This study was performed on the experiment farm at Southwest University, Chongqing, China (29°81′N, 106°41′E; elevation 244 m). The soil type was classified as purple soil (dystric regosols) on dry land (Liu et al., 2022). Before the study, the soil pH was 6.0, the soil moisture content was 23.73%, the soil organic matter (SOM) content was 18.62 g.kg⁻¹, and the soil total and available nitrogen contents were 1.065 g·kg⁻¹ and 99.35 mg^.kg⁻¹, respectively.

The cultivation pattern was wheat–maize–soybean rotation–intercropping, with the following details: each plot area was 28.8 m² (3.6 m × 8 m) and divided into eight strips (3.6 m × 1 m), with two crops intercropping in separate strips of the same plot, and each crop was planted four strips per plot. Wheat–maize intercropped from 20 April to 9 May 2019, following which soybean was cycled in wheat strips, and maize–soybean intercropped from 11 May to 14 August 2019. Maize seedlings were nurtured in a 25°C incubator (15,000 lx light intensity, 70% humidity) for 7 days before being planted in the field on March 20, and each strip grew two rows with ten seedlings per row. Wheat was grown from 2 November 2018 to 9 May 2019, with soybean planted in wheat strips on May 11. Three mulch amounts of wheat straw were designed, i.e., CK (0 kg·hm⁻² straw mulch amount), S1 (2,250 kg·hm⁻² straw mulch amount), and S2 (4,500 kg·hm⁻² straw mulch amount). The wheat straw was cut into ~20 cm long pieces and evenly covered on the maize field on May 23, using a randomized block design with three repetitions for a total of nine plots. The basic fertilizers were applied with a compound fertilizer of 750 kg·hm⁻² (including N 15%, P₂O₅ 15%, and K₂O 15%) and urea of 150 kg·hm⁻².

During the pustulation stage (26 June 2019), samples of maize rhizosphere and non-rhizosphere soils were obtained. With five plants per plot, by shaking the maize root to remove loose dirt, only soil attached to the root surface at 0–2 mm was preserved as rhizosphere soil samples. To sample the non-rhizosphere soil, a 0–15 cm soil layer was dug between the maize rows. Impurities were removed from the soils by passing the sample through a 2 mm mesh sieve. A portion of each soil sample was stored at −80°C for sequencing, another portion was stored at 4°C and used to determine the microbial carbon source metabolism and MBC, and the rest portion of the soil samples was air-dried for measuring the physical and chemical properties.

Soil DNA was extracted by using the Fast DNA^® SPIN Kit for Soil (MP Biomedicals, California, USA). The extracted DNA quality was measured by using a NanoDrop 2000 UV-Vis spectrophotometer (Thermo Scientific, Wilmington, USA; OD260/280 = 1.86–1.93, and the total DNA concentration range was 29.3–54.0 ng·μl⁻¹). The hypervariable regions of bacterial V3–V4 and fungal ITS1 were amplified by using a thermocycler PCR system (GeneAmp^® 9700, ABI, USA). The amplified primers of bacteria and fungi were 338F (5′-ACTCCTACGGGAGGCAGCAG-3′) and 806R (5′-GGACTACHVGGGTWTCTAAT-3′) (Xu et al., 2016), and ITS1F (5′-CTTGGTCATTTAGAGGAAGTAA-3′) and ITS2R (5′-GCTGCGTTCTTCATCGATGC-3′) (Adams et al., 2013), respectively. The PCR reaction mixture was as follows: 0.4 μl of FastPfu polymerase (TransGen AP221-02), 4 μl of 5 × FastPfu Buffer, 2 μl of 2.5 mM dNTPs, 0.8 μl of forwarding primer (5 μM), 0.8 μl of reverse primer (5 μM), 0.2 μl of BSA, 10 ng of template DNA, and added ddH₂O to 20 μl. The PCR amplification conditions were pre-denaturation at 95°C for 3 min, then denaturation at 95°C for 30 s, annealing at 55°C for 30 s, and elongation at 72°C for 45 s as a cycle (bacteria and fungi performed 28 and 36 cycles, respectively), and extension at 72°C for 10 min (PCR, ABI GeneAmp^® type 9700). AxyPrep DNA Gel Extraction Kit (Axygen Biosciences, Union City, CA, USA) was used to purify PCR products, and QuantiFluorTM-ST (Promega, USA) was used to quantify DNA.

Illumina's MiSeq PE300 platform was used for amplicon sequencing (Majorbio Biopharmaceutical Technology Co. LTD, Shanghai, China). The Trimmomatic was used to control the quality of original sequence fastq files, and then, the forward and reverse sequences were merged by Flash software (https://ccb.jhu.edu/software/FLASH/index.shtml) in the Mothur platform (Magoč and Salzberg, 2011). The UPARSE software (version 7.1 http://drive5.com/uparse/) was used to cluster the operational taxonomic units (OTUs) at the 97% sequence similarity level, where the singleton and chimera sequences were discarded. RDP Classifier (http://rdp.cme.msu.edu/) was performed to analyze the taxonomy of each 16S DNA and ITS sequence. In total, we obtained 443,448 bacterial sequences and 662,382 fungi sequences from 18 soil samples. Using a 97% similarity cutoff, we further clustered those sequences into 6,095 OTUs for bacteria (Silva: Release138 http://www.arb-silva.de) and 3,168 OTUs for fungi (Unite: Release 8.0 http://unite.ut.ee/index.php), respectively.

The Biology ECO-plate (Biology, Hayward, CA), including 31 of the most useful labile carbon substrates, could express the carbon source metabolism characteristics of microbial communities (Guo et al., 2020). The incubation and calculating procedures were detailed in our previous study (Liu et al., 2022). The average well-color development (AWCD) was used to calculate the microbial carbon source usage in each microplate as follows: AWCD = ∑(OD_i – R)/31, where OD_i represents the absorbance value of each hole except the control hole, and R represents the control hole absorbance value.

The soil MBC was measured by using a chloroform fumigation-extraction method (Vance et al., 1987). The soil POC and ROC were determined by sodium hexametaphosphate dispersion and the KMnO₄ oxidation method, respectively (Li et al., 2015; Hao et al., 2022). Soil total organic carbon (TOC), DOC, and dissolved organic nitrogen (DON) contents were determined using a TOC analyzer (TOC-L; Shimadzu, Kyoto, Japan) (Moon et al., 2019). The soil ammonium nitrogen (AMN) and nitrate nitrogen (NN) contents were tested by the MgO diffusion method and ultraviolet spectrophotometry, respectively (Holmes et al., 1998). The contents of soil total nitrogen (TN) and available nitrogen (AN) were determined by the Kjeldahl method and alkaline hydrolysis diffusion method, respectively (Athalye-Jape et al., 2020; Li et al., 2021).

To measure cellulase activity, 10 g of the soils were incubated with 20 ml of 1% carboxymethyl cellulose solution, 5.0 ml of phosphate buffer (pH = 5.5), and 1.5 ml of methylbenzene for 72 h at 37°C. The released glucose was estimated by the 3, 5-dinitro salicylic acid colorimetry (DNS) method and was expressed in terms of milligrams of Glucose Equivalents per kg of soil per 72 h (mg/kg) (Guan et al., 1986). Similarly, the DNS was used to measure amylase and sucrase activity, which was quantified in milligrams of Glucose Equivalents per gram of soil every 24 h (mg/g) (Guan et al., 1986). The potassium permanganate titration technique was used to assess catalase activity, which was represented in milliliters of KMnO₄ reduction per gram of soil per hour (ml/g) (Guan et al., 1986). The ninhydrin colorimetry technique was used to assess protease activity, which was expressed in milligrams of NH₂-N per gram of soil every 24 h (mg/g) (Guan et al., 1986). Urease activity was measured using the sodium phenolate-sodium hypochlorite colorimetry technique, and it was represented in milligrams of NH₃-N per gram of soil per 24 h (mg/g) (Guan et al., 1986).

Soil organic acids were extracted by a 0.1% H₃PO₄ aqueous solution. In brief, 5 g wet soil was dissolved in 10 ml 1% H₃PO₄ aqueous solution by shaking for 1 min at room temperature, then 5,000 r/min centrifuged 5 min. The suspension was filtered through 0.45 μm filter membranes for HPLC (Shimadzu prominence UFLC, LC 20 AD, Kyoto, Japan. C18 column: Shim-pack GIST, 4.6 × 250 mm, 5 μm) analysis. Mobile phases A and B were 0.1% H₃PO₄ deionized water and acetonitrile with a volume ratio of 98:2, respectively. The detecting ultraviolet wavelength was 210 nm, and the flow rate was maintained at 1 ml/ min. The injection volume was set at 20 μl, and the column temperature was kept constant at 25°C. Finally, by comparing retention durations and areas with pure standards, the organic acids were identified and quantified. Oxalic acid (OA), citric acid (CA), malic acid (MIA), malonic acid (MOA), and succinic acid (SA) were all found in our investigation, but lactic acid, propionic acid, acetic acid, and tartaric acid were not.

The alpha diversity and richness of the microbial community were calculated through the Tukey test of ANOVA analysis to compare the differences within samples, including the indexes of Chao 1, Shannon, Simpson, and others. Based on the Bray–Curtis distance matrix, the non-metric multidimensional scaling (NMDS) and Adonis analysis were generated by the R package of “vegan” to evaluate the microbial community structure variation (Oksanen et al., 2016). The microbial relative abundance was calculated based on the OTU tables, and the R package of “pheatmap” was used to build the heatmap of the microbial community relative abundance and carbon sources metabolism (Kolde, 2019). In addition, the volcano plot of enrichment and depletion OTUs was drawn using the R package “ggplot2” based on the OTUs computation results of the R package of “DESeq2” (Love et al., 2014; Wickham, 2016; Li et al., 2017). We employed the FAPROTAX database platform (http://mem.rcees.ac.cn:8080/) to predict functions of bacterial biogeochemical cycles, such as carbon, nitrogen, and sulfur cycle, as well as other ecological functions (Zhang et al., 2019; Yu et al., 2021). The FUNGuild database was used to predict fungal ecological function traits, which primarily include three trophic modes of the fungal community: pathotroph (by harming host cells to receive nutrients), symbiotroph (by exchanging resources with host cells to receive nutrients), and saprotroph (by breaking down dead host cells to receive nutrients) (Tedersoo et al., 2014; Nguyen et al., 2016). The changing curves of AWCD values of the Biology ECO-plate were created by R software. The Tukey–Kramer of ANOVA was performed to test the differences in microbial functions, soil carbon, nitrogen fractions, soil enzyme activity, and soil organic acid contents among multiple groups. The bubble chart of soil factors was created by R packages of “ggpubr.” The heatmap between bacterial biogeochemical functions and family lever communities was generated by R packages of “reshape,” “psych,” “ggtree,” “dplyr,” “tidyverse,” and “aplot” (Yu et al., 2018; Liu et al., 2022; Revelle, 2022). The Mantel test was used to analyze the relationship among microbial communities at the phylum level and soil carbon and nitrogen fractions, soil enzyme activity, and soil organic acids contents with straw mulch.

The “piecewiseSEM” of the R package was used to create the structural equation model (SEM) among microbial structure and soil carbon and nitrogen fractions, soil enzyme activity, and soil organic acid contents (Lefcheck, 2016). The first principal component of principal coordinate analysis (PCoA) of microbial communities was used based on OTUs to represent the microbial community structure at the SEM (Yang et al., 2021). The SEM was created based on the following hypothesizes: (1) The bacterial and fungal structure changed with the increasing straw mulch amount; (2) the changed bacterial and fungal structure had different contributions to the soil carbon and nitrogen cycle; (3) the soil enzyme activity and organic acid content induced by the changing microbial community would affect soil carbon and nitrogen pools. Finally, we chose the goodness of fit model according to the P-value and Akaike information criterion (AIC) value of models.

Within-sample diversity data revealed that two different quantities of straw mulch enhanced alpha diversity of the microbial community in maize rhizosphere and non-rhizosphere soil although not significantly (P = 0.63 and P = 0.067, respectively; Table 1; Supplementary Table S1). Otherwise, there was a significant difference in microbial community richness in maize non-rhizosphere soil (P = 0.048; Table 1). Furthermore, the NMDS analysis results of microbiological community abundance illustrated that the bacterial and fungal communities were reshaped remarkably into different individual groups by straw mulch amounts in maize rhizosphere and non-rhizosphere (P = 0.01), which were separated along the first coordinate axis (Figures 1C, D), indicating that both straw mulch and its amount disturbed the microbiota in maize rhizosphere and non-rhizosphere. In addition, the Adonis analysis results demonstrated that bacterial and fungal community compositions changed significantly by the increasing straw mulch amount in the maize rhizosphere (R² = 0.56, P = 0.005; R² = 0.65, P = 0.002) and non-rhizosphere soil (R² = 0.35, P = 0.004; R² = 0.47, P = 0.009; Table 1). Moreover, the volcano plot results of enrichment and depletion OTUs revealed that increasing straw mulch amounts increased the upregulated and downregulated population numbers of bacterial (Supplementary Figures S1A–C) and fungal (Supplementary Figures S1D–F) communities in maize rhizosphere soil. The fungal population in the non-rhizosphere exhibited the same results (Supplementary Figures S1J–L). In addition, the influence of straw mulch amount on microbial population structure was stronger for fungi than bacteria in maize rhizosphere and non-rhizosphere soil (Supplementary Figure S1).

The difference in maize soil microbiota among the straw mulch treatments was significant and detectable at the phylum level. Raising straw mulch amounts reduced the relative abundances of Proteobacteria and Firmicutes while increasing the relative abundances of Acidobacteria, Chloroflexi, Verrucomicrobia, and Planctomycetes in maize rhizosphere soil (Figure 1A). More specifically, the relative abundance of Bacteroidetes in treatment S1 was considerably greater than CK (P = 0.04) and S2 (P = 0.005), whereas the relative abundance of Firmicutes in treatment S2 was significantly lower than S1 (P = 0.04) and CK (P = 0.003) in maize rhizosphere soil (Figure 1A; Supplementary Table S2). Simultaneously, compared to CK, treatment S1 increased the relative abundance of Gemmatimonadetes (P = 0.04), whereas treatment S2 decreased the relative abundance of Planctomycetes (P = 0.04) in maize non-rhizosphere soil (Figure 1A; Supplementary Table S2). For the fungal community, in comparison with CK, the treatments S1 and S2 significantly reduced the relative abundance of Ascomycota (P = 0.04 and P = 0.001, respectively) while significantly increasing the relative abundance of Basidiomycota (P = 0.002 and P = 0.004, respectively) in maize rhizosphere soil (Figure 1B; Supplementary Table S3). Nevertheless, the relative abundance of Ascomycota and Basidiomycota in maize non-rhizosphere soil was raised marginally by the raising straw mulch amount (P > 0.05; Figure 1B; Supplementary Table S3).

Furthermore, the heatmap results of species relative abundance at the family level showed that the treatments S1 and S2 enriched more types of bacterial communities than CK in maize rhizosphere and non-rhizosphere soil (Supplementary Figures S2A, B). In particular, the treatments S1 and S2 increased the relative abundance of Acetobacteraceae, Acidothermaceae, Caulobacteraceae, Chitinophagaceae, Rhodanobacteraceae, and others in maize rhizosphere and non-rhizosphere soil while decreasing the relative abundance of Moraxellaceae (Supplementary Figures S2A, B). The treatment S2 was the most beneficial for enriching multiple kinds of the fungal community in the maize rhizosphere and non-rhizosphere soil, and it greatly enhanced the relative abundance of Chaetomiaceae, Chaetosphaeriaceae, Hydnodontaceae, Trichosphaeriaceae, Hypocreales_fam_Incertae_sedis, and others (Supplementary Figures S2C, D).

Our study demonstrated that applying and increasing straw mulch amounts cannot significantly change soil TN and TOC in maize rhizosphere and non-rhizosphere soils, as well as their ratio (P > 0.05; Figures 2A–C, F–H). Otherwise, the treatment S2 significantly increased the labile C fractions of ROC, MBC, and POC (Figure 2A) and labile N fractions of DON, AN, AMN, and NN (Figure 2C) in maize non-rhizosphere soil (P < 0.05). Simultaneously, treatments S1 and S2 substantially enhanced those soil enzymes related to C or N degradation such as protease, cellulase, amylase, and sucrase activities in the maize non-rhizosphere soil compared to CK (P < 0.05; Figure 2D). Compared with maize non-rhizosphere soil, the straw mulch had a smaller effect on labile C and N fractions and related enzyme activities in maize rhizosphere soil. In detail, the ROC, MBC (Figure 2F), and AN (Figure 2G) in the maize rhizosphere were outstandingly raised by the increasing straw mulch amount (P < 0.05). On the contrary, the DOC (Figures 2A, F) and DOC/DON (Figures 2C, H) ratio markedly decreased by the increasing straw mulch amounts in maize rhizosphere and non-rhizosphere soil (P < 0.05). In addition, in maize rhizosphere soil, the cellulase, sucrase, and catalase activities of the treatment S2 were significantly higher than CK (P < 0.05), whereas straw mulch had no significant effect on soil amylase, protease, or urease activity (Figure 2I). Furthermore, the content of succinic acid, oxalic acid, and malonic acid outstanding improved with increasing straw mulch amounts in maize non-rhizosphere (P < 0.05; Figure 2E), as well as the content of malic acid and succinic acid in maize rhizosphere (P < 0.05; Figure 2J).

We assessed the carbon source consumption efficiency of the microbial community, which was boosted by varying the quantity of straw mulch used (Figure 3; Supplementary Figure S3). The results showed that increasing the amount of straw mulch lowered the microbial utilization ratio of carbohydrates, esters, amino acids, carboxylic acids, and amines in maize rhizosphere and non-rhizosphere soil (Figures 3A, B). Compared with CK, the treatments S1 and S2 significantly decreased the carbohydrate metabolism ratio of microorganisms in maize rhizosphere soil (P < 0.05; Figure 3A), and the treatment S2 remarkably cut down the carboxylic acid metabolism ratio of microorganisms in maize non-rhizosphere soil (P < 0.05; Figure 3B). More specifically, compared with CK, the S1 treatment remarkably reduced the metabolism ratio of L-phenylalanine and glycyl-L-glutamic acid by microorganisms in maize rhizosphere and non-rhizosphere, respectively (P < 0.05; Figure 3C). The treatment S2 significantly decreased the utilization ratio of glycogen, D-galactonic acid γ-lactone, L-phenylalanine, and L-threonine by microorganisms in maize rhizosphere and α-ketobutyric acid in maize non-rhizosphere soil (P < 0.05; Figure 3C).

This study analyzed the functions of the bacterial biogeochemical matter cycle based on the FAPROTAX database. The results showed that performing straw mulch remarkably promoted the processes of chemoheterotrophy, aerobic chemoheterotrophy, ureolysis, and nitrogen fixation of the bacterial community in maize rhizosphere soil, while significantly inhibiting the processes of fermentation and nitrate reduction (P < 0.05; Figure 4A; Supplementary Table S4). The cellulolysis was also marginally raised by increasing the straw mulch amount in maize rhizosphere and non-rhizosphere soil (Figure 4A; Supplementary Figure S5A). Nonetheless, there was no substantial variation in these bacterial community functions in maize non-rhizosphere soil with straw mulch application (P > 0.05; Supplementary Figure S5A; Supplementary Table S5). Furthermore, the Pearson correlation analysis was performed between dominant bacterial communities and the environmental functions (Figure 4C; Supplementary Figure S5C). The findings revealed that chemoheterotrophy, aerobic chemoheterotrophy, ureolysis, nitrogen fixation, and cellulolysis had a significant positive correlation with the relative abundance of Acetobacteraceae, Burkholderiaceae, Xanthobacteraceae, Chitinophagaceae, Caulobacteraceae, SC-I-84, and Rhodanobacteraceae while having a significant negative correlation with the relative abundance of Enterobacteriaceae, Moraxellaceae, Streptococcaceae, and Pseudomonadaceae in the maize rhizosphere (P < 0.05; Figure 4C). Nevertheless, the fermentation, nitrate reduction, and aromatic compound degradation all showed contrary associations with the aforementioned species compared with the above functions (P < 0.05; Figure 4C). However, the correlation between environmental functions and multiple bacterial populations in maize non-rhizosphere did not alter considerably (Supplementary Figure S5C).

Simultaneously, the fungal trophic functions were analyzed by the FUNGuild database. We observed that the main trophic type of the fungal community was saprotroph in maize rhizosphere and non-rhizosphere soil (Supplementary Figure S4). After straw mulch, the endophyte and litter or wood saprotroph proportions raised outstanding in maize rhizosphere and non-rhizosphere soil (P < 0.01; Figure 4B; Supplementary Figure S5B; Supplementary Tables S6, S7). In addition, according to the significant differences in fungal guild type, the corresponding fungal communities in maize rhizosphere soil were selected (Supplementary Figure S6). The results exhibited that straw mulch application increased the relative abundance of Chaetomiaceae, Chaetosphaeriaceae, and Hypocreales_fam_Incertae_sedis, leading to the fungus of litter or wood saprotroph growing in maize rhizosphere soil (Supplementary Figure S6).

The results of the Pearson test showed that straw mulch (MT) had a significant positive correlation with the contents of AN, TOC, ROC, MBC, MIA, SA, and activity of cellulase and catalase in maize rhizosphere soil but a negative correlation with DOC content (P < 0.05; Figure 5A; Supplementary Table S8). The Mantel test results denoted that these soil factors exhibited a significant correlation with the abundance of microbial communities regulated by straw mulch, particularly Firmicutes, Ascomycota, and Basidiomycota (P < 0.05; Figure 5A; Supplementary Table S10). Similar results were presented in maize non-rhizosphere (P < 0.05; Supplementary Figure S7A; Supplementary Tables S9, S10). Hence, we created the piecewise structure equation model based on the Pearson and Mantel test among straw mulch, soil factors, and the microbial community. The model revealed that the straw mulch dominated the fungal community structures to drive the cycle of soil labile C and N (Figure 5B; Supplementary Figure S7B). Straw mulch, in particular, favorably controlled the fungal community structures (R² = 0.96, P < 0.001), considerably increasing the levels of MBC, ROC, AN, MIA, SA, and cellulase activity in the maize rhizosphere soil (P < 0.05; Figure 5B). In addition, the fungal community structures changed by straw mulch positively regulated MBC and DOC indirectly by improving MIA content and cellulase activity in the maize rhizosphere soil, respectively. Otherwise, in the maize rhizosphere soil, the fungal community structure had a direct negative and positive impact on the soil's DOC and ROC contents, respectively, and it directly enhanced soil cellulase activity to indirectly lower ROC contents (Figure 5B). In general, the total effect of the straw mulch on catalase activity was the highest (Figure 5C). The straw mulch positively regulated fungal community structure directly and then indirectly positively drove ROC content to improve catalase activity (Figure 5B).

For the maize non-rhizosphere soil, the regulation of microbial community structures changed by straw mulch was weaker than in rhizosphere soil, and it was the same for soil C and N components (Figure 5; Supplementary Figure S7). The straw mulch had a positive correlation with fungal community structure in non-rhizosphere soil (R² = 0.92, P < 0.001; Supplementary Figure S7), whereas the fungal community structure had a significant direct positive effect on the activity of amylase and protease, along with AN and NN content, and indirectly affected AMN by regulating protease (P < 0.05; Supplementary Figure S7). Meanwhile, the fungal community structure indirectly improved MBC content and cellulase activity by enhancing amylase and protease activity in the non-rhizosphere soil, respectively (P < 0.05; Supplementary Figure S7). The total effect of piecewiseSEM revealed that straw mulch had a detrimental influence on DOC content in the non-rhizosphere. This result indicated that straw mulch principal positively regulated fungal community structure, thereby improving the amylase activity to enhance the MBC fraction and reduce DOC content (Supplementary Figures S7B, C).

In our study, straw mulch marginally increased the alpha diversity of bacterial and fungal communities in maize rhizosphere and non-rhizosphere soil but not significantly. It is consistent with previous studies that found straw mulch had no effect on alpha diversity indices of soil bacterial and fungal communities but changed the microbial community composition (Zheng et al., 2018; Liu et al., 2021). This suggests that applying straw mulch for the short term will not disrupt the balance of soil native microbial species diversity. Otherwise, increasing the quantity of straw mulch dramatically affected the bacterial and fungal community structures and produced various independent microbial groups in the maize rhizosphere and non-rhizosphere soil. Similarly, recent research indicated that straw mulch significantly altered the organization of the soil microbial population in the wheat and rape field (Zhou et al., 2019; Liu et al., 2022). We further observed that the upregulated and downregulated population numbers of the microbial community were raised by increasing straw mulch amounts in both the maize rhizosphere and non-rhizosphere, in line with previous research that the change in microbial community structure induced by straw mulch amounts may be a foodweb competition mechanism because straw provides multiple nutrition matters such as the input of carbon and nitrogen (Kou et al., 2020; Song et al., 2020). Generally, fungi primarily decompose recalcitrant soil organic matter, while bacteria are more vital in the mineralization of labile fractions (Lindahl and Tunlid, 2015; Fu et al., 2019). As a result, fungi showed significant changes in species abundance under straw mulch than bacteria because fungal communities are adept at degrading lignin, cellulose, and hemicellulose, all of which are abundant in wheat straw (Cong et al., 2020; Tufail et al., 2021).

At the bacterial phylum level, we observed that the relative abundance of Firmicutes was significantly reduced from 3 to 0.87% by increasing the straw mulch amount in the soil of the maize field, which could produce urease and/or catalase and promote soil nitrogen cycle (Ren et al., 2018; Zhang et al., 2021). At the fungal phylum level, most previous studies confirmed that the Ascomycota, along with a few basidiomycetous fungi, dominate during the early stages of litter decay, with the Ascomycota gradually being replaced by the Basidiomycota during the later stages of litter decomposition (Frankland, 1998; Osono and Takeda, 2002; Osono, 2007; Eichlerová et al., 2015). During the litter degradation process, synergistic matters that relay between Ascomycota and Basidiomycota may be triggered by breakdown products induced at different stages (Taylor, 2001; Watkinson, 2016). Similarly, we found that the relative abundance of Ascomycota significantly decreased from 81 to 66% by increasing the straw mulch amount in the soil of the maize field, whereas the relative abundance of Basidiomycota significantly increased from 8 to 22%, indicating that increasing straw mulch amount could accelerate the succession process of the fungal community in the soil of the maize field. In addition, earlier research has revealed that soil ecological niche is also a crucial factor for microbial community structure (Dumbrell et al., 2010). In line with prior research, we discovered that the bacterial and fungal community composition with straw mulch, as well as their succession rules, differed between maize rhizosphere and non-rhizosphere soil. It might be disturbed by the activity of the maize root system, such as the production of root-system excretions, resulting in a soil ecological environment distinction between the rhizosphere and non-rhizosphere (Khan et al., 2009).

Wheat straws are rich in C and N fractions, including cellulose, hemicellulose, lignin, and protein (Khan and Mubeen, 2012; Zhong et al., 2020). Therefore, applying wheat straw mulch can reshape the soil microbial food web due to the input of C and N sources, sequentially leading to a change in the community composition and function of the microbiome (Mendes et al., 2014; Cobellis et al., 2016). In our study, straw mulch significantly increased the processes of bacterial chemoheterotrophy and aerobic chemoheterotrophy in maize rhizosphere soil, proving that a large number of bacteria obtain carbon and energy by oxidizing organic compounds of straw for their growth (Yu et al., 2021), and implying that straw mulch can stimulate the soil carbon cycle by providing food sources for the bacterial community. Additionally, our study demonstrated that straw mulch outstanding reduced aromatic compound degradation and fermentation bacteria in maize rhizosphere soil, indicating that the bacterial community modified by straw mulch can reduce carbon dioxide and methane emissions, thus benefiting soil carbon fix (Miller and Wolin, 1981; Wang et al., 2020). In addition, soil bacteria affect the soil nitrogen cycle by mediating nitrogen fixation, ammonification, denitrification, nitrification, and nitrate reduction (Yoon et al., 2015). Our study observed that straw mulch remarkably enhanced ureolysis and nitrogen fixation of bacteria in maize rhizosphere soil, whereas it significantly inhibited nitrate reduction. This suggests that straw mulch drives the soil nitrogen cycle by bacteria via two mechanisms. For one thing, straw mulch promoted bacterial ureolysis and nitrogen fixation to increase ammonia by degradation of organic nitrogen compounds such as urea and fixing dinitrogen, respectively (Burton and Prosser, 2001; Kuypers et al., 2018). Then, ammonia can fix ammonium nitrogen and nitrate nitrogen by hydrolysis and oxidization, respectively (Jiang et al., 2016; Kuypers et al., 2018). For another, straw mulch reduced the nitrate reduction of bacteria, thus improving nitrate-nitrogen accumulation in soil (Kuypers et al., 2018). It may be the reason that the content of ammonium and nitrate nitrogen in S1 and S2 was significantly higher than CK in maize non-rhizosphere soil (Figure 2B). Furthermore, the ammonium and nitrate nitrogen that accumulate in the maize rhizosphere soil might be absorbed by maize to promote the nitrogen cycle between soil and plant (Jackson et al., 1989; Li et al., 2013); hence, their contents differed insignificantly across treatments. In addition, most previous studies have illustrated that Proteobacteria, Firmicutes, and Bacteroidetes of bacteria are mostly responsible for driving soil carbon and nitrogen cycle (He et al., 2012; Ren et al., 2018; Zhang et al., 2021). Consistent with previous findings, we discovered that straw mulch accelerated N and C cycling in maize rhizosphere soil by regulating the bacterial community ratio, primarily including Burkholderiaceae (γ-Proteobacteria), Xanthobacteraceae (α-Proteobacteria), Chitinophagaceae (Bacteroidia), Rhodanobacteraceae (γ-Proteobacteria), Caulobacteraceae (α-Proteobacteria), Acetobacteraceae (α-Proteobacteria), Enterobacteriaceae (γ-Proteobacteria), and Streptococcaceae (Firmicutes). These bacteria can enhance the processes of chemoheterotrophy, aerobic chemoheterotrophy, ureolysis, cellulolysis, and nitrogen fixation and inhibit the processes of aromatic compound degradation, fermentation, and nitrate reduction, thereby promoting C and N cycle.

In the meantime, the results of the fungal community functional predictor revealed that adding straw mulch significantly increased the proportion of wood saprotrophs in maize rhizosphere soil, such as Chaetomiaceae and Chaetosphaeriaceae, which could regulate the C cycle by degrading cellulose, hemicellulose, and lignin (Kuramae et al., 2013; Zhang C. et al., 2020; Ferrari et al., 2021). This finding agrees with a recent study that found straw cellulose, hemicellulose, and lignin to be the key food web components that dominated the fungal community structure (He et al., 2022).

Additionally, the results of adding carbon sources incubation showed that the carbon metabolism ratio of the microbial community decreased by the increasing straw mulch amount, especially carbohydrates. There could be two reasons for this outcome. For one thing, straw mulch impacted the fungal community composition more than bacteria in our study, which benefits the metabolism of recalcitrant carbon sources rather than that of soluble carbon sources (Zhong et al., 2018; Cong et al., 2020). For another, the decomposition of straw mulch supplied adequate carbon for the microbial community to flourish, thus reducing their capacity to predation the carbon resource, which implied that more carbon components would be maintained in the soil environment (Huo et al., 2017; Hu et al., 2021). Furthermore, Zhang X. et al. (2020) demonstrated that root hair proliferation strongly influenced enzyme activities, exudate release, and microbial substrate utilization. Consistent with this study, we found that the carbon source metabolism ratio of the microbial community in the rhizosphere soil was higher than in the non-rhizosphere soil, illustrating that the maize root system with straw mulch may promote soil carbon consumption by driving microbial community activity.

Straw mulch delivers diverse nutrient matters to the soil via microorganism degradation and mineralization, and a series of biogeochemical events would vary the ratio of distinct soil C and N components, boosting the soil matter cycle (Guo and Gifford, 2002; Leifeld and Kögel-Knabner, 2005; Yang et al., 2018; Jin et al., 2020). Our study demonstrated that straw mulch mediated the soil C and N fractions by regulating microbial community structures such as Firmicutes, Ascomycota, and Basidiomycota. These microbial communities were reported to be dramatically correlated with SOC fractions (Cong et al., 2020). Previous studies have shown that increasing carbon sequestration could improve soil quality and health while reducing greenhouse gas emissions (Chen et al., 2009; Wang et al., 2018). In our study, soil TOC content was marginally increased by straw mulch (P > 0.05), indicating that the short-term straw mulch had no significant contribution to changing the soil's stable C pool. Whereas straw mulch significantly increased MBC and ROC content while reducing DOC content in maize rhizosphere and non-rhizosphere soil (P < 0.05), these C fractions have been identified as labile soil organic C pools and critical markers of soil quality (Chen et al., 2009; Strosser, 2010). Despite this, the networks of straw mulch that governed labile C pools differed across maize rhizosphere and non-rhizosphere soil. In maize rhizosphere soil, straw mulch positively promoted fungal community structure, thus indirectly positively mediating MBC and ROC while negatively influencing DOC. Otherwise, straw mulch indirectly positively regulated MBC by the positively affected fungal and bacterial community structure in maize non-rhizosphere soil and then the MBC negatively affected DOC. These distinction networks may be related to frequent reports that show plants interact with soil to shape the rhizosphere microbial community, thus changing community functions (Minz et al., 2013; Zolla et al., 2013; Bakker et al., 2015). Additionally, recent research has shown that the fungus Ascomycota and Basidiomycota degrade cellulose by producing multiple cellulases (Kumar et al., 2008; Berka et al., 2011; Strakowska et al., 2014). Similarly, our findings reveal that the dominating fungal communities, Ascomycota and Basidiomycota, altered considerably with straw mulch quantity in maize rhizosphere soil, thereby indirectly regulating ROC and DOC content by directly improving cellulase activity. Furthermore, Chowdhury et al. (2014) indicated that malic acid content was positively associated with soil labile C levels. Consistent with the previous study, we illustrated that straw mulch remarkably enhanced malic acid content by fungal communities intervening in maize rhizosphere soil, thus having a large indirect influence on MBC content. Otherwise, straw mulch had an indirect positive effect on MBC content in maize non-rhizosphere soil by regulating fungal community structure to stimulate amylase activity, which could directly participate in the metabolic process of soil organic matter by catalyzing starch hydrolysis (Sherene, 2017; Ali et al., 2019).

Ammonium and nitrate N are substantial and effective N donors which can be directly taken in by plants (Loo, 1931; Caicedo et al., 2000; Wang et al., 2015). We discovered that the amount of ammonium and nitrate N rose significantly with straw mulch in maize non-rhizosphere soil, but there was no significant difference in rhizosphere soil, although both their contents were greater in rhizosphere soil than in non-rhizosphere soil. This finding suggested that straw mulch could provide maize with extra utilizable nitrogen by enhancing ammonium and nitrate N generation and that the maize root system may promote the N cycle through the consumption of ammonium and nitrate N during the straw degradation process. Moreover, it is becoming increasingly clear that Ascomycota and Basidiomycota populations contribute significantly to the biogeochemical nitrogen cycle in terrestrial ecosystems by participating in the mobilization and mineralization processes of ammonium and nitrate N (Montanini et al., 2002; Gorfer et al., 2011; Maeda et al., 2015). Similarly, we observed that straw mulch directly dominated the fungal community structure in maize non-rhizosphere soil, and as a result, the fungal community structure directly influenced nitrate N and indirectly affected ammonium N by directly impacting protease activity. According to Akhtar et al. (2018), favorable temperature and soil water conditions caused by straw mulch boosted soil available N, which was responsible for improved crop development. In our study, straw mulch indirectly drove the available nitrogen increase in maize rhizosphere and non-rhizosphere soil by directly promoting fungal community structure, especially Ascomycota and Basidiomycota, as well as the Firmicutes of bacteria, which carry genes coding for nitrogen cycles of urease (Zhang et al., 2021) and significantly correlated with the available nitrogen content in maize rhizosphere soil (P = 0.023). Otherwise, total nitrogen had no significant difference among treatments in maize rhizosphere and non-rhizosphere soil. Overall, straw mulch promoted labile C and N pools to drive the C and N cycle by reshaping the structure of Firmicutes, Ascomycota, and Basidiomycota communities in the soil of the maize field.