Increasing methane (CH₄) emissions and altering rhizosphere microbial diversity in paddy soil by combining Chinese milk vetch and rice straw

Field experiment

We conducted the field experiment in a paddy field during winter 2015. We used a split plot design where the main plots had two levels of straw incorporation: 0 kg ha⁻¹ of incorporated straw (V) and 6,000 kg ha⁻¹ of incorporated straw (SV). We based the amount of straw returned to the field on conventional practices and previous studies (Aulakh et al., 2001). After harvesting late-season rice, we immediately removed and weighed the fresh straw from the ground. We cut the straw into approximately 10 cm pieces and returned 6,000 kg ha⁻¹ of straw to the field. Three different levels of nitrogen were applied to the subplots during the Chinese milk vetch growing season: 0 kg ha⁻¹ (a), 15 kg ha⁻¹ (b), and 30 kg ha⁻¹ (c). We used variations on the nitrogen levels and the use of straw to create six treatments: Va, Vb, Vc, SVa, SVb, and SVc. We also established a control treatment (NSV) using winter fallow that was cultivated before the rice (Table 1). We applied each treatment and the control treatment on three plots for a total of 21 plots. Each plot measured 25 m² (5.0 m × 5.0 m). The fertilizers contained urea (46% N), calcium magnesium phosphate (12% P₂O₅), and potassium chloride (60% KCl). A typical phosphate and potassium fertilization management system uses 20 kg ha⁻¹ of pure phosphorus and 60 kg ha⁻¹ of pure potassium. Nitrogen fertilizer was applied as a basal, tillering, and booting fertilizer at a 6:3:1 ratio. We applied phosphate fertilizers as basal fertilizers, and potassium fertilizer as a tillering and booting fertilizer at a 7:3 ratio. We applied basal fertilizers the day before rice transplanting, tillering fertilizer 7 days after transplanting seedlings, and heading fertilizer at 20% panicle emergence.

We transplanted the rice variety Yuenuo 06 on April 26, and harvested in early July. We manually harvested each rice plot and measured the aboveground fresh straw and rice yield. We used the same local irrigation management system. Before and after transplanting, we kept the rice submerged in water about three cm deep. Twenty-eight days after transplanting, we implemented a week of mid-term drainage. We irrigated the fields intermittently and did not drain them again until one week before maturity. We sowed the Chinese milk vetch 15 days before the late rice harvest in early October, applying 60 kg ha⁻¹ seed for each plot (excluding the NSV) to the plots. We used the Chinese milk vetch variety Yujiang big leaf seed, which we ploughed into the soil during the bloom stage. At the time of incorporation, fresh Chinese milk vetch showed the following characteristics: 88% water content, 350.52 g kg⁻¹ organic carbon (determined using the dry combustion method), 25.4 g kg⁻¹ total nitrogen (determined using the Kjeldahl digestion method), and a 13.8 C:N ratio. We additionally followed local pesticide and herbicide management practices. Pesticides were applied once during the tillering and booting stages, mainly to prevent borers and sheath blight. Herbicides were applied once during the seedling stage.

Rhizosphere soil sample collection

After 4 years of treatment, we sampled the soils during the early rice ear stage in June 2019. We collected five randomly selected plants from each plot and used a sterile spoon to scrape the soil from the root surface of each plant. We placed the rhizosphere soil in 50 mL sterile centrifuge tubes, added liquid nitrogen, transported it to the laboratory with dry ice, and stored it at −80 °C for microbial analyses. We collected an additional 500 g of bulk soil from each plot using the five-point snake sampling method, mixed the samples together (Nanjing Soil Research Institute CA of S, 1978), placed them in a self-sealing bag, and transported the samples to the laboratory. This soil was air-dried for physicochemical analysis.

We measured soil pH using a 1:5 soil-water ratio extraction method and a glass electrode (E-301-CF; LEICI). We used an automated flow injection analyzer (FIA, Lachat Instruments, Loveland, CO, USA) to measure nitrate and ammonium nitrogen levels. Total organic carbon (TC) was measured using dry combustion with a macro elemental analyzer (Vario MAX C/N; Elementar Analysensysteme, Hanau, Germany). We measured soil TN using the Kjeldahl digestion method (Henry et al., 2006). Available phosphorus (AP) was measured by extracting the samples in 0.5 M NaHCO₃. We measured available potassium (AK) using flame photometry (Clark et al., 1998), and microbial biomass carbon (MBC) and microbial biomass nitrogen (MBN) using chloroform fumigation and K₂SO₄ extraction, respectively (Kudeyarov & Jenkinson, 1976; Shen, Pruden & Jenkinson, 1984). We measured soil activated organic carbon (AOC) using the 333 mmol L⁻¹ potassium permanganate oxidation method (Blair, Lefroy & Lisle, 1995). We measured water content and bulk density using the methods reported by Avnimelech et al. (2001).

