration in rhizosphere. Therefore, regardless of the dates for measurements, average soil fluxes from 2 hr measurements between 9:00 and 11:00 can be taken to be the representative of daily averages, and be used to build the equations for predicating average daily soil CO2 flux. 3.2. S EASONAL VARIATION OF SOIL CO2 FLUX Figure 2 indicated that, soil flux gradually declined from d 1 (August, 1999) to d 180 (January, 2000), and reached the lowest value around d 180; after that, it increased gradually until d 365 (July, 2000). Based on the data for soil flux, annual soil CO2 flux was estimated as 1.65 ± 1.48 kg CO2 m−2 yr−1 during this experiment, which was calculated from the 37 daily measurements (2 hr average fluxes) multiplied by 10-d (the interval time) and then sum up the values for the annual flux. Soil fluxes determined during the winter and almost all spring (d 91 to 249) decreased to almost zero and then increased rapidly in March (around d 220) as soil temperature increased. Greater fluxes occurred during the summer and autumn (d 1 to 90 and d 250 to 365). The daily fluxes averaged 0.86 ± 0.49 and 7.16 ± 3.45 g CO2 m−2 d−1 for the former and latter two seasons, respectively. The estimated annual soil flux of 1.65 kg CO2 m−2 yr−1 from this study was among the ranges from 0.17 to 11.64 kg CO2 m−2 yr−1 for agricultural soils located in temperate or tropical zone, reported by some researchers (Larionova et al., 1998; Lal and Kimble, 1995). In the present experiment, the annual soil CO2 emission from red soil in subtropical China was larger than that from temperate soils, and lower than that from tropical soils, which may be affected mainly by the climatic temperature. According to Figure 2 and the standard deviation for the annual flux, high temporal variability was obvious in soil fluxes during the experiment, generally larger in summer and autumn than that in spring and winter. Higher soil CO2 flux during the summer and autumn may have been due to enhanced root respiration resulting from active root growth and increased microbial respiration from organic carbon transformation by higher microbial activity, both associated with high soil temperature (around 30 ◦ C) and suitable precipitation (55% total amount of annual rainfall) during the summer and autumn (Figure 2). On the contrary, lower soil
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Figure 2. Seasonal dynamics of soil moisture, soil temperature, dissolved organic carbon (DOC), and soil CO2 flux during the experiment. WHC means water holding capacity. Values are the mean of eight replicates measured between 9:00 a.m. and 11:00 at sampling dates. The experiment duration was from August, 1999 to July, 2000. Error bars are standard error (n = 8).
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CO2 fluxes in winter and spring were likely related to depressed root and microbial respiration by low soil temperature (< 10 ◦ C). 3.3. S OIL TEMPERATURE , MOISTURE AND DISSOLVED ORGANIC CARBON Soil CO2 flux had a seasonal tendency that more closely resembled that of soil temperature and dissolved organic carbon (DOC) than soil moisture (Figure 2). Thereby, during the experiment period soil temperature and DOC effects on soil CO2 flux were greater than soil moisture. This can be explained by simple regression analysis with soil flux against soil temperature, soil moisture, and DOC, respectively (Table I). Soil CO2 flux was positively correlated with soil temperature and DOC, but negatively with soil moisture. The correlation coefficients (r2 ) were 0.866, 0.588 and 0.263 (p ≤ 0.05, n = 37) for soil CO2 flux as the functions of soil temperature, DOC and moisture, respectively (Table I). In other words, the flux variability that could be attributed to soil temperature, DOC and moisture was 86.6, 58.8 and 26.3%, respectively. The reasons for weaker correlation between soil flux and soil moisture than between soil flux, soil temperature and DOC may be that soil temperature and DOC were more dominant than soil moisture in controlling soil CO2 flux. In agricultural soils, heterotrophic microbes were the main microbial communities which depended on enery supply or carbon availability and content (Burford and Bremner, 1975; Stevenson, 1986). The seasonal change in DOC during the present experiment may have been due to the microbial utilization of readily available soluble carbon for its respiration, and the changed activity of root systems from barley to foxtail millet. The possible reasons for higher DOC content during summer and autumn may be attributed to the rapid turnover of soil organic matter and more dissolved carbon input from plant root exudates connected with high soil temperature and fast growing plants. The change in DOC content was not surprising as other researchers also confirmed that DOC content changed with season and correlated well with soil respiration (Cook and Allan, 1992). Greater scatter was found in the relationship between soil CO2 flux and soil moisture than between soil flux and soil temperature (Table I), as other scientists suggested (Davidson et al., 1998; Knapp et al., 1998). The low correlation between flux and moisture may be due to the fact that the moisture-related factors were not considered in data analyses, i.e. (1) soil moisture regimes depended on not only precipitation but also evaporation, and showed high temporal and spatial variability as affected by e.g. soil properties and, plant growth; (2) In this study, soil moisture was measured to a depth of only 10 cm which was too shallow to match potential deep abilities of the plant root and microbial respiration. Wetter soil conditions at greater depth may buffer the effects of near-surface soil moisture deficits on soil CO2 flux (Singh et al., 1998).
