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Feb 13, 2018 - 28 and 265 times that of carbon dioxide (CO2) over a time ... ing open fields with plastic film, has been expanded rapidly .... design with three replicate plots (15 m × 20 m) of each treat- .... sealed in plastic bags. ... Water-filled pore ..... The authors also would like to acknowledge the coworkers and students.
Environmental Science and Pollution Research https://doi.org/10.1007/s11356-018-1559-4

RESEARCH ARTICLE

Decrease in the annual emissions of CH4 and N2O following the initial land management change from rice to vegetable production Lei Wu 1 & Xian Wu 1 & Muhammad Shaaban 1 & Minghua Zhou 2 & Jinsong Zhao 1 & Ronggui Hu 1 Received: 26 October 2017 / Accepted: 13 February 2018 # Springer-Verlag GmbH Germany, part of Springer Nature 2018

Abstract In recent years, rice paddies have been increasingly converted to vegetable production resulting from economic benefits and changes in demand of diets, potentially altering soil greenhouse gas (GHG) balance. Here, we implemented a parallel field experiment to simultaneously quantify the differences in emissions of CH4 and N2O among rice paddy (RP) and conventional vegetable field (CV) and greenhouse vegetable field (GV), both of which have been recently converted from rice paddy in subtropical China over a full year. The results revealed that CH4 emission was reduced dramatically by nearly 100% following the initial land management change from rice to vegetable production, with annual emissions of 720.9, 0.9, and 0.2 kg CH4C ha−1 for RP, CV, and GV, respectively. This conversion however substantially increased N2O emissions, resulting in the transition from a minor sink of N2O in RP (−0.1 kg N ha−1 yr−1) to considerable N2O sources in CV (31.8 kg N ha−1 yr−1) and GV (52.2 kg N ha−1 yr−1). Furthermore, annual N2O emission from GV significantly exceeded that from CV due to lower soil pH and higher soil temperature facilitating N2O production in GV relative to CV. Land management change significantly decreased the annual total emissions of CH4 and N2O from CVand GV by 19–51% as compared to RP, attributing to the reduced CH4 emissions outweighing the increased N2O emissions in CV and GV. These results indicate that expansion of vegetable production at the expense of rice paddies for higher economic benefits also helps mitigate the total emissions of CH4 and N2O. Keywords Land management change . CH4 . N2O . Rice paddy . Vegetable field

Introduction Atmospheric methane (CH4) and nitrous oxide (N2O) are generally regarded as the two major non-CO2 greenhouse gases (GHGs), with relative global warming potentials (GWPs) of 28 and 265 times that of carbon dioxide (CO2) over a time scale of 100 years, respectively (IPCC 2013). Agriculture and associated land management change serves as a significant source of CH4 and N2O which together contribute to more than one quarter of the total anthropogenic radiative forcing (IPCC 2013; Zhang et al. 2014). Changes in agricultural land management have direct impacts on soil environment Responsible editor: Philippe Garrigues * Ronggui Hu [email protected] 1

College of Resources and Environment, Huazhong Agricultural University, Wuhan 430070, China

2

Key Laboratory of Mountain Surface Processes and Ecological Regulation, Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu 610041, China

conditions and consequently influence the biogeochemical cycling of C and N and thereby production and emission of GHGs from soils (Eusufzai et al. 2010; Weller et al. 2016; Zhang et al. 2016a). China is one of the most important rice producers in the world, accounting for 20% of the world’s rice-producing area and 23% of all China’s cultivated land (FAO 2013). Numerous field studies and modeling approaches have documented CH4 and N2O emissions from rice paddies (Zhou et al. 2015; Kraus et al. 2016; Weller et al. 2016; Zhang et al. 2016a), which are estimated to emit 4.8 Tg CH4-C yr−1 and 114.5 Gg N2O-N yr−1 in China, respectively (Zhang et al. 2014). Over the last decades, because of economic benefits and changes in demand of diets, rice paddies have been increasingly undergoing shifts in land-use regimes, such as conversion of rice cropping systems to upland crop cultivations, including maize, fruits, and vegetables (Shen et al. 2008; Sun et al. 2011; Kraus et al. 2016). China ranks as the leading country of vegetable cultivation in the world, contributing 52% of the world’s total vegetable production in 2012 (FAO 2013). The vegetable cultivation area extends over 24.7 × 106 ha, accounting for about 12.4%

