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Article

Effect of Short-Term Organic Matter Returns on Soil Organic Carbon Fractions, Phosphorus Fractions and Microbial Community in Cold Region of China

by
Shuangshuang Yan
1,
Haowen Jiang
1,
Jinwang Li
1,
Chao Yan
1,
Chunmei Ma
1,
Zhongxue Zhang
2 and
Zhenping Gong
1,*
1
School of Agriculture, Northeast Agricultural University, Harbin 150030, China
2
School of Water Conservancy and Civil Engineering, Northeast Agricultural University, Harbin 150030, China
*
Author to whom correspondence should be addressed.
Agronomy 2023, 13(11), 2805; https://doi.org/10.3390/agronomy13112805
Submission received: 14 October 2023 / Revised: 10 November 2023 / Accepted: 11 November 2023 / Published: 13 November 2023
Browse Figures
Versions Notes

Abstract

:
To investigate the effect of different organic matter returns on soil organic carbon (SOC) fractions, phosphorus (P) fractions and microbial communities, a pot experiment was conducted in a cold region of China for three years. There were six treatments in this study, including no rice straw return (S0), rice straw return (SR), decomposed rice straw return (DS), rice-straw-burned return (BS), rice root return (RR) and decomposed cattle manure return (DM). The results indicated that the organic matter returns had no significant effect on the rice yield after three years. The SR, DS and DM treatments significantly increased the content of the soil’s total organic carbon (TOC), light fraction organic carbon (LFOC), particulate organic carbon (POC), dissolved organic carbon (DOC) and microbial biomass carbon (MBC). The BS treatment decreased the soil MBC content. The SR, DS, BS and DM treatments significantly increased the content of the soil’s total P, NaHCO3-P, NaOH-P and residual-P. The proportion of nonlabile P (HCl-P and residual-P) was reduced by the organic matter returns. The SOC fractions were positively correlated to the soil P fractions (except HCl-P). The organic matter returns did not affect the microbial diversity but did change the microbial community composition. The dominant phyla included Proteobacteria, Firmicutes, Chloroflexi, and Bacteroidetes. Compared with the S0 treatment, the organic matter returns increased the relative abundance of Actinobacteria, Anaerolineae and Alphaproteobacteria and decreased the relative abundance of Bacteroidetes, Clostridia and Bacteroidia. The contents of MBC, DOC and NaOH-P were the main factors affecting the microbial community composition, and the soil’s P fractions had a larger influence on the microbial community than the SOC fractions. These results indicated that the incorporation of rice straw, decomposed rice straw and decomposed cattle manure might be an effective practice for maintaining soil fertility in the cold region of China.

1. Introduction

Mollisols are the most fertile and productive of soil varieties. The antecedent organic carbon (C) pool of Mollisols in Northeast China has decreased by approximately 50% because of human activities [1]. Soil erosion and insufficient carbon input are the main reasons for the decrease of organic C content [2]. Soil organic carbon (SOC) plays an important role in the improvement of soil fertility and the maintenance of crop productivity in agricultural systems [3,4]. Long-term agricultural production decreases SOC and affects soil functions [5].
Farmyard manure and crop residues provide large amounts of organic matter, which increases the SOC when it is returned to the soil [4,6]. In subtropical paddy fields in China, the contents of SOC, light fraction organic carbon (LFOC), dissolved organic carbon (DOC) and microbial biomass carbon (MBC) are significantly increased with rice straw return in double cropping rice fields [7]. Straw burning results in the loss of carbon and nutrients in crop straw, reduces the activity of soil microbes [8] and has no effect on the soil’s total organic carbon (TOC) content [9]. Compared with rice straw return, farmyard manure application is better at improving the SOC and labile organic C fractions [4,10].
A large part of P absorbed by crops comes from the soil phosphorus (P), and this part of P is mainly supplemented by inorganic P fertilizer [11]. Organic matter returns, particularly for those with high P concentrations, increase the soil’s organic P (Po), providing a sustained P source for crop growth [12]. The addition of organic matter (rice straw, green manure, and pig manure) significantly increases the content of Po compared with chemical fertilizer application [13]. Rice straw return and straw burning both increase the soil P content compared with straw removal [14]. Farmyard manure application increases the soil’s TOC and Bray-P [15].
Crop residue returns change the soil’s environment, which in turn influences the composition and activity of the microbes and nutrient transformations in the soil [8]. The field investigation showed that both the chemical fertilizer and organic manure applications increased the biomass and diversity of the soil microbes [16]. The application of rice straw with chemical fertilizer significantly increases the bacterial abundance and changes the bacterial community composition [17]. Compost application also increases the soil’s enzyme activity and the diversity of the bacterial community [18]. The microbial community composition is closely related to the soil’s chemical properties and is mainly affected by the SOC and total P content [19].
Crop yield is affected by fertilizer application and organic matter management. In a long-term experiment in northwest China, the application of farmyard manure or straw combined with chemical fertilizer increased the crop yield as compared with the application of only chemical fertilizer [20]. In a 15-year field experiment, straw burning and straw removal both increased the rice and wheat yield as compared with the straw return [21]. The climate, soil conditions and agronomic practices all have effects on the crop yield [22].
Straw decomposition is slow in Northeast China because of its cold climate. Crop straw is often burned in situ, seriously polluting the environment. Crop straw or animal manure combined with chemical fertilizer can not only reduce the consumption of mineral resources but also reduce the environmental pollution caused by crop straw burning and animal manure abandonment. In this study, we used a pot experiment to study the effect of organic matter (crop residue and cattle manure) return on the rice yield as well as changes of SOC fractions, P fractions and microbial community composition. This study provides a theoretical reference for sustainable rice production in the cold region.

2. Materials and Methods

2.1. Experimental Design

The experiment was conducted at the experimental practice base of the Northeast Agricultural University, which is located in Harbin, Heilongjiang Province (45°34′–45°46′ N, 126°22′–126°50′ E) with an altitude of 171.7 m. From 2017 to 2019, the average annual precipitation was 643.54 mm, the annual average temperature was 5.38 °C and the frost-free period was 170 days (https://data.cma.cn/, accessed on 10 December 2020). Rice is cultivated once a year, and continuous cropping is adopted.
The experiment was started in 2017. Potted cultivation was used, with a height of 35 cm and a diameter of 30 cm, and each pot was filled with 20 kg soil. The soil used was Mollisols taken from the topsoil of paddy fields. The basic soil properties were as follows: total N, 1.57 g kg−1; total P, 0.61 g kg−1; total K, 28.80 g kg−1; NH4+-N, 11.23 mg kg−1; NO3−-N, 43.18 mg kg−1; available P, 27.34 mg kg−1; available K, 292.17 mg kg−1; and SOC, 21.64 g kg−1. The basic soil properties were measured according to the methods of Bai et al. [23] and Lu [24]; the total N, NH4+-N and NO3−-N were determined using a Kjeldahl apparatus (BÜCHI K-350, BÜCHI Labortechnik AG, Flawil, Switzerland); the total P and available P were determined using a UV spectrometer (Hitachi U-2910, Hitachi, Ltd., Tokyo, Japan); and the total K and available K were determined using a flame photometer (Sherwood M410, Sherwood Scientific Ltd., Cambridge, UK). These analyses were performed at the Northeast Agricultural University, Harbin.
The study involved six treatments: no rice straw return (S0), rice straw return (SR) 80 g pot−1 (12,500 kg ha−1), decomposed rice straw return (DS) 80 g pot−1 (12,500 kg ha−1), rice-straw-burned return (BS) 80 g pot−1 (12,500 kg ha−1), rice root return (RR) 20 g pot−1 (3125 kg ha−1) and decomposed cattle manure return (DM) 80 g pot−1 (12,500 kg ha−1). Each treatment had three repetitions. The amount of straw return corresponded to that of Yan et al. [25]. The nutrient content of organic matter was listed in Table 1.
The rice straw used in this study was collected from the paddy field after the rice harvest, air-dried and cut into approximately 5 cm pieces. The rice straw was decomposed in the field for 1 year. Straw decomposition was performed according to the method of Yan et al. [26]. The sheared rice straw was put into nylon bags (25 cm × 20 cm, 150 µm pore size). Each nylon bag was filled with 80 g of air-dried rice straw and buried in the paddy field before rice transplanting. After one year of decomposition, the nylon bags were dug out, rinsed thoroughly with water and then air-dried, thereby providing the decomposed straw. The residual amount of rice straw was 44.4% after one year of decomposition. After the rice harvest, the rice roots were removed, rinsed thoroughly with water and then air-dried, thereby providing the returned roots. The decomposed cattle manure was air-dried, manually broken into small pieces and sieved through an 8-mm mesh.
On 16 May of every year of the study, the rice straw, cattle manure and rice roots were evenly mixed with the soil. For straw-burned return, the rice straw was burned in situ, the ash was mixed evenly with the soil and then the pots were soaked. Thirty-day-old seedlings were transplanted (three seedlings per hole and three holes per pot) on 23 May. The rice variety was Longdao 21. Before rice transplantation, basic fertilizer was applied as follows: urea (N: 46%, Shandong Hualu-Hengsheng Chemical Co., Ltd., Dezhou, China); 1.06 g pot−1 (150 kg ha−1) and triple superphosphate (P2O5: 44%, Yunnan Yuntianhua, Co., Ltd., Kunming, China); 1.11 g pot−1 (157 kg ha−1) and potassium sulfate (K2O: 50%, Zhongnong Shuntian Ecological Fertilizer Industry Co., Ltd., Linyi, China); 0.71 g pot−1 (100 kg ha−1). Urea (1.06 g pot−1, 150 kg ha−1) was applied at the tillering stage. The rice was irrigated regularly from the seedling stage to the mature stage to maintain shallow standing water. The other management measures were the same as farmer practices [25]. The rice root was removed from the pots in all treatments after the rice’s annual harvest.