Soil genomic DNA extraction and HiSeq sequencing

Total genomic DNA was extracted from rice rhizosphere soil using a FastDNA SPIN Kit for Soil (MP Biomedicals, Solon, OH, USA) according to the manufacturer’s instructions. To examine bacterial community diversity, we amplified the V4 region of the 16s rDNA gene using the primers 515F (5′-GTGCCAGCMGCCGCGGTAA-3′) and 806R (5′-GGACTACHVGGGTWTCTAAT-3′) (Zhang et al., 2017). To examine fungal community diversity, we amplified the ITS1 gene region using the primers ITS1F (5′-CTTGGTCATTTAGAGGAAGTAA-3′) and ITS1R (5′-GCTGCGTTCTTCATCGATGC-3′) (Schmidt et al., 2019). We then barcoded the forward and reverse primers. We used a 30 ng genomic DNA sample and the corresponding fusion primers to configure the PCR reaction system (Gene Amp PCR-System^® 9700) (Zhang et al., 2017). Agencourt AMPure XP magnetic beads (Beckman Coulter, CA, USA) were used to purify the PCR amplification products, which were then dissolved in elution buffer, labeled, and used to construct the library. We cleaned the final amplicon libraries twice using the Agencourt AMPure XP Kit (Beckman Coulter GmbH, USA) and sequenced them on a BGI HiSeq2500 platform (BGI Huada, Shenzhen, China). We submitted the raw reads to the NCBI Sequence Read Archive database under Bioproject PRJNA587576, ITS1 sample accession numbers SAMN13671326 to SAMN13671346. and 16s rDNA sample accession numbers SAMN13195521 to SAMN13195541.

Pot experiment

We conducted a parallel field incubation pot experiment on a Jiangxi Agricultural University experimental field (28.77° latitude, 115.84° longitude). In March 2019, we collected soil samples from Dengjiabu Orientation experimental field plots. We incubated four pots for each treatment and merged the results. We placed the plastic pots on the surface of the soil and used the same treatment conditions as the field experiment. We collected soil samples (0 to 20 cm) using a five-point sampling method for each treatment. Each sample was mixed, air-dried, passed through a six mm sieve, and the stones were removed.

We filled the plastic pots (25 cm height, 21 cm bottom diameter, 25 cm top diameter) with 7.0 kg of dry soil to approximately the depth of field cultivation (20 cm). The freshly harvested Chinese milk vetch (100 g) were cut into three cm segments, incorporated into the pots (except in the NSV group), and incubated with 2–3 cm of water. We replenished the water every day after measuring the height of the water surface. A nylon mesh bag (37 µm mesh size (400 mesh), 10 cm diameter, 15 cm height) was placed in the center of each pot at a depth of 15 cm, dividing the pot into two soil compartments: a central root compartment and a surrounding non-root compartment. We inserted an automatic temperature and humidity meter (ZDR-20, Zeda Instruments, Hangzhou, China) into each pot to record the temperature and humidity every half hour. On April 25, 2019, two healthy early rice seedlings were transplanted into each pot’s root bag. We applied N, P, and K fertilizer in each pot according to their corresponding field treatment. A 2–3 cm layer of water was maintained during rice cultivation. After transplanting the rice, we measured CH₄ emissions using the static closed-chamber method at 7 day intervals (Zou et al., 2005; Jia, Cai & Tsuruta, 2006). We analyzed gas concentration using a gas chromatograph (Agilent 7890B, CA, USA). The CH₄ emissions were calculated using previously described methods (Afreh et al., 2018; Xiao et al., 2019). CH₄ flux was calculated using the following equation: ${\displaystyle F=\rho \times V∕A\times \Delta C∕\Delta t\times 273∕\left(273+T\right)}$ where F is the emission flux rate of CH₄ (mg m⁻² h⁻¹), ρ is the gas density of CH₄ under a standard state (mg m⁻³), V is the chamber volume (cm³), A is the soil area, ΔC is the concentration of CH₄ produced during an hour sealed, Δt is the time between sample collection (h), and T is the mean chamber temperature (°C).

The experiment ended 11 weeks after rice transplantation. During this period, approximately 90% of seasonal CH₄ emissions were generated (Xiao et al., 2019). At the end of the pot experiment, we harvested the plants and measured the above- and below-ground biomass. We oven-dried rice plants at 70 °C for 24 h to reach a constant weight. To determine physicochemical properties, we air-dried the remaining soil after harvesting using the same method as the field experiment.

Microbial diversity analysis

We used USEARCH software (v10.0.240, Robert Edgar) to cluster the stitched tags into amplicon sequence variants (ASVs). We also used USEARCH for dereplication, and unoise3 to denoise, predict biological sequences, and filter chimeras. We used the 16S database Greengene (V201305) for bacteria and the ITS fungus database UNITE (Version 6 20140910) for fungi. We filtered the annotated results to remove ASVs without unannotated results. We used USEARCH to calculate the alpha diversity index, then calculated the richness change of the dilution process and rarefaction from 1% to 100% in abundance (observed OTUs). The constrained canonical correspondence analysis (CCA) profile used a Bray-Curtis distance matrix (Hannula et al., 2017) and R package amplicon (Liu, 2019). We used a partial Mantel test to evaluate the relationships between soil microbial community richness and environmental factors. We deposited these raw reads in the NCBI Sequence Read Archive database.

We used R (version 3.6.3) (R Core Team, 2020) for data analyses and plotting. We used Bartlett’s test of homogeneity, and applied Fisher’s Least Significant Difference (LSD) test for multiple comparisons. Related packages included agricolae (Felipe, 2020), vegan....... (Oksanen et al., 2019), and ggplot2 (Wickham, 2016). We used the analysis of similarities (ANOSIM) function to find similarities across the microbial community composition data.