Coupled steel slag and biochar amendment correlated with higher methanotrophic abundance and lower CH4 emission in subtropical paddies

Aerobic methanotrophs in paddies serve as methane (CH4) filters and thereby reduce CH4 emissions. Amending soil with waste products can mitigate CH4 emissions in crops, but little is known about the impacts of amendments with steel slag and biochar on the populations and activities of aerobic methanotrophs in rice cropland. We used real-time quantitative PCR detecting system and high-throughput sequencing to determine the effects of slag and biochar amendments on CH4 emission, abundance, and community structure of methanotrophs, and the relationships between soil properties and the abundance and community composition of methanotrophs during the rice growing season in both early and late paddies. Soil salinity and pH were significantly higher for an amendment with both slag and biochar than the control in both the early and late paddies, and pH was significantly higher for a slag amendment in the late paddy. Cumulative CH4 emission was lower for the slag and slag + biochar amendments than the control in early paddy by—34.1%. Methanotrophic abundance was three- and sixfold higher for the slag + biochar amendment than the control in the early and late paddies (p < 0.05), respectively. The abundance of different groups of methanotrophs varied among the treatments. The relative abundance of Methylosarcina was higher for the slag amendment than the control, and the relative abundance of Methylomonas was lower for biochar, and slag + biochar amendments than the control. The relative abundance of Methylocystis was higher for the slag and slag + biochar amendments than the control in the early paddy, and the relative abundance of Methylocystis was higher for the slag, biochar, and slag + biochar amendments in the late paddy. Univariate and multivariate analyses indicated that the higher abundance of methanotrophic bacteria for the slag and slag + biochar amendments was correlated with soil pH, salinity, soil organic carbon, and C/N ratio, and the relative abundances of Methylocystis, Methylomonas, and Methylosarcina were associated with the effective mitigation of CH4 emission in the paddies. A discriminant general analysis indicated that the total population of methanotrophs was larger for the slag + biochar amendment than the control, and that this effect was only weakly correlated with changes in the soil properties, demonstrating that this effect on the size and species composition of methanotrophic soil populations was mostly associated with a direct effect of the slag + biochar amendment.


