A comparison of methane and nitrous oxide emissions from inland mixed-fish and crab aquaculture ponds

Science of the Total Environment 637–638 (2018) 517–523

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A comparison of methane and nitrous oxide emissions from inland mixed-fish and crab aquaculture ponds Yuchun Ma a,b,c,⁎, Liying Sun a,c, Cuiying Liu a, Xiaoya Yang a,c, Wei Zhou b, Bo Yang d, Graeme Schwenke e, De Li Liu f,g a

Jiangsu Key Laboratory of Agricultural Meteorology, College of Applied Meteorology, Nanjing University of Information Science & Technology, Nanjing, Jiangsu 210044, China State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Science, Nanjing, Jiangsu 210008, China Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters,Nanjing University of Information Science & Technology,Nanjing, Jiangsu 210044,China d Agro-Environmental Protection Institute, Ministry of Agriculture, Tianjin 300191, China e NSW Department of Primary Industries, 4 Marsden Park Road, Tamworth, NSW 2340, Australia f NSW Department of Primary Industries, Wagga Wagga Agricultural Institute, Wagga Wagga, NSW 2650, Australia g Climate Change Research Centre and ARC Centre of Excellence for Climate Extremes, University of New South Wales, Sydney, NSW 2052, Australia b c

H I G H L I G H T S

G R A P H I C A L

A B S T R A C T

• The annual CH4 emissions were 64.4 kg C ha-1 from mixed fish pond and 51.6 kg C ha-1 from crab pond. • The annual N2O emissions were 2.99 kg N ha-1 from mixed fish pond and 3.22 kg N ha-1 from crab pond. • CH4 emissions in the mixed fish pond were higher and N2O emissions were lower than the crab pond. • CH4 emissions were 14.0% greater in the area with aquatic vegetation than that without aquatic vegetation.

a r t i c l e

i n f o

Article history: Received 25 February 2018 Received in revised form 3 May 2018 Accepted 3 May 2018 Available online xxxx Editor: Jay Gan Keywords: Methane Nitrous oxide Mixed-fish aquaculture pond

⁎ Corresponding author. E-mail address: [email protected] (Y. Ma). https://doi.org/10.1016/j.scitotenv.2018.05.040 0048-9697/© 2018 Elsevier B.V. All rights reserved.

a b s t r a c t Inland aquaculture ponds in China collectively cover 2.57 million ha, so emissions of the greenhouse gases methane (CH4) and nitrous oxide (N2O) from these ponds may constitute a significant contribution to global warming. During 2016 and 2017, CH4 and N2O fluxes and a range of pond-water and sediment properties were measured in replicated (n = 4) “mixed-fish” and “crab” aquaculture ponds in southeast China. Annual CH4 and N2O emissions were 64.4 kg C ha−1 and 2.99 kg N ha−1, respectively, from the “mixed-fish” ponds, and 51.6 kg C ha−1 and 3.32 kg N ha−1, respectively, from the “crab” ponds. Emission differences between pond types were significant (p b 0.05) for both gases. CH4 fluxes from the “crab” ponds were significantly increased by the presence of aquatic vegetation, but N2O fluxes were not affected. Emissions of N2O were estimated to be 0.54% and 0.71% of the total nitrogen input (in the feed) for the “mixed-fish” and “crab” ponds, respectively. The net economic benefit-scaled sustained-flux global warming potential (NEB-scaled SGWP) of the “crab” ponds was 61.6% higher (p b 0.05) than that of the “mixed-fish” pond. Our CH4 and N2O emissions results suggest that aquaculture ponds can be

518 Crab aquaculture pond NEB-scaled SGWP

Y. Ma et al. / Science of the Total Environment 637–638 (2018) 517–523

important contributors to regional and national GHG inventories, with aquaculture type an important factor in total GHG impact. Further CH4 and N2O flux research is needed at aquaculture ponds across China to better establish the range of potential GHG impacts, and to confirm the importance of the influencing factors identified in this study. © 2018 Elsevier B.V. All rights reserved.

1. Introduction

2. Materials and methods

Methane (CH4) and nitrous oxide (N2O) are key radiatively active greenhouse gases (GHGs) in the atmosphere. Over a 100-year time scale, the global warming potential (GWP) of CH4 and N2O are 28 and 265 times that of carbon dioxide (CO2), respectively (IPCC, 2013a). Overall, CH4 and N2O contribute 16% and 6%, respectively, to global radiative forcing, and their atmospheric concentrations are rapidly increasing (World Meteorological Organization, 2016). Aquatic ecosystems are significant sources of atmospheric CH4 and N2O. To date, most research on GHG emissions from aquatic ecosystems has focused on natural lakes (Huttunen et al., 2003), rivers (Aufdenkampe et al., 2011; Clough et al., 2011; Yang et al., 2015), ditches (Schrier-Uijl et al., 2011) and reservoirs (Huttunen et al., 2003; Diem et al., 2012). These studies found that variations in GHG emissions were linked to weather, water thermal regimes, nutrient content and other environmental factors (Natchimuthu et al., 2014). Aquaculture is an important anthropogenic source of GHG emissions which has recently received worldwide attention (Liu et al., 2016). Aquaculture ecosystems receive large amounts of nutrient inputs to accelerate primary production (Serrano-Grijalva et al., 2011; Zhang et al., 2015; Xiao et al., 2017). The organic feeding material used can also have significant effects on microbial processes, which in turn affect carbon (C) and nitrogen (N) biogeochemical processes that emit CH4 and N2O (Yang et al., 2015). Current knowledge of GHG fluxes from aquaculture ponds is limited. The most recent Intergovernmental Panel on Climate Change (IPCC) report provides methodological guidance on CH4 emissions, but no field measured data of direct emissions. Methodologies are available to calculate emission factors and estimate N2O emissions from aquaculture ponds (IPCC, 2006). The model results based on indirect calculations suggest that global N2ON emissions from aquaculture will increase from 9.30 × 1010 g to 3.83 × 1011 g by 2030, which will account for 5.72% of global anthropogenic N2O emissions if the world aquaculture industry continues to grow at the present annual growth rate of 7.1% (Muralidhar et al., 2017). These modeling results must be validated and calibrated with field N2O flux measurements. There are few published measurements of direct CH4 and N2O fluxes from aquaculture ponds (Hu, 2015; Liu et al., 2016), with most focusing on CH4 and N2O emissions from the conversion of rice paddies to inland aquaculture ponds. Environmental factors that potentially affect GHG production should also be evaluated, including temperature (T), pH, dissolved oxygen (DO), and C substrate availability (Xing et al., 2005; Yang et al., 2015; Liu et al., 2016). Aquaculture is the fastest-growing food-production sector in China due to the increasing population and a rapidly expanding consumer demand for fish (Williams et al., 2010). Collectively, aquaculture ponds in China cover 2.57 million ha, about 10% of the total cropping area (Cao et al., 2011). The Taihu Lake region (Yangtze Delta Plain) is one of the most intensive regions of aquaculture, particularly for fish and crab production (Cao et al., 2007). The objectives of this study were to (1) quantify and compare CH4 and N2O emissions from inland “mixed-fish” and “crab” aquaculture ponds in the Taihu Lake region, and (2) to determine the properties driving temporal variation in CH4 and N2O fluxes. This data will be used to more accurately quantify the GHG budget and GWP of the Chinese aquaculture industry.

