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Article

Soil pH and Nutrient Stoichiometry as Key Drivers of Phosphorus Availability in Crop Rotation Systems

by
Yi Yuan
1,
Yi Zhu
1,
Yichen Zhao
1,
Meng Wang
1,
Zhaoming Qu
1,
Dongqing Lv
1,
Yanli Liu
1,
Yan Song
2,
Tingting Wang
2,
Chengliang Li
1 and
Haojie Feng
1,*
1
National Engineering Research Center for Efficient Utilization of Soil and Fertilizer Resources, College of Resources and Environment, Shandong Agricultural University, Taian 271018, China
2
Stanley Agriculture Group Co., Ltd., Linyi 276700, China
*
Author to whom correspondence should be addressed.
Agronomy 2025, 15(5), 1023; https://doi.org/10.3390/agronomy15051023
Submission received: 21 March 2025 / Revised: 17 April 2025 / Accepted: 22 April 2025 / Published: 24 April 2025
(This article belongs to the Section Innovative Cropping Systems)
Browse Figures
Versions Notes

Abstract

:
Crop rotation systems profoundly influence soil phosphorus (P) dynamics through physicochemical and microbial interactions. The mechanisms regulating P availability under various rotational practices remain poorly understood. This five-year field experiment investigated the effects of four rotation systems (WM: wheat–maize; WP: wheat–peanut; WS: wheat–soybean; MV: maize–hairy vetch) on soil P fractions, phosphatase activities, P-cycling gene abundance, and their interactions with soil properties. The WM rotation substantially reduced soil pH (6.29) while increasing labile P fractions (Ca2-P) and moderately labile P (Al-P, Fe-P, and Ca8-P), which was attributed to enhanced acid phosphatase activity. The WP rotation elevated soil pH (8.13) but reduced P availability due to calcium–P immobilization. The MV rotation stimulated microbial P cycling, exhibiting the highest phoD (2.01 × 106 copies g−1) and phnK (33,140 copies g−1) gene abundance, which was linked to green manure-induced microbial activation. Redundancy analysis identified soil pH, total nitrogen, and stoichiometric ratios (C/N and N/P) as key shared drivers of P fractions and enzymatic activity. Partial least squares path modeling (PLS–PM) indicated that crop rotation directly regulated P availability through pH modulation (r = −0.559 ***) and the C/N ratio (r = 0.343 ***) while indirectly regulating P fractions through phosphatase activity. Lower C/N ratios (<10) across all rotation regimes amplified the carbon limitation in the process of P transformation, indicating that exogenous carbon inputs and appropriate stoichiometry in the soil should be optimized. The results of this study inform the selection of suitable crop rotation patterns for sustainable agriculture.