Introduction
Methane is the second most important greenhouse gas after carbon dioxide, contributing approximately 18% of anthropogenic radiative forcing (Bridgham et al. 2013).Even small changes of CH4 concentrations in the atmosphere contribute substantially to global warming, because the global-warming potential of CH4 is 25fold higher than that of CO2 (Bridgham et al. 2013;Lee et al. 2014).CH4 is an important greenhouse gas due to its geophysical properties, such as its atmospheric residence time of 12.4 years and instantaneous forcing of 1.37×10 5 W m -2 ppb -1 (IPCC 2014).Rice paddy fields, which are cultivated worldwide on 155 million ha, contribute about 5-19% of the annual atmospheric CH4 emissions and are considered the most important anthropogenic source of CH4 (Ma et al. 2010).
CH4 emission from paddies are governed primarily by two microbial processes, CH4 production (by methanogens) and CH4 oxidation (by methanotrophs) (Wang et al. 2014;Nguyen et al. 2015).Methanogens are a group of strict anaerobic microorganisms that produce CH4 using CO2 or acetate as the final electron acceptor and hydrogen as an electron donor and are phylogenetically affiliated with the phylum Euryarchaeota of the domain Archaea (Woese et al. 1990).Methanotrophs, though, use CH4 as the main carbon source and can metabolize both aerobically and anaerobically.Aerobic methanotrophs belong to the Proteobacteria and Verrucomicrobia taxa.The former can be broadly divided into two physiological and phylogenetic groups: type I (Gammaproteobacteria) and type II (Alphaproteobacteria) methanotrophs (Sharp et al.2014).Some practices of agricultural management (e.g.water management and addition of straw compost) have been recommended for reducing CH4 emissions from paddies (Pandey et al 2014;Wang et al. 2014;Nguyen et al. 2015).Biochar amendment may reduce CH4 emissions mostly by inhibiting methanogenic activity or increasing CH4 oxidation associated with an increase in soil aeration (Liu et al. 2011;Dong et al. 2013;Han et al. 2016).Increasing the abundance of methanotrophs or decreasing the mcrA/pmoA ratio can also reduce CH4 emissions (Feng et al. 2012;Han et al. 2016).
The application of biochar may therefore decrease CH4 emissions, and the structure of biochar can provide a suitable environment for bacterial CH4 oxidation, but little attention has been paid to the influence of biochar amendments on methanotrophic diversity in paddies.
Steel slag is a waste product from the pyro-metallurgical processing of various ores.
Interest in finding uses for slag has been steadily increasing, because large volumes, on the order of hundreds of millions of tonnes, of this waste are produced annually worldwide (Piatak et al. 2015).Steel slag contains high concentrations of electron acceptors, such as active and free oxides of iron, and can effectively lower CH4 emissions from temperate paddies (Ali et al. 2008a(Ali et al. , 2009)).The steel slag should increase the soil redox status, and thus we should expect effects on methane production and oxidation processes (Wang et al. 2018).The addition of steel slag and/or biochar to soil could influence CH4 emissions by affecting the physicochemical properties of the soil and thus the microorganisms that emit and metabolize CH4 (Ali et al. 2008b;Wang et al. 2015).However, these effects remain largely unknown By using molecular approaches such as polymerase chain reactions (PCRs) targeting methane monooxygenase (pMMO) genes (Lau et al. 2013;Lima et al., 2014;Lüke et al. 2014;Yun et al. 2015) we aimed to : (1) determine the abundance and community structures of methanotrophs and the relationships between soil properties and the abundance and community composition of methanotrophs during the growing season in both early and late paddies, and ( 2) analyze the relationship between methanotrophs and CH4 emission.The results from this study may provide insights into the effects of waste amendments on soil methanotrophic communities and the subsequent effects on CH4 emissions.In-depth knowledge of these relationships should be particularly important for providing a theoretical and practical basis to control CH4 emissions in paddies.

Study site and experimental design
The field experiment was carried out in the Wufeng Agronomy field of the Fujian Academy of Agricultural Sciences, Fujian, southeastern China (Fig. 1).We studied the effect of the application of steel slag, biochar, and slag + biochar on CH4 emissions and methanotrophs during the early paddy season (16 April to 16 July, Hesheng 10 cultivar) and the late paddy season (25 July to 6 November, Qinxiangyou 212 cultivar) in 2015.
Air temperature and humidity during the study period are shown in Fig. S1.Our study site has a "Warm and humid climate" according with Köppen (1936) classification.The physicochemical properties in the top 15 cm were shown in Wang et al. (2014Wang et al. ( , 2015)).
The management of the paddies (including plowing, water management, and fertilization) was typical for subtropical paddies in China (Zhang et al. 2013;Wang et al. 2015), more detail was shown in the Wang et al. (2015).
The experimental field plots were laid out in a randomized block design, with triplicate plots (10 m 2 ) for each of the four treatments (including a control).The experiment tested the following treatments in a completely randomized block design: 1) control; 2) steel slag; 3) biochar; and 4) slag + biochar.We applied 8 Mg ha -1 of both steel slag and biochar.The selected steel slag was provided in granular form by Fujian Jinxing iron company and was composed mainly of CaO (34.9%),SiO2 (40.7%), and Fe2O3 (4.8%).This represents C (56.6%), N (1.4%),P (1.0%) and K (1.8%) on dry weight.Rice straw was heated at 600 °C to produce biochar.The chemical compositions of both amendments are presented in Table S1.All control and amended plots received the same amount of water and same mineral fertilizer and urea.More detail seen in Wang et al. (2015).

