Phosphorus Solubilizing Bacteria Regulate Soil Phosphorus Activation Mechanisms and Impact on Available Nutrients: A Meta-Analysis

Phosphorus Solubilizing Bacteria Regulate Soil Phosphorus Activation Mechanisms and Impact on Available Nutrients: A Meta-Analysis | 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 Phosphorus Solubilizing Bacteria Regulate Soil Phosphorus Activation Mechanisms and Impact on Available Nutrients: A Meta-Analysis YAN JIA, Xiaobin Li, Yuanpeng Zhu, Jingyang Ma, Xing Fan, Peishen Du, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7033664/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background and aims The available phosphorus, nitrogen, and potassium concentrations in soil collectively serve as key indicators of soil fertility levels. Comprehending the effects of phosphorus solubilizing bacteria (PSB) on expeditious content levels is crucial for enhancing soil fertility and advancing sustainable agricultural development. Methods Using a meta-analysis method, this study systematically evaluated the effects of different factors, including soil pH, soil organic matter (SOM), PSB and crop types, on the changes in soil available nutrients (i.e., available phosphorus, nitrogen, and potassium) induced by PSB inoculation. Results PSB inoculation significantly increased soil available phosphorus (86.8%), nitrogen (64.9%), and potassium (41.9%) compared to non-inoculated controls. Subgroup analyses revealed that soil pH, SOM, PSB and crop types significantly modulated PSB-mediated augmentation in soil available phosphorus. SOM, PSB and crop types considerably affected PSB augmentation of soil available nitrogen. Meanwhile, PSB types notably impacted the increase of soil available potassium by PSB. Further analysis showed a significant negative correlation between soil pH and the ability of PSB to enhance soil available phosphorus, whereas SOM was significantly positively correlated with PSB to enhance soil available phosphorus and nitrogen. Conclusions These findings highlight the need for comprehensive consideration of soil pH, SOM, PSB and crop types when applying PSB to improve soil nutrient availability, This study offers empirical evidence for the systematic and efficient utilization of PSB to improve soil nutrient availability. Phosphorus solubilizing bacteria Rhizosphere enhancing bacteria Phosphorus solubilization mechanism Soil nutrient availability Meta-analysis Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction Phosphorus is one of the three essential macronutrients for plant growth and development (Qin et al. 2019 ). As a critical element of protoplasts structural materials, encompassing nucleic acids and phospholipids, it participates in light energy conversion, photosynthesis, carbon assimilation, genetic material replication, and oxidative phosphorylation within the respiratory chain (Chi et al. 2021 ). Additionally, phosphorus guarantees the homeostasis of the environment (Ameen et al. 2019 ). In agricultural ecosystems, approximately 60–80% of total soil phosphorus exists as insoluble metal ion-bound phosphates and organic phosphorus, significantly limiting its availability (Gustafsson et al. 2012 ) and complicating direct plant absorption of soil phosphorus (Zhang et al. 2020 ). To meet the phosphorus needs of crops, modern agriculture relies heavily on phosphorus fertilizers. Nevertheless, coordination reactions enable P0 4 3− to rapidly form insoluble phosphate complexes with cations, including Ca²⁺, Fe²⁺ and Al³⁺, which are incorporated into the soil (Vazquez et al. 2000 ). Combined with specific adsorption of inorganic phosphorus fertilizers on soil colloidal surfaces and lattice fixation, this accelerates phosphorus immobilization. As a result, unavailable phosphorus reserves continuously accumulate in the soil, forming a vicious cycle of “high input, low efficiency” (Bai et al. 2024 ). Consequently, it leads to a substantial accumulation of phosphorus in the soil, as the actual utilization rates of phosphorus fertilizer are only 10–25%. In the interim, rainfall-driven surface runoff transports soil phosphorus to water bodies, causing annual global losses exceeding 10⁷ tons and triggering ecological crises such as algal blooms and the expansion of hypoxic zones in water bodies (Sashidhar and Podile 2010 ). Soil microorganisms serve as the primary biological factors driving soil nutrient cycling, with particularly critical functions in the phosphorus biogeochemical cycle (Wang et al. 2003 ). PSB facilitate phosphorus transformation through multiple mechanisms: (1) secretion of low-molecular-weight organic acids (citric acid and oxalic acid) and protons (Li et al. 2024 ) acidify the soil microregion, chemically dissolving metal-phosphorus complexes (Tian et al. 2021 ); (2) production of phosphates (acid phosphatase and phytase) to catalyze the mineralization of organic phosphorus; and (3) synthesis of plant growth regulators (indoleacetic acid and gibberellin) to improve the root phosphorus uptake capacity (Chaiharn and Lumyong 2011 ). Systematic analysis has identified Bacillus , Pseudomonas , Burkholderia , and Enterobacter as the primary genera where microbial genera with significant phosphorus solubilizing functions are distributed (Billah et al. 2019 ). Empirical studies further demonstrate the functional diversity of PSB: Jaafa (2019)found that inoculation with PSB such as Acinetobacter and Sphingomonas promotes plant absorption and utilization of soil nutrients while immobilizing heavy metal ions in the soil; Chen et al.༈2020༉observed that inoculation with Pseudomonas bacteria in the rhizosphere of camellia influences PSB, thereby elevating the availability of phosphorus in the soil; and Gao et al.༈2006༉confirmed that PSB agents concurrently increase soil available phosphorus and potassium concentrations. This study hypothesizes that PSB inoculation can increase soil available nutrients under appropriate conditions. The objectives of this global meta-analysis are to: (1) clarify the impact of PSB inoculation on soil available nutrients and identify key regulatory factors; (2) assess the potential impact of PSB technology on increasing soil available nutrients globally. The results of this study provide a scientific basis for understanding the impact of PSB technology on soil available nutrients and its precise application. Materials and methods Data collection Articles addressing the effects of PSB applications from 2000 to 2024 were retrieved from Web of Science ( http://apps.webofknowledge.com ), Google Scholar ( http://scholar.google.com ), and China National Knowledge Infrastructure ( http://www.cnki.net ). Search keywords included: (a) “phosphorus solubilizing bacteria,” (b) “phosphorus-dissolving microorganisms,” (c) “rhizosphere enhancing bacteria,” and (d) “soil available nutrients” (and their Chinese equivalents). In addition, to ensure comprehensiveness, both search engine results and reference lists of identified papers were manually screened for additional relevant studies. Literature screening followed these criteria: (1) The same experiment included paired treatments with and without PSB inoculation; (2) Experiments had a clear number of replicates; (3) Studies measured soil available phosphorus, nitrogen, and potassium; (4) Articles provided experimental data with sample size ( n ), mean, number of replicates, and either standard deviation (SD) or standard error (SE). Finally, a total of 48 articles met the inclusion criteria. When SD was provided in the article, it was used directly. For studies providing SE and n but not SD, SD was calculated using the following formula: \(\:SD=SE\:\sqrt{n}\) \(\:\left(1\right)\) Data classification In order to examine the impact of soil properties (pH, SOM), PSB and crop types on the improvement of soil available phosphorus, nitrogen, and potassium by PSB, the collected data were categorized into multiple subgroups for comparative analysis. Following the recommendations of the United States Department of Agriculture (Shen et al. 2023 ), soils were classified based on pH into three categories: acidic ( 7.3). According to organic matter content (Lv et al. 2022 ), soils were classified into three categories: low organic matter ( 30 g kg − 1 ). The types of PSB include Bacillus , Enterobacter , Burkholderia , and Pseudomonas ; crop types include Juglandaceae , Brassicaceae , Solanaceae , Poaceae , and Fabaceae . Data analysis In this meta-analysis, the response ratio \(\:\left(\text{ln}\text{R}\right)\) was used as a statistical indicator (Hedges et al. 1999 ), with 95% confidence intervals calculated. The heterogeneity test was performed on the collected data, and based on the test results, the random effects model was employed to calculate \(\:\text{ln}\text{R}\:\) using the following formula: \(\:\text{ln}\text{R}=\text{ln}\left({\text{X}}_{\text{t}}/{\text{X}}_{\text{c}}\right)\) \(\:\left(2\right)\) where \(\:{\text{X}}_{\text{t}}\:\) and \(\:{\:\text{X}}_{\text{c}}\:\) represent the mean values of the experimental and control groups, respectively. The variance of \(\:\text{ln}\text{R}\) \(\:\left({\text{V}}_{\text{ln}\text{R}}\right)\:\) was calculated as follows: \(\:\text{V}=\frac{\text{S}{\text{D}}_{\text{t}}^{2}}{{\text{n}}_{\text{t}}{\text{X}}_{\text{t}}^{2}}+\frac{\text{S}{\text{D}}_{\text{c}}^{2}}{{\text{n}}_{\text{c}}{\text{X}}_{\text{c}}^{2}}\) \(\:\left(3\right)\) Here, \(\:\text{S}{\text{D}}_{\text{t}}\) and \(\:\text{S}{\text{D}}_{\text{c}}\) represent the standard deviations of the experimental and control groups, while \(\:{\text{n}}_{\text{t}}\) and \(\:{\text{n}}_{\text{c}}\) represent their respective sample size. The mean effect size ( \(\:\stackrel{-}{\text{ln}\text{R}}\) ) was calculated as follows: \(\:\stackrel{-}{\text{ln}\text{R}}=\frac{{\sum\:}_{\text{i}}\left({\text{V}}_{\text{i}}\times\:\text{ln}{\text{R}}_{\text{i}}\right)}{{\sum\:}_{\text{i}}{\text{V}}_{\text{i}}}\) \(\:\left(4\right)\) where \(\:\text{ln}{\text{R}}_{\text{i}}\) denotes the effect size of the -th value and \(\:{\text{V}}_{\text{i}}\) denotes its corresponding variance. The 95% confidence interval (95% CI) for \(\:\text{ln}\text{R}\) was calculated as follows: \(\:95\text{%}\:\text{C}\text{I}=\stackrel{-}{\text{ln}\text{R}}\pm\:1.96\times\:\sqrt{\frac{1}{{\sum\:}_{\text{i}}{\text{V}}_{\text{i}}}}\) \(\:\left(5\right)\) The \(\:\stackrel{-}{\text{ln}\text{R}\:}\) is considered significant if the \(\:95\text{%}\) confidence interval excludes a value of zero. To enhance interpretability, all effect sizes were converted to percentage changes using the formula (Islam et al. 2022 ): \(\:\text{Z}=\left(\text{e}\text{x}\text{p}\left(\text{ln}\text{R}-1\right)\right)\times\:100\text{%}\) \(\:\left(6\right)\) Statistical analysis This study employed Microsoft Excel 2016 ( https://products.office.com ) to establish a database, Get Data Graph Digitizer 2.26 ( https://getdata-graph-digitizer.com ) to extract and retrieve data presented in image form from the literature, Stata MP 17 ( https://www.stata.com ) for meta-analysis, Origin 2024 ( https://www.originlab.com ) and GraphPad Prism 8 ( https://www.graphpad.com ) for correlation analysis and data visualization, and R Studio ( https://www.r-project.org ) for random models. Results Overall effect of PSB on soil available nutrients Meta-analysis results revealed that PSB inoculation significantly enhanced the soil available nutrients compared to non-inoculated PSB, in which the soil available phosphorus, nitrogen, and potassium increased by 86.8% (CI: 69.1–104.5%), 64.9% (CI: 47.6–82.1%), and 40.9% (CI: 25.9 to 56.1%), respectively (Fig. 1 ). Effect of soil properties on PSB-enhanced soil available nutrients Under varying soil conditions, PSB inoculation significantly increased soil available phosphorus, nitrogen, and potassium compared with controls (Fig. 2 ). However, soil pH differentially affected these responses: while PSB-induced phosphorus augmentation varied significantly across pH gradients (acidic: 165.6%; neutral: 76.1%; alkaline: 44.1%), nitrogen and potassium enhancements remained unaffected. A linear decline in phosphorus availability was observed with increasing pH in acidic soil (Fig. 3 c). In addition, SOM content significantly influenced PSB-mediated changes in soil available phosphorus and nitrogen, but not potassium. Soil available phosphorus increased significantly more in high SOM (188.7%) compared to medium (91.9%) and low (51.5%) SOM soils; while soil available nitrogen exhibited a more pronounced increase in high SOM soils (104.7%) than in low SOM soil (34%) (Fig. 2 ). Moreover, a significant positive linear relationship was observed between high SOM and both soil available phosphorus and nitrogen (Figs. 3 a, b). Effect of PSB types on PSB-enhanced soil available nutrients The enhancement of soil available nutrients by PSB varied significantly with PSB types (Fig. 4 ). Different PSB types exerted distinct effects on the alteration of soil available phosphorus, nitrogen, and potassium. Specifically, Bacillus induced a 159.2% increase in soil available phosphorus, significantly outperforming Enterobacter (48.6%) and Burkholderia (25.9%). For soil available nitrogen, Enterobacter (124.6%) showed significantly greater efficacy than Burkholderia (44.5%) and Pseudomonas (22%). In the case of soil available potassium, Bacillus (76.9%) caused a notably larger increase compared to Pseudomonas (15.2%). Effect of crop types on PSB-enhanced soil available nutrients Crop types significantly modulated PSB-driven changes in soil available phosphorus and nitrogen, with no impact on available potassium (Fig. 5 ). Specifically, PSB inoculation induced significantly greater increments in available phosphorus in Solanaceae crop (126.7%) compared to Juglandaceae (58.5%), Poaceae (39.5%), and Brassicaceae (25.9%) crops. In addition, PSB increases in soil available nitrogen were most pronounced in Fabaceae crop (140%), far exceeding those in Solanaceae (40.6%) and Brassicaceae (19.4%) crops. Influence of soil properties, PSB and crop types on soil available nutrients Random forest model was used to quantify the extent to which different soil properties, PSB and crop types influenced PSB alteration of soil available nutrients (Fig. 6 ). Soil pH (21.97%) emerged as the most critical factor for soil available phosphorus, followed by soil SOM (20.78%), crop type (20.22%), and PSB type (17.51%) (Fig. 6 a). For soil available nitrogen, soil pH (24.38%) had the most significant effect, followed by crop type (23.17%), PSB type (21.36%), and SOM (21.08%) (Fig. 6 -B). In contrast, soil available potassium was uniquely influenced by PSB type (37.98%) (Fig. 6 c). Discussion Mechanism of PSB effect on soil available nutrients Soil available nutrients serves as a key indicator of soil fertility. Compared with non-inoculated PSB, PSB inoculation has been demonstrated to substantially increase soil available phosphorus, nitrogen, and potassium by 86.8%, 64.9%, and 40.9%, respectively (Fig. 1 ). PSB secrete organic acids that chelate cations from phosphate salts, form complex reactions with phosphate metal ions, lower environmental pH and compete for adsorption sites with phosphates, thereby dissolving inorganic phosphates (Kishore et al. 2015 ). Simultaneously, PSB assimilate soil NH 4 + to synthesize amino acids (Parks et al. 1990); during NH 4 + dissociation, released H + protons acidify the microorganism cell matrix and dissolve insoluble phosphates (Seleiman et al. 2022). Additionally, PSB secrete phosphates or phosphohydrolases to catalyze phosphorization reactions, hydrolyzing soil total organic phosphorus into plant-available forms (Singh and Reddy 2011), thereby increasing the content of readily available phosphorus, a finding supported by Chen et al. (2006) Furthermore, PSB also enhance the available nitrogen by increasing soil urease activity, accelerating the decomposition of urea into ammonium nitrogen, and promoting root development and nitrogen metabolism (Oburger et al. 2009 ). This aligns with Zhu et al. (2004) who reported that the application of phosphate solubilizing bacteria significantly elevated soil total phosphorus and nitrogen. By activating the mineralization activity of PSB, phosphate ions released during the phosphorus-solubilization process by PSB can indirectly promote the growth and reproduction of potassium solubilizing bacteria, thereby increasing the available potassium (Bakhshandeh et al. 2017 ). This is consistent with Rao et al. ( 2002 ) who demonstrated that PSB can facilitate the growth and reproduction of potassium-solubilizing and nitrogen-fixing bacteria. Effect mechanism of soil properties on PSB-enhanced soil available nutrients Soil properties (pH, SOM) play a crucial role in regulating soil available nutrients by PSB. Based on the meta-analysis in this study, Random Forest Model revealed soil pH as the key driver of PSB-mediated increases in soil available phosphorus and nitrogen (Figs. 6 a, b). Notably, soil