1. Introduction

Phosphorus (P), a macronutrient essential for plant growth, plays a pivotal role in sustaining agricultural ecosystem productivity and biogeochemical cycling [1,2]. However, its bioavailability in soil systems is constrained by geochemical precipitation, colloidal adsorption, and microbial immobilization processes [3,4,5], resulting in limited accessibility for plant uptake [6]. The soil P pool comprises both inorganic and organic fractions, with inorganic P speciation serving as a critical indicator of soil fertility status [7]. Based on plant availability characteristics, inorganic P forms exhibit distinct bioavailability: calcium-bound labile P (Ca2-P) represents the immediately available fraction, whereas slow-release pools include moderately available forms (Ca8-P, Al-P, and Fe-P). The recalcitrant fractions (Ca10-P, O-P) constitute stable P reservoirs that are virtually inaccessible to plants [8,9,10]. This hierarchical availability underscores the need to elucidate P transformation mechanisms to improve soil P utilization efficiency.
The biogeochemical cycling of soil P represents a fundamental ecosystem process regulating agroecosystem sustainability, mediated through synergistic interactions between phosphatase enzymes and functional microbial genes [11]. Soil microbiotas enhance P availability by two mechanisms: organic acid-mediated solubilization of mineral P and enzymatic mineralization of organic P compounds [12]. Key functional genes, including phoD (governing alkaline phosphatase production) and pqqC (involved in pyrroloquinoline quinone biosynthesis for P solubilization), are critical molecular determinants of these processes [13,14]. Emerging evidence suggests a strong environmental regulation of P cycle gene expression, with soil physicochemical properties exerting a predominant control [15]. Empirical studies have demonstrated spatial heterogeneity in gene–environment interactions; phoD and pqqC abundance in eastern Chinese soils is strongly correlated with the available P content [13], whereas soil organic carbon (SOC) and total nitrogen (TN) have emerged as key predictors in other pedoenvironments [16].
Crop rotation is an essential agronomic practice for sustaining agricultural productivity and preserving soil fertility. Diversified rotational systems effectively maintain soil health and security by optimizing nutrient budgets and suppressing pathogen proliferation [17,18,19]. Unlike continuous monoculture systems, diversified crop rotation regimes mediate soil biochemical modifications through differential residue returning [20,21], while simultaneously modulating microbial functionality via root-derived substrates, particularly shaping P-cycling microbiota [10]. Leguminous rotations enhance Olsen-P content, whereas corn–soybean rotations substantially improve P bioavailability and agricultural sustainability [13,22,23]. Furthermore, the differential decomposition rates of crop residues and root exudates under various rotations directly alter soil pH and SOC content, thereby influencing P adsorption–desorption dynamics and mineralization processes [24,25]. However, critical knowledge gaps persist regarding how crop rotation systems regulate soil P dynamics through coupled physicochemical and biological processes.
The purpose of this research was to (1) examine the effects of various crop rotations on P fractions, phosphatase activities, and P-cycling gene abundance and (2) elucidate the mechanisms by which crop rotation influences soil P availability through complex interactions between biotic and abiotic factors. We hypothesized that green manure rotation would stimulate the transformation of P forms by enhancing phosphatase activity and increasing the abundance of P-cycling gene, thereby improving the availability of P in the soil.

2. Materials and Methods

2.1. Study Site

A prolonged field study commenced at the Mazhuang Experimental Station (35°59′ N, 117°00′ E), located in Taian City, Shandong Province, China. The study area is characterized by a warm, temperate, semi-humid, monsoon climate, with a mean annual temperature of 12.8 °C and mean annual precipitation of 720–750 mm, predominantly occurring between June and September. The experimental soil was classified as Typical Brown Soil according to the Chinese Soil Taxonomy and as Typic Spodosols under the United States Department of Agriculture Soil Taxonomy system. Initial soil properties in the 0–20 cm layer revealed the following characteristics: pH 7.28, SOC 10.2 g kg−1, TN 0.92 g kg−1, Olsen P 35.4 mg kg−1, and available K 210 mg kg−1.

2.2. Experimental Design and Soil Sampling

The crop rotation regime experiment began in 2019 and included the following four cropping rotations: wheat–maize (WM), wheat–peanut (WP), wheat–soybean (WS) and maize–hairy vetch (MV) rotations. The experiment was conducted using a randomized complete block design and was repeated three times. Each plot was 668 m2 (33.4 m × 20.0 m). Fertilization regimes differed in the rotation systems. For WM, WP, and WS rotations, chemical fertilizers were applied at 225 kg N ha−1, 225 kg P2O5 ha−1, and 225 kg K2O ha−1, respectively. Of the total amount, 80% was applied as a basal application and 20% as top-dressing. The MV system received 112.5 kg N ha−1, 112.5 kg P2O5 ha−1, and 112.5 kg K2O ha−1 of chemical fertilizers during maize cultivation, whereas hairy vetch biomass was incorporated as green manure. Post-harvest management included the direct incorporation of wheat, maize, peanut, and soybean residues into the plow layer. Lime amendment (150 kg ha−1) was applied in the WP treatment to meet calcium requirements for peanut growth. Sowing variety and other field management practices were consistent with local practices. Soil sampling was conducted in May 2023, following the crop harvest. Composite samples (0–20 cm depth) were obtained from each plot using a five-point sampling strategy with a soil core sampler. The samples were homogenized to create one representative sample per plot and promptly transported to the laboratory for analysis.

