Effect of forest conversion to tea plantations on soil aggregate stability and its stoichiometry of carbon, nitrogen and phosphorus

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However, the interactive effects of land management (LM) and plantation age (PA) on soil aggregate stability and C:N:P balance following forest-to-tea conversion remain poorly understood. Methods We investigated aggregate-associated nutrients in sloping (ST) and terraced (TT) tea plantations across a chronosequence (40 years), with adjacent natural forest (NF) as a reference. Results Forest-to-tea conversion significantly reduced the proportion of >2 mm aggregate, with terraced plantations at both TT 40 showing reductions of 16.7% and 17.5%, respectively, compared to NF. Aggregate stability (MWD and GMD) was strongly governed by the interaction between LM and PA. Among all treatments, ST >40 exhibited the highest aggregate stability, coinciding with its high root biomass and proportion of 2-1 mm macroaggregates. Aggregate-associated SOC and TN gradually recovered with PA, reaching levels comparable to NF in ST >40 and TT 20–40 . However, TP declined continuously with PA under both management practice, leading to increases in soil C:P and N:P ratios exceeding 140%, identifying P as the primary limiting nutrient. Path analysis revealed that aggregate stability was directly determined by aggregate-size distribution, with positive effects from 2-1 mm macroaggregates and negative effects from <0.25 mm microaggregates, while nutrient stoichiometry mediated indirect effects of management and age through microbial biomass and root inputs. Conclusion These findings highlight trade-offs between erosion control and nutrient management in tea plantations, emphasizing the need for age- and practice-specific strategies and P-mobilizing practices to address stoichiometric imbalances in intensively managed subtropical soils. Forest-to-tea conversion Soil aggregates Stoichiometry P-limitation Plantation age Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 1. Introduction Soil health is crucial for ecosystem sustainability and a critical component in addressing global challenges such as food security and climate change mitigation (Amundson et al., 2015). However, it is vulnerable to human disturbances, with land use change being a predominant driver (Guo & Gifford, 2002). In ecologically fragile hilly and mountainous regions, such as the Dabie Mountain area, the conflict between economic development and environmental protection is particularly prominent. Here, the widespread conversion of ecological forests to woody crops, driven by economic needs, has long-term ecological consequences for soil "micro-health" which remain poorly understood (de Blécourt et al., 2013). The integrity of soil micro-health hinges on the balance and cycling of core elements: carbon (C), nitrogen (N), and phosphorus (P) (Mao et al., 2020; Sardans et al., 2021). Their ecological stoichiometric ratios (C:N:P) serve as a master regulator of decomposition, nutrient cycling, and energy flow (Zhang, et al., 2021; Zheng et al., 2021; Rastetter et al., 2022). These biogeochemical processes are physically mediated by soil structure, particularly the distribution and stability of aggregates (Liu et al., 2010; Sarker et al., 2018). Soil aggregates are the key micro-structures that physically protect organic carbon and modulate nutrient accessibility. Therefore, the central question arising from forest conversion is: how does this transformation simultaneously alter the physical architecture (aggregate stability) and the biochemical balance (C:N:P stoichiometry) of the soil? Investigating their coupled response offers a mechanistic lens to understand soil degradation or resilience (Kan et al., 2023). While aggregates are recognized as primary nutrient reservoirs, predicting how carbon and nutrients are distributed among different aggregate sizes remains contentious. The classical aggregate hierarchy theory posits that concentrations of C, N, and P increase with aggregate size, as macroaggregates form around fresh organic matter(Blanco-Canqui & Lal, 2004; Gupta & Germida, 2015; Xiao et al., 2017). Conversely, a substantial body of research demonstrates that finer clay- and silt-sized fractions can exhibit higher nutrient concentrations due to the formation of stable organo-mineral complexes (von Lützow et al., 2007; J. R. Sarker et al., 2018). This fundamental contradiction highlights that aggregate-associated nutrient dynamics might be context-dependent, likely governed by factors such as soil type, vegetation, management practices, and time since land conversion(Tang et al., 2022; Kan et al., 2023). Among these contextual factors, land management practice and plantation age are paramount. Intensive land management practices, such as terracing, fundamentally alter soil disturbance and hydrological pathways compared to conventional slope cultivation. Terracing can help maintain aggregate stability. However, this effect might be affected by time (Wang et al., 2016; Yin et al., 2016; Zheng et al., 2023; Xue et al., 2024). The initial construction is often accompanied by intense soil disturbance, which could lead to a severe deterioration of soil structure and the loss of soil organic carbon in the short term. With the increase of management duration, erosion control function of terracing would promote the recovery of soil structure and nutrient balance. In contrast, slope cultivation causes sustained erosive forces, accelerating aggregate degradation and stoichiometric imbalances. Despite their importance, most research has focused on bulk soil properties or short-term responses (Zhu et al., 2018; Zhang et al., 2019a), neglecting how the interaction between management practice and plantation age drives the long-term evolution of nutrient storage within the soil aggregates. Tea plantations, a widespread perennial crop established on converted forest land in the Dabie Mountains, represent an ideal system to address this knowledge gap (Wang et al., 2020a; Xu et al., 2020). Intensive management practices, including periodic tillage, high rates of fertilization, and canopy pruning, impose distinct and persistent pressures on soil. Therefore, the objectives of this study were to: (1) characterize the evolution of soil aggregate stability and C:N:P stoichiometry across a chronosequence of terraced and sloped tea plantations; and (2) evaluate the key drivers and mechanisms through which plantation age (40 years) and management practices (slope vs. terrace) collectively regulate these properties. We hypothesize that the dynamics of soil aggregate stability and C:N:P stoichiometry are governed by the interaction between management practice and plantation age. Specifically, we expect that long-term slope cultivation will lead to a persistent decline in macro-aggregates and a divergence of C:N:P ratios from forest baselines. For terrace systems, we predicted an initial phase of degradation followed by long-term recovery in structure and nutrient balance, facilitated by erosion control. 2. Materials and methods 2.1 Study area and soil sampling The study was conducted in Jinzhai County, Anhui Province (115°22′-116°11′E, 31°06′-31°48′N), a major tea-producing region on the northern slope of the Dabie Mountains (Fig. 1). Covering a total area of 3,814 km², the terrain is characterized by high elevations in the south and lower elevations in the north, with slopes ranging from 8° to 15° and steep slopes from 15° to 25°. This region features a humid subtropical monsoon climate, with a mean annual precipitation of 1,389.6 mm and mean annual temperatures ranging from 15°C to 16.3°C. The predominant rock types are granite and granite gneiss, and the soils classified as Entisols, Ultisols and Alfisols, according to the U.S. Soil Taxonomy system (Hongda et al., 2022). The forest coverage rate is 74.1%. Native forests were dominated by Masson pine ( Pinus massoniana ) and Quercus acutissima (Rui-na et al., 2021). A field investigation was conducted in May 2023 on tea plantations with different land management practices (slope vs. terrace) and plantation ages (40 years). Therefore, 21 experimental sites (7 treatments × 3 replications) were employed (Table 1): ST 40 (sloping tea plantations older than 40 years), TT 40 (terraced tea plantations older than 40 years) and NF (natural forest) as control. Three subplots (10 m × 10 m) were set up at each site and a totally of 63 samples were collected. The study area is located in a typical rocky mountainous region, characterized by shallow soil layers (Zhang et al., 2013). To determine the sampling depth, we observed the soil profiles and found that the soil layer below 20 cm contains high gravel content, making it difficult to sample. Besides, considering that the surface soil is the layer most strongly affected by woody crop cultivation activities, we selected 0–20 cm layer for sampling. Mixed soil samples were collected using a stainless-steel auger, which were stored in plastic bags before being transported to the laboratory for analysis. Undisturbed soil samples were collected for soil aggregate analysis. The sampling strategy was consistent across sites with similar aspects, slopes and altitudes, although some site conditions varied slightly due to the practical limitation of finding locations with identical conditions in the field (Fig. 1). 2.2 Litter and root sampling Litter characteristics were assessed using three randomly established 1 m × 1 m quadrats per plot. Litter cover was visually estimated as the percentage of soil surface covered by dead organic debris (De Stefano et al., 2021). Litter thickness was measured with a ruler to an accuracy of 0.5 mm. For root trait analysis, soil cores were collected using a cylindrical auger (5.3 cm height × 5.0 cm diameter). Roots were separated from the soil using a 5 mm mesh sieve and then gently washed in water-filled basins to remove soil particles and debris. Root morphology was analyzed using the WinRHIZO root analysis system. Parameters including root length density (RLD; mm (100 cm 3 ) –1 ), root surface area (RSA; cm²) and root volume (RV; cm³) were measured. Finally, roots were oven-dried at 75 °C for 48 hours and weighed to determine root biomass (RB) (Liu et al., 2020). 2.3 Aggregate fractionation and stability analysis The undisturbed air-dried soils were fractionated with dry-sieving (2, 1, 0.5, 0.25 mm sieves) method using a mechanical shaker (60 oscillations/min, 2 min). Soil retained on each sieve was collected and weighed to calculate the mass fraction of each size class. The nutrient content of each aggregate fraction, including organic carbon, total nitrogen, and total phosphorus, was then determined. Soil aggregate stability was evaluated through: (1) mean weight diameter (MWD), (2) geometric mean diameter (GMD), and (3) the mass fraction of aggregates >0.25 mm (R >0.25 ), calculated according to standard equations (1-3) (Amézketa, 1999; Nimmo & Perkins, 2002): Where x i (mm) is the mean diameter of each aggregate size, w i (%) is the mass percentage of i -sized aggregates, m 0.25 (mm), and m t (g) is the total soil mass. The dry-sieving method was used as it retains labile nutrients more effectively than wet sieving. Wet sieving can cause loss of water-soluble C and N, disrupt microbial habitats, and underestimate nutrient pools in soil aggregates (Sainju, 2006; Sarkhot et al., 2007; Felde et al., 2021).This method is particularly suitable for coarse-textured subtropical soils, such as those in the present study (Table 2), which are characterized by low clay contents (<10%) and weak aggregation (Bruand et al., 2005; Sun et al., 2024). Additionally, dry-sieving is easier to perform and provides a reliable assessment of how land management and plantation age influence nutrient distribution within the soil aggregate in the long-term (Xu et al., 2017). 2.4 Soil properties analysis Mixed soil samples were air dried and passed 2 mm and 0.25 mm sieves, respectively, for chemical properties analysis. Soil organic carbon (SOC) and total nitrogen (TN) were measured by Vario Macro Cube elemental analyzer (Elementar Trading Shanghai, China). Total phosphorus (TP) was determined using the molybdenum blue colorimetric method. Soil pH was measured in a (soil-to-water: 1:2.5) suspension using a calibrated pH meter. We determined cation exchange capacity (CEC) through ammonium acetate extraction followed by HCl titration. Available phosphorus (AP) was extracted using 0.5M NaHCO 3 and quantified via molybdenum blue colorimetry. Available potassium (AK) was extracted with 1M ammonium acetate and analyzed by flame photometry. Available nitrogen (AN) was measured using alkaline hydrolysis (Rayment & Lyons, 2011). Microbial biomass carbon (MBC) and nitrogen (MBN) were analyzed following the chloroform fumigation-extraction protocol (Vance et al., 1987). Soil texture was measured with Microtrac S3500 laser particle size analyzer (Microtrac Inc., USA) (Šinkovičová et al., 2017). 2.5 Statistical analysis All statistical analyses were performed using SPSS 26.0 (https://www.ibm.com/analytics/spss-statistics-software). Data normality (Shapiro-Wilk) and homogeneity (Levene’s test) were tested prior to conducting analysis of variance (ANOVA). One-way ANOVA followed by Tukey’s HSD test (α = 0.05) was applied to compare across the seven treatments, and across the aggregate fractions within each treatment. Pearson's correlation analysis was employed to evaluate the relationships between various indicators. Partial Least Squares Path Modeling (PLS-PM) was conducted using the “plspm” package in R to identify the primary pathways from predictor variables to response variables (Li et al., 2023). The overall model quality and performance were assessed using the goodness-of-fit (GOF) index. To evaluate the stability and significance of the path coefficients, 1,000 bootstrap were performed (Chen et al., 2024). The general linear model (GLM) was employed to determine the variation in soil properties explained by land management and plantation age. Origin 8.0 (https://www.originlab.com/) was used for graph preparation. 3. Results 3.1 Basic soil properties The conversion of NF to tea plantations significantly altered soil properties (Table 2). Soil texture was significantly affected by long-term tea cultivation. The variation in sand and silt content was predominantly controlled by LM (p40 had the highest sand content (73.48%) and the lowest silt content (26.40%), forming a significant contrast with NF and ST >40 . Soil pH ranged from 4.5 to 5.6 in the study area. Soil pH was primarily governed by LM×PA interactions (p 40 . Similarly, CEC was most strongly influenced by PA (p < 0.0001, 57.8% contribution), leading to a significant decrease in all old tea plantations regardless of the management system compared to NF and TT <20 . Soil available nutrients exhibited contrasting patterns. AK was mainly controlled by PA (p < 0.0001, 52.8% contribution), with sloping tea plantation generally maintaining higher concentrations than terraced tea plantation. For AN, LM was the dominant factor (p 40 compared to NF. In contrast, AP variation was distributed more evenly among LM, PA, and their interaction, all being highly significant (p < 0.0001). This led to consistently higher AP levels in terraced tea across all age classes, with TT 40 having 74-165% higher AP concentrations than NF. MBC was overwhelmingly driven by PA (p < 0.0001), which alone explained 79.9% of its variance. In contrast, the variation in MBN was predominantly explained by the interactive effects (p < 0.0001, 58.8% contribution), resulting in the highest MBC and MBN atTT 20-40 . 