2.2. Plant and Soil Sampling

The soil samples were collected in October of 2019, following the rice harvest. The soil was collected with a probe (3 cm in diameter, a depth of 15 cm) from each pot and mixed as a sample, and each treatment contained five replicates. Fresh soil samples were sieved to pass through a 2 mm mesh and divided into three parts. One part was stored at −4 °C for determination of the MBC and DOC, the second part was stored at −80 °C for DNA extraction, and the third part was air-dried to determine the soil’s TOC, LFOC, particulate organic carbon (POC), labile organic carbon (LOC) and P contents.
At the maturity stage of each year, the rice was harvested by hand to determine the grain yield. The grains were dried at 105 °C for 30 min, then dried to a constant weight at 80 °C and weighed [27].

2.3. Analysis Method of Soil C and P Fractions

The soil TOC was digested with K2Cr2O7–H2SO4 and titrated with FeSO4 [23]. The DOC was extracted according to the method of Wang et al. [7] and determined using a total organic carbon analyzer (Shimadzu TOC-L, Shimadzu Corporation, Kyoto, Japan). The fumigation—extraction method was used to determine the MBC [28]. The digestion method with KMnO4 was used to estimate the LOC [29]. The NaI separation method was used to determine the LFOC [30]. The modified method of Cambardella and Elliott was used to determine the POC [30]. The molybdenum-blue colorimetric method was used to determine the soil’s available P and total P [24]. A corrected P fractionation scheme was used to determine the soil’s P fractions [31]. The soil (0.5 g dry weight) was extracted with deionized water (H2O-P); followed by 0.5 M NaHCO3 (NaHCO3-P), 0.1 M NaOH (NaOH-P), 1 M HCl (HCl-P); and then digested with potassium persulfate (K2S2O8) at high pressure (residual-P). The extracts were used to determine the inorganic P (Pi) (H2O-P, NaHCO3-Pi, NaOH-Pi, HCl-P and residual-P) with the molybdenum-blue colorimetric method by using a UV spectrometer (Hitachi U-2910, Hitachi, Ltd., Japan); the total P in the NaHCO3 and the NaOH extracts were measured after the extracts were digested with K2S2O8 at high pressure. The organic P (Po) in NaHCO3-P and NaOH-P extracts were calculated from the difference between the total P and Pi.

2.4. Soil Bacterial DNA Extraction and Sequencing

The soil’s DNA was extracted using a TIANamp Soil DNA Kit (Tiangen Biotech Co., Ltd., Beijing, China). Agarose gels (1%) were used to monitor the DNA’s concentration and purity. DNA was diluted to 1 ng μL−1 using sterile water according to the concentration. The 16S rRNA gene sequence in the V4 region was amplified using a pair of primers: 515F (5′-GTGCCAGCMGCCGCGGTAA-3′) and 806R (5′-GGACTACHVGGGTWTCTAAT-3′) [32]. The polymerase chain reaction (PCR) conditions were as follows: pre-denaturation at 98 °C for 1 min, 30 cycles at 98 °C for 10 s, 50 °C for 30 s, 72 °C for 30 s and finally polymerization at 72 °C for 5 min. The PCR products were mixed in equidensity ratios and purified using a Qiagen Gel Extraction Kit (Qiagen, N.V., Dusseldorf, Germany). The library was constructed using an Illumina TruSeq DNA PCR-Free Library Preparation Kit (Illumina, Inc., San Diego, CA, USA). The constructed library was quantified by a Qubit@ 2.0 Fluorometer (Thermo Fisher Scientific, Inc., Waltham, MA, USA) and an Agilent Bioanalyzer 2100 system. Finally, the library was sequenced using an IlluminaHiSeq2500 platform.

2.5. Data Analysis

The raw data were spliced and filtered to obtain clean data. The clean data with ≥97% similarity were clustered into the same operational taxonomic units (OTUs). According to the OTU clustering results, the representative sequences for each OTU were annotated. The alpha diversity indices and beta diversity were calculated using QIIME (Version 1.7.0) and displayed with the free software R 2.15.3 (www.r-project.org, accessed on 3 June 2023).
SPSS 21.0 (SPSS Inc., Chicago, IL, USA) was used for statistical analyses. All data were tested for normality before one-way analysis of variance (ANOVA), using Duncan’s multiple range at the significance level of 0.05. The correlations between rice yield, SOC fractions and P contents were analyzed by Pearson correlation analysis. The correlation between environmental factors and microbial community composition was analyzed using a canonical correlation analysis (CCA) using the free software R 2.15.3 (www.r-project.org, accessed on 3 June 2023).

3. Results

3.1. Rice Yield

Compared with the S0 treatment, the SR and DS treatments significantly decreased the rice yield in 2017 and 2019, and these two treatments did not significantly affect the rice yield in 2019 (Figure 1). The BS and RR treatments did not significantly affect the rice yield in 2017—2019. The yield of the DM treatment was highest during the 3-year period and significantly higher than the S0 treatment in the third year.

3.2. Soil TOC and Active SOC Fractions

Compared with the S0 treatment, the SR, DS and DM treatments significantly increased the soil’s TOC by 9.97%, 5.64% and 8.13%, respectively (Table 2). The soil’s LFOC, MBC and DOC were significantly affected by the organic matter returns. Compared with the S0 treatments, the soil’s LFOC in the SR, DS, BS and DM treatments increased by 88.83%, 64.08%, 36.89% and 78.16%, respectively, and the soil’s POC in the SR and DM treatments increased by 40.76% and 38.22%, respectively. The soil’s DOC in the DM treatment was significantly higher than that found in the other treatments. Compared with the S0 treatment, the soil’s MBC in the SR, DS, RR and DM treatments was significantly increased by 83.69%, 87.14%, 31.36% and 106.47%, respectively, and the BS treatment significantly decreased the soil’s MBC by 22.15%. The LOC content was not affected by the different organic matter returns.

3.3. Soil P Contents

The contents of the soil’s available P and total P in the DM treatment were significantly higher than those found in the other treatments (Figure 2). The available P content in the SR and DS treatments was significantly higher than that found in the S0, BS and RR treatments. Compared with the S0 treatment, the available P content in the SR, DS and DM treatments increased by 17.70%, 12.15% and 36.67%, respectively; the total P in the SR, DS, BS and DM treatments increased by 13.50%, 7.99%, 4.61% and 27.94%, respectively.
The H2O-P content in the DM treatment was significantly higher than that found in the other treatments (Figure 3). Compared with the S0 treatment, the contents of NaHCO3-Pi and NaHCO3-Po in the SR, DS, BS and DM treatments significantly increased, and the NaHCO3-Po content increased by 82.75%, 27.06%, 30.75% and 44.61%, respectively. The DM treatment significantly increased the NaOH-Pi and NaOH-Po contents compared with the other treatments, and the SR, DS and BS treatments had significantly higher contents of NaOH-Pi and NaOH-Po than those found in the S0 and RR treatments. Compared with the S0, DS, BS, RR and DM treatments, the SR treatment significantly increased the HCl-P content, while the DM and BS treatments significantly reduced the HCl-P content. The residual-P content in the SR, DS, BS and DM treatments significantly increased by 10.80%, 28.47%, 15.66% and 29.82%, respectively.
The percentage of labile P in the DM treatment was the highest. Compared with the S0 treatment, the percentage of labile P (H2O-P, NaHCO3-Pi and NaHCO3-Po) in the SR, BS and DM treatments increased by 7.57%, 6.95% and 8.60%, respectively. The percentages of moderately labile P (NaOH-Pi and NaOH-Po) in the DM and BS treatments were significantly higher than those found in the other treatments. The SR, DS and RR treatments had no effect on the percentage of moderately labile P. The organic matter returns reduced the percentage of the nonlabile P (HCl-P and residual-P), and the SR, DS, BS and DM treatments significantly decreased by 5.21%, 3.82%, 10.82% and 21.28%, respectively.

3.4. Correlation between Rice Yield, SOC Fractions and P Contents

In the first and second years of the experiment, the rice yield was mostly negatively correlated with the SOC fractions and P content. There was a positive correlation between the rice yield and NaHCO3-Pi and NaOH-P, and a low correlation with the SOC fractions in the third year. The soil’s P fractions (except HCl-P) were positively correlated with the SOC fractions (Figure 4). NaHCO3-P, NaOH-Pi and the total P were significantly positively correlated with the TOC, LFOC, POC, DOC and MBC. The residual-P and total P were significantly positively correlated with the LFOC, POC, DOC and MBC. The available P and total P were significantly positively correlated with the P fractions except HCl-P. H2O-P and NaHCO3-Pi were significantly positively correlated with NaOH-P. There was a positive correlation between the soil’s TOC and active SOC fractions.