2.3. Analysis of Soil Physicochemical Properties

Soil pH was determined potentiometrically in a 1:5 (w/v) soil–water suspension. Soil electrical conductivity (EC) was measured in the same suspension using a conductivity meter. Soil organic carbon (SOC) and total nitrogen (TN) were quantified with an elemental analyzer (Elementar, Langenselbold, Germany). Total phosphorus (TP) was determined via molybdenum blue colorimetry following H2SO4-HClO4 digestion. Olsen phosphorus (Olsen-P) was extracted using 0.5 M NaHCO3 and measured by molybdenum antimony colorimetry [26]. Available potassium (AK) was analyzed through ammonium acetate extraction-flame photometry [27].

2.4. Analysis of Soil P Fractions and Soil Phosphatase Activity

Inorganic P fractions were sequentially extracted following standard fractionation procedures [27,28], which involved the separation of six distinct inorganic P fractions. In summary, these P fractions were extracted stepwise using the following reagents: 0.25 M NaHCO3 (Ca2-P), 0.5 M NH4OAC (Ca8-P), 0.5 M NH4F (Al-P), 0.1 M NaOH + 0.1 M Na2CO3 (Fe-P), 0.3 M Na3C6H5O7 + Na2S2O3 + 0.5 M NaOH (Occluded P, O-P) and 0.25 M H2SO4 (Ca10-P). Concurrently, the activities of acid phosphatase (ACP) and alkaline phosphatase (ALP) were determined as described by Wei [29]. Briefly, ACP and ALP were assayed using p-nitrophenyl phosphate as the substrate with a modified universal buffer at pH 6.5 and 11.0. The colorimetric measurements were taken at 410 nm and 510 nm, respectively. Phosphatase activities were expressed as mg p-nitrophenol kg−1 soil h−1.

2.5. Soil DNA Extraction and Quantitative Polymerase Chain Reaction (PCR) of P Functional Genes

Genomic DNA was extracted from fresh soil (0.5 g) using an OMEGA Soil DNA Kit (D5625-01; Omega Bio-Tek, Norcross, GA, USA). DNA purity and concentration were verified using a NanoDrop 2000 spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA) and agarose gel electrophoresis. Quantitative PCR was performed to determine the gene copy numbers of phoD, phnK, and pqqC using specific primer sets: phoD733F (5′-TGGGAYGATCAYGARGT-3′)/phoD1083R (5′-GAGGCCGATCGGCATGTCG-3′) for phoD, phnKF (5′-CTGSGCSAKSACRTTCCA-3′)/phnKR (5′-GCTGTTGTCGTTGATGTCC-3′) for phnK, pqqCF (5′-CATGGCATCGAGCATGCTCC-3′)/pqqCR (5′-CAGGGCTGGGTCGCCAACC-3′) for pqqC.

2.6. Data Analysis

Data were analyzed using one-way analysis of variance with SPSS (version 26.0; SPSS, Inc., Chicago, IL, USA), and the means were compared using the least significant difference (LSD) and Duncan’s tests (at p < 0.05). Regression analyses and boxplots were generated using the “ggplot2” package in R. Redundancy analysis (RDA) was using with the “vegan” package. Random forest modeling was conducted using the ‘randomForest’ package with parameter optimization (ntree = 500). A partial least squares path model (PLS–PM) analysis was conducted to investigate the effects of the crop rotation patterns on pH, stoichiometric ratios, phosphatase activity, and labile P fractions. The figures were plotted using the Origin Pro software (version 2021; Origin Lab, Inc., Northampton, MA, USA).