3.2 Root and litter characteristics Root and litter characteristics showed clear differences between LM and PA (Table 3). Root system development responded strongly to land management. RLD was significantly influenced by LM (p = 0.003), which was the dominant factor contributing 30.4% of the observed variance (Table 4). Consequently, all terraced tea plantations and ST >40 yielded significantly higher RLD values compared to NF. In contrast, RSF was predominantly controlled by LM×PA interactions (p 40 had the largest RSF (234.16 cm²), significantly surpassing all other treatments. The NF maintained the highest RV, which was significantly greater than that in most young and mid-term tea plantations. However, the factors included in the GLM model (LM, PA, LM×PA) had limited explanatory power for RV (Table 4). For RB, ST >40 had the highest value, which was significantly greater than all other treatments, including NF. The GLM indicated that both LM and PA significantly affected RB, though the individual and interactive contributions were relatively modest (Table 4). Litter accumulation was severely impacted by forest-to-tea conversion. Both LC and LT were significantly lower in all tea plantations compared to NF (Table 3). The recovery patterns were governed by the LM. In sloping plantations, both LC and LT remained low across all ages. In contrast, TT exhibited a clear recovery over time, with the interactive effect being the most important factor for LC (44.0% contribution). Consequently, LC in TT >40 was significantly greater than in TT <20 and all sloping plantations. Meanwhile, PA alone was the dominant factor controlling LT, explaining 56.6% of its variance. 3.3 Soil aggregate size distributions and stability Soil aggregate size distribution and stability were significantly influenced by the conversion of NF to tea plantations (Fig. 2). The >2 mm and 2 mm aggregate fraction, with terraced tea at TT 40 showing reductions of 16.7% and 17.5%, respectively, compared to NF (p < 0.05). GLM analysis confirmed that this fraction was significantly affected by both LM (p = 0.029) and PA (p= 0.005), with PA being the dominant factor (45.1% contribution) (Table 4). The 2-1 mm fraction was predominantly controlled by LM×PA interactions (p = 0.001), which explained 53.2% of its variance (Table 4). Notably, ST >40 contained 28.3% more 2-1 mm aggregates than NF. In contrast, the distribution of the 1-0.5 mm and 0.5-0.25 mm fractions was mainly governed by LM (p < 0.0001), which contributed over 75% and 80% of the variance, respectively (Table 4). Consequently, terraced tea generally accumulated a higher proportion of the intermediate fractions compared to ST. The microaggregate (<0.25 mm) fraction was also primarily influenced by LM (p 0.25 mm (R >0.25mm ) was significantly affected by LM (p < 0.0001, 63.2% contribution), with TT 20–40 showing an 8.14% increase compared to NF. The stability indices MWD and GMD were most strongly driven by the LM×PA interactions, which explained 58.7% and 72.0% of their variance, respectively (Table 4). Among all treatments, ST >40 had the highest MWD and GMD values, whereas in terraced tea, aggregate stability generally decreased with increasing PA (Fig.3). 3.4 SOC, TN, TP contents and their stoichiometry ratios in bulk soil and soil aggregates The distribution of SOC, TN, and TP between bulk soil and aggregate fractions varied significantly across land management and plantation ages (Fig. 4). In bulk soil, the conversion of NF to tea plantations generally reduced SOC, TN, and TP contents, with the most pronounced depletion observed at TT 40 maintained the highest levels of SOC and TN among tea plantation treatments. Within soil aggregates, the distribution patterns of SOC, TN and TP varied with aggregate size (Fig. 4). Generally, the highest SOC and TN contents were found in 1-0.5 mm and 0.5-0.25 mm fractions, while the lowest values typically shown in the <0.25 mm fraction. TT 20-40 showed notably high SOC content in the 0.5-0.25 mm fraction, reaching 29.73 g kg⁻¹ (Fig. 4a). For TN content, NF maintained relatively high values in the 0.5-0.25 mm fraction (Fig. 4b). ST >40 showed the highest TN content among tea treatments. NF maintained the highest TP content in macroaggregate fractions (>0.25 mm), while terraced tea generally showed higher TP levels than sloping tea of similar age (Fig. 4c). In bulk soil, the C:N ratio ranged from 7 to 11 across treatments, with the highest value found in ST 40 and TT 20–40 treatments, increasing by more than 140% and 180%, respectively (Fig. 5b and c). Within soil aggregates, the stoichiometric ratios exhibited size-dependent patterns (Fig. 5). The C:N ratio generally showed less variation among aggregate sizes (Fig. 5a). The C:P ratio was consistently higher in the TT 20-40 and ST >40 treatments compared to other treatments across all aggregate fractions (Fig. 5b). In contrast, TT <20 maintained the lowest C:P ratios across all aggregate fractions, with values below 2 in all fractions. The highest C:P and N:P ratios were consistently observed in the 0.5-0.25 mm fraction across tea plantation treatments (Fig. 5b and c). However, NF had C:P ratios ranging from 2.01 to 5.84, with the highest value in the <0.25 mm fraction. The relative importance of the driving factors was further quantified by GLM analysis (Table 5). Notably, the interaction between land management and plantation age (LM×PA) was the most significant and dominant factor, explaining the largest portion of the variance for SOC, TN, and TP in almost all aggregate fractions. Plantation age independently showed a strong influence, especially on TP and the stoichiometric ratios. Furthermore, a significant PA effect was detected for SOC in the largest >2 mm and <0.25 mm aggregate fractions. While LM showed some significant effects on certain variables in specific fractions, its overall influence was not as strong as the interaction effect or the effect of PA. 3.5 Relationships among root, litter, soil nutrients stoichiometry, and aggregate stability Correlation analysis revealed a network of significant associations among measured variables (Fig. 6). Aggregate stability indices (R >0.25 , MWD, GMD) were strongly positively correlated with each other. These stability indices showed positive correlations with SOC, TN, and the stoichiometric ratios C:P and N:P. They were also positively correlated with MBC, MBN, and RLD. In contrast, MWD and GMD were negatively correlated with LC. SOC and TN were positively correlated with the C:P and N:P ratios. Both C:P and N:P ratios showed significant positive correlations with MBN, and silt content, but significant negative correlations with TP, CEC, and sand content. Root biomass was positively correlated with MWD, GMD, SOC, TN, AN, and N:P. Aggregate-associated TN was strongly positively correlated with MWD and GMD in the >2 mm and 2–1 mm fraction. Across nearly all aggregate fractions, SOC and TN showed significant positive correlations with bulk soil SOC, TN, C:P, pH, N:P, RV, and RB (Table 6). Aggregate-associated TP was negatively correlated with C:P, N:P, MBN, CEC, silt, and clay, but positively correlated with bulk soil TP and sand content in most fractions (Table 7). Aggregate-associated C:P and N:P ratios were positively related to SOC, MBN, and silt, but negatively correlated with TP, CEC, and sand across most aggregate sizes (Table 7). The Partial Least Squares Path Modeling (PLS-PM) elucidated the direct and indirect pathways governing soil aggregate stability (GMD) and bulk soil C:N:P stoichiometry (Fig. 7). GMD was simultaneously and directly influenced by the content of different aggregate fractions. Specifically, the 2-1 mm macroaggregates exerted a strong positive effect (path coefficient = 0.52), whereas an increase in the <0.25 mm microaggregates significantly reduced stability (path coefficient = -0.65; p < 0.05). Land management showed significant indirect negative effects on aggregate stability, mediated through multiple pathways: (1) a negative effect via reducing RB, 2-1 mm macroaggregates and <0.25 mm microaggregates; and (2) a positive effect via increasing microbial biomass (MBC and MBN). Land management practice negatively affected both aggregate-associated nutrients (path coefficient = -0.38; p < 0.05) and bulk soil nutrients (path coefficient = -0.39; p < 0.01), thereby lowered stoichiometry. Plantation age (PA) increased root biomass (path coefficient = 0.38; p < 0.05), bulk soil nutrients (path coefficient = 0.33; p < 0.01), and aggregate-associated nutrients (path coefficient = 0.46; p < 0.01), which collectively enhanced microbial biomass (path coefficient = 0.74; p < 0.01). These improvements decreased the proportion of microaggregates (path coefficient = -0.47; p < 0.01), resulting in a positive indirect impact on GMD. Soil C:N:P stoichiometry was significantly increased by both aggregate-associated and bulk soil nutrients, which played a positive mediating role, linking management- and age-driven changes to aggregate stability. 4. Discussion 4.1. Effects of forest-to-tea conversion on soil texture and aggregate stability In this study, we found that the > 2 mm aggregate fraction was dominant in all treatments and controlled mainly by PA (Fig. 2 ; Table 4 ). This predominance is likely attributable to the local granite-derived parent material, which yields a sandy loam texture that provides raw materials for the formation of large macroaggregates (> 2mm) (Wei et al., 2022 ; Wu et al., 2023 ). Furthermore, the release of reactive secondary clays and Fe/Al oxides during weathering promotes organo-mineral association, thereby enhancing the stability of these large aggregates (Ge et al., 2019 ; Liu et al., 2021 ). Conversion of forest to tea plantation introduced human disturbances, which reduced the proportion of the > 2 mm fraction, especially in TT < 20 , likely due to the intense disturbance during terrace construction ((Xue et al., 2024 ). The recovery of this fraction in mid-age plantations (ST 20−40 , TT 20−40 ) coincided with higher litter inputs (Table 3 ), which provided organic binding agents for large aggregate formation (Wang et al., 2022 ). The subsequent decline in the oldest plantations (> 40 years) may be attributed to soil compaction from long-term management, which disrupts pore networks and negatively impacts the microbial habitat and the production of binding agents (Frene et al., 2024 ; Zhan, 2024 ). Land management practice had a dominant and lasting control over the finer aggregate fractions (< 1 mm), thereby engineering the fundamental structure of the soil (Table 4 ). ST favored the accumulation of microaggregates (< 0.25 mm), while the terraced tea promoted the formation of intermediate-sized aggregates (1-0.25 mm). This management-driven divergence was vital, as it physically predefines the potential niches for soil organic matter stabilization and nutrient sequestration. The accumulation of the 2 − 1 mm fraction in ST > 40 , likely driven by high root biomass (Table 3 ) and its associated organic binding processes (Sarker et al., 2022 ; Cai et al., 2023 ), was a key factor leading to its superior aggregate stability (highest MWD and GMD). The 2 − 1 mm fraction, being highly sensitive to the LM×PA interaction, thus serves as a dynamic indicator of the balance between soil disturbance and biological recovery processes. A key finding lied in the differential response of stability indicators. Despite the R > 0.25 remaining statistically similar between NF and sloping tea, the significant increase in the MWD and GMD in ST > 40 revealed a qualitative improvement in aggregate stability that was not captured by macroaggregate content alone. This enhancement in aggregate stability aligned with the extensive root biomass in ST > 40 (Table 3 ), as roots and their associated fungal networks help create stable soil structures that resist hydraulic disruption (Negi et al., 2025 ). The turnover of larger aggregates into smaller but more stable units could potentially explain these temporal patterns, where long-term biological processes gradually build quality over quantity (Bai et al., 2020 ). Notably, our GLM analysis confirmed that the LM × PA interaction was the dominant force governing aggregate stability (MWD and GMD), highlighting that the development of a stable soil structure is an outcome of management practices interacting with ecosystem development over time. Long-term management also induced fundamental shifts in bulk soil texture that have profound implications for soil functioning(Panagea et al., 2020 ). Notably, terrace management developed the coarser texture, whereas sloping management showed finer texture among tea plantations (Table 2 ). The observed textural coarsening in older terraces likely reflects the cumulative effects of water-induced selective removal of fine particles and their redistribution within the terrace landscape over decades of cultivation(Li & Lindstrom, 2001 ;Zhang et al., 2014 ). These textural shifts have important functional consequences: sandier soils in old terraces face reduced water and nutrient retention capacity, while finer-textured slopes may become increasingly susceptible to surface sealing and erosion. This divergence in physical properties represents a fundamental pedogenetic differentiation driven by management practice. 4.2. Effects of land management and plantation age on bulk soil nutrients and stoichiometry Following the conversion of NF to tea plantations, aggregate-associated SOC, TN, TP and C:N:P ratios were profoundly influenced by land management practices and plantation age. Our study revealed that SOC and TN content recovered to levels comparable to NF in ST > 40 and TT 20−40 (Fig. 4 a-b). This finding aligned with previous studies demonstrating that SOC and TN content increase with plantation age (Zhu et al., 2019 ; Zhou et al., 2022 ). As tea plantations mature, ecosystems may recover from initial disturbances and reach a new equilibrium(Chiti et al., 2018 ;Wang et al., 2020b ). This recovery could be associated with the development of tea root systems and the accumulation of litter over time. The expansion of belowground root networks and the gradual buildup of aboveground litter increase organic inputs, stimulating microbial activity and improving nutrient cycling (Naresh et al., 2017 ; Nair et al., 2021 ). Moreover, the enhancement of aggregate stability in older plantation provides physical protection for SOC and TN against decomposition (Bhaduri et al., 2022 ). In the present study, the recovery of aggregate stability (MWD, GMD) was positively correlated with the accumulation of SOC and TN (Fig. 6 ). Compared to sloping plantations, terrace management facilitated faster recovery of SOC and TN, particularly in TT 20−40 . This faster recovery was probably due to terracing's structural advantages, which effectively reduce soil erosion, improve moisture retention, and promote organic matter accumulation (Qiu et al., 2014 ). In this study, the C:N ratio remained relatively stable across treatments. As structural components, the accumulation and turnover of C and N are relatively stable and coupled (Zhang et al., 2020 ). Carbon and nitrogen are closely linked, and their responses to environmental changes tend to follow similar patterns. A positive correlation between C and N was observed in both bulk soil and aggregate fractions (Fig. 6 and Table 6 ), consistent with findings by Zhang et al.