Optimizing Belowground Interactions in Young Rubber Tree−Banana Intercropping via Partial Organic Fertilizer Substitution: Root Competition, Soil Nutrients, and Microbial Communities

Optimizing Belowground Interactions in Young Rubber Tree−Banana Intercropping via Partial Organic Fertilizer Substitution: Root Competition, Soil Nutrients, and Microbial Communities | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Optimizing Belowground Interactions in Young Rubber Tree−Banana Intercropping via Partial Organic Fertilizer Substitution: Root Competition, Soil Nutrients, and Microbial Communities Dongqi Jin, Hongzhu Yang, Yujie Tan, Lingxuan Qiu, Binyao Chen, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8835228/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Aims Optimal fertilization strategies for rubber tree-banana intercropping systems and their comprehensive impacts on belowground interactions remain inadequately characterized. This study systematically evaluated the effects of different fertilization regimes on root distribution, interspecific competition, and rhizosphere properties. Methods The experimental design included conventional chemical fertilization (M1), 30% organic nitrogen substitution (M2), 45% controlled-release nitrogen combined with chemical nitrogen (M3), and rubber tree monoculture as control (CK). Results Results demonstrated that the M2 treatment produced the most significant improvements, enhancing rubber tree height by 16.26% and stem girth by 8.66% compared to CK, while simultaneously supporting optimal banana growth within the intercropping system. Detailed analysis of root spatial-temporal distribution revealed that M2 treatment improved root niche complementarity and enhanced system adaptability to subsurface competition. Furthermore, M2 significantly modified rhizosphere microbial community structure by increasing microbial diversity and enriching beneficial bacterial and fungal phyla. These microbial community shifts showed strong positive correlations with improved soil fertility indicators and plant growth performance. Importantly, this fertilization strategy effectively reduced root competition intensity across different soil layers during critical banana developmental stages, including the vigorous growth and bud development phases. Conclusions Our integrated analysis demonstrates that substituting 30% of chemical nitrogen with organic nitrogen represents an optimal fertilization approach, as it simultaneously enhances plant productivity, alleviates belowground competition, and improves soil ecological conditions. Therefore, this study provides a scientifically-grounded and sustainable management strategy for enhancing the productivity and ecological sustainability of rubber tree-banana intercropping systems. Young rubber tree−banana intercropping root spatial and temporal distribution root competition soil nutrients microbial community Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 Figure 12 Figure 13 Figure 14 Figure 15 Introduction Natural rubber, a key polymer material with exceptional properties, is widely utilized across various industrial applications. It is primarily sourced from rubber tree plantations(Oouchi et al. 2019 ; Silva et al. 2023). A significant challenge in global rubber production lies in the fact that rubber trees require an initial growth period of approximately six years before they begin to produce latex, during which no income is generated(Michels et al. 2012 ; Rodrigo et al. 2004 ). To address this income gap in the early stages of rubber production, farmers have adopted intercropping practices, integrating rubber trees with short−term annual and perennial crops such as tea, coffee, and bananas(Rodrigo et al. 2004 ; Wu et al. 2016a ; Yuan et al. 2024 ). Research suggests that native rubber tree agroforestry systems intercropped with other crops not only diversify income streams but also enable multi−variety and multi−level combinations, thereby optimizing resource utilization, including sunlight, soil moisture, and nutrients(Qi et al. 2024 ; Qi et al. 2021 ). Intercropping offers a potentially effective strategy for enhancing farm profitability by increasing crop yields, improving soil fertility, and reducing environmental impact(Li and Lin 2021b ; Yang et al. 2020b ). The full realization of these advantages relies critically on rational nutrient management and its regulation of root systems. The application of appropriate fertilization strategies and effective nutrient management can stimulate root growth and influence root morphology and architecture(Huang et al. 2022 ; Liu et al. 2024 ; Mengmeng et al. 2021 ). Moreover, the dynamic interplay between fertilization treatments and rhizosphere soil microorganisms also drive key biogeochemical processes, including nitrogen (N) fixation, phosphorus (P) solubilization, and carbon (C) cycling(Asghar et al. 2024 ; Roohi et al. 2020 ; Yu et al. 2020 ). For instance, legume−based intercropping systems demonstrate significant shifts in microbial diversity and abundance under varying N and P fertilization regimes, with low − N treatments often favoring nitrogen−fixing bacteria like Bradyrhizobium and Allorhizobium−Neorhizobium−Pararhizobium−Rhizobium (Cheng et al. 2023 ). Conversely, excessive N application can suppress these beneficial taxa, highlighting the need for balanced fertilization strategies to maintain microbial−mediated ecosystem services(A et al. 2021; Cheng et al. 2023 ). However, if the interaction between tree and crop root systems becomes excessively competitive, resource shortages may arise, undermining the potential benefits of intercropping and preventing optimal nutrient utilization. The competition for soil resources is influenced by the spatial distribution of roots, and the intensity of this competition can alter root spatial arrangement(Cardinael et al. 2015 ). Therefore, optimizing root system architecture may help regulate interspecific interactions within cropping systems(Liu et al. 2023 ). In intercropping systems, strategic nitrogen application can modify crop growth dynamics by enhancing or mitigating interspecific competition(Gong et al. 2021 ). Research demonstrates that the nutrient release characteristics of organic nitrogen and controlled−release nitrogen, when applied in appropriate proportions alongside chemical nitrogen, can improve both crop yield and stability. Innovative fertilization approaches, such as integrated organic−inorganic amendments (e.g., NPK−enriched compost or pig manure), have been shown to enhance microbial biomass and enzyme activities (e.g., sucrase, β − 1,4 − glucosidase, and phosphatases), which are critical for nutrient mobilization and soil health(Jiang et al. 2022; Roohi et al. 2020 ; Wu et al. 2016c ). It is critical for fertilization systems to adapt nitrogen management practices to optimize the temporal and spatial relationship between nitrogen supply and crop demand(Hu et al. 2020 ). In intercropping systems involving rubber trees and calla lilies, calla lilies enhance their competitive advantage for soil nitrogen by increasing root length and preferentially allocating root biomass(Li et al. 2018 ). Although rubber trees possess deep, extensive root systems, intercropped species typically concentrate their roots closer to the soil surface, thereby increasing competition for nutrients and water(Yang et al. 2021 ). Root competition between rubber trees and intercropped species presents a significant challenge in assessing the viability of rubber agroforestry systems(Wu et al. 2016b ). The functional redundancy and niche differentiation of microbial communities under intercropping further complicate their response to fertilization. For example, ammonia−oxidizing archaea (AOA) and bacteria (AOB) exhibit distinct preferences for soil microhabitats, with their abundances strongly correlated with soil pH and organic C content(Han et al. 2020 ; Zheng et al. 2022b ). Prior to the widespread implementation of rubber tree agroforestry, selecting intercropping species with complementary root strategies to mitigate competition is essential(Langenberger et al. 2016 ). Thus, effective nitrogen fertilizer management strategies in rubber−based agroforestry systems can significantly enhance soil nutrient levels, optimize the spatial and temporal distribution of roots, and promote the sustainable development of the system. Banana, a staple food crop grown in over 130 countries, is of particular importance in China as a tropical fruit. While some studies have examined the intercropping of rubber trees and bananas, research on the spatial and temporal distribution of root morphology, soil nutrient dynamics, and root competition under various fertilization patterns remains limited. Furthermore, how the rhizosphere microbial community in this system responds to partial organic nitrogen substitution, and how microbial processes interact with root distribution and soil nutrients, is currently unclear. This study posits that substituting 30% of chemical nitrogen fertilizer with organic nitrogen could positively influence rubber tree−banana intercropping systems. The goal of this research is to propose a science−based fertilization strategy for these systems, utilizing organic nitrogen to improve root morphology distribution, mitigate interspecific root competition, enhance soil nutrient levels, and further investigate the changes in rhizosphere microbial community structure and its