3. Results

3.1. Soil Physicochemical Properties

Various crop rotation patterns were shown to strongly influence the soil physicochemical properties over the 5 y experiment (Table 1). The lowest pH was observed in the WM treatment (6.29), whereas the highest value was recorded in the WP treatment (8.13). Soil electrical conductivity (EC) was substantially higher in the WS and WP treatments than in the WM and MV treatments. The highest soil organic carbon (SOC) value was recorded in the WM treatment, whereas the highest total nitrogen (TN) value was recorded in the WS treatment. The concentrations of total P (TP), total inorganic P (Pi), and total organic P (Po) followed the order: WM > MV > WS ≈ WP (p < 0.05). The Olsen-P content varied between treatments (p < 0.05), with the highest concentration in WM of 81.59 mg/kg, followed by MV, WS, and WP. The MV treatment had the highest carbon-to-phosphorus (C/P) ratio, followed by WM, WS, and WP. The C/N ratio followed a descending order in WM > MV > WP > WS, whereas the N/P ratios exhibited an inversely proportional relationship across treatments.

3.2. The Content and Relative Proportions of Inorganic P Fractions

The content of Ca2-P was the highest in WM (65.2 mg kg−1), representing an increase of 19.9% to 59.8% compared to MV, WP, and WS (P < 0.05; Figure 1a,b). The relative proportion of Ca2-P was 6.70–9.86%. Moderate labile P was the highest of the three fractions, accounting for 51.5–61.6% of the inorganic P fraction, whereas Ca8-P was the most abundant, at 40.1–44.1% of moderate labile P (Figure 1b). The concentrations of Ca8-P, Fe-P, and Al-P followed similar trends in the order: WM > MV > WS > WP. The highest levels of stable P were observed in WM and MV at 198.5 mg kg−1 and 194.2 mg kg−1, respectively, which were greater than the values for WP and WS (p < 0.05). Random forest modeling identified Al-P as the predominant predictor of Olsen-P, followed sequentially by Ca2-P, Ca8-P, Ca10-P, and Fe-P in terms of predictive importance (Figure 1c).

3.3. Soil Enzyme Activities and the Abundance of P-Cycling Genes

Soil acid phosphatase activity peaked at 140.5 mg kg−1 h−1 under WM management, representing 12.9–47.4% enhancements over other treatments (Figure 2a). Alkaline phosphatase activity was comparable between the WM and MV treatments, both maintaining 36.7–39.8% higher activity than the WS and WP treatments (p < 0.05; Figure 2b). Gene abundance of organic P mineralization phoD (47,582.0 copies g−1) and P uptake and transport phnK (12,274 copies g−1) was minimal in the WM soils, in contrast to the MV soils, which were 42.3-fold and 2.7-fold higher, respectively (Figure 3). The abundance of the inorganic P solubilization pqqC gene decreased in the order of MV > WP > WS > WM, indicating differential microbial P solubilization potential across the rotation systems.