2.1. Experiment site Field experiments were carried out during 2016–2017 in “mixedfish” and “crab” aquaculture ponds at the Changshu Agro-Ecological Experimental Station (31°32′93′′N, 120°41′88′′E) of the Chinese Academy of Sciences in Jiangsu province. The two sets of ponds were approximately 200 m apart. The soil under the pond-water is an Anthrosol (FAO World Reference Base) developed from lacustrine sediments, and has a silty clay texture. Physicochemical properties of the sediment are detailed in Table 1. 2.2. Field experiments in the “mixed-fish” and “crab” ponds Four “mixed-fish” aquaculture ponds (50 × 140 m) and four “crab” aquaculture ponds (50 × 100 m) were set up as experimental replicates. The “mixed-fish” and “crab” ponds were 2.0 m and 1.4 m deep, respectively. On 22 March 2016, the “mixed-fish” ponds were fry-stocked with 250 kg ha−1 of black carp (Mylopharyngodon piceus), 650 kg ha−1 of grass carp (Ctenopharyngodon idella), and 270 kg ha−1 of chub (Hypophthalmichthys molitrix). Each “crab” pond was split into ‘with aquatic vegetation’ or ‘without aquatic vegetation’. On 14 March 2016, Elodea nuttallii was planted across 60% of the bottom sediment area of each pond to provide food and a molting shelter for the crabs. On 28 March 2016, young crab fry (Eriocheir sinensis) were stocked at 100 kg ha−1. Sudan grass (Sorghum sudanense), snail compound feed, and pellet feed were used as feed in the “mixed-fish” pond, while corn, hairtail, and compound feeds were used for feed in the “crab” ponds. The total annual N input was 550 kg N ha−1 in the “mixedfish” ponds and 469 kg N ha−1 in the “crab” ponds. These stocking rates and feed inputs were in line with local commercial “mixed-fish” and “crab” farming practices. Details of aquaculture operations and N inputs are given in Table 2. 2.3. Measurement of CH4 and N2O fluxes Gas emissions from the water-atmosphere interface were collected with floating static chambers (Liu et al., 2016), consisting of a floating bottom collar and a PVC open-bottomed chamber (50 cm × 50 cm × 50 cm). During the pond drainage period, emissions from the sediment-atmosphere interface were collected with enclosed static chambers (Ma et al., 2013). The enclosed static chamber was 0.5 m high, covered an area of 0.25 m2, and was placed on a PVC frame inserted into the sediment. Gas fluxes were measured three or four times per month in both pond types (water-atmosphere interface: March 2016–December 2016; sediment-atmosphere interface: January 2017–March 2017). All samples were collected between 09:00 and 11:00 am. During sampling, gas samples were transferred from the chambers into airtight 500 mL gas sampling bags at 10 min intervals for 40 min after chamber closure. The airtight gas sampling bags were pre-evacuated to approximately 0 Pa. The CH4 and N2O concentrations were analyzed using a gas chromatograph (Agilent 7890) equipped with a flame ionization detector (FID) and an electron capture detector (ECD). The CH4 and N2O fluxes

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Table 1 Physicochemical properties of sediment in the ‘mixed-fish’ and ‘crab’ aquaculture ponds. Type

Total nitrogen (g N kg−1)

Bulk density (g cm−3)

Organic carbon (g C kg−1)

pH

‘Mixed-fish’ pond ‘Crab’ pond

1.56 ± 0.09 1.49 ± 0.06

1.34 ± 0.02 1.25 ± 0.11

31.44 ± 6.09 20.03 ± 3.12

6.8 ± 0.15 7.0 ± 0.08

were calculated from the changes in gas concentrations using a linear model (Ma et al., 2013).

N2O fluxes on water and sediment parameters. All statistical analyses were performed using SPSS version 19.0 (SPSS Incorporated, United States) at the 0.05 significance level.

