Introduction

Global warming undoubtedly results from greenhouse gas (GHG) emissions1. Nitrous oxide (N2O), methane (CH4) and carbon dioxide (CO2) are three GHGs of major concern that are emitted from agricultural soils2; however, large amounts of carbon can also be fixed in soil-crop systems through photosynthesis3. The net exchange of CH4, N2O and CO2 in terms of CO2 equivalents between soils and the atmosphere comprises the net global warming potential (NGWP) of a cropping system4, which can also be expressed on the basis of per unit of yield (greenhouse gas intensity, GHGI)3.

Agriculture is an important source of CH4 and N2O2, accounting for 50% and 60% of total global anthropogenic CH4 and N2O emissions, respectively, in 20055. Rice paddy fields have been identified as a major source of CH4 emission to the atmosphere; N2O is mainly generated by upland fields and is also produced from rice fields because of midseason drainage and moist irrigation6,7. The rice harvest in China, which averaged 30 M ha from 2010 to 2013, accounts for 18.7% of the world’s total8 and the total CH4 emissions from Chinese rice paddies are estimated to be 7.41 Tg CH4 year−1, 29.9% of the world’s total (25.5 Tg CH4 year−1)9. Additionally, direct N2O emission during the rice-growing season, which was measured at a rate of 32.3 Gg N2O-N in the 1990s, is responsible for 8–11% of the total N2O emission from Chinese croplands10.

Double rice (DR) and upland crop-single rice (UR) annual rotations are two major rice systems in China, with 75% of rice fields implementing these approaches11. Many studies have focused on CH4 and N2O emissions from UR7,12 and DR systems13,14,15 individually. Previous data based on pot experiments indicate that different cropping systems result in different amounts of N2O emission from paddy fields16 and individual field studies have also reported variable CH4 emissions among cropping systems12,13. However, no field study to date has simultaneously addressed CH4 and N2O emissions from different rice cropping systems. Moreover, to our knowledge, the differences in NGWP and GHGI between different rice cropping systems have not been documented.

Straw return has been widely recommended for agricultural ecosystems in China. Chinese agriculture produces approximately 620 Tg of crop straw every year, with an increasing trend of an annual rate of 1.4%17 and approximately 25% of the straw is currently returned to the field18. Indeed, straw incorporation is a common practice in rice production, as it helps to maintain soil quality and recycle mineral nutrients19. Straw incorporation also has a considerable influence on CH4 and N2O via changes in soil properties, such as the porosity, temperature and moisture20,21. In general, straw incorporation can enhance carbon sequestration, resulting in improved soil productivity and air quality and thus offset GHG emissions from rice fields. However, a significant stimulation of CH4 emission due to straw incorporation in rice fields has been well documented22,23,24. In contrast, straw incorporation inhibits7,12 or has no significant effect25 on N2O emission from rice fields. Nonetheless, the mechanism by which straw addition affects carbon sequestration as well as CH4 and N2O emissions and GHGI in different rice cropping systems remains unknown.

Based on previous studies, we hypothesize that (1) different rice cropping systems may differ greatly in CH4 and N2O emissions due to drastic flooding periods and (2) straw incorporation may result in different influences on CH4 and N2O emissions from different rice cropping systems. To test these hypotheses, a field experiment was established to measure CH4 and N2O emissions and SOC changes between the two major rice cropping systems in China. The objectives were to gain insight into the differences in grain yield, NGWP and GHGI between UR and DR systems as affected by straw application.

Results

CH4 emission

Analysis of variance (ANOVA) indicates that annual CH4 emission depended strongly on the cropping system, straw incorporation and their interactions (Table 1). Inter-annual variation was also observed (Table 1). In the UR system, similar seasonal patterns of net CH4 flux were observed for all treatments. The net CH4 flux was significant during the rice-growing season but was negligible during the wheat-growing season (Fig. 1, Table 2), ranging from −1.45 to 36.2 mg C m−2 h−1 during the three annual rotations. In addition, the net CH4 flux increased after rice transplantation and decreased dramatically during the midseason drainage; after reflooding, the flux increased again to a low emission peak and then decreased gradually to a negligible amount until harvest. In the DR system, all plots served as minor sinks or sources for atmospheric CH4 during the oil rape-growing season (Table 2) and all plots served as net sources of atmospheric CH4 during the early and late rice-growing seasons (Table 2). The patterns of CH4 flux observed during the early and late rice-growing seasons were similar to those of the rice-growing season in the UR system. Compared with the UR-S0 plot (104 kg CH4 ha−1 year−1), the annual CH4 emission increased significantly by 76.9% in the DR-S0 treatment (185 kg CH4 ha−1 year−1).