pH significantly modulated soil available phosphorus but not nitrogen and potassium (Fig. 2 ). The results showed that PSB induced a 165.6% increase of the available phosphorus in acidic soils, far exceeding neutral (76.1%) and alkaline (44.1%) soils. This disparity arises from enhanced acid phosphatase activity in acidic environments, which dissolves insoluble phosphorus minerals and liberates organic acids, such as citric acid, to improve the chelation of Fe 3+ and Al 3+ (Zhang et al. 2019 ). Furthermore, elevated acid phosphatase activity also accelerates organic phosphorus mineralization (Jiang et al. 2025 ), directly boosting soil available phosphorus (Wang et al. 2018 ). Interestingly, soil available phosphorus decreased linearly with increasing pH (Fig. 3 c), likely due to pH-dependent inhibition of acid phosphatase secretion by PSB. Meanwhile, SOM content differentially influenced available phosphorus and nitrogen, with no significant effects on available potassium (Fig. 2 ). High SOM exhibited a 188.7% increase in available phosphorus, significantly surpassing medium (91.1%) and low (51.5%) SOM. As the carbon source provided by organic matter in high SOM stimulated the expansion of PSB (Chen et al. 2016 ), PSB secreted organic acids and phosphates to accelerate mineralisation and dissolve insoluble phosphates, thus increasing the available phosphorus in the soil (Yadav et al. 2015 ). Concurrently, abundant carbon sources in high SOM soils facilitate PSB-mediated conversion of organic nitrogen to ammonium nitrogen (NH 4 + ) and nitrate nitrogen (NO 3 − ) through nitrification, increasing available nitrogen levels (Davidson et al. 1986 ). A significant positive correlation was observed between SOM content and both available phosphorus and nitrogen (Figs. 3 a, b). This may be related to the increase in soil SOM content, which promotes the growth and reproduction of PSB and thus accelerates the decomposition of soil available phosphorus and nitrogen by PSB (Pold et al. 2022). Effect mechanism of PSB types on PSB-enhanced soil available nutrients As indicated by the Random Forest model, the types of PSB exert the most profound influence on soil available potassium (Fig. 6 c). Subgroup analyses demonstrated distinct effects of different PSB types on soil available nutrients (Fig. 3 ). Bacillus had the most significant effects on soil available phosphorus (159.2%) and potassium (76.9%) compared to other PSB types (Fig. 3 ). This superiority may be attributed to the spore-producing property of Bacillus , which enables tolerance to the harsh environments, such as high temperature and drought, and prolonged soil activity (Kovacs. 2019). Additionally, Bacillus secretes low molecular weight organic acids, such as malic acid, lactic acid, and citric acid, promoting the conversion of insoluble inorganic phosphorus (e.g. iron phosphate, aluminium phosphate, calcium phosphate) into soluble phosphate ions (HPO 4 2− , H 2 PO 4− ) (Zeng et al. 2014), thereby enhancing soil effective phosphorus content. In terms of soil available potassium, Bacillus can release strong acids into the extracellular environment via the direct oxidation pathway in the wall membrane space (Rodrı́guez and Fraga 1999 ), thereby acidifying mineral potassium in silicate minerals (Wu et al. 2018 ), and thus increasing the soil available potassium. In addition, Enterobacter demonstrated the most significant effect on soil available nitrogen (124.6%) (Fig. 3 ), likely due to its nitrogen-fixing capacity to fix atmospheric nitrogen during phosphorus solubilization and increase soil nitrogen storage (Sharan et al. 2008), thereby increasing available nitrogen. Effect mechanism of crop types on PSB-enhanced soil available nutrients Different crops had significantly different effects on soil available phosphorus and nitrogen increased by PSB, with no impact on soil available potassium (Fig. 4 ). Meta-analysis showed that Solanaceae crop (126.7%) had the most significant effect on soil available phosphorus. This may be attributed to Solanaceae crop being secreted through the root system of small organic acids, amino acids, fatty acids, and sugars (Hallama et al. 2019 ), which alters the pH and redox potential of the rhizosphere microenvironment, activates phospholipase secretion, and significantly improves PSB’s mineralization capacity for insoluble phosphorus while also providing PSB with essential growth factors, such as carbon and nitrogen sources (Rodrı́guez and Fraga 1999 ). Additionally, PSB decrease the bioavailability of heavy metals by chelation or complexation (Fernandez et al. 2007 ) and reduce the heavy metal fixation of soil phosphorus (Taurian et al. 2010), thereby increasing the soil available phosphorus. Fabaceae crop (140%) showed the most significant effect on soil available nitrogen compared to other crops, primarily due to its well-developed root systems and symbiotic relationships with rhizobia, enhancing soil available nitrogen through rhizobia nitrogen fixation (Nguyen et al. 2017 ). Conclusions In this study, a meta-analysis showed that PSB inoculation increased soil available nutrients, with available phosphorus, nitrogen, and potassium increasing by 86.8%, 64.9%, and 40.9%, respectively, compared to non-inoculated PSB. The effects of PSB on soil available nutrients were modulated by soil properties, PSB and crop types. Acidic and high SOM soil, Bacillus , and Solanaceae crops significantly increased available phosphorus. Notably, high SOM soil, Enterobacter , and Fabaceae crops exhibited the highest efficacy on enhancing available nitrogen, while Bacillus significantly increased available potassium. In conclusion, strategic selection of PSB, crop, and soil types can optimize the activation efficiency of soil phosphorus, nitrogen, and potassium, hence improving the availability of nutrients in the soil. This is essential for building an efficient PSB fertilizer application technology system and reducing fertilizer consumption to promote green and sustainable agricultural development. Declarations CRediT authorship contribution statement Yan Jia: Writing – original draft, Visualization, Formal analysis, Data curation. Xiaobin Li: Formal analysis, Data curation. Yuanpeng Zhu: Formal analysis, Data curation. Jingyang Ma: Formal analysis, Data curation. Xing Fan: Formal analysis, Data curation. Peishen Du: Formal analysis, Data curation. Ronghao Liu: Writing – review & editing, Visualization, Funding acquisition, Data curation, Conceptualization. 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. Data availability Data will be made available on request. Acknowledgements This research was funded by the Key Research and Development Program Young Scientist Project (2023YFD1901900), the Natural Science Foundation of Shanxi province (202203021211139), the Inner Mongolia Ordos City Science and Technology Program, and Research and Promotion Project of Water Conservancy Science and Technology in Shanxi Province (2025GM15). References Ameen F, AlYahya SA, AlNadhari S, Alasmari H, Alhoshani F, Wainwright M (2019) Phosphate solubilizing bacteria and fungi in desert soils: species, limitations and mechanisms. Arch Agron Soil Sci 65: 1446-1459. 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Zhang Z, Gao S, Chu C (2020) Improvement of nutrient use efficiency in rice: current toolbox and future perspectives. Theor Appl Genet 133: 1365-1384. Zhao ZX, Wang XY, Tian YJ, Wang R, Peng Q, Cai HJ (2022) Effects of straw returning on soil ammonia volatilization under different production conditions based on meta-analysis. Environ Sci 43: 1678-1687. Zheng BX, Hao XL, Ding K, Zhou GW, Chen QL, Zhang JB, Zhu YG (2017) Long-term nitrogen fertilization decreased the abundance of inorganic phosphate solubilizing bacteria in an alkaline soil. Sci Rep-Uk 7 : 42284. Supplementary Files Highlight.docx SupplementaryMaterials.docx data.xlsx Cite Share Download PDF Status: Posted Version 1 posted 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. 