association with system functioning. The study compared monoculture native rubber trees with three fertilization treatments in the rubber tree/banana intercropping system. The specific objectives are: (1) to analyze differences in the spatiotemporal distribution of roots between native rubber trees and bananas in monoculture and intercropping systems with varying fertilization approaches; (2) to assess how modifications in root distribution can reduce interspecific competition in intercropping systems with different fertilization regimes; (3) to evaluate soil nutrient levels in both monoculture and intercropping systems under the three fertilization treatments; and (4) to elucidate the impact of fertilization on the rhizosphere microbial community structure and explore its intrinsic links with soil nutrients and root distribution. This study aims to provide practical recommendations for optimizing nitrogen fertilizer management in native rubber tree−banana intercropping systems by enhancing root distribution, improving soil nutrient status, and regulating the rhizosphere microbial community, thereby establishing a pathway to the sustainable development of intercropping systems. Materials and methods Experimental site Field experiments were conducted from October 2021 to August 2022 at the Tropical Fruit Tree Variety Improvement Base, Tropical Crops Genetic Resources Institute, Chinese Academy of Tropical Agricultural Sciences, located in Danzhou County, Hainan Province, China (109.5°E, 19.5°N). The experimental site is situated in a hot and humid climate, with a mean annual temperature of 23.3°C and annual precipitation of 1826 mm (Fig. 1). [Insert Fig. 1] Experimental materials The soil at the experimental site was classified as brick − red loam, with a pH of 5.16, organic matter content of 8.74 g·kg − 1 , total nitrogen content of 0.76 g·kg − 1 , and available nitrogen content of 100.85 mg·kg − 1 . The available phosphorus content was 7.32 mg·kg − 1 , and the available potassium content was 90.83 mg·kg − 1 at the beginning of the experiment. The fertilizers used in the experiment included diammonium phosphate (N ≥ 20.8%, P 2 O 5 ≥ 53%), urea (N ≥ 46%), potassium dihydrogen phosphate (P 2 O 5 ≥ 52%, K 2 O ≥ 34%), potassium chloride (K 2 O ≥ 60%), polyurethane−coated urea with a fertilizer efficacy period of three months (N ≥ 43%), organic fertilizer (organic matter ≥ 45%, N−P 2 O 5 −K 2 O ≥ 5%), and water−soluble organic fertilizer (organic matter ≥ 320 g/L; N− P 2 O 5 − K 2 O ≥ 80 g/L). The seedlings tested included one−year − old tissue culture rubber tree Reyan 7 − 33−97 seedlings and Jiali banana tissue culture seedlings with 8–9 leaves. Experimental design The experiment employed a single−factor random block design with four treatments: monoculture rubber trees (CK), rubber tree−banana intercropping with conventional fertilization (M1), rubber tree−banana intercropping with a 30% organic nitrogen substitution treatment (M2), and rubber tree−banana intercropping with a 45% controlled−release nitrogen fertilizer combined with conventional chemical nitrogen treatment (M3). Each plot contained 7 rubber trees planted at a spacing of 2 m × 4 m × 20 m, and 54 banana plants spaced 1.5 m × 1.5 m. Each treatment was replicated three times, yielding a total of 12 experimental plots, each with an area of 126 m 2 (10.5 m × 12.0 m). In the initial year, the rubber trees in all treatments received the following fertilizer application: N 50 g·tree − 1 , P 2 O 5 20 g·tree − 1 , K 2 O 55 g·tree − 1 . For the banana plants, treatments M1, M2, and M3 received a total nutrient dosage throughout their growth period of N 180 g, P 2 O 5 80 g, and K 2 O 400 g. Nitrogen (N) was applied according to the following distribution: 10% at the seedling stage, 20% during vigorous growth, 20% at flower bud differentiation, 25% during bud development, 20% at bud emergence, and 5% at fruit expansion. Phosphorus (P) application followed this schedule: 20% at the seedling stage, 20% during vigorous growth, 20% at flower bud differentiation, 20% during bud development, 15% at bud emergence, and 5% at fruit expansion. Potassium (K) was distributed as follows: 5% at the seedling stage, 10% during vigorous growth, 20% at flower bud differentiation, 25% during bud development, 30% at bud emergence, and 10% at fruit expansion. In the M2 treatment, 50% of the organic fertilizer was applied as powdered organic fertilizer at the base, with the remaining 50% applied as water−soluble organic fertilizer, in line with the nitrogen application schedule for each growth stage. The M1and M2 treatment employed fertigation, while the M3 treatment involved six split applications of fertilizers via furrow application. Detailed quantities of fertilizer for banana cultivation are presented in Table S1 . Tree height and stem girth The height of each rubber tree and banana plant was measured at the banana harvest stage using a hypsometer. Stem girth was recorded 100 cm above the soil surface for each plant within the plot (N = 5). Leaf chlorophyll content During the banana harvest stage, mature leaves from the second leaf of both rubber trees and banana plants were selected for sampling. A 1:1 mixture of acetone and ethanol was used for a 24 − hour light−proof extraction. The photosynthetic pigment content, including chlorophyll a, chlorophyll b, and total chlorophyll, was quantified using a UV−visible spectrophotometer (Wellburn, 1994). Roots and soil sampling and analysis The rubber trees selected from each plot showed consistent growth, and a stratified excavation method was employed to sample the intercropping zones of rubber trees and bananas in the vigorous growth stage of bananas, the bud development stage, and the harvest stage. The rubber tree−banana intercropping area was divided into five equal sections, each 30 cm apart, with reference to the rubber tree. Sampling blocks, each measuring 60 cm × 30 cm × 20 cm (volume = 3.6 × 10 4 cm 3 ), were excavated at depths of 0 − 20 cm, 20 − 40 cm, and 40 − 60 cm (Fig. 2). Root systems were carefully retrieved from each soil block. The bulk soil loosely adhering to the roots was removed and mixed to form a composite non-rhizosphere soil sample. This soil was then sealed in bags and transported to the laboratory for the determination of available nitrogen, available phosphorus, available potassium, and organic matter content. All collected roots were thoroughly rinsed with water and stored at − 4°C for further analysis. The rhizosphere soil was collected and preserved in centrifuge tubes, immediately frozen in liquid nitrogen, transferred to a − 80°C ultra-low temperature freezer upon arrival at the laboratory, and subsequently used for microbial analysis. [Insert Fig. 2] Determination of morphological measurements and soil nutrients Root morphological measurements The root shape index was determined by gently drying the clean rubber and banana roots using soft paper, followed by measuring their fresh weight. The roots were then scanned using an Epson scanner, and the obtained data, including root length and root surface area, were analyzed with WinRHIZO™ software (Regent Instruments Inc., Quebec, Canada). Data processing The root length density (RLD, cm·cm − 3 ) was calculated using Eq. (1): RLD = RL/SV (1) In this equation, RL represents root length (cm) and SV denotes soil volume (cm 3 ). The root surface area density (RSAD, cm 2 ·cm − 3 ) was determined using Eq. (2): RSAD = RSA/SV (2) In this equation, RSA refers to the root surface area (cm 2 ) and SV is the soil volume (cm 3 ). The underground interspecific competition intensity index (UICII) was calculated by Eq. (3): $$\:UICII=\frac{\sum\:_{i=1}^{n}\:{P}_{Ri}{P}_{Bi}}{\sqrt{\sum\:_{i=1}^{n}\:{P}_{Ri}^{2}\sum\:_{i=1}^{n}\:{P}_{Bi}^{2}}}$$ 3 The intensity of soil nutrient competition between the roots of rubber trees and bananas was quantified by quantifying the degree of overlap between the ecological niches occupied by each species (Levins, 1968). The formula of UICII (0 ≤ UICII ≤ 1) is as follows (Pianka 1973 ):, where n represents the number of soil layers, and P Ri and P Bi denote the root proportion of rubber trees and bananas, respectively, in the i th soil layer, relative to the total root distribution across all layers (soil depth 0 − 60 cm, distance from the tree 0 − 150 cm). Soil nutrition measurements Soil properties were determined as follows: soil organic matter content was quantified using the potassium dichromate volumetric method with external heating; available nitrogen was measured through distillation using a semi−micro Kjeldahl apparatus; available phosphorus was determined by HCl−NH 4 F molybdenum blue colorimetry; and available potassium was analyzed via flame photometry following ammonia acetate extraction. These analytical methods were adapted from Bao (2000). Microbiome Analysis The bacterial and fungal community structures in the rhizosphere soil of rubber trees and bananas were analyzed using 16S rRNA and ITS amplicon sequencing, respectively. The detailed experimental procedure was as follows: (1) DNA Extraction and Amplicon Sequencing Total DNA was extracted from the collected rhizosphere soil samples using a commercial kit. The V3 − V4 hypervariable region of the bacterial 16S rRNA gene was amplified using the specific primers 338F (5′−ACTCCTACGGGAGGCAGCAG − 3′) and 806R (5′−GGACTACHVGGGTWTCTAAT − 3′). The ITS1 region of the fungal ITS gene was amplified using the