3.5. Microbial Richness and Diversity

After quality control, an average of 83,635 raw data points were obtained, and the amount of clean data was 62,947. The average GC content was 55.06%, the average Q20 was 99.30% and the average Q30 was 97.69%, which showed that the sequencing data were of good quality and high reliability. The sequences were clustered into OTUs with 97% identity, and 11,767 OTUs were obtained. The rarefaction curves all tended to be saturated (Figure S1), and the species’ accumulation box plot tended to be flat (Figure S2), indicating that the sequencing data were sufficient. The total number of shared OTUs in the six treatments was 3920 (27.96%), and the number of unique OTUs was DS > S0 > SR > RR > DM > BS (Figure S3).
The observed species in the SR, BS and DS treatments were significantly lower than those in the S0 treatment (Figure S4a). The organic matter returns did not affect the Shannon index, indicating that the species’ richness and evenness were not influenced by the organic matter returns (Figure S4b). Compared with the S0 treatment, the number of OTUs was significantly decreased in the DS and BS treatments (Figure S4c,d). The Good’s coverage index of all treatments was high (0.97–0.98) (Figure S4e), and the sequencing depth was sufficient.
The first and second principal components explained 9.84% and 8.59% of the microbial community changes, respectively (Figure 5a). The microbial community composition of the S0 and BS treatments was similar, while the DS and DM treatments formed a cohesive group and separated from the other treatments (Figure 5b).

3.6. Composition of the Microbial Community

Proteobacteria was the most abundant phylum (Figure 6). The dominant phyla included Proteobacteria (0.29–0.35), Firmicutes (0.11–0.19), Chloroflexi (0.11–0.20), Bacteroidetes (0.08–0.13), Acidobacteria (0.06–0.08) and Actinobacteria (0.04–0.07), occupying 0.84—0.87 of the microbe’s total amount. The relative abundance of Proteobacteria and Verrucomicrobia were not affected by the organic matter returns. Compared with the S0 treatment, the organic matter returns decreased the relative abundance of Bacteroidetes and increased the relative abundance of Actinobacteria. The relative abundance of Bacteroidetes was significantly reduced in the RR and DM treatments, while the relative abundance of Actinobacteria was significantly increased in the SR, RR and DM treatments (Figure S5). Compared with the S0 treatment, the relative abundance of Firmicutes was significantly reduced; the relative abundance of Chloroflexi, Acidobacteria and Gemmatimonadetes were significantly increased in the DM treatment; the relative abundance of Chloroflexi and Actinobacteria were significantly increased in the SR treatment; and Chloroflexi was significantly increased in the DS treatment.
Gammaproteobacteria was the most abundant class (Figure 7). The dominant classes included Gammaproteobacteria, Anaerolineae, Clostridia, Deltaproteobacteria, Bacteroidia, Bacilli and Alphaproteobacteria. Compared with the S0 treatment, organic matter returns increased the relative abundance of Anaerolineae, Alphaproteobacteria and unidentified Actinobacteria, and decreased the relative abundance of Clostridia and Bacteroidia (Figure S6). The DM treatment significantly increased the relative abundance of Anaerolineae and unidentified Actinobacteria, while the RR and DM treatments significantly reduced the relative abundance of Bacteroidia and increased the relative abundance of unidentified Actinobacteria. The DS and DM treatments significantly reduced the relative abundance of Bacilli. The organic matter returns had no significant effect on the relative abundance of Gammaproteobacteria and Deltaproteobacteria.
The microbial community composition had a greater difference at the genus level (Figure S7). The dominant genera in the S0, BS and RR treatments included unidentified Deltaproteobacteria, unidentified Clostridiales, and Lactobacillus. Unidentified Clostridiales was the most abundant genus in the S0 and SR treatments. The unidentified Deltaproteobacteria was the highest genus in the DS, BS, RR and DM treatments. Geobacter was the most abundant genus in the DS treatment, which was significantly higher than that in the BS and RR treatments (Figure S8). Compared with the S0 treatment, the organic matter returns increased the relative abundance of Anaerolinea, which was significantly increased in the SR, DS and DM treatments.
The LEfSe analysis showed that 17 biomarkers were further screened out (Figure S9). There were two, five, one, four and four biomarkers in the S0, SR, DS, BS, RR and DM treatments, respectively. The main biomarkers included Actinobacteria, Bacilli and Pseudomonadaceae.

3.7. Relationship between the Soil Microbial Community and Environmental Factors

The relationships between the soil microbial community, SOC fractions and soil P fractions were analyzed using RDA (Figure 8). As shown in Figure 8a, the two axes of CCA explained 48.56% of the total variation; the first axis explained 28.52% of the variation, indicating that the MBC and DOC were critical factors affecting the microbial community. As shown in Figure 8b, the two axes of CCA explained 38.84% of the total variation; the contribution rate of the first axis is 20.44%, indicating that NaOH-Po and NaOH-Pi were critical factors affecting the microbial community.
The SOC fractions and P fractions explained 89.69% of the soil’s microbial distribution; the common explanation of the SOC fractions and the soil’s P fractions was 16.96%, and 10.31% was unexplainable (Figure S10). The results showed that the soil’s P content had a greater effect on the microbial distribution than the SOC fractions.

4. Discussion

4.1. Changes in Rice Yield

The straw return significantly reduced the rice yield in the cold, waterlogged paddy soils of North China under flooding conditions [33]. The SR and DS treatments inhibited rice growth and significantly reduced the rice yield in the first two years (Figure 1). The reason may be that the straw decomposed slowly in the cold climate of Northeast China, and the returned straw may have led to N fixation during decomposition [21], enhanced the reduction state in flooding paddy soil [34], and promoted the accumulation of organic acids and sulfides in soil, resulting in the inhibition of rice growth and the reduction of the rice yield [35,36]. The SR treatment had no significant influence on the rice yield in the third year, while the rice yield from the SR treatment was still lower than that from the S0 treatment. The reason for the change in rice yield in the different years may be due to the soil’s nutrient variation and climate difference; the detailed reasons needed to be further explored. Gupta et al. [14] found that the wheat yield in the straw burning in situ was similar to that in the no-straw return. Beri et al. [21] found that straw burning for more than 11 years had a higher yield of rice and wheat than the no-straw return. In this study, the BS treatment had no influence on rice growth (Figure 1), although the effect of straw burning on yield may change with the increase of time. Due to the small amount of rice root returned, the RR treatment had no effect on the rice yield. The farmyard manure + NPK treatment increased the plants’ available P and crop yield in a long-term experiment [37]. The rice yield was highest in the DM treatment during the three years, and the yield was significantly higher than the S0 treatment in the third year. The difference between the results may be the short return time and the different nutrients in the manure.

4.2. Changes in SOC Fractions

Compared with the S0 treatment, the SR, DS and DM treatments significantly increased the soil TOC, LFOC, POC, DOC and MBC contents, and the DM treatment increased the most (Table 2), the content of MBC increased the most under the organic matter returns, followed by LFOC. In Loess Plateau of China, a semiarid, warm temperate, continental monsoon climate, maize straw return also significantly increased the SOC content [38]. In a temperate, semi-humid, continental climate region, straw return significantly increased the soil’s MBC content [39]. In the subtropical monsoon climate, compared with the application of chemical fertilizer and straw, manure application increases the SOC and active SOC fractions, and the manure treatment has the highest MBC content [10]; straw return had no significant influence on the LOC content and significantly increased the soil’s TOC, DOC and MBC contents [40]. Our results were similar to those previous studies conducted in different climate conditions: the SR, DS and DM treatments increased the C input to the soil and significantly increased the soil’s TOC and active SOC fractions (Table 2).
Compared with the S0 treatment, the BS treatment significantly reduced the MBC content and had no effect on the TOC, LOC, POC and DOC contents (Table 2). Huang et al. [9] found that the straw-burned return did not affect the soil TOC and MBC contents and significantly increased the DOC content, and straw-burned return was not conducive to the SOC sequestration. Most of carbon is lost when straw burns, and the amount and diversity of soil microbes are decreased by straw burning [8], thus resulting in a significant decrease in the soil’s MBC content in the BS treatment. The RR treatment significantly increased the soil’s MBC content as compared with the S0 treatment but had no effect on the other SOC fractions, which may be due to the low rate of rice root returned, which had little influence on SOC fractions. Compared with green manure and rice straw return, the farmyard manure return increased the MBC content [41]. In this study, the DOC and MBC contents in the DM treatment were significantly higher than those found in the other treatments (Table 2). Compost cattle manure has a lower C/N ratio and decomposes faster than rice straw, compost straw and root [42], and manure can maintain higher DOC and increase microbial biomass [43].