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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-7033664","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":485156788,"identity":"c0746ffd-1704-41fc-aa3f-af209fc09405","order_by":0,"name":"YAN JIA","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA5klEQVRIie3RMWvCUBDA8QsPrsujb72QolvnJ4Hgx0kIdCs4ZhANWOqg7votHDs+KbzpbNdsTcnaoeKSUXFtSeLm8H7z/eGOA3CcG4TweazqmgTC+66Ms3F7cu+ZKPSWwzvl2VSXbNuTnjA6AMyUP+NH//tFdFgMTRyOJAXaMmZJjqDmi7g5kcZU6yGFmve2SN4egHi/bU5ol2spKdXFx1ORMIKm55akXwFJpOn26ycaJa+iQwIWgnMi/Jwj6JgwDjZLEgpsSjFb2XpLP2dR/taTyysPdTbuqfmqOflDXjfuOI7j/OsEHGlLd0zyl3sAAAAASUVORK5CYII=","orcid":"","institution":"Taiyuan University of Technology College of Hydro Science and Engineering: Taiyuan University of Technology School of Hydro Science and Engineering","correspondingAuthor":true,"prefix":"","firstName":"YAN","middleName":"","lastName":"JIA","suffix":""},{"id":485156789,"identity":"52979818-ca60-4a1e-89c9-fd733b710ae4","order_by":1,"name":"Xiaobin Li","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Xiaobin","middleName":"","lastName":"Li","suffix":""},{"id":485156790,"identity":"0959571e-5192-45c3-87fd-6a021f47cf28","order_by":2,"name":"Yuanpeng Zhu","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Yuanpeng","middleName":"","lastName":"Zhu","suffix":""},{"id":485156791,"identity":"5d51298a-8c8f-458b-b2d9-9d4707d9a61f","order_by":3,"name":"Jingyang Ma","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Jingyang","middleName":"","lastName":"Ma","suffix":""},{"id":485156792,"identity":"37441f2f-5da8-4d95-aa81-ab61cfdfd89d","order_by":4,"name":"Xing Fan","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Xing","middleName":"","lastName":"Fan","suffix":""},{"id":485156793,"identity":"66873438-04ce-46be-bfc5-a1edd40d2788","order_by":5,"name":"Peishen Du","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Peishen","middleName":"","lastName":"Du","suffix":""},{"id":485156794,"identity":"a84f0f39-b448-4f42-8244-1cefb08a53cb","order_by":6,"name":"Ronghao Liu","email":"","orcid":"https://orcid.org/0000-0002-9590-3653","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Ronghao","middleName":"","lastName":"Liu","suffix":""}],"badges":[],"createdAt":"2025-07-03 03:13:21","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7033664/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7033664/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":86933700,"identity":"d2b30df0-c9db-4649-895c-f8b168ed491c","added_by":"auto","created_at":"2025-07-17 10:16:05","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":24178,"visible":true,"origin":"","legend":"\u003cp\u003eThe overall effect of PSB on soil content of available phosphorus, available nitrogen and available potassium. Symbols indicate mean effect sizes and error lines indicate 95% confidence intervals. Error lines that do not coincide with zero indicate a significant effect of treatment. Values in parentheses represent sample sizes.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7033664/v1/0b7bdf6b6154a9091fa9e8b7.png"},{"id":86932711,"identity":"b062a3f5-d628-4a6a-946f-e210d8d99fb1","added_by":"auto","created_at":"2025-07-17 10:08:04","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":76521,"visible":true,"origin":"","legend":"\u003cp\u003eEffect of PSB on available phosphorus, available nitrogen, and available potassium levels in soil. Symbols indicate mean effect sizes and error lines indicate 95% confidence intervals. Numbers in parentheses indicate sample size. Error lines that do not coincide with zero indicate a significant effect of treatment. Different letters indicate significant differences between subgroups (i.e., 95% confidence intervals do not overlap). *, ** and *** indicate significance levels of p \u0026lt; 0.05, p \u0026lt; 0.01 and p \u0026lt; 0.001 for between-group heterogeneity, respectively.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7033664/v1/48231069468c0bfac0d3deb6.png"},{"id":86932712,"identity":"a3800805-4c99-4050-82fb-4a885aeee737","added_by":"auto","created_at":"2025-07-17 10:08:05","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":107203,"visible":true,"origin":"","legend":"\u003cp\u003eThe relationship between soil available phosphorus and available nitrogen and soil pH (c) and SOM (ab).\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7033664/v1/362f3353dbf06a7fdbc55606.png"},{"id":86932716,"identity":"99fba6eb-b14c-4344-a3ab-bf0ea9d72120","added_by":"auto","created_at":"2025-07-17 10:08:05","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":58397,"visible":true,"origin":"","legend":"\u003cp\u003eEffect of PSB type on PSB on soil content of available phosphorus, available nitrogen and available potassium. The symbols are the same as in Fig.2.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-7033664/v1/653a1c7f590f9e2ba26bd439.png"},{"id":86932720,"identity":"c088e637-3487-449c-835f-589a842a5037","added_by":"auto","created_at":"2025-07-17 10:08:05","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":63830,"visible":true,"origin":"","legend":"\u003cp\u003eEffect of different crop types on PSB alteration of soil available phosphorus, available nitrogen and available potassium content. Symbols are the same as in Fig.2.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-7033664/v1/dd8f55b5c4f991df066ff78d.png"},{"id":86932718,"identity":"f3688ffd-16f7-4d31-8c4f-77f1956f95be","added_by":"auto","created_at":"2025-07-17 10:08:05","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":54675,"visible":true,"origin":"","legend":"\u003cp\u003eRelative importance of each variable in the Random Forest Model analysis for PSB enhancement of soil available phosphorus, available nitrogen, and available potassium.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-7033664/v1/5f6acf7b1f1c024f2521cfa9.png"},{"id":92343768,"identity":"649f1d8e-b662-44a4-9742-af0c4c63c2ef","added_by":"auto","created_at":"2025-09-28 08:02:44","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":886262,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7033664/v1/4942d539-fd04-4bf2-b057-6106eab096af.pdf"},{"id":86934579,"identity":"5cf23b6c-187c-4195-8f6d-75977208ca7e","added_by":"auto","created_at":"2025-07-17 10:24:05","extension":"docx","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":13966,"visible":true,"origin":"","legend":"","description":"","filename":"Highlight.docx","url":"https://assets-eu.researchsquare.com/files/rs-7033664/v1/ebde61aaa688d27b7ed0e83c.docx"},{"id":86932719,"identity":"09e96fa7-bff1-4093-9cb0-b5fcd754991b","added_by":"auto","created_at":"2025-07-17 10:08:05","extension":"docx","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":102312,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMaterials.docx","url":"https://assets-eu.researchsquare.com/files/rs-7033664/v1/8913b739c2bbe006da904cd7.docx"},{"id":86934578,"identity":"b385f1c2-3614-4054-999c-72ee17c792a2","added_by":"auto","created_at":"2025-07-17 10:24:05","extension":"xlsx","order_by":7,"title":"","display":"","copyAsset":false,"role":"supplement","size":31138,"visible":true,"origin":"","legend":"","description":"","filename":"data.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7033664/v1/d1c82188eee9c1ff636354cd.xlsx"}],"financialInterests":"","formattedTitle":"Phosphorus Solubilizing Bacteria Regulate Soil Phosphorus Activation Mechanisms and Impact on Available Nutrients: A Meta-Analysis","fulltext":[{"header":"Introduction","content":"\u003cp\u003ePhosphorus is one of the three essential macronutrients for plant growth and development (Qin et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). As a critical element of protoplasts structural materials, encompassing nucleic acids and phospholipids, it participates in light energy conversion, photosynthesis, carbon assimilation, genetic material replication, and oxidative phosphorylation within the respiratory chain (Chi et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Additionally, phosphorus guarantees the homeostasis of the environment (Ameen et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). In agricultural ecosystems, approximately 60\u0026ndash;80% of total soil phosphorus exists as insoluble metal ion-bound phosphates and organic phosphorus, significantly limiting its availability (Gustafsson et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) and complicating direct plant absorption of soil phosphorus (Zhang et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). To meet the phosphorus needs of crops, modern agriculture relies heavily on phosphorus fertilizers. Nevertheless, coordination reactions enable P0\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e3\u0026minus;\u003c/sup\u003e to rapidly form insoluble phosphate complexes with cations, including Ca\u0026sup2;⁺, Fe\u0026sup2;⁺ and Al\u0026sup3;⁺, which are incorporated into the soil (Vazquez et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2000\u003c/span\u003e). Combined with