Measurement of CH4 flux
Static closed chambers were used to measure CH4 emissions during the rice growing season (Datta et al. 2013).More detail seen the Wang et al. (2015).We deployed three replicate chambers in each treatment.A wooden boardwalk was built for accessing the plots to minimize disturbance of the soil during gas sampling.Gas flux was measured weekly in all chambers.The sampling CH4 concentrations in the headspace air samples were determined by gas chromatography (GC) using a stainless steel Porapak Q column (2 m long, 4 mm outside diameter, 80/100 mesh) (Shimadzu GC-2010, Kyoto, Japan).
More detail of the gas sampling and concentrations determination were shown in Wang et al. (2015).

Measurement of soil properties
Soil samples were collected from the 0-15 cm layer in triplicate for each treatment using a soil sampler during the elongation stage (Wang et al. 2014;Wang et al. 2018).We only collected one time in the elongation period, i.e. at mid period of rice growth, when the water and fertilizer management was also at the average level between the beginning of the rice transplantation and the rice ripening period.This sampling time was the sampling time also used in previous studies (Wang et al. 2018).The samples were immediately stored in sterile bags in ice coolers and transported to the laboratory.Subsamples were then immediately processed for DNA extraction.The remaining soil was stored at 4 °C until the analysis of physical and chemical properties.
Soil properties, such as pH was measured with a pH/temperature meter (IQ Scientific Instruments, Carlsbad, USA), and salinity was measured using a 2265FS EC meter (Spectrum Technologies Inc., Paxinos, USA).Soil water content was measured by weighing the soil before and after drying at 105 °C to a constant weight (Barton et al. 2013).Soil organic carbon (SOC) and TN concentrations were determined using a Vario Max Elemental Analyzer (Elementar Scientific Instruments, Hanau, Germany).

DNA extraction and PCR amplification
When we determined the amount of DNA we use three repeats per plot.However, when we determined the microbe structure we only used the mixed into 0.5-g composite samples per plot, thus following the method applied in several previous studies (Wang et al. 2018).Total genomic DNA was extracted from these samples using an E.Z.N.A TM Soil DNA Kit (Omega, USA).The DNA quality and concentration were assessed by 1× TAE agarose gel (1%) electrophoresis and spectrophotometric analysis using a NanoDrop 1000 spectrophotometer (Thermo Scientific Technologies Inc., Waltham, USA).
The pmoA genes of methanotrophs were amplified by PCR using the primer pair A189F (5′-GGN GAC TGG GAC TTC TGG-3′) and mb661R (5′-CCG GMG CAA CGT CYT TAC C-3′) (May et al. 2018).Amplification was performed in a final volume of 25 μL containing 2.5 μL of 10× PCR buffer, 2.5 μL of 2.5 mM dNTPs, 0.25 μL of Taq polymerase (5 U μL -1 ) (Takara, Japan), 0.5 μL of each primer (final concentration 0.3 μM), and 20 ng of extracted DNA.The PCR program had an initial denaturation at 94 °C for 3 min followed by 30 cycles of denaturation at 94 °C for 45 s, annealing at 55 °C for 1 min, and extension at 72 °C for 90 s, with a final extension at 72 °C for 10 min.Amplified PCR products were purified with a PCR clean-up kit (Sangon Inc., Shanghai, China) and stored at -20 °C for further analysis.

MiSeq Sequence processing and analysis
All PCR products were sequenced by Novogene Corporation, Beijing, China.