(2019b). The conversion from NF to tea plantation significantly decreased TP content, which continued to decline in both management systems with increasing plantation age, particularly in ST > 40 and TT 20−40 . This aligns with findings by Wang et al. ( 2023 ) and highlights the profound and long-lasting P loss due to forest-to-tea conversion. The continuous depletion of TP in long-term tea plantations was likely due to plant uptake, as the harvesting of tea leaves results in significant and often irreversible removal of P from the soil system (Dang, 2005 ). The substantial increases in C:P and N:P ratios in TT 20−40 and ST > 40 further indicated P limitation in tea plantations. The lower TP content and elevated C:P and N:P ratios in TT 20−40 might be attributed to the rapid release of organic matter in terrace systems, which is facilitated by enhanced water retention and reduced erosion, without proportional replenishment of P. Chen & Lin, ( 2016 ) found that although terracing reduces P loss via runoff, the retained P is prone to rapid immobilization. This occurs primarily due to the precipitation of phosphate into insoluble Fe/Al compounds in the acidic, iron- and aluminum-rich soils typical of tea plantations (Ruan et al., 2007 ). Unlike terrace systems, sloping plantations experienced greater long-term P losses, resulting primarily from topsoil erosion driven by natural rainfall (Fig. 4 c). Thus, while C and N accumulate more slowly on slopes, the long-term loss of P and limited replenishment lead to elevated C:P and N:P ratios. 4.3 Aggregate-associated nutrient distribution and its functional significance The distribution patterns of nutrients within different aggregate size fractions provide critical insights into the mechanisms of soil carbon stabilization and nutrient cycling (Sbih et al., 2024 ; Chen et al., 2025 ). In this study, we observed that aggregate-associated SOC, TN, and TP concentrations generally increased with decreasing aggregate size, with the highest values consistently found in the 0.5 − 0.25 mm fraction across most treatments (Fig. 4 ). This pattern aligned with the microaggregate-based stabilization mechanism, where organic matter becomes progressively enriched in finer fractions through the formation of stable organo-mineral complexes (Totsche et al., 2018 ; von Lützow et al., 2007 ).The 0.5 − 0.25 mm fraction represents a critical transitional zone in the aggregate hierarchy that balances physical protection with biological accessibility (Yudina & Kuzyakov, 2023 ). Notably, this enrichment pattern was consistent across both management systems and all plantation ages, suggesting that the fundamental mechanism of nutrient stabilization within aggregates is robust to land-use change and management practices. However, the magnitude of nutrient enrichment varied significantly among treatments. TT 20−40 exhibited the highest SOC and TN concentrations in the 0.5 − 0.25 mm fraction (29.73 g kg⁻¹ and 2.45 g kg⁻¹, respectively), coinciding with its peak microbial biomass and optimal aggregate stability. This indicated that the mid-term terrace system created particularly favorable conditions for the formation of nutrient-rich microaggregates through enhanced microbial processing of organic matter (Costa et al., 2018 ). In contrast, ST > 40 showed relatively lower nutrient concentrations in this key fraction despite having high root biomass, suggesting that the stress-induced root strategy may produce organic inputs of lower quality that are less effectively incorporated into stable microaggregates (Lehmann et al., 2020 ). The stoichiometric ratios within aggregate fractions revealed additional insights into nutrient limitation patterns at the micro-scale (Cui et al., 2020 ; Zhang et al., 2021 ).The C:P and N:P ratios were consistently highest in the 0.5 − 0.25 mm fraction across all treatments, with particularly elevated values in TT 20−40 (C:P: 8.68; N:P: 0.91) and ST > 40 (C:P: 7.51; N:P: 0.83) (Fig. 5 ). This indicated that P limitation was most pronounced in the most biologically active aggregate fraction, which hosts the majority of microbial biomass and mediates nutrient turnover (Liu et al., 2014 ). The enrichment of P-depleted organic matter in this fraction suggests that microbial communities actively process and transform organic materials but are constrained by P availability, leading to the accumulation of organic matter with high C:P ratios (Feng et al., 2023 ).This micro-scale phosphorus limitation may, in turn, feedback to constrain microbial growth efficiency and the production of aggregate-stabilizing agents. The GLM analysis further revealed that the interaction between land management and plantation age was the dominant factor controlling SOC and TN concentrations in most aggregate fractions (contributing 46.4–81.4% of variation), while plantation age alone was the primary driver for TP variation in smaller fractions (35.5–35.7% contribution) (Table 4 ). This distinction highlighted a fundamental difference in the cycling of C:N versus P at the aggregate scale: C and N dynamics are tightly coupled to the integrated effects of management history and ecosystem development, reflecting their dependence on biological processes (e.g., organic matter inputs and microbial processing). In contrast, phosphorus dynamics in smaller aggregates are primarily governed by time-dependent processes, including weathering, leaching, and gradual depletion through plant uptake, which function largely independently of specific management practice (Walker & Syers, 1976 ; Crews et al., 1995 ). The 0.5 − 0.25 mm aggregates fraction functioned as "microbial hotspots" where organic matter, microorganisms, and mineral surfaces interact closely, creating ideal conditions for enzymatic processing and nutrient cycling (Kuzyakov & Blagodatskaya, 2015 ). This aggregate size class offers critical physical protection. Its dimensions are small enough to restrict oxygen diffusion and predator entry, yet large enough to sustain pore connectivity. Consequently, it creates suitable conditions for microbial activity and organic matter stabilization (Six et al., 2004 ). The consistent enrichment of nutrients in this fraction across all treatments underscores its fundamental importance in soil functioning and suggests that management strategies aimed at promoting the formation and stability of 0.5 − 0.25 mm aggregates could enhance both C sequestration and nutrient availability in the studied soils. 4.4 Driving factors of aggregate stability and nutrient dynamics after land use change Pearson correlation and PLS-PM analyses indicate that soil aggregate stability is regulated by aggregate-size distribution, nutrient stoichiometry, microbial activity, and root inputs, consistent with previous studies (Wang et al., 2017 ; Li et al., 2024 ). Aggregate stability indices (R > 0.25 , MWD, and GMD) were strongly correlated with SOC, TN, and C:P and N:P ratios, highlighting the importance of nutrient availability and stoichiometric balance. Positive relationships between aggregate stability, MBC and MBN, and root length density highlight the contribution of biological binding agents from roots and microbial by-products. Additionally, PLS-PM results indicated that aggregate-size composition is a direct structural determinant of stability. Macroaggregates (2 − 1 mm) showed a strong positive effect on GMD, while microaggregates (< 0.25 mm) have a pronounced negative indirect effect, indicating structural degradation. The contrasting root foraging strategies observed between the two management practices provide a mechanistic basis for understanding these patterns. Terrace plantations developed an "efficient foraging strategy," characterized by high root surface area with moderate root biomass, which maximizes soil exploration per unit carbon invested (Comas et al., 2013 ; Lynch, 2018 ). This strategy, combined with significant litter recovery (litter cover > 67% in TT 20−40 and TT > 40 ), created an "aboveground-belowground coupling" that enhanced organic matter input and stimulated microbial activity (Wardle et al., 2004 ). Whereas, sloping plantations exhibited a "stress-induced foraging strategy," with exceptionally high root biomass but only moderate root surface area (Poorter et al., 2012 ). Notably, this high root investment occurred without corresponding litter recovery, with litter cover remaining persistently low (< 35%) across all sloping plantations (Table 3 ). This decoupling between belowground carbon investment and aboveground litter input represents a fundamental inefficiency in carbon allocation that helps explain the slower recovery of soil properties in sloping systems. Land management directly enhanced microbial biomass but had direct negative effects on microaggregate, macroaggregate, root biomass, aggregate-associated nutrient and bulk soil nutrient. This pattern likely reflects the mechanical disturbance associated with terrace construction, which disrupts soil aggregate hierarchy and redistributes aggregate size fractions (He et al., 2025 ). Aggregate breakdown exposes previously protected organic matter, increases soil aeration and permeability, and accelerates nutrient losses, while temporarily enhancing microbial biomass through increased substrate accessibility (Six et al., 2000 ). The negative effects of land management on both aggregate-associated and bulk soil nutrients lead to reduced C:N:P stoichiometry, which plays a central role in regulating microbial metabolism. Stoichiometric imbalance limits microbial growth efficiency, compelling microbes to allocate a greater proportion of assimilated carbon to maintenance respiration rather than to the synthesis of persistent binding agents, such as glomalin and extracellular polysaccharides, that stabilize microaggregates and facilitate macroaggregate formation (Li et al., 2022 ; Redmile-Gordon et al., 2020 ). Plantation age had negative direct effects on microbial biomass, this might be due to increase of soil acidification as plantation age increased (Table 2 ), at which accumulation of aluminum and antimicrobial substance (Phenolics and polyphenols) likely caused a decline in microbial biomass and activity (H. Li et al., 2012 ). However, plantation age indirectly promoted microbial biomass by increasing bulk-soil and aggregate-associated nutrient pools and improving C:N:P stoichiometric balance, thereby enhancing microbial growth efficiency. Additionally, increasing planation age increased root biomass which negatively affects microaggregates. This biologically driven pathway reduced the proportion of microaggregates and indirectly increased GMD, indicating progressive structural recovery with plantation age. A particularly striking finding was the "N paradox" observed in ST > 40 , which exhibited the highest AN concentration among all treatments (157.89 mg kg⁻¹) but simultaneously showed the lowest MBC (0.95 mg kg⁻¹). This decoupling between N availability and microbial activity reveals fundamental constraints on ecosystem functioning in long-term sloping systems. The abundant N likely cannot be effectively utilized due to constraints on microbial growth (Janssens et al., 2010 ; Treseder, 2008 ). Several interacting mechanisms may explain this phenomenon. First, C limitation: despite high RB, the stress-induced root strategy in sloping systems may produce root exudates of lower quality, and the absence of litter input limits C availability (Janssens et al., 2010 ). Second, physical habitat degradation: unstable soil structure and frequent wet-dry cycles on slopes create unfavorable microhabitats for microbial colonization(Six et al., 2004 ). Third, potential Al toxicity: the acidified conditions (pH as low as 4.50 in ST 20−40 ) may release toxic Al³⁺ that suppresses microbial activity even when N is abundant (Kochian et al., 2005 ; von Uexküll & Mutert, 1995 ).This N-microbial decoupling demonstrates that nutrient pools alone do not indicate ecosystem health; rather, the connectivity between nutrient availability and biological activity is a more meaningful indicator of soil functionality (Kuzyakov & Blagodatskaya, 2015 ). Synthesizing these path analyses with the observed patterns of soil properties, root traits, and litter dynamics revealed fundamentally different system-level feedback mechanisms operating under the two management regimes. Terrace systems establish a "virtuous cycle": erosion control enables litter recovery (LC > 67%), which combined with an efficient root foraging strategy (high RSA, moderate RB) enhances organic matter input and supports robust microbial communities (high MBC/MBN in TT 20−40 ). This biological activity, promotes aggregate formation and nutrient cycling, driving the recovery of SOC and TN. However, this cycle contains an inherent vulnerability: the rapid turnover of organic matter without proportional P replenishment, coupled with P fixation in acid soils, leads to progressive P limitation (elevated C:Pand N:P) (Siepel et al., 2018 ). In contrast, sloping systems showed a "vicious cycle": persistent erosion prevents litter accumulation (LC consistently < 35%), forcing plants into a costly stress-induced root strategy (exceptionally high RB but moderate RSA). This high-carbon investment in roots fails to effectively support microbial communities (lowest MBC despite highest AN), resulting in the nitrogen-microbial decoupling observed in ST > 40 . The absence of litter input and the inefficient root strategy create a "carbon trap" where photosynthate is allocated to roots but does not translate into soil carbon accumulation or microbial activity (Cotrufo et al., 2013 ), leading to physical degradation and stoichiometric imbalance. These contrasting feedback mechanisms, elucidated by the PLS-PM analysis, highlight that sustainable management of tea plantations requires not only erosion control but also targeted interventions such as organic amendments and phosphorus-mobilizing practices to disrupt the vicious cycle on slopes and address emerging vulnerabilities in terraces 5. Conclusion The conversion of natural forests to tea plantations initiates divergent trajectories of soil structure and nutrient dynamics that are governed by the interaction between land management and plantation age, thereby supporting our first hypothesis. Partial support was found for our second hypothesis: while terrace systems facilitated faster recovery of aggregate stability and carbon pools through erosion control and efficient root foraging, they simultaneously accelerated P depletion, leading to pronounced stoichiometric imbalance. Contrary to expectations, long-term sloping cultivation did not result in persistent macroaggregate decline. Instead, it