specific adsorption of inorganic phosphorus fertilizers on soil colloidal surfaces and lattice fixation, this accelerates phosphorus immobilization. As a result, unavailable phosphorus reserves continuously accumulate in the soil, forming a vicious cycle of \u0026ldquo;high input, low efficiency\u0026rdquo; (Bai et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Consequently, it leads to a substantial accumulation of phosphorus in the soil, as the actual utilization rates of phosphorus fertilizer are only 10\u0026ndash;25%. In the interim, rainfall-driven surface runoff transports soil phosphorus to water bodies, causing annual global losses exceeding 10⁷ tons and triggering ecological crises such as algal blooms and the expansion of hypoxic zones in water bodies (Sashidhar and Podile \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2010\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eSoil microorganisms serve as the primary biological factors driving soil nutrient cycling, with particularly critical functions in the phosphorus biogeochemical cycle (Wang et al. \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). PSB facilitate phosphorus transformation through multiple mechanisms: (1) secretion of low-molecular-weight organic acids (citric acid and oxalic acid) and protons (Li et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) acidify the soil microregion, chemically dissolving metal-phosphorus complexes (Tian et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2021\u003c/span\u003e); (2) production of phosphates (acid phosphatase and phytase) to catalyze the mineralization of organic phosphorus; and (3) synthesis of plant growth regulators (indoleacetic acid and gibberellin) to improve the root phosphorus uptake capacity (Chaiharn and Lumyong \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Systematic analysis has identified \u003cem\u003eBacillus\u003c/em\u003e, \u003cem\u003ePseudomonas\u003c/em\u003e, \u003cem\u003eBurkholderia\u003c/em\u003e, and \u003cem\u003eEnterobacter\u003c/em\u003e as the primary genera where microbial genera with significant phosphorus solubilizing functions are distributed (Billah et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Empirical studies further demonstrate the functional diversity of PSB: Jaafa (2019)found that inoculation with PSB such as \u003cem\u003eAcinetobacter\u003c/em\u003e and \u003cem\u003eSphingomonas\u003c/em\u003e promotes plant absorption and utilization of soil nutrients while immobilizing heavy metal ions in the soil; Chen et al.༈2020༉observed that inoculation with \u003cem\u003ePseudomonas\u003c/em\u003e bacteria in the rhizosphere of camellia influences PSB, thereby elevating the availability of phosphorus in the soil; and Gao et al.༈2006༉confirmed that PSB agents concurrently increase soil available phosphorus and potassium concentrations.\u003c/p\u003e\u003cp\u003eThis study hypothesizes that PSB inoculation can increase soil available nutrients under appropriate conditions. The objectives of this global meta-analysis are to: (1) clarify the impact of PSB inoculation on soil available nutrients and identify key regulatory factors; (2) assess the potential impact of PSB technology on increasing soil available nutrients globally. The results of this study provide a scientific basis for understanding the impact of PSB technology on soil available nutrients and its precise application.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cp\u003eData collection\u003c/p\u003e\u003cp\u003eArticles addressing the effects of PSB applications from 2000 to 2024 were retrieved from 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), Google Scholar (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://scholar.google.com\u003c/span\u003e\u003cspan address=\"http://scholar.google.com\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), and China National Knowledge Infrastructure (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.cnki.net\u003c/span\u003e\u003cspan address=\"http://www.cnki.net\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). Search keywords included: (a) \u0026ldquo;phosphorus solubilizing bacteria,\u0026rdquo; (b) \u0026ldquo;phosphorus-dissolving microorganisms,\u0026rdquo; (c) \u0026ldquo;rhizosphere enhancing bacteria,\u0026rdquo; and (d) \u0026ldquo;soil available nutrients\u0026rdquo; (and their Chinese equivalents). In addition, to ensure comprehensiveness, both search engine results and reference lists of identified papers were manually screened for additional relevant studies. Literature screening followed these criteria: (1) The same experiment included paired treatments with and without PSB inoculation; (2) Experiments had a clear number of replicates; (3) Studies measured soil available phosphorus, nitrogen, and potassium; (4) Articles provided experimental data with sample size (\u003cem\u003en\u003c/em\u003e), mean, number of replicates, and either standard deviation (SD) or standard error (SE). Finally, a total of 48 articles met the inclusion criteria. When SD was provided in the article, it was used directly. For studies providing SE and \u003cem\u003en\u003c/em\u003e but not SD, SD was calculated using the following formula:\u003c/p\u003e\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:SD=SE\\:\\sqrt{n}\\)\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\left(1\\right)\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\u003cp\u003eData classification\u003c/p\u003e\u003cp\u003eIn order to examine the impact of soil properties (pH, SOM), PSB and crop types on the improvement of soil available phosphorus, nitrogen, and potassium by PSB, the collected data were categorized into multiple subgroups for comparative analysis. Following the recommendations of the United States Department of Agriculture (Shen et al. \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), soils were classified based on pH into three categories: acidic (\u0026lt;\u0026thinsp;6.5), neutral (6.5\u0026ndash;7.3), and alkaline (\u0026gt;\u0026thinsp;7.3). According to organic matter content (Lv et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), soils were classified into three categories: low organic matter (\u0026lt;\u0026thinsp;15 g kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e), medium organic matter (15\u0026ndash;30 g kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e), and high organic matter (\u0026gt;\u0026thinsp;30 g kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e). The types of PSB include \u003cem\u003eBacillus\u003c/em\u003e, \u003cem\u003eEnterobacter\u003c/em\u003e, \u003cem\u003eBurkholderia\u003c/em\u003e, and \u003cem\u003ePseudomonas\u003c/em\u003e; crop types include \u003cem\u003eJuglandaceae\u003c/em\u003e, \u003cem\u003eBrassicaceae\u003c/em\u003e, \u003cem\u003eSolanaceae\u003c/em\u003e, \u003cem\u003ePoaceae\u003c/em\u003e, and \u003cem\u003eFabaceae\u003c/em\u003e.\u003c/p\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eData analysis\u003c/h2\u003e\u003cp\u003eIn this meta-analysis, the response ratio \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\left(\\text{ln}\\text{R}\\right)\\)\u003c/span\u003e\u003c/span\u003ewas used as a statistical indicator (Hedges et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e1999\u003c/span\u003e), with 95% confidence intervals calculated. The heterogeneity test was performed on the collected data, and based on the test results, the random effects model was employed to calculate \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\text{ln}\\text{R}\\:\\)\u003c/span\u003e\u003c/span\u003e using the following formula:\u003c/p\u003e\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\text{ln}\\text{R}=\\text{ln}\\left({\\text{X}}_{\\text{t}}/{\\text{X}}_{\\text{c}}\\right)\\)\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\left(2\\right)\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\u003cp\u003ewhere \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\text{X}}_{\\text{t}}\\:\\)\u003c/span\u003e\u003c/span\u003eand\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\:\\text{X}}_{\\text{c}}\\:\\)\u003c/span\u003e\u003c/span\u003erepresent the mean values of the experimental and control groups, respectively. The variance of \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\text{ln}\\text{R}\\)\u003c/span\u003e\u003c/span\u003e \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\left({\\text{V}}_{\\text{ln}\\text{R}}\\right)\\:\\)\u003c/span\u003e\u003c/span\u003ewas