4.3. Changes in Soil P Content

Related studies have shown that straw return increases the soil’s Pi, Po and available P content [14], and that the combined application of farmyard manure or rice straw with chemical fertilizer increases the content of the soil’s available P and total P in subtropical central China [44]. In this study, compared with the S0 treatment, the soil’s available P and total P content were significantly increased in the SR, DS and DM treatments (Figure 2), especially in the DM treatment. The straw and farmyard manure returns both reduce the soil’s P adsorption and improve its P availability [14], and the DM treatment was more beneficial to the soil’s P accumulation due to the higher P content of cattle manure. In a long-term fertilization experiment in the temperate monsoon climate, as compared with chemical fertilizer application, the farmyard manure application significantly increased the soil’s total P and available P; however, the straw return had no influence on the soil’s total P and available P [45]. Damon et al. [46] found that the application of crop straw with low P content had no significant agronomic contribution to the availability of the soil’s P. The difference in these results is mainly due to the difference in the P forms and adsorption characteristics of the soil [47]; the different climate conditions may also have contributed to these differences.
Gupta et al. [14] found that the straw return increased the soil’st Pi and Po contents and reduced the adsorption of the soil’s P in a rice-wheat system. Our study showed that the SR, DS, BS and DM treatments significantly increased the content of the soil’s NaHCO3-P, NaOH-P and residual-P compared with the S0 treatment, while the RR treatment had no effect on the soil’s P fractions (Figure 3). The DM treatment had the highest soil P fraction contents, followed by the SR treatment. The SR, DS and BS treatments decreased the H2O-P content, while the DM treatment significantly increased the H2O-P content. This may be because manure has a higher P content than rice straw, and most of the P in manure is dissolvable in water and NaHCO3 [48], thus increasing the soil’s H2O-P content and having a more obvious effect on the increase of the soil’s P content. Ye et al. [49] found that after the pig manure return, the P in pig manure was mainly converted into the soil’s H2O-P and NaHCO3-Pi, which significantly increased the soil’s P component. Rice-straw burning in situ loses 5.5% of P [50], and most of the P is still returned to the soil; thus, the BS treatment increased the soil’s P fractions. Due to the low rate applied and low P content of the rice root, the RR treatment had no significant effect on the soil’s P fractions. The SR, DS, BS and DM treatments increased the contents of the soil’s Pi and Po, and the Po content increased more (Figure 3). The reason for this may be that organic matter returns brings continuous organic C input and stimulates the microbial activity. The P from organic matter is not easily adsorbed and precipitated compared with inorganic P fertilizer, which leads to the formation of Po [12].
Compared with the S0 treatment, the organic matter significantly reduced the percentage of the nonlabile P in the soil, and the DM treatments significantly increased the percentage of labile P and moderately labile P (Figure 3). The application of farmyard manure + NPK lowered the P adsorption and increased the available P for plants in the tropical region [37]. The wheat straw return decreased the P adsorption in the subhumid tropical region [51]. Mao et al. [52] found that in the subtropical monsoon region, the residual P fertilizer mainly accumulated in the form of moderately labile P and a small amount of labile P, and the organic fertilizer application prevented the transformation of applied P into difficult decomposed P, thus increasing the proportion of available phosphorus. Our results were similar to those of the previous studies. The organic matter addition reduces the P adsorption and enhances the soil’s P availability in black soil [53]. The organic matter (straw or manure) returns had similar effects on the soil’s P adsorption in different climate conditions. Our results showed that the organic matter returns increased the P availability of soil in the cold region, which may be the reason that the percentage of labile P and moderately labile P increased with the organic matter returns in this study.

4.4. Correlations between Rice Yield, SOC Fractions and P Fractions

Yang et al. [54] found that the maize yield was positively related to the soil’s P composition and bioavailability. Li et al. [55] found that the rice yield was not significantly related to the SOC content, and the rice yield showed an increasing trend in the Chinese milk vetch application as compared with rice straw return. Our study showed that the correlation between the rice yield, SOC fractions and P content changed with experiment time, and the rice yield was positively correlated with the NaHCO3-Pi and NaOH-P content in the third year (Figure 4). The SR and DS treatments significantly decreased the rice yield in the previous two years but had significant influence on the rice yield in the third year; the change of rice yield may be the main reason for the difference correlation between the rice yield, SOC fractions and P content during the three years. The DM, BS, and RR treatments had higher rice yields than the S0 treatment in the third year; the soil’s P content was also increased by the organic matter returns. NaHCO3-Pi and NaOH-P were easily absorbed and utilized [49], which may have resulted in a positive correlation between the rice yield and the NaHCO3-Pi and NaOH-P content. In our study, there was a significant positive correlation between the SOC fractions and a positive correlation between the P fractions (except HCl-P) and SOC fractions (Figure 4). Benbi et al. [56] found that the DOC, LOC, and MBC were positively related to the TOC. The soil’s P content is the most important factor for the process of C cycling in the black soil region [48]. Our results were similar to this previous study: the soil’s available P, total P, NaHCO3-P, NaOH-P and residual P were significantly positively corrected with the LFOC, POC, DOC and MBC.

4.5. Changes in Microbial Community Composition

Daquiado et al. [57] showed that compost (straw compost mixed with cattle manure) reduced the total number of OTUs, and the soil’s microbial structure was not affected by long-term fertilization in paddy soils. Kumar et al. [58] showed that rice-straw burning significantly reduced the population of microbes. Our results showed that the SR, DS and BS treatments reduced the microbial quantity, and that the organic matter returns did not affect the diversity and evenness of the microbial community (Figure S4). Our results were similar to those of previous studies [57,58]. While in the paddy fields in the subtropical region of China, the combination of rice straw with chemical fertilizer changed the bacterial community’s composition and significantly increased the abundance of bacteria. The difference in these research results may be due to the influence of soil and climate conditions, organic matter application amounts and tillage methods.
In our study, the organic matter returns had no significant influence on the relative abundance of Proteobacteria but reduced the relative abundance of Bacteroidetes (Figure 6); the relative abundance of Bacteroidetes reduced the most in the DM treatment, which was significantly lower than that of the S0 treatment. Bacteroidetes are oligotrophic bacteria, and the organic fertilizer increased the soil’s nutrients and reduced the relative abundance of Bacteroidetes [59]. The organic matter returns increased the soil’s C and P contents in this study, especially the decomposed cattle manure return, resulting in the decrease of Bacteroidetes. Our study showed that the organic matter returns increased the relative abundance of Chloroflexi and Actinobacteria (Figure 6), among which the DM treatment increased the most; the results of the LEfSe analyses showed that Actinobacteria was one of the main biomarkers (Figure S9). Polysaccharides are mainly degraded by Chloroflexi in paddy soil [60], and Actinobacteria plays a key role in cellulose decomposition [61]. Sun et al. [18] found that the application of cattle manure significantly increased the relative abundance of Actinobacteria. In this study, the organic matter returns brought large amounts of nutrients for microbes, thus increasing the relative abundance of Chloroflexi and Actinobacteria. The relative abundance of Chloroflexi and Actinobacteria were higher in the DM, SR and RR treatments than in the BS treatment. Straw burning caused a large amount of organic carbon loss (Table 1); less organic carbon was returned as compared with the other treatments, resulting in a lower relative abundance of Chloroflexi and Actinobacteria in the BS treatment. The DM treatment significantly reduced the relative abundance of Firmicutes but significantly increased the relative abundance of Acidobacteria and Gemmatimonadetes as compared with the S0 treatment (Figure S5); there was no significant difference between other treatments. Tian et al. [62] found that the relative abundance of Firmicutes was significantly reduced with compost application, and Firmicutes was negatively correlated with SOC. Acidobacteria are heterotrophic bacteria with a wide range of carbon sources [63], and the decomposed cattle manure return brings a large amount of carbon sources, thus increasing the relative abundance of Acidobacteria [64]. Gemmatimonadetes is one of the C-cycling bacteria in the black soils [65]; organic-inorganic compound fertilizer increased the abundance of Gemmatimonadetes [66]. Our results were similar to those of the previous studies.
Zhao et al. [66] found that the organic—inorganic compound fertilizer increased the relative abundance of Alphaproteobacteria and Gammaproteobacteria. Wang et al. [59] showed that, compared with the organic fertilizer treatment, inorganic fertilizer application had a higher relative abundance of Gemmaproteobacteria. In this study, the organic matter returns had no effect on the relative abundance of Gemmaproteobacteria (Figure 7 and Figure S6) and increased the relative abundance of Alphaproteobacteria, Anaerolineae, unidentified Actinobacteria and Anaerolinea, and decreased the relative abundance of Clostridia and Bacteroidia; the DM treatment had the largest influence on these bacteria. Clostridia is a member of the phylum Firmicutes, Bacteroidia is a member of the phylum Bacteroidetes, and Firmicutes and Bacteroidetes are oligotrophic bacteria [62,65]. The organic matter returns increased the soil nutrients, thus reducing the relative abundance of Clostridia and Bacteroidia; the decomposed cattle matter had higher nutrients than other organic matter, and the relative abundance of Bacteroidia was significantly decreased in the DM treatment. Anaerolinea is a member of the class Anaerolineae, and Anaerolineae plays an important role in organic matter decomposition [67]. The organic matter returns provided carbon sources for soil microbes and promoted the relative abundance of Anaerolineae and Anaerolinea (Figure 7 and Figure S7), which were significantly increased in the DS and DM treatments. The organic matter returns increased the relative abundance of C-cycling bacteria, the organic matter returned was decomposed and turned into SOC, and the increased SOC improved the soil’s fertility and maintained the crop productivity in agricultural systems [3].
Hu et al. [68] found that the organic fertilizer application increased the bacterial population of the dissolved inorganic P, while the P fertilizer application had no direct effect in a long-term experiment. Soil phosphate-solubilizing bacteria (PSB) are predominantly represented by Actinobacteria, Proteobacteria and Bacteroidetes at the phylum level, and Alphaproteobacteria, Betaproteobacteria, Gammaproteobacteria and Bacilli, etc. at the class level [69]. Our study showed that compared with the S0 treatment, the organic matter returns had no effect on the relative abundance of Proteobacteria and Gammaproteobacteria, while decreasing the relative abundance of Bacteroidetes and increasing the relative abundance of Actinobacteria and Alphaproteobacteria (Figure 6 and Figure 7). In the results of the LEfSe analyses, the main biomarkers included Bacilli and Pseudomonadaceae (Figure S9), the relative abundance of Bacilli was increased in the SR and RR treatments but decreased in the other treatments, and the organic matter returns (except the BS treatment) reduced the relative abundance of Pseudomonadaceae. The results of Mander et al. [69] showed that Pseudomonadaceae was the most abundant PS family in the low-P soils. In this study, the organic matter returns increased the soil’s P content, which may be the influencing factor on the relative abundance of Pseudomonadaceae in this study. Some bacteria involved in the PSB also play an important role in the C-cycling: the organic matter returns changed the composition of the PSB and Bacteroidetes belonging to oligotrophic bacteria [59] and the organic matter returns increased the SOC content and P content, especially the DM treatment, thus decreasing Bacteroidetes abundance. Actinobacteria and Alphaproteobacteria are the dominant taxa in the C-cycling [65], the organic matter returns increased the relative abundance of C-cycling bacteria, and the relative abundance of Actinobacteria and Alphaproteobacteri increased more in the DM, RR and SR treatments than in the DS and BS treatments. Kucey [70] found that there was no correlation between the soil P content and the PSB. In our study, the variation of PSB abundance was inconsistent with that of the soil’s P content, which was similar to the previous study. The SOC had a greater influence on the relative abundance of the PSB than the soil’s P content. The organic matter returns mainly affected the composition of the microbes participating in the soil’s C and P cycles.