primers ITS1F (5′−CTTGGTCATTTAGAGGAAGTAA − 3′) and ITS2R (5′−GCTGCGTTCTTCATCGATGC − 3′). The PCR reactions were carried out in a 15 µL mixture containing Phusion® High−Fidelity PCR Master Mix, 0.2 µM of each forward and reverse primer, and approximately 10 ng of template DNA. The thermal cycling conditions consisted of an initial denaturation at 98°C for 1 min; followed by 30 cycles of denaturation at 98°C for 10 s, annealing at 50°C for 30 s, and elongation at 72°C for 30 s; with a final extension at 72°C for 5 min. (2) Library Construction and Sequencing The PCR products were detected by electrophoresis on a 2% agarose gel. Subsequently, the PCR products were pooled in equimolar ratios and purified. Sequencing libraries were constructed, and the quality of the libraries was assessed using Qubit for quantification and a bioanalyzer for size distribution detection. The qualified libraries were finally paired − end sequenced on an Illumina platform according to the effective library concentration and the required data volume. Statistical analyses Data are presented as the mean ± standard error (SE) from triplicate measurements. Statistical analysis was performed using one − way ANOVA followed by Duncan’s multiple range test (p < 0.05). All computations, including comparisons of the relative abundances of microbial taxa and alpha diversity indices (Shannon and Chao1), were carried out using SPSS 29.0 (IBM Corporation, USA). Experimental figures were generated using Origin 2021 (Origin Lab, USA). For microbial community analysis, Spearman correlation analysis was conducted to evaluate relationships between the relative abundance of dominant microbial phyla and root morphological or soil nutrient parameters. These analyses and associated visualizations were performed using R software (version 3.4.2) with the vegan and ggplot2 packages. Results Plant Growth and Leaf Chlorophyll Content The rubber tree/banana intercropping system with different fertilization strategies significantly influenced both plant growth and leaf chlorophyll content. For rubber trees, plant height increased by 4.83% under M1 and 16.26% under M2 compared to the monoculture control (CK), with M2 showing statistical significance while M3 resulted in a non-significant reduction (Fig. 3a). Stem girth of rubber trees increased by 8.17% under M2 compared to CK, whereas M1 and M3 showed minor non-significant decreases (Fig. 3b). In bananas, both M1 and M2 significantly enhanced plant height by 5.32% and 8.66%, respectively, compared to M3 (Fig. 3a), while stem girth increased by 8.34% and 10.93% under the same treatments (Fig. 3b). Regarding leaf chlorophyll content, rubber trees under M1 and M2 showed increased chlorophyll a by 5.42% and 3.61%, and total chlorophyll by 4.94% and 6.77% compared to CK, while M3 decreased total chlorophyll by 4.62% (Fig. 3c). No significant differences in chlorophyll content were observed in banana leaves across treatments (Fig. 3c). These findings demonstrate that the M2 treatment (30% organic nitrogen substitution) in the intercropping system most effectively promoted plant growth and leaf chlorophyll content in both crops. [Insert Fig. 3] Spatial and temporal distribution of root system Root biomass The temporal and spatial distribution of root biomass for rubber tree monoculture and three different fertilization treatments in rubber−banana intercropping systems is presented in Fig. 4. Over time, from the banana vigorous growth stage to the bud development stage, the rubber tree root biomass decreased in the CK, M1, and M2 treatments, while it increased in the M3 treatment. At the banana bud development stage, the rubber root biomass was highest in the M2 treatment, reaching 21.78 g. From the banana bud development stage to the banana harvest stage, rubber root biomass generally increased in all treatments, except for a slight decrease in the M2 treatment. Nonetheless, by the banana harvest stage, the rubber tree root biomass in the M2 treatment remained the highest, at 19.70 g. In terms of banana root biomass, the M1 and M3 treatments peaked during the harvest period, reaching 177.69 g and 140.48 g, respectively, while the M2 treatment showed its peak at 203.02 g during the bud development stage. Regarding vertical spatial variation, during the banana bud development stage, rubber tree root biomass in the M2 treatment was higher than in other treatments. Specifically, in the 0 − 20 cm soil layer, biomass increased by 66.91% to 115.84%, while in the 20 − 40 cm layer, it increased by 140.08% to 625.47%. In the 40 − 60 cm layer, the increase ranged from 113.10% to 239.40%. Comparatively, banana root biomass in the M2 treatment in the 0 − 20 cm layer increased by 47.51% to 85.67% over the M1 and M3 treatments, while in the 20 − 40 cm layer, the increase was 11.10%, and in the 40 − 60 cm layer, it increased by 20.17% and 92.80%, respectively. In the horizontal distribution, during the banana harvest stage, within a 0 − 30 cm radius from the rubber tree, the rubber tree root biomass in the M2 treatment increased by 7.09% to 29.17% compared to other treatments. [Insert Fig. 4] Root length destiny (RLD) The temporal and spatial distribution of RLD in rubber tree monoculture and three different fertilization modes in rubber−banana intercropping systems is presented in Fig. 5. In terms of temporal variation, from the vigorous growth stage to the bud development stage of banana, the total RLD of rubber trees in the CK treatment decreased, while in the M1, M2, and M3 treatments, it increased. At the bud development stage, the total RLD of rubber trees in the M2 treatment peaked at 0.364 cm·cm − 3 . Moving from the bud development stage to the harvest stage, the total RLD of rubber trees increased in the CK, M1, and M3 treatments, while it decreased in the M2 treatment. At the harvest stage, the highest total RLD of rubber trees was observed in the CK treatment, at 0.380 cm·cm − 3 . Regarding banana RLD, the total RLD of the M1 and M3 treatments showed an increasing trend throughout banana growth, reaching peaks of 0.673 cm·cm − 3 and 0.764 cm·cm − 3 , respectively, at the harvest stage. In contrast, the highest total RLD for bananas in the M2 treatment occurred at the bud development stage, at 0.963 cm·cm − 3 . In terms of vertical spatial variation, during the banana bud development stage, in the 0 − 20 cm soil layer, the total RLD of rubber trees in the M2 treatment increased by 213.44%, 44.78%, and 171.84% compared to the CK, M1, and M3 treatments, respectively. The total banana RLD in the M2 treatment increased by 88.50% and 79.98% compared to the M1 and M3 treatments, respectively. In the horizontal distribution, during the banana bud development stage, within a 0 − 30 cm distance from the rubber tree, the RLD of rubber trees in the M2 treatment increased by 203.37%, 34.53%, and 124.02% compared to the CK, M1, and M3 treatments, respectively. At a distance of 120 − 150 cm from the rubber tree, the RLD of bananas in the M2 treatment increased by 135.52% and 89.12% compared to the M1 and M3 treatments. [Insert Fig. 5] Root surface area destiny (RSAD) The temporal and spatial distribution of RSAD in rubber tree monoculture and three different fertilization modes in rubber−banana intercropping systems is illustrated in Fig. 6. From the banana vigorous growth stage to the bud development stage, the RSAD of rubber trees decreased in the CK treatment, while it increased in the M1, M2, and M3 treatments. The highest RSAD value for rubber trees during the bud development stage was recorded in the M2 treatment, at 0.138 cm 2 ·cm − 3 . At the harvest stage, the RSAD of rubber trees in the M2 treatment slightly decreased, while it increased in the other treatments. The RSAD in the CK treatment was 0.116 cm 2 ·cm − 3 , the highest among all treatments. Regarding banana RSAD, the peak values in the M1 and M3 treatments occurred during the harvest stage, at 0.424 cm 2 ·cm − 3 and 0.469 cm 2 ·cm − 3 , respectively, while the maximum RSAD in the M2 treatment was observed during the bud development stage, at 0.534 cm 2 ·cm − 3 . From the perspective of vertical spatial variation during the banana bud development stage, in the 0 − 20 cm soil layer, the RSAD of rubber trees in the M2 treatment increased by 187.48%, 77.08%, and 162.10% compared to the CK, M1, and M3 treatments, respectively. Additionally, the RSAD of banana plants in the M2 treatment was higher than in the M1 and M3 treatments, with increases of 58.48% and 72.63%, respectively. In the horizontal distribution, at a distance of 0 − 30 cm from the rubber tree, the RSAD of rubber trees treated with M2 increased by 182.84%, 70.01%, and 133.58% compared to the CK, M1, and M3 treatments. At a distance of 120 − 150 cm from the rubber tree, the RSAD of banana plants in the M2 treatment was higher than in the M1 and M3 treatments, with increases of 98.06% and 89.45%, respectively. [Insert Fig. 6] Underground interspecific competition intensity index (UICII) Underground interspecific competition intensity index for each treatment and different soil depths The root competition dynamics in the rubber tree−banana intercropping system, influenced by various fertilization treatments, exhibited distinct patterns across different soil layers and growth stages of the rubber tree (Table 1). During the vigorous growth stage, the highest UICII for the M1 treatment was observed in the 40 − 60 cm soil layer, while the M2 and M3 treatments