calculated as follows:\u003c/p\u003e\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\text{V}=\\frac{\\text{S}{\\text{D}}_{\\text{t}}^{2}}{{\\text{n}}_{\\text{t}}{\\text{X}}_{\\text{t}}^{2}}+\\frac{\\text{S}{\\text{D}}_{\\text{c}}^{2}}{{\\text{n}}_{\\text{c}}{\\text{X}}_{\\text{c}}^{2}}\\)\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\left(3\\right)\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\u003cp\u003eHere, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\text{S}{\\text{D}}_{\\text{t}}\\)\u003c/span\u003e\u003c/span\u003e and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\text{S}{\\text{D}}_{\\text{c}}\\)\u003c/span\u003e\u003c/span\u003e represent the standard deviations of the experimental and control groups, while \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\text{n}}_{\\text{t}}\\)\u003c/span\u003e\u003c/span\u003e and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\text{n}}_{\\text{c}}\\)\u003c/span\u003e\u003c/span\u003e represent their respective sample size. The mean effect size (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\stackrel{-}{\\text{ln}\\text{R}}\\)\u003c/span\u003e\u003c/span\u003e) was calculated as follows:\u003c/p\u003e\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\stackrel{-}{\\text{ln}\\text{R}}=\\frac{{\\sum\\:}_{\\text{i}}\\left({\\text{V}}_{\\text{i}}\\times\\:\\text{ln}{\\text{R}}_{\\text{i}}\\right)}{{\\sum\\:}_{\\text{i}}{\\text{V}}_{\\text{i}}}\\)\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\left(4\\right)\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\u003cp\u003ewhere \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\text{ln}{\\text{R}}_{\\text{i}}\\)\u003c/span\u003e\u003c/span\u003e denotes the effect size of the \u003cspan class=\"InlineEquation\"\u003e\u003c/span\u003e-th value and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\text{V}}_{\\text{i}}\\)\u003c/span\u003e\u003c/span\u003e denotes its corresponding variance. The 95% confidence interval (95% CI) for \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\text{ln}\\text{R}\\)\u003c/span\u003e\u003c/span\u003e was calculated as follows:\u003c/p\u003e\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:95\\text{%}\\:\\text{C}\\text{I}=\\stackrel{-}{\\text{ln}\\text{R}}\\pm\\:1.96\\times\\:\\sqrt{\\frac{1}{{\\sum\\:}_{\\text{i}}{\\text{V}}_{\\text{i}}}}\\)\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\left(5\\right)\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\u003cp\u003eThe \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\stackrel{-}{\\text{ln}\\text{R}\\:}\\)\u003c/span\u003e\u003c/span\u003e is considered significant if the \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:95\\text{%}\\)\u003c/span\u003e\u003c/span\u003e confidence interval excludes a value of zero. To enhance interpretability, all effect sizes were converted to percentage changes using the formula (Islam et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2022\u003c/span\u003e):\u003c/p\u003e\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\text{Z}=\\left(\\text{e}\\text{x}\\text{p}\\left(\\text{ln}\\text{R}-1\\right)\\right)\\times\\:100\\text{%}\\)\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\left(6\\right)\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003eStatistical analysis\u003c/h2\u003e\u003cp\u003eThis study employed Microsoft Excel 2016 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://products.office.com\u003c/span\u003e\u003cspan address=\"https://products.office.com\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) to establish a database, Get Data Graph Digitizer 2.26 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://getdata-graph-digitizer.com\u003c/span\u003e\u003cspan address=\"https://getdata-graph-digitizer.com\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) to extract and retrieve data presented in image form from the literature, Stata MP 17 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.stata.com\u003c/span\u003e\u003cspan address=\"https://www.stata.com\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) for meta-analysis, Origin 2024 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.originlab.com\u003c/span\u003e\u003cspan address=\"https://www.originlab.com\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) and GraphPad Prism 8 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.graphpad.com\u003c/span\u003e\u003cspan address=\"https://www.graphpad.com\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) for correlation analysis and data visualization, and R Studio (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.r-project.org\u003c/span\u003e\u003cspan address=\"https://www.r-project.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) for random models.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eOverall effect of PSB on soil available nutrients\u003c/p\u003e\u003cp\u003eMeta-analysis results revealed that PSB inoculation significantly enhanced the soil available nutrients compared to non-inoculated PSB, in which the soil available phosphorus, nitrogen, and potassium increased by 86.8% (CI: 69.1\u0026ndash;104.5%), 64.9% (CI: 47.6\u0026ndash;82.1%), and 40.9% (CI: 25.9 to 56.1%), respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eEffect of soil properties on PSB-enhanced soil available nutrients\u003c/p\u003e\u003cp\u003eUnder varying soil conditions, PSB inoculation significantly increased soil available phosphorus, nitrogen, and potassium compared with controls (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e2\u003c/span\u003e). However, soil pH differentially affected these responses: while PSB-induced phosphorus augmentation varied significantly across pH gradients (acidic: 165.6%; neutral: 76.1%; alkaline: 44.1%), nitrogen and potassium enhancements remained unaffected. A linear decline in phosphorus availability was observed with increasing pH in acidic soil (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e3\u003c/span\u003ec). In addition, SOM content significantly influenced PSB-mediated changes in soil available phosphorus and nitrogen, but not potassium. Soil available phosphorus increased significantly more in high SOM (188.7%) compared to medium (91.9%) and low (51.5%) SOM soils; while soil available nitrogen exhibited a more pronounced increase in high SOM soils (104.7%) than in low SOM soil (34%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Moreover, a significant positive linear relationship was observed between high SOM and both soil available phosphorus and nitrogen (Figs.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e3\u003c/span\u003ea, b).\u003c/p\u003e\u003cp\u003eEffect of PSB types on PSB-enhanced soil available nutrients\u003c/p\u003e\u003cp\u003eThe enhancement of soil available nutrients by PSB varied significantly with PSB types (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Different PSB types exerted distinct effects on the alteration of soil available phosphorus, nitrogen, and potassium. Specifically, \u003cem\u003eBacillus\u003c/em\u003e induced a 159.2% increase in soil available phosphorus, significantly outperforming \u003cem\u003eEnterobacter\u003c/em\u003e (48.6%) and \u003cem\u003eBurkholderia\u003c/em\u003e (25.9%). For soil available nitrogen, \u003cem\u003eEnterobacter\u003c/em\u003e (124.6%) showed significantly greater efficacy than \u003cem\u003eBurkholderia\u003c/em\u003e (44.5%) and \u003cem\u003ePseudomonas\u003c/em\u003e (22%). In the case of soil available potassium, \u003cem\u003eBacillus\u003c/em\u003e (76.9%) caused a notably larger increase compared to \u003cem\u003ePseudomonas\u003c/em\u003e (15.2%).\u003c/p\u003e\u003cp\u003eEffect of crop types on PSB-enhanced soil available nutrients\u003c/p\u003e\u003cp\u003eCrop types significantly modulated PSB-driven changes in soil available phosphorus and nitrogen, with no impact on available potassium (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e5\u003c/span\u003e). Specifically, PSB inoculation induced significantly greater increments in available phosphorus in \u003cem\u003eSolanaceae\u003c/em\u003e crop (126.7%) compared to \u003cem\u003eJuglandaceae\u003c/em\u003e (58.5%), \u003cem\u003ePoaceae\u003c/em\u003e (39.5%), and \u003cem\u003eBrassicaceae\u003c/em\u003e (25.9%) crops. In addition, PSB increases in soil available nitrogen were most pronounced in \u003cem\u003eFabaceae\u003c/em\u003e crop (140%), far exceeding those in \u003cem\u003eSolanaceae\u003c/em\u003e (40.6%) and \u003cem\u003eBrassicaceae\u003c/em\u003e (19.4%) crops.