4.6. Relationship between Soil C and P Fractions and Soil Microbial Communities

Dong et al. [19] showed that the soil’s nutrients and soil microbial activity were highly dependent upon each other, and the SOC, TN and TP were important determinant factors affecting soil’s microbial communities. In our study, the SOC fractions and P content all affected the soil’s microbial composition; the contents of the MBC, DOC, and NaOH-P had great influence on the microbial community (Figure 8); and the relative abundance of Actinobacteria and Alphaproteobacteria were increased more in the DM, RR and SR treatments than in the DS and BS treatments. The MBC and DOC were most sensitive to the straw return, straw return changed the composition of the microbes, and the microbial communities were mainly affected by the MBC [40]. The soil’s DOC is a C source for microbes and a higher labile C resulted in higher microbial activity [56]; thus, the DOC also had great influence on the microbial community. The soil’s available P is significantly corrected with bacterial PLFAs [16]. Our results showed that NaOH-P had a greater influence on the microbial community than the other P fractions; the reasons for the different results of these studies need to be further explored. Zhao et al. [66] found that the correlation between soil’s P and the bacterial communities was greater than the SOC. Ding et al. [71] found that the soil’s total P and available P had a greater influence on microbial communities than the soil’s organic matter. In this study, the soil’s P content had a greater effect on the microbial community than the SOC fractions (Figure S10); this result was consistent with previous studies.

5. Conclusions

In this study, the rice straw and decomposed rice straw returns reduced the rice yield in the previous two years and had no effect on the rice yield in the third year. The other treatments had no influence on the rice yield. The organic matter returns promoted the accumulation of SOC and P content, especially the incorporation of rice straw, decomposed rice straw and decomposed cattle manure. The active SOC fractions increased more than soil TOC, and MBC and LFOC were the most sensitive factors. The proportion of nonlabile P was reduced by the organic matter returns, consequently increasing the available P for rice growth. The organic matter returns changed the microbial biomass and composition and increased the relative abundance of C-cycling microbes, especially with rice straw and decomposed cattle manure return. The relative abundance of PSB was increased under rice straw return but decreased in the other treatments, which was mainly affected by the SOC content rather than the soil P content. MBC, DOC, NaOH-Po and NaOH-Pi contents had obvious effects on the microbial community composition. The cattle manure return had the greatest potential to increase the soil nutrients and rice yield. The rice straw return increased soil fertility but decreased rice yield under the short-term return; long-term experiment is still needed to investigate the effect of rice straw on rice yield in the cold region of China.

Supplementary Materials

The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/agronomy13112805/s1: Figure S1: Rarefaction curves of the OTU number at 97% similarity level; Figure S2: Species accumulation box plot; Figure S3: Petal diagram of the number of shared and unique OTUs in different treatments; Figure S4: Microbial richness and alpha diversity index at a 97% identity threshold; Figure S5: Box line plot of dominant microbial phyla; Figure S6: Box line plot of dominant microbial classes. Figure S7: Relative abundance of the dominant microbial genera; Figure S8: Box line plot of dominant microbial genera; Figure S9: LEfSe analysis of microbial different species; Figure S10: Variation partitioning analysis (VPA) analysis of effects of SOC fractions and P fractions on microbial communities.

Author Contributions

Conceptualization, Z.G. and S.Y.; methodology, S.Y.; software, J.L.; validation, Z.G. and Z.Z.; formal analysis, S.Y.; investigation, S.Y. and H.J.; resources, Z.G.; data curation, H.J. and C.Y.; writing—original draft preparation, S.Y.; writing—review and editing, S.Y.; visualization, S.Y.; supervision, C.M.; project administration, Z.G.; funding acquisition, S.Y. All authors have read and agreed to the published version of the manuscript.

Funding

This study was funded by the General Program of the Heilongjiang Provincial Postdoctoral Foundation of China, grant number LBH-Z22077.

Data Availability Statement

The data presented in this study are included within the article.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Xu, X.; Pei, J.; Xu, Y.; Wang, J. Soil organic carbon depletion in global Mollisols regions and restoration by management practices: a review. J. Soils Sediments 2020, 20, 1173–1181. [Google Scholar] [CrossRef]
  2. Xie, Z.; Zhu, J.; Liu, G.; Cadisch, G.; Hasegawa, T.; Chen, C.; Sun, H.; Tang, H.; Zeng, Q. Soil organic carbon stocks in China and changes from 1980s to 2000s. Glob. Chang. Biol. 2007, 13, 1989–2007. [Google Scholar] [CrossRef]
  3. Johnston, A.E.; Poulton, P.R.; Coleman, K. Soil organic matter: its importance in sustainable agriculture and carbon dioxide fluxes. Adv. Agron. 2009, 101, 1–57. [Google Scholar]
  4. Sądej, W.; Żołnowski, A.C. Comparison of the effect of various long-term fertilization systems on the content and fractional composition of humic compounds in Lessive soil. Plant Soil Environ. 2019, 65, 172–180. [Google Scholar] [CrossRef]
  5. Sleutel, S.; Neve, S.D.; Singier, B.; Hofman, G. Organic C levels in intensively managed arable soils–long-term regional trends and characterization of fractions. Soil Use Manag. 2006, 22, 188–196. [Google Scholar] [CrossRef]
  6. Benbi, D.K.; Senapati, N. Soil aggregation and carbon and nitrogen stabilization in relation to residue and manure application in rice–wheat systems in northwest India. Nutr. Cycl. Agroecosyst. 2010, 87, 233–247. [Google Scholar] [CrossRef]
  7. Wang, W.; Lai, D.Y.F.; Wang, C.; Pan, T.; Zeng, C. Effects of rice straw incorporation on active soil organic carbon pools in a subtropical paddy field. Soil Tillage Res. 2015, 152, 8–16. [Google Scholar] [CrossRef]
  8. Yadvinder, S.; Bijay, S.; Timsina, J. Crop residue management for nutrient cycling and improving soil productivity in rice-based cropping systems in the tropics. Adv. Agron. 2005, 85, 269–407. [Google Scholar]
  9. Huang, W.; Wu, J.; Pan, X.; Tan, X.; Zeng, Y.; Shi, Q.; Liu, T.; Zeng, Y. Effects of long-term straw return on soil organic carbon fractions and enzyme activities in a double-cropped rice paddy in South China. J. Integr. Agric. 2021, 20, 236–247. [Google Scholar] [CrossRef]
  10. Yan, D.; Wang, D.; Yang, L. Long-term effect of chemical fertilizer, straw, and manure on labile organic matter fractions in a paddy soil. Biol. Fertil. Soils 2007, 44, 93–101. [Google Scholar] [CrossRef]
  11. Sanyal, S.K.; De Datta, S.K. Chemistry of Phosphorus Transformations in Soil: Advances in Soil Science; Springer: New York, NY, USA, 1991; Volume 16. [Google Scholar]
  12. Malik, M.A.; Marschner, P.; Khan, K.S. Addition of organic and inorganic P sources to soil–Effects on P pools and microorganisms. Soil Biol. Biochem. 2012, 49, 106–113. [Google Scholar] [CrossRef]
  13. Wei, Z.; Wu, J.; Yan, X.; Ni, G. Phosphorus and carbon status of a paddy soil under different fertilization regimes. J. Soils Sediments 2016, 16, 1727–1734. [Google Scholar] [CrossRef]
  14. Gupta, R.K.; Yadvinder, S.; Ladha, J.K.; Bijay, S.; Singh, J.; Singh, G.; Pathak, H. Yield and phosphorus transformations in a rice wheat system with crop residue and phosphorus management. Soil Sci. Soc. Am. J. 2007, 71, 1500–1507. [Google Scholar] [CrossRef]
  15. Regmi, A.P.; Ladha, J.K.; Pathak, H.; Pasuquin, E.; Bueno, C.; Dawe, D.; Hobbs, P.R.; Joshy, D.; Maskey, S.L.; Pandey, S.P. Yield and soil fertility trends in a 20-year rice–rice–wheat experiment in Nepal. Soil Sci. Soc. Am. J. 2002, 66, 857–867. [Google Scholar] [CrossRef]
  16. Zhong, W.; Gu, T.; Wang, W.; Zhang, B.; Lin, X.; Huang, Q.; Shen, W. The effects of mineral fertilizer and organic manure on soil microbial community and diversity. Plant Soil 2010, 326, 511–522. [Google Scholar] [CrossRef]
  17. Wu, M.; Qin, H.; Chen, Z.; Wu, J.; Wei, W. Effect of long-term fertilization on bacterial composition in rice paddy soil. Biol. Fertil. Soils 2011, 47, 397–405. [Google Scholar] [CrossRef]
  18. Sun, J.; Zhang, Q.; Zhou, J.; Wei, Q. Pyrosequencing technology reveals the impact of different manure doses on the bacterial community in apple rhizosphere soil. Appl. Soil Ecol. 2014, 78, 28–36. [Google Scholar] [CrossRef]
  19. Dong, W.; Zhang, X.; Dai, X.; Fu, X.; Yang, F.; Liu, X.; Sun, X.; Wen, X.; Schaeffer, S. Changes in soil microbial community composition in response to fertilization of paddy soils in subtropical China. Appl. Soil Ecol. 2014, 84, 140–147. [Google Scholar] [CrossRef]
  20. Zhao, Y.; Wang, P.; Li, J.; Chen, Y.; Ying, X.; Liu, S. The effects of two organic manures on soil properties and crop yields on a temperate calcareous soil under a wheat–maize cropping system. Eur. J. Agron. 2009, 31, 36–42. [Google Scholar] [CrossRef]
  21. Beri, V.; Sidhu, B.S.; Bahl, G.S.; Bhat, A.K. Nitrogen and phosphorus transformations as affected by crop residue management practices and their influence on crop yield. Soil Use Manag. 1995, 11, 51–54. [Google Scholar] [CrossRef]
  22. Huang, S.; Zeng, Y.; Wu, J.; Shi, Q.; Pan, X. Effect of crop residue retention on rice yield in China: A meta-analysis. Field Crops Res. 2013, 154, 188–194. [Google Scholar] [CrossRef]
  23. Bai, J.; Ouyang, H.; Deng, W.; Zhu, Y.; Zhang, X.; Wang, Q. Spatial distribution characteristics of organic matter and total nitrogen of marsh soils in river marginal wetlands. Geoderma 2005, 124, 181–192. [Google Scholar] [CrossRef]
  24. Lu, R. Methods of Agricultural Chemical Analysis of Soil; China Agricultural Science and Technology Press: Beijing, China, 2000. [Google Scholar]
  25. Yan, S.; Song, J.; Fan, J.; Yan, C.; Dong, S.; Ma, C.; Gong, Z. Changes in soil organic carbon fractions and microbial community under rice straw return in Northeast China. Glob. Ecol. Conserv. 2020, 22, e00962. [Google Scholar] [CrossRef]
  26. Yan, C.; Yan, S.; Jia, T.; Dong, S.; Ma, C.; Gong, Z. Decomposition characteristics of rice straw returned to the soil in northeast China. Nutr. Cycl. Agroecosyst. 2019, 114, 211–224. [Google Scholar] [CrossRef]
  27. Bai, Y.; Wang, L.; Lu, Y.; Yang, L.; Zhou, L.; Ni, L.; Cheng, M. Effects of long-term full straw return on yield and potassium response in wheat-maize rotation. J. Integr. Agric. 2015, 14, 2467–2476. [Google Scholar] [CrossRef]
  28. Vance, E.D.; Brookes, P.C.; Jenkinson, D.S. An extraction method for measuring soil microbial biomass C. Soil Biol. Biochem. 1987, 19, 703–707. [Google Scholar] [CrossRef]
  29. Vieira, F.C.B.; Bayer, C.; Zanatta, J.A.; Dieckow, J.; Mielniczuk, J.; He, Z.L. Carbon management index based on physical fractionation of soil organic matter in an Acrisol under long-term no-till cropping systems. Soil Tillage Res. 2007, 96, 195–204. [Google Scholar] [CrossRef]
  30. Cambardella, C.A.; Elliott, E.T. Particulate soil organic matter change across a grassland cultivation sequence. Soil Sci. Soc. Am. J. 1992, 56, 777–783. [Google Scholar] [CrossRef]
  31. Hedley, M.J.; Stewart, J.W.B.; Chauhan, B.S. Changes in inorganic and organic soil phosphorus fractions induced by cultivation practices and by laboratory incubations. Soil Sci. Soc. Am. J. 1982, 46, 970–976. [Google Scholar] [CrossRef]
  32. Caporaso, J.G.; Lauber, C.L.; Walters, W.A.; Berg-Lyons, D.; Lozupone, C.A.; Turnbaugh, P.J.; Fierer, N.; Knight, R. Global patterns of 16S rRNA diversity at a depth of millions of sequences per sample. Proc. Natl. Acad. Sci. USA 2011, 108 (Suppl. 1), 4516–4522. [Google Scholar] [CrossRef]
  33. Cui, Y.; Meng, J.; Wang, Q.; Zhang, W.; Cheng, X.; Chen, W. Effects of straw and biochar addition on soil nitrogen, carbon, and super rice yield in cold waterlogged paddy soils of North China. J. Integr. Agric. 2017, 16, 1064–1074. [Google Scholar] [CrossRef]
  34. Tanji, K.K.; Gao, S.; Scardaci, S.C.; Chow, A.T. Characterizing redox status of paddy soils with incorporated rice straw. Geoderma 2003, 114, 333–353. [Google Scholar] [CrossRef]
  35. Gao, S.; Tanji, K.K.; Scardaci, S.C. Impact of rice straw incorporation on soil redox status and sulfide toxicity. Agron. J. 2004, 96, 70–76. [Google Scholar] [CrossRef]
  36. Shan, Y.; Cai, Z.; Han, Y.; Johnson, S.E.; Buresh, R.J. Organic acid accumulation under flooded soil conditions in relation to the incorporation of wheat and rice straws with different C:N ratios. Soil Sci. Plant Nutr. 2008, 54, 46–56. [Google Scholar] [CrossRef]
  37. Bhattacharyya, P.; Nayak, A.K.; Shahid, M.; Tripathi, R.; Mohanty, S.; Kumar, A.; Raja, R.; Panda, B.B.; Lal, B.; Gautam, P.; et al. Effects of 42-year long-term fertilizer management on soil phosphorus availability, fractionation, adsorption–desorption isotherm and plant uptake in flooded tropical rice. Crop J. 2015, 3, 387–395. [Google Scholar] [CrossRef]
  38. Zhang, P.; Wei, T.; Li, Y.; Wang, K.; Jia, Z.; Han, Q.; Ren, X. Effects of straw incorporation on the stratification of the soil organic C, total N and C:N ratio in a semiarid region of China. Soil Tillage Res. 2015, 153, 28–35. [Google Scholar] [CrossRef]
  39. Hao, M.; Hu, H.; Liu, Z.; Dong, Q.; Sun, K.; Feng, Y.; Li, G.; Ning, T. Shifts in microbial community and carbon sequestration in farmland soil under long-term conservation tillage and straw returning. Appl. Soil Ecol. 2019, 136, 43–54. [Google Scholar] [CrossRef]
  40. Chen, Z.; Wang, H.; Liu, X.; Zhao, X.; Lu, D.; Zhou, J.; Li, C. Changes in soil microbial community and organic carbon fractions under short-term straw return in a rice–wheat cropping system. Soil Tillage Res. 2017, 165, 121–127. [Google Scholar] [CrossRef]
  41. Liu, M.; Hu, F.; Chen, X.; Huang, Q.; Jiao, J.; Zhang, B.; Li, H. Organic amendments with reduced chemical fertilizer promote soil microbial development and nutrient availability in a subtropical paddy field: The influence of quantity, type and application time of organic amendments. Appl. Soil Ecol. 2009, 42, 166–175. [Google Scholar] [CrossRef]
  42. Johnson, J.M.F.; Barbour, N.W.; Weyers, S.L. Chemical composition of crop biomass impacts its decomposition. Soil Sci. Soc. Am. J. 2007, 71, 155–162. [Google Scholar] [CrossRef]
  43. Wang, D.; Lin, J.Y.; Sayre, J.M.; Schmidt, R.; Fonte, S.J.; Rodrigues, J.L.M.; Scow, K.M. Compost amendment maintains soil structure and carbon storage by increasing available carbon and microbial biomass in agricultural soil—A six-year field study. Geoderma 2022, 427, 116117. [Google Scholar] [CrossRef]
  44. Jiang, B.; Shen, J.; Sun, M.; Hu, Y.; Jiang, W.; Wang, J.; Li, Y.; Wu, J. Soil phosphorus availability and rice phosphorus uptake in paddy fields under various agronomic practices. Pedosphere 2021, 31, 103–115. [Google Scholar] [CrossRef]
  45. Hua, K.; Zhang, W.; Guo, Z.; Wang, D.; Oenema, O. Evaluating crop response and environmental impact of the accumulation of phosphorus due to long-term manuring of vertisol soil in northern China. Agric. Ecosyst. Environ. 2016, 219, 101–110. [Google Scholar] [CrossRef]
  46. Damon, P.M.; Bowden, B.; Rose, T.; Rengel, Z. Crop residue contributions to phosphorus pools in agricultural soils: A review. Soil Biol. Biochem. 2014, 74, 127–137. [Google Scholar] [CrossRef]
  47. Blake, L.; Mercik, S.; Koerschens, M.; Moskal, S.; Poulton, P.R.; Goulding, K.W.T.; Weigel, A.; Powlson, D.S. Phosphorus content in soil, uptake by plants and balance in three European long-term field experiments. Nutr. Cycl. Agroecosyst. 2000, 56, 263–275. [Google Scholar] [CrossRef]
  48. Pagliari, P.H.; Laboski, C.A.M. Dairy manure treatment effects on manure phosphorus fractionation and changes in soil test phosphorus. Biol. Fertil. Soils 2013, 49, 987–999. [Google Scholar] [CrossRef]
  49. Ye, D.; Li, T.; Yu, H.; Chen, G.; Zheng, X.; Li, J. P accumulation of Polygonum hydropiper, soil P fractions and phosphatase activity as affected by swine manure. Appl. Soil Ecol. 2015, 86, 10–18. [Google Scholar] [CrossRef]
  50. Sharma, P.; Mishra, B. Effect of burning rice and wheat crop residues: loss of N, P, K and S from soil and changes in the nutrient availability. J. Indian Soc. Soil Sci. 2001, 49, 425–429. [Google Scholar]
  51. Reddy, D.D.; Kushwaha, S.; Srivastava, S.; Khamparia, R.S. Long-Term Wheat Residue Management and Supplementary Nutrient Input Effects on Phosphorus Fractions and Adsorption Behavior in a Vertisol. Commun. Soil Sci. Plant Anal. 2014, 45, 541–554. [Google Scholar] [CrossRef]
  52. Mao, X.; Xu, X.; Lu, K.; Gielen, G.; Luo, J.; He, L.; Donnison, A.; Xu, Z.; Xu, J.; Yang, W.; et al. Effect of 17 years of organic and inorganic fertilizer applications on soil phosphorus dynamics in a rice–wheat rotation cropping system in eastern China. J. Soils Sediments 2015, 15, 1889–1899. [Google Scholar] [CrossRef]
  53. Yang, X.; Chen, X.; Yang, X. Effect of organic matter on phosphorus adsorption and desorption in a black soil from Northeast China. Soil Tillage Res. 2019, 187, 85–91. [Google Scholar] [CrossRef]
  54. Yang, Z.; Zhang, Y.; Wang, Y.; Zhang, H.; Zhu, Q.; Yan, B.; Fei, J.; Xiangmin, R.; Peng, J.; Luo, G. Intercropping regulation of soil phosphorus composition and microbially-driven dynamics facilitates maize phosphorus uptake and productivity improvement. Field Crops Res. 2022, 287, 108666. [Google Scholar] [CrossRef]
  55. Li, T.; Gao, J.; Bai, L.; Wang, Y.; Huang, J.; Kumar, M.; Zeng, X. Influence of green manure and rice straw management on soil organic carbon, enzyme activities, and rice yield in red paddy soil. Soil Tillage Res. 2019, 195, 104428. [Google Scholar] [CrossRef]
  56. Benbi, D.K.; Brar, K.; Toor, A.S.; Sharma, S. Sensitivity of labile soil organic carbon pools to long-term fertilizer, straw and manure management in rice-wheat system. Pedosphere 2015, 25, 534–545. [Google Scholar] [CrossRef]
  57. Daquiado, A.R.; Kuppusamy, S.; Kim, S.Y.; Kim, J.H.; Yoon, Y.E.; Kim, P.J.; Oh, S.H.; Kwak, Y.S.; Lee, Y.B. Pyrosequencing analysis of bacterial community diversity in long-term fertilized paddy field soil. Appl. Soil Ecol. 2016, 108, 84–91. [Google Scholar] [CrossRef]
  58. Kumar, A.; Kushwaha, K.K.; Singh, S.; Shivay, Y.S.; Meena, M.C.; Nain, L. Effect of paddy straw burning on soil microbial dynamics in sandy loam soil of Indo-Gangetic plains. Environ. Technol. Innov. 2019, 16, 100469. [Google Scholar] [CrossRef]
  59. Wang, J.; Song, Y.; Ma, T.; Raza, W.; Li, J.; Howland, J.G.; Huang, Q.; Shen, Q. Impacts of inorganic and organic fertilization treatments on bacterial and fungal communities in a paddy soil. Appl. Soil Ecol. 2017, 112, 42–50. [Google Scholar] [CrossRef]
  60. Podosokorskaya, O.A.; Bonch-Osmolovskaya, E.A.; Novikov, A.A.; Kolganova, T.V.; Kublanov, I.V. Ornatilinea apprima gen. nov., sp. nov., a cellulolytic representative of the class Anaerolineae. Int. J. Syst. Evol. Microbiol. 2013, 63, 86–92. [Google Scholar] [CrossRef]
  61. Zhang, Q.; Liang, G.; Guo, T.; He, P.; Wang, X.; Zhou, W. Evident variations of fungal and actinobacterial cellulolytic communities associated with different humified particle-size fractions in a long-term fertilizer experiment. Soil Biol. Biochem. 2017, 113, 1–13. [Google Scholar] [CrossRef]
  62. Tian, W.; Wang, L.; Li, Y.; Zhuang, K.; Li, G.; Zhang, J.; Xiao, X.; Xi, Y. Responses of microbial activity, abundance, and community in wheat soil after three years of heavy fertilization with manure-based compost and inorganic nitrogen. Agric. Ecosyst. Environ. 2015, 213, 219–227. [Google Scholar] [CrossRef]
  63. Ward, N.L.; Challacombe, J.F.; Janssen, P.H.; Bernard, H.; Coutinho, P.M.; Martin, W.; Gary, X.; Haft, D.H.; Michelle, S.; Jonathan, B. Three genomes from the phylum Acidobacteria provide insight into the lifestyles of these microorganisms in soils. Appl. Environ. Microbiol. 2009, 75, 2046. [Google Scholar] [CrossRef] [PubMed]
  64. Liu, C.; Ding, N.; Fu, Q.; Brookes, P.C.; Xu, J.; Guo, B.; Lin, Y.; Li, H.; Li, N. The influence of soil properties on the size and structure of bacterial and fungal communities along a paddy soil chronosequence. Eur. J. Soil Biol. 2016, 76, 9–18. [Google Scholar] [CrossRef]
  65. Hu, X.; Gu, H.; Liu, J.; Wei, D.; Zhu, P.; Cui, X.A.; Zhou, B.; Chen, X.; Jin, J.; Liu, X.; et al. Metagenomics reveals divergent functional profiles of soil carbon and nitrogen cycling under long-term addition of chemical and organic fertilizers in the black soil region. Geoderma 2022, 418, 115846. [Google Scholar] [CrossRef]
  66. Zhao, J.; Ni, T.; Li, J.; Lu, Q.; Fang, Z.; Huang, Q.; Zhang, R.; Li, R.; Shen, B.; Shen, Q. Effects of organic–inorganic compound fertilizer with reduced chemical fertilizer application on crop yields, soil biological activity and bacterial community structure in a rice–wheat cropping system. Appl. Soil Ecol. 2016, 99, 1–12. [Google Scholar] [CrossRef]
  67. Petriglieri, F.; Nierychlo, M.; Nielsen, P.H.; McIlroy, S.J. In situ visualisation of the abundant Chloroflexi populations in full-scale anaerobic digesters and the fate of immigrating species. PLoS ONE 2018, 13, e0206255. [Google Scholar] [CrossRef]
  68. Hu, J.; Lin, X.; Wang, J.; Chu, H.; Yin, R.; Zhang, J. Population size and specific potential of P-mineralizing and -solubilizing bacteria under long-term P-deficiency fertilization in a sandy loam soil. Pedobiologia 2009, 53, 49–58. [Google Scholar] [CrossRef]
  69. Mander, C.; Wakelin, S.; Young, S.; Condron, L.; O’Callaghan, M. Incidence and diversity of phosphate-solubilising bacteria are linked to phosphorus status in grassland soils. Soil Biol. Biochem. 2012, 44, 93–101. [Google Scholar] [CrossRef]
  70. Kucey, R.M.N. Phosphate-solubilizing bacteria and fungi in various cultivated and virgin Alberta soils. Can. J. Soil Sci. 1983, 63, 671–678. [Google Scholar] [CrossRef]
  71. Ding, J.; Xin, J.; Ma, M.; Zhou, B.; Guan, D.; Zhao, B.; Jing, Z.; Cao, F.; Li, L.; Li, J. Effect of 35 years inorganic fertilizer and manure amendment on structure of bacterial and archaeal communities in black soil of northeast China. Appl. Soil Ecol. 2016, 105, 187–195. [Google Scholar] [CrossRef]
Agronomy 13 02805 g001
Figure 1. Rice yield from 2017 to 2019. Different letters indicate significant difference at p < 0.05 among treatments. Error bars represent the standard error of the means (n = 3). S0: no rice straw return; SR: rice straw return; DS: decomposed rice straw return; BS: rice-straw-burned return; RR: rice root return; DM: decomposed cattle manure return.
Figure 1. Rice yield from 2017 to 2019. Different letters indicate significant difference at p < 0.05 among treatments. Error bars represent the standard error of the means (n = 3). S0: no rice straw return; SR: rice straw return; DS: decomposed rice straw return; BS: rice-straw-burned return; RR: rice root return; DM: decomposed cattle manure return.
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Figure 2. Available P and total P content in the soil. (a) available P content, (b) total P content. In the comparison between treatments, the different letters indicate significant differences at p < 0.05. Error bars represent standard error of the means (n = 3). S0: no rice straw return; SR: rice straw return; DS: decomposed rice straw return; BS: rice-straw-burned return; RR: rice root return; DM: decomposed cattle manure return.
Figure 2. Available P and total P content in the soil. (a) available P content, (b) total P content. In the comparison between treatments, the different letters indicate significant differences at p < 0.05. Error bars represent standard error of the means (n = 3). S0: no rice straw return; SR: rice straw return; DS: decomposed rice straw return; BS: rice-straw-burned return; RR: rice root return; DM: decomposed cattle manure return.
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Figure 3. The P fraction content and the percentage of P fractions in the soil. (a) H2O-P content, (b) NaHCO3-Pi content, (c) NaHCO3-Po content, (d) NaOH-Pi content, (e) NaOH-Po content, (f) HCl-P content, (g) residual-P content, (h) percentage of P fractions. In the comparison between treatments, the different letters indicate significant differences at p < 0.05. Error bars represent standard error of the means (n = 3). S0: no rice straw return; SR: rice straw return; DS: decomposed rice straw return; BS: rice-straw-burned return; RR: rice root return; DM: decomposed cattle manure return.
Figure 3. The P fraction content and the percentage of P fractions in the soil. (a) H2O-P content, (b) NaHCO3-Pi content, (c) NaHCO3-Po content, (d) NaOH-Pi content, (e) NaOH-Po content, (f) HCl-P content, (g) residual-P content, (h) percentage of P fractions. In the comparison between treatments, the different letters indicate significant differences at p < 0.05. Error bars represent standard error of the means (n = 3). S0: no rice straw return; SR: rice straw return; DS: decomposed rice straw return; BS: rice-straw-burned return; RR: rice root return; DM: decomposed cattle manure return.
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Figure 4. Pearson correlation coefficients between the rice yield and the soil’s P and C fractions (n = 18). * p < 0.05, ** p < 0.01 and *** p < 0.001 indicate significant correlations. Y1: rice yield in 2017; Y2: rice yield in 2018; Y3: rice yield in 2019.
Figure 4. Pearson correlation coefficients between the rice yield and the soil’s P and C fractions (n = 18). * p < 0.05, ** p < 0.01 and *** p < 0.001 indicate significant correlations. Y1: rice yield in 2017; Y2: rice yield in 2018; Y3: rice yield in 2019.
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Figure 5. Principal coordinate analysis (PCoA) and cluster tree of microbial diversity based on unweighted UniFrac distances (a) PCoA, (b) cluster tree at the phylum level. S0: no rice straw return; SR: rice straw return; DS: decomposed rice straw return; BS: rice-straw-burned return; RR: rice root return; DM: decomposed cattle manure return.
Figure 5. Principal coordinate analysis (PCoA) and cluster tree of microbial diversity based on unweighted UniFrac distances (a) PCoA, (b) cluster tree at the phylum level. S0: no rice straw return; SR: rice straw return; DS: decomposed rice straw return; BS: rice-straw-burned return; RR: rice root return; DM: decomposed cattle manure return.
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Figure 6. Relative abundance of the dominant microbial phyla. S0: no rice straw return; SR: rice straw return; DS: decomposed rice straw return; BS: rice-straw-burned return; RR: rice root return; DM: decomposed cattle manure return.
Figure 6. Relative abundance of the dominant microbial phyla. S0: no rice straw return; SR: rice straw return; DS: decomposed rice straw return; BS: rice-straw-burned return; RR: rice root return; DM: decomposed cattle manure return.
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Figure 7. Relative abundance of the dominant microbial classes. S0: no rice straw return; SR: rice straw return; DS: decomposed rice straw return; BS: rice-straw-burned return; RR: rice root return; DM: decomposed cattle manure return.
Figure 7. Relative abundance of the dominant microbial classes. S0: no rice straw return; SR: rice straw return; DS: decomposed rice straw return; BS: rice-straw-burned return; RR: rice root return; DM: decomposed cattle manure return.
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Figure 8. Canonical correspondence analysis (CCA) of the SOC fractions, P contents and soil microbial community composition at the phylum level. S0: no rice straw return; SR: rice straw return; DS: decomposed rice straw return; BS: rice-straw-burned return; RR: rice root return; DM: decomposed cattle manure return.
Figure 8. Canonical correspondence analysis (CCA) of the SOC fractions, P contents and soil microbial community composition at the phylum level. S0: no rice straw return; SR: rice straw return; DS: decomposed rice straw return; BS: rice-straw-burned return; RR: rice root return; DM: decomposed cattle manure return.
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Table 1. The nutrient content of organic matter (g kg−1).
Table 1. The nutrient content of organic matter (g kg−1).
Organic Matter ReturnedTotal PTotal NTotal KTOC
Rice straw1.1611.1315.40419.34
Decomposed rice straw0.529.250.60431.79
Rice straw ash8.979.8071.27134.62
Decomposed cattle manure8.1017.5310.54216.79
Rice root1.606.652.00431.70
Table 2. The contents of the soil’s TOC and active SOC fractions.
Table 2. The contents of the soil’s TOC and active SOC fractions.
TreatmentsTOC
(g kg−1)		LFOC
(g kg−1)		LOC
(g kg−1)		POC
(g kg−1)		DOC
(mg kg−1)		MBC
(mg kg−1)
S022.88 ± 0.38 cd2.06 ± 0.13 d5.05 ± 0.01 a4.71 ± 0.21 b341.43 ± 2.80 c55.97 ± 0.66 d
SR25.16 ± 0.53 a3.89 ± 0.15 a5.61 ± 0.61 a6.63 ± 0.17 a389.18 ± 2.74 b102.81 ± 2.61 b
DS24.17 ± 0.44 ab3.38 ± 0.40 ab5.78 ± 0.11 a6.03 ± 0.31 a385.92 ± 2.32 b104.74 ± 1.32 b
BS22.24 ± 0.27 d2.82 ± 0.23 bc5.27 ± 0.13 a5.14 ± 0.20 b337.55 ± 5.35 c45.82 ± 1.75 e
RR23.46 ± 0.34 bc2.16 ± 0.11 cd5.08 ± 0.04 a4.73 ± 0.16 b347.30 ± 2.30 c73.52 ± 4.14 c
DM24.74 ± 0.13 a3.67 ± 0.16 a5.68 ± 0.09 a6.51 ± 0.18 a432.97 ± 3.10 a115.56 ± 1.30 a
Comparison between treatments: different letters indicate significant differences at p < 0.05. Values are means ± standard errors (n = 3). S0: no rice straw return; SR: rice straw return; DS: decomposed rice straw return; BS: rice-straw-burned return; RR: rice root return; DM: decomposed cattle manure return.
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Yan, S.; Jiang, H.; Li, J.; Yan, C.; Ma, C.; Zhang, Z.; Gong, Z. Effect of Short-Term Organic Matter Returns on Soil Organic Carbon Fractions, Phosphorus Fractions and Microbial Community in Cold Region of China. Agronomy 2023, 13, 2805. https://doi.org/10.3390/agronomy13112805

AMA Style

Yan S, Jiang H, Li J, Yan C, Ma C, Zhang Z, Gong Z. Effect of Short-Term Organic Matter Returns on Soil Organic Carbon Fractions, Phosphorus Fractions and Microbial Community in Cold Region of China. Agronomy. 2023; 13(11):2805. https://doi.org/10.3390/agronomy13112805

Chicago/Turabian Style

Yan, Shuangshuang, Haowen Jiang, Jinwang Li, Chao Yan, Chunmei Ma, Zhongxue Zhang, and Zhenping Gong. 2023. "Effect of Short-Term Organic Matter Returns on Soil Organic Carbon Fractions, Phosphorus Fractions and Microbial Community in Cold Region of China" Agronomy 13, no. 11: 2805. https://doi.org/10.3390/agronomy13112805

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