Table 1 Three-way analysis of variance (ANOVA) results for the effects of cropping system (C), straw incorporation (S), year (Y) and their interactions on CH4 and N2O emissions, grain yield, NGWP and GHGI.
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Table 2 Seasonal CH4 and N2O emissions and grain yields measured in UR and DR systems from November 2008 to November 2011.
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Figure 1
figure 1

Seasonal variation of CH4 fluxes in the three annual cycles of UR and DR systems from November 2008 to November 2011.

The arrow indicates straw incorporation.

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Straw incorporation significantly stimulated CH4 emission. The highest CH4 fluxes, i.e., 24.8, 34.5 and 36.2 mg C m−2 h−1, were observed in 2009, 2010 and 2011, respectively, in the UR-S2 plot. The annual CH4 emissions averaged over the three years were 104, 208 and 303 kg CH4 ha−1 year−1 for the UR-S0, UR-S1 and UR-S2 plots, respectively (Table 3). The average annual CH4 emissions were 99.7% and 191% higher in the UR-S1 and UR-S2 plots, respectively, than in the UR-S0 plot. In comparison to UR-S1, the annual CH4 emission was significantly increased in the UR-S2 treatment (by 45.5%). Similar to the UR system, the highest CH4 fluxes were observed in the DR-S2 plot, i.e., 59.0, 87.4 and 66.4 mg C m−2 h−1 in 2009, 2010 and 2011, respectively. The annual CH4 emissions averaged over the three years were 185, 469 and 702 kg CH4 ha−1 year−1 for the DR-S0, DR-S1 and DR-S2 plots, respectively. Compared with the DR-S0 plots, annual CH4 emissions were significantly increased by 150% and 280% in DR-S1 and DR-S2, respectively.

Table 3 Annual CH4 and N2O emissions, grain yield, NGWP and GHGI of UR and DR systems over the three rotations from November 2008 to November 2011.
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Furthermore, straw incorporation enhanced the differences between the DR and UR systems (Table 3). The increase due to straw incorporation in the DR system was 150% and 280% for DR-S1 and DR-S2, respectively, obviously higher than the 99.7% and 191% observed for UR-S1 and UR-S2, respectively in the UR system.

N2O emission

The majority of N2O emission occurred during the wheat-growing season in the UR system and the oil rape-growing season in the DR system (Fig. 2) and the N2O fluxes were primarily driven by fertilizer application and precipitation. No peaks of N2O flux were observed during the 2009 wheat- and oil rape-growing seasons because almost no precipitation occurred after the application of the basic fertilizer. However, during the rice-growing season, N2O flux peaks were observed in response to both N fertilizer application and midseason aeration. Straw incorporation tended to decrease N2O emission during the rice-growing season in both systems; however, the effects were not statistically significant (Table 2).

Figure 2
figure 2

Seasonal variation of N2O fluxes in the three annual cycles of UR and DR systems from November 2008 to November 2011.

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The annual N2O cumulative emissions averaged over the three years were 2.26, 2.08 and 2.19 kg N ha−1 year−1 for the UR-S0, UR-S1 and UR-S2 plots and 2.77, 3.13 and 3.04 kg N ha−1 year−1 for the DR-S0, DR-S1 and DR-S2 plots, respectively (Table 3). It is apparent that the annual N2O emissions were significantly increased in the DR system relative to the UR system (Table 3). Analysis of variance (ANOVA) indicated that the annual N2O emission was strongly dependent on the cropping system but not influenced by straw incorporation. Although inter-annual variation was observed, no interactions were found (Table 1).