Statistical analysis
The sequencing data were processed as described by Caporaso et al. (2010) and Wang et al. (2017).A one-way analysis of variance (ANOVA) was conducted to test the differences in soil physicochemical properties and methanotrophic abundances among the treatments in both crop seasons.All statistical analyses used SPSS Statistics 17.0 (IBM SPSS Inc., Chicago, USA).
We also performed multivariate statistical analyses.We used a principal component analysis (PCA) to determine the overall differences of soil salinity, pH, water content, TN content, C:N ratio, SOC content, bulk density, CH4 emission, and methanotrophic gene abundance among treatments in the early and in late paddies.We conducted one-way ANOVAs with Bonferroni post hoc tests of the scores of the first PC axis to determine differences among the treatments.We then used a general discriminant analysis (GDA) to determine the overall differences of soil salinity, pH, water content, TN content, C:N ratio, SOC content, bulk density, CH4 emission, and methanotrophic gene abundance among treatments using the combined data from the two paddy seasons.These analyses also assessed the component of the variance due to the paddy season (early and late) as an independent categorical variable.Discriminant analyses consist of a supervised statistical algorithm that derives an optimal separation between groups established a priori by maximizing between-group variance while minimizing within-group variance (Raamsdonk et al. 2001).GDA is thus an appropriate tool for identifying the variables most responsible for the differences among groups while controlling the component of the variance due to other categorical variables, the two paddy seasons (early and late) in this study.The GDAs were performed using Statistica 8.0 (StatSoft, Inc., Tulsa, USA).

Soil physicochemical properties in the paddies
The soil physicochemical properties for the treatments and paddy fields are shown in Table 1.Soil salinity and pH were significantly higher (p<0.05) in the slag + biochar treatment than the control in both the early and late paddies, and pH was significantly higher (p<0.05) in the slag treatment than the control in the late paddy.

Cumulative CH4 emission in paddies
Total cumulative CH4 emission varied among the treatments in both the early and late paddies (Fig. 2).Cumulative CH4 emission was lower in the slag and slag + biochar amendments than the control in both the early and late paddies, by 10.2 and 34.1% and 14.9 and 33.5%, respectively.Cumulative CH4 emission for the biochar treatment, however, was 7.6% higher in the early paddy field but 43.7% lower in late paddy relative to the control.

Methanotrophic abundance in the paddies
Methanotrophic pmoA copy number for both the early and late paddies were shown in Fig. 3. Methanotrophic pmoA abundance in the control, slag, biochar, and slag + biochar treatments in the early paddies were 2.84×10 5 , 1.35×10 5 , 2.50×10 5 and 1.44×10 6 g -1 dry soil, respectively.The pmoA copy number was 52.5 and 12.1% lower in the slag and biochar treatments, respectively, but about three-fold higher in the slag + biochar treatment, than the control.The copy number was significantly higher (p<0.05) in the slag + biochar treatment than the control.The pmoA copy numbers in the late paddy field were 1.32×10 5 , 5.63×10 4 , 1.91×10 5 , and 9.88×10 5 g -1 dry soil in the control, slag, biochar, and slag + biochar treatments, respectively.The copy number was 57.6% lower in the slag treatment but 43.5% and six-fold higher in the biochar and slag + biochar treatments, respectively, than the control.The pmoA copy number was significantly higher (p<0.05) in the slag + biochar treatment than the control in both the early and late paddies.The copy number was also significantly higher (p<0.05) in the early than the late paddy for the control and slag treatments.

Relationships between methanotrophic abundance and environmental factors
The relationships between the abundance of methanotrophs and environmental factors in both the early and late paddies were shown in Table 3.The pmoA copy numbers in both the early and late paddies were strongly positively correlated with soil salinity, pH and, SOC content (Table 3).But CH4 emission was not strongly correlated the soil parameters, indicating that CH4 emissions were not directly affected by the physicochemical parameters(Table 3).

Analysis of alpha and beta diversity of pmoA in the paddies
The microbial communities in the paddies were analyzed based on pmoA gene sequences using high-throughput sequencing.The number of sequences, coverage, number of OTUs, and ecological indices are summarized in Table 2.More than 98% coverage was obtained for all samples, with the number of OTUs ranging from 612 to 2537.The heatmap in Fig. 4 shows the abundance cluster of the top 50 ranking species of methanotrophs.The number of unclassified bacterial genera in the paddies ranged from 1.63 to 62.97%.Most methanotrophic species in the paddies belonged to Methylocystis, Methylogaea, and Methylococcus, representing 17.26-79.35% of the total.