Environ Sci Pollut Res

of the total cropping area in China today (FAO 2013). Meanwhile, greenhouse vegetable cultivation, converted from cereal grain and conventional vegetable cultivation by covering open fields with plastic film, has been expanded rapidly since late 1970s, occupying almost 3.4 × 106 ha in 2010 (Chang et al. 2013). According to survey data (Shen et al. 2008; Sun et al. 2011), many recent vegetable fields were previously used for rice production. It is expected that high profits and increasing demand for vegetables will motivate farmers to expand vegetable cultivation at the expense of rice paddies in coming years. Conversion of paddy field to vegetable cultivation modifies management practices particularly with respect to fertilization, tillage, and irrigation regimes (Wang et al. 2014). Vegetable cultivations are characterized by higher nitrogen fertilizer inputs, more intensive tillage, and frequent irrigation in comparison with cereal grain cultivations (Deng et al. 2012; Cao et al. 2015). Such land management change may strongly result in the alteration of soil physiochemical properties and biological processes and associated C and N cycles with implications for GHG emissions (Wang et al. 2014; Cao et al. 2015; Qin et al. 2016). Land management change from rice to upland cultivation significantly reduces CH4 emission while increasing N2O emissions, due to enhanced aerobic conditions inhibiting CH 4 production and facilitating N transformation (Nishimura et al. 2008; Qin et al. 2016; Weller et al. 2016). While it remains unclear whether the positive effect on CH4 mitigation could be partly offset or even over-compensated by the corresponding increases in N2O emissions, resulting in the increase or decrease of the total GWP (CH 4 + N 2 O) (Nishimura et al. 2005; Yuan et al. 2015). Kraus et al. (2016) reported that the responses of GHG emissions at the early stage of land management change considerably differ from those observed after long-term duration of land management change. However, most of the existing studies regarding land management change effects on GHG emissions have so far concentrated on long-term effects, with fewer studies investigating at the initial stage of such conversion (Nishimura et al. 2008; Wang et al. 2011; Deng et al. 2012; Weller et al. 2016). With increasing concern about global climate warming, the responses of CH4 and N2O emissions at the initial stage of rice paddy conversion to vegetable production need to be critically evaluated to attain high economic benefits while devising appropriate strategies for GHG mitigation. In this study, in situ fluxes of CH4 and N2O were simultaneously measured from rice paddy, and conventional vegetable field and greenhouse vegetable field both of which have been recently converted from rice paddy in subtropical China over a full year. The objectives were (1) to evaluate the responses of CH4 and N2O emissions, and the resulting annual GWP (CH4 + N2O) to land management change from rice to

vegetable production and (2) to examine the principal soil properties that regulate the temporal dynamics of CH4 and N2O fluxes. This study would also provide Bbaseline^ GHG emission data, valuable information when assessing beneficial management practices for sustainable production while mitigating GHG emissions.

Materials and methods Site description This study was carried out at the Changsha Research Station for Agricultural & Environmental Monitoring of the Chinese Academy of Sciences (28°32′46″ N, 113°19′50″ E, and 80 m above mean sea level), Hunan Province, China. The study region is characterized by a subtropical humid monsoon climate with mean annual air temperature of 17.5 °C. The annual precipitation averages 1150 mm, with 70% of rainfall occurring between April and June. Double rice cropping with winter fallow is the dominant cropping system in this region, where some rice paddy fields have been drained out and converted to vegetable cultivation in recent years. The paddy soil in this study region is classified as Stagnic Anthrosols developed from granite-weathered red parental material (Gong et al. 2007), with clay-dominated soil texture (44.2% clay, 29.1% silt, and 26.7% sand). Daily air temperature and precipitation during the study period are shown in Fig. 1a, b, respectively.

Field experimental design All the selected plots had been under permanent cultivation of double-rice cropping for at least 100 years prior to the experiment. Portions of these rice paddy fields were randomly assigned to convert to conventional vegetable field plots and greenhouse vegetable field plots, respectively, after late rice harvest in October 2013. The experiment was initiated in October 2014 and lasted for over a full year with three treatments: rice paddy plots (RP), conventional vegetable plots converted from rice paddy (CV), and greenhouse vegetable plots converted from rice paddy (GV) in a randomized block design with three replicate plots (15 m × 20 m) of each treatment. Field management followed local farming practices. For RP, nitrogen fertilizer in the form of urea was applied at rates of 120 and 150 kg N ha−1 in the early rice and late rice seasons, respectively, with three splits: 50% as basal fertilizer, 30% as tiller fertilizer, and 20% as panicle fertilizer. P and K were concurrently applied in the form of calcium superphosphate at a rate of 40 kg P2O5 ha−1 and potassium chloride at a rate of 100 kg K2O ha−1, respectively, as basal fertilizers for both rice seasons. After rice transplantation, the paddy field remained flooded for one month. Thereafter, it was drained for

Environ Sci Pollut Res GV

Air temperature

(b)

40

Rainfall Season 1

0.10

Season 2

Season 3

-1

80 60

10

20

0.05

0.00 60 40

-0.05

20 0

0

(d) -1

N 2O flux (m g N m h )

Type *** Season *** Type×Season ***

0.09 0.06 0.03 0.00

120

80 60 40

Type * Season *** Type×Season ***

20

10

(h)

300

NH 4 -N (mg N kg dry soil)

Type *** Season NS Type×Season ***

-1

-1

DOC (mg C kg dry soil)

1

0

400

200

+

100

0

150

Type *** Season *** Type×Season ***

120 90 60 30 0

400

Type *** Season *** Type×Season ***

300

2014/10/1

2014/12/1

2015/2/1

2015/4/1

2015/6/1

2015/8/1

2015/10/1

-1

NO 3 -N (mg N kg dry soil)

2

30

20

(i)

3

40

Soil temperature ( ºC)

WFPS (%)

(f)

*** Type Season *** Type×Season ***

100

(g)

Type *** Season *** Type×Season ***

4

0

-0.03

(e)

0

5

-2

-2

-1

CH 4 flux (m g C m h )

(c) 0.12

-0.10

Precipitation (mm)

20 40

-2

30

-2

-1

100

CV

Season 3

Air temperature ( ºC)

CH 4 flux (m g C m h )

Season 2

Season 1

N 2O flux (m g N m h )

RP

(a)