SOC sequestration

The soil organic C content was 14.6 g kg−1 upon establishment of the field experiment in November 2008 and SOC in the topsoil (0–20 cm) increased in all treatments over the three years of the study. After the three cycles of field experiment, the SOC contents reached 14.7 g kg−1, 15.7 g kg−1, 16.7 g kg−1, 15.2 g kg−1, 16.3 g kg−1 and 17.4 g kg−1 in UR-S0, UR-S1, UR-S2, DR-S0, DR-S1 and DR-S2, respectively. From November 2008 to November 2011, the rate of SOC increase ranged from 0.03 g C kg−1 yr−1 for the UR-S0 plot to 0.95 g C kg−1 yr−1 for the DR-S2 plot. The topsoil SOC density was estimated based on the topsoil SOC content and bulk density, with the SOC sequestration rate (SOCSR) ranging from 0.08 t C yr−1 for UR-S0 to 2.42 t C yr−1 for DR-S2 (Table 3). Compared with the UR-S0 plot, SOCSR tended to increase in the DR-S0 plot, but this effect was not statistically significant. Straw incorporation enhanced SOCSR in both the UR and DR systems, but the differences among UR-S1 and DR-S1 and UR-S2 and DR-S2 were not statistically significant (Table 3).

Yield, NGWP and GHGI

Over the three years, the annual yields were strongly dependent on the cropping system and year as well as their interaction (Table 1). The annual yield was significantly increased in the DR-S0 plot compared with the UR-S0 plot (Table 3). However, straw incorporation had no significant effect on the seasonal grain yield, except that the late rice yield from DR-S2 was increased by 14.7% compared with DR-S0 (Table 2); straw incorporation tended to increase the annual grain yield of both systems but not to a statistically significant extent (Table 3). Relative to the UR system, the annual grain yield of the DR system was significantly increased when straw was incorporated (Table 3).

NGWP was significantly influenced by the cropping system, straw incorporation and the year, varying significantly as a result of interactions between the cropping system and straw incorporation as well as straw incorporation and the year. GHGI also strongly depended on the cropping system, straw incorporation and the year as well as the interaction between the cropping system and straw incorporation (Table 1). Relative to the UR system, the annual NGWP of the DR system increased markedly while no significant difference between the UR-S0 and DR-S0 treatments was observed for GHGI (Table 3). Although straw incorporation had no significant effect on the annual NGWP and GHGI of the UR system, these parameters significantly increased in the DR system and compared with a moderate rate, the incorporation of straw at a high rate resulted in further annual NGWP and GHGI increases in the DR system (Table 3).

Discussion

In the present study, the annual CH4 emission from the DR system was significantly higher than that from the UR system (Table 3). Due to the long period of flooding, double rice cropping systems emit more CH4 than single rice cultivation systems26. In fact, water management has been recognized as one of the most important practices affecting CH4 emission from paddy fields27. When plots are flooded, oxygen cannot diffuse into the soil and strong anaerobic conditions may develop, thus favouring the growth of methanogen28.

In our study, annual N2O emissions were significantly increased in the DR system, which is not in agreement with the results of previous pot experiments16. However, differences between field and pot experiments may produce different results with regard to N2O emissions. Nonetheless, the inter-annual variation in N2O emissions was significant (Table 1) and the cumulative N2O emissions were considerably lower during the non-rice season in both the UR and DR systems in 2009 compared with 2010 and 2011 (Table 2). When soil is not maintained under flooded conditions, the water-filled pore space (WFPS) and the available N content are the two most important factors affecting N2O emissions7,29,30. In addition, high N2O emissions during the non-rice season generally occurred after the application of basal fertilizer and precipitation events in 2010 and 2011, consistent with a previous study21. Indeed, precipitation events can create suitable soil moisture conditions for N2O production via microbial processes31, yet almost no N2O flux peaks were observed during the non rice-growing season in both the UR and DR systems in 2009 because no precipitation occurred after the basal fertilizer application. Similar results were observed by Ma et al.30 in the same region.

Because NGWP is dominated by CH4 emissions in both systems, high CH4 emissions resulted in a significantly higher NGWP for the DR system compared with the UR system (Table 3). NGWP was also significantly higher in DR-S0 than in UR-S0, which was accompanied by an annual grain yield that was dramatically higher in DR-S0 compared with UR-S0. Consequently, there was no significant difference between the UR-S0 and DR-S0 treatments with respect to GHGI (Table 3). These two major rice cropping systems are equally appropriate for sustainable rice production on the basis of per unit of yield.