2.4. Ancillary environmental variables 3. Results Meteorological data, including daily mean air temperature (T) and precipitation, were collected from the Changshu automatic weather station, located 100 m from the experimental site. We used a YSI EXO 1 multi-parameter probe to measure the sediment temperature, sediment pH and water dissolved oxygen (DO) of the water samples in situ. An N/C 3100 (Analytik Jena AG, Germany) multi-analyzer was used to determine the sediment dissolved organic carbon (DOC) from samples taken on the days of gas sampling. The sampling frequency was 2–3 times per month, and the samples were taken to 0–10 cm depth. The accuracy of the probes was 0.01 °C for sediment T, 0.1 unit for sediment pH, and 0.1 mg kg−1 for water DO. Water/sediment nitrate + (NO− 3 -N) and ammonium (NH4 -N) were determined in filtered (cellulose acetate, 0.45 μm) samples using a SmartChem 140 discrete auto-analyzer (Westco Scientific Instruments) with detection limits of −1 0.01 mg N kg−1 for NO− for NH+ 3 -N and 0.02 mg N kg 4 -N. All water samples were stored at 4 °C and were analyzed within 7 days.

3.1. CH4 emissions Temporal trends of CH4 fluxes were similar between the “mixedfish” and “crab” aquaculture ponds (Fig. 1). In general, emissions of CH4 increased steadily with the length-of-time of flooding and air temperature, with a mid-season peak in both pond types corresponding with the maximum temperature. Subsequently, CH4 emissions decreased with decreasing temperature until the fish and crabs were harvested, and ponds were drained of water. The presence of aquatic vegetation in the “crab” ponds did not alter the annual pattern of CH4 fluxes (Fig. 1). Cumulative CH4 emitted over the annual cycle was 19.8% greater from the “mixed-fish” ponds than from the “crab” ponds (Table 3). In the “crab” ponds, yearly CH4 emitted was 14.0% greater in areas of aquatic vegetation than areas without aquatic vegetation. CH4 emissions were minimal in the post-harvest pond drainage period (Fig. 1).

2.5. Statistical analyses 3.2. N2O emissions Differences in annual CH4 and N2O emissions between the two different aquaculture pond types were examined using a one-way analysis of variance (ANOVA). The differences between the treatments were further examined by Tukey's multiple range tests. Spearman's correlation coefficients were computed to examine the dependence of CH4 and

In both “mixed-fish” and “crab” ponds, N2O emissions were negligible during the waterlogged period, but increased dramatically after the ponds were drained in December 2016 (Fig. 2). Cumulative N2O emitted from the “crab” ponds was 11.0% greater than from the “mixed-fish”

Table 2 Agricultural practice and N content in the ‘mixed-fish’ and ‘crab’ aquaculture ponds. Date (yyyy/mm/dd) ‘Mixed-fish’ ponds 2016/3/15 2016/3/22

2016/5–2017/1

2017/1/5

2017/1/5 2017/1/6 ‘Crab’ ponds 2016/3/14 2016/3/15 2016/3/28 2016/5/9 2016/5–2016/10

2016/10–2016/12 2017/1/5 2017/1/10

Aquaculture operation

Details

Total N content

Pond flooding (water depth) Fry stocking ~ Black carp Grass carp Chub Feed inputs ~ Sudan grass Snail Compound feed Pellet feed Fish harvest ~ Black carp Grass carp Chub Pond disinfection Pond drying

2.0 m

–

250 kg ha−1 650 kg ha−1 270 kg ha−1

2.73% 2.19% 2.32%

2600 kg ha−1 1350 kg ha−1 6910 kg ha−1 850 kg ha−1

0.36% 0.60% 6.82% 4.00%

652 kg ha−1 1474 kg ha−1 1923 kg ha−1 – –

– – – – –

30 kg ha−1 1.4 m 100 kg ha−1 2150 kg ha−1

0.32% – 2.22% 0.60%

950 kg ha−1 3000 kg ha−1 6800 kg ha−1 960 kg ha−1 – –

1.58% 2.65% 5.28% – – –

Planting waterweed (Elodea Canadensis) Pond flooding (water depth) Crab stocking Snail stocking Feeds inputs ~ Corn Hairtail Compound feed Crab harvest Pond drying Pond disinfection

520

Y. Ma et al. / Science of the Total Environment 637–638 (2018) 517–523

3.5 waterlogging period (a)

350

drainage

waterlogging period

Mixed fish pond

(a)

2.5

250 N2 O fluxes (μg m-2 h-1 )

CH4 fulxes (mg m-2 h -1 )

drainage

300

1.5

Mixed fish pond

200 150 100

0.5

50 0 water depth: 1.5 m

water depth: 2.0 m

-0.5

-50

3.5 waterlogging period (b)

350

drainage

waterlogging period 300

Crab pond with aquatic vegetation

(b)

2.5

Crab pond with Aquatic vegetation

250 N2 O fluxes (μg m-2 h-1 )

Crab pond without aquatic vegetation

CH4 fulxes (mg m-2 h -1 )

drainage

1.5

Crab pond without Aquatic vegetation 200 150 100

0.5

50 0

water depth: 1.4 m

water depth: 1.0 m

-50 15-Mar-16 30-Mar-16 14-Apr-16 29-Apr-16 14-May-16 29-May-16 13-Jun-16 28-Jun-16 13-Jul-16 28-Jul-16 12-Aug-16 27-Aug-16 11-Sep-16 26-Sep-16 11-Oct-16 26-Oct-16 10-Nov-16 25-Nov-16 10-Dec-16 25-Dec-16 9-Jan-17 24-Jan-17 8-Feb-17 23-Feb-17 10-Mar-17

15-Mar-16 30-Mar-16 14-Apr-16 29-Apr-16 14-May-16 29-May-16 13-Jun-16 28-Jun-16 13-Jul-16 28-Jul-16 12-Aug-16 27-Aug-16 11-Sep-16 26-Sep-16 11-Oct-16 26-Oct-16 10-Nov-16 25-Nov-16 10-Dec-16 25-Dec-16 9-Jan-17 24-Jan-17 8-Feb-17 23-Feb-17 10-Mar-17

-0.5

Date (dd-m-yy) Date (dd-m-yy) Fig. 1. CH4 fluxes from the ‘mixed-fish’ and ‘crab’ aquaculture ponds.