developed exceptional mechanical stability through stress-induced root investment, but at the cost of microbial decoupling—high N availability coexisted with severely suppressed microbial biomass. Critically, across both management systems, progressive P depletion with increasing plantation age emerged as the dominant constraint, with C:P and N:P ratios increasing by more than 140% in older plantations, establishing P as the primary limiting nutrient in these systems. These findings demonstrate that sustainable management must address not only erosion control but also the emerging stoichiometric imbalances—particularly through targeted P interventions—to maintain long-term soil health in mountainous tea plantations. Declarations Acknowledgements The authors gratefully acknowledge the National Natural Science Foundation of China (Grant No. 32071840) and the Key Project of the Ministry of Water Resources (SBJ2018010). The authors also thank Yannan Xu, Yaowen Chang, Wei Lu, Jianpeng Chen, Haiyang Wang and many others for assisting with soil sample collection and analyses. Author contributions Material preparation, data collection, and analysis were performed by Abdul Hakim Jamshidi, Yaowen Chang, Yi Lu, and Na Jin. Conceptualization and review were performed by Lei Sun, Xia Liu, Di Wu, and Zhaofei Fan. The first draft of the manuscript was written by Abdul Hakim Jamshidi. All authors contributed to the study design, interpretation of data, review and editing of manuscript. Conceptualization, supervision, and project administration were led by Xia Liu and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript. Funding This work was supported by the National Natural Science Foundation of China (Grant No. 32071840) and the Key Project of the Ministry of Water Resources (SBJ2018010). Data availability The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request. Competing interest The authors have no competing interests to declare that are relevant to the content of this article. References Amézketa, E. (1999). Soil Aggregate Stability: A Review. Journal of Sustainable Agriculture , 14 (2–3), 83–151. https://doi.org/10.1300/J064v14n02_08 Amundson, R., Berhe, A. A., Hopmans, J. W., Olson, C., Sztein, A. E., & Sparks, D. L. (2015). Soil and human security in the 21st century. Science , 348 (6235), 1261071. https://doi.org/10.1126/science.1261071 Bai, Y., Ma, L., Degen, A. A., Rafiq, M. K., Kuzyakov, Y., Zhao, J., Zhang, R., Zhang, T., Wang, W., Li, X., Long, R., & Shang, Z. (2020). 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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-9267649","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":617142217,"identity":"1b75a822-6869-40a5-89d7-c2217b9178a6","order_by":0,"name":"Abdul hakim Jamshidi","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAxklEQVRIiWNgGAWjYBACAwY2hgMMFQzM7A1AHg/xWs4wMPMcIEULA2MbUDXRWszZjyUeujnvDjuPRALjg7dtDPLmhLRY9qQdOJy77RkzUAuz4dw2BsOdDYQcdiC9AajlMLO9RAKbNG8bQ4LBAUJazj8HaplzGGQL+2/itNwAOawBrIWNmUgtzxIO5xwDauF52Cw555yE4QbCDksz/pxTcziZhz354Ic3ZTbyBG2BgWRg7DQAaQki1QOBHfFKR8EoGAWjYMQBAGt+QQDFKmKWAAAAAElFTkSuQmCC","orcid":"","institution":"Nanjing Forestry University","correspondingAuthor":true,"prefix":"","firstName":"Abdul","middleName":"hakim","lastName":"Jamshidi","suffix":""},{"id":617142218,"identity":"584934a7-91d9-43a7-b0bb-d85962f59f28","order_by":1,"name":"Di Wu","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Di","middleName":"","lastName":"Wu","suffix":""},{"id":617142219,"identity":"c149e807-6dbe-4984-bbe8-909a1687f5c4","order_by":2,"name":"Lei Sun","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Lei","middleName":"","lastName":"Sun","suffix":""},{"id":617142220,"identity":"61f01a6a-3b65-426d-b7ec-d6d30c9d6675","order_by":3,"name":"Yaowen Chang","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Yaowen","middleName":"","lastName":"Chang","suffix":""},{"id":617142221,"identity":"78ef11fa-e801-4b44-882a-a1e8f6526594","order_by":4,"name":"Yi Lu","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Yi","middleName":"","lastName":"Lu","suffix":""},{"id":617142222,"identity":"182f53f6-ec1b-49dd-ad7e-b0a2259bc84a","order_by":5,"name":"Na Jin","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Na","middleName":"","lastName":"Jin","suffix":""},{"id":617142223,"identity":"516b7aec-d234-4d13-a02c-6586e2da1ef3","order_by":6,"name":"Xia Liu","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Xia","middleName":"","lastName":"Liu","suffix":""},{"id":617142224,"identity":"f285d636-36b1-46e2-b374-9313bdd350ee","order_by":7,"name":"Zhaofei Fan","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Zhaofei","middleName":"","lastName":"Fan","suffix":""}],"badges":[],"createdAt":"2026-03-30 13:34:36","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9267649/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9267649/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":106724478,"identity":"b04a26f2-ba88-44ac-a588-c609bb690c29","added_by":"auto","created_at":"2026-04-12 18:28:17","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1384194,"visible":true,"origin":"","legend":"\u003cp\u003eGeographical location of study area and photos of sampling sites. ST\u003csub\u003e\u0026lt;20\u003c/sub\u003e (sloping tea plantations less than 20 years old), ST\u003csub\u003e20-40\u003c/sub\u003e (sloping tea plantations aged 20-40 years), ST\u003csub\u003e\u0026gt;40 \u003c/sub\u003e(sloping tea plantations older than 40 years), TT\u003csub\u003e\u0026lt;20 \u003c/sub\u003e(terraced tea plantations less than 20 years old), TT\u003csub\u003e20-40 \u003c/sub\u003e(terraced tea plantations aged 20-40 years), TT\u003csub\u003e\u0026gt;40 \u003c/sub\u003e(terraced tea plantations older than 40 years) and NF (natural forest).\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-9267649/v1/b456f39d51602d6ea4202a0c.png"},{"id":106491526,"identity":"cfd63719-a417-46ad-abea-22b5c8f6d779","added_by":"auto","created_at":"2026-04-09 07:34:20","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":312433,"visible":true,"origin":"","legend":"\u003cp\u003eAggregate size distribution under different treatments. ST\u003csub\u003e\u0026lt;20\u003c/sub\u003e (sloping tea plantations less than 20 years old), ST\u003csub\u003e20-40\u003c/sub\u003e (sloping tea plantations aged 20-40 years), ST\u003csub\u003e\u0026gt;40 \u003c/sub\u003e(sloping tea plantations older than 40 years), TT\u003csub\u003e\u0026lt;20 \u003c/sub\u003e(terraced tea plantations less than 20 years old), TT\u003csub\u003e20-40 \u003c/sub\u003e(terraced tea plantations aged 20-40 years), TT\u003csub\u003e\u0026gt;40 \u003c/sub\u003e(terraced tea plantations older than 40 years) and NF (natural forest).Values are means ± standard errors (n\u0026nbsp;= 3). Lowercase letters indicate significant differences (p\u0026nbsp;\u0026lt; 0.05) among treatments within the same aggregate fraction, while uppercase letters indicate significant differences between aggregate size fractions under same treatment.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-9267649/v1/1011765fcad15a15978fa06e.png"},{"id":106724671,"identity":"620fa5ac-4920-4149-9717-56556efe62eb","added_by":"auto","created_at":"2026-04-12 18:29:05","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":238847,"visible":true,"origin":"","legend":"\u003cp\u003eSoil aggregate stability indices across treatments. ST\u003csub\u003e\u0026lt;20\u003c/sub\u003e (sloping tea plantations less than 20 years old), ST\u003csub\u003e20-40\u003c/sub\u003e (sloping tea plantations aged 20-40 years), ST\u003csub\u003e\u0026gt;40 \u003c/sub\u003e(sloping tea plantations older than 40 years), TT\u003csub\u003e\u0026lt;20 \u003c/sub\u003e(terraced tea plantations less than 20 years old), TT\u003csub\u003e20-40 \u003c/sub\u003e(terraced tea plantations aged 20-40 years), TT\u003csub\u003e\u0026gt;40 \u003c/sub\u003e(terraced tea plantations older than 40 years) and NF (natural forest).R\u003csub\u003e\u0026gt;0.25\u003c/sub\u003e\u0026nbsp;(\u0026gt;0.25 mm aggregate fraction),\u0026nbsp;MWD\u0026nbsp;(mean weight diameter, mm),\u0026nbsp;GMD\u0026nbsp;(geometric mean diameter), Values are expressed as means ± standard errors (n=3). Different letters denote significant differences (p \u0026lt; 0.05) between treatment.\u003cbr\u003e\n\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-9267649/v1/f2c66c8e664dd6e10eecce38.png"},{"id":106724362,"identity":"1044978d-1ff3-4c81-b653-a1bd4bbcf82a","added_by":"auto","created_at":"2026-04-12 18:27:44","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":348116,"visible":true,"origin":"","legend":"\u003cp\u003eDistributions of soil organic carbon (SOC, a), total nitrogen (TN, b), and total phosphorus (TP, c) in bulk soil and aggregate fractions across treatments. ST\u003csub\u003e\u0026lt;20\u003c/sub\u003e (sloping tea plantations less than 20 years old), ST\u003csub\u003e20-40\u003c/sub\u003e (sloping tea plantations aged 20-40 years), ST\u003csub\u003e\u0026gt;40 \u003c/sub\u003e(sloping tea plantations older than 40 years), TT\u003csub\u003e\u0026lt;20 \u003c/sub\u003e(terraced tea plantations less than 20 years old), TT\u003csub\u003e20-40 \u003c/sub\u003e(terraced tea plantations aged 20-40 years), TT\u003csub\u003e\u0026gt;40 \u003c/sub\u003e(terraced tea plantations older than 40 years) and NF (natural forest). Values are means ± standard errors (n\u0026nbsp;= 3). Lowercase letters indicate significant differences (p\u0026nbsp;\u0026lt; 0.05) among treatments within the same aggregate fraction or bulk soil, while uppercase letters indicate significant differences between aggregate size fractions under same treatment.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-9267649/v1/131bbf1788a3921cac3c85e6.png"},{"id":106491528,"identity":"40cefe36-ab12-4075-b311-a7e46106d7a2","added_by":"auto","created_at":"2026-04-09 07:34:21","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":334544,"visible":true,"origin":"","legend":"\u003cp\u003eDistributions of soil C:N (a), C:P (b), and N:P (c) ratios in bulk soil and aggregate fractions across treatments.\u0026nbsp;ST\u003csub\u003e\u0026lt;20\u003c/sub\u003e (sloping tea plantations less than 20 years old), ST\u003csub\u003e20-40\u003c/sub\u003e (sloping tea plantations aged 20-40 years), ST\u003csub\u003e\u0026gt;40 \u003c/sub\u003e(sloping tea plantations older than 40 years), TT\u003csub\u003e\u0026lt;20 \u003c/sub\u003e(terraced tea plantations less than 20 years old), TT\u003csub\u003e20-40 \u003c/sub\u003e(terraced tea plantations aged 20-40 years), TT\u003csub\u003e\u0026gt;40 \u003c/sub\u003e(terraced tea plantations older than 40 years) and NF (natural forest). Values are means ± standard errors (n\u0026nbsp;= 3). Lowercase letters indicate significant differences (p\u0026nbsp;\u0026lt; 0.05) among treatments within the same aggregate fraction or bulk soil, while uppercase letters indicate significant differences between aggregate size fractions under same treatment.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-9267649/v1/cc16f0f0a6a945a94b3547ad.png"},{"id":106724561,"identity":"7829625c-7efe-4bf0-952c-be40e892cd15","added_by":"auto","created_at":"2026-04-12 18:28:37","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":493655,"visible":true,"origin":"","legend":"\u003cp\u003eSpearman correlation heatmap among soil physical, chemical, biological properties, and aggregate stability-related indices. R\u003csub\u003e\u0026gt;0.25\u003c/sub\u003e\u0026nbsp;(\u0026gt; 0.25 mm aggregate fraction),\u0026nbsp;MWD\u0026nbsp;(mean weight diameter, mm),\u0026nbsp;GMD\u0026nbsp;(geometric mean diameter, mm). SOC (soil organic carbon), TN (total nitrogen), TP (total phosphorus); stoichiometric ratios (C:N, C:P, and N:P) CEC (cation exchange capacity); AN (available nitrogen), AP (available phosphorus), AK (available potassium); MBC (microbial biomass carbon), MBN (microbial biomass nitrogen); LC (litter cover), LT (litter thickness); RB (root biomass), RSA (root surface area), RV (root volume), and RLD (root length density).\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-9267649/v1/fa0ab5bf46cf628afd407888.png"},{"id":106724573,"identity":"24ecdb80-5d87-4dbd-8e4a-f45378aa354a","added_by":"auto","created_at":"2026-04-12 18:28:40","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":235178,"visible":true,"origin":"","legend":"\u003cp\u003ePartial least squares path modeling (PLS-PM) showing direct and indirect effects of land management practice, plantation age, and soil variables on aggregate stability (GMD) and C:N:P stoichiometry. Numbers on arrow lines denote significant standardized path coefficients. *, P \u0026lt; 0.05, **, P \u0026lt; 0.01, ***, P \u0026lt; 0.001. R2 represents the variance of dependent variables explained by the inner model. GMD (geometric mean diameter), SOC (soil organic carbon), TN (total nitrogen), TP (total phosphorus), stoichiometric ratios (C:N, C:P, and N:P), AN (available nitrogen), AP (available phosphorus), MBC (microbial biomass carbon), MBN (microbial biomass nitrogen) and RB (root biomass).\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-9267649/v1/557764f141f54d782d66dfb5.png"},{"id":108977438,"identity":"0084308d-22fd-40f7-9484-fa06a35f1a3c","added_by":"auto","created_at":"2026-05-11 11:31:46","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3627289,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9267649/v1/7dc98703-53d9-49a5-b7be-f041036b8e06.pdf"},{"id":106959595,"identity":"4fc37b94-a73a-4478-b005-84300b0682ff","added_by":"auto","created_at":"2026-04-15 09:12:00","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":63107,"visible":true,"origin":"","legend":"","description":"","filename":"Tables.docx","url":"https://assets-eu.researchsquare.com/files/rs-9267649/v1/8fabb98c07fb1f3f30eb42e7.docx"}],"financialInterests":"","formattedTitle":"Effect of forest conversion to tea plantations on soil aggregate stability and its stoichiometry of carbon, nitrogen and phosphorus","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eSoil health is crucial for ecosystem sustainability and a critical component in addressing global challenges such as food security and climate change mitigation (Amundson et al., 2015). However, it is vulnerable to human disturbances, with land use change being a predominant driver (Guo \u0026amp; Gifford, 2002). In ecologically fragile hilly and mountainous regions, such as the Dabie Mountain area, the conflict between economic development and environmental protection is particularly prominent. Here, the widespread conversion of ecological forests to woody crops, driven by economic needs, has long-term ecological consequences for soil \u0026quot;micro-health\u0026quot; which remain poorly understood (de Bl\u0026eacute;court et al., 2013).