3.4. Relationships of P Fractions, Phosphatase Activities, P-Cycling Genes, and Soil Physicochemical Properties

Redundancy and Pearson’s correlation analyses revealed strong associations between soil physicochemical properties, P fractions, phosphatase activities, and functional gene profiles (Figure 4 and Figure 5). Redundancy analysis (RDA) indicated that soil physicochemical parameters accounted for 96.55%, 98.97%, and 95.87% of the total variance in P fractions, phosphatase activity, and P-cycling gene distributions, respectively (Figure 4). Soil pH, TN, C/N ratio, and N/P ratio emerged as the principal determinants driving the differentiation of P fractions, phosphatase activity, and P-cycling gene abundance, with all factors exhibiting strong explanatory power (p < 0.05). Correlation analysis indicated distinct interaction patterns; P-cycling gene abundance (phoD, pqqC, and phnK) was not associated with P fractions or phosphatase activities (p > 0.05), whereas enzymatic activities displayed strong positive correlations with all P fractions (r = 0.729 *–0.976 ***, Figure 5). Soil pH was negatively correlated with phosphatase activity (r = −0.945 *** to −0.716 *), Olsen-P (r = −0.691 *), and labile P fractions (Al-P: r = −0.691 *; Ca2-P: r = −0.757 **). The C/N ratio was positively correlated with phosphatase activity (r = 0.604 *–0.867 ***), Olsen-P (r = 0.944 ***), and labile P fractions (Al-P: r = 0.956 ***; Ca2-P: r = 0.927 ***).
The partial least squares path modeling (PLS–PM) elucidated the multivariate drivers of labile P fractions through soil physicochemical and biological environmental factors (Figure 6). The model indicated direct effects of the crop rotation system on soil pH (r = −0.721 **) and C/N ratio (r = 0.972 ***). Subsequent pathway analysis demonstrated that soil pH (r = −0.559 ***) exerted negative direct controls on soil P availability and C/N ratio (r = 0.343 ***) exerted positive direct controls on soil P availability. Soil pH and C/N ratio moderated the P fraction transformation by influencing enzymatic activity. Specifically, it was found to negatively regulate phosphatase activity, while the C/N ratio exhibited a positive regulatory effect on phosphatase activity. Multivariate decomposition of standardized effects indicated the hierarchical importance of the following predictors: crop rotation system > soil pH > C/N ratio > enzymatic activities (Figure 6b).

4. Discussion

4.1. Effects of Different Crop Rotation Systems on Soil P Fractions

The regulation of soil P bioavailability represents a critical challenge in agriculture because crop rotation systems exert substantial control over soil P fractions. This 5 y field observation indicated distinct P fractionation patterns across different rotational regimes, with TP content following the hierarchy: WM > MV > WS ≈ WP (Table 1). This suggests a smaller soil P surplus in WS and WP under equivalent P fertilizer input conditions (225 kg ha−1 P2O5). Legume crops have a higher P utilization rate than other crops, which can be attributed to the rhizosphere acidification and carboxylate exudation associated with legume cultivation [30,31,32]. This led to a reduced amount of residual P in the soil at the conclusion of crop production, as well as a lower TP content in WS and WP compared to the WM crop rotation.
Compared to the WS and WP treatments, the contents of soil labile P and moderately labile P in the WM treatment increased by 56.7–59.4% and 35.0–40.9%, respectively (Figure 1). The observed increase in soil labile P fractions in the WM treatment was directly associated with the lowest pH value. Low pH conditions can facilitate the desorption of Fe/Al-bound P and the dissolution of calcium phosphate, thereby enhancing the bioavailability of P in the soil [33]. MV had the second highest concentrations of Po, Ca2-P, Ca8-P, Al-P, and Fe-P (p < 0.05). This observation may be attributed to the incorporation of green manure, which appears to stimulate enzymatic mineralization processes through rhizodeposit-mediated microbial activation [34,35,36]. Additionally, the MV treatment resulted in the highest abundance of P-cycling genes (phoD, pqqC, and phnK) and elevated phosphatase activity, further supporting this conclusion.