peaked in the 20 − 40 cm soil layer. Notably, the UICII for the M2 treatment was 31.65% and 22.69% lower than that of the M1 and M3 treatments, respectively. In the bud development stage, both M1 and M2 treatments showed their highest UICII values in the 40 − 60 cm soil layer, while the M3 treatment peaked in the 20 − 40 cm soil layer, indicating the weakest root competition during this period, with reductions of 5.45% and 4.10% compared to M1 and M2, respectively. By the harvest stage, the highest UICII for all treatments was recorded in the 40 − 60 cm soil layer, each achieving a value of 1. However, the M3 treatment showed a reduction in root competition by 19.58% and 18.34% compared to M1 and M2 treatments. These results suggest that a 30% substitution of organic nitrogen mitigates root competition across all soil layers during the banana's vigorous growth stage, while a 45% substitution of slow−release nitrogen effectively reduces root competition during the bud development and harvest stages within the intercropping system. [Insert Table 1] Underground interspecific competition intensity index for each treatment and different distance from tree In terms of interspecific root competition during the banana growth periods, the UICII across various distances from the rubber tree also showed notable differences depending on the fertilization treatment (Table 2). During the vigorous growth stage, the UICII for the M1 treatment peaked at a distance of 90 cm from the rubber tree, while the M2 and M3 treatments reached their highest values at 150 cm. In this phase, the UICII of the M2 treatment was 14.91% and 13.14% lower than that of M1 and M3 treatments, respectively. During the banana bud development stage, the highest UICII for both M1 and M2 treatments was observed at 90 cm from the rubber tree, while the M3 treatment peaked at 120 cm. The M2 treatment recorded UICII values that were 23.00% and 22.92% lower than those of M1 and M3 treatments, respectively. By the banana harvest period, the highest UICII for M1 and M3 treatments was found again at 150 cm from the rubber tree, whereas the M2 treatment peaked at 90 cm. Compared to the M1 and M3 treatments, the UICII of the M2 treatment increased by 14.84% and 18.12%, respectively. These results suggest that a 30% substitution of organic nitrogen effectively alleviates root competition intensity during the banana’s vigorous growth and bud development stages while promoting interspecific root competition during the harvest period. [Insert Table 1] Soil nutrient Available N The distribution of soil available nitrogen content in monoculture and intercropped rubber/banana systems under varying fertilization regimes is depicted (Fig. 7). Overall, soil available nitrogen initially increased and then declined, reaching its peak during the banana bud development stage. Vertically, the highest nitrogen content was observed in the 0 − 20 cm layer for both monoculture and intercropped systems, with a gradual decrease at greater depths. During the vigorous growth stage (Fig. 7a, 7d, 7g, 7j), intercropping systems employing the three fertilization treatments resulted in increases in available nitrogen content by 14.49%, 16.93%, and 7.59% in the 0 − 20 cm layer, 21.57%, 15.41%, and 3.84% in the 20 − 40 cm layer, and 16.02%, 13.36%, and 10.04% in the 40 − 60 cm layer, relative to the CK treatment. By the bud development stage (Fig. 7b, 7e, 7h, 7k), the M2 treatment demonstrated increases of 4.30%, 3.83%, and 3.96% in soil nitrogen content at the 0 − 20 cm, 20 − 40 cm, and 40 − 60 cm depths, respectively, compared to the CK treatment. At the harvest stage (Fig. 7c, 7f, 7i, 7l), the M1 treatment resulted in increases of 1.60%, 10.91%, and 5.30%, the M2 treatment in increases of 14.43%, 26.49%, and 21.32%, and the M3 treatment in increases of 4.41%, 9.61%, and 7.48% at the 0 − 20 cm, 20 − 40 cm, and 40 − 60 cm layers, respectively, compared to the CK treatment. These results highlight the capacity of the rubber/banana intercropping system to enhance soil nitrogen availability relative to monoculture rubber, with the M2 fertilization mode proving to be the most effective. [Insert Fig. 7] Available P The distribution of soil available phosphorus content in monoculture and intercropped rubber/banana systems under various fertilization modes is presented (Fig. 8). Generally, the available phosphorus content initially decreased and then increased with increasing distance from the rubber trees. At the vigorous growth stage (Fig. 8a, 8d, 8g, 8j), the soil available phosphorus content in the 0 − 20 cm layer was 6.94%, 70.31%, and 28.15% lower in the CK treatment compared to M1, M2, and M3 treatments, respectively. By the bud development stage (Fig. 8b, 8e, 8h, 8k), available phosphorus content in the 0 − 20 cm depth increased by 24.12%, 25.89%, and 12.29% in the M1, M2, and M3 treatments, respectively, compared to CK. In terms of horizontal distribution, at the closest distance from the banana, the M2 treatment exhibited significant increases of 119.80%, 149.58%, and 147.97% in the 0 − 20 cm soil layer relative to CK, M1, and M3 treatments, respectively. At the harvest stage (Fig. 8c, 8f, 8i, 8l), soil available phosphorus content in the 0 − 20 cm layer of intercropping systems M2 and M3 treatments increased by 12.72% and 4.80%, respectively, compared to the CK treatment. At a 30 cm distance from the rubber tree, M2 and M3 treatments showed increases of 11.32% and 22.53%, respectively, relative to CK. Overall, at the vigorous growth stage, the M1 treatment increased available phosphorus content by 6.35% compared to CK. During the bud development stage, intercropping treatments M1 to M3 resulted in yield increases ranging from 2.16% to 23.29% compared to CK. At the harvest stage, available phosphorus content in the M2 and M3 treatments rose by 16.66% to 19.45% relative to CK, with the M2 treatment exhibiting the highest level. These results suggest that intercropping treatments generally enhance soil available phosphorus content relative to monocropping, with the 30% organic nitrogen substitution treatment (M2) showing significant advantages during the banana bud development and harvest stages. [Insert Fig. 8] Available K The distribution of soil available potassium content in monoculture and intercropped rubber/banana systems under three different fertilization regimes is shown (Fig. 9). Generally, the soil available potassium content in intercropping systems was lower than in monoculture systems. At the vigorous growth stage (Fig. 9a, 9d, 9g, 9j), in the 0 − 20 cm soil layer, only the M1 treatment exhibited a 10.17% increase compared to the CK treatment, while the M2 and M3 treatments showed decreases of 26.32% and 25.58%, respectively. At both the bud development stage (Fig. 9b, 9e, 9h, 9k) and the harvest stage (Fig. 9c, 9f, 9i, 9l), available potassium content in the 0 − 20 cm depth decreased by 7.47%−43.82% for M1, 34.05%−60.84% for M2, and 69.02%−78.37% for M3, compared to the CK treatment. [Insert Fig. 9] Organic matter The distribution of soil organic matter content in monoculture and intercropped rubber/banana systems under three different fertilization regimes is presented (Fig. 10). Vertically, the highest soil organic matter content was observed in the 0 − 20 cm layer for both monoculture and intercropping systems. Horizontally, the content was higher at the outer edges and lower at the center. At the vigorous growth stage (Fig. 10a, 10d, 10g, 10j), soil organic matter content in the 0 − 20 cm layer increased by 6.22% and 17.71% in the M1 and M2 treatments, respectively, compared to the CK treatment. By the bud development stage (Fig. 10b, 10e, 10h, 10k), the M2 treatment exhibited the highest soil organic matter content in the 0 − 20 cm layer, with a 2.34% increase compared to the CK treatment. At the harvest stage (Fig. 10c, 10f, 10i, 10l), M2 treatment showed a 7.77% increase in soil organic matter content relative to the CK treatment. These results suggest that the M2 treatment effectively enhances soil organic matter content compared to monoculture rubber cultivation. [Insert Fig. 10] Response of rhizosphere microbial community structure and diversity to fertilization treatments Effects of Different Fertilization Treatments on the Alpha Diversity of Rhizosphere Microbial Communities Different fertilization treatments significantly affected the alpha diversity of rhizosphere microbial communities in rubber trees and banana plants (Fig. 11a–p). Analysis of bacterial communities showed that the Shannon index was highest under the M1 treatment in both the 0–30 cm rubber tree rhizosphere (Fig. 11a) and the intercropping zone rubber rhizosphere (Fig. 11b), with values of 7.02 and 6.73, respectively—the former representing an 18.84% increase compared to CK. In contrast, the intercropping zone banana rhizosphere (Fig. 11c) and the 0–30 cm banana rhizosphere (Fig. 11d) reached their maximum values under M2, at 6.88 and 6.95, reflecting increases of 18.14% and 20.08% compared to M3, respectively. Chao1 index analysis indicated that the 0–30 cm rubber tree rhizosphere (Fig. 11e) and intercropping zone rubber rhizosphere (Fig. 11f) also exhibited the highest values under M1, at 1903.67 and 1551.33, respectively, with the former showing a significant 42.67% increase compared to CK. The intercropping zone banana rhizosphere (Fig. 11g) reached its maximum under M2 (1726), increasing by 10.93% compared to M1, while the 0–30 cm