ponds (Table 3). Within the “crab” ponds, the presence of aquatic vegetation did not influence N2O emissions. Seasonal N2O emissions were positively correlated to the pond sediment T, sediment DOC, pH, NH+ 4 N and NO− 3 -N concentrations, and negatively correlated to water DO (Table 4). 3.3. Environmental factors The daily sediment temperature at a depth of 10 cm during the sampling period ranged from 3.8–33.7 °C in the “mixed-fish” ponds and

Fig. 2. N2O fluxes from the “mixed- fish” and ‘crab’ aquaculture ponds.

from 2.5–32.4 °C in “crab” ponds. DO concentrations ranged from 3.6– 6.6 mg L−1 in the “mixed-fish” ponds and from 5.1–8.1 mg L−1 in the “crab” ponds. The sediments in the “mixed-fish” and “crab” ponds were slightly alkaline, with mean pHs of 8.5 and 7.9, respectively. The sediment DOC varied from 50 to 316 mg C kg−1 in the “mixed-fish” ponds and from 61 to 325 mg C kg−1 in the “crab” ponds. Concentra−1 tions of sediment NH+ in the 4 -N ranged from 5.1–35.6 mg kg “mixed-fish” ponds, and from 1.0–6.3 mg N kg−1 in the “crab” ponds. Both pond types maintained high concentrations of NH+ 4 -N in the

Table 3 Annual NEB and SGWP derived from CH4 and N2O emissions in inland ‘mixed-fish’ and ‘crab’ aquaculture ponds. Treatmenta

CH4 (kg C ha−1)

N2O (kg N ha−1)

SGWPb (kg CO2-eq ha−1 y−1)

NEB-scaled SGWPc (kg CO2-eq income y−1)

‘Mixed-fish’ pond ‘Crab’ pond ‘Crab’ pond with aquatic vegetation ‘Crab’ pond without aquatic vegetation

64.4 ± 3.2a 51.6 ± 4.0b 54.3 ± 4.6b 47.7 ± 1.1c

2.99 ± 0.04b 3.32 ± 0.10a 3.34 ± 0.13a 3.28 ± 0.04a

5131.0 ± 248.3a 4506.6 ± 119.7b 4676.3 ± 149.3b 4252.1 ± 75.3c

9.9 ± 1.3b 16.0 ± 2.2a – –

a

Statistically significant differences between different treatments are indicated by different lower-case letters within each column (p b 0.05). SGWP was the sustained-flux global warming potential for use when gas fluxes persist over time and was calculated assuming a sustained gas flux rate of 1 kg m−2 y−1 over the 100 years period. SGWP = 45 × CH4 + 270 × N2O (Neubauer and Megonigal, 2015). c NEB-scaled SGWP=SGWP/income. b

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Table 4 Spearman's correlation coefficients for linear regressions between CH4/N2O fluxes and aquaculture parameters during the waterlogging and pond drainage periods, respectively. Flux (mg m−2 h−1) [n = 63]

Sediment T (°C) [n = 53]

Sediment DOC (mg kg−1) [n = 11]

Water DO (mg L−1) [n = 52]

Sediment pH [n = 52]

− + Sediment NH+ 4 -N (mg Sediment NO3 -N (mg Water NH4 -N (mg kg−1) [n = 11] kg−1) [n = 11] L−1) [n = 24]

Water NO− 3 -N (mg L−1) [n = 24]

‘Mixed-fish’ ponds Waterlogged CH4 N2 O period

0.309⁎⁎ 0.123

0.439⁎ 0.176

−0.813⁎⁎ −0.299⁎

−0.357 −0.148

0.333 0.782⁎

0.194 0.313

0.188 0.435⁎

0.296 0.455⁎

Drainage period

CH4 N2 O

0.560 0.910⁎⁎

0.676⁎ 0.923⁎⁎

– –

−0.635⁎ −0.868⁎⁎

0.297 0.819⁎

0.792⁎ 0.880⁎⁎

– –

– –

‘Crab’ ponds Waterlogged period

CH4 N2 O

0.592⁎⁎ 0.294⁎⁎

0.724⁎⁎ 0.189⁎

−0.426⁎⁎ −0.384⁎

0.078 −0.253⁎⁎

0.751⁎⁎ 0.478⁎⁎

0.079 0.102

0.441 0.311⁎

0.297⁎ 0.087

Drainage period

CH4 N2 O

0.499⁎⁎ 0.814⁎⁎

0.317 0.514⁎⁎

– –

0.084 −0.428⁎⁎

0.546 0.776⁎

0.736 0.852⁎⁎

– –

– –

Pond type

*and ** indicate correlation significant at the 0.05 and 0.01 level, respectively.

water, but the “mixed-fish” ponds were significantly higher than those in the “crab” ponds (p b 0.05). The concentrations of NO− 3 -N in sediment ranged from 0.2–1.7 mg N kg−1 for the “mixed-fish” ponds and from 0.1–0.5 mg kg−1 for the “crab” ponds.

in our study ranged from 0.54–0.73 mg C m−2 h−1: values comparable to those reported from previous aquaculture studies (Hu, 2015; Liu et al., 2016), but generally much less than those recorded in esturarine studies (Song et al., 2017; Lan, 2015; Zhu et al., 2016; Yang et al., 2013, 2015, 2017, 2018) (Table 5).