-

200

100

0 2014/10/1

2014/12/1

2015/2/1

2015/4/1

2015/6/1

2015/8/1

2015/10/1

Fig. 1 Temporal dynamics of (a) air temperature, CH4 and (b) N2O fluxes from rice paddy field (RP) and daily precipitation, (c) CH4 and (d) N2O fluxes from conventional vegetable field (CV) and greenhouse vegetable field (GV), and (e) water-filled pore space (WFPS), (f) soil temperature, (g) dissolved organic carbon (DOC), (h) ammonium (NH4+), and (i) nitrate (NO3−) in RP, CV, and GV over the study period. ANOVA was used to evaluate the effects of land-use type, season, and their interaction on seasonal mean values of CH4 and N2O fluxes, WFPS, soil temperature, DOC, NH4+-N, and NO3−-N. NS, * and *** indicate not

significant, significant at p < 0.05 and p < 0.001 level, respectively. Season 1 refers to Bfallow season^ for rice paddy field, and Bcabbage growing season^ for conventional and greenhouse vegetable fields; season 2 refers to Bearly rice growing season^ for rice paddy field, and Beggplant growing season^ for conventional and greenhouse vegetable fields; season 3 refers to Blate rice growing season^ for rice paddy field, and Bbaby bok choy growing season^ for conventional and greenhouse vegetable fields. Solid downward black arrows indicate N fertilization events. Vertical bars indicate standard errors of three replicates

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two weeks, followed by intermittent irrigation until its final drainage 10 days before the rice harvest. According to local cropping rotations for vegetable production, the CV and GV were consecutively cultivated with cabbage, eggplant, and baby bok choy during the full-year study period. Before transplanting vegetable seedlings, calcium ammonium nitrate (containing 13.5% NO3−-N and 13.5% NH4+-N) was used as basal N fertilizer and incorporated into the soil by plowing. For the topdressing events, urea was dissolved in the water and then evenly applied to the field with irrigation. Other management practices (including tillage, fertilization dose and time, and irrigation) were performed according to local conventional practices. Weeding practice was performed manually to keep all the plots weed-free. The full-year study period was divided into three seasons: season 1 referred to Bfallow season^ for RP, and Bcabbage growing season^ for CV and GV; season 2 referred to Bearly rice growing season^ for RP, and Beggplant growing season^ for CV and GV; season 3 referred to Blate rice growing season^ for RP, and Bbaby bok choy growing season^ for CV and GV. Since the dates of the three growing seasons between the rice paddies and vegetable cropping systems were not exactly identical, we divided the seasons of the rice paddies and vegetable cropping systems according to the dates of rice growing seasons in order to compare GHG emission from different cropping systems within the same season. The crop cultivation, season, and fertilization calendar for the RP, CV, and GV treatments during the study period is described in detail in Table 1. The aboveground portions of crop straw residues were removed out of the plots after each harvest, and only some short stubbles were left in the field.

Soil CH4 and N2O flux measurements In situ fluxes of CH4 and N2O were measured simultaneously from RP, CV, and GV treatments using static opaque chamber technique (Zheng et al. 2008) from October 2014 to October 2015. In each treatment plot, a square stainless steel base frame (0.5 m × 0.5 m) with a groove around the upper edge was inserted 30 cm into the soil and remained in situ except for tillage. The square chambers (0.5 m × 0.5 m × 1.0 m high) were equipped with mini fans inside to ensure well-mixed headspace air and covered with plastic foam insulation outside to minimize air temperature change inside when gas sampling. A 30-cm long Teflon tube (internal diameter of 0.2 cm) was connected to the top of each chamber for gas sampling. When gas sampling, the chambers were manually placed on the base frames with a groove that was filled with water to provide an airtight seal. There were no differences in the planting density of rice seedlings or vegetables between inside and outside of the frames. A boardwalk was built for access to each base frame to avoid soil

disturbance when gas sampling. To measure CH4 and N2O fluxes, five gas samples were collected from the headspace of each chamber at 0, 10, 20, 30, and 40 min after chamber closure using 30 mL polypropylene syringes via the Teflon tube that was fitted to a three-way valve. The gases were sampled between 9:00 and 11:00 a.m. local standard time to approximate average daily fluxes and minimize diurnal variation in flux patterns (Reeves and Wang 2015). The 30-mL gas samples were immediately transferred into 12-mL pre-evacuated screw-cap septum glass vials (Labco Exetainer, Labco Limited, UK) and analyzed within 24 h on a gas chromatograph (Agilent 7890A, Agilent Technologies, Palo Alto, California, USA) equipped with a flame ionization detector for CH4 analyses at 250 °C and an electron capture detector for N2O analyses at 350 °C. The fluxes of CH4 and N2O were calculated from the linear or nonlinear changes in five gas concentrations measured over the closure time and corrected by chamber temperature and atmospheric pressure. In each treatment plot, CH4 and N2O fluxes were measured every other day for 7–10 days following fertilization and irrigation, and twice per week for the remainder of observation period. Seasonal and annual cumulative CH4 and N2O emissions were calculated by linear interpolation between successive sampling dates for each treatment. To compare the seasonal and annual GHG emissions of different treatments, the GWP of CH4 and N2O was calculated using the CO2-equivalent (CO2-eq) of 28 for CH4 and 265 for N2O relative to CO2 over a 100-year time horizon (IPCC 2013). The GWP (Mg CO2-eq ha−1) of the seasonal and annual emissions of CH 4 (Mg CH 4 ha − 1 ) and N 2 O (Mg N2O ha−1) was calculated using the following equation: GWP ¼ cumulative CH4 emission  28 þ cumulative N2 O emission  265:

Auxiliary variable measurements Concurrent with CH4 and N2O flux measurements, air temperature (TA) inside the chamber headspace and soil temperature (TS) at depth of 5 cm belowground in the vicinity of the base frames were measured using portable digital thermometers (JM624, Liwen Electronics LTD, Tianjin, China) in each plot. Surface water depths in the rice paddy plots were monitored during the flooding period. Topsoil samples (0–20 cm) were randomly collected from five points in each plot using a gauge auger (3 cm inside diameter) and then pooled and sealed in plastic bags. The soil samples were placed on ice and immediately carried to the laboratory for analysis of soil water content (SWC), mineral N (NH4+ and

Environ Sci Pollut Res Table 1 Cultivation and nitrogen fertilization practices in rice, conventional and greenhouse vegetable cropping systems

Crop type

Growth perioda

Fertilization dates

Ratesb (kg N ha−1)

(kg N ha−1 yr−1)

Rice paddy field Fallow

3 Oct 2014, 23 Apr 2015

Early rice

(Season 1) 24 Apr 2015, 17 Jul 2015

27 Apr 2015

60

(Oryza sativa L.)

(Season 2)

6 May 2015

36

Late rice

20 Jul 2015, 3 Oct 2015

25 Jun 2015 20 Jul 2015

24 75

(Oryza sativa L.)

(Season 3)

28 Jul 2015 7 Sep 2015

45 30

3 Oct 2014, 6 Apr 2015 (Season 1)

2 Oct 2014 31 Oct 2014

180 70

(Solanum melongena L.) Baby bok choy

20 Apr 2015, 2 Jul 2015 (Season 2)

24 Apr 2015 5 Jun 2015

150 60

14 Jul 2015, 3 Oct 2015

19 Jul 2015

250

(Brassica chinensis L.)

(Season 3)

8 Sep 2015

60

270

Conventional and greenhouse vegetable fields Cabbage (Brassica oleracea L.) Eggplant

770

Season 1 refers to Bfallow season^ for rice paddy field, and Bcabbage growing season^ for conventional and greenhouse vegetable fields; season 2 refers to Bearly rice growing season^ for rice paddy field, and Beggplant growing season^ for conventional and greenhouse vegetable fields; season 3 refers to Blate rice growing season^ for rice paddy field, and Bbaby bok choy growing season^ for conventional and greenhouse vegetable fields

a

b

Nitrogen fertilization rate represents the conventional N rate in this study

NO3−), and soil dissolved organic carbon (DOC). The frequency of soil sampling was once or twice a week, and the sampling date was concurrent with CH 4 and N2O flux measurement. Topsoil (0–20 cm) cores were collected from all treatment plots when the field experiment was initiated in October 2014 and after a full year in October 2015 to determine SOC and organic nitrogen (SON) contents. Additional topsoil cores were used for bulk density (BD) measurement. Soil samples were air-dried, ground after removing crop residue and coarse roots, and passed through a 0.15-mm sieve. Soil pH was measured in a 1 to 2.5 soil/water suspension. Soil organic C (inorganic C removal with dilute HCl before analysis) and total N were analyzed on a C/N elemental analyzer (Variomax CN Analyzer, Elementar GmbH, Hanau, Germany). Soil NH4+ and NO3− were determined, and SON was calculated by subtracting inorganic N (NH4+ + NO3−) from total N. Daily precipitation, air temperature, and air pressure were recorded by an automatic meteorological monitoring system (Intelimet Advantage, Dynamax Inc., USA) located within 80 m of the experimental site. Water-filled pore space (WFPS) was adopted to describe soil moisture and calculated as WFPS = (SWC × BD) / (1 − BD/PD), where particle density (PD) of the soil was assumed to be 2.65 g cm−3. The WFPS was assumed to be 100% when the rice paddy plot was under flooding condition.

Statistical analysis Prior to statistical analysis, all data were checked for normal distribution using the Kolmogorov–Smirnov test, and data displaying non-normality was natural logarithm transformed. Analysis of variance (ANOVA) was used to evaluate the effects of land-use type, season, and their interaction on CH4 and N2O emissions and soil properties. Stepwise multiple linear regression analysis was performed to create simple explanatory models to identify the principal factors controlling the temporal dynamics of CH4 and N2O fluxes. The statistical significance was set at the p < 0.05 level for all statistical tests. All data were statistically analyzed using the SPSS software package (SPSS 20.0, SPSS Inc., Chicago, USA).

Results Soil properties, environmental conditions, mineral N, and DOC SOC contents were slightly higher but not statistically significant in the RP plots relative to the CV and GV plots in both October 2014 and October 2015 (Table 2). Compared with the CV and GV soils, the RP soil had significantly greater SON but lower bulk density (Table 2). The SOC and SON contents showed declining trends for the three cropping systems over

Environ Sci Pollut Res Table 2 Topsoil organic carbon (SOC), organic nitrogen (SON), and dissolved organic carbon (DOC) contents, bulk density (BD), and pH in rice paddy field (RP), conventional vegetable field (CV) and greenhouse vegetable field (GV) measured at the start (Oct 2014) and end (Oct 2015) of the experiment SOC (g kg−1)

SON (g kg−1)

DOC (mg kg−1)