\u003c/p\u003e\n\u003cp\u003eThe integrity of soil micro-health hinges on the balance and cycling of core elements: carbon (C), nitrogen (N), and phosphorus (P) (Mao et al., 2020; Sardans et al., 2021). Their ecological stoichiometric ratios (C:N:P) serve as a master regulator of decomposition, nutrient cycling, and energy flow\u0026nbsp;(Zhang, et al., 2021; Zheng et al., 2021; Rastetter et al., 2022). These biogeochemical processes are physically mediated by soil structure, particularly the distribution and stability of aggregates (Liu et al., 2010; Sarker et al., 2018). Soil aggregates are the key micro-structures that physically protect organic carbon and modulate nutrient accessibility. Therefore, the central question arising from forest conversion is: how does this transformation simultaneously alter the physical architecture (aggregate stability) and the biochemical balance (C:N:P stoichiometry) of the soil? Investigating their coupled response offers a mechanistic lens to understand soil degradation or resilience (Kan et al., 2023).\u003c/p\u003e\n\u003cp\u003eWhile aggregates are recognized as primary nutrient reservoirs, predicting how carbon and nutrients are distributed among different aggregate sizes remains contentious. The classical aggregate hierarchy theory posits that concentrations of C, N, and P increase with aggregate size, as macroaggregates form around fresh organic matter(Blanco-Canqui \u0026amp; Lal, 2004; Gupta \u0026amp; Germida, 2015; Xiao et al., 2017). Conversely, a substantial body of research demonstrates that finer clay- and silt-sized fractions can exhibit higher nutrient concentrations due to the formation of stable organo-mineral complexes (von L\u0026uuml;tzow et al., 2007; J. R. Sarker et al., 2018). This fundamental contradiction highlights that aggregate-associated nutrient dynamics might be context-dependent, likely governed by factors such as soil type, vegetation, management practices, and time since land conversion(Tang et al., 2022; Kan et al., 2023).\u003c/p\u003e\n\u003cp\u003eAmong these contextual factors, land management practice and plantation age are paramount. Intensive land management practices, such as terracing, fundamentally alter soil disturbance and hydrological pathways compared to conventional\u0026nbsp;slope cultivation. Terracing can help maintain aggregate stability. However, this effect might be affected by time (Wang et al., 2016; Yin et al., 2016; Zheng et al., 2023; Xue et al., 2024). The initial construction is often accompanied by intense soil disturbance, which could lead to a severe deterioration of soil structure and the loss of soil organic carbon in the short term. With the increase of management duration, erosion control function of terracing would promote the recovery of soil structure and nutrient balance. In contrast, slope cultivation causes sustained erosive forces, accelerating aggregate degradation and stoichiometric imbalances. Despite their importance, most research has focused on bulk soil properties or short-term responses (Zhu et al., 2018; Zhang et al., 2019a), neglecting how the interaction between management practice and plantation age drives the long-term evolution of nutrient storage within the soil aggregates.\u003c/p\u003e\n\u003cp\u003eTea plantations, a widespread perennial crop established on converted forest land in the Dabie Mountains, represent an ideal system to address this knowledge gap (Wang et al., 2020a; Xu et al., 2020). Intensive management practices, including periodic tillage, high rates of fertilization, and canopy pruning, impose distinct and persistent pressures on soil. Therefore, the objectives of this study were to: (1) characterize the evolution of soil aggregate stability and C:N:P stoichiometry across a chronosequence of terraced and sloped tea plantations; and (2) evaluate the key drivers and mechanisms through which plantation age (\u0026lt;20, 20-40 and \u0026gt;40 years) and management practices (slope vs. terrace) collectively regulate these properties. We hypothesize that the dynamics of soil aggregate stability and C:N:P stoichiometry are governed by the interaction between management practice and plantation age. Specifically, we expect that long-term slope cultivation will lead to a persistent decline in macro-aggregates and a divergence of C:N:P ratios from forest baselines. For terrace systems, we predicted an initial phase of degradation followed by long-term recovery in structure and nutrient balance, facilitated by erosion control.\u0026nbsp;\u003c/p\u003e"},{"header":"2. Materials and methods","content":"\u003ch2\u003e2.1 Study area and soil sampling\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eThe study was conducted in Jinzhai County, Anhui Province (115\u0026deg;22\u0026prime;-116\u0026deg;11\u0026prime;E, 31\u0026deg;06\u0026prime;-31\u0026deg;48\u0026prime;N), a major tea-producing region on the northern slope of the Dabie Mountains (Fig. 1). Covering a total area of 3,814 km\u0026sup2;, the terrain is characterized by high elevations in the south and lower elevations in the north, with slopes ranging from 8\u0026deg; to 15\u0026deg; and steep slopes from 15\u0026deg; to 25\u0026deg;. This region features a humid subtropical monsoon climate, with a mean annual precipitation of 1,389.6 mm and mean annual temperatures ranging from 15\u0026deg;C to 16.3\u0026deg;C. The predominant rock types are granite and granite gneiss, and the soils classified as Entisols, Ultisols and Alfisols, according to the U.S. Soil Taxonomy system (Hongda et al., 2022). The forest coverage rate is 74.1%. Native forests were dominated by Masson pine (\u003cem\u003ePinus massoniana\u003c/em\u003e) and \u003cem\u003eQuercus acutissima\u0026nbsp;\u003c/em\u003e(Rui-na et al., 2021).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eA field investigation was conducted in May 2023 on tea plantations with different land management practices (slope vs. terrace) and plantation ages (\u0026lt;20 years, 20-40 years; \u0026gt;40 years). Therefore, 21 experimental sites (7 treatments \u0026times; 3 replications) were employed (Table 1): ST\u003csub\u003e\u0026lt;20\u003c/sub\u003e (sloping tea plantations less than 20 years old), ST\u003csub\u003e20-40\u003c/sub\u003e (sloping tea plantations aged 20-40 years), ST\u003csub\u003e\u0026gt;40\u0026nbsp;\u003c/sub\u003e(sloping tea plantations older than 40 years), TT\u003csub\u003e\u0026lt;20\u0026nbsp;\u003c/sub\u003e(terraced tea plantations less than 20 years old), TT\u003csub\u003e20-40\u0026nbsp;\u003c/sub\u003e(terraced tea plantations aged 20-40 years), TT\u003csub\u003e\u0026gt;40\u0026nbsp;\u003c/sub\u003e(terraced tea plantations older than 40 years) and NF (natural forest) as control. Three subplots (10 m \u0026times; 10 m) were set up at each site and a totally of 63 samples were collected.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe study area is located in a typical rocky mountainous region, characterized by shallow soil layers (Zhang et al., 2013). To determine the sampling depth, we observed the soil profiles and found that the soil layer below 20 cm contains high gravel content, making it difficult to sample. Besides, considering that the surface soil is the layer most strongly affected by woody crop cultivation activities, we selected 0\u0026ndash;20 cm layer for sampling. Mixed soil samples were collected using a stainless-steel auger, which were stored in plastic bags before being transported to the laboratory for analysis. Undisturbed soil samples were collected for soil aggregate analysis. The sampling strategy was consistent across sites with similar aspects, slopes and altitudes, although some site conditions varied slightly due to the practical limitation of finding locations with identical conditions in the field (Fig. 1).\u003c/p\u003e\n\u003ch2\u003e2.2 Litter and root sampling \u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eLitter characteristics were assessed using three randomly established 1 m \u0026times; 1 m quadrats per plot. Litter cover was visually estimated as the percentage of soil surface covered by dead organic debris (De Stefano et al., 2021). Litter thickness was measured with a ruler to an accuracy of 0.5 mm. For root trait analysis, soil cores were collected using a cylindrical auger (5.3 cm height \u0026times; 5.0 cm diameter). Roots were separated from the soil using a 5 mm mesh sieve and then gently washed in water-filled basins to remove soil particles and debris. Root morphology was analyzed using the WinRHIZO root analysis system. Parameters including root length density (RLD; mm (100 cm\u003csup\u003e3\u003c/sup\u003e)\u003csup\u003e\u0026ndash;1\u003c/sup\u003e), root surface area (RSA; cm\u0026sup2;) and root volume (RV; cm\u0026sup3;) were measured. Finally, roots were oven-dried at 75 \u0026deg;C for 48 hours and weighed to determine root biomass (RB) (Liu et al., 2020).\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003e2.3 Aggregate fractionation and stability analysis\u003c/h2\u003e\n\u003cp\u003eThe undisturbed air-dried soils were fractionated with dry-sieving (2, 1, 0.5, 0.25 mm sieves) method using a mechanical shaker (60 oscillations/min, 2 min). Soil retained on each sieve was collected and weighed to calculate the mass fraction of each size class. The nutrient content of each aggregate fraction, including organic carbon, total nitrogen, and total phosphorus, was then determined. Soil aggregate stability\u0026nbsp;was evaluated through: (1) mean weight diameter (MWD), (2) geometric mean diameter (GMD), and (3) the mass fraction of aggregates \u0026gt;0.25 mm (R\u003csub\u003e\u0026gt;0.25\u003c/sub\u003e), calculated according to standard equations (1-3) (Am\u0026eacute;zketa, 1999; Nimmo \u0026amp; Perkins, 2002):\u003c/p\u003e\n\u003cp\u003e\u003cimg 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\"\u003e\u003c/p\u003e\n\u003cp\u003eWhere \u003cem\u003ex\u003csub\u003ei\u0026nbsp;\u003c/sub\u003e\u003c/em\u003e(mm) is the mean diameter of each aggregate size, \u003cem\u003ew\u003csub\u003ei\u003c/sub\u003e\u0026nbsp;\u003c/em\u003e(%) is the mass percentage of \u003cem\u003ei\u003c/em\u003e-sized aggregates,\u003cem\u003e\u0026nbsp;m\u003csub\u003e0.25\u003c/sub\u003e\u003c/em\u003e\u003csub\u003e\u0026nbsp;\u003c/sub\u003e(mm), and \u003cem\u003em\u003csub\u003et\u003c/sub\u003e\u003c/em\u003e (g) is the total soil mass.\u003c/p\u003e\n\u003cp\u003eThe dry-sieving method was used as it retains labile nutrients more effectively than wet sieving. Wet sieving can cause loss of water-soluble C and N, disrupt microbial habitats, and underestimate nutrient pools in soil aggregates\u0026nbsp;(Sainju, 2006; Sarkhot et al., 2007; Felde et al., 2021).This method is particularly suitable for coarse-textured subtropical soils, such as those in the present study (Table 2), which are characterized by low clay contents (\u0026lt;10%) and weak aggregation\u0026nbsp;(Bruand et al., 2005; Sun et al., 2024). Additionally, dry-sieving \u0026nbsp;is easier to perform and provides a reliable assessment of how land management and plantation age influence nutrient distribution within the soil aggregate in the long-term\u0026nbsp;(Xu et al., 2017).\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003e2.4 Soil properties analysis\u003c/h2\u003e\n\u003cp\u003eMixed soil samples were air dried and passed 2 mm and 0.25 mm sieves, respectively, for chemical properties analysis. Soil organic carbon (SOC) and total nitrogen (TN) were measured by Vario Macro Cube elemental analyzer (Elementar Trading Shanghai, China). Total phosphorus (TP) was determined using the molybdenum blue colorimetric method. Soil pH was measured in a (soil-to-water: 1:2.5) suspension using a calibrated pH meter. We determined cation exchange capacity (CEC) through ammonium acetate extraction followed by HCl titration. Available phosphorus (AP) was extracted using 0.5M NaHCO\u003csub\u003e3\u003c/sub\u003e and quantified via molybdenum blue colorimetry. Available potassium (AK) was extracted with 1M ammonium acetate and analyzed by flame photometry. Available nitrogen (AN) was measured using alkaline hydrolysis (Rayment \u0026amp; Lyons, 2011). Microbial biomass carbon (MBC) and nitrogen (MBN) were analyzed following the chloroform fumigation-extraction protocol (Vance et al., 1987). Soil texture was measured with Microtrac S3500 laser particle size analyzer (Microtrac Inc., USA) (\u0026Scaron;inkovičov\u0026aacute; et al., 2017).\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003e2.5 Statistical analysis\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eAll statistical analyses were performed using SPSS 26.0 (https://www.ibm.com/analytics/spss-statistics-software). Data normality (Shapiro-Wilk) and homogeneity (Levene\u0026rsquo;s test) were tested prior to conducting analysis of variance (ANOVA). One-way ANOVA followed by Tukey\u0026rsquo;s HSD test (\u0026alpha; = 0.05) was applied to compare across the seven treatments, and across the aggregate fractions within each treatment. Pearson\u0026apos;s correlation analysis was employed to evaluate the relationships between various indicators. Partial Least Squares Path Modeling (PLS-PM) was conducted using the \u0026ldquo;plspm\u0026rdquo; package in R to identify the primary pathways from predictor variables to response variables (Li et al., 2023). The overall model quality and performance were assessed using the goodness-of-fit (GOF) index. To evaluate the stability and significance of the path coefficients, 1,000 bootstrap were performed (Chen et al., 2024). The general linear model (GLM) was employed to determine the variation in soil properties explained by land management and plantation age. Origin 8.0 (https://www.originlab.com/) was used for graph preparation.\u003c/p\u003e"},{"header":"3. Results","content":"\u003ch2\u003e3.1 Basic soil properties\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eThe conversion of NF to tea plantations significantly altered soil properties (Table 2). Soil texture was significantly affected by long-term tea cultivation. The variation in sand and silt content was predominantly controlled by LM (p\u0026lt;0.0001), contributing 47.0% of the variance for each (Table 4). Consequently, TT\u003csub\u003e\u0026gt;40\u003c/sub\u003ehad the highest sand content (73.48%) and the lowest silt content (26.40%), forming a significant contrast with NF and ST\u003csub\u003e\u0026gt;40\u003c/sub\u003e.\u003c/p\u003e\n\u003cp\u003eSoil pH ranged from 4.5 to 5.6 in the study area. Soil pH was primarily governed by LM\u0026times;PA interactions (p \u0026lt; 0.0001), causing the decline of pH with plantation age, particularly at ST\u003csub\u003e20\u0026ndash;40\u003c/sub\u003e and TT\u003csub\u003e\u0026gt;40\u003c/sub\u003e. Similarly, CEC was most strongly influenced by PA (p \u0026lt; 0.0001, 57.8% contribution), leading to a significant decrease in all old tea plantations regardless of the management system compared to NF and TT\u003csub\u003e\u0026lt;20\u003c/sub\u003e.\u003c/p\u003e\n\u003cp\u003eSoil available nutrients exhibited contrasting patterns. AK was mainly controlled by PA (p \u0026lt; 0.0001, 52.8% contribution), with sloping tea plantation generally maintaining higher concentrations than terraced tea plantation. For AN, LM was the dominant factor (p \u0026lt; 0.0001, 51.4% contribution), resulting in a significant accumulation in the ST\u003csub\u003e\u0026gt;40\u003c/sub\u003e compared to NF. In contrast, AP variation was distributed more evenly among LM, PA, and their interaction, all being highly significant (p \u0026lt; 0.0001). This led to consistently higher AP levels in terraced tea across all age classes, with TT\u003csub\u003e\u0026lt;20\u003c/sub\u003e and TT\u003csub\u003e\u0026gt;40\u003c/sub\u003e having 74-165% higher AP concentrations than NF.