Straw incorporation significantly increases CH4 emissions because of the additional C that is available for methanogenesis during the rice-growing season, which has been widely demonstrated in previous studies12,14,23. CH4 emissions were highest in the S2 treatment, followed by S1 and S0, during the rice-growing seasons in both the UR and DR systems (Table 2). CH4 is typically produced under strictly anaerobic conditions with a low soil redox potential27 and the net CH4 flux is the balance between methanogenic and methanotrophic processes32. Thus, organic amendment and the water regime during the rice-growing season are the top two variables controlling CH4 flux33.

Straw incorporation tended to decrease N2O emissions during the rice-growing season in both the UR and DR systems (Table 2), a finding also supported by previous studies7,34. N2O is naturally produced in soil through nitrification and denitrification2, which are generally regulated by the availability of organic C and the availability and forms of N in the soil under anaerobic or aerobic conditions35,36. The observed decreases in N2O during the rice-growing season in the presence of straw incorporation may be explained by the following: the decomposition of crop residues with a high C:N ratio (>40) can enhance microbial N immobilization, resulting in less available N for nitrification and denitrification and consequently decreased N2O emissions12,22. Furthermore, our previous study proved that straw incorporation during the rice-growing season can decrease the soil redox potential (Eh) and increase the concentration of Fe2+, thus facilitating the further reduction of N2O to N2 and resulting in decreased N2O emissions7.

Although straw incorporation had no effect on NGWP and GHGI in the UR system, significant increases were observed in the DR system (Table 3). This finding is primarily related to the high amount of CH4 emissions induced by straw incorporation. In addition, straw incorporation enhanced the difference in NGWP between the UR and DR systems (Table 3) because the incorporation occurred in both the early and late rice seasons in the latter system. As the annual NGWP driven by straw incorporation outweighed the benefits of grain yield and SOCSR increases, the annual GHGI was significantly increased in DR-S1 and DR-S2 compared with UR-S1 and UR-S2, respectively. Therefore, considering the annual NGWP and GHGI, direct straw incorporation during the rice-growing season in China is beneficial for the UR system but is not a good strategy for the DR system.

Materials and Methods

Experimental site

A 3-year field experiment was conducted from November 2008 to November 2011 in Mo ling town, Nanjing, Jiangsu Province, China (31°52′N, 118°50′E). The site is located on the Yangtze Delta Plain, which is one of the most developed regions of China and includes portions of Jiangsu Province, Zhejiang Province and Shanghai City. Triple cropping systems with double rice seasons or double cropping systems with single rice seasons within one year are generally implemented in this region. Details of the cultivation practices for each crop season are shown in Table S1. The region is characterized by a typical subtropical climate with an annual average air temperature of 15.7°C and precipitation of 1050 mm. The daily mean air temperatures and precipitation during the experiment were collected from a nearby weather station, as shown in Fig. S1. The soil of the experimental field has a bulk density of 1.28 g cm−3, pH 5.7, organic C content of 14.6 g kg−1 and total N content of 1.32 g kg−1.

Experimental treatments and field management

Two crop rotation systems were included in this experiment, i.e., a wheat-rice rotation, which represents the UR system and an oil rape-early rice-late rice rotation, which represents the DR system. Straw (0, 3 and 6 t/ha) was incorporated during the rice season in the UR system (UR-S0, UR-S1, UR-S2) and during both the early and late rice seasons in the DR system (DR-S0, DR-S1, DR-S2) before rice transplantation (Table S2). Nitrogen fertilizer (urea) was applied at a rate of 200 kg N ha−1 for the early and late rice seasons and 250 kg N ha−1 for the other crop seasons. A total of six field experimental treatments with three replicated plots (4 m × 5 m) were established using a randomized block design. The nitrogen fertilizer (urea) was split broadcast at a ratio of 4:3:3 as a basal fertilizer and two topdressings. Phosphate and potassium fertilizers were applied uniformly as a basal fertilizer to the different treatments at 60 kg P2O5 ha−1 and 120 kg K2O ha−1. Field management followed the local agronomic practices, including cultivation, irrigation, fertilizer application and pest and weed control.

All field plots were drained in the winter season. Consistent with the water management of local winter crop-rice systems, flooding was initiated 2–3 days before rice transplantation and was maintained for 30–40 days until midseason drainage for one week. A final drainage event occurred approximately 15 days before rice harvesting in all treatments.