BD (g cm−3)

pH

RP 18.9a CV 16.9a GV 17.5a Oct 2015

2.07a 1.64b 1.70b

61.9c 212.9a 118.0b

1.02c 1.25b 1.35ab

5.28ab 5.50a 4.93bc

18.8a 16.0a 17.1a

2.02a 1.52c 1.56c

54.8c 152.6b 261.3a

1.06c 1.28ab 1.39a

5.54a 5.09b 4.64c

Oct 2014

RP CV GV

Different lowercase letters within the same column indicate significant difference among cropping systems at p < 0.05 level; values denote as means of three replicates

time and were most pronounced in CV, but the differences were only significant for SON in CV and GV. The values of soil pH were significantly lower for GV compared to RP and CV at both sampling dates (Table 2). Soil temperature (TS) exhibited seasonal variation patterns following that of air temperature with lowest values recorded in January 2015 (Fig. 1). Cropping systems had significant impact on T S with annual mean value higher in GV (20.4 °C) relative to RP (18.8 °C) and CV (18.3 °C) over the study period (Fig. 1). There also existed significant effects of season, cropping system, and their interaction on soil moisture (Fig. 1). RP had higher WFPS than either CV or GV in most days of the study period. Soil NH4+ contents varied from 2.4 to 79.1, 3.3 to 130.0, and 7.7 to 107.8 mg N kg−1 in RP, CV, and GV, respectively, with corresponding mean values of 20.5, 27.7, and 36.8 mg N kg−1 (Fig. 1). For RP, mineral N in the soil was dominated by NH4+, whereas soil NO3− contents remained lower than 4 mg N kg−1 throughout the study period (Fig. 1). The average soil NO 3 − contents were 42.9 and 150.2 mg N kg−1 in CV and GV, respectively, significantly higher than that in RP (1.2 mg N kg−1). Soil NH4+ was positively related to NO3− in both CV and GV (CV r = 0.50, p < 0.001; GV r = 0.90, p < 0.001). Soil DOC contents from RP, CV, and GV ranged from 31.9 to 264.0, 66.8 to 276.4, and 16.4 to 326.3 mg C kg−1, respectively, with corresponding mean values of 109.5, 159.8, and 143.8 mg C kg−1 (Fig. 1).

CH4 emission The CH4 emission from the RP plots varied significantly across seasons (Table 3, Fig. 1). During the fallow season, CH4 fluxes were negligible as a consequence of aeration,

varying between 0 and 2.2 mg C m−2 h−1, with a mean value of 0.1 mg C m−2 h−1. Significant CH4 emissions were observed over the rice growing seasons, particularly during early rice season. When the rice paddies were flooded, CH4 fluxes increased steadily over time, reaching peak fluxes of 56.8–72.6 mg C m−2 h−1 approximately 2 weeks after early rice transplantation under waterlogged condition. Thereafter, the fluxes gradually decreased to almost zero at the end of early rice season as the field was drained. During late rice season, CH 4 emission ]rates increased dramatically and peaked up to 24.4 mg C m−2 h−1 within 10 days following rice transplantation. Then, the fluxes decreased along with midseason drainage at the end of August. After reflooding, CH4 fluxes sharply increased and reached the second peak fluxes which were higher than the previous ones. Subsequently, CH4 fluxes decreased and fluctuated slightly at low rates until the final drainage for late rice harvest. CH4 fluxes from RP were positively correlated (p < 0.05) with soil temperature and WFPS. WFPS was the key factor regulating CH4 fluxes from RP, explaining 33% of the temporal variation in CH4 fluxes (Table 4). Land management change from RP to CVand GV substantially decreased CH4 emission by nearly 100% (Table 3, Fig. 1). Both CV and GV plots acted as minor sources of CH4 emissions. CH4 fluxes ranged from − 24.8 to 70.2 μg C m−2 h−1 in CV and − 22.9 to 62.4 μg C m−2 h−1 in GV, with corresponding mean values of 9.8 and 2.7 μg C m−2 h−1 over the study period. There was no significant difference in cumulative CH4 emissions between CVand GVacross the three vegetable cropping seasons. Nevertheless, season, cropping system, and their interaction had significant effects on CH4 emissions. CH4 fluxes from CV were positively driven by TS which explained 22% of the temporal variation in CH4 fluxes (Table 4). For GV, 5% of the variation in CH4 fluxes was explained by WFPS (Table 4).

N2O emission The RP soil acted as either a minor sink or source of atmospheric N2O across the three seasons and consumed 0.1 kg N 2 O-N ha −1 over the full-year study period (Table 3, Fig. 1). N2O fluxes from RP averaged − 0.9, − 4.5, and 2.4 μg N m−2 h−1 over the fallow, early rice, and late rice seasons, respectively, without significant difference among seasons. Furthermore, there existed no determined environmental factors affecting the temporal dynamics of N2O fluxes from RP. Land management change from RP to CV and GV dramatically increased N2O emissions (Table 3, Fig. 1). N2O emission rates from CV and GV showed considerably seasonal variation, with seasonal mean N2O flux significantly higher over the baby bok choy growing season in comparison with

Environ Sci Pollut Res Table 3 Seasonal and annual mean fluxes and cumulative emissions of CH4 and N2O from rice paddy field (RP), conventional vegetable field (CV), and greenhouse vegetable field (GV) Seasona

Treatment

Mean CH4 fluxb (mg m−2 h−1)

Cumulative CH4 emissionc (kg C ha−1)

Mean N2O flux (μg m−2 h−1)