\u003c/p\u003e\n\u003cp\u003eMBC was overwhelmingly driven by PA (p \u0026lt; 0.0001), which alone explained 79.9% of its variance. In contrast, the variation in MBN was predominantly explained by the interactive effects (p \u0026lt; 0.0001, 58.8% contribution), resulting in the highest MBC and MBN atTT\u003csub\u003e20-40\u003c/sub\u003e.\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003e3.2 Root and litter characteristics\u003c/h2\u003e\n\u003cp\u003eRoot and litter characteristics showed clear differences between LM and PA (Table 3). Root system development responded strongly to land management. RLD was significantly influenced by LM (p = 0.003), which was the dominant factor contributing 30.4% of the observed variance (Table 4). Consequently, all terraced tea plantations and ST\u003csub\u003e\u0026gt;40\u003c/sub\u003e yielded significantly higher RLD values compared to NF. In contrast, RSF was predominantly controlled by LM\u0026times;PA interactions (p \u0026lt; 0.0001), which explained 48.8% of its variance. This interactive effect was evident as the TT\u003csub\u003e\u0026gt;40\u003c/sub\u003e had the largest RSF (234.16 cm\u0026sup2;), significantly surpassing all other treatments. The NF maintained the highest RV, which was significantly greater than that in most young and mid-term tea plantations. However, the factors included in the GLM model (LM, PA, LM\u0026times;PA) had limited explanatory power for RV (Table 4). For RB, ST\u003csub\u003e\u0026gt;40\u003c/sub\u003e had the highest value, which was significantly greater than all other treatments, including NF. The GLM indicated that both LM and PA significantly affected RB, though the individual and interactive contributions were relatively modest (Table 4).\u003c/p\u003e\n\u003cp\u003eLitter accumulation was severely impacted by forest-to-tea conversion. Both LC and LT were significantly lower in all tea plantations compared to NF (Table 3). The recovery patterns were governed by the LM. In sloping plantations, both LC and LT remained low across all ages. In contrast, TT exhibited a clear recovery over time, with the interactive effect being the most important factor for LC (44.0% contribution). Consequently, LC in TT\u003csub\u003e\u0026gt;40\u003c/sub\u003e was significantly greater than in TT\u003csub\u003e\u0026lt;20\u003c/sub\u003e and all sloping plantations. Meanwhile, PA alone was the dominant factor controlling LT, explaining 56.6% of its variance.\u003c/p\u003e\n\u003ch2\u003e3.3 Soil aggregate size distributions and stability\u003c/h2\u003e\n\u003cp\u003eSoil aggregate size distribution and stability were significantly influenced by the conversion of NF to tea plantations (Fig. 2). The \u0026gt;2 mm and \u0026lt;0.25 mm fractions were the dominant sizes in all treatments, while 0.5-0.25 mm fraction consistently represented the smallest proportion. Forest-to-tea plantation conversion caused the decline of \u0026gt;2 mm aggregate fraction, with terraced tea at TT\u003csub\u003e\u0026lt;20\u0026nbsp;\u003c/sub\u003eand TT\u003csub\u003e\u0026gt;40\u003c/sub\u003e showing reductions of 16.7% and 17.5%, respectively, compared to NF (p \u0026lt; 0.05). GLM analysis confirmed that this fraction was significantly affected by both LM (p = 0.029) and PA (p= 0.005), with PA being the dominant factor (45.1% contribution) (Table 4). The 2-1 mm fraction was predominantly controlled by LM\u0026times;PA interactions (p = 0.001), which explained 53.2% of its variance (Table 4). Notably, ST\u003csub\u003e\u0026gt;40\u003c/sub\u003e contained 28.3% more 2-1 mm aggregates than NF. In contrast, the distribution of the 1-0.5 mm and 0.5-0.25 mm fractions was mainly governed by LM (p \u0026lt; 0.0001), which contributed over 75% and 80% of the variance, respectively (Table 4). Consequently, terraced tea generally accumulated a higher proportion of the intermediate fractions compared to ST. The microaggregate (\u0026lt;0.25 mm) fraction was also primarily influenced by LM (p \u0026lt;0.0001, 62.9% contribution). ST consistently resulted in a higher proportion of microaggregates than terrace systems (Fig. 2).\u003c/p\u003e\n\u003cp\u003eThe mass fraction of aggregates \u0026gt;0.25 mm (R\u003csub\u003e\u0026gt;0.25mm\u003c/sub\u003e) was significantly affected by LM (p \u0026lt; 0.0001, 63.2% contribution), with TT\u003csub\u003e20\u0026ndash;40\u003c/sub\u003e showing an 8.14% increase compared to NF. The stability indices MWD and GMD were most strongly driven by the LM\u0026times;PA interactions, which explained 58.7% and 72.0% of their variance, respectively (Table 4). Among all treatments, ST\u003csub\u003e\u0026gt;40\u003c/sub\u003e had the highest MWD and GMD values, whereas in terraced tea, aggregate stability generally decreased with increasing PA (Fig.3).\u003c/p\u003e\n\u003ch2\u003e3.4 SOC, TN, TP contents and their stoichiometry ratios in bulk soil and soil aggregates\u003c/h2\u003e\n\u003cp\u003eThe distribution of SOC, TN, and TP between bulk soil and aggregate fractions varied significantly across land management and plantation ages (Fig. 4). In bulk soil, the conversion of NF to tea plantations generally reduced SOC, TN, and TP contents, with the most pronounced depletion observed at TT\u003csub\u003e\u0026lt;20\u003c/sub\u003e. In contrast, ST\u003csub\u003e\u0026gt;40\u003c/sub\u003e maintained the highest levels of SOC and TN among tea plantation treatments. Within soil aggregates, the distribution patterns of SOC, TN and TP varied with aggregate size (Fig. 4). Generally, the highest SOC and TN contents were found in 1-0.5 mm and 0.5-0.25 mm fractions, while the lowest values typically shown in the \u0026lt;0.25 mm fraction. TT\u003csub\u003e20-40\u003c/sub\u003e showed notably high SOC content in the 0.5-0.25 mm fraction, reaching 29.73 g kg⁻\u0026sup1; (Fig. 4a). For TN content, NF maintained relatively high values in the 0.5-0.25 mm fraction (Fig. 4b). ST\u003csub\u003e\u0026gt;40\u003c/sub\u003e showed the highest TN content among tea treatments. NF maintained the highest TP content in macroaggregate fractions (\u0026gt;0.25 mm), while terraced tea generally showed higher TP levels than sloping tea of similar age (Fig. 4c).\u003c/p\u003e\n\u003cp\u003eIn bulk soil, the C:N ratio ranged from 7 to 11 across treatments, with the highest value found in ST\u003csub\u003e\u0026lt;20\u003c/sub\u003e (Fig. 5a). In contrast, the soil C:P and N:P ratios were significantly higher in ST\u003csub\u003e\u0026gt;40\u003c/sub\u003e and TT\u003csub\u003e20\u0026ndash;40\u003c/sub\u003e treatments, increasing by more than 140% and 180%, respectively (Fig. 5b and c). Within soil aggregates, the stoichiometric ratios exhibited size-dependent patterns (Fig. 5). The C:N ratio generally showed less variation among aggregate sizes (Fig. 5a). The C:P ratio was consistently higher in the TT\u003csub\u003e20-40\u003c/sub\u003e and ST\u003csub\u003e\u0026gt;40\u003c/sub\u003e treatments compared to other treatments across all aggregate fractions (Fig. 5b). In contrast, TT\u003csub\u003e\u0026lt;20\u003c/sub\u003e maintained the lowest C:P ratios across all aggregate fractions, with values below 2 in all fractions. The highest C:P and N:P ratios were consistently observed in the 0.5-0.25 mm fraction across tea plantation treatments (Fig. 5b and c). However, NF had C:P ratios ranging from 2.01 to 5.84, with the highest value in the \u0026lt;0.25 mm fraction.\u003c/p\u003e\n\u003cp\u003eThe relative importance of the driving factors was further quantified by GLM analysis (Table 5). Notably, the interaction between land management and plantation age (LM\u0026times;PA) was the most significant and dominant factor, explaining the largest portion of the variance for SOC, TN, and TP in almost all aggregate fractions. Plantation age independently showed a strong influence, especially on TP and the stoichiometric ratios. Furthermore, a significant PA effect was detected for SOC in the largest \u0026gt;2 mm and \u0026lt;0.25 mm aggregate fractions. While LM showed some significant effects on certain variables in specific fractions, its overall influence was not as strong as the interaction effect or the effect of PA.\u003c/p\u003e\n\u003ch2\u003e3.5 Relationships among root, litter, soil nutrients stoichiometry, and aggregate stability\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eCorrelation analysis revealed a network of significant associations among measured variables (Fig. 6). Aggregate stability indices (R\u003csub\u003e\u0026gt;0.25\u003c/sub\u003e, MWD, GMD) were strongly positively correlated with each other. These stability indices showed positive correlations with SOC, TN, and the stoichiometric ratios C:P and N:P. They were also positively correlated with MBC, MBN, and RLD. In contrast, MWD and GMD were negatively correlated with LC. SOC and TN were positively correlated with the C:P and N:P ratios. Both C:P and N:P ratios showed significant positive correlations with MBN, and silt content, but significant negative correlations with TP, CEC, and sand content. Root biomass was positively correlated with MWD, GMD, SOC, TN, AN, and N:P. Aggregate-associated TN was strongly positively correlated with MWD and GMD in the \u0026gt;2 mm and 2\u0026ndash;1 mm fraction. Across nearly all aggregate fractions, SOC and TN showed significant positive correlations with bulk soil SOC, TN, C:P, pH, N:P, RV, and RB (Table 6). Aggregate-associated TP was negatively correlated with C:P, N:P, MBN, CEC, silt, and clay, but positively correlated with bulk soil TP and sand content in most fractions (Table 7). Aggregate-associated C:P and N:P ratios were positively related to SOC, MBN, and silt, but negatively correlated with TP, CEC, and sand across most aggregate sizes (Table 7).\u003c/p\u003e\n\u003cp\u003eThe Partial Least Squares Path Modeling (PLS-PM) elucidated the direct and indirect pathways governing soil aggregate stability (GMD) and bulk soil C:N:P stoichiometry (Fig. 7). GMD was simultaneously and directly influenced by the content of different aggregate fractions. Specifically, the 2-1 mm macroaggregates exerted a strong positive effect (path coefficient = 0.52), whereas an increase in the \u0026lt;0.25 mm microaggregates significantly reduced stability (path coefficient = -0.65; p \u0026lt; 0.05). Land management showed significant indirect negative effects on aggregate stability, mediated through multiple pathways: (1) a negative effect via reducing RB, 2-1 mm macroaggregates and \u0026lt;0.25 mm microaggregates; and (2) a positive effect via increasing microbial biomass (MBC and MBN). Land management practice negatively affected both aggregate-associated nutrients (path coefficient = -0.38; p \u0026lt; 0.05) and bulk soil nutrients (path coefficient = -0.39; p \u0026lt; 0.01), thereby lowered stoichiometry. Plantation age (PA) increased root biomass (path coefficient = 0.38; p \u0026lt; 0.05), bulk soil nutrients (path coefficient = 0.33; p \u0026lt; 0.01), and aggregate-associated nutrients (path coefficient = 0.46; p \u0026lt; 0.01), which collectively enhanced microbial biomass (path coefficient = 0.74; p \u0026lt; 0.01). These improvements decreased the proportion of microaggregates (path coefficient = -0.47; p \u0026lt; 0.01), resulting in a positive indirect impact on GMD. Soil C:N:P stoichiometry was significantly increased by both aggregate-associated and bulk soil nutrients, which played a positive mediating role, linking management- and age-driven changes to aggregate stability.\u003c/p\u003e"},{"header":"4. Discussion","content":"\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e4.1. Effects of forest-to-tea conversion on soil texture and aggregate stability\u003c/h2\u003e \u003cp\u003eIn this study, we found that the \u0026gt;\u0026thinsp;2 mm aggregate fraction was dominant in all treatments and controlled mainly by PA (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e; Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e4\u003c/span\u003e). This predominance is likely attributable to the local granite-derived parent material, which yields a sandy loam texture that provides raw materials for the formation of large macroaggregates (\u0026gt;\u0026thinsp;2mm) (Wei et al., \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Wu et al., \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Furthermore, the release of reactive secondary clays and Fe/Al oxides during weathering promotes organo-mineral association, thereby enhancing the stability of these large aggregates (Ge et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Liu et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eConversion of forest to tea plantation introduced human disturbances, which reduced the proportion of the \u0026gt;\u0026thinsp;2 mm fraction, especially in TT\u003csub\u003e\u0026lt;\u0026thinsp;20\u003c/sub\u003e, likely due to the intense disturbance during terrace construction ((Xue et al., \u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The recovery of this fraction in mid-age plantations (ST\u003csub\u003e20\u0026minus;40\u003c/sub\u003e, TT\u003csub\u003e20\u0026minus;40\u003c/sub\u003e) coincided with higher litter inputs (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e3\u003c/span\u003e), which provided organic binding agents for large aggregate formation (Wang et al., \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The subsequent decline in the oldest plantations (\u0026gt;\u0026thinsp;40 years) may be attributed to soil compaction from long-term management, which disrupts pore networks and negatively impacts the microbial habitat and the production of binding agents (Frene et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Zhan, \u003cspan citationid=\"CR89\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eLand management practice had a dominant and lasting control over the finer aggregate fractions (\u0026lt;\u0026thinsp;1 mm), thereby engineering the fundamental structure of the soil (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e4\u003c/span\u003e). ST favored the accumulation of microaggregates (\u0026lt;\u0026thinsp;0.25 mm), while the terraced tea promoted the formation of intermediate-sized aggregates (1-0.25 mm). This management-driven divergence was vital, as it physically predefines the potential niches for soil organic matter stabilization and nutrient sequestration. The accumulation of the 2\u0026thinsp;\u0026minus;\u0026thinsp;1 mm fraction in ST\u003csub\u003e\u0026gt;\u0026thinsp;40\u003c/sub\u003e, likely driven by high root biomass (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e3\u003c/span\u003e) and its associated organic binding processes (Sarker et al., \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Cai et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), was a key factor leading to its superior aggregate stability (highest MWD and GMD). The 2\u0026thinsp;\u0026minus;\u0026thinsp;1 mm fraction, being highly sensitive to the LM\u0026times;PA interaction, thus serves as a dynamic indicator of the balance between soil disturbance and biological recovery processes.