3.4. Response of greenhouse gases emissions to environmental factors 4.2. N2O emissions and environmental factors Significant positive relationships were detected between CH4 or N2O fluxes and sediment temperature in both “mixed-fish” and “crab” ponds (Table 4). CH4 or N2O fluxes were negatively related to water DO concentrations but positively related to DOC. Emissions of CH4 were not affected by mineral N concentrations in either sediment or pond water, but N2O fluxes were positively related to mineral N. Fluxes of N2O were negatively correlated with pH in both pond types. 4. Discussion 4.1. CH4 emissions and environmental factors In the “mixed-fish” and “crab” ponds, CH4 fluxes were associated with several environmental factors, including sediment temperature, water DO, and sediment DOC concentrations. Our study also idenitified a strong positive correlation between CH4 flux and sediment temperature (Table 4), which suggests that CH4 emissions were driven by the aquaculture pond thermal regime. An increase in temperature may stimulate methanogenesis and therefore increase CH4 emissions (Therien and Morrison, 2005; Kellner et al., 2006; Sun et al., 2013; Treat et al., 2014). This result is also supported by previous studies (Xing et al., 2005) which demonstrated that the diffusive emission rate and transport efficiency of the CH4 flux were influenced by temperature (Stadmark and Leonardson, 2005; Ma et al., 2013; Natchimuthu et al., 2014). Moreover, the fluctuating temperature causes variation in DO concentration, which may also affect CH4 production (Yang et al., 2017). High DO concentration in water promotes CH4 oxidation, while low DO concentrations inhibit CH4 oxidation (Schrier-Uijl et al., 2011; Yang et al., 2015). In this study, the CH4 flux was negatively correlated with DO concentrations (Table 4), indicating that DO may be the key factor driving variations in both CH4 production and emissions in both “mixed-fish” and “crab” ponds. Previous research has linked aquaculture systems high in labile C with high CH4 emissions (Singh et al., 2000; Shang et al., 2011). Similarly, in our study, DOC, a measure of highly labile C in sediments, was positively correlated with CH4 flux. The differences in CH4 emissions between the “mixed-fish” and “crab” ponds were likely caused by differences in the water DO and sediment DOC concentrations. DO concentrations in the “mixed-fish” ponds were significantly lower and DOC concentrations significantly higher than those in the “crab” ponds (p b 0.01). Average CH4 fluxes

The major processes of N2O production are aerobic nitrification and anaerobic denitrification. N2O production generally occurs under conditions of high NO− 3 -N concentration and low oxygen (Garnier et al., 2006; Zhou et al., 2017), which is supported by our results. Our studies showed that N2O emissions were positive correlated to both sediment + NO− 3 -N concentrations (p b 0.01 for both ponds) and sediment NH4 -N concentrations (p b 0.05 for both ponds) in the drainage period from December 2016 to March 2017. We postulate that initially, the draining ponds would have been still quite anerobic, so denitrification of the nitrate present would have rapidly proceeded, liberating N2O at a high rate. Emission of N2O tends to peak at 80% water-filled pore space in soils, not at higher water levels. Therefore, as the ponds dried further, the sediments likely became more aerobic allowing nitrification of sediment ammonium, also liberating N2O but at a less rate. (Murray et al., 2015). The negative correlation between N2O emissions and water DO concentrations (p b 0.05) can be explained as follows: (1) high DO concentrations would weaken denitrification, the dominant process of N2O production; and (2) the process of assimilative NO− 3 -N reduction was influenced by DO concentrations and thus affected N2O emissions during the sampling period (Garnier et al., 2006; Zhou et al., 2017). Consistent with previous reports (Yagi and Minami, 1990; Singh et al., 2000; Liu et al., 2016), greater N2O fluxes were associated with higher sediment DOC, especially during the pond drainage period (Table 4), which is likely because the DOC provides an energy source for the heterotropic bacteria that carry out denitrification and release N2O. In a previous study by Clough et al. (2011), temporal variations in N2O fluxes from two typical aquaculture ponds were affected by pH, which governed the nitrification and denitrification processes in aquatic environments. In our study, we found that N2O emissions were negatively related to pH (Table 4). Reductase activity of N2O may be inhibited under lower pH environment, and N2O production would be promoted (Stow et al., 2005; Clough et al., 2011). The average N2O fluxes during the study year ranged from 30.4–34.8 μg N m−2 h−1 (Table 5), which fall within the range of N2O fluxes reported by previous studies (Song et al., 2017; Lan, 2015; Zhu et al., 2016; Yang et al., 2013, 2015, 2017, 2018; Hu, 2015; Liu et al., 2016). The differences in N2O emissions between the “mixed-fish” and “crab”

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Table 5 Average CH4 (mg C m−2 h−1) and N2O (μg N m−2 h−1) fluxes from aquaculture pond studies in China. Type of aquaculture pond

Location

Sample Dates

Shrimp

Yellow River estuary in Shandong province

Fish

CH4 emission flux

N2O emission flux

Reference

2013.06–2014.04 0.0059

2.7

2014.01–2014.11 0.00042

0.0045

2014.12–2015.2

6.89

Zhu et al., 2016

Mixed

Teaching base of fisheries college of Huazhong Agricultural University Experiment base in Chinese Academy of Fishery Sciences, Shanghai Min River estuary in Fujian province

Song et al., 2017 Lan, 2015

2011.09–2012.01 3.15

16.58

Shrimp

Min River estuary in Fujian province

2011.09–2011.11 19.95

10.74

Mixed

Min River estuary in Fujian province

2012.06–2012.11 1.65

11.8

Drained polyculture

Min River estuary in Fujian province

2011.10–2012.01 7.92

547.12

Undrained polyculture

Min River estuary in Fujian province

2011.10–2012.01 0.84

0.28

Shrimp

Min River estuary in Fujian province

2015.07–2015.10 92.25

10.82

Crab Fish Crab-fish with aquatic vegetation

Xinshe town, Xinghua City Xinshe town, Xinghua City Experimental farm of Nanjing Agricultural University in Xinghua City Experimental farm of Nanjing Agricultural University in Xinghua City Xinzhuang town in Changshu city, Jiangsu Province Xinzhuang town in Changshu city, Jiangsu Province Xinzhuang town in Changshu city, Jiangsu Province