\u003c/p\u003e\u003cp\u003eInfluence of soil properties, PSB and crop types on soil available nutrients\u003c/p\u003e\u003cp\u003eRandom forest model was used to quantify the extent to which different soil properties, PSB and crop types influenced PSB alteration of soil available nutrients (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e6\u003c/span\u003e). Soil pH (21.97%) emerged as the most critical factor for soil available phosphorus, followed by soil SOM (20.78%), crop type (20.22%), and PSB type (17.51%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e6\u003c/span\u003ea). For soil available nitrogen, soil pH (24.38%) had the most significant effect, followed by crop type (23.17%), PSB type (21.36%), and SOM (21.08%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e6\u003c/span\u003e-B). In contrast, soil available potassium was uniquely influenced by PSB type (37.98%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e6\u003c/span\u003ec).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eMechanism of PSB effect on soil available nutrients\u003c/p\u003e\u003cp\u003eSoil available nutrients serves as a key indicator of soil fertility. Compared with non-inoculated PSB, PSB inoculation has been demonstrated to substantially increase soil available phosphorus, nitrogen, and potassium by 86.8%, 64.9%, and 40.9%, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e1\u003c/span\u003e). PSB secrete organic acids that chelate cations from phosphate salts, form complex reactions with phosphate metal ions, lower environmental pH and compete for adsorption sites with phosphates, thereby dissolving inorganic phosphates (Kishore et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Simultaneously, PSB assimilate soil NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e to synthesize amino acids (Parks et al. 1990); during NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e dissociation, released H\u003csup\u003e+\u003c/sup\u003e protons acidify the microorganism cell matrix and dissolve insoluble phosphates (Seleiman et al. 2022). Additionally, PSB secrete phosphates or phosphohydrolases to catalyze phosphorization reactions, hydrolyzing soil total organic phosphorus into plant-available forms (Singh and Reddy 2011), thereby increasing the content of readily available phosphorus, a finding supported by Chen et al. (2006) Furthermore, PSB also enhance the available nitrogen by increasing soil urease activity, accelerating the decomposition of urea into ammonium nitrogen, and promoting root development and nitrogen metabolism (Oburger et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). This aligns with Zhu et al. (2004) who reported that the application of phosphate solubilizing bacteria significantly elevated soil total phosphorus and nitrogen. By activating the mineralization activity of PSB, phosphate ions released during the phosphorus-solubilization process by PSB can indirectly promote the growth and reproduction of potassium solubilizing bacteria, thereby increasing the available potassium (Bakhshandeh et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). This is consistent with Rao et al. (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2002\u003c/span\u003e) who demonstrated that PSB can facilitate the growth and reproduction of potassium-solubilizing and nitrogen-fixing bacteria.\u003c/p\u003e\u003cp\u003eEffect mechanism of soil properties on PSB-enhanced soil available nutrients\u003c/p\u003e\u003cp\u003eSoil properties (pH, SOM) play a crucial role in regulating soil available nutrients by PSB. Based on the meta-analysis in this study, Random Forest Model revealed soil pH as the key driver of PSB-mediated increases in soil available phosphorus and nitrogen (Figs.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e6\u003c/span\u003ea, b). Notably, soil pH significantly modulated soil available phosphorus but not nitrogen and potassium (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The results showed that PSB induced a 165.6% increase of the available phosphorus in acidic soils, far exceeding neutral (76.1%) and alkaline (44.1%) soils. This disparity arises from enhanced acid phosphatase activity in acidic environments, which dissolves insoluble phosphorus minerals and liberates organic acids, such as citric acid, to improve the chelation of Fe\u003csup\u003e3+\u003c/sup\u003e and Al\u003csup\u003e3+\u003c/sup\u003e (Zhang et al. \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Furthermore, elevated acid phosphatase activity also accelerates organic phosphorus mineralization (Jiang et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2025\u003c/span\u003e), directly boosting soil available phosphorus (Wang et al. \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Interestingly, soil available phosphorus decreased linearly with increasing pH (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e3\u003c/span\u003ec), likely due to pH-dependent inhibition of acid phosphatase secretion by PSB. Meanwhile, SOM content differentially influenced available phosphorus and nitrogen, with no significant effects on available potassium (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e2\u003c/span\u003e). High SOM exhibited a 188.7% increase in available phosphorus, significantly surpassing medium (91.1%) and low (51.5%) SOM. As the carbon source provided by organic matter in high SOM stimulated the expansion of PSB (Chen et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), PSB secreted organic acids and phosphates to accelerate mineralisation and dissolve insoluble phosphates, thus increasing the available phosphorus in the soil (Yadav et al. \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Concurrently, abundant carbon sources in high SOM soils facilitate PSB-mediated conversion of organic nitrogen to ammonium nitrogen (NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e) and nitrate nitrogen (NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e) through nitrification, increasing available nitrogen levels (Davidson et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e1986\u003c/span\u003e). A significant positive correlation was observed between SOM content and both available phosphorus and nitrogen (Figs.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e3\u003c/span\u003ea, b). This may be related to the increase in soil SOM content, which promotes the growth and reproduction of PSB and thus accelerates the decomposition of soil available phosphorus and nitrogen by PSB (Pold et al. 2022).\u003c/p\u003e\u003cp\u003eEffect mechanism of PSB types on PSB-enhanced soil available nutrients\u003c/p\u003e\u003cp\u003eAs indicated by the Random Forest model, the types of PSB exert the most profound influence on soil available potassium (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e6\u003c/span\u003ec). Subgroup analyses demonstrated distinct effects of different PSB types on soil available nutrients (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e3\u003c/span\u003e). \u003cem\u003eBacillus\u003c/em\u003e had the most significant effects on soil available phosphorus (159.2%) and potassium (76.9%) compared to other PSB types (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e3\u003c/span\u003e). This superiority may be attributed to the spore-producing property of \u003cem\u003eBacillus\u003c/em\u003e, which enables tolerance to the harsh environments, such as high temperature and drought, and prolonged soil activity (Kovacs. 2019). Additionally, \u003cem\u003eBacillus\u003c/em\u003e secretes low molecular weight organic acids, such as malic acid, lactic acid, and citric acid, promoting the conversion of insoluble inorganic phosphorus (e.g. iron phosphate, aluminium phosphate, calcium phosphate) into soluble phosphate ions (HPO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e, H\u003csub\u003e2\u003c/sub\u003ePO\u003csup\u003e4\u0026minus;\u003c/sup\u003e) (Zeng et al. 2014), thereby enhancing soil effective phosphorus content. In terms of soil available potassium, \u003cem\u003eBacillus\u003c/em\u003e can release strong acids into the extracellular environment via the direct oxidation pathway in the wall membrane space (Rodrı́guez and Fraga \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e1999\u003c/span\u003e), thereby acidifying mineral potassium in silicate minerals (Wu et al. \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), and thus increasing the soil available potassium. In addition, \u003cem\u003eEnterobacter\u003c/em\u003e demonstrated the most significant effect on soil available nitrogen (124.6%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e3\u003c/span\u003e), likely due to its nitrogen-fixing capacity to fix atmospheric nitrogen during phosphorus solubilization and increase soil nitrogen storage (Sharan et al. 2008), thereby increasing available nitrogen.