\u003c/p\u003e \u003cp\u003eA key finding lied in the differential response of stability indicators. Despite the R\u003csub\u003e\u0026gt;\u0026thinsp;0.25\u003c/sub\u003e remaining statistically similar between NF and sloping tea, the significant increase in the MWD and GMD in ST\u003csub\u003e\u0026gt;\u0026thinsp;40\u003c/sub\u003e revealed a qualitative improvement in aggregate stability that was not captured by macroaggregate content alone. This enhancement in aggregate stability aligned with the extensive root biomass in ST\u003csub\u003e\u0026gt;\u0026thinsp;40\u003c/sub\u003e (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e3\u003c/span\u003e), as roots and their associated fungal networks help create stable soil structures that resist hydraulic disruption (Negi et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). The turnover of larger aggregates into smaller but more stable units could potentially explain these temporal patterns, where long-term biological processes gradually build quality over quantity (Bai et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Notably, our GLM analysis confirmed that the LM \u0026times; PA interaction was the dominant force governing aggregate stability (MWD and GMD), highlighting that the development of a stable soil structure is an outcome of management practices interacting with ecosystem development over time.\u003c/p\u003e \u003cp\u003eLong-term management also induced fundamental shifts in bulk soil texture that have profound implications for soil functioning(Panagea et al., \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Notably, terrace management developed the coarser texture, whereas sloping management showed finer texture among tea plantations (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The observed textural coarsening in older terraces likely reflects the cumulative effects of water-induced selective removal of fine particles and their redistribution within the terrace landscape over decades of cultivation(Li \u0026amp; Lindstrom, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2001\u003c/span\u003e;Zhang et al., \u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). These textural shifts have important functional consequences: sandier soils in old terraces face reduced water and nutrient retention capacity, while finer-textured slopes may become increasingly susceptible to surface sealing and erosion. This divergence in physical properties represents a fundamental pedogenetic differentiation driven by management practice.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e4.2. Effects of land management and plantation age on bulk soil nutrients and stoichiometry\u003c/h2\u003e \u003cp\u003eFollowing the conversion of NF to tea plantations, aggregate-associated SOC, TN, TP and C:N:P ratios were profoundly influenced by land management practices and plantation age. Our study revealed that SOC and TN content recovered to levels comparable to NF in ST\u003csub\u003e\u0026gt;\u0026thinsp;40\u003c/sub\u003e and TT\u003csub\u003e20\u0026minus;40\u003c/sub\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea-b). This finding aligned with previous studies demonstrating that SOC and TN content increase with plantation age (Zhu et al., \u003cspan citationid=\"CR101\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Zhou et al., \u003cspan citationid=\"CR99\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). As tea plantations mature, ecosystems may recover from initial disturbances and reach a new equilibrium(Chiti et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2018\u003c/span\u003e;Wang et al., \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2020b\u003c/span\u003e). This recovery could be associated with the development of tea root systems and the accumulation of litter over time. The expansion of belowground root networks and the gradual buildup of aboveground litter increase organic inputs, stimulating microbial activity and improving nutrient cycling (Naresh et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Nair et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Moreover, the enhancement of aggregate stability in older plantation provides physical protection for SOC and TN against decomposition (Bhaduri et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). In the present study, the recovery of aggregate stability (MWD, GMD) was positively correlated with the accumulation of SOC and TN (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). Compared to sloping plantations, terrace management facilitated faster recovery of SOC and TN, particularly in TT\u003csub\u003e20\u0026minus;40\u003c/sub\u003e. This faster recovery was probably due to terracing's structural advantages, which effectively reduce soil erosion, improve moisture retention, and promote organic matter accumulation (Qiu et al., \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). In this study, the C:N ratio remained relatively stable across treatments. As structural components, the accumulation and turnover of C and N are relatively stable and coupled (Zhang et al., \u003cspan citationid=\"CR91\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Carbon and nitrogen are closely linked, and their responses to environmental changes tend to follow similar patterns. A positive correlation between C and N was observed in both bulk soil and aggregate fractions (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e and Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e), consistent with findings by Zhang et al.(2019b).\u003c/p\u003e \u003cp\u003eThe conversion from NF to tea plantation significantly decreased TP content, which continued to decline in both management systems with increasing plantation age, particularly in ST\u003csub\u003e\u0026gt;\u0026thinsp;40\u003c/sub\u003e and TT\u003csub\u003e20\u0026minus;40\u003c/sub\u003e. This aligns with findings by Wang et al. (\u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) and highlights the profound and long-lasting P loss due to forest-to-tea conversion. The continuous depletion of TP in long-term tea plantations was likely due to plant uptake, as the harvesting of tea leaves results in significant and often irreversible removal of P from the soil system (Dang, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). The substantial increases in C:P and N:P ratios in TT\u003csub\u003e20\u0026minus;40\u003c/sub\u003e and ST\u003csub\u003e\u0026gt;\u0026thinsp;40\u003c/sub\u003e further indicated P limitation in tea plantations. The lower TP content and elevated C:P and N:P ratios in TT\u003csub\u003e20\u0026minus;40\u003c/sub\u003e might be attributed to the rapid release of organic matter in terrace systems, which is facilitated by enhanced water retention and reduced erosion, without proportional replenishment of P. Chen \u0026amp; Lin, (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) found that although terracing reduces P loss via runoff, the retained P is prone to rapid immobilization. This occurs primarily due to the precipitation of phosphate into insoluble Fe/Al compounds in the acidic, iron- and aluminum-rich soils typical of tea plantations (Ruan et al., \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). Unlike terrace systems, sloping plantations experienced greater long-term P losses, resulting primarily from topsoil erosion driven by natural rainfall (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ec). Thus, while C and N accumulate more slowly on slopes, the long-term loss of P and limited replenishment lead to elevated C:P and N:P ratios.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e4.3 Aggregate-associated nutrient distribution and its functional significance\u003c/h2\u003e \u003cp\u003eThe distribution patterns of nutrients within different aggregate size fractions provide critical insights into the mechanisms of soil carbon stabilization and nutrient cycling (Sbih et al., \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Chen et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). In this study, we observed that aggregate-associated SOC, TN, and TP concentrations generally increased with decreasing aggregate size, with the highest values consistently found in the 0.5\u0026thinsp;\u0026minus;\u0026thinsp;0.25 mm fraction across most treatments (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). This pattern aligned with the microaggregate-based stabilization mechanism, where organic matter becomes progressively enriched in finer fractions through the formation of stable organo-mineral complexes (Totsche et al., \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; von L\u0026uuml;tzow et al., \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2007\u003c/span\u003e).The 0.5\u0026thinsp;\u0026minus;\u0026thinsp;0.25 mm fraction represents a critical transitional zone in the aggregate hierarchy that balances physical protection with biological accessibility (Yudina \u0026amp; Kuzyakov, \u003cspan citationid=\"CR88\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eNotably, this enrichment pattern was consistent across both management systems and all plantation ages, suggesting that the fundamental mechanism of nutrient stabilization within aggregates is robust to land-use change and management practices. However, the magnitude of nutrient enrichment varied significantly among treatments. TT\u003csub\u003e20\u0026minus;40\u003c/sub\u003e exhibited the highest SOC and TN concentrations in the 0.5\u0026thinsp;\u0026minus;\u0026thinsp;0.25 mm fraction (29.73 g kg⁻\u0026sup1; and 2.45 g kg⁻\u0026sup1;, respectively), coinciding with its peak microbial biomass and optimal aggregate stability. This indicated that the mid-term terrace system created particularly favorable conditions for the formation of nutrient-rich microaggregates through enhanced microbial processing of organic matter (Costa et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). In contrast, ST\u003csub\u003e\u0026gt;\u0026thinsp;40\u003c/sub\u003e showed relatively lower nutrient concentrations in this key fraction despite having high root biomass, suggesting that the stress-induced root strategy may produce organic inputs of lower quality that are less effectively incorporated into stable microaggregates (Lehmann et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe stoichiometric ratios within aggregate fractions revealed additional insights into nutrient limitation patterns at the micro-scale (Cui et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Zhang et al., \u003cspan citationid=\"CR92\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).The C:P and N:P ratios were consistently highest in the 0.5\u0026thinsp;\u0026minus;\u0026thinsp;0.25 mm fraction across all treatments, with particularly elevated values in TT\u003csub\u003e20\u0026minus;40\u003c/sub\u003e (C:P: 8.68; N:P: 0.91) and ST\u003csub\u003e\u0026gt;\u0026thinsp;40\u003c/sub\u003e (C:P: 7.51; N:P: 0.83) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). This indicated that P limitation was most pronounced in the most biologically active aggregate fraction, which hosts the majority of microbial biomass and mediates nutrient turnover (Liu et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). The enrichment of P-depleted organic matter in this fraction suggests that microbial communities actively process and transform organic materials but are constrained by P availability, leading to the accumulation of organic matter with high C:P ratios (Feng et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).This micro-scale phosphorus limitation may, in turn, feedback to constrain microbial growth efficiency and the production of aggregate-stabilizing agents. The GLM analysis further revealed that the interaction between land management and plantation age was the dominant factor controlling SOC and TN concentrations in most aggregate fractions (contributing 46.4\u0026ndash;81.4% of variation), while plantation age alone was the primary driver for TP variation in smaller fractions (35.5\u0026ndash;35.7% contribution) (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThis distinction highlighted a fundamental difference in the cycling of C:N versus P at the aggregate scale: C and N dynamics are tightly coupled to the integrated effects of management history and ecosystem development, reflecting their dependence on biological processes (e.g., organic matter inputs and microbial processing). In contrast, phosphorus dynamics in smaller aggregates are primarily governed by time-dependent processes, including weathering, leaching, and gradual depletion through plant uptake, which function largely independently of specific management practice (Walker \u0026amp; Syers, \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e1976\u003c/span\u003e; Crews et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e1995\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe 0.5\u0026thinsp;\u0026minus;\u0026thinsp;0.25 mm aggregates fraction functioned as \"microbial hotspots\" where organic matter, microorganisms, and mineral surfaces interact closely, creating ideal conditions for enzymatic processing and nutrient cycling (Kuzyakov \u0026amp; Blagodatskaya, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). This aggregate size class offers critical physical protection. Its dimensions are small enough to restrict oxygen diffusion and predator entry, yet large enough to sustain pore connectivity. Consequently, it creates suitable conditions for microbial activity and organic matter stabilization (Six et al., \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). The consistent enrichment of nutrients in this fraction across all treatments underscores its fundamental importance in soil functioning and suggests that management strategies aimed at promoting the formation and stability of 0.5\u0026thinsp;\u0026minus;\u0026thinsp;0.25 mm aggregates could enhance both C sequestration and nutrient availability in the studied soils.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e4.4 Driving factors of aggregate stability and nutrient dynamics after land use change\u003c/h2\u003e \u003cp\u003ePearson correlation and PLS-PM analyses indicate that soil aggregate stability is regulated by aggregate-size distribution, nutrient stoichiometry, microbial activity, and root inputs, consistent with previous studies (Wang et al., \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Li et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Aggregate stability indices (R\u003csub\u003e\u0026gt;\u0026thinsp;0.25\u003c/sub\u003e, MWD, and GMD) were strongly correlated with SOC, TN, and C:P and N:P ratios, highlighting the importance of nutrient availability and stoichiometric balance. Positive relationships between aggregate stability, MBC and MBN, and root length density highlight the contribution of biological binding agents from roots and microbial by-products. Additionally, PLS-PM results indicated that aggregate-size composition is a direct structural determinant of stability. Macroaggregates (2\u0026thinsp;\u0026minus;\u0026thinsp;1 mm) showed a strong positive effect on GMD, while microaggregates (\u0026lt;\u0026thinsp;0.25 mm) have a pronounced negative indirect effect, indicating structural degradation.