2013.06–2015.06 0.37 2014.06–2015.06 0.48 2013.10–2014.10 0.48

30.66 26.03 46.2

Yang et al., 2013 Yang et al., 2015 Yang et al., 2015 Yang et al., 2018 Yang et al., 2018 Yang et al., 2017 Hu, 2015 Hu, 2015 Liu et al., 2016

2013.10–2014.10 0.21

51.3

Liu et al., 2016

2016.03–2017.03 0.73 2016.03–2017.03 0.61 2016.03–2017.03 0.54

30.4 34.8 34.2

This study This study This study

Megalobrama amblycephala

Crab-fish without aquatic vegetation ‘Mixed-fish’ ‘Crab’ with aquatic vegetation ‘Crab’ without aquatic vegetation

ponds were caused by the differences in mineral N concentrations. Sediment and water mineral N concentrations in the “mixed-fish” ponds were significantly higher than those in the “crab” ponds (p b 0.05). 4.3. N2O emission factors N2O emission factors are important for evaluating the degree of loss of input anthropogenic N as N2O gas. There are few published field measurements of direct N2O emission factors from aquaculture ponds (Hu et al., 2012; IPCC, 2013b). In our study, N2O emission factors for the “mixed-fish” and “crab” ponds were 0.54% and 0.71%, respectively, which is within the range of estimates given by a bench-scale intensive aquaculture system (Yang et al., 2017). However, our emission factors are higher than those reported by Liu et al. (2016), mainly because the present study did not feature a pond-cleaning operation during the culture period. Therefore, surplus nutrients remained in the pond sediment to promote N2O emissions during the post-harvest drainage period. Our results were slightly lower than the IPCC default value of 0.75% (an indirect N2O emission factor, which includes the processes of leaching and runoff N) (IPCC, 2006). 4.4. Effects of aquatic vegetation on CH4 and N2O emissions CH4 emissions were 14% greater from vegetated areas of the “crab” ponds than from the non-vegetated areas (Table 3, p b 0.05), which is similar to results obtained by Liu et al. (2016). One of the potential reasons is that new substrates for methanogenesis are produced in the vegetation which consumes more oxygen thereby increasing CH4 production (Palma-Silva et al., 2013; Wang et al., 2013). Another possible reason is that heterotrophs and nitrifiers deplete oxygen in the water creating an anaerobic environment for CH4 to be transported into the atmosphere through ebullition or molecular diffusion (Bhullar et al., 2014). Plants also serve as a major pathway for CH4 emissions. Dependence of CH4 emissions on plant growth has been well documented in other wetlands (Yan et al., 2005; Ma et al., 2013). N2O emissions tended to be greater from areas with aquatic vegetation than from unvegetated areas, but this effect was not statistically significant (Table 3). During the waterlogging stage, vegetation

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photosynthesis can produce a small amount of NO− 3 and DO, which would increase the proportion of N2O produced by coupled denitrification and nitrification (Ding et al., 2013). Also, the rapid decomposition of planktonic vegetation likely releases more bio-available nutrients which can supply extra substrates for N2O production (Vörös et al., 2003). However, the N2O emitted during the drainage period without aquatic vegetation was much greater. 4.5. Sustained-flux global warming potential (SGWP) and net economic benefit-scaled (NEB-scaled) SGWP from the “mixed-fish” and “crab” ponds To generate a complete accounting of the climatic impact of the “mixed-fish” and “crab” systems under local farming practices, we adopted the sustained-flux global warming potential (SGWP, for gas emissions) for gas fluxes derived from CH4 and N2O emissions calculated on a 100-year timescale (Neubauer and Megonigal, 2015). The GWP of both aquaculture pond types in our study was significantly higher than those reported by Liu et al. (2016), which is largely due to (1) the longer waterlogging period in our study extending the duration of CH4 emissions, and (2) the lack of pond-cleaning in our study. The “mixed-fish” ponds were 13.9% greater in SGWP compared to the “crab” ponds in our study (Table 3). The annual net economic benefit (NEB), estimated by deducting the total cost from the economic income from the two pond types, were 50,625 CNY ha−1 y−1 for the “mixedfish” ponds and 72,000 CNY ha−1 y−1 for the “crab” ponds. The NEBscaled SGWP, calculated by linking the SGWP to NEB, was 61.6% greater in the “mixed-fish” ponds than in the “crab” ponds (Table 3). The results of this study suggest that GWP and net ecosystem economic profits should also be considered when evaluating GHG profiles from aquaculture ponds. 5. Conclusions Inland “mixed-fish” and “crab” aquaculture ponds in China contribute significantly to regional and national GHG budgets due to their high CH4 and N2O emissions. The “mixed-fish” and “crab” ponds were strong CH4 and weak N2O emitters during the culture period and weak CH4 and strong N2O emitters during the post-harvest drainage period. GHG