4.2. Response of P-Cycling Process to Crop Rotation Regimes

The P transformation process in agricultural systems is governed by coupled physicochemical and biological processes. The current study identified pH gradients, nutrient stoichiometry, and enzymatic activity as the hierarchical controls. Previous studies have identified a remarkable correlation between the abundance of phosphorus cycling genes and phosphatase activity [37,38]. However, we observed decoupled relationships between the abundance of P-cycling genes (phoD, phnK, pqqC) and enzymatic activity, particularly in the WM system, which exhibited maximal phosphatase activity with minimal gene copies. This result can be attributed to the external available P content (81.59 mg kg−1) under WM treatment, which led to a marked decrease in the relative abundance of genes associated with inorganic P-solubilization and organic P-mineralization [39,40].
The current study shows that crop rotation modulates soil P cycling processes by altering phosphatase activity through the regulation of soil environmental factors (Figure 6). Redundancy analysis (RDA) identified soil pH, TN, and stoichiometric ratios (C/N and N/P) as the key environmental drivers of phosphatase activity (Figure 4). These findings align with established theories that posit that alkaline phosphatase governs the mineralization of organic P into labile P, further confirming the pivotal regulatory roles of soil environmental factors, such as soil pH and the C/N ratio, in enzyme activity [41,42].
The WM treatment induced a slightly acidic soil environment (pH 6.29 ± 0.06). The enhanced acid phosphatase activity in this system likely elevated P availability via two mechanisms: (1) enzymatic mineralization of organic P and (2) dissolution of Ca-bound P and desorption of Fe/Al-bound P [43,44]. Conversely, the WP treatment, which involved lime disinfection, resulted in a significantly elevated soil pH (8.13 ± 0.01), leading to markedly reduced concentrations of available P compared to other treatments (p < 0.05). This pH-dependent pattern of P availability suggests that excessive alkalization induced by lime application may trigger P immobilization through Ca-P co-precipitation, a phenomenon consistent with classical theories of P speciation dynamics in calcareous soils [45].
Soil C: N: P stoichiometry directly affects phosphatase activity by regulating microbial nutrient limitation and enzyme production, which play pivotal roles in soil phosphorus cycling and microbial processes [46]. Moderate C/N (15–25:1), C/P (100–150:1), and N/P (10–15:1) ratios optimize microbial community function, promoting P mineralization, and increasing the available P supply for plant uptake [41,47]. The current study indicates that acid phosphatase activity and alkaline phosphatase activity are significantly influenced by C/N ratio (p < 0.05; Figure 5), indicating that the C/N ratio serves as key regulators of enzyme-mediated P transformation processes. Compared to the WS treatment, the MV treatment exhibited a more moderate C/N ratio, which accounted for the higher levels of soil phosphatase, P-cycling genes, and P availability under similar pH conditions. However, the results of this study indicate substantially lower C/N ratio (5.6–10.2) in all treatments compared to typical agricultural soils, indicating N sufficiency and carbon limitation (C/N < 10). Nevertheless, excessive N nutrient accumulation in the soil can suppress phosphatase activity, leading to decreased P availability [48].

5. Conclusions

This 5 y rotation study demonstrated that crop rotation systems regulate soil P bioavailability through synergistic physicochemical and microbial mechanisms, with soil pH and stoichiometric balance emerging as pivotal control factors. WM rotation substantially enhanced the labile P (Ca2-P) and moderately labile P (Ca8-P, Al-P, Fe-P) fractions by creating a mildly acidic environment (pH 6.29), which promoted acid phosphatase activity and facilitated organic P mineralization. Conversely, WP rotation elevated the soil pH to 8.13, inducing Ca-P precipitation and reducing labile P content by 35.1% compared to WM, highlighting pH as the primary driver of P speciation. The MV rotation optimized microbial P cycling through balanced C/N ratio under similar pH conditions, stimulating phosphatase activity and amplifying phoD gene abundance (2.01 × 106 copies g−1) via green manure-driven microbial activation. The WM treatment exhibited functional decoupling between phosphatase activity and P-cycling gene abundance under high Olsen-P conditions (>80 mg kg−1), indicating potential functional redundancy in soil P-cycling networks and highlighting microbial metabolic plasticity under P-replete conditions. Excessively low stoichiometry (C/N < 10) under WS and WP rotations exacerbated carbon limitation, suppressing phosphatase-mediated P solubilization, despite nutrient sufficiency. Overall, MV treatment demonstrates a more effective rotation method for enhancing soil phosphorus availability and promoting sustainable agriculture compared to other rotation types. Future research should thoroughly consider the phosphorus absorption preferences of various crops, conduct in-depth studies on how crop rotation systems influence the distribution and availability of soil P from a holistic soil–plant perspective, and further enhance our understanding of the phosphorus cycle within agricultural ecosystems.

Author Contributions

H.F. designed this research; Y.Z. (Yi Zhu), Y.Z. (Yichen Zhao), M.W., Z.Q. and D.L. performed test data analysis; Y.S. and T.W. managed the experimental field; Y.Y. wrote the paper; H.F., C.L. and Y.L. reviewed and commented on the draft. All authors have read and agreed to the published version of the manuscript.