\u003c/p\u003e \u003cp\u003eThe contrasting root foraging strategies observed between the two management practices provide a mechanistic basis for understanding these patterns. Terrace plantations developed an \"efficient foraging strategy,\" characterized by high root surface area with moderate root biomass, which maximizes soil exploration per unit carbon invested (Comas et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Lynch, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). This strategy, combined with significant litter recovery (litter cover\u0026thinsp;\u0026gt;\u0026thinsp;67% in TT\u003csub\u003e20\u0026minus;40\u003c/sub\u003e and TT\u003csub\u003e\u0026gt;\u0026thinsp;40\u003c/sub\u003e), created an \"aboveground-belowground coupling\" that enhanced organic matter input and stimulated microbial activity (Wardle et al., \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). Whereas, sloping plantations exhibited a \"stress-induced foraging strategy,\" with exceptionally high root biomass but only moderate root surface area (Poorter et al., \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Notably, this high root investment occurred without corresponding litter recovery, with litter cover remaining persistently low (\u0026lt;\u0026thinsp;35%) across all sloping plantations (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e3\u003c/span\u003e). This decoupling between belowground carbon investment and aboveground litter input represents a fundamental inefficiency in carbon allocation that helps explain the slower recovery of soil properties in sloping systems.\u003c/p\u003e \u003cp\u003eLand management directly enhanced microbial biomass but had direct negative effects on microaggregate, macroaggregate, root biomass, aggregate-associated nutrient and bulk soil nutrient. This pattern likely reflects the mechanical disturbance associated with terrace construction, which disrupts soil aggregate hierarchy and redistributes aggregate size fractions (He et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Aggregate breakdown exposes previously protected organic matter, increases soil aeration and permeability, and accelerates nutrient losses, while temporarily enhancing microbial biomass through increased substrate accessibility (Six et al., \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2000\u003c/span\u003e). The negative effects of land management on both aggregate-associated and bulk soil nutrients lead to reduced C:N:P stoichiometry, which plays a central role in regulating microbial metabolism. Stoichiometric imbalance limits microbial growth efficiency, compelling microbes to allocate a greater proportion of assimilated carbon to maintenance respiration rather than to the synthesis of persistent binding agents, such as glomalin and extracellular polysaccharides, that stabilize microaggregates and facilitate macroaggregate formation (Li et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Redmile-Gordon et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003ePlantation age had negative direct effects on microbial biomass, this might be due to increase of soil acidification as plantation age increased (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), at which accumulation of aluminum and antimicrobial substance (Phenolics and polyphenols) likely caused a decline in microbial biomass and activity (H. Li et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). However, plantation age indirectly promoted microbial biomass by increasing bulk-soil and aggregate-associated nutrient pools and improving C:N:P stoichiometric balance, thereby enhancing microbial growth efficiency. Additionally, increasing planation age increased root biomass which negatively affects microaggregates. This biologically driven pathway reduced the proportion of microaggregates and indirectly increased GMD, indicating progressive structural recovery with plantation age.\u003c/p\u003e \u003cp\u003eA particularly striking finding was the \"N paradox\" observed in ST\u003csub\u003e\u0026gt;\u0026thinsp;40\u003c/sub\u003e, which exhibited the highest AN concentration among all treatments (157.89 mg kg⁻\u0026sup1;) but simultaneously showed the lowest MBC (0.95 mg kg⁻\u0026sup1;). This decoupling between N availability and microbial activity reveals fundamental constraints on ecosystem functioning in long-term sloping systems. The abundant N likely cannot be effectively utilized due to constraints on microbial growth (Janssens et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Treseder, \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). Several interacting mechanisms may explain this phenomenon. First, C limitation: despite high RB, the stress-induced root strategy in sloping systems may produce root exudates of lower quality, and the absence of litter input limits C availability (Janssens et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Second, physical habitat degradation: unstable soil structure and frequent wet-dry cycles on slopes create unfavorable microhabitats for microbial colonization(Six et al., \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). Third, potential Al toxicity: the acidified conditions (pH as low as 4.50 in ST\u003csub\u003e20\u0026minus;40\u003c/sub\u003e) may release toxic Al\u0026sup3;⁺ that suppresses microbial activity even when N is abundant (Kochian et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; von Uexk\u0026uuml;ll \u0026amp; Mutert, \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e1995\u003c/span\u003e).This N-microbial decoupling demonstrates that nutrient pools alone do not indicate ecosystem health; rather, the connectivity between nutrient availability and biological activity is a more meaningful indicator of soil functionality (Kuzyakov \u0026amp; Blagodatskaya, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSynthesizing these path analyses with the observed patterns of soil properties, root traits, and litter dynamics revealed fundamentally different system-level feedback mechanisms operating under the two management regimes. Terrace systems establish a \"virtuous cycle\": erosion control enables litter recovery (LC\u0026thinsp;\u0026gt;\u0026thinsp;67%), which combined with an efficient root foraging strategy (high RSA, moderate RB) enhances organic matter input and supports robust microbial communities (high MBC/MBN in TT\u003csub\u003e20\u0026minus;40\u003c/sub\u003e). This biological activity, promotes aggregate formation and nutrient cycling, driving the recovery of SOC and TN. However, this cycle contains an inherent vulnerability: the rapid turnover of organic matter without proportional P replenishment, coupled with P fixation in acid soils, leads to progressive P limitation (elevated C:Pand N:P) (Siepel et al., \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). In contrast, sloping systems showed a \"vicious cycle\": persistent erosion prevents litter accumulation (LC consistently\u0026thinsp;\u0026lt;\u0026thinsp;35%), forcing plants into a costly stress-induced root strategy (exceptionally high RB but moderate RSA). This high-carbon investment in roots fails to effectively support microbial communities (lowest MBC despite highest AN), resulting in the nitrogen-microbial decoupling observed in ST\u003csub\u003e\u0026gt;\u0026thinsp;40\u003c/sub\u003e. The absence of litter input and the inefficient root strategy create a \"carbon trap\" where photosynthate is allocated to roots but does not translate into soil carbon accumulation or microbial activity (Cotrufo et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), leading to physical degradation and stoichiometric imbalance. These contrasting feedback mechanisms, elucidated by the PLS-PM analysis, highlight that sustainable management of tea plantations requires not only erosion control but also targeted interventions such as organic amendments and phosphorus-mobilizing practices to disrupt the vicious cycle on slopes and address emerging vulnerabilities in terraces\u003c/p\u003e \u003c/div\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eThe conversion of natural forests to tea plantations initiates divergent trajectories of soil structure and nutrient dynamics that are governed by the interaction between land management and plantation age, thereby supporting our first hypothesis. Partial support was found for our second hypothesis: while terrace systems facilitated faster recovery of aggregate stability and carbon pools through erosion control and efficient root foraging, they simultaneously accelerated P depletion, leading to pronounced stoichiometric imbalance. Contrary to expectations, long-term sloping cultivation did not result in persistent macroaggregate decline. Instead, it developed exceptional mechanical stability through stress-induced root investment, but at the cost of microbial decoupling\u0026mdash;high N availability coexisted with severely suppressed microbial biomass. Critically, across both management systems, progressive P depletion with increasing plantation age emerged as the dominant constraint, with C:P and N:P ratios increasing by more than 140% in older plantations, establishing P as the primary limiting nutrient in these systems. These findings demonstrate that sustainable management must address not only erosion control but also the emerging stoichiometric imbalances\u0026mdash;particularly through targeted P interventions\u0026mdash;to maintain long-term soil health in mountainous tea plantations.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003cbr\u003e\u003c/strong\u003eThe authors gratefully acknowledge the National Natural Science Foundation of China (Grant No. 32071840) and the Key Project of the Ministry of Water Resources (SBJ2018010). The authors also thank Yannan Xu, Yaowen Chang, Wei Lu, Jianpeng Chen, Haiyang Wang and many others for assisting with soil sample collection and analyses.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMaterial preparation, data collection, and analysis were performed by Abdul Hakim Jamshidi, Yaowen Chang, Yi Lu, and Na Jin. Conceptualization and review were performed by Lei Sun, Xia Liu, Di Wu, and Zhaofei Fan. The first draft of the manuscript was written by Abdul Hakim Jamshidi. All authors contributed to the study design, interpretation of data, review and editing of manuscript. Conceptualization, supervision, and project administration were led by Xia Liu and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;This work was supported by the National Natural Science Foundation of China (Grant No. 32071840) and the Key Project of the Ministry of Water Resources (SBJ2018010).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003cbr\u003e\u003cstrong\u003eCompeting interest\u003c/strong\u003e The authors have no competing interests to declare that are relevant to the content of this article.\u003cem\u003e\u003cbr clear=\"all\"\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eAm\u0026eacute;zketa, E. (1999). 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Effects of soil aggregate stability on soil N following land use changes under erodible environment. \u003cem\u003eAgriculture, Ecosystems \u0026amp; Environment\u003c/em\u003e, \u003cem\u003e262\u003c/em\u003e, 18\u0026ndash;28. https://doi.org/10.1016/j.agee.2018.04.012\u003c/li\u003e\n \u003cli\u003eZhu, R., Zheng, Z., Li, T., He, S., Zhang, X., Wang, Y., \u0026amp; Liu, T. (2019). Effect of tea plantation age on the distribution of glomalin-related soil protein in soil water-stable aggregates in southwestern China. \u003cem\u003eEnvironmental Science and Pollution Research\u003c/em\u003e, \u003cem\u003e26\u003c/em\u003e(2), 1973\u0026ndash;1982. https://doi.org/10.1007/s11356-018-3782-4\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTables 1 to 7 are available in the supplementary files section\u003c/p\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":"Forest-to-tea conversion, Soil aggregates, Stoichiometry, P-limitation, Plantation age","lastPublishedDoi":"10.21203/rs.3.rs-9267649/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9267649/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground and Aims\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLand-use conversion from natural forest to agricultural land can profoundly alter soil structure and nutrient dynamics. However, the interactive effects of land management (LM) and plantation age (PA) on soil aggregate stability and C:N:P balance following forest-to-tea conversion remain poorly understood.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003cbr\u003e\nWe investigated aggregate-associated nutrients in sloping (ST) and terraced (TT) tea plantations across a chronosequence (\u0026lt;20, 20-40, \u0026gt;40 years), with adjacent natural forest (NF) as a reference.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003cbr\u003e\nForest-to-tea conversion significantly reduced the proportion of \u0026gt;2 mm aggregate, with terraced plantations at both TT\u003csub\u003e\u0026lt;20\u003c/sub\u003e and TT\u003csub\u003e\u0026gt;40\u003c/sub\u003e showing reductions of 16.7% and 17.5%, respectively, compared to NF. Aggregate stability (MWD and GMD) was strongly governed by the interaction between LM and PA. Among all treatments, ST\u003csub\u003e\u0026gt;40\u003c/sub\u003e exhibited the highest aggregate stability, coinciding with its high root biomass and proportion of 2-1 mm macroaggregates. Aggregate-associated SOC and TN gradually recovered with PA, reaching levels comparable to NF in ST\u003csub\u003e\u0026gt;40\u003c/sub\u003e and TT\u003csub\u003e20–40\u003c/sub\u003e. However, TP declined continuously with PA under both management practice, leading to increases in soil C:P and N:P ratios exceeding 140%, identifying P as the primary limiting nutrient. Path analysis revealed that aggregate stability was directly determined by aggregate-size distribution, with positive effects from 2-1 mm macroaggregates and negative effects from \u0026lt;0.25 mm microaggregates, while nutrient stoichiometry mediated indirect effects of management and age through microbial biomass and root inputs.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e\u003cbr\u003e\nThese findings highlight trade-offs between erosion control and nutrient management in tea plantations, emphasizing the need for age- and practice-specific strategies and P-mobilizing practices to address stoichiometric imbalances in intensively managed subtropical soils.\u003c/p\u003e","manuscriptTitle":"Effect of forest conversion to tea plantations on soil aggregate stability and its stoichiometry of carbon, nitrogen and phosphorus","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-09 07:34:16","doi":"10.21203/rs.3.rs-9267649/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":"83bb8e65-7b6a-4370-8ac5-9befec19e25d","owner":[],"postedDate":"April 9th, 2026","published":true,"recentEditorialEvents":[{"type":"decision","content":"Reject after review","date":"2026-05-09T04:04:16+00:00","index":"","fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-05-09T21:59:48+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-09 07:34:16","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9267649","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9267649","identity":"rs-9267649","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}