banana rhizosphere (Fig. 11h) was highest under M3 (2186.55). Analysis of fungal communities revealed that the Shannon index reached its maximum under M2 in both the intercropping zone rubber rhizosphere (Fig. 11j) and banana rhizosphere (Fig. 11k), with values of 4.31 and 4.06, representing increases of 18.50% and 19.03% compared to M3, respectively (the latter being significant at P < 0.05). In contrast, the 0–30 cm rubber tree rhizosphere (Fig. 11i) and banana rhizosphere (Fig. 11l) showed the highest values under M3. The Chao1 index indicated that the 0–30 cm rubber tree rhizosphere (Fig. 11m) and the intercropping zone banana rhizosphere (Fig. 11o) both reached their maximum under M2, with values of 651.67 and 532, reflecting significant increases of 36.71% (P < 0.05) and 36.29% compared to the control treatment, respectively. The intercropping zone rubber rhizosphere (Fig. 11n) and 0–30 cm banana rhizosphere (Fig. 11p), however, showed the highest values under M1. These results indicate that the M2 treatment has a significant advantage in enhancing bacterial diversity in the banana rhizosphere and fungal community richness in the intercropping zone, suggesting that this fertilization approach plays a positive role in improving the rhizosphere micro−ecological environment. [Insert Fig. 11] Effects of Different Fertilization Treatments on the Rhizosphere Bacterial Community Characteristics of Rubber Trees and Banana Plants Different fertilization treatments significantly altered the rhizosphere bacterial community structure of both rubber trees and banana plants (Fig. 12a–d), with the M2 treatment showing a notable advantage in increasing the relative abundance of multiple beneficial bacterial phyla. In the rubber tree rhizosphere (Fig. 12a), M2 significantly increased the relative abundance of Bacteroidota and Firmicutes, with Bacteroidota increasing by 66.40% compared to M1 (p < 0.05) and Firmicutes increasing by 131.00% and 45.58% compared to M1 and M3, respectively. In the intercropping zone rubber tree rhizosphere (Fig. 12b), Crenarchaeota reached its highest relative abundance under M2, increasing by 24.00% and 107.00% compared to M1 and M3. The intercropping zone banana rhizosphere (Fig. 12c) exhibited particularly pronounced responses under M2, where Proteobacteria increased by 11.26% and 68.61% compared to M1 and M3, Actinobacteria increased by 20.96% and 49.54%, and Chloroflexi increased by 37.09% compared to M3. In the banana rhizosphere (Fig. 12d), M2 also significantly enhanced the relative abundance of several phyla: Acidobacteriota increased by 152.00% compared to M3 (P < 0.05), Firmicutes increased by 92.54% compared to M3, Crenarchaeota increased by 69.84% compared to M1, and Myxococcota increased by 37.70% and 43.37% compared to M1 and M3. In summary, the M2 treatment demonstrated a significant advantage in promoting the assembly of beneficial rhizosphere bacterial communities. [Insert Fig. 12] Effects of Different Fertilization Treatments on the Rhizosphere Fungal Community Characteristics of Rubber Trees and Banana Plants Different fertilization treatments significantly influenced the rhizosphere fungal community structure of rubber trees and banana plants at the phylum level (Fig. 13a–d), with the M2 treatment demonstrating notable advantages in increasing the relative abundance of several key fungal phyla. In the rubber tree rhizosphere (Fig. 13a), the relative abundance of Ascomycota under M2 reached 87.15%, representing a 28.36% increase compared to M1, while Basidiomycota was highest under M1 (21.58%). In the intercropping zone rubber tree rhizosphere (Fig. 13b), Mortierellomycota showed the highest relative abundance under M2 (3.51%), with a significant increase of 205.00% compared to M3 (P < 0.05). In the intercropping zone banana rhizosphere (Fig. 13c), the relative abundance of Mortierellomycota under M2 was 2.07%, reflecting a 38.08% increase compared to M1. In the banana rhizosphere (Fig. 13d), all observed phyla performed optimally under M2: the relative abundance of Ascomycota was 73.76%, increasing by 6.31% compared to M3; the relative abundance of Basidiomycota was 8.11%, with significant increases of 24.62% and 111.00% compared to M1 and M3, respectively; and the relative abundance of Mortierellomycota was 2.69%, increasing by 27.42% and 65.53% compared to M1 and M3. In summary, the M2 treatment exhibited a clear advantage in promoting the establishment of beneficial rhizosphere fungal communities. [Insert Fig. 13] Interactions Between Rhizosphere Microbial Communities and Root−Soil System Factors Correlation Analysis Between Bacterial Communities and Root/Soil Factors Correlation analysis between rhizosphere bacterial communities and root indices as well as soil factors under different fertilization treatments is shown in Fig. 14. In the 0–30 cm rubber tree rhizosphere (Fig. 14a), the relative abundance of Proteobacteria showed a significant positive correlation with root biomass (p < 0.05). In the intercropping zone rubber tree rhizosphere (Fig. 14b), Bacteroidota was significantly positively correlated with root length density and root surface area density, while Proteobacteria was highly significantly positively correlated with root length density (p < 0.01) and significantly positively correlated with root surface area density. Analysis in the intercropping zone banana rhizosphere (Fig. 14c) indicated that Acidobacteriota and Chloroflexi were significantly negatively correlated with root biomass, root length density, and root surface area density, with Chloroflexi showing highly significant negative correlations with these root indices and a significant negative correlation with soil available phosphorus. Firmicutes was significantly positively correlated with soil available potassium, while Proteobacteria was highly significantly positively correlated with available potassium. Bacteroidota showed significant positive correlations with available potassium, root biomass, root length density, and root surface area density, and Myxococcota was significantly positively correlated with soil available phosphorus. In the 0–30 cm banana rhizosphere (Fig. 14d), Actinobacteria and Bacteroidota were significantly negatively correlated with soil alkaline hydrolyzable nitrogen, and Chloroflexi was significantly negatively correlated with root biomass. It is worth noting that beneficial bacterial groups such as Proteobacteria and Bacteroidota, which were significantly enriched in the M2 treatment, exhibited significant positive correlations with both root development indices and soil nutrient availability, revealing the potential mechanism by which this fertilization approach promotes plant growth from a microbial ecological perspective. [Insert Fig. 14] Correlation Analysis Between Fungal Communities and Root/Soil Factors Correlation analysis between fungal community structure at the phylum level and root indices as well as soil factors is shown in Fig. 15. In the 0 − 30 cm rubber tree rhizosphere (Fig. 15a), no significant correlations were observed between any fungal phyla and the root or environmental factors. Analysis in the intercropping zone rubber tree rhizosphere (Fig. 16b) indicated that Chytridiomycota showed a significant positive correlation with root biomass, whereas Rozellomycota was significantly negatively correlated with root biomass, root length density, and root surface area density, and exhibited highly significant negative correlations with soil available phosphorus, alkaline hydrolyzable nitrogen, and organic matter content. In the intercropping zone banana rhizosphere (Fig. 15c), the relative abundance of Calcarisporiellomycota was significantly negatively correlated with soil available phosphorus and highly significantly negatively correlated with alkaline hydrolyzable nitrogen and organic matter. Analysis in the 0 − 30 cm banana rhizosphere (Fig. 15d) revealed that Blastocladiomycota was significantly positively correlated with soil available potassium, alkaline hydrolyzable nitrogen, and organic matter; Ascomycota was significantly positively correlated with available potassium; and Mortierellomycota was significantly negatively correlated with available phosphorus. It is worth noting that fungal taxa such as Blastocladiomycota, which were significantly enriched in the M2 treatment, showed significant positive correlations with soil nutrient availability, indicating that this fertilization approach may improve soil fertility by regulating the structure of fungal communities. [Insert Fig. 15] Discussion Roots morphology in intercropping Competition for underground resources in agroforestry systems is influenced by the distribution and density of root systems (Noordwijk et al. 2015 ). However, research on the root system characteristics of rubber trees intercropped with other crops under varying fertilization regimes remains limited. A study on nitrogen fertilization levels for intercropped rubber trees and calla lilies revealed that intercropping only inhibited calla lily growth when nitrogen application was below 200 kg·ha − 1 , while it enhanced root system development by increasing root number and length and promoting dry matter allocation to the root system (Li and Lin 2021a ). In the present study, during the banana bud development stage, both rubber tree and banana root biomass showed increases at various soil depths under the M2 treatment compared to other treatments. Specifically, within