\u003c/p\u003e\u003cp\u003eEffect mechanism of crop types on PSB-enhanced soil available nutrients\u003c/p\u003e\u003cp\u003eDifferent crops had significantly different effects on soil available phosphorus and nitrogen increased by PSB, with no impact on soil available potassium (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Meta-analysis showed that \u003cem\u003eSolanaceae\u003c/em\u003e crop (126.7%) had the most significant effect on soil available phosphorus. This may be attributed to \u003cem\u003eSolanaceae\u003c/em\u003e crop being secreted through the root system of small organic acids, amino acids, fatty acids, and sugars (Hallama et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), which alters the pH and redox potential of the rhizosphere microenvironment, activates phospholipase secretion, and significantly improves PSB\u0026rsquo;s mineralization capacity for insoluble phosphorus while also providing PSB with essential growth factors, such as carbon and nitrogen sources (Rodrı́guez and Fraga \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e1999\u003c/span\u003e). Additionally, PSB decrease the bioavailability of heavy metals by chelation or complexation (Fernandez et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2007\u003c/span\u003e) and reduce the heavy metal fixation of soil phosphorus (Taurian et al. 2010), thereby increasing the soil available phosphorus. \u003cem\u003eFabaceae\u003c/em\u003e crop (140%) showed the most significant effect on soil available nitrogen compared to other crops, primarily due to its well-developed root systems and symbiotic relationships with rhizobia, enhancing soil available nitrogen through rhizobia nitrogen fixation (Nguyen et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn this study, a meta-analysis showed that PSB inoculation increased soil available nutrients, with available phosphorus, nitrogen, and potassium increasing by 86.8%, 64.9%, and 40.9%, respectively, compared to non-inoculated PSB. The effects of PSB on soil available nutrients were modulated by soil properties, PSB and crop types. Acidic and high SOM soil, \u003cem\u003eBacillus\u003c/em\u003e, and \u003cem\u003eSolanaceae\u003c/em\u003e crops significantly increased available phosphorus. Notably, high SOM soil, \u003cem\u003eEnterobacter\u003c/em\u003e, and \u003cem\u003eFabaceae\u003c/em\u003e crops exhibited the highest efficacy on enhancing available nitrogen, while \u003cem\u003eBacillus\u003c/em\u003e significantly increased available potassium. In conclusion, strategic selection of PSB, crop, and soil types can optimize the activation efficiency of soil phosphorus, nitrogen, and potassium, hence improving the availability of nutrients in the soil. This is essential for building an efficient PSB fertilizer application technology system and reducing fertilizer consumption to promote green and sustainable agricultural development.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eCRediT authorship contribution statement\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eYan Jia: Writing \u0026ndash; original draft, Visualization, Formal analysis, Data curation. Xiaobin Li: Formal analysis, Data curation. Yuanpeng Zhu: Formal analysis, Data curation. Jingyang Ma: Formal analysis, Data curation. Xing Fan: Formal analysis, Data curation. Peishen Du: Formal analysis, Data curation. Ronghao Liu: Writing \u0026ndash; review \u0026amp; editing, Visualization, Funding acquisition, Data curation, Conceptualization.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of competing interest\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\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\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData will be made available on request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was funded by the Key Research and Development Program Young Scientist Project (2023YFD1901900), the Natural Science Foundation of Shanxi province (202203021211139), the Inner Mongolia Ordos City Science and Technology Program, and Research and Promotion Project of Water Conservancy Science and Technology in Shanxi Province (2025GM15).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAmeen F, AlYahya SA, AlNadhari S, Alasmari H, Alhoshani F, Wainwright M (2019) Phosphate solubilizing bacteria and fungi in desert soils: species, limitations and mechanisms. 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Theor Appl Genet\u003cem\u003e \u003c/em\u003e133: 1365-1384.\u003c/li\u003e\n\u003cli\u003eZhao ZX, Wang XY, Tian YJ, Wang R, Peng Q, Cai HJ (2022) Effects of straw returning on soil ammonia volatilization under different production conditions based on meta-analysis. Environ Sci 43: 1678-1687.\u003c/li\u003e\n\u003cli\u003eZheng BX, Hao XL, Ding K, Zhou GW, Chen QL, Zhang JB, Zhu YG (2017) Long-term nitrogen fertilization decreased the abundance of inorganic phosphate solubilizing bacteria in an alkaline soil. Sci Rep-Uk \u003cstrong\u003e7\u003c/strong\u003e: 42284.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"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":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Phosphorus solubilizing bacteria, Rhizosphere enhancing bacteria, Phosphorus solubilization mechanism, Soil nutrient availability, Meta-analysis","lastPublishedDoi":"10.21203/rs.3.rs-7033664/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7033664/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground and aims\u003c/h2\u003e\u003cp\u003eThe available phosphorus, nitrogen, and potassium concentrations in soil collectively serve as key indicators of soil fertility levels. Comprehending the effects of phosphorus solubilizing bacteria (PSB) on expeditious content levels is crucial for enhancing soil fertility and advancing sustainable agricultural development.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eUsing a meta-analysis method, this study systematically evaluated the effects of different factors, including soil pH, soil organic matter (SOM), PSB and crop types, on the changes in soil available nutrients (i.e., available phosphorus, nitrogen, and potassium) induced by PSB inoculation.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003ePSB inoculation significantly increased soil available phosphorus (86.8%), nitrogen (64.9%), and potassium (41.9%) compared to non-inoculated controls. Subgroup analyses revealed that soil pH, SOM, PSB and crop types significantly modulated PSB-mediated augmentation in soil available phosphorus. SOM, PSB and crop types considerably affected PSB augmentation of soil available nitrogen. Meanwhile, PSB types notably impacted the increase of soil available potassium by PSB. Further analysis showed a significant negative correlation between soil pH and the ability of PSB to enhance soil available phosphorus, whereas SOM was significantly positively correlated with PSB to enhance soil available phosphorus and nitrogen.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003eThese findings highlight the need for comprehensive consideration of soil pH, SOM, PSB and crop types when applying PSB to improve soil nutrient availability, This study offers empirical evidence for the systematic and efficient utilization of PSB to improve soil nutrient availability.\u003c/p\u003e","manuscriptTitle":"Phosphorus Solubilizing Bacteria Regulate Soil Phosphorus Activation Mechanisms and Impact on Available Nutrients: A Meta-Analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-17 10:08:00","doi":"10.21203/rs.3.rs-7033664/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"c40bdf09-52ab-4ab7-8b59-518ade2e915e","owner":[],"postedDate":"July 17th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-09-28T07:54:36+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-17 10:08:00","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7033664","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7033664","identity":"rs-7033664","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}