Cumulative N2O emission (kg N ha−1)

GWP (Mg CO2-eq ha−1)d

Season 1 (203 d)

RP CV GV RP CV GV RP CV GV

0.11C 0.002C −0.001C 24.3A 0.019C 0.002C 11.9B 0.020C 0.012C

5.34a 0.09b −0.03b 496.6a 0.39b 0.04b 219.0a 0.38b 0.21b

−0.91E 197.0D 242.4D −4.49E 339.5C 216.8D 2.35E 826.6B 1946.8A

−0.04b 9.60a 11.8a −0.09c 6.93a 4.42b 0.04c 15.3b 36.0a

0.18b 4.00a 4.92a 18.5a 2.90b 1.84b 8.19b 6.38b 15.0a

RP CV GV

8.23 0.010 0.003

720.9a 0.86b 0.23b

−1.06 363.0 596.0

−0.09c 31.8b 52.2a

26.9a 13.3c 21.8b

Season 2 (85 d) Season 3 (77 d) Annual (365 d)

Season 1 refers to Bfallow season^ for rice paddy field, and Bcabbage growing season^ for conventional and greenhouse vegetable fields; season 2 refers to Bearly rice growing season^ for rice paddy field, and Beggplant growing season^ for conventional and greenhouse vegetable fields; season 3 refers to Blate rice growing season^ for rice paddy field, and Bbaby bok choy growing season^ for conventional and greenhouse vegetable fields

a

b

Different capital letters within the same column indicate significant difference among seasons and cropping systems at p < 0.05 level

c

Different lowercase within the same column letters indicate significant difference among cropping systems for each season at p < 0.05 level

d

The global warming potentials (GWPs) of combined CH4 and N2O emissions were calculated using the CO2-equivalent (CO2-eq) of 28 for CH4 and 265 for N2O relative to CO2 over a 100-year time horizon (IPCC 2013) Values denote as means of three replicates

the cabbage and eggplant growing seasons for both CV and GV. For CV, N 2 O fluxes averaged 197.0, 339.5, and 826.6 μg N m−2 h−1 during the cabbage, eggplant, and baby bok choy growing seasons, respectively. For GV, the seasonal N2O flux averaged 1946.8 μg N m−2 h−1 over the baby bok Table 4 Parameters and coefficients of determination of the linear regression models explaining the temporal variation in annual CH4 and N2O fluxes from rice paddy field, conventional vegetable field and greenhouse vegetable field

choy growing season, being almost 7 and 8 times higher than those during the cabbage and eggplant growing seasons, respectively. The peaks of N2O fluxes from CV and GV were mainly concentrated within 10 days following basal fertilization and topdressing events in combination with irrigation

Dependent variable

Parameter

Coefficient

p value

Adjust R2

p value

Rice paddy field CH4

Intercept

− 56.7

< 0.001

0.33

< 0.001

74.9

< 0.001

− 0.01 0.001 − 7.30 0.14 7.04 1.15

0.041 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001

0.22

< 0.001

0.47

< 0.001

− 7.30 9.51 − 3.00 7.68 0.11

0.052 0.042 0.001 < 0.001 < 0.001

0.05

0.042

0.62

< 0.001

WFPS None N2O Conventional vegetable field Intercept CH4 Ts Intercept lnN2O Ts WFPS ln(NH4 + NO3) Greenhouse vegetable field Intercept CH4 WFPS Intercept lnN2O WFPS Ts

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during the three vegetable growing seasons (Fig. 1d). Annual cumulative N2O emission from GV was 52.2 kg N ha−1, significantly higher as compared to CV (31.8 kg N ha −1) (Table 3). The annual N2O emission factors, uncorrected for background emissions, were 4.1% and 6.8% of the total amount of mineral N applied over the three vegetable cropping seasons for CV and GV, respectively. N2O emission was significantly influenced by season, cropping system, and their interaction (Fig. 1). N2O fluxes from both CV and GV were significantly and positively correlated with TS and WFPS. The stepwise regression model indicated that TS, WFPS, and mineral N were the main factors controlling N2O fluxes from CV, together accounting for 47% of the temporal variance in annual N2O fluxes (Table 4). For GV, 62% of the temporal variation in N2O emission rates could be explained by WFPS and TS.

The GWP of CH4 and N2O emissions The GWP (CO2-eq) was calculated based on a 100-year time horizon to compare the seasonal and annual total emissions of CH4 and N2O among the three cropping systems (Table 3). The seasonal GWP was significantly influenced by season, cropping system and their interaction. For RP, the annual GWP was 26.9 Mg CO2-eq ha−1, significantly higher than those for CV (13.3 Mg CO2-eq ha−1) and GV (21.8 Mg CO2-eq ha−1). These results indicated that land management change significantly decreased the total emission of CH4 and N2O by 19–51% in CV and GV relative to RP.