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fluxes were regulated by sediment temperature, sediment pH, sediment DOC, sediment mineral N and water DO in the aquaculture ponds. The GWP contribution from different aquaculture ponds should be considered when calculating GHG emissions profiles for the Chinese aquaculture industry. Further field research in aquaculture ponds is needed to better evaluate the range in GHG fluxes possible under varying climatic conditions and management pratices. Acknowledgments This work was supported by the National Natural Science Foundation of China (grant numbers NSFC 41601233, 41501245), the Natural Science Foundation of Jiangsu Province (grant numbers BK20140990, BK20140988) and the Open Project of State Key Laboratory of Soil and Sustainable Agriculture (grant numbers Y20160034). We would like to thank the Changshu agro-ecological experimental station for its support in sample collection and analysis. References Aufdenkampe, A., Mayorga, E., Raymond, P.A., Melack, J.M., Doney, S.C., Alin, S.R., Aalto, R. E., Yoo, K., 2011. Riverine coupling of biogeochemical cycles between land, oceans, and atmosphere. Front. Ecol. Environ. 9, 307–358. Bhullar, G.S., Edwards, P.J., Venterink, H.O., 2014. Influence of different plant species on methane emissions from soil in a restored Swiss wetland. PLoS One 9, e89588. Cao, L., Wang, W.M., Yang, Y., Yang, C.T., Yuan, Z.H., Xiong, S.B., Diana, J., 2007. Environmental impact of aquaculture and countermeasures to aquaculture pollution in China. Environ. Sci. Pollut. Res. 14, 452–462. Cao, L., Diana, J.S., Keoleian, G.A., Lai, Q.M., 2011. Life cycle assessment of Chinese shrimp farming systems targeted for export and domestic sales. Environ. Sci. Technol. 45, 6531–6538. Clough, T.J., Buckthought, L.E., Casciotti, K.L., Kelliher, F.M., Jond, P.K., 2011. Nitrous oxide dynamics in a braided river system, New Zealand. J. Environ. Qual. 40, 1532–1541. Diem, T., Koch, S., Schwarzenbach, S., Wehrli, B., Schubert, C.J., 2012. Greenhouse gas emissions (CO2, CH4 and N2O) from several perialpine and alpine hydropower reservoirs by diffusion and loss in turbines. Aquat. Sci. 74, 619–635. Ding, W., Zhu, R.B., Ma, D.W., Xu, H., 2013. Summertime fluxes of N2O, CH4 and CO2 from the littoral zone of Lake Daming. East Antarctica effects of environmental conditions. Antarct. Sci. 25, 752–762. Garnier, J., Cévron, A., Tallec, G., Billen, G., Sebilo, M., Marrtinea, A., 2006. Nitrogen behaviour and nitrous oxide emission in the tidal Seine River Estuary (France) as influenced by human activities in the upstream watershed. Biogeochemistry 77, 305–326. Hu, Z.Q., 2015. A Comparison of Methane and Nitrous Oxide Emissions between Paddy Fields and Crab-Fish Farming Wetlands in Southeast China. Nanjing Agriculture University (Doctoral degree dissertation). Huttunen, J.T., Alm, J., Liikanen, A., Juutinen, S., Larmola, T., Hammar, T., Silvola, J., Martikainen, P.J., 2003. Fluxes of methane, carbon dioxide and nitrous oxide in boreal lakes and potential anthropogenic effects on the aquatic greenhouse gas emissions. Chemosphere 52, 609–621. Intergovernmental Panel on Climate Change (IPCC), 2006. IPCC Guidelines for National Greenhouse Gas Inventories, National Greenhouse Gas Inventories Programme; IPCC/IGES. Kanagawa, Japan. Intergovernmental Panel on Climate Change (IPCC), 2013a. The Physical Science Basis, Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge. Intergovernmental Panel on Climate Change (IPCC), 2013b. In: Hiraishi, T., Krug, T., et al. (Eds.), Supplement to the 2006 IPCC Guidelines of National Greenhouse Gas Inventories: Wetlands. IPCC, Switzerland, p. 2014. Kellner, E., Baird, A.J., Oosterwoud, M., Harrison, K., Waddington, J.M., 2006. Effect of temperature and atmospheric pressure on methane (CH4) ebullition from near-surface peats. Geophy. Res. Lett. 33, L18405. Lan, J., 2015. Greenhouse Gases Concentration, Emission and Influence Factors in Farming Waters. Huazhong Agricultural University (Master's degree dissertation). Hu, Z., Lee, J.W., Chandran, K., Kim, S., 2012. Nitrous oxide (N2O) emission from aquaculture: a review. Environ. Sci. Technol. 46, 6470–6480. Liu, S.W., Hu, Z.Q., Wu, S., 2016. Methane and nitrous oxide emissions reduced following conversion of rice paddies to inland crab-fish aquaculture in Southeast China. Environ. Sci. Technol. 50, 633–642. Ma, Y.C., Kong, X.W., Yang, B., Zhang, X.L., Yan, X.Y., Yang, J.C., Xiong, Z.Q., 2013. Net global warming potential and greenhouse gas intensity of annual rice-wheat rotations with integrated soil-crop system management. Agric. Ecosys. Environ. 164, 209–219. Muralidhar, M., Vasanth, M., Chitra, V., Thulasi, D., Kathyayani, S., Jannathulla, R., 2017. Agriculture under Climate Change: Threats, Strategies and Policies. Section-II: Greenhouse Gases Emission and Mitigation from Brackish Water Aquaculture Systems. (Eds.: Belavadi, N., Nataraja Karaba, N., Gangadharappa, N.R.). Applied Publishers Pty. Ltd., pp. 269.