Measurements of CH4 and N2O fluxes

CH4 and N2O emissions were measured from November 2008 to November 2011 using static opaque chambers and gas chromatography. One chamber was placed within each treatment replicate to achieve three replicate gas flux measurements for each observation time. The chamber, which was 0.5 or 1.1 m tall, having been adapted for the crop growth and plant height, covered a field area of 0.2025 m2 (45 × 45 cm) and was placed on a fixed PVC frame in each plot. To minimize air temperature changes inside the chamber during sampling, the chamber was wrapped with a layer of sponge and aluminium foil. For each flux measurement, four gas samples were collected from 9:00 to 11:00 am using a 25-mL syringe at 0, 10, 20 and 30 min after the chambers were placed on the fixed frames. Over the three annual cycles, CH4 and N2O fluxes were generally measured once a week in triplicate plots for all treatments, but samples were collected more frequently after a precipitation event, fertilizer application and rice transplantation.

The flux (F) of CH4 and N2O was calculated using the following equation:

where F is the flux of greenhouse gas (mg•m−2•h−1), ρ is the density of CH4 (0.536 g•L−1) or N2O (1.25 g•L−1), V is the volume of the static opaque chamber (m3), A is the cover areas of the fixed PVC frame (m2), dc/dt is the rate at which the concentration of CH4 or N2O changes with time and T is the temperature inside the static opaque chamber (°C).

The gas samples were analysed for CH4 and N2O concentrations using a gas chromatograph (Agilent 7890A, Shanghai, China) equipped with an electron capture detector (ECD) for N2O analysis and a hydrogen flame ionization detector (FID) for CH4 analysis (CO2 was first reduced by hydrogen to CH4 in a nickel catalytic converter at 375°C). N2O was separated using two stainless steel columns packed with 80–100 mesh Porapak Q. One column was 2 m long with an inner diameter of 2 mm; the other column was 3 m long with an inner diameter of 2 mm. The carrier gas was argon-methane (5%) at a flow rate of 40 ml min−1. The temperatures of the columns and the ECD detector were maintained at 40°C and 300°C, respectively and the oven and FID were operated at 50°C and 300°C, respectively. The detection limits for CH4 and N2O in this study are 0.023 mg C m−2 h−1 and 1.72 μg N m−2 h−1, respectively.

Measurements of changes in SOC

Soil samples were collected when the field experiment was initiated in November 2008 and after three years in November 2011. A composite sample for each plot was obtained by randomly collecting five or six soil cores at a depth of 20 cm (3 cm diameter) and mixing them thoroughly. Any visible roots, stones, or organic residues were removed manually after air-drying the samples at room temperature. The samples were then ground to pass through a 2-mm sieve and a portion was subsequently ground in a porcelain mortar to pass through a 0.15-mm sieve for SOC measurement. The total SOC was analysed following wet digestion with H2SO4-K2Cr2O7. The minimum change in SOC that can be detected by this method is 0.01 g kg−1.

The soil organic carbon sequestration rate (SOCSR) was calculated as follows:

where SOCt and SOC0 are the SOC contents measured in November 2011 and 2008, respectively and γ and δ2mm are the average bulk density (in grams per cubic centimetres) and gravel content (>2 mm) of the topsoil (0–20 cm), respectively. The sand fractions of paddy soils in China are largely negligible. The number 20 represents the thickness of the topsoil.

Calculation of NGWP and GHGI

NGWP of a cropland ecosystem equals the total CO2 emission equivalents minus the change in SOC; thus, NGWP and GHGI were calculated as follows:

where the numbers 34 and 298 represent the IPCC factors for the conversion of CH4 and N2O to CO2 equivalents, respectively1.

Statistical analysis

Statistical analyses were performed using JMP 9.0 (SAS Institute Inc., Cary, USA). Three-way factorial analysis of variance (ANOVA) was used to test the effect of cropping system, straw incorporation and year on annual CH4 and N2O emissions, yields, NGWP and GHGI.

Additional Information

How to cite this article: Xiong, Z. et al. Differences in net global warming potential and greenhouse gas intensity between major rice-based cropping systems in China. Sci. Rep. 5, 17774; doi: 10.1038/srep17774 (2015).