Methanotrophic community composition in the paddies
High-throughput sequencing of pmoA was used to investigate changes in the composition of the methanotrophic communities in both the early and late paddies (Fig. 5).Approximately 24.40-53.36% of the Proteobacteria sequencing reads for both the early and late paddies were classified as type I methanotrophs, including PCA and GDA of CH4 emission, methanotrophs, and physicochemical parameters The PCA (both in early and in late paddy) found that the amendments containing slag (alone or particularly with biochar) were associated with larger methanotrophic populations and with higher soil pH, salinity, and TN and SOC contents and lower CH4 emissions (Fig. 6, 7).The GDA supported these results.We must, however, stress that all treatments were significantly separated (Table S2) and that overall soil traits, CH4 emissions, and methanotrophic abundance differed the most in the slag + biochar treatment (Fig. 8).The GDA found that methanotrophic abundance and soil pH to some extent were most responsible for these differences among the treatments (Table S3).

Discussion
Understanding the ecology of methanotrophs and their abundance and taxonomic composition under different waste amendments is crucial for controlling CH4 emissions in paddies.Our results provided clear evidence that amendments with slag and slag + biochar decreased CH4 emissions in both the early and late paddies, an effect correlated with the increase in the methanotrophic abundance, specially for the relative abundances of Methylocystis, Methylomonas, and Methylosarcina that were associated with the effective mitigation of CH4 emission in the paddies.The various treatments, however, were associated with different soil properties.The effect of the treatments was especially important in changing methanotrophic abundance and community composition, evidence that the change of methanotrophic abundance and community composition was due mainly to the components of the treatments, mainly slag.

Effects of slag amendment on the abundance and community structure of methanotrophs
The application of slag inhibited total CH4 emissions from the paddy fields, consistent with previous reports by Singla et al. (2015) and Wang et al. (2015).The slag amendments in our study slightly increased soil salinity, because slag usually contains a specific suite of salt components (K, Ca, Mg, and Fe) that are important for soil fertility (Ali et al. 2008b).Slag contains large amounts of chemically reactive iron oxide, which increases soil salinity (Ali et al. 2008b).Our results, though, also strongly suggest that the slag amendments increased soil pH, as also reported by Lee et al. (2012), due to the calcium and iron contents in the slag (Susilawati et al. 2015).Methanotrophic abundance, however, was not higher in the slag amendments than the control, perhaps because slag contains iron that can reduce CH4 emissions.High levels of electron acceptors suppress CH4 emission (Susilawati et al. 2015).The higher soil salinity and pH due to amendment with slag may not decrease CH4 emissions by increasing the abundance of methanotrophs, but by changing the community composition or structure or the abundance of methanogens.
Slag amendment increased the relative abundance of Methylosarcina compared with the control (Fig. 5).Methylosarcina is a type I methanotroph dominant in paddies (Lee et al. 2014).The growth of Methylosarcina requires a pH of 5.0-9.0 (Wise et al., 2001), so slag amendments with near-neutral pHs (6.90-6.99)may increase the relative abundance of Methylosarcina by increasing soil pH.Furthermore, iron is an important element for methanotrophs (Mohanty et al., 2014), because methane monooxygenase, a di-iron protein complex, uses iron as a transition metal (co-factor) at the active site (Guallar et al. 2002), so slag containing iron oxide may inhibit CH4 emissions by increasing soil pH and thereby increasing the relative abundance of Methylosarcina.The iron in slag fertilizers may also act as an electron acceptor, suppressing CH4 emission by decreasing methanogenic activity (Jackel et al. 2000).