Funding

This research was supported by Shandong Province Key Scientific and Technological Innovation Projects Program (2022SFGC0302 and 2021CXGC010801).

Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Acknowledgments

Our gratitude extends to the editors and anonymous reviewers for their insightful feedback and recommendations in enhancing our manuscript.

Conflicts of Interest

Authors Yan Song and Tingting Wang were employed by the company Stanley Agriculture Group Co., Ltd. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Figure 1. The inorganic P fractions in soil under different crop rotation regimes (a); the proportion of different inorganic P components to total inorganic P (b); random forest analysis indicating of P fractions on Olsen-P under various crop rotation (c). Note: WM, wheat–maize; WP, wheat–peanut; WS, wheat–soybean; MV, maize–hairy vetch. MSE, mean squared error. Lines at the top of the columns represent standard deviation. * was represented the significant level (p < 0.05). Different letters on the column (a, b, c, d) indicate significant differences (p < 0.05) between different treatments on the same Pi fractions.
Figure 1. The inorganic P fractions in soil under different crop rotation regimes (a); the proportion of different inorganic P components to total inorganic P (b); random forest analysis indicating of P fractions on Olsen-P under various crop rotation (c). Note: WM, wheat–maize; WP, wheat–peanut; WS, wheat–soybean; MV, maize–hairy vetch. MSE, mean squared error. Lines at the top of the columns represent standard deviation. * was represented the significant level (p < 0.05). Different letters on the column (a, b, c, d) indicate significant differences (p < 0.05) between different treatments on the same Pi fractions.
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Figure 2. Effects of different crop rotation on soil acid phosphatase (a) and alkaline phosphatase activities (b). Note: Lines at the top of the columns represent standard deviation. Differences marked by lowercase letters are statistically significant (p < 0.05).
Figure 2. Effects of different crop rotation on soil acid phosphatase (a) and alkaline phosphatase activities (b). Note: Lines at the top of the columns represent standard deviation. Differences marked by lowercase letters are statistically significant (p < 0.05).
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Figure 3. The gene abundance of phoD, pqqC, and phnK in different crop rotation regimes. Note: Different lowercase letters indicate significant differences (p < 0.05).
Figure 3. The gene abundance of phoD, pqqC, and phnK in different crop rotation regimes. Note: Different lowercase letters indicate significant differences (p < 0.05).
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Figure 4. Redundancy analysis (RDA) of inorganic P fractions (a), phosphatase activities (b), and P-cycling gene abundances as explained by soil physicochemical properties (c). Note: The significant levels were *** p ≤ 0.001, ** 0.001 < p ≤ 0.01, * 0.01 < p < 0.05.
Figure 4. Redundancy analysis (RDA) of inorganic P fractions (a), phosphatase activities (b), and P-cycling gene abundances as explained by soil physicochemical properties (c). Note: The significant levels were *** p ≤ 0.001, ** 0.001 < p ≤ 0.01, * 0.01 < p < 0.05.
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Figure 5. Relationships between the pH, nutrient stoichiometric and P availability under different crop rotation systems. Note: ACP, acid phosphatase activities; ALP, alkaline phosphatase activities. Red indicates positive correlation; blue indicates negative correlation. *, ** and *** were represented p ≤ 0.001, 0.001 < p ≤ 0.01, and 0.01 < p < 0.05, respectively.
Figure 5. Relationships between the pH, nutrient stoichiometric and P availability under different crop rotation systems. Note: ACP, acid phosphatase activities; ALP, alkaline phosphatase activities. Red indicates positive correlation; blue indicates negative correlation. *, ** and *** were represented p ≤ 0.001, 0.001 < p ≤ 0.01, and 0.01 < p < 0.05, respectively.
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Figure 6. Partial least squares path modeling (PLS–PM) for crop rotation, pH, C/N, phosphatase activities, and labile P fractions (a) and the total standardized effects of crop rotation, pH, C/N, and phosphatase activities on labile P fractions derived from the PLS–PM used above (b). Note: The red and blue lines represent positive and negative pathways, respectively. The width of the arrows indicates the strength of path coefficients. The model utilized the goodness of fit statistic (GOF = 0.896). Levels of significance: *** p ≤ 0.001, ** 0.001 < p ≤ 0.01.
Figure 6. Partial least squares path modeling (PLS–PM) for crop rotation, pH, C/N, phosphatase activities, and labile P fractions (a) and the total standardized effects of crop rotation, pH, C/N, and phosphatase activities on labile P fractions derived from the PLS–PM used above (b). Note: The red and blue lines represent positive and negative pathways, respectively. The width of the arrows indicates the strength of path coefficients. The model utilized the goodness of fit statistic (GOF = 0.896). Levels of significance: *** p ≤ 0.001, ** 0.001 < p ≤ 0.01.
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Table 1. Basic physical and chemical properties of soil with different crop rotation regimes.
Table 1. Basic physical and chemical properties of soil with different crop rotation regimes.
Soil PropertiesCrop Rotation Regimes
WM WP WSMV
pH6.29c8.13a7.19b7.14b
EC (μS cm−1)162.8c330.6a292.4a178.6b
SOC (g kg−1)16.8a10.1d11.6c14.3b
Total N (g kg−1)1.64b1.35d2.08a1.52c
Total P (g kg−1)1.09a0.72c0.73c0.95b
Olsen-P (mg kg−1)81.6a32.9d43.5c59.7b
Pi (g kg−1)0.66a0.44c0.43c0.62b
Po (g kg−1)0.43a0.28c0.30bc0.33b
C/N10.24a7.48c5.57d9.41b
C/P39.3ab36.0b39.0ab42.9a
N/P3.83c4.81b7.01a4.55b
Note: WM, wheat–maize; WP, wheat–peanut; WS, wheat–soybean; MV, maize–hairy vetch; SOC, soil organic carbon; Total N, total nitrogen; Total P, total phosphorus; Pi, inorganic phosphorus; Po, organic phosphorus; C/N, the ratio of SOC to total N; C/P, the ratio of SOC to Po; N/P, the ratio of Total N to Po. Different lowercase letters indicate significant differences between treatments at p < 0.05.
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MDPI and ACS Style