the 0–30 cm range from the rubber tree, root biomass in the M2 treatment was 7.09% to 29.17% higher than in the other treatments (Fig. 4b, e, h, k). Furthermore, during the banana harvest period, monoculture rubber trees exhibited superior RLD compared to the intercropping treatments. Analysis of vertical spatial changes revealed that, during the budding stage, the total banana RLD in the 0–20 cm soil layer increased by 88.50% and 79.98% under the M2 treatment compared to the M1 and M3 treatments, respectively (Fig. 5f, i, l). Additionally, within the 0–30 cm range from the rubber tree during the bud development stage, rubber tree RLD under the M2 treatment exceeded that of the CK, M1, and M3 treatments, with increases of 203.37%, 34.53%, and 124.02%, respectively (Fig. 5b, e, h, k). Moreover, during the banana harvest period, the RSAD was highest under monoculture rubber trees, with a value of 0.116 cm 2 ·cm − 3 (Fig. 6c, f, i, l). These findings indicate that the temporal and spatial distribution of root system morphology is influenced by growth stages, underscoring the benefits of both monoculture and intercropping systems. The M2 fertilization regime in rubber/banana intercropping systems plays a pivotal role in optimizing root system competition and spatial niche adaptation, demonstrating significant advantages in complementarity. Research on intercropping rubber trees with other crops has demonstrated that in deeper soil layers, the fine RLD of rubber trees intercropped with kudzu reaches 0.92 cm·cm − 3 , with a biomass density of 0.74 g·dm − 3 . This represents a significant increase of 26.03% and 89.74%, respectively, compared to monoculture (Clermont-Dauphin et al. 2018 ). Similarly, rubber trees in agroforestry systems intercropped with perennial galangal, tea, and cocoa exhibited average root length densities of 0.18 cm·cm − 3 , 0.18 cm·cm − 3 , and 0.13 cm·cm − 3 , respectively, indicating varying degrees of decline compared to monoculture. A substantial portion of fine rubber tree roots (60.7%–72.5%) were concentrated in the 0–20 cm soil layer across all treatments (Yang et al. 2020a ). Studies on other intercrops reveal that intercropped corn and soybeans exhibit significantly greater RLD and RSAD compared to monoculture, while intercropped peanuts experience restricted root systems with lower densities (Zheng et al. 2022a ). Intercropping wheat and corn resulted in a reduction in root biomass density, RLD, and RSAD of intercropped corn by 53%, 81%, and 70%, respectively, compared to monocrop corn (Wang et al. 2018 ). Furthermore, intercropping walnuts and wheat led to a significant decrease in RLD, RSAD, and other root morphological indicators compared to monoculture (Duan et al. 2017 ). Overall, this study demonstrates that the treatment involving 30% organic nitrogen substitution (M2) yielded favorable outcomes in terms of root morphology plasticity and spatial distribution within the young rubber tree/banana intercropping system. It appears that competition for underground resources between trees and crops in agroforestry systems is influenced by root distribution and spatial allocation (Forey et al., 2017). By strategically organizing root distribution within the system, competition can be minimized, thereby enhancing the productivity of the entire agroforestry system (Li et al., 2021 ; Wei et al., 2024 ). Underground interspecific competition intensity index in intercropping systems Crop roots compete for nutrient resources in the soil, and when the demand for these resources exceeds their availability, interspecific competition is inevitable (Wang et al., 2020; Shen et al., 2022). The nature of this competition—whether complementary or competitive—depends largely on the distribution and density of root systems (Noordwijk et al. 2015 ). Additionally, the dynamics of root competition are influenced by the spatial arrangement of crops. For instance, when crops are planted in close proximity, their roots are likely to compete more intensely for the same volume of soil, potentially reducing nutrient uptake for both species. In contrast, when root systems are differentiated by depth and spread, they can access distinct soil layers, thereby reducing competition and improving overall resource utilization efficiency (Li et al., 2023; Liu et al., 2022). In this study, the M3 treatment exhibited a lower root competition intensity index (UICII) during the harvest stage compared to the bud development stage, reflecting a reduction in vertical root competition. In contrast, UICII values for both the M1 and M2 treatments increased as rubber trees and bananas progressed through their growth stages. Specifically, the M2 treatment showed a lower UICII during the vigorous growth stage, whereas the M3 treatment recorded the lowest values during both the bud development and harvest stages (Table 1). In terms of horizontal root competition, the M2 treatment demonstrated lower UICII values during the vigorous growth and bud development stages, while the M3 treatment exhibited a lower index during the harvest stage. This is likely attributed to the slower nutrient release and prolonged efficacy of organic and controlled−release fertilizers (Table 2). The 30% organic fertilizer substitution combined with 45% controlled−release nitrogen significantly reduced root competition throughout the banana growth cycle, thereby improving ecological niche complementarity. Previous research has shown that excessive root competition in agroforestry systems exacerbates resource competition, leading to shortages that hinder efficient resource utilization in intercropping systems (Dai et al. 2021 ; Liu et al. 2019 ). Moreover, interspecific competition within such systems affects the root growth of fruit trees, with crops competing for essential resources, ultimately influencing system−wide yields (Zhao et al., 2022). For example, the concentration of roots from multiple crops can intensify belowground competition, potentially reducing crop yields (Zhang et al., 2013). This highlights that the advantages of intercropping extend beyond mere resource competition and include complex root interactions that can enhance plant health and productivity. Root competition in intercropping systems presents a multifaceted challenge, influenced by factors such as root structure and spatial arrangement. A comprehensive understanding of these factors is critical for optimizing intercropping practices to improve crop yields and bolster the sustainability of agricultural systems. Effective agronomic interventions, such as rational fertilization, are essential for mitigating the negative impacts of root competition. Soil nutrients in intercropping Intercropping enhances soil fertility, improves soil quality, and optimizes nutrient utilization (Duan et al. 2019 ; Li et al. 2021 ). Previous studies have demonstrated that intercropping systems can increase the availability of essential macronutrients—nitrogen, phosphorus, and potassium—which are critical for plant growth (Zhang et al., 2018; Shen et al., 2024). The current study reveals that, compared to rubber monoculture, the rubber/banana intercropping system significantly increased soil nitrogen availability, with the M2 fertilization treatment proving most effective (Fig. 7). Regarding soil phosphorus content, the M1 treatment showed certain advantages over the CK treatment during the vigorous growth stage. In both the bud development and harvest stages, the M2 treatment outperformed monoculture and other intercropping fertilization treatments (Fig. 8). Additionally, the M2 treatment consistently exhibited superior outcomes in soil organic matter content, reaching its peak value across various banana growth stages (Fig. 10). In contrast, intercropping generally led to a decrease in soil potassium content (Fig. 9). Previous research has indicated that transitioning rubber trees from monoculture to agroforestry systems resulted in significant increases in soil nitrogen and phosphorus by 38.5% and 48.2%, respectively, suggesting that rubber tree intercropping improves the physical and chemical properties of soil, thereby contributing to the sustainable development of agriculture and the environment (Chen et al. 2019 ). Multiple studies have reported that intercropping enhances soil organic matter content (Cong et al. 2015 ; Li et al. 2021 ; Wei et al. 2024 ). However, studies on rubber tree and calla lily intercropping indicate that such practices may reduce soil potassium levels (Li and Lin 2021a ). Organic fertilizers, rich in nutrients and organic matter, have been shown to significantly improve soil fertility and fertilizer efficiency (Ma et al. 2022 ; Saudy et al. 2020 ), which may explain the observed relationship between soil available nitrogen, phosphorus, and the M2 treatment in this study. The higher organic matter content observed in this study, compared to monoculture and other fertilization treatments, is likely attributed to these factors. In conclusion, intercropping is a sustainable agricultural practice that integrates diverse plant species, enabling optimized nutrient cycling, enhanced soil health, and increased crop yields. This approach is therefore a valuable strategy for sustainable agriculture, offering benefits beyond nutrient acquisition, such as long−term improvements in soil fertility and ecosystem health. Fertilization Effects on Rhizosphere Microbial Communities This study demonstrated that the M2 treatment (combined organic−inorganic fertilization) most effectively enhanced the rhizosphere microbial community structure and diversity in the rubber tree−banana intercropping system. For bacteria, M2 significantly increased the relative abundance of beneficial phyla such as Bacteroidota and Firmicutes in the rubber tree rhizosphere, and Proteobacteria, Actinobacteria, and Chloroflexi in the intercropped banana rhizosphere (Fig. 11), which are pivotal for nutrient cycling and soil health (Liu et al. 2020 ; Ning et al. 2020 ). Notable increases in Acidobacteriota and Myxococcota under M2 further highlighted the role of organic inputs in shaping microbial assembly (Liu et al. 2020 ; Yang et al. 2024 ). Concurrently, M2 enhanced the fungal community by boosting the relative abundance of Ascomycota, Basidiomycota, and Mortierellomycota (Fig. 12), taxa essential for organic matter decomposition and pathogen suppression (Jianhong et al. 2021 ; Zhao et al. 2024 ). The significant enrichment of Mortierellomycota suggests a role in phosphorus solubilization, supported by findings that organic fertilizers stimulate P−cycling microbes (Asif et al. 2023 ; Zhu et al. 2024 ). The enhanced bacterial alpha diversity in the banana rhizosphere under M2 (Fig. 13c–d) confirms that this fertilization approach fosters a more stable and functionally diverse rhizosphere micro−ecology, resonating with the benefits of integrated NPKM practices observed in other systems (Asif et al. 2023 ; Xu et al. 2017 ). The positive influence of the M2 treatment on plant−microbe−soil interactions was further elucidated through correlation analysis. Key bacterial taxa enriched by M2, specifically Proteobacteria and Bacteroidota, showed significant positive correlations with root development indices (root length density, root surface area) and soil available potassium (Fig. 14), indicating their potential role in promoting banana growth and K utilization. Similarly, the fungal phylum Blastocladiomycota, which was positively correlated with soil nutrients (Fig. 15), suggests a mechanism through which M2 improves soil fertility by regulating the fungal community (Guo et al. 2019 ; Yang et al. 2024 ). In summary, the M2 treatment optimized both the composition and diversity of bacterial and fungal communities, enhancing the efficiency of plant−soil system interactions. This aligns with conclusions from long−term experiments that advocate the “manure + chemical fertilizer” model to enhance microbial functions and crop productivity (Asif et al. 2023 ; Ren et al. 2021 ; Xu et al. 2017 ). Future research should integrate metagenomics and metabolomics to unravel the precise functional mechanisms of these key microbial taxa, thereby informing the design of precision fertilization strategies for sustainable intercropping systems (Chen et al. 2021 ; Zhao et al. 2024 ; Zou et al. 2024 ). Conclusion The intercropping system of young rubber trees and bananas, under various fertilization regimes, significantly impacts both the temporal and spatial distribution of their root systems, interspecific competition, soil nutrient availability, and rhizosphere microbial communities. Notably, the strategy of replacing 30% of chemical nitrogen with organic fertilizer (M2) offers distinct advantages. This approach alleviates root competition and ecological challenges across most growth stages while enhancing complementary effects and improving soil nitrogen, phosphorus, and organic matter content. Critically, the M2 treatment was most effective in modulating the rhizosphere micro−ecological environment, fostering a more beneficial microbial community structure and enhancing bacterial diversity in the banana rhizosphere. The observed positive correlations between these optimized microbial communities, root development indices, and soil nutrient availability underscore the role of microbial regulation in the improved plant growth and system performance under the M2 regimen. The findings of this study provide both theoretical and practical insights for optimizing fertilization strategies in young rubber tree–banana intercropping systems under the specified experimental conditions. Furthermore, these results lay the groundwork for future investigations into the mechanisms of interspecific interactions and plant−microbe−soil feedbacks facilitated by this fertilization approach. Future research should focus on unraveling the molecular mechanisms that underpin the benefits of the rubber−banana intercropping system within this fertilization framework, particularly the functional roles of key microbial taxa in facilitating nutrient cycling and plant health. Declarations Acknowledgments This work was financially supported by the National Key R&D Program of China (Grant no. 2023YFD1901400), the National Natural Science Foundation of China (Grant no. 32460811), the Central Public−interest Scientific Institution Basal Research Fund, China (Grant no. 1630022022002), the China Agriculture Research System (Grant no. CARS − 33 − ZP2). Credit authorship contribution statement Dongqi Jin: Methodology, Investigation, Data curation, Writing−Original draft preparation. Hongzhu Yang: Data curation, Methodology, Investigation, Writing−Original draft preparation. Yujie Tan: Methodology, Investigation, Writing−Original draft preparation. Lingxuan Qiu: Investigation, Writing−Original draft preparation. Binyao Chen: Data curation, Investigation. Tao Bi: Data curation, Investigation. Wei Luo: Supervision, Conceptualization. Zhengzao Cha: Methodology, Investigation. Hailin Liu: Funding acquisition, Data curation, Writing – review & editing. Qinghuo Lin: Funding acquisition, Supervision, Writing – review & editing. References A MM GLM, Ming G, C RSMRHJ, Jinliang SJRAJ Y (2021) Rhizosphere Microbiomes in a Historical Maize-Soybean Rotation System Respond to Host Species and Nitrogen Fertilization at the Genus and Subgenus Levels. Appl Environ Microbiol 87:e0313220–e0313220. 10.1128/aem.03132-20 Asghar W, Craven KD, Swenson JR, Kataoka R, Mahmood A, Farias JG (2024) Enhancing the Resilience of Agroecosystems Through Improved Rhizosphere Processes: A Strategic Review. Int J Mol Sci 26:109–109. 10.3390/ijms26010109 Asif K, Gaoning Z, Tianyang L, Binghui H (2023) Fertilization and cultivation management promotes soil phosphorus availability by enhancing soil P-cycling enzymes and the phosphatase encoding genes in bulk and rhizosphere soil of a maize crop in sloping cropland. Ecotoxicol Environ Saf 264:115441–115441. 10.1016/j.Ecoenv.2023.115441 Cardinael R, Mao Z, Prieto I, Stokes A, Dupraz C, Kim JH, Jourdan C (2015) Competition with winter crops induces deeper rooting of walnut trees in a Mediterranean alley cropping agroforestry system. Plant Soil 391:219–235. 10.1007/s11104-015-2422-8 Chen C, Liu W, Wu J, Jiang X, Zhu X (2019) Can intercropping with the cash crop help improve the soil physico-chemical properties of rubber plantations? Geoderma 335:149–160. 10.1016/j.geoderma.2018.08.023 Chen P, Chaoyang M, Chao H, Hao C, Jingdong L, Jingping Y (2021) Shift of microbial turnover time and metabolic efficiency strongly regulates rhizosphere priming effect under nitrogen fertilization in paddy soil. Sci Total Environ 800:149590–149590. 10.1016/j.Scitotenv.2021.149590 Cheng Z, Meng L, Yin T, Li Y, Zhang Y, Li S (2023) Changes in Soil Rhizobia Diversity and Their Effects on the Symbiotic Efficiency of Soybean Intercropped with Maize. Agronomy 13:997. 10.3390/agronomy13040997 Clermont-Dauphin C, Dissataporn C, Suvannang N, Pongwichian P, Maeght J-l, Hammecker C, Jourdan C (2018) Intercrops improve the drought resistance of young rubber trees. Agron Sustain Dev 38. 10.1007/s13593-018-0537-z Cong WF, Hoffland E, Li L, Six J, Sun JH, Bao XG, Zhang FS, Van Der Werf W (2015) Intercropping enhances soil carbon and nitrogen. Glob Chang Biol 21:1715–1726. 10.1111/gcb.12738 Dai YS, Yang T, Shen L, Wang XY, Zhang WL, Liu TT, Lu WH, Li LH, Zhang W (2021) Root growth, distribution, and physiological characteristics of alfalfa in a poplar/alfalfa silvopastoral system compared to sole-cropping in northwest Xinjiang, China. Agrofor Syst 95:1137–1153. 10.1007/s10457-021-00639-1 Duan Y, Shen J, Zhang X, Wen B, Ma Y, Wang Y, Fang W, Zhu X (2019) Effects of soybean–tea intercropping on soil-available nutrients and tea quality. Acta Physiol Plant 41. 10.1007/s11738-019-2932-8 Duan ZP, Gan YW, Wang BJ, Hao XD, Xu WL, Zhang W, Li LH (2017) Interspecific interaction alters root morphology in young walnut/wheat agroforestry systems in northwest China. Agrofor Syst 93:419–434. 10.1007/s10457-017-0133-2 Gong X, Dang K, Lv S, Zhao G, Wang H, Feng B (2021) Interspecific competition and nitrogen application alter soil ecoenzymatic stoichiometry, microbial nutrient status, and improve grain yield in broomcorn millet/mung bean intercropping systems. Field Crops Res 270. 10.1016/j.fcr.2021.108227 Guo Z, Zhang J, Fan J, Yang X, Yi Y, Han X, Wang D, Zhu P, Peng X (2019) Does animal manure application improve soil aggregation? Insights from nine long-term fertilization experiments. Sci Total Environ 660:1029–1037. 10.1016/j.scitotenv.2019.01.051 Han S, Luo X, Tan S, Wang J, Chen W, Huang Q (2020) Soil aggregates impact nitrifying microorganisms in a vertisol under diverse fertilization regimes. Eur J Soil Sci 71:536–547. 10.1111/ejss.12881 Hu F, Tan Y, Yu A, Zhao C, Fan Z, Yin W, Chai Q, Coulter JA, Cao W (2020) Optimizing the split of N fertilizer application over time increases grain yield of maize-pea intercropping in arid areas. Eur J Agron 119. 