Effects of biochar amendment on CH4 emission associated with changes of the abundance and community structure of methanotrophs
The biochar amendment decreased the total CH4 emission, but without increasing methanotrophic abundance, during the entire study period compared to the control, highly consistent with previous studies (Castaldi et al. 2011;Zhang et al. 2012).Biochar application can reduce CH4 emissions (Feng et al. 2012;Wang et al. 2012) and has increased rice yield up to 28% (Zhang et al. 2010(Zhang et al. , 2012;;Wang et al. 2012) by increasing methanotrophic abundance, which would decrease CH4 emission (Zhang et al. 2010).
The impact of biochar on CH4 emission may be due to the biochar components and the influence of biochar on soil physicochemical properties.The SOC content and the C:N ratio were higher in the biochar and slag + biochar treatments than the control.The highly aromatic chemical structure of biochar provides an organic carbon with higher biochemical activity and thermal stability, allowing the biochar to be preserved in the environment for a long time.The addition of biochar to soil may therefore improve soil stability.The reduced CH4 emissions from paddies with added biochar are likely due to a lack of substrate (CO2) availability (Liu et al. 2011;Chang et al. 2012).Kim et al. (2017) reported that biochar inhibited methanogenesis by increasing soil aeration and oxygen availability.The slightly higher pHs due to the alkaline properties of biochar, though, may contribute to the inhibition of CH4 emissions by changing methanotrophic community structure.The abundance of Methylomonas was lower in the slag, biochar, and slag + biochar treatments than the control.The growth of Methylomonas requires a pH of 5.0-9.0 and is optimal at pHs of 6.5-7.0 (Lu et al. 2016).Amendments with slag, biochar, or slag + biochar with higher pHs (6.46-7.41)may thus not be suitable for the growth and proliferation of this group.Members of the genus Methylomonas require higher oxygen and CH4 concentrations for CH4 oxidation than other methanotrophs (Reim et al. 2012).A reduction in the relative abundance of Methylomonas by altering soil pH may thus be a mechanism to suppress CH4 emission under waste amendments.Wang et al. (2012), however, found that CH4 emission in paddy fields increased significantly when amended with biochar.The addition of biochar in flooded paddies increases the substrate supply and creates a favorable environment for methanogenic activity (Kögel-Knabner et al. 2010;Lehmann et al. 2011).The labile components of biochar can decompose and become the predominant source of substrates for methanogens, particularly in the early stages of the rice growing season (Knoblauch et al. 2008).The effects of biochar amendment on CH4 emission are thus inconsistent among studies, and the underlying mechanisms may vary with soil type, agricultural management, and origin of the biochar (Lehmann et al. 2011).

Effects of the slag + biochar amendment on CH4 emission associated with changes of methanotrophic abundance and community structure
Our study demonstrated that the three amended treatments lowered total CH4 emissions to different extents relative to the control treatment.Slag + biochar was the best amendment for suppressing total CH4 emissions in early paddy field.Methanotrophic abundance was significantly higher in the slag + biochar treatment than the control, biochar, and slag treatments, likely because biochar can improve soil permeability and the granular texture of slag can further enhance the ability of soil to supply oxygen.
Slag and biochar contain K, Ca, Mg, and Fe, which strongly increase CH4 oxidation, which would increase the abundance of methanotrophs in the slag + biochar treatment.
CH4 emission was inversely correlated with the abundance of methanotrophs, so the increase in methanotrophic abundance would likely decrease in CH4 emissions under the slag + biochar treatment.The relative abundance of Methylocystis in the early paddy was higher in the slag and slag + biochar treatments than the control, especially in the slag + biochar treatment where the abundance was about 183% higher.The three amended treatments increased the relative abundance of methanotrophs in the late paddy.Methylocystis can form resting cells, surviving on multi-carbon compounds and using CH4 at both high and low concentrations (Ho et al. 2013).Some type II methanotrophs (Methylocella, Methylocapsa, and Methylocystis) have recently been characterized as facultative methanotrophs able to conserve energy for growth on multicarbon compounds such as acetates, pyruvate, succinate, malate, and ethanol (Esson et al. 2016).The slag + biochar treatment in our study also decreased the relative abundance of Methylomonas.Bacterial diversity may be affected by SOC and N contents (Chan et al. 2006).We also found that the community composition of methanotrophs was significantly correlated with SOC content and the C:N ratio (Fig. 6), suggesting that the combination of slag and biochar, with its high SOC content, may provide a rich substrate for CH4 synthesis, which would further change methanotrophic community structure.Methylocystis has a low minimum threshold concentration (Michaelis constant, Km) for CH4 oxidation (Lee et al. 2014).A lower Km is associated with a higher affinity of enzymes and substrates and stronger CH4 oxidation.Increasing the abundance of CH4-oxidizing bacteria would likely have a critical impact on CH4 reduction (Kima et al. 2017).Increasing the relative abundance of Methylocystis may therefore reduce CH4 emission.In conclusion, the slag + biochar treatment likely increased the oxygen content of the soil, which would increase the oxidation of CH4 by methanotrophs, leading to lower CH4 emissions.