Discussion Effect of land management change on CH4 emissions CH4 emission rates from our rice paddy exhibited a distinct seasonal variation pattern, consistent with previous findings (Haque et al. 2015; Wang et al. 2016; Weller et al. 2016; Zhang et al. 2016a) that peak values mostly occur during rice growing seasons (Fig. 1). The combination of submerged soil condition creating anaerobic environment, abundant labile carbon substrates sourced from root exudates and root debris and high soil temperature provided optimal conditions facilitating CH4 production during rice seasons (Shang et al. 2011; Feng et al. 2013; Gaihre et al. 2013). The magnitude of CH4 emission was significantly higher in the early rice-growing season relative to late rice-growing season. This phenomenon was likely due to the abundant weed biomass growing in the preceding fallow season, being incorporated into soil by spring plowing when transplanting early rice seedlings. This green manure could supply enough substrates for methanogenesis, thus enhancing CH4 emission during early rice cultivation. Moreover, cumulative rainfall during the early

rice-growing season was 610 mm, higher than that in the late rice-growing season (211 mm) (Fig. 1). The submerged condition with abundant rainfall during early rice growing season favored CH4 production. Our study demonstrated that RP act as a significant source of atmospheric CH 4 , emitting 720.9 kg CH4-C ha−1 yr−1 (Table 3), exceeding those values reported in some previous studies (Wang et al. 2016; Zhang et al. 2016a), but falling within the upper range of 10.3– 880.5 kg CH4-C ha−1 yr−1 reported in the literature for other rice paddies (Shang et al. 2011; Zhang et al. 2017). The high annual CH4 emission observed in the present study was partially attributed to the combined influence of prolonged flooding period creating low redox potentials and high soil temperature. This favorable condition facilitated CH4 production from the double-rice cropping system at our study site relative to single rice or rice-upland crop rotation cropping system in other regions (Feng et al. 2013; Ma et al. 2013). In addition, most of the previous studies mainly focused on the CH4 emissions from rice paddies during the growing seasons, neglecting emissions from the fallow season, therefore underestimating the annual emissions (Eusufzai et al. 2010; Yang et al. 2010; Haque et al. 2016). Further studies should investigate CH4 emissions during rice growing season and fallow season simultaneously to develop management strategies for mitigating GHG emissions from rice paddies. Land management change from rice to vegetable cultivation drastically decreased annual CH4 emission by almost 100% (Table 3). Net CH4 exchanges largely result from the balance between CH4 production and consumption (Inubushi et al. 2003a). Drainage of rice paddy for upland cultivation can have dramatic effects on soil properties (i.e., soil porosity, moisture and redox status) that influence soil C cycling and associated CH4 emission (Breidenbach et al. 2015; Liu et al. 2015). Significantly lower CH4 fluxes and lack of seasonal patterns were observed from the converted CV and GV in comparison with those from RP (Fig. 1). The reduced CH4 fluxes could be explained by the decreased annual mean WFPS from 90% in RP to 69% in CV and 81% in GV, improving soil aeration associated with higher redox potential, thus inhibiting CH4 production while enhancing CH4 oxidation (Aulakh et al. 2001; Yuan et al. 2015). This conversion led to negligible CH4 emission from CV and GV across vegetable-growing seasons, and even net CH4 uptake occurring in GV during the cabbage-growing season (Table 3).

Effect of land management change on N2O emissions N2O fluxes were negligible in RP over the full annual cycle, resulting in no pronounced seasonal variation and low to negative seasonal cumulative emissions (Table 3, Fig. 1). This is in contrast with the results of previous studies (Liu et al. 2010; Shang et al. 2011; Zhang et al. 2014) which often reported rice paddy system acting as a significant source of N2O, but

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comparable to the result obtained from Inubushi et al. (2003b) that paddy field was an N2O sink, consuming 0.47 kg N2ON ha−1 yr−1. Previous investigations (Letey et al. 1981; Yang and Silver 2016) have demonstrated redox potential to affect N2O emission by regulating the balance between N2O production and consumption. The reason for the minor sink of N2O for RP in the present study was likely because of the prolonged submerged condition limiting soil oxygen availability and nitrification potential, thus suppressing the supply of NO3− (mean 1.2 mg NO3−-N kg−1) for subsequent denitrification (Fig. 1). In the absence of NO3−, N2O can act as the primary electron acceptor for denitrification process (Ryden 1983; Chapuis-Lardy et al. 2007). Submerged soil conditions and negligible NO3− contents in RP limited N2O production while promoting N2O consumption. Though in the fallow season after drainage, RP still acted as a minor N2O sink. The high soil moisture during the fallow season due to high soil clay content (44.2% clay) and rainfall restricted nitrification process, resulting in low NO3− content (0.81 mg N kg−1) and contributing to minor N2O sink in the fallow season. The lack of correlation between N2O fluxes and mineral N in rice paddy further demonstrated that soil moisture rather than available N was the major factor influencing N2O emission. This finding indicates that strictly anaerobic condition in flooded rice paddy is the most likely reason inhibiting N2O production from coupled nitrification-denitrification and stimulating N2O reduction to N2 via denitrification (Zou et al. 2007; Jørgensen et al. 2012). Drainage of rice paddy for vegetable cultivation triggered substantial N2O emissions (Fig. 1). This phenomenon could be attributed to the following reasons: (a) The amounts of N fertilizer input were higher in CV and GV relative to RP (770 vs. 270 kg N ha−1 yr−1), providing sufficient substrates for microbial nitrification and denitrification processes during vegetable cultivation (Zhang et al. 2016c). (b) Conversion of rice paddy to vegetable cultivation decreased WFPS, thus increasing soil oxygen availability and promoting nitrification process (Yang et al. 2016; Qin et al. 2016). (c) Improved soil aeration porosity facilitated soil N2O diffusion into the atmosphere. (d) Increased soil aerobic respiration triggered the coexistence of anoxic and oxic microsites stimulating coupled nitrification-denitrification, thereby enhancing N2O production (Penton et al. 2013; Deppe et al. 2017). Multiple regression models indicated that soil moisture and temperature were the predominant factors positively affecting N2O fluxes in both CV and GV (Table 4), confirming a number of previous studies on factors controlling N2O emissions from vegetable fields (Mei et al. 2011; Li et al. 2017; Wu et al. 2017). Given the high levels of soil moisture (WFPS > 60% for most of the study period) and soil NO3− in both CV and GV, the positive relationship between N2O fluxes and WFPS