523

Murray, R.H., Erler, D.V., Eyre, B.D., 2015. Nitrous oxide fluxes in estuarine environments: response to global change. Glob. Chang. Biol. 21, 3219–3245. Natchimuthu, S., Selvam, B.P., Bastviken, D., 2014. Influence of weather variables on methane and carbon dioxide flux from a shallow pond. Biogeochem. 100, 21–37. Neubauer, S.C., Megonigal, J.P., 2015. Moving beyond global warming potentials to quantify the climatic role of ecosystems. Ecosystems 18, 1000–1013. Palma-Silva, C., Marinho, C.C., Albertoni, F.E., Giacomini, I.B., Barros, M.P.F., Furlanetto, L. M., Trindade, C.R.T., DE Assis Esteves, F., 2013. Methane emissions in two small shallow neotropical lakes: the role of temperature and trophic level. Atmos. Environ. 81, 373–379. Schrier-Uijl, A.P., Veraatr, A.J., Leffelaar, P.A., Berendse, F., Veenendaal, E.M., 2011. Release of CO2 and CH4 from inland waters in India - implications for large scale greenhouse gas balances. Glob. Change biol. Ecol. 402, 65–74. Serrano-Grijalva, L., Sánchez-Carrillo, S., Angeler, D.G., Sánchez-Andrés, R., ÁlvareaCobelas, M., 2011. Effects of shrimp-farm effluents on the food web structure in subtropical coastal lagoons. J. Exp. Mar. Biol. Ecol. 402, 65–74. Shang, Q.Y., Yang, X.X., Gao, C.M., Wu, P.P., Liu, J.J., Xu, Y.C., Shen, Q.R., Zou, J.W., Guo, S.W., 2011. Net annual global warming potential and greenhouse gas intensity in Chinese double rice-cropping systems: 3-year field measurement in long-term fertilizer experiments. Glob. Chang. Biol. 17, 2196–2210. Singh, S.N., Kulshreshtha, K., Agnihotri, S., 2000. Seasonal dynamics of methane emission from wetlands. Chemosphere Global Chang. Sci. 2, 39–46. Song, H.L., Liu, X.T., Wen, B.L., 2017. Greenhouse gases fluxes at water-air interface of aquaculture ponds in the Yellow River estuary. Ecol. Environ. Sci. 26, 1554–1561. Stadmark, J., Leonardson, L., 2005. Emissions of greenhouse gases from ponds constructed for nitrogen removal. Ecol. Eng. 25, 542–551. Stow, C.A., Walker, J.T., Cardoch, L., Spence, P., Geron, C., 2005. N2O emissions from streams in the Neuse River watershed, North Carolina. Environ. Sci. Technol. 39, 6999–7004. Sun, Z.G., Jiang, H.H., Wang, L.L., Mou, X.J., Sun, W.L., 2013. Seasonal and spatial variations of methane emissions from coastal marshes in the northern Yellow River estuary, China. Plant Soil 369, 317–333. Therien, N., Morrison, K., 2005. Production of GHG from the decomposition of in vitro inundated phytomass and soil. In: Tremalay, A., Varfalvy, L., Roehm, C., Garneau, M. (Eds.), Greenhouse Gases Emissions-Fluxes and Processes: Hydro-Electric Reservoirs and Natural Environments. Springer, New York, pp. 315–338. Treat, C.C., Wollheim, W.M., Varner, R.K., Grandy, A.S., Talbot, J., Frolking, S., 2014. Temperature and peat type control CO2 and CH4 production in Alaskan permafrost peats. Glob. Change Biol. 20, 2674–2686. Vörös, L., Balogh, K.V., Koncz, E., Kovacs, A., 2003. Phytoplankton and bacterioplankton production in a reed-covered water body. Aquat. Bot. 77, 99–110. Wang, Y.H., Yang, H., Ye, C., Chen, X., Xie, B.H., 2013. Effects of plant species on soil microbial processes and CH4 emission from constructed wetlands. Environ. Pollut. 174, 273–278. Williams, J., Crutzen, P.J., Jickeels, T., 2010. Nitrous oxide and methane fluxes vs. carbon, nitrogen and phosphorous burial in new intertidal and saltmarsh sediments. Sci. Tot. Environ. 518–519, 16–23. World Meteorlogical Organization, 2016. WMO Greenhouse Gas Bulletin No.12 (October 2016). http://library.wmo.int/opac/doc_num.php?explnum_id=3084.pdf. Xiao, X., Agusti, S., Lin, F., Li, K., Pan, Y.R., Zheng, Y.Y., Wu, J.P., Duarte, C.M., 2017. Nutrient Removal from Chinese Coastal Waters by Large-Scale Seaweed Aquaculture. https:// doi.org/10.1038/srep46613. Xing, Y.P., Xie, P., Yang, H., Yang, H., Ni, L.Y., Wang, Y.S., Kewen, R., 2005. Methane and carbon dioxide fluxes from a shallow hypereutrophic subtropical lake in China. Atmos. Environ. 39, 5532–5540. Yagi, K., Minami, K., 1990. Effect of organic matter application on methane emission from some Japanese rice fields. Soil Sci. Plant Nutr. 36, 599–610. Yan, X.Y., Akiyama, H., Yagi, K., 2005. Global estimations of the inventory and mitigation potential of methane emissions from rice cultivation conducted using the 2006 intergovernmental panel on climate change guidelines. Glob. Biogeochem. Cycles 23 (GB2002). https://doi.org/10.1029/2008GB3299. Yang, P., Tong, C., He, Q.H., Huang, J.F., 2013. Greenhouse gas fluxes at water-air interface of aquaculture ponds and influencing factors in the Min River estuary. Acta Sci. Circumst. 33, 1493–1503. Yang, P., He, Q.H., Huang, J.F., Tong, C., 2015. Fluxes of greenhouse gases at two different aquaculture ponds in the coastal zone of southeastern China. Atmos. Environ. 115, 269–277. Yang, P., Bastviken, D., Jin, B.S., Mou, X.J., Tong, C., Yao, Y.C., 2017. Effects of coastal marsh conversion to shrimp aquaculture ponds on CH4 and N2O emissions. Estuar. Coast. Shelf Sci. 199, 125–131. Yang, P., Lai, D.Y.F., Huang, J.F., Tong, C., 2018. Effect of drainage on CO2, CH4, and N2O fluxes from aquaculture ponds during winter in a subtropical estuary of China. J. Environ. Sci. 65, 72–82. Zhang, Y., Bleeker, A., Liu, J.G., 2015. Nutrient discharge from China's aquaculture industry and associated environmental impact. Environ. Res. Lett. 10, 045002. https://doi.org/ 10.1088/1748-9326/10/4/045002. Zhou, W., Xia, L.L., Yan, X.Y., 2017. Vertical distribution of denitrification end-products in paddy soils. Sci. Total. Environ. 576, 462–471. Zhu, L., Che, X., Liu, H., Liu, X.G., Shi, X., Yang, J.P., Wang, X.D., Gu, Z.J., Cheng, G.F., Zhu, H., 2016. Greenhouse gases emissions of Megalobrama amblycephala culture pond ecosystems during sun drying of pond. Trans. Chin. Soc. Agric. Eng. 32, 210–215.