Conclusions and final remarks
Our results indicated that soil amendment with both slag and biochar significantly increased soil salinity and pH in both the early and late paddies and that amendment with slag significantly increased pH in the late paddy.The slag and slag + biochar treatments decreased the cumulative CH4 emission compared to the control in both the early and late paddies, by 10.2 and 34.1% and 14.9 and 33.5%, respectively.The abundance of methanotrophs in the slag + biochar treatment significantly increased methanotrophic abundance about three-and six-fold in the early and late paddies (p<0.05),respectively.The slag treatment increased the relative abundance of Methylosarcina, and biochar, slag + biochar treatments decreased the relative abundance of Methylomonas, relative to the control.The slag and slag + biochar treatments increased the relative abundance of Methylocystis in the early paddy, and all three amended treatments increased the relative abundance of Methylocystis in the late paddy, relative to the control.The application of both slag and biochar provided the best overall results, increasing soil pH, salinity, SOC content, and the C:N ratio associated with methanotrophic abundance and the relative abundances of Methylocystis, Methylomonas, and Methylosarcina, which may effectively mitigate CH4 emissions in paddies.Chan, O.C., Yang, X.D., Fu, Y., Feng, Z.L., Sha, L.Q., Casper, P. & Zou, X.M. (2006).

Tables
Index sequences were trimmed, aligned to the SILVA database (Quast et al. 2013), screened, and filtered by the mothur pipeline (Schloss et al. 2009).The sequences were taxonomically classified using the training set, version 9, of the Ribosomal Database Project (Cole et al. 2009), followed by the removal of non-archaeal/bacterial sequences based on the taxonomic classification.Diversity indices and operational taxonomic units (OTUs) at 97% identity with pmoA were estimated using mothur (https://www.mothur.org/).The pmoA sequences have been deposited in the GenBank database (https://www.ncbi.nlm.nih.gov/bioproject/PRJNA445632/)under accession number SRR6901783.Data can be obtained from the Biosample database (https://www.ncbi.nlm.nih.gov/biosample),accession number SAMN 08794436.Quantitative analysis of the methanotrophs by real-time PCR Methanotrophic abundance was determined by qPCR using pmoA-targeted primers A189F/mb661R in triplicate 20-μL reaction mixtures containing SYBR green Master Mix (Sangon Inc., Shanghai, China).The reaction mixture contained 1× Master Mix (Sangon Inc., Shanghai, China), 200 nM of each primer, ten-fold diluted DNA extractions, and double-distilled H2O to a final volume of 20 μL.Real-time quantitative PCR detecting system (qPCR) was carried out with the protocol for target groups as: denaturation at 95 °C for 3 min followed by 45 cycles of denaturation at 95 °C for 15 s, annealing at 57 °C for 20 s, and plate reading at 83 °C.Standard curves were obtained with serial dilutions of plasmid DNA containing the target genes.The data were analyzed using LightCycler 480 Software Setup (Roche Inc., Shanghai, China).
properties for the amended and control plots in the early and late paddy fields