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TABLE I Soil daily CO2 flux (g CO2 m−2 d−1 ) as a function of soil temperature (◦ C), soil moisture (% of water holding capacity, WHC) or dissolved organic carbon (DOC, mg kg−1 ) Regression Variable
n
Equation
Correlation coefficient (r2 )
Separately Soil temperature Soil moisture DOC Jointly
37 37 37 37
flux = 0.4052 × e0.1065×temp flux = 99.967 × e−0.0572×moisture flux = 0.1434 × e0.0248×doc Y = –2.531–0.496X1 + 0.0461X2 –0.0392X3
0.866a 0.263a 0.589a 0.852a
In above multiple equation, Y, X1 , X2 , and X3 are soil flux, soil temperature, soil moisture, and DOC, respectively. a = significant at p ≤ 0.05.
3.4. S OIL CO2 FLUX PREDICATION Regressed jointly, a multiple linear equation was built to predict soil flux using soil temperature, DOC and soil moisture (Table I). Obviously, soil flux was significantly correlated to soil temperature, DOC and soil moisture. However stepwise regression analysis showed that, among the three variables, soil temperature was the dominant one affecting soil flux, with significant partial correlation coefficient (r2 = 0.804, p ≤ 0.05, n = 37), and the other two variables (DOC and soil moisture) could be excluded from the multiple equation. Some researchers also reported that when considering only a single variable, soil temperature was the first choice for predicting soil CO2 fluxes (Lloyd and Taylor, 1994; Mielnick and Dugas, 2000). Therefore, the exponential relationship between soil flux and soil temperature can be used as the model for predicting soil flux (Table I). Based on the exponential equation using soil temperature, the predicated average daily soil fluxes were calculated and showed a seasonal tendency resembling that of the measured fluxes through the experiments duration. No significant difference was detected between average predicted flux and measured one (Table II and Figure 3). Furthermore, more than 83% of soil flux variability can be explained by the equation. In order to investigate whether the exponential equation using soil temperature can be used for accurately predicating soil fluxes in other experimental sites similar to this study, a real independent data set determined at QYZ Ecological Station in subtropical China was applied to the above equation (Zhou et al., 2002). The QYZ Station is located in Taihe, Jiangxi Province, China (26◦ 44 48 N, 115◦ 04 13 E), with a typical subtropical monsoon climate as this study site. Soil CO2 flux and soil temperature (at 5 cm depth) were measured in red soils under maize or citrus from November, 1998 to October, 1999. Statistical analysis showed that the above equation accurately predicted the measured fluxes at QYZ Ecological Station, and no significant difference was found between the two averages, irrespective of veget-
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TABLE II Comparison of measured and predicated average diurnal flux (g CO2 m−2 d−1 ) from the present experimental site (n = 37) and an independent data set under maize or citrus from QYZ Ecological Station (n = 12–24, Zhou et al., 2002) Data set
This experiment
QYZ Ecological Station Maize field and Citrus garden Maize field
Measured Predicated r2
4.59 ± 4.06 a 4.55 ± 4.18 a 0.83a
3.67 ± 1.56 a 4.03 ± 2.54 a 0.74a
4.31 ± 1.78 a 4.30 ± 2.80 a 0.89a
Values in a column followed by the same letter were not significantly different (p ≤ 0.05) by IST (Independent Samples T Test) method. a = significant at p ≤ 0.05.
Figure 3. Relationship between measured and predicated average soil CO2 flux. The correlation equation is Y = 0.938X + 0.2415 (r2 = 0.8324, p ≤ 0.05, n = 37), where Y and X represent predicated and measured soil flux, respectively.
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Figure 4. Correlation between measured and predicated daily flux in a subtropical red soil at QYZ Ecological Station. Measured data is from Zhou et al. (2002).
ation (Table II and Figure 4). However, the correlation coefficient (r2 = 0.74) was slightly lower for maize field and citrus garden (Table II), which may be related to the fact that the data used here were collected from red soils under different vegetations. A higher coefficient (r2 = 0.89) was obtained if data were used and tested only from maize fields more similar to this study (Table II). These results suggested the exponential equation developed from soil temperature could be used for accurately predicting soil flux for red soils in subtropical China. By the way, since soil CO2 flux was affected by diverse abiotic and biotic environmental factors, for more accurate prediction of soil flux, the equation for predicting soil CO2 flux should be built on key flux-related factors, not only including soil temperature, DOC and moisture but also other factors, i.e. soil properties, land use pattern, plant biomass, etc.
Acknowledgements The authors are grateful to the National Natural Science Foundation of China (Approved No. 39899370) for the financial support, and to the editors and reviewers for their constructive suggestions and comments on the original manuscript.
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