Yuan, Y.; Zhu, Y.; Zhao, Y.; Wang, M.; Qu, Z.; Lv, D.; Liu, Y.; Song, Y.; Wang, T.; Li, C.; et al. Soil pH and Nutrient Stoichiometry as Key Drivers of Phosphorus Availability in Crop Rotation Systems. Agronomy 2025, 15, 1023. https://doi.org/10.3390/agronomy15051023

AMA Style

Yuan Y, Zhu Y, Zhao Y, Wang M, Qu Z, Lv D, Liu Y, Song Y, Wang T, Li C, et al. Soil pH and Nutrient Stoichiometry as Key Drivers of Phosphorus Availability in Crop Rotation Systems. Agronomy. 2025; 15(5):1023. https://doi.org/10.3390/agronomy15051023

Chicago/Turabian Style

Yuan, Yi, Yi Zhu, Yichen Zhao, Meng Wang, Zhaoming Qu, Dongqing Lv, Yanli Liu, Yan Song, Tingting Wang, Chengliang Li, and et al. 2025. "Soil pH and Nutrient Stoichiometry as Key Drivers of Phosphorus Availability in Crop Rotation Systems" Agronomy 15, no. 5: 1023. https://doi.org/10.3390/agronomy15051023

APA Style

Yuan, Y., Zhu, Y., Zhao, Y., Wang, M., Qu, Z., Lv, D., Liu, Y., Song, Y., Wang, T., Li, C., & Feng, H. (2025). Soil pH and Nutrient Stoichiometry as Key Drivers of Phosphorus Availability in Crop Rotation Systems. Agronomy, 15(5), 1023. https://doi.org/10.3390/agronomy15051023

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