implied that denitrification rather than nitrification could be the dominant microbial process for N2O production. Substantial N2O emissions from the vegetable cropping systems were mainly due to high fertilizer N-induced N2O emissions, which could be inferred from the N fertilization events induced N2O peaks. These peaks of N2O fluxes contributed to the majority (82–87%) of the annual N2O emission from CV and GV with 32–39% time duration of the full year study period (Fig. 1). The magnitude of annual N2O emission from GV significantly exceeded that from CV. This difference was likely attributed to differences in soil moisture, soil temperature and pH, all of which could significantly influence N 2O emissions (Mei et al. 2011; Samad et al. 2016). In general, the higher WFPS in GV relative to CV (81% vs. 69%) could result in tightly coupled nitrification-denitrification processes and thus higher N2O production (Deppe et al. 2017). The plastic film cover caused annual mean soil temperature to be higher in GV than that in CV (20.4 vs. 18.3 °C), contributing to higher activities of nitrifiers and denitrifiers and thus more N2O emissions from GV. An alternative explanation for the higher N2O fluxes from GV was the increased soil acidity (Table 2), potentially inhibiting the activities of the functional N 2 O reductase enzymes, resulting in increased N2O emission from denitrification (Qu et al. 2014). In addition, the higher N2O emission from GV relative to CV was partially explained by the lack of N runoff and little N leaching due to the shielding of rainfall by plastic film cover, retaining more mineral N as available substrates in the GV soil (70.5 and 187.0 mg N kg−1 in CV and GV, respectively) for nitrification and denitrification processes. Annual N2O emissions from our converted CV and GV are much higher as compared to those reported for other vegetable fields (Liu et al. 2013; Yan et al. 2014; Yao et al. 2015). The considerable differences in N2O emissions presented here are most likely driven by differences in soil properties and management practices. Since CV and GV were established in 2013, there probably existed legacy effects from previous rice crop cultivation accumulating high content of soil organic N, thus influencing current N cycling and associated N2O production. The lower SOC and SON but higher DOC in CV and GV relative to RP, and the decreased SOC and SON in CVand GVover time both demonstrated the release of bio-available C and N from intense decomposition of soil organic matter after drainage and tillage (Table 2). The soil labile C and N could act as energy and substrates for nitrifying and denitrifying microbes, thus contributing to increased N2O production (Grandy and Robertson 2006; Wang et al. 2011). The present study suggests that mineral N derived from soil organic N mineralization following land management change should be regarded as a potential source of substrate for N2O production.

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Effect of land management change on the GWP

References

Agriculture land management change significantly affects GHG budgets because of trade-offs that develop between CH4 and N2O emissions (Shang et al. 2011; Weller et al. 2016). Conversion of rice to vegetable cultivation significantly increased N2O emission, partially offsetting the benefits of CH4 mitigation, resulting in the GWP significantly lower in CVand GV relative to RP. These results suggest that vegetable cultivation on paddy field could significantly mitigate the total emissions of CH4 and N2O. Since it takes decades for detectable changes in SOC stock due to the high spatial heterogeneity of SOC contents (Smith 2004), the present study lasted for a full year and referred to CH4 and N2O for calculation of the GWP. Changes in the SOC and indirect GHG emissions arising from ammonia volatilization, labile C and N runoff and leaching, farm operation and agricultural inputs associated with land management change may also significantly contribute to GWP, and would be required so as to make a life-cycling evaluation of GHG budgets under different land management practices (West and Marland 2002; Zhang et al. 2016b).

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Conclusions Initial land management change from RP to CV and GV dramatically reduced CH4 emissions while triggering substantial N2O emissions over the annual cycle. N2O emission from GV (52.2 kg N ha−1 yr−1) significantly exceeded that from CV (31.8 kg N ha−1 yr−1), owing to lower soil pH and higher soil temperature facilitating N2O production in GV. Given the high levels of soil moisture and soil NO3− in both CV and GV, the positive relationship between N2O fluxes and WFPS implied that denitrification could be the dominant process for N2O production. The reduced CH4 emission outweighed the increased N2O emission following RP conversion to CV and GV, leading to significant reduction in the GWP (CH4 and N2O) by 19–51%. Overall, these results indicate that initial land management change from rice to vegetable production for higher economic benefits also helps mitigate the total emissions of CH4 and N2O. Further research is required for simultaneous investigation of direct and indirect GHG emissions and soil carbon budget to provide reliable information on life-cycling assessment of GHG emissions following agricultural land management change. Acknowledgements The authors would like to thank the National Program on Key Basic Research Project of China (2012CB417106) and the Fundamental Research Fund for the Central Universities (2662016PY098) for financially supporting this research. Minghua Zhou received support via the CAS Pioneer Hundred Talents Program. The authors also would like to acknowledge the coworkers and students of the Changsha Research Station for Agricultural & Environmental Monitoring who helped with field sampling and laboratory analyses.

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