10.1016/j.eja.2020.126117 Huang H, Wu H, Rosana L, Yin D, Shen H, Zhang P (2022) Effects of Pre-Hardening and Autumn Fertilization on Biomass Allocation and Root Morphology of Pinus koraiensis Seedlings. Forests 14:59–59. 10.3390/f14010059 Jiang Y, Zhang R, Zhang C, Su J, Wen F, Deng X (2022) Long-term organic fertilizer additions elevate soil extracellular enzyme activities and tobacco quality in a tobacco-maize rotation. Frontiers in Plant Science 13: 973639–973639. doi: 10.3389/fpls.2022.973639 Jianhong R, Xiaoli L, Wenping Y, Xiaoxiao Y, Wenguang L, Qing X, Junhui L, Zhiqiang G, Zhenping Y (2021) Rhizosphere soil properties, microbial community, and enzyme activities: Short-term responses to partial substitution of chemical fertilizer with organic manure. J Environ Manage 299:113650–113650. 10.1016/j.Jenvman.2021.113650 Langenberger G, Cadisch G, Martin K, Min S, Waibel H (2016) Rubber intercropping: a viable concept for the 21st century? Agrofor Syst 91:577–596. 10.1007/s10457-016-9961-8 Li J, Lin W (2021a) Effects of nitrogen fertilizer rates on the growth and nutrient utilization of calla lily intercropped with rubber trees. Soil Tillage Res 211. 10.1016/j.still.2021.105031 Li J, Lin W (2021b) Effects of nitrogen fertilizer rates on the growth and nutrient utilization of calla lily intercropped with rubber trees. Soil Tillage Res 211. 10.1016/j.Still.2021.105031 Li J, Zhou L, Lin W (2018) Competitive characteristics related to nitrogen utilization and calla lily growth in rubber–calla lily intercropping systems. Industrial Crops Prod 125:567–572. 10.1016/j.indcrop.2018.09.032 Li X-F, Wang Z-G, Bao X-G, Sun J-H, Yang S-C, Wang P, Wang C-B, Wu J-P, Liu X-R, Tian X-L, Wang Y, Li J-P, Wang Y, Xia H-Y, Mei P-P, Wang X-F, Zhao J-H, Yu R-P, Zhang W-P, Che Z-X, Gui L-G, Callaway RM, Tilman D, Li L (2021) Long-term increased grain yield and soil fertility from intercropping. Nat Sustain 4:943–950. 10.1038/s41893-021-00767-7 Liu C, Gong X, Dang K, Li J, Yang P, Gao X, Deng X, Feng B (2020) Linkages between nutrient ratio and the microbial community in rhizosphere soil following fertilizer management. Environ Res 184:109261. 10.1016/j.envres.2020.109261 Liu P, Li X, Hu S, He W, Zhou Y, Wang Y (2024) Effects of Nitrogen Forms on Root Morphology and Nitrogen Accumulation inPinus tabuliformiscarr. Seedlings under Exponential Fertilization. Forests 15. 10.3390/f15020271 Liu T, Wang X, Shen L, Wei W, Zhang S, Wang M, Zhu Y, Tuertia T, Zhang W (2023) Apricot can improve root system characteristics and yield by intercropping with alfalfa in semi-arid areas. Plant Soil 506:1–18. 10.1007/s11104-023-05919-6 Liu Y-X, Sun J-H, Zhang F-F, Li L (2019) The plasticity of root distribution and nitrogen uptake contributes to recovery of maize growth at late growth stages in wheat/maize intercropping. Plant Soil 447:39–53. 10.1007/s11104-019-04034-9 Ma P, Nan S, Yang X, Qin Y, Ma T, Li X, Yu Y, Bodner G (2022) Macroaggregation is promoted more effectively by organic than inorganic fertilizers in farmland ecosystems of China—A meta-analysis. Soil Tillage Res 221. 10.1016/j.still.2022.105394 Mengmeng C, Zhang S, Liu L, Wu L, Ding X (2021) Combined organic amendments and mineral fertilizer application increase rice yield by improving soil structure, P availability and root growth in saline-alkaline soil. Soil Tillage Res 212. 10.1016/j.Still.2021.105060 Michels T, Eschbach J-M, Lacote R, Benneveau A, Papy F (2012) Tapping panel diagnosis, an innovative on-farm decision support system for rubber tree tapping. Agron Sustain Dev 32:791–801. 10.1007/s13593-011-0069-2 Ning R, Yang W, Youliang Y, Yanan Z, Yufang H, Wen F, Xv C (2020) Effects of Continuous Nitrogen Fertilizer Application on the Diversity and Composition of Rhizosphere Soil Bacteria. Front Microbiol 11:1948–1948. 10.3389/fmicb.2020.01948 Noordwijk MV, Lawson G, Hairiah K, Wilson J (2015) Root distribution of trees and crops Competition andor complementarity. In Tree-Crop Interactions Agroforestry in a Changing Climate Oouchi M, Ukawa J, Ishii Y, Maeda H (2019) Structural Analysis of the Terminal Groups in Commercial Hevea Natural Rubber by 2D-NMR with DOSY Filters and Multiple-WET Methods Using Ultrahigh-Field NMR. Biomacromolecules 20:1394–1400. 10.1021/acs.biomac.8b01771 Pianka ER (1973) The structure of lizard communities. Annu Rev Ecol Syst 4:53–74 Qi D, Wu Z, Chen B, Zhang X, Yang C, Fu Q (2024) Integrative cultivation pattern, distribution, yield and potential benefit of rubber based agroforestry system in China. Industrial Crops Prod 220:119228–119228. 10.1016/j.Indcrop.2024.119228 Qi D, Wu Z, Yang C, Xie G, Li Z, Yang X, Li D (2021) Can intercropping with native trees enhance structural stability in young rubber (Hevea brasiliensis) agroforestry system? Eur J Agron 130. 10.1016/j.Eja.2021.126353 Ren J, Xiaoli L, Wenping Y, Xiaoxiao Y, Wenguang L, Qing X, Junhui L, Zhiqiang G, Zhenping Y (2021) Rhizosphere soil properties, microbial community, and enzyme activities: Short-term responses to partial substitution of chemical fertilizer with organic manure. J Environ Manage 299:113650–113650. 10.1016/j.Jenvman.2021.113650 Rodrigo VHL, Stirling CM, Silva TUK, Pathirana PD (2004) The growth and yield of rubber at maturity is improved by intercropping with banana during the early stage of rubber cultivation. Field Crops Res 91:23–33. 10.1016/j.fcr.2004.05.005 Roohi M, Arif MS, Yasmeen T, Riaz M, Rizwan M, Shahzad SM, Ali S, Bragazza L (2020) Effects of cropping system and fertilization regime on soil phosphorous are mediated by rhizosphere-microbial processes in a semi-arid agroecosystem. J Environ Manage 271:111033–111033. 10.1016/j.jenvman.2020.111033 Saudy HS, Hamed MF, Abd El-Momen WR, Hussein H (2020) Nitrogen use Rationalization and Boosting Wheat Productivity by Applying Packages of Humic, Amino Acids, and Microorganisms. Commun Soil Sci Plant Anal 51:1036–1047. 10.1080/00103624.2020.1744631 Silva MJ, J. DY LYA (2023) Electrically-assisted supersonic solution blowing and solution blow spinning of fibrous materials from natural rubber extracted from havea brasilienses. Industrial Crops Prod 192. 10.1016/j.Indcrop.2022.116101 Wang Y, Qin Y, Chai Q, Feng F, Zhao C, Yu A (2018) Interspecies Interactions in Relation to Root Distribution Across the Rooting Profile in Wheat-Maize Intercropping Under Different Plant Densities. Front Plant Sci 9:483. 10.3389/fpls.2018.00483 Wei W, Liu T, Zhang S, Shen L, Wang X, Li L, Zhu Y, Zhang W (2024) Root spatial distribution and belowground competition in an apple/ryegrass agroforestry system. Agric Syst 215. 10.1016/j.agsy.2024.103869 Wu J, Liu W, Chen C (2016a) Can intercropping with the world's three major beverage plants help improve the water use of rubber trees? J Appl Ecol 53:1787–1799. 10.1111/1365-2664.12730 Wu J, Liu W, Chen C, Bennett J (2016b) Can intercropping with the world's three major beverage plants help improve the water use of rubber trees? J Appl Ecol 53:1787–1799. 10.1111/1365-2664.12730 Wu X, Wu F, Zhou X, Fu X, Tao Y, iXu W, Pan K, Liu S (2016c) Effects of Intercropping with Potato Onion on the Growth of Tomato and Rhizosphere Alkaline Phosphatase Genes Diversity. Front Plant Sci 7:846. 10.3389/fpls.2016.00846 Xu L, Min Y, Huilan Y, Erhu G, Aiying Z (2017) Manure and mineral fertilization change enzyme activity and bacterial community in millet rhizosphere soils. World J Microbiol Biotechnol 34:8. 10.1007/s11274-017-2394-3 Yang B, Meng X, Singh AK, Wang P, Song L, Zakari S, Liu W (2020a) Intercrops improve surface water availability in rubber-based agroforestry systems. Agric Ecosyst Environ 298. 10.1016/j.agee.2020.106937 Yang B, Meng X, Singh AK, Wang P, Song L, Zakari S, Liu W (2020b) Intercrops improve surface water availability in rubber-based agroforestry systems. Agric Ecosyst Environ 298. 10.1016/j.agee.2020.106937 Yang B, Meng X, Zhu X, Zakari S, Singh AK, Bibi F, Mei N, Song L, Liu W (2021) Coffee performs better than amomum as a candidate in the rubber agroforestry system: Insights from water relations. Agric Water Manage 244. 10.1016/j.agwat.2020.106593 Yang Y, Yao F, Sun Y, Yang Z, Li R, Bai G, Lin W, Chen H (2024) Appropriately Reduced Nitrogen and Increased Phosphorus in Ratooning Rice Increased the Yield and Reduced the Greenhouse Gas Emissions in Southeast China. Plants (Basel Switzerland) 13:438. 10.3390/plants13030438 Yu L, Luo S, Xu X, Gou Y, Wang J (2020) The soil carbon cycle determined by GeoChip 5.0 in sugarcane and soybean intercropping systems with reduced nitrogen input in South China. Appl Soil Ecol 155. 10.1016/j.apsoil.2020.103653 Yuan X, Yang B, Liu W, Wu J, Li X (2024) Intercropping with cash crops promotes sustainability of rubber agroforestry: Insights from litterfall production and associated carbon and nutrient fluxes. Eur J Agron 154:127071. 10.1016/j.Eja.2023.127071 Zhao Y, Wang S, Zhang M, Zeng L, Zhang L, Huang S, Zhang R, Zhou W, Ai C (2024) Nitrogen Application and Rhizosphere Effect Exert Opposite Effects on Key Straw-Decomposing Microorganisms in Straw-Amended Soil. Microorganisms 12. 10.3390/microorganisms12030574 Zheng B-c, Ying Z, Ping C, Xiao-na Z, Qing DU, Huan Y, Xiao-chun W, Feng Y, Te X, Long LI, Wen-yu Y, Tai-wen Y (2022a) Maize–legume intercropping promote N uptake through changing the root spatial distribution, legume nodulation capacity, and soil N availability. J Integr Agric 21:1755–1771. 10.1016/s2095-3119(21)63730-9 Zheng B, Chen P, Du Q, