Green manure intercropping reshapes beneficial microbial consortia to enhance soil multifunctionality and agroecosystem resilience

Green manure intercropping reshapes beneficial microbial consortia to enhance soil multifunctionality and agroecosystem resilience | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Green manure intercropping reshapes beneficial microbial consortia to enhance soil multifunctionality and agroecosystem resilience Gaosen Zhang, Yiming Zhao, Xiaoyi Liu, Xinyue Wang, Jiří Doležan, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7449409/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 4 You are reading this latest preprint version Abstract Intercropping crops with green manure offers a sustainable strategy to reduce nitrogen fertilizer dependency, enhance yields, and improve land use efficiency. While beneficial soil microorganisms are known to be key drivers of improved soil fertility and crop productivity, the differential responses of specific functional microbial communities to agronomic practices and their precise contributions to overall community structure and ecosystem function remain unclear. Here, we investigate how four key functional groups (NPK nutrient absorption [NPK], pathogen antagonism [PA], drought resisting [DR], and plastic degradation [PD]) driver ecosystem functions in a long-term maize-green manure intercropping field experiment. We found that green manure intercropping significantly decreased the Shannon and Simpson diversity and alterd four soil health-associated functional community composition. Moreover, green manure intercropping improved species connections and increased the network’s overall complexity. Crucially, we identified 11 novel core microbial genera with previously unrecognized roles in underpinning soil multifunctionality. Importantly, green manure-driven restructuring of the bacterial community optimizes functional redundancy, offering a novel pathway for the targeted manipulation of microbial communities and the optimization of agroecosystem functions. Intercropping of green manure beneficial microorganisms metagenomes functional genes soil function Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 1. Introduction Ecosystem services such as soil fertility, nutrient cycling, water availability, and pest and disease control are fundamental to the productivity of agroecosystems (Altieri et al., 2012 ). The effectiveness of an agroecosystem is influenced by the decisions and techniques used in agricultural management. Compared to chemical fertilizers, green fertilizers can provide nutrient sources for subsequent crops, offer more organic substrates and carbon resources for microbial growth, increase microbial activity and diversity (Jangid et al., 2008 ), improve soil quality, and boost crop yields(Esperschütz et al., 2007 ). Maize-legume intercropping systems have been shown to provide substantial integrative benefits (Li et al., 2021a ). Over 40% of the Earth's surface is covered by dry and semi-arid regions, home to vast populations relying predominantly on agriculture to meet their basic needs (Golla, 2021 ). Consequently, there is an urgent need to synergize crop production and environmental health improvements in these regions under prolonged resource, environmental, and population pressures (Li et al., 2019 ). In predicting soil health indicators, biological data may outperform physical or chemical soil properties (Wilhelm et al., 2022 ). However, these properties are interrelated, as the microbiome's structure and function are influenced by the soil's chemical and physical characteristics, while the soil's characteristics are also affected by the microbiome. Increasing evidence reveals that soil and beneficial microbial communities provide numerous life-supporting activities for their host plants. Soil microorganisms assist in various functional processes, including nutrient cycling, disease suppression, primary production, and stress resistance. Thus, functional microbial communities in soil play a critical role in ecosystem multifunctionality (EMF) (Han et al., 2022 ; Singh et al., 2021 ), and changes in their abundance are powerful predictors of EMF. Cultivating beneficial microorganisms to improve crop productivity and ecosystem health is considered one of the most promising biotechnological solutions for achieving food security and sustainable agriculture(Xiong and Lu, 2022 ). The stability and functioning of soil microbial communities are highly dependent on the role of key beneficial microorganisms as “core species”. (Banerjee et al., 2016 ; Banerjee et al., 2019 ). These key groups may play a distinct and critical role in organizing the soil microbial community structure, with downstream effects on ecosystem processes. Key functional microbial communities in soil promote soil nutrient cycling by managing biomass and enzyme production, thereby enhancing ecosystem function (Li et al., 2023b ). In this context, key functional microorganisms are also considered beneficial microorganisms. Furthermore, losing key groups may lead to the disintegration of modules and networks, highlighting their crucial role in ensuring ecosystem stability (Shi et al., 2016 ). A relatively stable microbial community is necessary for the long-term viability of terrestrial ecosystem processes and services (Griffiths and Philippot, 2013 ). Generally, the soil microbiome exhibits functional redundancy, meaning that a minor decrease in the abundance of any group may have a negligible impact on the soil microbiome's overall function, as other bacteria can perform the same role (Nannipieri et al., 2017 ). If a community is sufficiently stable, continuous environmental disruptions will not cause significant changes in composition or function. It follows that beneficial microorganisms in the soil have a greater capacity than the community to provide essential ecosystem services. Trivedi et al (Trivedi et al., 2020 ) demonstrated a positive correlation between beneficial bacterial abundance and the functions performed by the soil microbial community for the plant, as well as an indirect increase in plant growth and nutrient acquisition due to beneficial microorganisms' modification of the structure and functions of the overall microbial community. Globally maize is a major crop humans and animals consume (Silva et al., 2018 ). Its large and consistent production is crucial for ensuring China's food security. Northwestern China produces the majority of the country's maize crop, which is vital to maintaining consistent production levels and preserving the condition of agricultural soils. Based on the long-term positioning experiment of maize intercropping conducted at the Gansu Academy of Agricultural Sciences in 2009, this study constructed a species library of local beneficial microorganisms at the genus level, focusing on four beneficial microbial functional groups (NPK, PA, DR, and PD). The aims were: (1) to explore the effects of different fertilizer application modes on the diversity and composition of the soil's beneficial functional microbiomes and their community construction; (2) to investigate the contribution of beneficial microorganisms to the total community in terms of stability and functional metabolism; (3) to reveal the contribution of beneficial microorganisms to the soil microenvironment and ecosystem multifunctionality; and (4) to classify species that contribute positively to microbial communities and soil ecosystems as beneficial microorganisms. The results of this study provide a theoretical foundation for further investigation of beneficial microorganisms to improve soil health, maintain community stability, enhance soil ecosystem function, and improve corn yield, expand the ecological definition of beneficial microorganisms, as well as provide a reference for the research and development of highly effective mycological agents. 2. Materials and methods 2.1 Site description The experiment was initiated in 2009 at the Wuwei Agricultural Experiment Station of the Gansu Academy of Agricultural Sciences in China (38°37 ′N, 102°40 ′E). The test site experiences a temperate continental arid climate, with an average annual temperature of 7.7°C, annual sunshine hours ranging from 2,800 to 3,300 hours, total annual solar radiation between 140 and 158 kJ/cm, a frost-free period of 150 days, an average rainfall of 222 mm, and evapotranspiration of 2,021 mm. The basic physicochemical properties of the soil were as follows: soil bulk density of 1.39 g/cm 3 ; soil organic matter content of 19.4 g/kg; total nitrogen (TN) of 1.36 g/kg; total phosphorus (TP) of 0.43 g/kg; total potassium (TK) of 20.9 g/kg; nitrate nitrogen (NO 3 − -N) of 12.85 mg/kg; ammonium nitrogen (NH 4 + -N) of 0.39 mg/kg; available phosphorus (AP) of 17.92 mg/kg; and available potassium (AK) of 121.21 mg/kg. The Hexi Oasis Irrigation District is one of the largest maize-producing areas in the country, with intensive agriculture widely practiced. Sweet peas and pin peas are used as green manure and are planted around March 20 each year. Maize is sown in April when the green manure seedlings are growing. Two methods are employed for applying green manure: root stubble and pressed green. Root stubble involves cutting the plant's above-ground parts (including stems, leaves, and legumes) while leaving the roots in the soil. Pressed green involves turning the green manure (whole plant) into the soil. The test area consisted of 15 plots, and all treatments were replicated using a completely randomized design (n = 3). A 50×30 cm ridge bed was used between the sample plots, and each plot covered an area of 19.8 m 2 (5.5×3.6 m). The study investigated five fertilization patterns: (1) root-stubble intercropping with coniferous pea (CPR), (2) green-stubble intercropping with coniferous pea (CPG), (3) root-stubble intercropping with sweet pea (SPR), (4) green-stubble intercropping with sweet pea (SPG), and (5) no green fertilizer application (CK). The layout of the plots is depicted in Fig. 1. 2.2 Sample collection and soil characterization In June 2022, soil samples were collected from each plot using an S-shaped random sampling method at a depth of 10–20 cm (REF). Five cores were randomly collected from each plot and combined into one sample, with three replicates per treatment. After removing rocks and plant residues, a portion of the soil was stored at -20 ° C for subsequent DNA extraction, and the remaining soil was stored at 4 ° C for soil property determination. Soil moisture content (VWC) was determined by drying the soil at 105°C for 12 hours. Soil bulk density (VW) was determined using the ring knife method, and soil texture was analyzed using a laser particle size analyzer. Soil pH was measured with a pH meter (LeiMagnet PHS-3E, Shanghai, China), and soil electrical conductivity (EC) was measured with a conductivity meter (LeiMagnet DDSJ-307F, Shanghai, China) using a soil-to-water ratio of 1:2.5.Soil total carbon (TC) and TN were determined using an elemental analyzer (Vario Macro Elementar, Munich, Germany). Total P (TP) was extracted using the H 2 SO 4 -HNO 3 digestion method and determined by the molybdenum blue method. The concentrations of ammonium (NH 4 + -N) and nitrate (NO 3 − -N) were determined using a flow automatic analyzer (Smartchem, Munich, Germany). Soil phosphatase activity was determined by phenyl disodium phosphate colorimetry, soil urease activity by sodium phenol-sodium hypochlorite colorimetry, and soil sucrase activity by 3, 5-dinitrosalicylic acid colorimetry. Maize yield per acre was measured at maturity. 2.3 Soil DNA extraction and metagenomic sequencing According to the manufacturer's instructions, total soil DNA was extracted from 0.5 g of mixed fresh soil using the Mo Bio PowerSoil™ DNA separation kit (Mo Bio Laboratories, Carlsbad, CA, USA). The mass and concentration of soil DNA were measured using a NanoDrop 2000 spectrophotometer (Thermo Scientific, USA), and the samples were sequenced via metagenomic sequencing. Sequencing was performed on the Illumina HiSeq 4000 platform at Majorbio Bio-Pharm Technology Co., Ltd. (Shanghai, China). Covaris M220 (China Gene Co., Ltd.) was used to fragment the DNA extracts into segments with an average size of approximately 400 bp. PE libraries were constructed using the NEXTflex™ Rapid DNA-Seq Kit (Bioo Scientific, Austin, TX, USA). Bridge PCR and sequencing were performed using the NovaSeq Reagent Kit (Illumina, USA). The metagenomic raw read data have been deposited in the NCBI sequence read file database (entry number: PRJNA1086341). After the original sequences were optimized for splitting, quality cutting, and pollution removal, the optimized sequences were used for splicing assembly and gene prediction. Sequences were mapped to the NCBI-NR/KEGG database to classify and annotate the species-function of Reads. 2.4 Screening for beneficial microorganisms in microbial communities Literature was collected using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) program(Murphy and Romanuk, 2013 ; Ribero and Filloy, 2023 ) (Figure_S1). An extensive literature survey was conducted until June 2023 through the Web of Science ( http://apps.webofknowledge.com/ ) and Google Scholar ( https://www.google.com/ ). Targeted searches were performed using various combinations of keywords in the title, keywords, or abstract, e.g. ("microorganisms" or "soil microorganisms," or "farm microorganisms" or "beneficial microorganisms") and ("nitrogen fixation" or "phosphorus solubilization" or "potash solubilization" or "drought resistance" or "pathogen antagonism" or "plastic degradation"). A total of 4,743 publications were retrieved and screened using the following criteria: (i) Studies involving field experiments and laboratory culture experiments focused on the beneficial effects of microorganisms on soil or crops; (ii). Beneficial traits were tested in situ or in vitro, including at least one function (nitrogen fixation, phosphorus solubilization, drought resistance, pathogen antagonism, plastic degradation); (iii) Results demonstrated beneficial microorganisms at the generic level; iv. Studies provided average values and repetitions (≥ 3). After screening for duplicates and content assessment, 82 related papers were identified, 107 related genera were selected at the genus level, and 56 beneficial genera (including multifunctional genera) were retained and listed in Table S1 after comparison and screening with the species annotation table in the sample. Furthermore, because some beneficial genera may contain potentially phytopathogenic bacteria, this study used the list of phytopathogenic bacteria compiled by Li et al (Li et al., 2023a ) (which includes almost all known phytopathogenic bacteria recorded up to 2022) to exclude potentially pathogenic species when annotating species abundance using a database of native beneficial microorganisms. 2.5 Statistical analyses All experiments were conducted using a completely randomized design (n ≥ 3). Analysis of variance (ANOVA) and Duncan's test ( p < 0.05) were used for multiple comparisons of physicochemical properties, enzyme activities, yield, and microbial diversity of maize soils under different fertilization treatments using SPSS Statistics 26 (IBM Corporation, Armonk, NY, USA). Microbial α-diversity was assessed using the Shannon, Simpson, and Chao indices. Partial Least Squares Discriminant Analysis (PLS-DA) based on the Bray-Curtis distance matrix was performed using the "vegan" package in R software (R-4.1.0) to explore similarities and differences ( p < 0.05) in changes in beneficial microbial communities of different functions between treatments. The JVenn program ( http://jvenn.toulouse.inra.fr/app/index.html ) was used to compare common and differential genera across functional beneficial microbial communities. Some data were visualized using GraphPad Prism 8.0 (GraphPad, La Jolla, CA, USA). Based on previous research, the microbial community was divided into six categories: always abundant taxa (AAT), conditionally abundant taxa (CAT), always rare taxa (ART), conditionally rare taxa (CRT), moderate taxa (MT), and conditionally rare and abundant taxa (CRAT) (Xue et al., 2018 ). The proportion of beneficial taxa within the total community was observed with categorization. Linear discriminant analysis effect size (LEfSe) was used to determine the significantly enriched taxa under different treatments, with the threshold for the logarithmic LDA score of the discriminant feature set at 2 and the α value set at 0.05. The niche width of the taxonomic group was obtained using the "niche. width" function (Levins algorithm) of the "spaa" package in R. The species occurrence frequency was randomly rearranged 1,000 times using the permutation algorithm implemented in the "EcolUtils" software package. The upper limit of the confidence interval, where the niche width of a species exceeds 95%, was classified as a generalized species of the plot, while a lower limit defined it as a specialized species of the plot (Wu et al., 2017 ). The neutral community model (NCM) and normalized stochasticity ratio (NST) were used to evaluate the relative importance of deterministic or stochastic processes in microbial community structuring (Ning et al., 2019 ; Sloan et al., 2006 ). For NCM, we used the"Hmisc", "minpack. lm", and "stats 4" R packages with default parameters for model fitting. The "NST" software package was used to calculate standardized stochasticity ratios for all treatments at each locus, using various similarity measures and zero model algorithms, randomness ratios, standard effects, and modified Raup Crick metrics to calculate NST. Considering the stability and reliability of the microbial network, we constructed the microbial co-occurrence network by combining the two green manure fertilizer application methods of the same type. We calculated the spearman's correlation coefficient and set the thresholds at R > 0.65 and p < 0.05. The"igraph" package in R was used to extract the topological parameters of the network under different fertilization methods and calculate intra-module connectivity (Zi) and inter-module connectivity (Pi), and we used Gephi ( https://gephi.org/ ) to calculate the network topological parameters. The network was visualized using Gephi ( https://gephi.org/ ). The "linkET" package was used to perform a Mantel test for correlation between environmental factors and yields with beneficial microbial taxa. A dichotomous network diagram was drawn using the "netET" and "ggraph" packages to show the correlation between the beneficial genera and the environmental factors. The main microbial predictors of soil processes were identified by constructing a random forest model using the "randomForest" package(Liaw and Wiener, 2001 ), and the significance of each predictor was evaluated using the "rfPermute" package. Using 17 variables as indicators of ecosystem function (Table S2), Z-score transformation was performed on individual functional indicators, and the soil ecosystem multifunctionality (EMF) index was calculated using the mean method(Delgado-Baquerizo et al., 2016 ; Luo et al., 2018 ). 3. Results 3.1 Analysis of beneficial microbial communities under green manure treatment Based on Illumina platform metagenomic sequencing data, 1,335,170,654 clean reads, each 150 bp length, were obtained (average 89,011,376 per sample) (Table S3). Annotated species were screened at the genus level using Web of Science and Google Scholar search results. Table S1 lists four functional taxa of soil-beneficial microorganisms selected based on distinct functions: a) genus favoring the uptake of N, P, and K elements ( NPK); b) genus with antagonistic effects against pathogenic bacteria (PA); c) genus with beneficial resistance to arid environments (DR); and d) genus with plastic degradation functions (PD). Intercropping maize with various green manures decreased the Shannon and Simpson diversity indices of the NPK, PA, DR, and PD communities compared to monocropping, but no treatment significantly affected the Chao index, which measures the richness of these beneficial communities (Fig. 2a). However, the structure of the four beneficial microbial communities was altered by long-term green manure intercropping and different fertilization strategies. PLS-DA analysis revealed that samples under green manure treatments of coniferous pea (CPG and CPR) were more tightly clustered than those of the control (CK) (Fig. 2b). Further investigation was conducted to determine the composition of beneficial microbial communities with varying functions under different treatments (Fig. 3a). The abundance bar-stacked plots showed that, among the four beneficial microbial communities, genera with the same function had similar compositions under various treatments. However, the abundance of the dominant genera increased in all of them after applying green manure compared to CK. The abundance of the NPK and DR communities was higher under the green manure returning treatments (CPG and SPG) than in the relic stubble treatments (CPR and SPR). The most abundant genera in the NPK community were Microvirga, Bradyrhizobium , and Mesorhizobium ; in the PA community, Streptomyces, Micromonospora , and Amycolatopsis were the most abundant; in the DR community, Bacillus and Pseudomonas were the dominant genera; and in the PD microbial community, Mycobacterium, Mycobacterium , and Bacillus were dominant. An Edwards-Venn diagram (Figure_3b) was created to analyze the similarities and differences in the various functional microbial taxa compositions using Jvenn (Huang et al., 2022 ). The findings revealed that the four beneficial microbial communities—NPK, PA, DR, and PD—contained 26, 7, 7, and 9 distinct genera, respectively. Compared to CK, the presence of seven multifunctional genera ( Bacillus, Pseudomonas, Enterobacter, Stenotrophomunas, Herbaspirllium, Ochrobactrum, and Breribacillus ) increased significantly ( p < 0.05) (Figure S2). Beneficial microbial communities varied proportionately across all treatments, ranging from approximately 15.3–16.23% (Fig. 4a). The highest percentage was recorded by the NPK community (10.32%), followed by PA (3.15%), PD (1.53%), and DR (0.17%). When green manure was applied, the proportion of all four functionally beneficial microorganisms in the community increased. Most of the community's genera were classified as AT (47.12–48.85%) and MT (39.56–40.22%) under each fertilization management mode (Figure S3a). Only four genera of beneficial microorganisms were found to belong to AT, 29 to MT, and 19 to RT (Figure_S3b). At the genus level, LefSe analysis (LDA > 2) showed that 12 and 5 genera were enriched in the CK and SPR groups, respectively, none of which contained beneficial genera. The CPG group was the most enriched in differential genera, with 16 genera, including 5 beneficial genera. The CPR and SPG groups each included one beneficial genus among the differential genera (Fig. 4b). Calculating the Levins niche width index of beneficial microbial communities with different functions revealed that the NPK and PA communities had much higher values than the DR and PD communities, with the DR community having the lowest niche width index (Fig. 4c). Generalists and specialists were divided based on niche breadth. The findings revealed that generalists accounted for a higher proportion in the NPK and DR communities, at 3.9% and 4.3%, respectively, while there were no generalists in the PD community (Fig. 4c).To better understand the potential role of stochastic processes in the formation of beneficial microbial communities, this study used a neutral community model (NCM) to predict the relationship between species occurrence frequency and relative abundance in the four functional communities (Fig. 4e). The findings revealed that the NCM effectively predicted the stochastic process of beneficial microbial communities, with strong explanatory power (R 2 ) in all four functional communities, and that the stochastic process had a greater impact on the formation of the NPK and PA communities. Among the four functional communities, NPK (m = 0.198) had the highest migration rate, suggesting the community's lowest diffusion constraint, followed by PA and DR (m = 0.195), while the PD community had the strongest diffusion limitation. This is consistent with the estimated results of microbial community diffusion shown by Nm. We statistically investigated the roles of deterministic ( 50%) processes in beneficial microbial community development using the null model's standardized stochastic rate (NST). As shown in Fig. 4d, all four functional communities had NST values greater than 50%, indicating that stochastic processes dominated and contributed similarly to the community construction process ( p > 0.05). 3.2 The importance of beneficial microorganisms in the overall community and ecosystem Co-occurrence networks were constructed for the top 800 genera regarding microbial community abundance under CK, green manure returning, and relic stubble treatments (Fig. 5a). Additionally, sub-networks of beneficial microbial communities were constructed (Fig. 5b). Data on network-related topological properties are presented in Table S4, and the findings demonstrate that adding green manure improved species connections and increased the network's overall complexity. To identify key species in the network, nodes were classified by computing within-module connectivities (Zi) and among-module connectivities (Pi) (Figure_5c). Table S5 lists the key species in the network identified by these values. Compared to CK, green manure returning and root stubble treatments led to an increase in 166 and 97 core genera, which included four important beneficial genera: Brevibacillus (NPK, PA), Marinobacterium (PD), Alcanivorax (PD), and Acinetobacter (NPK). Also, different fertilization treatments increased the relative abundance of these core genera (Figure_5c). Most of the major beneficial genera in the overall network belonged to NPK, with PA coming in second (Table S5).In addition, five connectors were identified in the sub-network of beneficial microorganisms as Bacillus (NPK, PA, DR, PD), Brevibacillus (NPK, PA), Ensifer (NPK), Nocardia (PD) and Streptomyces (PA), with the application of green manures increasing the abundance of these genera. Meanwhile, Figure_S4 shows the Zi and Pi values of beneficial genera in the core microorganisms of the network under different treatments, and we found that the application of green manure mainly increased the Pi value. The average variation degree (AVD) is used to quantify community stability. The lower the AVD index, the more stable the community is and the greater its resistance to disruption. As indicated in Fig. 5d, regardless of the type and fertilizing method of green manure, when compared to CK, the AVD value decreased significantly, while community stability increased under green manure treatment. We investigated the association between AVD values and the number of core beneficial genera to assess the importance of core beneficial microorganisms in overall community stability. Except for Nocardia , all seven genera were significantly negatively correlated with AVD ( p < 0.05), with Streptomyces showing the highest negative correlation. ( p < 0.01) (Figure_5e). 3.3 Contribution of beneficial microorganisms to community function Figure 6a shows the relative contribution of core beneficial genera to the entire community's KEGG pathway level 2 metabolic pathways under various green manures and fertilization methods based on species and functional contribution analysis. The core beneficial genera were primarily involved in the global and overview maps route (which included processes such as microbial metabolism, carbon metabolism, fatty acid metabolism, secondary metabolites, and amino acid biosynthesis), followed by carbohydrate metabolism and amino acid metabolism. Fertilization treatments significantly impacted the contributions of Acinetobacter, Alcanivorax, Brevibacillus , and Marinobacterium to overall community function. Green manure application increased the relative contribution of Acinetobacter to carbohydrate metabolism and promoted the involvement of this beneficial genus in amino acid metabolism and glycan biosynthesis and metabolism pathways under coniferous pea treatment (CPG/CPR). Green manure of four application modes increased the relative contribution of Alcanivorax to carbohydrate metabolism to varying degrees (5.26% − 10.92%), and the green-stubble treatment (CPG/SPG) promoted the involvement of this beneficial genus in energy metabolism, while the addition of green manure enhanced the relative contribution of Marinobacterium to lipid metabolism and Brevibacillus to the metabolism of cofactors and vitamins. The relative contribution of the core beneficial genera to the top 10 metabolic pathways in terms of gene abundance in the total community KEGG pathway level 3 was further investigated under different fertilizer treatments (Figure_6b), and it was found that they were mainly involved in metabolic pathways, biosynthesis of secondary metabolites, and microbial metabolism in diverse environments. Fertilization increased the relative contribution of Acinetobacter to metabolic pathways by 11.82% − 23.85%, and the sweet pea treatment (SPG/SPR) was more conducive to the involvement of Alcanivorax in pyruvate metabolism. Brevibacillus contribution to microbial metabolism in diverse environments was elevated by the application of green manure (4.30% − 6.24%), and the contribution to biosynthesis of amino acids also increased (0.21% − 3.16%). Moreover, the contribution of Marinobacterium to pyruvate metabolism was zero when no green manure was applied, and the four green manure treatments promoted its participation in pyruvate metabolism. The relative contribution of the core beneficial genera to the top 50 functional genes in terms of abundance was then analyzed (Figure_6c). Acinetobacter , Alcanivorax , Brevibacillus , and Marinobacterium had a high overall contribution to functional genes, with Acinetobacter and Alcanivorax contributing significantly to the abundance of atoB and acnA genes, Brevibacillus favoring the enrichment of amiE , hyuA , hyuB , and serA genes, and Marinobacterium contributing significantly to the abundance of GDH2 , gatA , and glnA genes. 3.4 The role of beneficial microbial communities in ecosystems The physical and chemical characteristics of maize plots under different fertilization treatments are presented in Table S6. Applying different green fertilizers with varying fertilization methods significantly altered most soil properties compared to the control soil. Different green manure treatments markedly improved soil water content (VWC) and ammonia nitrogen (NH 4 ⁺-N) content. Under the green manure returning treatments (CPG/SPG), the nitrate nitrogen (NO 3 ⁻-N) and sucrase activity were significantly higher than CK ( p < 0.05), while the activities of phosphatase and urease were the highest under SPG treatment. The total nitrogen (TN) content increased under the root stubble treatments (CPR/SPR), and the soil carbon-nitrogen ratio (C/N) decreased ( p < 0.05) compared to CK and the green manure returning treatment. After applying green manure, soil bulk density significantly decreased ( p < 0.05). Meanwhile, adding green manure significantly increased maize yield, regardless of the type and manner of fertilization. Nonetheless, the effects of all green manure treatments on soil texture, electrical conductivity (EC), total phosphorus (TP), and total carbon (TC) were less pronounced ( p > 0.05). According to these findings, green manure enhanced soil fertility and increased maize yield by 1.8–6.6%. Mantel tests (Fig. 7a) were carried out on the distance matrix of the total beneficial microbial communities and environmental factors to analyze the association between environmental variables and beneficial microorganisms. Compared to other environmental variables, the results suggested a substantial correlation between beneficial microbial communities and soil bulk weight (VW), soil water content (VWC), and maize yield (MY). Table S7 provides the individual values of the Mantel test parameters. It can be seen that VWC had the highest correlation (r = 0.817, p = 0.001), followed by MY (r = 0.423, p = 0.007). Meanwhile, spearman correlation analysis showed that soil VW was significantly negatively correlated with VWC, soil nitrate nitrogen (NO 3 ⁻-N) content, pH, and soil phosphatase (PHO) activity, while soil VWC was significantly positively correlated with soil ammoniacal nitrogen (NH 4 + -N) content. Moreover, there was a substantial positive correlation between MY and soil VWC, NO 3 − -N, NH 4 + -N content, and a negative correlation between MY and soil VW. Using the random forest model (Fig. 7b), the correlations between the four functional beneficial microbial communities and environmental factors were further evaluated. It was discovered that beneficial communities with varying functions contributed differently to soil physicochemical properties and yield. The results of the correlation analysis indicated that the abundance of the NPK and PA communities had a significant positive correlation with soil VWC and MY (Table S8). Additionally, the abundance of the NPK community had a strong positive correlation ( p < 0.01) with soil NO 3 − -N content and the abundance of the PA community had a significant positive correlation ( p < 0.05) with soil NH 4 ⁺-N content. Environmental factors and the DR and PD communities showed no meaningful association. It was discovered that the NPK and PA communities contributed more to the soil physicochemical differences under different treatments. Association analysis of differential core beneficial genera in the network and core genera in the beneficial microbial subnetwork with environmental factors (Figure_7c) revealed significant positive correlations between Brevibacillus and soil TC and TP content. Acinetobacter was significantly positively correlated with soil VWC and NO 3 − -N content and both genera had a positive correlation with soil PHO activity and a substantial negative correlation with soil VW. Additionally, Alcanivorax showed a significant positive correlation with soil TN, SC, and silt contents, while Streptomyces had a significant positive correlation with sand fraction. However, Streptomyces , Bacillus , and Nocardia all exhibited a significant negative correlation with soil URE activity, and Nocardia demonstrated a negative correlation with clay components. The average method was used to evaluate soil ecosystem multifunctionality (EMF), and the results showed that regardless of the type of green manure and fertilization method, the addition of green manure changed soil multifunctionality (Figure_7d). Specifically, under CPG treatment, the improvement of EMF was most significant ( p < 0.01), followed by SPR. The regression model in Figure_7e demonstrates a substantial positive association ( p < 0.05) between the relative abundance of the core beneficial genus Ensifer and EMF. Additionally, there is a highly significant positive correlation ( p < 0.01) between Alcanivorax, Bacillus, Brevibacillus, Streptomyces , and EMF. This study identified a significant correlation between 11 network core genera (not previously reported as beneficial genera) and soil properties that contribute to soil health (Figure_8a), such as a significant positive correlation with soil moisture content ( p < 0.05) and a significant negative correlation with soil bulkiness ( p < 0.05), which is beneficial for improving sand content. Although there have been no research reports on their beneficial effects on soil and plants, they have made significant contributions to supporting community co-occurrence networks and soil physicochemical properties.It was also observed that Aureimonas, Hoeflea , Janibacter , Labrys , Planosporangium , Planotetraspora , and Spirilliplanes showed significant positive correlations with the EMF index (Figure_8b). 4. Discussion 4.1 Response of beneficial microbial communities to different fertilization treatments According to existing literature, the beneficial properties of soil microorganisms to plants primarily include bioprophylaxis, bioprevention, and assisting plant resistance(Hunter, 2016 ). Combining these findings with the conditions of this sample site, this study further refined the classification of the beneficial genera: plant bioprophylaxis focuses on nutrient absorption qualities such as nitrogen fixation, phosphorus solubilization, and potassium solubilization; pathogen antagonism includes systemic resistance caused by bacteria, fungi, or the activation of antiphlogistic bacteria; and stress tolerance traits prioritize beneficial genera that can withstand drought and have the potential to degrade plastics, given the semi-arid region of the sample site and the susceptibility of corn mulch to microplastic contamination. Thus, the beneficial genera were classified as follows: nutrient uptake promotion (NPK) (El-Egami et al., 2024 ; Faller et al., 2024 ; Pang et al., 2024 ; Sepp et al., 2023 ; Wahab et al., 2024; Youssef et al., 2023 ), pathogen antagonism (PA) (Beneduzi et al., 2012 ; Chang et al., 2022 ; Kaur et al., 2023 ; Lee et al., 2023 ; Sermswan and Wongratanacheewin, 2017 ), drought resistance (DR)(Ali et al., 2022 ; Aslam et al., 2022 ; de Vries et al., 2020 ; Xi et al., 2018 ), and plastic degradation (PD) (Chen et al., 2023 ; Niu et al., 2023 ; Sun et al., 2022 ). Previous research has found that microbial diversity and abundance in legume rotational and intercropping systems are much higher than in monocrops(Ablimit et al., 2022 ; Latati et al., 2014 ). However, findings from this research showed that the abundance of beneficial microbial communities and their share of the total community increased significantly with green manure treatment, but the diversity index was significantly lower than the control, and the difference in richness was not significant.This suggests that the number of specific genera decreased during long-term green manure rotation, despite an increase in the overall beneficial community, which aligns with the findings of Liu et al(Zhang et al., 2017 ).β diversity analysis results showed that green manure had a significant effect on beneficial microbial community structure. Long-term use of green manure may cause an accumulation of crop root secretions, such as root deposits(Dennis et al., 2010 ), which greatly influence the formation of soil microbial communities and strengthen the process of selecting beneficial microbial communities. This could be one explanation for the observed phenomenon.In addition, the composition of the dominant groups of beneficial microorganisms with different functions remained stable under different fertilization treatments. When the beneficial genera of different functional groups were compared, there were seven multifunctional genera, and green manure treatment significantly increased their relative abundance.The multifunctional genera Bacillus and Pseudomonas , which have four roles simultaneously, are the dominant genera in the beneficial community and have been extensively studied and proven to have favorable effects on soil health and crops(Fasusi et al., 2021 ). The relative abundance of these genera in maize soil after long-term application and rotation of green manure was 1.23–1.77 times higher than CK, indicating that these well-known plant-associated bacteria are more likely to accumulate in maize soil under green manure rotation. LefSe analyses showed that different green manures or different fertilization practices enriched different differential genera compared to the control, and that the green manure returning treatment (CPG/SPG) was more favorable for enrichment of beneficial genera than the root stubble treatment (CPR/SPR). Deterministic processes (interspecies interactions, environmental filtering, etc.) and stochastic processes (probability diffusion, birth -death events, and ecological drift, etc.) are frequently thought to explain microbial community assembly concurrently (Zhou and Ning, 2017 ), and the relative contributions of these two ecological processes differ between generalists and specialists. Generalists are less impacted by the environment, whereas specialists have more stringent growth circumstances, which may include unique metabolic requirements and species interactions (Xu et al., 2021 ). In this study, stochastic processes contributed more to the construction of the four functional communities than deterministic processes, and compared to PA and PD communities, the proportion of generalists in the NPK and DR communities was higher, with increases of 5.9% and 3.8%, respectively, after applying green manure (Figure_4c), indicating that generalists can be enriched. Due to the wide adaptability of generalists and their higher abundance, they allow for better random diffusion, which is consistent with the results of NST calculations. Fan et al(Fan et al., 2024 ) discovered that subcommunity combinations of microbial taxa with higher frequency of occurrence and larger ecological niches are less limited by diffusion restrictions and more influenced by drift. Microbial taxa with a greater niche width often have more metabolic flexibility, making them less susceptible to environmental selection and more governed by random processes(Li et al., 2022 ; Luo et al., 2019 ). The best fit of NPK and PA communities in the neutral model (NCM) (NPK: R 2 = 0.9601, PA: R 2 = 0.9604) corresponds to their rather wide niche widths (Figure_4d-e), which supports this. A recent study found that substantial diffusion constraints can result in a shortage of beneficial microorganisms in maize fields(Wu et al., 2022). Thus, inoculating beneficial microorganisms or microbial communities with higher diffusion rates appears to have the potential to promote ecosystem health(Xiong and Lu, 2022 ). 4.2 Beneficial microorganisms exert beneficial properties in microbial communities Farm management introduces physical, chemical, and biological elements that, when combined, have the potential to modify soil characteristics significantly and, hence, the environment for the survival of the soil microbiome(Fierer, 2017 ). The structure and diversity of the microbiome are inextricably tied to the multiplicity of coexisting microhabitats (Liu et al., 2022 ). These microhabitats are likely the most critical influences on microbiome-mediated biogeochemical processes in soil (Lavelle et al., 2016 ). Green manure application modulates soil microhabitats, altering microbial populations (Szoboszlay and Tebbe, 2021 ; Wilpiszeski et al., 2019 ). However, species diversity is not the best predictor of its value to the community (Banerjee et al., 2018 ), and the beneficial genera belonging to the core species in the overall community network are only Microvirga, Mesorhizobium, Bradyrhizobium , and Streptomyces , which are abundant taxa (Table S5, Figure S3). Nevertheless, other beneficial genera also act as core species, determining the community's integrity and persistence independently of time (Cottee-Jones and Whittaker, 2012 ), and keystone species may have disproportionately significant impacts(Wu et al., 2023 ). Similar to Fan et al (Fan et al., 2019 ), our study discovered that keystone species are more abundant when fertilized, especially Nocardia (39% -70%). Keystone species are crucial to community stability, and the addition of organic fertilizers can dramatically change the complexity of networks (Wang et al., 2022a ). The application of green manure increased microbial interactions and network complexity, as evidenced by changes in network topological features (Table S4). Furthermore, green manure significantly increased the number of core microorganisms in the network, which are composed of beneficial microorganisms (all connectors) and essential for network stability and connectivity of individual modules. At the same time, a sufficiently stable community will not alter significantly in composition or function due to ongoing environmental perturbations (Rogers and Tate, 2001 ). Xun et al (Xun et al., 2021 ) created a new strategy that investigates the stability of soil microbial communities by computing AVD values based on experimental design. This method is not restricted by sample size and has advantages over existing methods for evaluating community stability. In this study, the lower the AVD value, the lower the average variability in the sample after applying green manure, and the more stable the microbial community, with core beneficial bacteria acting as a significantly correlated driving force for community stability. Soil microbes are key components of soil ecosystems that perform various tasks, including nutrient cycling and metabolism(Gao et al., 2021 ). Metagenomics proved more practical and efficient in this study than previous genomic techniques for accurately predicting soil microbial functions using KEGG databases. KEGG analysis offered precise information regarding the role of core beneficial microbes in metabolic pathways in soil microbial communities. The results revealed that metabolism was the primary function of the soil microbial community in maize, accounting for more than 52% of all treatments, showing that microbial activities in the soil were primarily metabolism-based. Therefore, our study included a more thorough analysis of the secondary routes of metabolism. Various metabolic pathways can result in distinct physiological outcomes. The overall function of the maize soil microbial community under various fertilization treatments was found to be relatively conservative when maintaining a stable, functional metabolism in the face of external perturbations (Gao et al., 2021 ). Furthermore, we discovered that fertilization treatments quickly affected the contribution of Acinetobacter, Alcanivorax, Brevibacillus , and Marinobacterium to the overall community function and that treatments with green manure were more favorable to these beneficial genera' participation in carbohydrate metabolism, amino acid metabolism, glycan biosynthesis and metabolism, energy metabolism, and metabolism of cofactors and vitamins to provide essential nutrients for crop growth better (DeAngelis et al., 2008 ). Meanwhile, the beneficial genera whose contribution to metabolic functions was susceptible to fertilization ( Acinetobacter, Alcanivora, Brevibacillus, Marinobacterium ) also had higher overall contributions to the relevant functional genes. Among them, Acinetobacter and Alcanivorax promote soil carbon sequestration processes (Berg, 2011 ) by participating in the acetyl coenzyme A pathway (Beulig et al., 2016 ), TCA cycle (Delgado-Baquerizo et al., 2013 ), and other related pathways. Brevibacillus favors the synthesis of amylase and amino acids in soil (Syldatk et al., 1999 ), and Marinobacterium contributes more to the synthesis of glutamate, facilitating the conversion of inorganic to organic nitrogen (Yang et al., 2016 ). It follows that beneficial genera have beneficial properties in terms of network and community stability and community metabolic functions in addition to their single beneficial function. 4.3 Beneficial characterization of beneficial microorganisms in ecosystems Anthropogenic activities and farm management practices can fundamentally alter soil properties and the composition of the soil microbiome (Geisseler and Scow, 2014 ; Johnsen et al., 2001 ). Soil microorganisms in agricultural soils perform many ecosystem services (ecosystem multifunctionality), which are critical for geochemical nutrient cycling, primary production, litter decomposition, and climate regulation (Bardgett and van der Putten, 2014 ; Bender et al., 2016 ; Chen et al., 2020 ). Significant interactions exist between soil environment, soil microbes, and plant quality (Tao et al., 2016). Our work confirmed that communities of beneficial microorganisms that could promote NPK nutrient uptake and antagonize pathogens had relatively higher contributions to improving soil physicochemical properties and promoting soil health. The microbiome is intricately linked to soil structure (e.g., aggregation and pore connectivity), as this structure regulates the flow of water, oxygen, and nutrients through the systém (Hartmann and Six, 2022 ). According to the Mantel test, there is a substantial positive correlation between the abundance of the beneficial microbial community and both soil water content and bulk weight, and the core beneficial microorganisms Acinetobacter were significantly and positively correlated with soil water content. At the same time, Acinetobacter and Brevibacillus were significantly and negatively correlated with soil bulk weight. Microorganisms can secrete compounds that directly alter soil water dynamics, such as EPS, which increases water retention in soil (Granato et al., 2019 ), reduces hydraulic conductivity by plugging large pores (Shafi et al., 2017 ), slows evaporation from the soil (Bravo et al., 2011 ), does not readily desaturate due to smaller pore sizes, and maintains fluid continuity under drying conditions, allowing nutrients and metabolites to diffuse. Microorganisms can influence soil particle cohesiveness, pore organization, and soil structure, affecting soil water retention and infiltration rates (Tang et al., 2021 ). Beneficial microorganisms, particularly their core genera Streptomyces and Alcanivorax , showed a strong positive correlation with soil sand and silt content, respectively, while Nocardia demonstrated a negative correlation with clay fractions. This indicates that core beneficial microorganisms were able to promote the structural transformation of soil texture to a structure dominated by larger soil particles, which contain more carbon, nitrogen, and organic matter, promoting aggregate formation and maintaining soil structural stability, thereby favoring soil health(Puget et al., 1995 ). Microorganisms degrade organic matter to release plant-available inorganic nutrients, modify nutrient availability by oxidative, reductive, solubilizing, and chelating activities, and store and release nutrients in necrotic matter (Marschner and Rengel, 2007 ). These activities drive global nutrient cycling (Falkowski et al., 2008 ) and regulate approximately 90% of soil energy fluxes(Lukac et al., 2017 ). In this study, for example, Brevibacillus was shown to improve the uptake and utilization of soil carbon and phosphorus, Acinetobacter was found to aid in the increase of soil available nitrogen content, and Alcanivorax had a positive effect on the accumulation of total soil nitrogen. Furthermore, Li et al(Li et al., 2023a ) suggested that there was always a positive correlation between the relative abundance of potentially beneficial microorganisms and maize yield, and this study confirmed the significant correlation between the abundance of beneficial microbial communities and maize yield ( p < 0.01). Crop yields are high when the soil is healthy, owing to simple root colonization, adequate water entering and storing, appropriate nutrient delivery, fewer hazardous soil pollutants, and highly active beneficial microorganisms that suppress potential pests and drive plant growth. Most studies have investigated whether more species are required to improve ecosystem multifunctionality and quantified biodiversity's impact on communities. However, in these assessments, the identity of species has been mainly neglected(Cadotte et al., 2017 ; Wagg et al., 2020 ). Depending on the metrics used and the systems investigated, various species have distinct and comparable functions (redundancy)(Mori et al., 2023 ). As a result, it is vital to assess each species' relevance while maintaining their individuality in various functional contexts (Hautier et al., 2018). This work reveals that core beneficial genera play a crucial role in improving ecosystem multifunctionality, in line with Wang et al. (Wang et al., 2022b ), who found that changes in the abundance of functional microbes had a considerable impact on EMF. Our finding could be attributed to the substantial redundancy of microbial communities used for general functions in soil (Li et al., 2021b ). More abundant microbes result in more interactions between them, which drives EMF and improves ecological stability (Chen et al., 2022 ). We identified 11 core genera by the network that were not previously reported to have direct beneficial effects on plants. As Qiao et al(Qiao et al., 2024 ) stated the core taxa enhanced potential microbial cooperation and network complexity, which ultimately enhanced plant health and biomass. This study also found that these core genera are crucial in network support and soil property improvement, favoring EMF and thus benefiting plant health and yield. We, therefore, suggest that such microorganisms should be categorized as beneficial microorganisms in a completely new sense. Thus, we believe that such microorganisms should also be classified as beneficial microorganisms, expanding the scope of the definition of beneficial microorganisms. 5. Conclusions In this study, the clustering of beneficial microorganisms according to their reported single functions revealed that green manure returning treatment was more conducive to enriching beneficial microbial communities than relic stubble. The mix of diverse functionally advantageous dominant taxa remained consistent across fertilization treatments, and stochastic processes mainly influenced their aggregation. Beneficial genera and their inherent single beneficial function serve as keystone species that contribute to the complexity and stability of the overall co-occurrence network by enhancing inter-module connectivity. The core beneficial genera Brevibacillus, Marinobacterium, Alcanivorax, Acinetobacter, Bacillus, Ensifer, Nocardia , and Streptomyces favor reducing community average variability (AVD) to improve community stability. The overall functions of microbial communities under different fertilization treatments were relatively conservative, and the green manure treatment was more conducive to increasing the relative contribution of core beneficial genera to essential metabolic pathways such as carbohydrate metabolism, amino acid metabolism, and energy metabolism, and enhancing the contribution of core beneficial genera to functional gene abundance in the processes of element cycling and amino acid synthesis to provide essential nutrients for crop growth better. The relative contribution of core beneficial genera to the abundance of functional genes in the processes of element cycling and amino acid synthesis was enhanced, better providing essential nutrients for crop growth. Additionally, core beneficial genera are significantly associated with soil nutrient transformation, soil enzyme activity, soil structure, and texture, which are beneficial in maintaining soil structural stability and promoting soil health. Core beneficial genera have the potential to enhance ecosystem stability as drivers of ecosystem multifunctionality. This study also identified 11 network core genera whose beneficial properties have not been reported, and due to their positive effects on microbial communities and soil properties, we suggest that such microorganisms extend previous definitions of beneficial microorganisms, making them more accurate and comprehensive. Declarations Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Author Contribution G.Z. and J.Z. wrote the original draft. G.Z. also contributed to methodology, visualization, and data curation. Y.Z. conducted the investigation, developed methodology, performed software-related tasks, and carried out formal analysis. X.L. contributed to methodology and project administration. X.W. participated in investigation and data curation. J.D. provided supervision and writing-review & editing. P.L. was involved in project administration. J.Y. contributed to writing-review & editing. J.Z. provided resources, conceptualization, supervision, and writing-original draft. Y.C. contributed to writing-review & editing, resources, project administration, funding acquisition, and conceptualization. All authors reviewed the manuscript. Acknowledgements This project was supported by the National Key Research and Development Program of China (2022YFF1303301 and 2022YFF1302603), the Key Research and Development Project of Gansu Provincial Science and Technology Program (25YFWA004), National Nature Science Foundation of China (52179026), Gansu Provincial Science and Technology Department of China (22ZD6NA049), Strategic Research and Consulting Project of the Chinese Academy of Engineering (2023-XZ-80) and The Major Key Projects of Natural Science of the Gansu Province (No. 23ZDFA018). Data Availability The metagenomic raw read data have been deposited in the NCBI sequence read file database (entry number: PRJNA1086341). References Ablimit, R., Li, W., Zhang, J., Gao, H., Zhao, Y., Cheng, M., Meng, X., An, L. and Chen, Y., 2022. Altering microbial community for improving soil properties and agricultural sustainability during a 10-year maize-green manure intercropping in Northwest China. Journal of Environmental Management. 321.http://dx.doi.org/10.1016/j.jenv man.2022.115859 Ali, S., Tyagi, A., Park, S., Mir, R.A., Mushtaq, M., Bhat, B., Mahmoudi, H. and Bae, H., 2022. Deciphering the plant microbiome to improve drought tolerance: Mechanisms and perspectives. Environmental and Experimental Botany. 201.http://dx.doi.org/10.1016/j.envex pbot.2022.104933 Altieri, M.A., Funes-Monzote, F.R. and Petersen, P., 2012. Agroecologically efficient agricultural systems for smallholder farmers: contributions to food sovereignty. Agronomy for Sustainable Development. 32, 1-13.http://dx.doi.org/10.1007/s13 593-011-0065-6 Aslam, M.M., Okal, E.J., Idris, A.L., Qian, Z., Xu, W., Karanja, J.K., Wani, S.H. and Yuan, W., 2022. Rhizosphere microbiomes can regulate plant drought tolerance. Pedosphere. 32, 61-74.http://dx.doi.org/10.1016/s1002 -0160(21)60061-9 Banerjee, S., Kirkby, C.A., Schmutter, D., Bissett, A., Kirkegaard, J.A. and Richardson, A.E., 2016. Network analysis reveals functional redundancy and keystone taxa amongst bacterial and fungal communities during organic matter decomposition in an arable soil. Soil Biology and Biochemistry. 97, 188-198.http://dx.doi.org/https://doi.org/10.1016 /j.soilbio.2016.03.017 Banerjee, S., Schlaeppi, K. and van der Heijden, M.G.A., 2018. Keystone taxa as drivers of microbiome structure and functioning. Nature Reviews Microbiology. 16, 567-576.http://dx.doi.org/10.1038/s41 579-018-0024-1 Banerjee, S., Walder, F., Büchi, L., Meyer, M., Held, A.Y., Gattinger, A., Keller, T., Charles, R. and van der Heijden, M.G.A., 2019. Agricultural intensification reduces microbial network complexity and the abundance of keystone taxa in roots. The ISME Journal. 13, 1722-1736.http://dx.doi.org/10.1038/s41 396-019-0383-2 Bardgett, R.D. and van der Putten, W.H., 2014. Belowground biodiversity and ecosystem functioning. Nature. 515, 505-511.http://dx.doi.org/10.1038 /nature13855 Bender, S.F., Wagg, C. and van der Heijden, M.G.A., 2016. An Underground Revolution: Biodiversity and Soil Ecological Engineering for Agricultural Sustainability. Trends in Ecology & Evolution. 31, 440-452.http://dx.doi.org/https://doi.org/10.10 16/j.tree.2016.02.016 Beneduzi, A., Ambrosini, A. and Passaglia, L., 2012. Plant growth-promoting rhizobacteria (PGPR): Their potential as antagonists and biocontrol agents. Genetics and molecular biology. 35, 1044-51.http://dx.doi.org/10.1590/S1415-47 572012000600020 Berg, I.A., 2011. Ecological Aspects of the Distribution of Different Autotrophic CO 2 Fixation Pathways. Applied and Environmental Microbiology. 77, 1925-1936.http://dx.doi.org/10.1128/ aem.02473-10 Beulig, F., Urich, T., Nowak, M., Trumbore, S.E., Gleixner, G., Gilfillan, G.D., Fjelland, K.E. and Küsel, K., 2016. Altered carbon turnover processes and microbiomes in soils under long-term extremely high CO2 exposure. Nature Microbiology. 1, 15025.http://dx.doi.org/10.1038/nm icrobiol.2015.25 Bravo, A., Likitvivatanavong, S., Gill, S.S. and Soberón, M., 2011. Bacillus thuringiensis: A story of a successful bioinsecticide. Insect Biochemistry and Molecular Biology. 41, 423-431.http://dx.doi.org/https://doi.org/10.101 6/j.ibmb.2011.02.006 Cadotte, M.W., Livingstone, S.W., Yasui, S.L.E., Dinnage, R. and Shu, W.J.E., 2017. Explaining ecosystem multifunction with evolutionary models. 98, 3175-3187 Chang, X., Wei, D., Zeng, Y., Zhao, X., Hu, Y., Wu, X., Song, C., Gong, G., Chen, H., Yang, C., Zhang, M., Liu, T., Chen, W. and Yang, W., 2022. Maize-soybean relay strip intercropping reshapes the rhizosphere bacterial community and recruits beneficial bacteria to suppress Fusarium root rot of soybean. Frontiers in Microbiology. 13.http://dx.doi.org/10.3389/fmic b.2022.1009689 Chen, B., Zhang, Z., Wang, T., Hu, H., Qin, G., Lu, T., Hong, W., Hu, J., Penuelas, J. and Qian, H., 2023. Global distribution of marine microplastics and potential for biodegradation. Journal of Hazardous Materials. 451.http://dx.doi.org/10.1016/j.jhaz mat.2023.131198 Chen, Q.-L., Ding, J., Zhu, D., Hu, H.-W., Delgado-Baquerizo, M., Ma, Y.-B., He, J.-Z. and Zhu, Y.-G., 2020. Rare microbial taxa as the major drivers of ecosystem multifunctionality in long-term fertilized soils. Soil Biology and Biochemistry. 141.http://dx.doi.org/10.1016/j.soil bio.2019.107686 Chen, W., Wang, J., Chen, X., Meng, Z., Xu, R., Duoji, D., Zhang, J., He, J., Wang, Z., Chen, J., Liu, K., Hu, T. and Zhang, Y., 2022. Soil microbial network complexity predicts ecosystem function along elevation gradients on the Tibetan Plateau. Soil Biology and Biochemistry. 172, 108766.http://dx.doi.org/https://doi.org/10.1016 /j.soilbio.2022.108766 Cottee-Jones, H.E.W. and Whittaker, R.J., 2012. perspective: The keystone species concept: a critical appraisal. Frontiers of Biogeography. 4.http://dx.doi.org/10.2142 5/f5fbg12533 de Vries, F.T., Griffiths, R.I., Knight, C.G., Nicolitch, O. and Williams, A., 2020. Harnessing rhizosphere microbiomes for drought-resilient crop production. Science. 368, 270-274.http://dx.doi.org/10.1126/s cience.aaz5192 DeAngelis, K.M., Lindow, S.E. and Firestone, M.K., 2008. Bacterial quorum sensing and nitrogen cycling in rhizosphere soil. FEMS Microbiology Ecology. 66, 197-207.http://dx.doi.org/10.1111/j.1574- 6941.2008.00550.x %J FEMS Microbiology Ecology Delgado-Baquerizo, M., Maestre, F.T., Gallardo, A., Bowker, M.A., Wallenstein, M.D., Quero, J.L., Ochoa, V., Gozalo, B., García-Gómez, M., Soliveres, S., García-Palacios, P., Berdugo, M., Valencia, E., Escolar, C., Arredondo, T., Barraza-Zepeda, C., Bran, D., Carreira, J.A., Chaieb, M., Conceição, A.A., Derak, M., Eldridge, D.J., Escudero, A., Espinosa, C.I., Gaitán, J., Gatica, M.G., Gómez-González, S., Guzman, E., Gutiérrez, J.R., Florentino, A., Hepper, E., Hernández, R.M., Huber-Sannwald, E., Jankju, M., Liu, J., Mau, R.L., Miriti, M., Monerris, J., Naseri, K., Noumi, Z., Polo, V., Prina, A., Pucheta, E., Ramírez, E., Ramírez-Collantes, D.A., Romão, R., Tighe, M., Torres, D., Torres-Díaz, C., Ungar, E.D., Val, J., Wamiti, W., Wang, D. and Zaady, E., 2013. Decoupling of soil nutrient cycles as a function of aridity in global drylands. Nature. 502, 672-676.http://dx.doi.org/10.1038 /nature12670 Delgado-Baquerizo, M., Maestre, F.T., Reich, P.B., Jeffries, T.C., Gaitan, J.J., Encinar, D., Berdugo, M., Campbell, C.D. and Singh, B.K., 2016. Microbial diversity drives multifunctionality in terrestrial ecosystems. Nature Communications. 7, 10541.http://dx.doi.org/10.1038/ ncomms10541 Dennis, P.G., Miller, A.J. and Hirsch, P.R., 2010. Are root exudates more important than other sources of rhizodeposits in structuring rhizosphere bacterial communities? FEMS Microbiology Ecology. 72, 313-327.http://dx.doi.org/10.1111/j.1574-6 941.2010.00860.x %J FEMS Microbiology Ecology El-Egami, H.M., Hegab, R.H., Montaser, H., El-Hawary, M.M. and Hasanuzzaman, M., 2024. Impact of Potassium-Solubilizing Microorganisms with Potassium Sources on the Growth, Physiology, and Productivity of Wheat Crop under Salt-Affected Soil Conditions. Agronomy. 14.http://dx.doi.org/10.3390/agr onomy14030423 Esperschütz, J., Gattinger, A., Mäder, P., Schloter, M. and Fliessbach, A., 2007. Response of soil microbial biomass and community structures to conventional and organic farming systems under identical crop rotations. FEMS Microbiol Ecol. 61, 26-37.http://dx.doi.org/10.1111/j.1574-6 941.2007.00318.x Falkowski, P.G., Fenchel, T. and Delong, E.F., 2008. The Microbial Engines That Drive Earth's Biogeochemical Cycles. 320, 1034-1039.http://dx.doi.org/doi:10.1126/ science.1153213 Faller, L., Leite, M.F.A. and Kuramae, E.E., 2024. Enhancing phosphate-solubilising microbial communities through artificial selection. Nat Commun. 15, 1649.http://dx.doi.org/10.1038/s414 67-024-46060-x Fan, K., Delgado-Baquerizo, M., Guo, X., Wang, D., Wu, Y., Zhu, M., Yu, W., Yao, H., Zhu, Y.-g. and Chu, H., 2019. Suppressed N fixation and diazotrophs after four decades of fertilization. Microbiome. 7, 143.http://dx.doi.org/10.1186/s40 168-019-0757-8 Fan, Q., Liu, K., Wang, Z., Liu, D., Li, T., Hou, H., Zhang, Z., Chen, D., Zhang, S., Yu, A., Deng, Y., Cui, X. and Che, R., 2024. Soil microbial subcommunity assembly mechanisms are highly variable and intimately linked to their ecological and functional traits. Molecular Ecology.http://dx.doi.org/10.111 1/mec.17302 Fasusi, O.A., Cruz, C. and Babalola, O.O., 2021. Agricultural Sustainability: Microbial Biofertilizers in Rhizosphere Management. Agriculture. 11.http://dx.doi.org/10.3390/agri culture11020163 Fierer, N., 2017. Embracing the unknown: disentangling the complexities of the soil microbiome. Nature Reviews Microbiology. 15, 579-590.http://dx.doi.org/10.1038/n rmicro.2017.87 Gao, Y., Du, J., Bahar, M.M., Wang, H., Subashchandrabose, S., Duan, L., Yang, X., Megharaj, M., Zhao, Q., Zhang, W., Liu, Y., Wang, J. and Naidu, R., 2021. Metagenomics analysis identifies nitrogen metabolic pathway in bioremediation of diesel contaminated soil. Chemosphere. 271, 129566.http://dx.doi.org/https://doi.org/10.1016/j.ch emosphere.2021.129566 Geisseler, D. and Scow, K.M., 2014. Long-term effects of mineral fertilizers on soil microorganisms A review. Soil Biology and Biochemistry. 75, 54-63.http://dx.doi.org/https://doi.org/10.1016 /j.soilbio.2014.03.023 Golla, B., 2021. Agricultural production system in arid and semi-arid regions. International Journal of Agricultural Science and Food Technology. 234-244.http://dx.doi.org/10.17352/24 55-815X.000113 Granato, E.T., Meiller-Legrand, T.A. and Foster, K.R., 2019. The Evolution and Ecology of Bacterial Warfare. Current Biology. 29, R521-R537.http://dx.doi.org/https://doi.org/10.10 16/j.cub.2019.04.024 Griffiths, B.S. and Philippot, L., 2013. Insights into the resistance and resilience of the soil microbial community. FEMS Microbiology Reviews. 37, 112-129.http://dx.doi.org/10.1111/j.1574-6 976.2012.00343.x Han, Z., Xu, P., Li, Z., Lin, H., Zhu, C., Wang, J. and Zou, J., 2022. Microbial diversity and the abundance of keystone species drive the response of soil multifunctionality to organic substitution and biochar amendment in a tea plantation. GCB Bioenergy. 14, 481-495.http://dx.doi.org/10.1111 /gcbb.12926 Hartmann, M. and Six, J., 2022. Soil structure and microbiome functions in agroecosystems. Nature Reviews Earth & Environment. 4, 4-18.http://dx.doi.org/10.1038/s430 17-022-00366-w Hautier, Y., Isbell, F., Borer, E.T., Seabloom, E.W., Harpole, W.S., Lind, E.M., MacDougall, A.S., Stevens, C.J., Adler, P.B., Alberti, J., Bakker, J.D., Brudvig, L.A., Buckley, Y.M., Cadotte, M., Caldeira, M.C., Chaneton, E.J., Chu, C., Daleo, P., Dickman, C.R., Dwyer, J.M., Eskelinen, A., Fay, P.A., Firn, J., Hagenah, N., Hillebrand, H., Iribarne, O., Kirkman, K.P., Knops, J.M.H., La Pierre, K.J., McCulley, R.L., Morgan, J.W., Pärtel, M., Pascual, J., Price, J.N., Prober, S.M., Risch, A.C., Sankaran, M., Schuetz, M., Standish, R.J., Virtanen, R., Wardle, G.M., Yahdjian, L. and Hector, A., 2018. Local loss and spatial homogenization of plant diversity reduce ecosystem multifunctionality. Nature Ecology & Evolution. 2, 50-56.http://dx.doi.org/10.1038/s41 559-017-0395-0 Huang, X., Rehman, H.M., Szollosi, A.G. and Zhou, S., 2022. Network Pharmacology-Based Approach Combined with Bioinformatic Analytics to Elucidate the Potential of Curcumol against Hepatocellular Carcinoma. Genes (Basel). 13.http://dx.doi.org/10.3390/g enes13040653 Hunter, P., 2016. Plant microbiomes and sustainable agriculture. EMBO reports. 17, 1696-1699.http://dx.doi.org/10.15252/e mbr.201643476 Jangid, K., Williams, M.A., Franzluebbers, A.J., Sanderlin, J.S., Reeves, J.H., Jenkins, M.B., Endale, D.M., Coleman, D.C. and Whitman, W.B., 2008. Relative impacts of land-use, management intensity and fertilization upon soil microbial community structure in agricultural systems. Soil Biology and Biochemistry. 40, 2843-2853.http://dx.doi.org/https://doi.org/10.1016 /j.soilbio.2008.07.030 Johnsen, K., Jacobsen, C.S., Torsvik, V. and Sørensen, J., 2001. Pesticide effects on bacterial diversity in agricultural soils – a review. Biology and Fertility of Soils. 33, 443-453.http://dx.doi.org/10.1007/s 003740100351 Kaur, T., Khanna, K., Sharma, S. and Manhas, R.K., 2023. Mechanistic insights into the role of actinobacteria as potential biocontrol candidates against fungal phytopathogens. Journal of Basic Microbiology. 63, 1196-1218.http://dx.doi.org/10.1002/jo bm.202300027 Latati, M., Blavet, D., Alkama, N., Laoufi, H., Drevon, J.J., Gérard, F., Pansu, M. and Ounane, S.M., 2014. The intercropping cowpea-maize improves soil phosphorus availability and maize yields in an alkaline soil. Plant and Soil. 385, 181-191.http://dx.doi.org/10.1007/s11 104-014-2214-6 Lavelle, P., Spain, A., Blouin, M., Brown, G., Decaëns, T., Grimaldi, M., Jiménez, J.J., McKey, D., Mathieu, J., Velasquez, E. and Zangerlé, A., 2016. Ecosystem Engineers in a Self-organized Soil: A Review of Concepts and Future Research Questions. Soil Science. 181, Lee, S.H., Jeon, S.H., Park, J.Y., Kim, D.S., Kim, J.A., Jeong, H.Y. and Kang, J.W., 2023. Isolation and Evaluation of the Antagonistic Activity of Cnidium officinale Rhizosphere Bacteria against Phytopathogenic fungi (Fusarium solani). Microorganisms. 11.http://dx.doi.org/10.3390/microo rganisms11061555 Li, C., Bo, H., Song, B., Chen, X., Cao, Q., Yang, R., Ji, S., Wang, L. and Liu, J., 2022. Reshaping of the soil microbiome by the expansion of invasive plants: shifts in structure, diversity, co-occurrence, niche breadth, and assembly processes. Plant and Soil. 477, 629-646.http://dx.doi.org/10.1007/s111 04-022-05445-x Li, F., Zhang, K., Ren, J., Yin, C., Zhang, Y. and Nie, J., 2021a. Driving mechanism for farmers to adopt improved agricultural systems in China: The case of rice-green manure crops rotation system. Agricultural Systems. 192, 103202.http://dx.doi.org/https://doi.org/10.101 6/j.agsy.2021.103202 Li, J., Huang, L., Zhang, J., Coulter, J.A., Li, L. and Gan, Y., 2019. Diversifying crop rotation improves system robustness. Agronomy for Sustainable Development. 39, 38.http://dx.doi.org/10.1007/s13 593-019-0584-0 Li, M., Guo, J., Ren, T., Luo, G., Shen, Q., Lu, J., Guo, S. and Ling, N., 2021b. Crop rotation history constrains soil biodiversity and multifunctionality relationships. Agriculture, Ecosystems & Environment. 319, 107550.http://dx.doi.org/https://doi.org/10.101 6/j.agee.2021.107550 Li, P., Tedersoo, L., Crowther, T.W., Dumbrell, A.J., Dini-Andreote, F., Bahram, M., Kuang, L., Li, T., Wu, M., Jiang, Y., Luan, L., Saleem, M., de Vries, F.T., Li, Z., Wang, B. and Jiang, J., 2023a. Fossil-fuel-dependent scenarios could lead to a significant decline of global plant-beneficial bacteria abundance in soils by 2100. Nature Food.http://dx.doi.org/10.1038/s430 16-023-00869-9 Li, Q.-m., Zhang, D., Zhang, J.-z., Zhou, Z.-j., Pan, Y., Yang, Z.-h., Zhu, J.-h., Liu, Y.-h. and Zhang, L.-f., 2023b. Crop rotations increased soil ecosystem multifunctionality by improving keystone taxa and soil properties in potatoes. Frontiers in Microbiology. 14.http://dx.doi.org/10.3389/fmic b.2023.1034761 Liaw, A. and Wiener, M., 2001. Classification and Regression by RandomForest. Forest. 23, Liu, B., Arlotti, D., Huyghebaert, B. and Tebbe, C.C., 2022. Disentangling the impact of contrasting agricultural management practices on soil microbial communities – Importance of rare bacterial community members. Soil Biology and Biochemistry. 166.http://dx.doi.org/10.1016/j.soil bio.2022.108573 Lukac, M., Grenni, P. and Gamboni, M., 2017. Soil biological communities and ecosystem resilience. Luo, G., Rensing, C., Chen, H., Liu, M., Wang, M., Guo, S., Ling, N., Shen, Q. and Briones, M., 2018. Deciphering the associations between soil microbial diversity and ecosystem multifunctionality driven by long‐term fertilization management. Functional Ecology. 32, 1103-1116.http://dx.doi.org/10.1111/13 65-2435.13039 Luo, Z., Liu, J., Zhao, P., Jia, T., Li, C. and Chai, B., 2019. Biogeographic Patterns and Assembly Mechanisms of Bacterial Communities Differ Between Habitat Generalists and Specialists Across Elevational Gradients. 10.http://dx.doi.org/10.3389/fm icb.2019.00169 Marschner, P. and Rengel, Z., 2007. Nutrient Cycling in Terrestrial Ecosystems. Mori, A.S., Isbell, F. and Cadotte, M.W., 2023. Assessing the importance of species and their assemblages for the biodiversity‐ecosystem multifunctionality relationship. Ecology. 104.http://dx.doi.org/10.10 02/ecy.4104 Murphy, G.E.P. and Romanuk, T.N., 2013. A meta‐analysis of declines in local species richness from human disturbances. Ecology and Evolution. 4, 91-103.http://dx.doi.org/10.10 02/ece3.909 Nannipieri, P., Ascher, J., Ceccherini, M.T., Landi, L., Pietramellara, G. and Renella, G., 2017. Microbial diversity and soil functions. European Journal of Soil Science. 68, 12-26.http://dx.doi.org/10.1111 /ejss.4_12398 Ning, D., Deng, Y., Tiedje, J.M. and Zhou, J., 2019. A general framework for quantitatively assessing ecological stochasticity. 116, 16892-16898.http://dx.doi.org/doi:10.1073/p nas.1904623116 Niu, L., Chen, Y., Li, Y., Wang, Y., Shen, J., Wang, L., Zhang, W., Zhang, H. and Zhao, B., 2023. Diversity, abundance and distribution characteristics of potential polyethylene and polypropylene microplastic degradation bacterial communities in the urban river. Water Research. 232.http://dx.doi.org/10.1016/j.wa tres.2023.119704 Pang, F., Li, Q., Solanki, M.K., Wang, Z., Xing, Y.-X. and Dong, D.-F., 2024. Soil phosphorus transformation and plant uptake driven by phosphate-solubilizing microorganisms. Frontiers in Microbiology. 15.http://dx.doi.org/10.3389/fmic b.2024.1383813 Puget, P., Chenu, C. and Balesdent, J., 1995. Total and young organic carbon distributions in aggregates of silty cultivated soils. Qiao, Y., Wang, T., Huang, Q., Guo, H., Zhang, H., Xu, Q., Shen, Q. and Ling, N., 2024. Core species impact plant health by enhancing soil microbial cooperation and network complexity during community coalescence. Soil Biology and Biochemistry. 188.http://dx.doi.org/10.1016/j.soil bio.2023.109231 Ribero, M.N. and Filloy, J., 2023. Geographical trends of soil‐associated biodiversity changes due to tree plantations in South America: Biome and climate constraints revealed through meta‐analysis. Global Ecology and Biogeography.http://dx.doi.org/10.111 1/geb.13739 Rogers, B.F. and Tate, R.L., 2001. Temporal analysis of the soil microbial community along a toposequence in Pineland soils. Soil Biology and Biochemistry. 33, 1389-1401.http://dx.doi.org/https://doi.org/10.1016/S 0038-0717(01)00044-X Sepp, S.-K., Vasar, M., Davison, J., Oja, J., Anslan, S., Al-Quraishy, S., Bahram, M., Bueno, C.G., Cantero, J.J., Fabiano, E.C., Decocq, G., Drenkhan, R., Fraser, L., Garibay Oriel, R., Hiiesalu, I., Koorem, K., Kõljalg, U., Moora, M., Mucina, L., Öpik, M., Põlme, S., Pärtel, M., Phosri, C., Semchenko, M., Vahter, T., Vasco Palacios, A.M., Tedersoo, L. and Zobel, M., 2023. Global diversity and distribution of nitrogen-fixing bacteria in the soil. Frontiers in Plant Science. 14.http://dx.doi.org/10.3389/fpl s.2023.1100235 Sermswan, R.W. and Wongratanacheewin, S., 2017. Physicochemical and Biological Factors of Soil and the Potential Use of Antagonistic Microbes for Biocontrol of Burkholderia pseudomallei. Current Tropical Medicine Reports. 4, 192-198.http://dx.doi.org/10.1007/s40 475-017-0125-3 Shafi, J., Tian, H. and Ji, M., 2017. Bacillus species as versatile weapons for plant pathogens: a review. Biotechnology & Biotechnological Equipment. 31, 446-459.http://dx.doi.org/10.1080/131028 18.2017.1286950 Shi, S., Nuccio, E.E., Shi, Z.J., He, Z., Zhou, J. and Firestone, M.K., 2016. The interconnected rhizosphere: High network complexity dominates rhizosphere assemblages. Ecol Lett. 19, 926-36.http://dx.doi.org/10.11 11/ele.12630 Silva, C.d.F., Medeiros, E.V.d., Santana, M.D., Araújo, M.B.d., Martins Filho, A.P. and Moura, M.F.d., 2018. SOIL MICROBIOLOGICAL ACTIVITY AND PRODUCTIVITY OF MAIZE FODDER WITH LEGUMES AND MANURE DOSES. Revista Caatinga. 31, Singh, V.K., Rai, S., Singh, D. and Upadhyay, R.S., 2021. Application of Soil Microorganisms for Agricultural and Environmental Sustainability: A Review, in: Dubey, S.K. and Verma, S.K. Eds.), Plant, Soil and Microbes in Tropical Ecosystems. Springer Singapore, Singapore, pp. 151-175. Sloan, W.T., Lunn, M., Woodcock, S., Head, I.M., Nee, S. and Curtis, T.P., 2006. Quantifying the roles of immigration and chance in shaping prokaryote community structure. Environmental Microbiology. 8, 732-740.http://dx.doi.org/10.1111/j.1462-2 920.2005.00956.x Sun, X., Chen, Z., Kong, T., Chen, Z., Dong, Y., Kolton, M., Cao, Z., Zhang, X., Zhang, H., Liu, G., Gao, P., Yang, N., Lan, L., Xu, Y. and Sun, W., 2022. Mycobacteriaceae Mineralizes Micropolyethylene in Riverine Ecosystems. Environmental Science & Technology. 56, 15705-15717.http://dx.doi.org/10.1021/a cs.est.2c05346 Syldatk, C., May, O., Altenbuchner, J., Mattes, R. and Siemann, M., 1999. Microbial hydantoinases – industrial enzymes from the origin of life? Applied Microbiology and Biotechnology. 51, 293-309.http://dx.doi.org/10.1007/s 002530051395 Szoboszlay, M. and Tebbe, C.C., 2021. Hidden heterogeneity and co-occurrence networks of soil prokaryotic communities revealed at the scale of individual soil aggregates. 10, e1144.http://dx.doi.org/https://doi.org/1 0.1002/mbo3.1144 Tang, F.H.M., Lenzen, M., McBratney, A. and Maggi, F., 2021. Risk of pesticide pollution at the global scale. Nature Geoscience. 14, 206-210.http://dx.doi.org/10.1038/s415 61-021-00712-5 Tao, J., Liu, X., Liang, Y., Niu, J., Xiao, Y., Gu, Y., Ma, L., Meng, D., Zhang, Y., Huang, W., Peng, D. and Yin, H., 2016. Maize growth responses to soil microbes and soil properties after fertilization with different green manures. Applied Microbiology and Biotechnology. 101, 1289-1299.http://dx.doi.org/10.1007/s00 253-016-7938-1 Trivedi, P., Leach, J.E., Tringe, S.G., Sa, T. and Singh, B.K., 2020. Plant–microbiome interactions: from community assembly to plant health. Nature Reviews Microbiology. 18, 607-621.http://dx.doi.org/10.1038/s41 579-020-0412-1 Wagg, C., Hautier, Y., Pellkofer, S., Banerjee, S. and Heijden, M.G.A.V.D., 2020. Diversity and asynchrony in soil microbial communities stabilizes ecosystem functioning. Cold Spring Harbor Laboratory. 10: 62813., Wahab, A., Batool, F., Muhammad, M., Zaman, W., Mikhlef, R.M., Qaddoori, S.M., Ullah, S., Abdi, G. and Saqib, S., 2024. Unveiling the complex molecular dynamics of arbuscular mycorrhizae: A comprehensive exploration and future perspectives in harnessing phosphate-solubilizing microorganisms for sustainable progress. Environmental and Experimental Botany. 219, 105633.http://dx.doi.org/https://doi.org/10.1016/j. envexpbot.2023.105633 Wang, P., Wang, X., Nie, J., Wang, Y., Zang, H., Peixoto, L., Yang, Y. and Zeng, Z., 2022a. Manure Application Increases Soil Bacterial and Fungal Network Complexity and Alters Keystone Taxa. Journal of Soil Science and Plant Nutrition. 22, 607-618.http://dx.doi.org/10.1007/s427 29-021-00673-z Wang, T., Duan, Y., Liu, G., Shang, X., Liu, L., Zhang, K., Li, J., Zou, Z., Zhu, X. and Fang, W., 2022b. Tea plantation intercropping green manure enhances soil functional microbial abundance and multifunctionality resistance to drying-rewetting cycles. Science of The Total Environment. 810.http://dx.doi.org/10.1016/j.scito tenv.2021.151282 Wilhelm, R.C., van Es, H.M. and Buckley, D.H., 2022. Predicting measures of soil health using the microbiome and supervised machine learning. Soil Biology and Biochemistry. 164, 108472.http://dx.doi.org/https://doi.org/10.1016 /j.soilbio.2021.108472 Wilpiszeski, R.L., Aufrecht, J.A., Retterer, S.T., Sullivan, M.B., Graham, D.E., Pierce, E.M., Zablocki, O.D., Palumbo, A.V. and Elias, D.A., 2019. Soil Aggregate Microbial Communities: Towards Understanding Microbiome Interactions at Biologically Relevant Scales. 85, e00324-19.http://dx.doi.org/doi:10.1128 /AEM.00324-19 Wu, C., Yan, B., Wei, F., Wang, H., Gao, L., Ma, H., Liu, Q., Liu, Y., Liu, G. and Wang, G., 2023. Long-term application of nitrogen and phosphorus fertilizers changes the process of community construction by affecting keystone species of crop rhizosphere microorganisms. Science of The Total Environment. 897.http://dx.doi.org/10.1016/j.scito tenv.2023.165239 Wu, W., Logares, R., Huang, B. and Hsieh, C.h., 2017. Abundant and rare picoeukaryotic sub‐communities present contrasting patterns in the epipelagic waters of marginal seas in the northwestern Pacific Ocean. Environmental Microbiology. 19, 287-300.http://dx.doi.org/10.1111/14 62-2920.13606 Wu, X., Rensing, C., Han, D., Xiao, K.-Q., Dai, Y., Tang, Z., Liesack, W., Peng, J., Cui, Z., Zhang, F. and Bouskill, N., 2022. Genome-Resolved Metagenomics Reveals Distinct Phosphorus Acquisition Strategies between Soil Microbiomes. mSystems. 7.http://dx.doi.org/https://doi.org/10.112 8/msystems.01107-21 Xi, N., Chu, C. and Bloor, J.M.G., 2018. Plant drought resistance is mediated by soil microbial community structure and soil-plant feedbacks in a savanna tree species. Environmental and Experimental Botany. 155, 695-701.http://dx.doi.org/10.1016/j.envex pbot.2018.08.013 Xiong, C. and Lu, Y., 2022. Microbiomes in agroecosystem: Diversity, function and assembly mechanisms. Environmental Microbiology Reports. 14, 833-849.http://dx.doi.org/10.1111/17 58-2229.13126 Xu, Q., Luo, G., Guo, J., Xiao, Y., Zhang, F., Guo, S., Ling, N. and Shen, Q., 2021. Microbial generalist or specialist: Intraspecific variation and dormancy potential matter. Molecular Ecology. 31, 161-173.http://dx.doi.org/10.111 1/mec.16217 Xue, Y., Chen, H., Yang, J.R., Liu, M., Huang, B. and Yang, J., 2018. Distinct patterns and processes of abundant and rare eukaryotic plankton communities following a reservoir cyanobacterial bloom. The ISME Journal. 12, 2263-2277.http://dx.doi.org/10.1038/s41 396-018-0159-0 Xun, W., Liu, Y., Li, W., Ren, Y., Xiong, W., Xu, Z., Zhang, N., Miao, Y., Shen, Q. and Zhang, R., 2021. Specialized metabolic functions of keystone taxa sustain soil microbiome stability. Microbiome. 9, 35.http://dx.doi.org/10.1186/s401 68-020-00985-9 Yang, X., Nian, J., Xie, Q., Feng, J., Zhang, F., Jing, H., Zhang, J., Dong, G., Liang, Y., Peng, J., Wang, G., Qian, Q. and Zuo, J., 2016. Rice Ferredoxin-Dependent Glutamate Synthase Regulates Nitrogen–Carbon Metabolomes and Is Genetically Differentiated between japonica and indica Subspecies %J Molecular Plant. 9, 1520-1534 Youssef, S.M., Shaaban, A., Abdelkhalik, A., Abd El Tawwab, A.R., Abd Al Halim, L.R., Rabee, L.A., Alwutayd, K.M., Ahmed, R.M.M., Alwutayd, R. and Hemida, K.A., 2023. Compost and Phosphorus/Potassium-Solubilizing Fungus Effectively Boosted Quinoa’s Physio-Biochemical Traits, Nutrient Acquisition, Soil Microbial Community, and Yield and Quality in Normal and Calcareous Soils. 12, 3071 Zhang, X., Zhang, R., Gao, J., Wang, X., Fan, F., Ma, X., Yin, H., Zhang, C., Feng, K. and Deng, Y., 2017. Thirty-one years of rice-rice-green manure rotations shape the rhizosphere microbial community and enrich beneficial bacteria. Soil Biology and Biochemistry. 104, 208-217.http://dx.doi.org/10.1016/j.soi lbio.2016.10.023 Zhou, J. and Ning, D., 2017. Stochastic Community Assembly: Does It Matter in Microbial Ecology? Microbiology and Molecular Biology Reviews. 81, 10.1128/mmbr.00002-17.http://dx.doi.org/10.1128/m mbr.00002-17 Additional Declarations No competing interests reported. Supplementary Files supplementarymaterial.docx Abstract.pdf Cite Share Download PDF Status: Under Review Version 1 posted Reviewers invited by journal 12 Sep, 2025 Editor assigned by journal 26 Aug, 2025 Submission checks completed at journal 25 Aug, 2025 First submitted to journal 24 Aug, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7449409","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":514967227,"identity":"a5adec7a-d641-4045-9c64-d567a74b15c0","order_by":0,"name":"Gaosen Zhang","email":"","orcid":"","institution":"Northwest Institute of Eco-Environment and Resources，Chinese Academy of Sciences","correspondingAuthor":false,"prefix":"","firstName":"Gaosen","middleName":"","lastName":"Zhang","suffix":""},{"id":514967228,"identity":"7e2b6fdc-980a-4bee-852b-6a3d8c2dc795","order_by":1,"name":"Yiming Zhao","email":"","orcid":"","institution":"School of Life Sciences, Lanzhou university","correspondingAuthor":false,"prefix":"","firstName":"Yiming","middleName":"","lastName":"Zhao","suffix":""},{"id":514967230,"identity":"1b272321-ac29-4423-9753-731c58f1b6f8","order_by":2,"name":"Xiaoyi Liu","email":"","orcid":"","institution":"College of ecology, Lanzhou university","correspondingAuthor":false,"prefix":"","firstName":"Xiaoyi","middleName":"","lastName":"Liu","suffix":""},{"id":514967231,"identity":"d37083c3-b1c8-49f1-9fd7-d648daa84a94","order_by":3,"name":"Xinyue Wang","email":"","orcid":"","institution":"School of Life Sciences, Lanzhou university","correspondingAuthor":false,"prefix":"","firstName":"Xinyue","middleName":"","lastName":"Wang","suffix":""},{"id":514967232,"identity":"b903c0b5-d696-45d6-8ddc-74e6975a6598","order_by":4,"name":"Jiří Doležan","email":"","orcid":"","institution":"Institute of Botany of the Czech Academy of Sciences","correspondingAuthor":false,"prefix":"","firstName":"Jiří","middleName":"","lastName":"Doležan","suffix":""},{"id":514967233,"identity":"280324aa-0735-43e4-8fb9-0b82b1111b76","order_by":5,"name":"Pierre Liancourt","email":"","orcid":"","institution":"Faculty of Science, University of South Bohemia","correspondingAuthor":false,"prefix":"","firstName":"Pierre","middleName":"","lastName":"Liancourt","suffix":""},{"id":514967234,"identity":"53b65e22-ad95-469f-b393-c6c261e30a4c","order_by":6,"name":"Jiansheng Ye","email":"","orcid":"","institution":"College of ecology, Lanzhou university","correspondingAuthor":false,"prefix":"","firstName":"Jiansheng","middleName":"","lastName":"Ye","suffix":""},{"id":514967235,"identity":"d428030e-f7fe-414d-9ac1-a9d962986638","order_by":7,"name":"Jiudong Zhang","email":"","orcid":"","institution":"Institute of Soil, Fertilizer, and Water Saving Agriculture, Gansu Academy of Agricultural Sciences","correspondingAuthor":false,"prefix":"","firstName":"Jiudong","middleName":"","lastName":"Zhang","suffix":""},{"id":514967236,"identity":"ef3b58cd-183e-4322-b52d-a03e861b5db4","order_by":8,"name":"Yong Chen","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA2ElEQVRIiWNgGAWjYDACCSjNzw6mmEnQItlMshaDw8Rq4Z/dfOwxT8Udu82H2Z9JMFRYJzawnz2A35I7x9KNec48S952mCFNguFMemIDT14CXi0GEjlm0rxth5PNDjMck2BsO5zYIMFjQEBL/jewFuNmxjYJxn9EaclhA2mxM2BmZpNgbCBCi8SNNDPJOWcOJ0gcZmO2SAB6rI0nB78W/hnJzyTeVBy2529vf3jjQ421bD/7GfxaQICJh4EhsQHESgBiNoLqgYDxBwODPTEKR8EoGAWjYIQCAHb6PuAzxAbQAAAAAElFTkSuQmCC","orcid":"","institution":"School of Life Sciences, Lanzhou university","correspondingAuthor":true,"prefix":"","firstName":"Yong","middleName":"","lastName":"Chen","suffix":""}],"badges":[],"createdAt":"2025-08-25 03:53:18","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7449409/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7449409/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":91700742,"identity":"537a8a13-526c-435b-bc18-4edb88ae2b5d","added_by":"auto","created_at":"2025-09-19 10:28:27","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1116887,"visible":true,"origin":"","legend":"\u003cp\u003eLegend not included with this version\u003c/p\u003e","description":"","filename":"fig1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7449409/v1/53f66a63a8c936e4dc87bc33.jpg"},{"id":91700743,"identity":"5f4d0df8-7552-4834-a56b-91e3af4796ba","added_by":"auto","created_at":"2025-09-19 10:28:27","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1302393,"visible":true,"origin":"","legend":"\u003cp\u003eLegend not included with this version\u003c/p\u003e","description":"","filename":"fig2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7449409/v1/ee707d2d2e401b58d6a1da53.jpg"},{"id":91700751,"identity":"247abd98-45af-4cd3-9799-a4c82e98751e","added_by":"auto","created_at":"2025-09-19 10:28:27","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":3123605,"visible":true,"origin":"","legend":"\u003cp\u003eLegend not included with this version\u003c/p\u003e","description":"","filename":"fig3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7449409/v1/25c4bd62f593679f02325d0a.jpg"},{"id":91700747,"identity":"482ef12f-0af3-4fc4-9dc1-52611bf64e01","added_by":"auto","created_at":"2025-09-19 10:28:27","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1919359,"visible":true,"origin":"","legend":"\u003cp\u003eLegend not included with this version\u003c/p\u003e","description":"","filename":"fig4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7449409/v1/d8926fa779192f6a7ee11129.jpg"},{"id":91702110,"identity":"55143291-1f74-4498-9877-a3a2ac9eabd6","added_by":"auto","created_at":"2025-09-19 10:44:27","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":5884396,"visible":true,"origin":"","legend":"\u003cp\u003eLegend not included with this version\u003c/p\u003e","description":"","filename":"fig5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7449409/v1/c97d7d5ebc57fd1e33f2cf91.jpg"},{"id":91700756,"identity":"465b0cfd-fb10-4f38-8201-b36808876692","added_by":"auto","created_at":"2025-09-19 10:28:28","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":2989657,"visible":true,"origin":"","legend":"\u003cp\u003eLegend not included with this version\u003c/p\u003e","description":"","filename":"fig6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7449409/v1/10809789d37496f572bf61e6.jpg"},{"id":91701150,"identity":"f2e38e03-9637-4de0-8fbc-3177b470182c","added_by":"auto","created_at":"2025-09-19 10:36:28","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":3824161,"visible":true,"origin":"","legend":"\u003cp\u003eLegend not included with this version\u003c/p\u003e","description":"","filename":"fig7.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7449409/v1/f657a39bcd6616feb5d497ea.jpg"},{"id":91702111,"identity":"17a73f0a-2894-4228-a4a1-8e7b7c80ef6a","added_by":"auto","created_at":"2025-09-19 10:44:27","extension":"jpg","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":846088,"visible":true,"origin":"","legend":"\u003cp\u003eLegend not included with this version\u003c/p\u003e","description":"","filename":"fig8.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7449409/v1/0be4796891d94bbe1c2417b1.jpg"},{"id":91702634,"identity":"dabbf495-d2cf-45c4-991a-bb253d75f53e","added_by":"auto","created_at":"2025-09-19 10:52:35","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":22036952,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7449409/v1/ab2141a7-b35b-4857-a2b5-a83ce8560c33.pdf"},{"id":91701148,"identity":"a47873f7-f794-48ce-9968-9a07d91c2d12","added_by":"auto","created_at":"2025-09-19 10:36:27","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":946243,"visible":true,"origin":"","legend":"","description":"","filename":"supplementarymaterial.docx","url":"https://assets-eu.researchsquare.com/files/rs-7449409/v1/9d683649f12ebfd79eef2404.docx"},{"id":91700746,"identity":"f6539509-68b4-43c8-9484-0d5fd04286bd","added_by":"auto","created_at":"2025-09-19 10:28:27","extension":"pdf","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":955463,"visible":true,"origin":"","legend":"","description":"","filename":"Abstract.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7449409/v1/1cdb5847566a5345814ea14f.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Green manure intercropping reshapes beneficial microbial consortia to enhance soil multifunctionality and agroecosystem resilience","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eEcosystem services such as soil fertility, nutrient cycling, water availability, and pest and disease control are fundamental to the productivity of agroecosystems (Altieri et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). The effectiveness of an agroecosystem is influenced by the decisions and techniques used in agricultural management. Compared to chemical fertilizers, green fertilizers can provide nutrient sources for subsequent crops, offer more organic substrates and carbon resources for microbial growth, increase microbial activity and diversity (Jangid et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2008\u003c/span\u003e), improve soil quality, and boost crop yields(Espersch\u0026uuml;tz et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). Maize-legume intercropping systems have been shown to provide substantial integrative benefits (Li et al., \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2021a\u003c/span\u003e). Over 40% of the Earth's surface is covered by dry and semi-arid regions, home to vast populations relying predominantly on agriculture to meet their basic needs (Golla, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Consequently, there is an urgent need to synergize crop production and environmental health improvements in these regions under prolonged resource, environmental, and population pressures (Li et al., \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn predicting soil health indicators, biological data may outperform physical or chemical soil properties (Wilhelm et al., \u003cspan citationid=\"CR107\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). However, these properties are interrelated, as the microbiome's structure and function are influenced by the soil's chemical and physical characteristics, while the soil's characteristics are also affected by the microbiome. Increasing evidence reveals that soil and beneficial microbial communities provide numerous life-supporting activities for their host plants. Soil microorganisms assist in various functional processes, including nutrient cycling, disease suppression, primary production, and stress resistance. Thus, functional microbial communities in soil play a critical role in ecosystem multifunctionality (EMF) (Han et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Singh et al., \u003cspan citationid=\"CR91\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), and changes in their abundance are powerful predictors of EMF. Cultivating beneficial microorganisms to improve crop productivity and ecosystem health is considered one of the most promising biotechnological solutions for achieving food security and sustainable agriculture(Xiong and Lu, \u003cspan citationid=\"CR116\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The stability and functioning of soil microbial communities are highly dependent on the role of key beneficial microorganisms as \u0026ldquo;core species\u0026rdquo;. (Banerjee et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Banerjee et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). These key groups may play a distinct and critical role in organizing the soil microbial community structure, with downstream effects on ecosystem processes. Key functional microbial communities in soil promote soil nutrient cycling by managing biomass and enzyme production, thereby enhancing ecosystem function (Li et al., \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2023b\u003c/span\u003e). In this context, key functional microorganisms are also considered beneficial microorganisms. Furthermore, losing key groups may lead to the disintegration of modules and networks, highlighting their crucial role in ensuring ecosystem stability (Shi et al., \u003cspan citationid=\"CR89\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). A relatively stable microbial community is necessary for the long-term viability of terrestrial ecosystem processes and services (Griffiths and Philippot, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Generally, the soil microbiome exhibits functional redundancy, meaning that a minor decrease in the abundance of any group may have a negligible impact on the soil microbiome's overall function, as other bacteria can perform the same role (Nannipieri et al., \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). If a community is sufficiently stable, continuous environmental disruptions will not cause significant changes in composition or function. It follows that beneficial microorganisms in the soil have a greater capacity than the community to provide essential ecosystem services. Trivedi et al (Trivedi et al., \u003cspan citationid=\"CR99\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) demonstrated a positive correlation between beneficial bacterial abundance and the functions performed by the soil microbial community for the plant, as well as an indirect increase in plant growth and nutrient acquisition due to beneficial microorganisms' modification of the structure and functions of the overall microbial community.\u003c/p\u003e\u003cp\u003eGlobally maize is a major crop humans and animals consume (Silva et al., \u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Its large and consistent production is crucial for ensuring China's food security. Northwestern China produces the majority of the country's maize crop, which is vital to maintaining consistent production levels and preserving the condition of agricultural soils. Based on the long-term positioning experiment of maize intercropping conducted at the Gansu Academy of Agricultural Sciences in 2009, this study constructed a species library of local beneficial microorganisms at the genus level, focusing on four beneficial microbial functional groups (NPK, PA, DR, and PD). The aims were: (1) to explore the effects of different fertilizer application modes on the diversity and composition of the soil's beneficial functional microbiomes and their community construction; (2) to investigate the contribution of beneficial microorganisms to the total community in terms of stability and functional metabolism; (3) to reveal the contribution of beneficial microorganisms to the soil microenvironment and ecosystem multifunctionality; and (4) to classify species that contribute positively to microbial communities and soil ecosystems as beneficial microorganisms. The results of this study provide a theoretical foundation for further investigation of beneficial microorganisms to improve soil health, maintain community stability, enhance soil ecosystem function, and improve corn yield, expand the ecological definition of beneficial microorganisms, as well as provide a reference for the research and development of highly effective mycological agents.\u003c/p\u003e"},{"header":"2. Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1 Site description\u003c/h2\u003e\u003cp\u003eThe experiment was initiated in 2009 at the Wuwei Agricultural Experiment Station of the Gansu Academy of Agricultural Sciences in China (38\u0026deg;37 \u0026prime;N, 102\u0026deg;40 \u0026prime;E). The test site experiences a temperate continental arid climate, with an average annual temperature of 7.7\u0026deg;C, annual sunshine hours ranging from 2,800 to 3,300 hours, total annual solar radiation between 140 and 158 kJ/cm, a frost-free period of 150 days, an average rainfall of 222 mm, and evapotranspiration of 2,021 mm. The basic physicochemical properties of the soil were as follows: soil bulk density of 1.39 g/cm\u003csup\u003e3\u003c/sup\u003e; soil organic matter content of 19.4 g/kg; total nitrogen (TN) of 1.36 g/kg; total phosphorus (TP) of 0.43 g/kg; total potassium (TK) of 20.9 g/kg; nitrate nitrogen (NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e-N) of 12.85 mg/kg; ammonium nitrogen (NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N) of 0.39 mg/kg; available phosphorus (AP) of 17.92 mg/kg; and available potassium (AK) of 121.21 mg/kg.\u003c/p\u003e\u003cp\u003eThe Hexi Oasis Irrigation District is one of the largest maize-producing areas in the country, with intensive agriculture widely practiced. Sweet peas and pin peas are used as green manure and are planted around March 20 each year. Maize is sown in April when the green manure seedlings are growing. Two methods are employed for applying green manure: root stubble and pressed green. Root stubble involves cutting the plant's above-ground parts (including stems, leaves, and legumes) while leaving the roots in the soil. Pressed green involves turning the green manure (whole plant) into the soil. The test area consisted of 15 plots, and all treatments were replicated using a completely randomized design (n\u0026thinsp;=\u0026thinsp;3). A 50\u0026times;30 cm ridge bed was used between the sample plots, and each plot covered an area of 19.8 m\u003csup\u003e2\u003c/sup\u003e (5.5\u0026times;3.6 m). The study investigated five fertilization patterns: (1) root-stubble intercropping with coniferous pea (CPR), (2) green-stubble intercropping with coniferous pea (CPG), (3) root-stubble intercropping with sweet pea (SPR), (4) green-stubble intercropping with sweet pea (SPG), and (5) no green fertilizer application (CK). The layout of the plots is depicted in Fig.\u0026nbsp;1.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2 Sample collection and soil characterization\u003c/h2\u003e\u003cp\u003eIn June 2022, soil samples were collected from each plot using an S-shaped random sampling method at a depth of 10\u0026ndash;20 cm (REF). Five cores were randomly collected from each plot and combined into one sample, with three replicates per treatment. After removing rocks and plant residues, a portion of the soil was stored at -20 \u0026deg; C for subsequent DNA extraction, and the remaining soil was stored at 4 \u0026deg; C for soil property determination.\u003c/p\u003e\u003cp\u003eSoil moisture content (VWC) was determined by drying the soil at 105\u0026deg;C for 12 hours. Soil bulk density (VW) was determined using the ring knife method, and soil texture was analyzed using a laser particle size analyzer. Soil pH was measured with a pH meter (LeiMagnet PHS-3E, Shanghai, China), and soil electrical conductivity (EC) was measured with a conductivity meter (LeiMagnet DDSJ-307F, Shanghai, China) using a soil-to-water ratio of 1:2.5.Soil total carbon (TC) and TN were determined using an elemental analyzer (Vario Macro Elementar, Munich, Germany). Total P (TP) was extracted using the H\u003csub\u003e2\u003c/sub\u003eSO\u003csub\u003e4\u003c/sub\u003e-HNO\u003csub\u003e3\u003c/sub\u003e digestion method and determined by the molybdenum blue method. The concentrations of ammonium (NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N) and nitrate (NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e-N) were determined using a flow automatic analyzer (Smartchem, Munich, Germany). Soil phosphatase activity was determined by phenyl disodium phosphate colorimetry, soil urease activity by sodium phenol-sodium hypochlorite colorimetry, and soil sucrase activity by 3, 5-dinitrosalicylic acid colorimetry. Maize yield per acre was measured at maturity.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3 Soil DNA extraction and metagenomic sequencing\u003c/h2\u003e\u003cp\u003eAccording to the manufacturer's instructions, total soil DNA was extracted from 0.5 g of mixed fresh soil using the Mo Bio PowerSoil\u0026trade; DNA separation kit (Mo Bio Laboratories, Carlsbad, CA, USA). The mass and concentration of soil DNA were measured using a NanoDrop 2000 spectrophotometer (Thermo Scientific, USA), and the samples were sequenced via metagenomic sequencing. Sequencing was performed on the Illumina HiSeq 4000 platform at Majorbio Bio-Pharm Technology Co., Ltd. (Shanghai, China). Covaris M220 (China Gene Co., Ltd.) was used to fragment the DNA extracts into segments with an average size of approximately 400 bp. PE libraries were constructed using the NEXTflex\u0026trade; Rapid DNA-Seq Kit (Bioo Scientific, Austin, TX, USA). Bridge PCR and sequencing were performed using the NovaSeq Reagent Kit (Illumina, USA). The metagenomic raw read data have been deposited in the NCBI sequence read file database (entry number: PRJNA1086341). After the original sequences were optimized for splitting, quality cutting, and pollution removal, the optimized sequences were used for splicing assembly and gene prediction. Sequences were mapped to the NCBI-NR/KEGG database to classify and annotate the species-function of Reads.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.4 Screening for beneficial microorganisms in microbial communities\u003c/h2\u003e\u003cp\u003eLiterature was collected using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) program(Murphy and Romanuk, \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Ribero and Filloy, \u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) (Figure_S1). An extensive literature survey was conducted until June 2023 through the Web of Science (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://apps.webofknowledge.com/\u003c/span\u003e\u003cspan address=\"http://apps.webofknowledge.com/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) and Google Scholar (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.google.com/\u003c/span\u003e\u003cspan address=\"https://www.google.com/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). Targeted searches were performed using various combinations of keywords in the title, keywords, or abstract, e.g. (\"microorganisms\" or \"soil microorganisms,\" or \"farm microorganisms\" or \"beneficial microorganisms\") and (\"nitrogen fixation\" or \"phosphorus solubilization\" or \"potash solubilization\" or \"drought resistance\" or \"pathogen antagonism\" or \"plastic degradation\"). A total of 4,743 publications were retrieved and screened using the following criteria: (i) Studies involving field experiments and laboratory culture experiments focused on the beneficial effects of microorganisms on soil or crops; (ii). Beneficial traits were tested in situ or in vitro, including at least one function (nitrogen fixation, phosphorus solubilization, drought resistance, pathogen antagonism, plastic degradation); (iii) Results demonstrated beneficial microorganisms at the generic level; iv. Studies provided average values and repetitions (\u0026ge;\u0026thinsp;3). After screening for duplicates and content assessment, 82 related papers were identified, 107 related genera were selected at the genus level, and 56 beneficial genera (including multifunctional genera) were retained and listed in Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e after comparison and screening with the species annotation table in the sample. Furthermore, because some beneficial genera may contain potentially phytopathogenic bacteria, this study used the list of phytopathogenic bacteria compiled by Li et al (Li et al., \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2023a\u003c/span\u003e) (which includes almost all known phytopathogenic bacteria recorded up to 2022) to exclude potentially pathogenic species when annotating species abundance using a database of native beneficial microorganisms.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e2.5 Statistical analyses\u003c/h2\u003e\u003cp\u003eAll experiments were conducted using a completely randomized design (n\u0026thinsp;\u0026ge;\u0026thinsp;3). Analysis of variance (ANOVA) and Duncan's test (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) were used for multiple comparisons of physicochemical properties, enzyme activities, yield, and microbial diversity of maize soils under different fertilization treatments using SPSS Statistics 26 (IBM Corporation, Armonk, NY, USA). Microbial α-diversity was assessed using the Shannon, Simpson, and Chao indices. Partial Least Squares Discriminant Analysis (PLS-DA) based on the Bray-Curtis distance matrix was performed using the \"vegan\" package in R software (R-4.1.0) to explore similarities and differences (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) in changes in beneficial microbial communities of different functions between treatments. The JVenn program (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://jvenn.toulouse.inra.fr/app/index.html\u003c/span\u003e\u003cspan address=\"http://jvenn.toulouse.inra.fr/app/index.html\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) was used to compare common and differential genera across functional beneficial microbial communities. Some data were visualized using GraphPad Prism 8.0 (GraphPad, La Jolla, CA, USA).\u003c/p\u003e\u003cp\u003eBased on previous research, the microbial community was divided into six categories: always abundant taxa (AAT), conditionally abundant taxa (CAT), always rare taxa (ART), conditionally rare taxa (CRT), moderate taxa (MT), and conditionally rare and abundant taxa (CRAT) (Xue et al., \u003cspan citationid=\"CR118\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). The proportion of beneficial taxa within the total community was observed with categorization. Linear discriminant analysis effect size (LEfSe) was used to determine the significantly enriched taxa under different treatments, with the threshold for the logarithmic LDA score of the discriminant feature set at 2 and the α value set at 0.05. The niche width of the taxonomic group was obtained using the \"niche. width\" function (Levins algorithm) of the \"spaa\" package in R. The species occurrence frequency was randomly rearranged 1,000 times using the permutation algorithm implemented in the \"EcolUtils\" software package. The upper limit of the confidence interval, where the niche width of a species exceeds 95%, was classified as a generalized species of the plot, while a lower limit defined it as a specialized species of the plot (Wu et al., \u003cspan citationid=\"CR111\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). The neutral community model (NCM) and normalized stochasticity ratio (NST) were used to evaluate the relative importance of deterministic or stochastic processes in microbial community structuring (Ning et al., \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Sloan et al., \u003cspan citationid=\"CR92\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). For NCM, we used the\"Hmisc\", \"minpack. lm\", and \"stats 4\" R packages with default parameters for model fitting. The \"NST\" software package was used to calculate standardized stochasticity ratios for all treatments at each locus, using various similarity measures and zero model algorithms, randomness ratios, standard effects, and modified Raup Crick metrics to calculate NST.\u003c/p\u003e\u003cp\u003eConsidering the stability and reliability of the microbial network, we constructed the microbial co-occurrence network by combining the two green manure fertilizer application methods of the same type. We calculated the spearman's correlation coefficient and set the thresholds at R\u0026thinsp;\u0026gt;\u0026thinsp;0.65 and \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05. The\"igraph\" package in R was used to extract the topological parameters of the network under different fertilization methods and calculate intra-module connectivity (Zi) and inter-module connectivity (Pi), and we used Gephi (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://gephi.org/\u003c/span\u003e\u003cspan address=\"https://gephi.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) to calculate the network topological parameters. The network was visualized using Gephi (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://gephi.org/\u003c/span\u003e\u003cspan address=\"https://gephi.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). The \"linkET\" package was used to perform a Mantel test for correlation between environmental factors and yields with beneficial microbial taxa. A dichotomous network diagram was drawn using the \"netET\" and \"ggraph\" packages to show the correlation between the beneficial genera and the environmental factors. The main microbial predictors of soil processes were identified by constructing a random forest model using the \"randomForest\" package(Liaw and Wiener, \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2001\u003c/span\u003e), and the significance of each predictor was evaluated using the \"rfPermute\" package. Using 17 variables as indicators of ecosystem function (Table S2), Z-score transformation was performed on individual functional indicators, and the soil ecosystem multifunctionality (EMF) index was calculated using the mean method(Delgado-Baquerizo et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Luo et al., \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003e3.1 Analysis of beneficial microbial communities under green manure treatment\u003c/h2\u003e\u003cp\u003eBased on Illumina platform metagenomic sequencing data, 1,335,170,654 clean reads, each 150 bp length, were obtained (average 89,011,376 per sample) (Table S3). Annotated species were screened at the genus level using Web of Science and Google Scholar search results. Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e lists four functional taxa of soil-beneficial microorganisms selected based on distinct functions: a) genus favoring the uptake of N, P, and K elements ( NPK); b) genus with antagonistic effects against pathogenic bacteria (PA); c) genus with beneficial resistance to arid environments (DR); and d) genus with plastic degradation functions (PD). Intercropping maize with various green manures decreased the Shannon and Simpson diversity indices of the NPK, PA, DR, and PD communities compared to monocropping, but no treatment significantly affected the Chao index, which measures the richness of these beneficial communities (Fig.\u0026nbsp;2a). However, the structure of the four beneficial microbial communities was altered by long-term green manure intercropping and different fertilization strategies. PLS-DA analysis revealed that samples under green manure treatments of coniferous pea (CPG and CPR) were more tightly clustered than those of the control (CK) (Fig.\u0026nbsp;2b).\u003c/p\u003e\u003cp\u003eFurther investigation was conducted to determine the composition of beneficial microbial communities with varying functions under different treatments (Fig.\u0026nbsp;3a). The abundance bar-stacked plots showed that, among the four beneficial microbial communities, genera with the same function had similar compositions under various treatments. However, the abundance of the dominant genera increased in all of them after applying green manure compared to CK. The abundance of the NPK and DR communities was higher under the green manure returning treatments (CPG and SPG) than in the relic stubble treatments (CPR and SPR). The most abundant genera in the NPK community were \u003cem\u003eMicrovirga, Bradyrhizobium\u003c/em\u003e, and \u003cem\u003eMesorhizobium\u003c/em\u003e; in the PA community, \u003cem\u003eStreptomyces, Micromonospora\u003c/em\u003e, and \u003cem\u003eAmycolatopsis\u003c/em\u003e were the most abundant; in the DR community, \u003cem\u003eBacillus\u003c/em\u003e and \u003cem\u003ePseudomonas\u003c/em\u003e were the dominant genera; and in the PD microbial community, \u003cem\u003eMycobacterium, Mycobacterium\u003c/em\u003e, and \u003cem\u003eBacillus\u003c/em\u003e were dominant. An Edwards-Venn diagram (Figure_3b) was created to analyze the similarities and differences in the various functional microbial taxa compositions using Jvenn (Huang et al., \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The findings revealed that the four beneficial microbial communities\u0026mdash;NPK, PA, DR, and PD\u0026mdash;contained 26, 7, 7, and 9 distinct genera, respectively. Compared to CK, the presence of seven multifunctional genera (\u003cem\u003eBacillus, Pseudomonas, Enterobacter, Stenotrophomunas, Herbaspirllium, Ochrobactrum, and Breribacillus\u003c/em\u003e) increased significantly (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Figure S2).\u003c/p\u003e\u003cp\u003eBeneficial microbial communities varied proportionately across all treatments, ranging from approximately 15.3\u0026ndash;16.23% (Fig.\u0026nbsp;4a). The highest percentage was recorded by the NPK community (10.32%), followed by PA (3.15%), PD (1.53%), and DR (0.17%). When green manure was applied, the proportion of all four functionally beneficial microorganisms in the community increased. Most of the community's genera were classified as AT (47.12\u0026ndash;48.85%) and MT (39.56\u0026ndash;40.22%) under each fertilization management mode (Figure S3a). Only four genera of beneficial microorganisms were found to belong to AT, 29 to MT, and 19 to RT (Figure_S3b). At the genus level, LefSe analysis (LDA\u0026thinsp;\u0026gt;\u0026thinsp;2) showed that 12 and 5 genera were enriched in the CK and SPR groups, respectively, none of which contained beneficial genera. The CPG group was the most enriched in differential genera, with 16 genera, including 5 beneficial genera. The CPR and SPG groups each included one beneficial genus among the differential genera (Fig.\u0026nbsp;4b).\u003c/p\u003e\u003cp\u003eCalculating the Levins niche width index of beneficial microbial communities with different functions revealed that the NPK and PA communities had much higher values than the DR and PD communities, with the DR community having the lowest niche width index (Fig.\u0026nbsp;4c). Generalists and specialists were divided based on niche breadth. The findings revealed that generalists accounted for a higher proportion in the NPK and DR communities, at 3.9% and 4.3%, respectively, while there were no generalists in the PD community (Fig.\u0026nbsp;4c).To better understand the potential role of stochastic processes in the formation of beneficial microbial communities, this study used a neutral community model (NCM) to predict the relationship between species occurrence frequency and relative abundance in the four functional communities (Fig.\u0026nbsp;4e). The findings revealed that the NCM effectively predicted the stochastic process of beneficial microbial communities, with strong explanatory power (R\u003csup\u003e2\u003c/sup\u003e) in all four functional communities, and that the stochastic process had a greater impact on the formation of the NPK and PA communities. Among the four functional communities, NPK (m\u0026thinsp;=\u0026thinsp;0.198) had the highest migration rate, suggesting the community's lowest diffusion constraint, followed by PA and DR (m\u0026thinsp;=\u0026thinsp;0.195), while the PD community had the strongest diffusion limitation. This is consistent with the estimated results of microbial community diffusion shown by Nm. We statistically investigated the roles of deterministic (\u0026lt;\u0026thinsp;50%) and stochastic (\u0026gt;\u0026thinsp;50%) processes in beneficial microbial community development using the null model's standardized stochastic rate (NST). As shown in Fig.\u0026nbsp;4d, all four functional communities had NST values greater than 50%, indicating that stochastic processes dominated and contributed similarly to the community construction process (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003e3.2 The importance of beneficial microorganisms in the overall community and ecosystem\u003c/h2\u003e\u003cp\u003eCo-occurrence networks were constructed for the top 800 genera regarding microbial community abundance under CK, green manure returning, and relic stubble treatments (Fig.\u0026nbsp;5a). Additionally, sub-networks of beneficial microbial communities were constructed (Fig.\u0026nbsp;5b). Data on network-related topological properties are presented in Table S4, and the findings demonstrate that adding green manure improved species connections and increased the network's overall complexity. To identify key species in the network, nodes were classified by computing within-module connectivities (Zi) and among-module connectivities (Pi) (Figure_5c). Table S5 lists the key species in the network identified by these values. Compared to CK, green manure returning and root stubble treatments led to an increase in 166 and 97 core genera, which included four important beneficial genera: \u003cem\u003eBrevibacillus\u003c/em\u003e (NPK, PA), \u003cem\u003eMarinobacterium\u003c/em\u003e (PD), \u003cem\u003eAlcanivorax\u003c/em\u003e (PD), and \u003cem\u003eAcinetobacter\u003c/em\u003e (NPK). Also, different fertilization treatments increased the relative abundance of these core genera (Figure_5c). Most of the major beneficial genera in the overall network belonged to NPK, with PA coming in second (Table S5).In addition, five connectors were identified in the sub-network of beneficial microorganisms as \u003cem\u003eBacillus\u003c/em\u003e (NPK, PA, DR, PD), \u003cem\u003eBrevibacillus\u003c/em\u003e (NPK, PA), \u003cem\u003eEnsifer\u003c/em\u003e (NPK), \u003cem\u003eNocardia\u003c/em\u003e (PD) and \u003cem\u003eStreptomyces\u003c/em\u003e (PA), with the application of green manures increasing the abundance of these genera. Meanwhile, Figure_S4 shows the Zi and Pi values of beneficial genera in the core microorganisms of the network under different treatments, and we found that the application of green manure mainly increased the Pi value.\u003c/p\u003e\u003cp\u003eThe average variation degree (AVD) is used to quantify community stability. The lower the AVD index, the more stable the community is and the greater its resistance to disruption. As indicated in Fig.\u0026nbsp;5d, regardless of the type and fertilizing method of green manure, when compared to CK, the AVD value decreased significantly, while community stability increased under green manure treatment. We investigated the association between AVD values and the number of core beneficial genera to assess the importance of core beneficial microorganisms in overall community stability. Except for \u003cem\u003eNocardia\u003c/em\u003e, all seven genera were significantly negatively correlated with AVD (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), with \u003cem\u003eStreptomyces\u003c/em\u003e showing the highest negative correlation.\u003c/p\u003e\u003cp\u003e(\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01) (Figure_5e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003e3.3 Contribution of beneficial microorganisms to community function\u003c/h2\u003e\u003cp\u003eFigure 6a shows the relative contribution of core beneficial genera to the entire community's KEGG pathway level 2 metabolic pathways under various green manures and fertilization methods based on species and functional contribution analysis. The core beneficial genera were primarily involved in the global and overview maps route (which included processes such as microbial metabolism, carbon metabolism, fatty acid metabolism, secondary metabolites, and amino acid biosynthesis), followed by carbohydrate metabolism and amino acid metabolism. Fertilization treatments significantly impacted the contributions of \u003cem\u003eAcinetobacter, Alcanivorax, Brevibacillus\u003c/em\u003e, and \u003cem\u003eMarinobacterium\u003c/em\u003e to overall community function. Green manure application increased the relative contribution of \u003cem\u003eAcinetobacter\u003c/em\u003e to carbohydrate metabolism and promoted the involvement of this beneficial genus in amino acid metabolism and glycan biosynthesis and metabolism pathways under coniferous pea treatment (CPG/CPR). Green manure of four application modes increased the relative contribution of \u003cem\u003eAlcanivorax\u003c/em\u003e to carbohydrate metabolism to varying degrees (5.26% \u0026minus;\u0026thinsp;10.92%), and the green-stubble treatment (CPG/SPG) promoted the involvement of this beneficial genus in energy metabolism, while the addition of green manure enhanced the relative contribution of \u003cem\u003eMarinobacterium\u003c/em\u003e to lipid metabolism and \u003cem\u003eBrevibacillus\u003c/em\u003e to the metabolism of cofactors and vitamins. The relative contribution of the core beneficial genera to the top 10 metabolic pathways in terms of gene abundance in the total community KEGG pathway level 3 was further investigated under different fertilizer treatments (Figure_6b), and it was found that they were mainly involved in metabolic pathways, biosynthesis of secondary metabolites, and microbial metabolism in diverse environments. Fertilization increased the relative contribution of \u003cem\u003eAcinetobacter\u003c/em\u003e to metabolic pathways by 11.82% \u0026minus;\u0026thinsp;23.85%, and the sweet pea treatment (SPG/SPR) was more conducive to the involvement of \u003cem\u003eAlcanivorax\u003c/em\u003e in pyruvate metabolism.\u003cem\u003eBrevibacillus\u003c/em\u003e contribution to microbial metabolism in diverse environments was elevated by the application of green manure (4.30% \u0026minus;\u0026thinsp;6.24%), and the contribution to biosynthesis of amino acids also increased (0.21% \u0026minus;\u0026thinsp;3.16%). Moreover, the contribution of \u003cem\u003eMarinobacterium\u003c/em\u003e to pyruvate metabolism was zero when no green manure was applied, and the four green manure treatments promoted its participation in pyruvate metabolism. The relative contribution of the core beneficial genera to the top 50 functional genes in terms of abundance was then analyzed (Figure_6c). \u003cem\u003eAcinetobacter\u003c/em\u003e, \u003cem\u003eAlcanivorax\u003c/em\u003e, \u003cem\u003eBrevibacillus\u003c/em\u003e, and \u003cem\u003eMarinobacterium\u003c/em\u003e had a high overall contribution to functional genes, with \u003cem\u003eAcinetobacter\u003c/em\u003e and \u003cem\u003eAlcanivorax\u003c/em\u003e contributing significantly to the abundance of \u003cem\u003eatoB\u003c/em\u003e and \u003cem\u003eacnA\u003c/em\u003e genes, \u003cem\u003eBrevibacillus\u003c/em\u003e favoring the enrichment of \u003cem\u003eamiE\u003c/em\u003e, \u003cem\u003ehyuA\u003c/em\u003e, \u003cem\u003ehyuB\u003c/em\u003e, and \u003cem\u003eserA\u003c/em\u003e genes, and \u003cem\u003eMarinobacterium\u003c/em\u003econtributing significantly to the abundance of \u003cem\u003eGDH2\u003c/em\u003e, \u003cem\u003egatA\u003c/em\u003e, \u003cem\u003eand glnA\u003c/em\u003e genes.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003e3.4 The role of beneficial microbial communities in ecosystems\u003c/h2\u003e\u003cp\u003eThe physical and chemical characteristics of maize plots under different fertilization treatments are presented in Table S6. Applying different green fertilizers with varying fertilization methods significantly altered most soil properties compared to the control soil. Different green manure treatments markedly improved soil water content (VWC) and ammonia nitrogen (NH\u003csub\u003e4\u003c/sub\u003e⁺-N) content. Under the green manure returning treatments (CPG/SPG), the nitrate nitrogen (NO\u003csub\u003e3\u003c/sub\u003e⁻-N) and sucrase activity were significantly higher than CK (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), while the activities of phosphatase and urease were the highest under SPG treatment. The total nitrogen (TN) content increased under the root stubble treatments (CPR/SPR), and the soil carbon-nitrogen ratio (C/N) decreased (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) compared to CK and the green manure returning treatment. After applying green manure, soil bulk density significantly decreased (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Meanwhile, adding green manure significantly increased maize yield, regardless of the type and manner of fertilization. Nonetheless, the effects of all green manure treatments on soil texture, electrical conductivity (EC), total phosphorus (TP), and total carbon (TC) were less pronounced (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05). According to these findings, green manure enhanced soil fertility and increased maize yield by 1.8\u0026ndash;6.6%.\u003c/p\u003e\u003cp\u003eMantel tests (Fig.\u0026nbsp;7a) were carried out on the distance matrix of the total beneficial microbial communities and environmental factors to analyze the association between environmental variables and beneficial microorganisms. Compared to other environmental variables, the results suggested a substantial correlation between beneficial microbial communities and soil bulk weight (VW), soil water content (VWC), and maize yield (MY). Table S7 provides the individual values of the Mantel test parameters. It can be seen that VWC had the highest correlation (r\u0026thinsp;=\u0026thinsp;0.817, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001), followed by MY (r\u0026thinsp;=\u0026thinsp;0.423, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.007). Meanwhile, spearman correlation analysis showed that soil VW was significantly negatively correlated with VWC, soil nitrate nitrogen (NO\u003csub\u003e3\u003c/sub\u003e⁻-N) content, pH, and soil phosphatase (PHO) activity, while soil VWC was significantly positively correlated with soil ammoniacal nitrogen (NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N) content. Moreover, there was a substantial positive correlation between MY and soil VWC, NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e-N, NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N content, and a negative correlation between MY and soil VW. Using the random forest model (Fig.\u0026nbsp;7b), the correlations between the four functional beneficial microbial communities and environmental factors were further evaluated. It was discovered that beneficial communities with varying functions contributed differently to soil physicochemical properties and yield. The results of the correlation analysis indicated that the abundance of the NPK and PA communities had a significant positive correlation with soil VWC and MY (Table S8). Additionally, the abundance of the NPK community had a strong positive correlation (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01) with soil NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e-N content and the abundance of the PA community had a significant positive correlation (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) with soil NH\u003csub\u003e4\u003c/sub\u003e⁺-N content. Environmental factors and the DR and PD communities showed no meaningful association. It was discovered that the NPK and PA communities contributed more to the soil physicochemical differences under different treatments. Association analysis of differential core beneficial genera in the network and core genera in the beneficial microbial subnetwork with environmental factors (Figure_7c) revealed significant positive correlations between \u003cem\u003eBrevibacillus\u003c/em\u003e and soil TC and TP content. \u003cem\u003eAcinetobacter\u003c/em\u003e was significantly positively correlated with soil VWC and NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e-N content and both genera had a positive correlation with soil PHO activity and a substantial negative correlation with soil VW. Additionally, \u003cem\u003eAlcanivorax\u003c/em\u003e showed a significant positive correlation with soil TN, SC, and silt contents, while \u003cem\u003eStreptomyces\u003c/em\u003e had a significant positive correlation with sand fraction. However, \u003cem\u003eStreptomyces\u003c/em\u003e, \u003cem\u003eBacillus\u003c/em\u003e, and \u003cem\u003eNocardia\u003c/em\u003e all exhibited a significant negative correlation with soil URE activity, and \u003cem\u003eNocardia\u003c/em\u003e demonstrated a negative correlation with clay components.\u003c/p\u003e\u003cp\u003eThe average method was used to evaluate soil ecosystem multifunctionality (EMF), and the results showed that regardless of the type of green manure and fertilization method, the addition of green manure changed soil multifunctionality (Figure_7d). Specifically, under CPG treatment, the improvement of EMF was most significant (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), followed by SPR. The regression model in Figure_7e demonstrates a substantial positive association (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) between the relative abundance of the core beneficial genus \u003cem\u003eEnsifer\u003c/em\u003e and EMF. Additionally, there is a highly significant positive correlation (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01) between \u003cem\u003eAlcanivorax, Bacillus, Brevibacillus, Streptomyces\u003c/em\u003e, and EMF.\u003c/p\u003e\u003cp\u003eThis study identified a significant correlation between 11 network core genera (not previously reported as beneficial genera) and soil properties that contribute to soil health (Figure_8a), such as a significant positive correlation with soil moisture content (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) and a significant negative correlation with soil bulkiness (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), which is beneficial for improving sand content. Although there have been no research reports on their beneficial effects on soil and plants, they have made significant contributions to supporting community co-occurrence networks and soil physicochemical properties.It was also observed that \u003cem\u003eAureimonas, Hoeflea\u003c/em\u003e, \u003cem\u003eJanibacter\u003c/em\u003e, \u003cem\u003eLabrys\u003c/em\u003e, \u003cem\u003ePlanosporangium\u003c/em\u003e, \u003cem\u003ePlanotetraspora\u003c/em\u003e, and \u003cem\u003eSpirilliplanes\u003c/em\u003e showed significant positive correlations with the EMF index (Figure_8b).\u003c/p\u003e\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003e4.1 Response of beneficial microbial communities to different fertilization treatments\u003c/h2\u003e\u003cp\u003eAccording to existing literature, the beneficial properties of soil microorganisms to plants primarily include bioprophylaxis, bioprevention, and assisting plant resistance(Hunter, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Combining these findings with the conditions of this sample site, this study further refined the classification of the beneficial genera: plant bioprophylaxis focuses on nutrient absorption qualities such as nitrogen fixation, phosphorus solubilization, and potassium solubilization; pathogen antagonism includes systemic resistance caused by bacteria, fungi, or the activation of antiphlogistic bacteria; and stress tolerance traits prioritize beneficial genera that can withstand drought and have the potential to degrade plastics, given the semi-arid region of the sample site and the susceptibility of corn mulch to microplastic contamination. Thus, the beneficial genera were classified as follows: nutrient uptake promotion (NPK) (El-Egami et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Faller et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Pang et al., \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Sepp et al., \u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Wahab et al., 2024; Youssef et al., \u003cspan citationid=\"CR122\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), pathogen antagonism (PA) (Beneduzi et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Chang et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Kaur et al., \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Lee et al., \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Sermswan and Wongratanacheewin, \u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), drought resistance (DR)(Ali et al., \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Aslam et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; de Vries et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Xi et al., \u003cspan citationid=\"CR115\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), and plastic degradation (PD) (Chen et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Niu et al., \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Sun et al., \u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Previous research has found that microbial diversity and abundance in legume rotational and intercropping systems are much higher than in monocrops(Ablimit et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Latati et al., \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). However, findings from this research showed that the abundance of beneficial microbial communities and their share of the total community increased significantly with green manure treatment, but the diversity index was significantly lower than the control, and the difference in richness was not significant.This suggests that the number of specific genera decreased during long-term green manure rotation, despite an increase in the overall beneficial community, which aligns with the findings of Liu et al(Zhang et al., \u003cspan citationid=\"CR123\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).β diversity analysis results showed that green manure had a significant effect on beneficial microbial community structure. Long-term use of green manure may cause an accumulation of crop root secretions, such as root deposits(Dennis et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2010\u003c/span\u003e), which greatly influence the formation of soil microbial communities and strengthen the process of selecting beneficial microbial communities. This could be one explanation for the observed phenomenon.In addition, the composition of the dominant groups of beneficial microorganisms with different functions remained stable under different fertilization treatments. When the beneficial genera of different functional groups were compared, there were seven multifunctional genera, and green manure treatment significantly increased their relative abundance.The multifunctional genera \u003cem\u003eBacillus\u003c/em\u003e and \u003cem\u003ePseudomonas\u003c/em\u003e, which have four roles simultaneously, are the dominant genera in the beneficial community and have been extensively studied and proven to have favorable effects on soil health and crops(Fasusi et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The relative abundance of these genera in maize soil after long-term application and rotation of green manure was 1.23\u0026ndash;1.77 times higher than CK, indicating that these well-known plant-associated bacteria are more likely to accumulate in maize soil under green manure rotation. LefSe analyses showed that different green manures or different fertilization practices enriched different differential genera compared to the control, and that the green manure returning treatment (CPG/SPG) was more favorable for enrichment of beneficial genera than the root stubble treatment (CPR/SPR). Deterministic processes (interspecies interactions, environmental filtering, etc.) and stochastic processes (probability diffusion, birth -death events, and ecological drift, etc.) are frequently thought to explain microbial community assembly concurrently (Zhou and Ning, \u003cspan citationid=\"CR124\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), and the relative contributions of these two ecological processes differ between generalists and specialists. Generalists are less impacted by the environment, whereas specialists have more stringent growth circumstances, which may include unique metabolic requirements and species interactions (Xu et al., \u003cspan citationid=\"CR117\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). In this study, stochastic processes contributed more to the construction of the four functional communities than deterministic processes, and compared to PA and PD communities, the proportion of generalists in the NPK and DR communities was higher, with increases of 5.9% and 3.8%, respectively, after applying green manure (Figure_4c), indicating that generalists can be enriched. Due to the wide adaptability of generalists and their higher abundance, they allow for better random diffusion, which is consistent with the results of NST calculations. Fan et al(Fan et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) discovered that subcommunity combinations of microbial taxa with higher frequency of occurrence and larger ecological niches are less limited by diffusion restrictions and more influenced by drift. Microbial taxa with a greater niche width often have more metabolic flexibility, making them less susceptible to environmental selection and more governed by random processes(Li et al., \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Luo et al., \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The best fit of NPK and PA communities in the neutral model (NCM) (NPK: R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.9601, PA: R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.9604) corresponds to their rather wide niche widths (Figure_4d-e), which supports this. A recent study found that substantial diffusion constraints can result in a shortage of beneficial microorganisms in maize fields(Wu et al., 2022). Thus, inoculating beneficial microorganisms or microbial communities with higher diffusion rates appears to have the potential to promote ecosystem health(Xiong and Lu, \u003cspan citationid=\"CR116\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003e4.2 Beneficial microorganisms exert beneficial properties in microbial communities\u003c/h2\u003e\u003cp\u003eFarm management introduces physical, chemical, and biological elements that, when combined, have the potential to modify soil characteristics significantly and, hence, the environment for the survival of the soil microbiome(Fierer, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). The structure and diversity of the microbiome are inextricably tied to the multiplicity of coexisting microhabitats (Liu et al., \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). These microhabitats are likely the most critical influences on microbiome-mediated biogeochemical processes in soil (Lavelle et al., \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Green manure application modulates soil microhabitats, altering microbial populations (Szoboszlay and Tebbe, \u003cspan citationid=\"CR95\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Wilpiszeski et al., \u003cspan citationid=\"CR108\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). However, species diversity is not the best predictor of its value to the community (Banerjee et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), and the beneficial genera belonging to the core species in the overall community network are only \u003cem\u003eMicrovirga, Mesorhizobium, Bradyrhizobium\u003c/em\u003e, and \u003cem\u003eStreptomyces\u003c/em\u003e, which are abundant taxa (Table S5, Figure S3). Nevertheless, other beneficial genera also act as core species, determining the community's integrity and persistence independently of time (Cottee-Jones and Whittaker, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2012\u003c/span\u003e), and keystone species may have disproportionately significant impacts(Wu et al., \u003cspan citationid=\"CR109\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Similar to Fan et al (Fan et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), our study discovered that keystone species are more abundant when fertilized, especially \u003cem\u003eNocardia\u003c/em\u003e (39% -70%). Keystone species are crucial to community stability, and the addition of organic fertilizers can dramatically change the complexity of networks (Wang et al., \u003cspan citationid=\"CR104\" class=\"CitationRef\"\u003e2022a\u003c/span\u003e). The application of green manure increased microbial interactions and network complexity, as evidenced by changes in network topological features (Table S4). Furthermore, green manure significantly increased the number of core microorganisms in the network, which are composed of beneficial microorganisms (all connectors) and essential for network stability and connectivity of individual modules. At the same time, a sufficiently stable community will not alter significantly in composition or function due to ongoing environmental perturbations (Rogers and Tate, \u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). Xun et al (Xun et al., \u003cspan citationid=\"CR119\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) created a new strategy that investigates the stability of soil microbial communities by computing AVD values based on experimental design. This method is not restricted by sample size and has advantages over existing methods for evaluating community stability. In this study, the lower the AVD value, the lower the average variability in the sample after applying green manure, and the more stable the microbial community, with core beneficial bacteria acting as a significantly correlated driving force for community stability.\u003c/p\u003e\u003cp\u003eSoil microbes are key components of soil ecosystems that perform various tasks, including nutrient cycling and metabolism(Gao et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Metagenomics proved more practical and efficient in this study than previous genomic techniques for accurately predicting soil microbial functions using KEGG databases. KEGG analysis offered precise information regarding the role of core beneficial microbes in metabolic pathways in soil microbial communities. The results revealed that metabolism was the primary function of the soil microbial community in maize, accounting for more than 52% of all treatments, showing that microbial activities in the soil were primarily metabolism-based. Therefore, our study included a more thorough analysis of the secondary routes of metabolism. Various metabolic pathways can result in distinct physiological outcomes. The overall function of the maize soil microbial community under various fertilization treatments was found to be relatively conservative when maintaining a stable, functional metabolism in the face of external perturbations (Gao et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Furthermore, we discovered that fertilization treatments quickly affected the contribution of \u003cem\u003eAcinetobacter, Alcanivorax, Brevibacillus\u003c/em\u003e, and \u003cem\u003eMarinobacterium\u003c/em\u003e to the overall community function and that treatments with green manure were more favorable to these beneficial genera' participation in carbohydrate metabolism, amino acid metabolism, glycan biosynthesis and metabolism, energy metabolism, and metabolism of cofactors and vitamins to provide essential nutrients for crop growth better (DeAngelis et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). Meanwhile, the beneficial genera whose contribution to metabolic functions was susceptible to fertilization (\u003cem\u003eAcinetobacter, Alcanivora, Brevibacillus, Marinobacterium\u003c/em\u003e) also had higher overall contributions to the relevant functional genes. Among them, \u003cem\u003eAcinetobacter\u003c/em\u003e and \u003cem\u003eAlcanivorax\u003c/em\u003epromote soil carbon sequestration processes (Berg, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2011\u003c/span\u003e) by participating in the acetyl coenzyme A pathway (Beulig et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), TCA cycle (Delgado-Baquerizo et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), and other related pathways. \u003cem\u003eBrevibacillus\u003c/em\u003e favors the synthesis of amylase and amino acids in soil (Syldatk et al., \u003cspan citationid=\"CR94\" class=\"CitationRef\"\u003e1999\u003c/span\u003e), and \u003cem\u003eMarinobacterium\u003c/em\u003e contributes more to the synthesis of glutamate, facilitating the conversion of inorganic to organic nitrogen (Yang et al., \u003cspan citationid=\"CR121\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). It follows that beneficial genera have beneficial properties in terms of network and community stability and community metabolic functions in addition to their single beneficial function.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003e4.3 Beneficial characterization of beneficial microorganisms in ecosystems\u003c/h2\u003e\u003cp\u003eAnthropogenic activities and farm management practices can fundamentally alter soil properties and the composition of the soil microbiome (Geisseler and Scow, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Johnsen et al., \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). Soil microorganisms in agricultural soils perform many ecosystem services (ecosystem multifunctionality), which are critical for geochemical nutrient cycling, primary production, litter decomposition, and climate regulation (Bardgett and van der Putten, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Bender et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Chen et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Significant interactions exist between soil environment, soil microbes, and plant quality (Tao et al., 2016). Our work confirmed that communities of beneficial microorganisms that could promote NPK nutrient uptake and antagonize pathogens had relatively higher contributions to improving soil physicochemical properties and promoting soil health. The microbiome is intricately linked to soil structure (e.g., aggregation and pore connectivity), as this structure regulates the flow of water, oxygen, and nutrients through the syst\u0026eacute;m (Hartmann and Six, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). According to the Mantel test, there is a substantial positive correlation between the abundance of the beneficial microbial community and both soil water content and bulk weight, and the core beneficial microorganisms \u003cem\u003eAcinetobacter\u003c/em\u003e were significantly and positively correlated with soil water content. At the same time, \u003cem\u003eAcinetobacter\u003c/em\u003e and \u003cem\u003eBrevibacillus\u003c/em\u003e were significantly and negatively correlated with soil bulk weight. Microorganisms can secrete compounds that directly alter soil water dynamics, such as EPS, which increases water retention in soil (Granato et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), reduces hydraulic conductivity by plugging large pores (Shafi et al., \u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), slows evaporation from the soil (Bravo et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2011\u003c/span\u003e), does not readily desaturate due to smaller pore sizes, and maintains fluid continuity under drying conditions, allowing nutrients and metabolites to diffuse. Microorganisms can influence soil particle cohesiveness, pore organization, and soil structure, affecting soil water retention and infiltration rates (Tang et al., \u003cspan citationid=\"CR96\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eBeneficial microorganisms, particularly their core genera \u003cem\u003eStreptomyces\u003c/em\u003e and \u003cem\u003eAlcanivorax\u003c/em\u003e, showed a strong positive correlation with soil sand and silt content, respectively, while \u003cem\u003eNocardia\u003c/em\u003e demonstrated a negative correlation with clay fractions. This indicates that core beneficial microorganisms were able to promote the structural transformation of soil texture to a structure dominated by larger soil particles, which contain more carbon, nitrogen, and organic matter, promoting aggregate formation and maintaining soil structural stability, thereby favoring soil health(Puget et al., \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e1995\u003c/span\u003e). Microorganisms degrade organic matter to release plant-available inorganic nutrients, modify nutrient availability by oxidative, reductive, solubilizing, and chelating activities, and store and release nutrients in necrotic matter (Marschner and Rengel, \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). These activities drive global nutrient cycling (Falkowski et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2008\u003c/span\u003e) and regulate approximately 90% of soil energy fluxes(Lukac et al., \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). In this study, for example, \u003cem\u003eBrevibacillus\u003c/em\u003e was shown to improve the uptake and utilization of soil carbon and phosphorus, \u003cem\u003eAcinetobacter\u003c/em\u003e was found to aid in the increase of soil available nitrogen content, and \u003cem\u003eAlcanivorax\u003c/em\u003e had a positive effect on the accumulation of total soil nitrogen.\u003c/p\u003e\u003cp\u003eFurthermore, Li et al(Li et al., \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2023a\u003c/span\u003e) suggested that there was always a positive correlation between the relative abundance of potentially beneficial microorganisms and maize yield, and this study confirmed the significant correlation between the abundance of beneficial microbial communities and maize yield (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01). Crop yields are high when the soil is healthy, owing to simple root colonization, adequate water entering and storing, appropriate nutrient delivery, fewer hazardous soil pollutants, and highly active beneficial microorganisms that suppress potential pests and drive plant growth. Most studies have investigated whether more species are required to improve ecosystem multifunctionality and quantified biodiversity's impact on communities. However, in these assessments, the identity of species has been mainly neglected(Cadotte et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Wagg et al., \u003cspan citationid=\"CR101\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Depending on the metrics used and the systems investigated, various species have distinct and comparable functions (redundancy)(Mori et al., \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). As a result, it is vital to assess each species' relevance while maintaining their individuality in various functional contexts (Hautier et al., 2018).\u003c/p\u003e\u003cp\u003eThis work reveals that core beneficial genera play a crucial role in improving ecosystem multifunctionality, in line with Wang et al. (Wang et al., \u003cspan citationid=\"CR106\" class=\"CitationRef\"\u003e2022b\u003c/span\u003e), who found that changes in the abundance of functional microbes had a considerable impact on EMF. Our finding could be attributed to the substantial redundancy of microbial communities used for general functions in soil (Li et al., \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2021b\u003c/span\u003e). More abundant microbes result in more interactions between them, which drives EMF and improves ecological stability (Chen et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). We identified 11 core genera by the network that were not previously reported to have direct beneficial effects on plants. As Qiao et al(Qiao et al., \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) stated the core taxa enhanced potential microbial cooperation and network complexity, which ultimately enhanced plant health and biomass. This study also found that these core genera are crucial in network support and soil property improvement, favoring EMF and thus benefiting plant health and yield. We, therefore, suggest that such microorganisms should be categorized as beneficial microorganisms in a completely new sense. Thus, we believe that such microorganisms should also be classified as beneficial microorganisms, expanding the scope of the definition of beneficial microorganisms.\u003c/p\u003e\u003c/div\u003e"},{"header":"5. Conclusions","content":"\u003cp\u003eIn this study, the clustering of beneficial microorganisms according to their reported single functions revealed that green manure returning treatment was more conducive to enriching beneficial microbial communities than relic stubble. The mix of diverse functionally advantageous dominant taxa remained consistent across fertilization treatments, and stochastic processes mainly influenced their aggregation. Beneficial genera and their inherent single beneficial function serve as keystone species that contribute to the complexity and stability of the overall co-occurrence network by enhancing inter-module connectivity. The core beneficial genera \u003cem\u003eBrevibacillus, Marinobacterium, Alcanivorax, Acinetobacter, Bacillus, Ensifer, Nocardia\u003c/em\u003e, and \u003cem\u003eStreptomyces\u003c/em\u003e favor reducing community average variability (AVD) to improve community stability. The overall functions of microbial communities under different fertilization treatments were relatively conservative, and the green manure treatment was more conducive to increasing the relative contribution of core beneficial genera to essential metabolic pathways such as carbohydrate metabolism, amino acid metabolism, and energy metabolism, and enhancing the contribution of core beneficial genera to functional gene abundance in the processes of element cycling and amino acid synthesis to provide essential nutrients for crop growth better. The relative contribution of core beneficial genera to the abundance of functional genes in the processes of element cycling and amino acid synthesis was enhanced, better providing essential nutrients for crop growth. Additionally, core beneficial genera are significantly associated with soil nutrient transformation, soil enzyme activity, soil structure, and texture, which are beneficial in maintaining soil structural stability and promoting soil health. Core beneficial genera have the potential to enhance ecosystem stability as drivers of ecosystem multifunctionality. This study also identified 11 network core genera whose beneficial properties have not been reported, and due to their positive effects on microbial communities and soil properties, we suggest that such microorganisms extend previous definitions of beneficial microorganisms, making them more accurate and comprehensive.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003ch2\u003eDeclaration of competing interest\u003c/h2\u003e\u003cp\u003eThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eG.Z. and J.Z. wrote the original draft. G.Z. also contributed to methodology, visualization, and data curation. Y.Z. conducted the investigation, developed methodology, performed software-related tasks, and carried out formal analysis. X.L. contributed to methodology and project administration. X.W. participated in investigation and data curation. J.D. provided supervision and writing-review \u0026amp; editing. P.L. was involved in project administration. J.Y. contributed to writing-review \u0026amp; editing. J.Z. provided resources, conceptualization, supervision, and writing-original draft. Y.C. contributed to writing-review \u0026amp; editing, resources, project administration, funding acquisition, and conceptualization. All authors reviewed the manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgements\u003c/h2\u003e\u003cp\u003eThis project was supported by the National Key Research and Development Program of China (2022YFF1303301 and 2022YFF1302603), the Key Research and Development Project of Gansu Provincial Science and Technology Program (25YFWA004), National Nature Science Foundation of China (52179026), Gansu Provincial Science and Technology Department of China (22ZD6NA049), Strategic Research and Consulting Project of the Chinese Academy of Engineering (2023-XZ-80) and The Major Key Projects of Natural Science of the Gansu Province (No. 23ZDFA018).\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe metagenomic raw read data have been deposited in the NCBI sequence read file database (entry number: PRJNA1086341).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAblimit, R., Li, W., Zhang, J., Gao, H., Zhao, Y., Cheng, M., Meng, X., An, L. and Chen, Y., 2022. Altering microbial community for improving soil properties and agricultural sustainability during a 10-year maize-green manure intercropping in Northwest China. Journal of Environmental Management. 321.http://dx.doi.org/10.1016/j.jenv\u003cu\u003eman.2022.115859\u003c/u\u003e \u003c/li\u003e\n\u003cli\u003eAli, S., Tyagi, A., Park, S., Mir, R.A., Mushtaq, M., Bhat, B., Mahmoudi, H. and Bae, H., 2022. Deciphering the plant microbiome to improve drought tolerance: Mechanisms and perspectives. Environmental and Experimental Botany. 201.http://dx.doi.org/10.1016/j.envex\u003cu\u003epbot.2022.104933\u003c/u\u003e \u003c/li\u003e\n\u003cli\u003eAltieri, M.A., Funes-Monzote, F.R. and Petersen, P., 2012. Agroecologically efficient agricultural systems for smallholder farmers: contributions to food sovereignty. Agronomy for Sustainable Development. 32, 1-13.http://dx.doi.org/10.1007/s13\u003cu\u003e593-011-0065-6\u003c/u\u003e \u003c/li\u003e\n\u003cli\u003eAslam, M.M., Okal, E.J., Idris, A.L., Qian, Z., Xu, W., Karanja, J.K., Wani, S.H. and Yuan, W., 2022. Rhizosphere microbiomes can regulate plant drought tolerance. Pedosphere. 32, 61-74.http://dx.doi.org/10.1016/s1002\u003cu\u003e-0160(21)60061-9\u003c/u\u003e \u003c/li\u003e\n\u003cli\u003eBanerjee, S., Kirkby, C.A., Schmutter, D., Bissett, A., Kirkegaard, J.A. and Richardson, A.E., 2016. Network analysis reveals functional redundancy and keystone taxa amongst bacterial and fungal communities during organic matter decomposition in an arable soil. Soil Biology and Biochemistry. 97, 188-198.http://dx.doi.org/https://doi.org/10.1016\u003cu\u003e/j.soilbio.2016.03.017\u003c/u\u003e \u003c/li\u003e\n\u003cli\u003eBanerjee, S., Schlaeppi, K. and van der Heijden, M.G.A., 2018. Keystone taxa as drivers of microbiome structure and functioning. Nature Reviews Microbiology. 16, 567-576.http://dx.doi.org/10.1038/s41\u003cu\u003e579-018-0024-1\u003c/u\u003e \u003c/li\u003e\n\u003cli\u003eBanerjee, S., Walder, F., B\u0026uuml;chi, L., Meyer, M., Held, A.Y., Gattinger, A., Keller, T., Charles, R. and van der Heijden, M.G.A., 2019. Agricultural intensification reduces microbial network complexity and the abundance of keystone taxa in roots. The ISME Journal. 13, 1722-1736.http://dx.doi.org/10.1038/s41\u003cu\u003e396-019-0383-2\u003c/u\u003e \u003c/li\u003e\n\u003cli\u003eBardgett, R.D. and van der Putten, W.H., 2014. Belowground biodiversity and ecosystem functioning. Nature. 515, 505-511.http://dx.doi.org/10.1038\u003cu\u003e/nature13855\u003c/u\u003e \u003c/li\u003e\n\u003cli\u003eBender, S.F., Wagg, C. and van der Heijden, M.G.A., 2016. An Underground Revolution: Biodiversity and Soil Ecological Engineering for Agricultural Sustainability. Trends in Ecology \u0026amp; Evolution. 31, 440-452.http://dx.doi.org/https://doi.org/10.10\u003cu\u003e16/j.tree.2016.02.016\u003c/u\u003e \u003c/li\u003e\n\u003cli\u003eBeneduzi, A., Ambrosini, A. and Passaglia, L., 2012. Plant growth-promoting rhizobacteria (PGPR): Their potential as antagonists and biocontrol agents. Genetics and molecular biology. 35, 1044-51.http://dx.doi.org/10.1590/S1415-47\u003cu\u003e572012000600020\u003c/u\u003e \u003c/li\u003e\n\u003cli\u003eBerg, I.A., 2011. Ecological Aspects of the Distribution of Different Autotrophic CO 2 Fixation Pathways. Applied and Environmental Microbiology. 77, 1925-1936.http://dx.doi.org/10.1128/\u003cu\u003eaem.02473-10\u003c/u\u003e \u003c/li\u003e\n\u003cli\u003eBeulig, F., Urich, T., Nowak, M., Trumbore, S.E., Gleixner, G., Gilfillan, G.D., Fjelland, K.E. and K\u0026uuml;sel, K., 2016. Altered carbon turnover processes and microbiomes in soils under long-term extremely high CO2 exposure. Nature Microbiology. 1, 15025.http://dx.doi.org/10.1038/nm\u003cu\u003eicrobiol.2015.25\u003c/u\u003e \u003c/li\u003e\n\u003cli\u003eBravo, A., Likitvivatanavong, S., Gill, S.S. and Sober\u0026oacute;n, M., 2011. Bacillus thuringiensis: A story of a successful bioinsecticide. Insect Biochemistry and Molecular Biology. 41, 423-431.http://dx.doi.org/https://doi.org/10.101\u003cu\u003e6/j.ibmb.2011.02.006\u003c/u\u003e \u003c/li\u003e\n\u003cli\u003eCadotte, M.W., Livingstone, S.W., Yasui, S.L.E., Dinnage, R. and Shu, W.J.E., 2017. Explaining ecosystem multifunction with evolutionary models. 98, 3175-3187 \u003c/li\u003e\n\u003cli\u003eChang, X., Wei, D., Zeng, Y., Zhao, X., Hu, Y., Wu, X., Song, C., Gong, G., Chen, H., Yang, C., Zhang, M., Liu, T., Chen, W. and Yang, W., 2022. Maize-soybean relay strip intercropping reshapes the rhizosphere bacterial community and recruits beneficial bacteria to suppress Fusarium root rot of soybean. Frontiers in Microbiology. 13.http://dx.doi.org/10.3389/fmic\u003cu\u003eb.2022.1009689\u003c/u\u003e \u003c/li\u003e\n\u003cli\u003eChen, B., Zhang, Z., Wang, T., Hu, H., Qin, G., Lu, T., Hong, W., Hu, J., Penuelas, J. and Qian, H., 2023. Global distribution of marine microplastics and potential for biodegradation. Journal of Hazardous Materials. 451.http://dx.doi.org/10.1016/j.jhaz\u003cu\u003emat.2023.131198\u003c/u\u003e \u003c/li\u003e\n\u003cli\u003eChen, Q.-L., Ding, J., Zhu, D., Hu, H.-W., Delgado-Baquerizo, M., Ma, Y.-B., He, J.-Z. and Zhu, Y.-G., 2020. Rare microbial taxa as the major drivers of ecosystem multifunctionality in long-term fertilized soils. Soil Biology and Biochemistry. 141.http://dx.doi.org/10.1016/j.soil\u003cu\u003ebio.2019.107686\u003c/u\u003e \u003c/li\u003e\n\u003cli\u003eChen, W., Wang, J., Chen, X., Meng, Z., Xu, R., Duoji, D., Zhang, J., He, J., Wang, Z., Chen, J., Liu, K., Hu, T. and Zhang, Y., 2022. Soil microbial network complexity predicts ecosystem function along elevation gradients on the Tibetan Plateau. Soil Biology and Biochemistry. 172, 108766.http://dx.doi.org/https://doi.org/10.1016\u003cu\u003e/j.soilbio.2022.108766\u003c/u\u003e \u003c/li\u003e\n\u003cli\u003eCottee-Jones, H.E.W. and Whittaker, R.J., 2012. perspective: The keystone species concept: a critical appraisal. Frontiers of Biogeography. 4.http://dx.doi.org/10.2142\u003cu\u003e5/f5fbg12533\u003c/u\u003e \u003c/li\u003e\n\u003cli\u003ede Vries, F.T., Griffiths, R.I., Knight, C.G., Nicolitch, O. and Williams, A., 2020. Harnessing rhizosphere microbiomes for drought-resilient crop production. Science. 368, 270-274.http://dx.doi.org/10.1126/s\u003cu\u003ecience.aaz5192\u003c/u\u003e \u003c/li\u003e\n\u003cli\u003eDeAngelis, K.M., Lindow, S.E. and Firestone, M.K., 2008. Bacterial quorum sensing and nitrogen cycling in rhizosphere soil. FEMS Microbiology Ecology. 66, 197-207.http://dx.doi.org/10.1111/j.1574-\u003cu\u003e6941.2008.00550.x\u003c/u\u003e %J FEMS Microbiology Ecology \u003c/li\u003e\n\u003cli\u003eDelgado-Baquerizo, M., Maestre, F.T., Gallardo, A., Bowker, M.A., Wallenstein, M.D., Quero, J.L., Ochoa, V., Gozalo, B., Garc\u0026iacute;a-G\u0026oacute;mez, M., Soliveres, S., Garc\u0026iacute;a-Palacios, P., Berdugo, M., Valencia, E., Escolar, C., Arredondo, T., Barraza-Zepeda, C., Bran, D., Carreira, J.A., Chaieb, M., Concei\u0026ccedil;\u0026atilde;o, A.A., Derak, M., Eldridge, D.J., Escudero, A., Espinosa, C.I., Gait\u0026aacute;n, J., Gatica, M.G., G\u0026oacute;mez-Gonz\u0026aacute;lez, S., Guzman, E., Guti\u0026eacute;rrez, J.R., Florentino, A., Hepper, E., Hern\u0026aacute;ndez, R.M., Huber-Sannwald, E., Jankju, M., Liu, J., Mau, R.L., Miriti, M., Monerris, J., Naseri, K., Noumi, Z., Polo, V., Prina, A., Pucheta, E., Ram\u0026iacute;rez, E., Ram\u0026iacute;rez-Collantes, D.A., Rom\u0026atilde;o, R., Tighe, M., Torres, D., Torres-D\u0026iacute;az, C., Ungar, E.D., Val, J., Wamiti, W., Wang, D. and Zaady, E., 2013. Decoupling of soil nutrient cycles as a function of aridity in global drylands. Nature. 502, 672-676.http://dx.doi.org/10.1038\u003cu\u003e/nature12670\u003c/u\u003e \u003c/li\u003e\n\u003cli\u003eDelgado-Baquerizo, M., Maestre, F.T., Reich, P.B., Jeffries, T.C., Gaitan, J.J., Encinar, D., Berdugo, M., Campbell, C.D. and Singh, B.K., 2016. Microbial diversity drives multifunctionality in terrestrial ecosystems. Nature Communications. 7, 10541.http://dx.doi.org/10.1038/\u003cu\u003encomms10541\u003c/u\u003e \u003c/li\u003e\n\u003cli\u003eDennis, P.G., Miller, A.J. and Hirsch, P.R., 2010. Are root exudates more important than other sources of rhizodeposits in structuring rhizosphere bacterial communities? FEMS Microbiology Ecology. 72, 313-327.http://dx.doi.org/10.1111/j.1574-6\u003cu\u003e941.2010.00860.x\u003c/u\u003e %J FEMS Microbiology Ecology \u003c/li\u003e\n\u003cli\u003eEl-Egami, H.M., Hegab, R.H., Montaser, H., El-Hawary, M.M. and Hasanuzzaman, M., 2024. Impact of Potassium-Solubilizing Microorganisms with Potassium Sources on the Growth, Physiology, and Productivity of Wheat Crop under Salt-Affected Soil Conditions. Agronomy. 14.http://dx.doi.org/10.3390/agr\u003cu\u003eonomy14030423\u003c/u\u003e \u003c/li\u003e\n\u003cli\u003eEspersch\u0026uuml;tz, J., Gattinger, A., M\u0026auml;der, P., Schloter, M. and Fliessbach, A., 2007. Response of soil microbial biomass and community structures to conventional and organic farming systems under identical crop rotations. FEMS Microbiol Ecol. 61, 26-37.http://dx.doi.org/10.1111/j.1574-6\u003cu\u003e941.2007.00318.x\u003c/u\u003e \u003c/li\u003e\n\u003cli\u003eFalkowski, P.G., Fenchel, T. and Delong, E.F., 2008. The Microbial Engines That Drive Earth\u0026apos;s Biogeochemical Cycles. 320, 1034-1039.http://dx.doi.org/doi:10.1126/\u003cu\u003escience.1153213\u003c/u\u003e \u003c/li\u003e\n\u003cli\u003eFaller, L., Leite, M.F.A. and Kuramae, E.E., 2024. Enhancing phosphate-solubilising microbial communities through artificial selection. Nat Commun. 15, 1649.http://dx.doi.org/10.1038/s414\u003cu\u003e67-024-46060-x\u003c/u\u003e \u003c/li\u003e\n\u003cli\u003eFan, K., Delgado-Baquerizo, M., Guo, X., Wang, D., Wu, Y., Zhu, M., Yu, W., Yao, H., Zhu, Y.-g. and Chu, H., 2019. Suppressed N fixation and diazotrophs after four decades of fertilization. Microbiome. 7, 143.http://dx.doi.org/10.1186/s40\u003cu\u003e168-019-0757-8\u003c/u\u003e \u003c/li\u003e\n\u003cli\u003eFan, Q., Liu, K., Wang, Z., Liu, D., Li, T., Hou, H., Zhang, Z., Chen, D., Zhang, S., Yu, A., Deng, Y., Cui, X. and Che, R., 2024. Soil microbial subcommunity assembly mechanisms are highly variable and intimately linked to their ecological and functional traits. Molecular Ecology.http://dx.doi.org/10.111\u003cu\u003e1/mec.17302\u003c/u\u003e \u003c/li\u003e\n\u003cli\u003eFasusi, O.A., Cruz, C. and Babalola, O.O., 2021. Agricultural Sustainability: Microbial Biofertilizers in Rhizosphere Management. Agriculture. 11.http://dx.doi.org/10.3390/agri\u003cu\u003eculture11020163\u003c/u\u003e \u003c/li\u003e\n\u003cli\u003eFierer, N., 2017. Embracing the unknown: disentangling the complexities of the soil microbiome. Nature Reviews Microbiology. 15, 579-590.http://dx.doi.org/10.1038/n\u003cu\u003ermicro.2017.87\u003c/u\u003e \u003c/li\u003e\n\u003cli\u003eGao, Y., Du, J., Bahar, M.M., Wang, H., Subashchandrabose, S., Duan, L., Yang, X., Megharaj, M., Zhao, Q., Zhang, W., Liu, Y., Wang, J. and Naidu, R., 2021. Metagenomics analysis identifies nitrogen metabolic pathway in bioremediation of diesel contaminated soil. Chemosphere. 271, 129566.http://dx.doi.org/https://doi.org/10.1016/j.ch\u003cu\u003eemosphere.2021.129566\u003c/u\u003e \u003c/li\u003e\n\u003cli\u003eGeisseler, D. and Scow, K.M., 2014. Long-term effects of mineral fertilizers on soil microorganisms A review. Soil Biology and Biochemistry. 75, 54-63.http://dx.doi.org/https://doi.org/10.1016\u003cu\u003e/j.soilbio.2014.03.023\u003c/u\u003e \u003c/li\u003e\n\u003cli\u003eGolla, B., 2021. Agricultural production system in arid and semi-arid regions. International Journal of Agricultural Science and Food Technology. 234-244.http://dx.doi.org/10.17352/24\u003cu\u003e55-815X.000113\u003c/u\u003e \u003c/li\u003e\n\u003cli\u003eGranato, E.T., Meiller-Legrand, T.A. and Foster, K.R., 2019. The Evolution and Ecology of Bacterial Warfare. Current Biology. 29, R521-R537.http://dx.doi.org/https://doi.org/10.10\u003cu\u003e16/j.cub.2019.04.024\u003c/u\u003e \u003c/li\u003e\n\u003cli\u003eGriffiths, B.S. and Philippot, L., 2013. Insights into the resistance and resilience of the soil microbial community. FEMS Microbiology Reviews. 37, 112-129.http://dx.doi.org/10.1111/j.1574-6\u003cu\u003e976.2012.00343.x\u003c/u\u003e \u003c/li\u003e\n\u003cli\u003eHan, Z., Xu, P., Li, Z., Lin, H., Zhu, C., Wang, J. and Zou, J., 2022. Microbial diversity and the abundance of keystone species drive the response of soil multifunctionality to organic substitution and biochar amendment in a tea plantation. GCB Bioenergy. 14, 481-495.http://dx.doi.org/10.1111\u003cu\u003e/gcbb.12926\u003c/u\u003e \u003c/li\u003e\n\u003cli\u003eHartmann, M. and Six, J., 2022. Soil structure and microbiome functions in agroecosystems. Nature Reviews Earth \u0026amp; Environment. 4, 4-18.http://dx.doi.org/10.1038/s430\u003cu\u003e17-022-00366-w\u003c/u\u003e \u003c/li\u003e\n\u003cli\u003eHautier, Y., Isbell, F., Borer, E.T., Seabloom, E.W., Harpole, W.S., Lind, E.M., MacDougall, A.S., Stevens, C.J., Adler, P.B., Alberti, J., Bakker, J.D., Brudvig, L.A., Buckley, Y.M., Cadotte, M., Caldeira, M.C., Chaneton, E.J., Chu, C., Daleo, P., Dickman, C.R., Dwyer, J.M., Eskelinen, A., Fay, P.A., Firn, J., Hagenah, N., Hillebrand, H., Iribarne, O., Kirkman, K.P., Knops, J.M.H., La Pierre, K.J., McCulley, R.L., Morgan, J.W., P\u0026auml;rtel, M., Pascual, J., Price, J.N., Prober, S.M., Risch, A.C., Sankaran, M., Schuetz, M., Standish, R.J., Virtanen, R., Wardle, G.M., Yahdjian, L. and Hector, A., 2018. Local loss and spatial homogenization of plant diversity reduce ecosystem multifunctionality. Nature Ecology \u0026amp; Evolution. 2, 50-56.http://dx.doi.org/10.1038/s41\u003cu\u003e559-017-0395-0\u003c/u\u003e \u003c/li\u003e\n\u003cli\u003eHuang, X., Rehman, H.M., Szollosi, A.G. and Zhou, S., 2022. Network Pharmacology-Based Approach Combined with Bioinformatic Analytics to Elucidate the Potential of Curcumol against Hepatocellular Carcinoma. Genes (Basel). 13.http://dx.doi.org/10.3390/g\u003cu\u003eenes13040653\u003c/u\u003e \u003c/li\u003e\n\u003cli\u003eHunter, P., 2016. Plant microbiomes and sustainable agriculture. EMBO reports. 17, 1696-1699.http://dx.doi.org/10.15252/e\u003cu\u003embr.201643476\u003c/u\u003e \u003c/li\u003e\n\u003cli\u003eJangid, K., Williams, M.A., Franzluebbers, A.J., Sanderlin, J.S., Reeves, J.H., Jenkins, M.B., Endale, D.M., Coleman, D.C. and Whitman, W.B., 2008. Relative impacts of land-use, management intensity and fertilization upon soil microbial community structure in agricultural systems. Soil Biology and Biochemistry. 40, 2843-2853.http://dx.doi.org/https://doi.org/10.1016\u003cu\u003e/j.soilbio.2008.07.030\u003c/u\u003e \u003c/li\u003e\n\u003cli\u003eJohnsen, K., Jacobsen, C.S., Torsvik, V. and S\u0026oslash;rensen, J., 2001. Pesticide effects on bacterial diversity in agricultural soils \u0026ndash; a review. Biology and Fertility of Soils. 33, 443-453.http://dx.doi.org/10.1007/s\u003cu\u003e003740100351\u003c/u\u003e \u003c/li\u003e\n\u003cli\u003eKaur, T., Khanna, K., Sharma, S. and Manhas, R.K., 2023. Mechanistic insights into the role of actinobacteria as potential biocontrol candidates against fungal phytopathogens. Journal of Basic Microbiology. 63, 1196-1218.http://dx.doi.org/10.1002/jo\u003cu\u003ebm.202300027\u003c/u\u003e \u003c/li\u003e\n\u003cli\u003eLatati, M., Blavet, D., Alkama, N., Laoufi, H., Drevon, J.J., G\u0026eacute;rard, F., Pansu, M. and Ounane, S.M., 2014. The intercropping cowpea-maize improves soil phosphorus availability and maize yields in an alkaline soil. Plant and Soil. 385, 181-191.http://dx.doi.org/10.1007/s11\u003cu\u003e104-014-2214-6\u003c/u\u003e \u003c/li\u003e\n\u003cli\u003eLavelle, P., Spain, A., Blouin, M., Brown, G., Deca\u0026euml;ns, T., Grimaldi, M., Jim\u0026eacute;nez, J.J., McKey, D., Mathieu, J., Velasquez, E. and Zangerl\u0026eacute;, A., 2016. Ecosystem Engineers in a Self-organized Soil: A Review of Concepts and Future Research Questions. Soil Science. 181, \u003c/li\u003e\n\u003cli\u003eLee, S.H., Jeon, S.H., Park, J.Y., Kim, D.S., Kim, J.A., Jeong, H.Y. and Kang, J.W., 2023. Isolation and Evaluation of the Antagonistic Activity of Cnidium officinale Rhizosphere Bacteria against Phytopathogenic fungi (Fusarium solani). Microorganisms. 11.http://dx.doi.org/10.3390/microo\u003cu\u003erganisms11061555\u003c/u\u003e \u003c/li\u003e\n\u003cli\u003eLi, C., Bo, H., Song, B., Chen, X., Cao, Q., Yang, R., Ji, S., Wang, L. and Liu, J., 2022. Reshaping of the soil microbiome by the expansion of invasive plants: shifts in structure, diversity, co-occurrence, niche breadth, and assembly processes. Plant and Soil. 477, 629-646.http://dx.doi.org/10.1007/s111\u003cu\u003e04-022-05445-x\u003c/u\u003e \u003c/li\u003e\n\u003cli\u003eLi, F., Zhang, K., Ren, J., Yin, C., Zhang, Y. and Nie, J., 2021a. Driving mechanism for farmers to adopt improved agricultural systems in China: The case of rice-green manure crops rotation system. Agricultural Systems. 192, 103202.http://dx.doi.org/https://doi.org/10.101\u003cu\u003e6/j.agsy.2021.103202\u003c/u\u003e \u003c/li\u003e\n\u003cli\u003eLi, J., Huang, L., Zhang, J., Coulter, J.A., Li, L. and Gan, Y., 2019. Diversifying crop rotation improves system robustness. Agronomy for Sustainable Development. 39, 38.http://dx.doi.org/10.1007/s13\u003cu\u003e593-019-0584-0\u003c/u\u003e \u003c/li\u003e\n\u003cli\u003eLi, M., Guo, J., Ren, T., Luo, G., Shen, Q., Lu, J., Guo, S. and Ling, N., 2021b. Crop rotation history constrains soil biodiversity and multifunctionality relationships. Agriculture, Ecosystems \u0026amp; Environment. 319, 107550.http://dx.doi.org/https://doi.org/10.101\u003cu\u003e6/j.agee.2021.107550\u003c/u\u003e \u003c/li\u003e\n\u003cli\u003eLi, P., Tedersoo, L., Crowther, T.W., Dumbrell, A.J., Dini-Andreote, F., Bahram, M., Kuang, L., Li, T., Wu, M., Jiang, Y., Luan, L., Saleem, M., de Vries, F.T., Li, Z., Wang, B. and Jiang, J., 2023a. Fossil-fuel-dependent scenarios could lead to a significant decline of global plant-beneficial bacteria abundance in soils by 2100. Nature Food.http://dx.doi.org/10.1038/s430\u003cu\u003e16-023-00869-9\u003c/u\u003e \u003c/li\u003e\n\u003cli\u003eLi, Q.-m., Zhang, D., Zhang, J.-z., Zhou, Z.-j., Pan, Y., Yang, Z.-h., Zhu, J.-h., Liu, Y.-h. and Zhang, L.-f., 2023b. Crop rotations increased soil ecosystem multifunctionality by improving keystone taxa and soil properties in potatoes. Frontiers in Microbiology. 14.http://dx.doi.org/10.3389/fmic\u003cu\u003eb.2023.1034761\u003c/u\u003e \u003c/li\u003e\n\u003cli\u003eLiaw, A. and Wiener, M., 2001. Classification and Regression by RandomForest. Forest. 23, Liu, B., Arlotti, D., Huyghebaert, B. and Tebbe, C.C., 2022. Disentangling the impact of contrasting agricultural management practices on soil microbial communities \u0026ndash; Importance of rare bacterial community members. Soil Biology and Biochemistry. 166.http://dx.doi.org/10.1016/j.soil\u003cu\u003ebio.2022.108573\u003c/u\u003e \u003c/li\u003e\n\u003cli\u003eLukac, M., Grenni, P. and Gamboni, M., 2017. Soil biological communities and ecosystem resilience. Luo, G., Rensing, C., Chen, H., Liu, M., Wang, M., Guo, S., Ling, N., Shen, Q. and Briones, M., 2018. Deciphering the associations between soil microbial diversity and ecosystem multifunctionality driven by long‐term fertilization management. Functional Ecology. 32, 1103-1116.http://dx.doi.org/10.1111/13\u003cu\u003e65-2435.13039\u003c/u\u003e \u003c/li\u003e\n\u003cli\u003eLuo, Z., Liu, J., Zhao, P., Jia, T., Li, C. and Chai, B., 2019. Biogeographic Patterns and Assembly Mechanisms of Bacterial Communities Differ Between Habitat Generalists and Specialists Across Elevational Gradients. 10.http://dx.doi.org/10.3389/fm\u003cu\u003eicb.2019.00169\u003c/u\u003e Marschner, P. and Rengel, Z., 2007. Nutrient Cycling in Terrestrial Ecosystems. \u003c/li\u003e\n\u003cli\u003eMori, A.S., Isbell, F. and Cadotte, M.W., 2023. Assessing the importance of species and their assemblages for the biodiversity‐ecosystem multifunctionality relationship. Ecology. 104.http://dx.doi.org/10.10\u003cu\u003e02/ecy.4104\u003c/u\u003e \u003c/li\u003e\n\u003cli\u003eMurphy, G.E.P. and Romanuk, T.N., 2013. A meta‐analysis of declines in local species richness from human disturbances. Ecology and Evolution. 4, 91-103.http://dx.doi.org/10.10\u003cu\u003e02/ece3.909\u003c/u\u003e \u003c/li\u003e\n\u003cli\u003eNannipieri, P., Ascher, J., Ceccherini, M.T., Landi, L., Pietramellara, G. and Renella, G., 2017. Microbial diversity and soil functions. European Journal of Soil Science. 68, 12-26.http://dx.doi.org/10.1111\u003cu\u003e/ejss.4_12398\u003c/u\u003e \u003c/li\u003e\n\u003cli\u003eNing, D., Deng, Y., Tiedje, J.M. and Zhou, J., 2019. A general framework for quantitatively assessing ecological stochasticity. 116, 16892-16898.http://dx.doi.org/doi:10.1073/p\u003cu\u003enas.1904623116\u003c/u\u003e \u003c/li\u003e\n\u003cli\u003eNiu, L., Chen, Y., Li, Y., Wang, Y., Shen, J., Wang, L., Zhang, W., Zhang, H. and Zhao, B., 2023. Diversity, abundance and distribution characteristics of potential polyethylene and polypropylene microplastic degradation bacterial communities in the urban river. Water Research. 232.http://dx.doi.org/10.1016/j.wa\u003cu\u003etres.2023.119704\u003c/u\u003e \u003c/li\u003e\n\u003cli\u003ePang, F., Li, Q., Solanki, M.K., Wang, Z., Xing, Y.-X. and Dong, D.-F., 2024. Soil phosphorus transformation and plant uptake driven by phosphate-solubilizing microorganisms. Frontiers in Microbiology. 15.http://dx.doi.org/10.3389/fmic\u003cu\u003eb.2024.1383813\u003c/u\u003e \u003c/li\u003e\n\u003cli\u003ePuget, P., Chenu, C. and Balesdent, J., 1995. Total and young organic carbon distributions in aggregates of silty cultivated soils. \u003c/li\u003e\n\u003cli\u003eQiao, Y., Wang, T., Huang, Q., Guo, H., Zhang, H., Xu, Q., Shen, Q. and Ling, N., 2024. Core species impact plant health by enhancing soil microbial cooperation and network complexity during community coalescence. Soil Biology and Biochemistry. 188.http://dx.doi.org/10.1016/j.soil\u003cu\u003ebio.2023.109231\u003c/u\u003e \u003c/li\u003e\n\u003cli\u003eRibero, M.N. and Filloy, J., 2023. Geographical trends of soil‐associated biodiversity changes due to tree plantations in South America: Biome and climate constraints revealed through meta‐analysis. Global Ecology and Biogeography.http://dx.doi.org/10.111\u003cu\u003e1/geb.13739\u003c/u\u003e \u003c/li\u003e\n\u003cli\u003eRogers, B.F. and Tate, R.L., 2001. Temporal analysis of the soil microbial community along a toposequence in Pineland soils. Soil Biology and Biochemistry. 33, 1389-1401.http://dx.doi.org/https://doi.org/10.1016/S\u003cu\u003e0038-0717(01)00044-X\u003c/u\u003e \u003c/li\u003e\n\u003cli\u003eSepp, S.-K., Vasar, M., Davison, J., Oja, J., Anslan, S., Al-Quraishy, S., Bahram, M., Bueno, C.G., Cantero, J.J., Fabiano, E.C., Decocq, G., Drenkhan, R., Fraser, L., Garibay Oriel, R., Hiiesalu, I., Koorem, K., K\u0026otilde;ljalg, U., Moora, M., Mucina, L., \u0026Ouml;pik, M., P\u0026otilde;lme, S., P\u0026auml;rtel, M., Phosri, C., Semchenko, M., Vahter, T., Vasco Palacios, A.M., Tedersoo, L. and Zobel, M., 2023. Global diversity and distribution of nitrogen-fixing bacteria in the soil. Frontiers in Plant Science. 14.http://dx.doi.org/10.3389/fpl\u003cu\u003es.2023.1100235\u003c/u\u003e \u003c/li\u003e\n\u003cli\u003eSermswan, R.W. and Wongratanacheewin, S., 2017. Physicochemical and Biological Factors of Soil and the Potential Use of Antagonistic Microbes for Biocontrol of Burkholderia pseudomallei. Current Tropical Medicine Reports. 4, 192-198.http://dx.doi.org/10.1007/s40\u003cu\u003e475-017-0125-3\u003c/u\u003e \u003c/li\u003e\n\u003cli\u003eShafi, J., Tian, H. and Ji, M., 2017. Bacillus species as versatile weapons for plant pathogens: a review. Biotechnology \u0026amp; Biotechnological Equipment. 31, 446-459.http://dx.doi.org/10.1080/131028\u003cu\u003e18.2017.1286950\u003c/u\u003e \u003c/li\u003e\n\u003cli\u003eShi, S., Nuccio, E.E., Shi, Z.J., He, Z., Zhou, J. and Firestone, M.K., 2016. The interconnected rhizosphere: High network complexity dominates rhizosphere assemblages. Ecol Lett. 19, 926-36.http://dx.doi.org/10.11\u003cu\u003e11/ele.12630\u003c/u\u003e \u003c/li\u003e\n\u003cli\u003eSilva, C.d.F., Medeiros, E.V.d., Santana, M.D., Ara\u0026uacute;jo, M.B.d., Martins Filho, A.P. and Moura, M.F.d., 2018. SOIL MICROBIOLOGICAL ACTIVITY AND PRODUCTIVITY OF MAIZE FODDER WITH LEGUMES AND MANURE DOSES. Revista Caatinga. 31, \u003c/li\u003e\n\u003cli\u003eSingh, V.K., Rai, S., Singh, D. and Upadhyay, R.S., 2021. Application of Soil Microorganisms for Agricultural and Environmental Sustainability: A Review, in: Dubey, S.K. and Verma, S.K. Eds.), Plant, Soil and Microbes in Tropical Ecosystems. Springer Singapore, Singapore, pp. 151-175. \u003c/li\u003e\n\u003cli\u003eSloan, W.T., Lunn, M., Woodcock, S., Head, I.M., Nee, S. and Curtis, T.P., 2006. Quantifying the roles of immigration and chance in shaping prokaryote community structure. Environmental Microbiology. 8, 732-740.http://dx.doi.org/10.1111/j.1462-2\u003cu\u003e920.2005.00956.x\u003c/u\u003e \u003c/li\u003e\n\u003cli\u003eSun, X., Chen, Z., Kong, T., Chen, Z., Dong, Y., Kolton, M., Cao, Z., Zhang, X., Zhang, H., Liu, G., Gao, P., Yang, N., Lan, L., Xu, Y. and Sun, W., 2022. Mycobacteriaceae Mineralizes Micropolyethylene in Riverine Ecosystems. Environmental Science \u0026amp; Technology. 56, 15705-15717.http://dx.doi.org/10.1021/a\u003cu\u003ecs.est.2c05346\u003c/u\u003e \u003c/li\u003e\n\u003cli\u003eSyldatk, C., May, O., Altenbuchner, J., Mattes, R. and Siemann, M., 1999. Microbial hydantoinases \u0026ndash; industrial enzymes from the origin of life? Applied Microbiology and Biotechnology. 51, 293-309.http://dx.doi.org/10.1007/s\u003cu\u003e002530051395\u003c/u\u003e \u003c/li\u003e\n\u003cli\u003eSzoboszlay, M. and Tebbe, C.C., 2021. Hidden heterogeneity and co-occurrence networks of soil prokaryotic communities revealed at the scale of individual soil aggregates. 10, e1144.http://dx.doi.org/https://doi.org/1\u003cu\u003e0.1002/mbo3.1144\u003c/u\u003e \u003c/li\u003e\n\u003cli\u003eTang, F.H.M., Lenzen, M., McBratney, A. and Maggi, F., 2021. Risk of pesticide pollution at the global scale. Nature Geoscience. 14, 206-210.http://dx.doi.org/10.1038/s415\u003cu\u003e61-021-00712-5\u003c/u\u003e \u003c/li\u003e\n\u003cli\u003eTao, J., Liu, X., Liang, Y., Niu, J., Xiao, Y., Gu, Y., Ma, L., Meng, D., Zhang, Y., Huang, W., Peng, D. and Yin, H., 2016. Maize growth responses to soil microbes and soil properties after fertilization with different green manures. Applied Microbiology and Biotechnology. 101, 1289-1299.http://dx.doi.org/10.1007/s00\u003cu\u003e253-016-7938-1\u003c/u\u003e \u003c/li\u003e\n\u003cli\u003eTrivedi, P., Leach, J.E., Tringe, S.G., Sa, T. and Singh, B.K., 2020. Plant\u0026ndash;microbiome interactions: from community assembly to plant health. Nature Reviews Microbiology. 18, 607-621.http://dx.doi.org/10.1038/s41\u003cu\u003e579-020-0412-1\u003c/u\u003e \u003c/li\u003e\n\u003cli\u003eWagg, C., Hautier, Y., Pellkofer, S., Banerjee, S. and Heijden, M.G.A.V.D., 2020. Diversity and asynchrony in soil microbial communities stabilizes ecosystem functioning. Cold Spring Harbor Laboratory. 10: 62813., \u003c/li\u003e\n\u003cli\u003eWahab, A., Batool, F., Muhammad, M., Zaman, W., Mikhlef, R.M., Qaddoori, S.M., Ullah, S., Abdi, G. and Saqib, S., 2024. Unveiling the complex molecular dynamics of arbuscular mycorrhizae: A comprehensive exploration and future perspectives in harnessing phosphate-solubilizing microorganisms for sustainable progress. Environmental and Experimental Botany. 219, 105633.http://dx.doi.org/https://doi.org/10.1016/j.\u003cu\u003eenvexpbot.2023.105633\u003c/u\u003e \u003c/li\u003e\n\u003cli\u003eWang, P., Wang, X., Nie, J., Wang, Y., Zang, H., Peixoto, L., Yang, Y. and Zeng, Z., 2022a. Manure Application Increases Soil Bacterial and Fungal Network Complexity and Alters Keystone Taxa. Journal of Soil Science and Plant Nutrition. 22, 607-618.http://dx.doi.org/10.1007/s427\u003cu\u003e29-021-00673-z\u003c/u\u003e \u003c/li\u003e\n\u003cli\u003eWang, T., Duan, Y., Liu, G., Shang, X., Liu, L., Zhang, K., Li, J., Zou, Z., Zhu, X. and Fang, W., 2022b. Tea plantation intercropping green manure enhances soil functional microbial abundance and multifunctionality resistance to drying-rewetting cycles. Science of The Total Environment. 810.http://dx.doi.org/10.1016/j.scito\u003cu\u003etenv.2021.151282\u003c/u\u003e \u003c/li\u003e\n\u003cli\u003eWilhelm, R.C., van Es, H.M. and Buckley, D.H., 2022. Predicting measures of soil health using the microbiome and supervised machine learning. Soil Biology and Biochemistry. 164, 108472.http://dx.doi.org/https://doi.org/10.1016\u003cu\u003e/j.soilbio.2021.108472\u003c/u\u003e \u003c/li\u003e\n\u003cli\u003eWilpiszeski, R.L., Aufrecht, J.A., Retterer, S.T., Sullivan, M.B., Graham, D.E., Pierce, E.M., Zablocki, O.D., Palumbo, A.V. and Elias, D.A., 2019. Soil Aggregate Microbial Communities: Towards Understanding Microbiome Interactions at Biologically Relevant Scales. 85, e00324-19.http://dx.doi.org/doi:10.1128\u003cu\u003e/AEM.00324-19\u003c/u\u003e \u003c/li\u003e\n\u003cli\u003eWu, C., Yan, B., Wei, F., Wang, H., Gao, L., Ma, H., Liu, Q., Liu, Y., Liu, G. and Wang, G., 2023. Long-term application of nitrogen and phosphorus fertilizers changes the process of community construction by affecting keystone species of crop rhizosphere microorganisms. Science of The Total Environment. 897.http://dx.doi.org/10.1016/j.scito\u003cu\u003etenv.2023.165239\u003c/u\u003e \u003c/li\u003e\n\u003cli\u003eWu, W., Logares, R., Huang, B. and Hsieh, C.h., 2017. Abundant and rare picoeukaryotic sub‐communities present contrasting patterns in the epipelagic waters of marginal seas in the northwestern Pacific Ocean. Environmental Microbiology. 19, 287-300.http://dx.doi.org/10.1111/14\u003cu\u003e62-2920.13606\u003c/u\u003e \u003c/li\u003e\n\u003cli\u003eWu, X., Rensing, C., Han, D., Xiao, K.-Q., Dai, Y., Tang, Z., Liesack, W., Peng, J., Cui, Z., Zhang, F. and Bouskill, N., 2022. Genome-Resolved Metagenomics Reveals Distinct Phosphorus Acquisition Strategies between Soil Microbiomes. mSystems. 7.http://dx.doi.org/https://doi.org/10.112\u003cu\u003e8/msystems.01107-21\u003c/u\u003e \u003c/li\u003e\n\u003cli\u003eXi, N., Chu, C. and Bloor, J.M.G., 2018. Plant drought resistance is mediated by soil microbial community structure and soil-plant feedbacks in a savanna tree species. Environmental and Experimental Botany. 155, 695-701.http://dx.doi.org/10.1016/j.envex\u003cu\u003epbot.2018.08.013\u003c/u\u003e \u003c/li\u003e\n\u003cli\u003eXiong, C. and Lu, Y., 2022. Microbiomes in agroecosystem: Diversity, function and assembly mechanisms. Environmental Microbiology Reports. 14, 833-849.http://dx.doi.org/10.1111/17\u003cu\u003e58-2229.13126\u003c/u\u003e \u003c/li\u003e\n\u003cli\u003eXu, Q., Luo, G., Guo, J., Xiao, Y., Zhang, F., Guo, S., Ling, N. and Shen, Q., 2021. Microbial generalist or specialist: Intraspecific variation and dormancy potential matter. Molecular Ecology. 31, 161-173.http://dx.doi.org/10.111\u003cu\u003e1/mec.16217\u003c/u\u003e \u003c/li\u003e\n\u003cli\u003eXue, Y., Chen, H., Yang, J.R., Liu, M., Huang, B. and Yang, J., 2018. Distinct patterns and processes of abundant and rare eukaryotic plankton communities following a reservoir cyanobacterial bloom. The ISME Journal. 12, 2263-2277.http://dx.doi.org/10.1038/s41\u003cu\u003e396-018-0159-0\u003c/u\u003e \u003c/li\u003e\n\u003cli\u003eXun, W., Liu, Y., Li, W., Ren, Y., Xiong, W., Xu, Z., Zhang, N., Miao, Y., Shen, Q. and Zhang, R., 2021. Specialized metabolic functions of keystone taxa sustain soil microbiome stability. Microbiome. 9, 35.http://dx.doi.org/10.1186/s401\u003cu\u003e68-020-00985-9\u003c/u\u003e \u003c/li\u003e\n\u003cli\u003eYang, X., Nian, J., Xie, Q., Feng, J., Zhang, F., Jing, H., Zhang, J., Dong, G., Liang, Y., Peng, J., Wang, G., Qian, Q. and Zuo, J., 2016. Rice Ferredoxin-Dependent Glutamate Synthase Regulates Nitrogen\u0026ndash;Carbon Metabolomes and Is Genetically Differentiated between japonica and indica Subspecies %J Molecular Plant. 9, 1520-1534 \u003c/li\u003e\n\u003cli\u003eYoussef, S.M., Shaaban, A., Abdelkhalik, A., Abd El Tawwab, A.R., Abd Al Halim, L.R., Rabee, L.A., Alwutayd, K.M., Ahmed, R.M.M., Alwutayd, R. and Hemida, K.A., 2023. Compost and Phosphorus/Potassium-Solubilizing Fungus Effectively Boosted Quinoa\u0026rsquo;s Physio-Biochemical Traits, Nutrient Acquisition, Soil Microbial Community, and Yield and Quality in Normal and Calcareous Soils. 12, 3071 \u003c/li\u003e\n\u003cli\u003eZhang, X., Zhang, R., Gao, J., Wang, X., Fan, F., Ma, X., Yin, H., Zhang, C., Feng, K. and Deng, Y., 2017. Thirty-one years of rice-rice-green manure rotations shape the rhizosphere microbial community and enrich beneficial bacteria. Soil Biology and Biochemistry. 104, 208-217.http://dx.doi.org/10.1016/j.soi\u003cu\u003elbio.2016.10.023\u003c/u\u003e \u003c/li\u003e\n\u003cli\u003eZhou, J. and Ning, D., 2017. Stochastic Community Assembly: Does It Matter in Microbial Ecology? Microbiology and Molecular Biology Reviews. 81, 10.1128/mmbr.00002-17.http://dx.doi.org/10.1128/m\u003cu\u003embr.00002-17\u003c/u\u003e \u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-biology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [BMC Biology](https://bmcbiol.biomedcentral.com/)","snPcode":"12915","submissionUrl":"https://submission.springernature.com/new-submission/12915/3","title":"BMC Biology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Intercropping of green manure, beneficial microorganisms, metagenomes, functional genes, soil function","lastPublishedDoi":"10.21203/rs.3.rs-7449409/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7449409/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eIntercropping crops with green manure offers a sustainable strategy to reduce nitrogen fertilizer dependency, enhance yields, and improve land use efficiency. While beneficial soil microorganisms are known to be key drivers of improved soil fertility and crop productivity, the differential responses of specific functional microbial communities to agronomic practices and their precise contributions to overall community structure and ecosystem function remain unclear. Here, we investigate how four key functional groups (NPK nutrient absorption [NPK], pathogen antagonism [PA], drought resisting [DR], and plastic degradation [PD]) driver ecosystem functions in a long-term maize-green manure intercropping field experiment. We found that green manure intercropping significantly decreased the Shannon and Simpson diversity and alterd four soil health-associated functional community composition. Moreover, green manure intercropping improved species connections and increased the network\u0026rsquo;s overall complexity. Crucially, we identified 11 novel core microbial genera with previously unrecognized roles in underpinning soil multifunctionality. Importantly, green manure-driven restructuring of the bacterial community optimizes functional redundancy, offering a novel pathway for the targeted manipulation of microbial communities and the optimization of agroecosystem functions.\u003c/p\u003e","manuscriptTitle":"Green manure intercropping reshapes beneficial microbial consortia to enhance soil multifunctionality and agroecosystem resilience","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-19 10:28:23","doi":"10.21203/rs.3.rs-7449409/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewersInvited","content":"","date":"2025-09-12T09:11:27+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-08-26T10:39:07+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-08-25T09:58:10+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Biology","date":"2025-08-25T03:42:56+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-biology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [BMC Biology](https://bmcbiol.biomedcentral.com/)","snPcode":"12915","submissionUrl":"https://submission.springernature.com/new-submission/12915/3","title":"BMC Biology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"dc477c6e-e8ab-4bf0-8814-6a17b6b61ac5","owner":[],"postedDate":"September 19th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-09-19T10:28:23+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-19 10:28:23","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7449409","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7449409","identity":"rs-7449409","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}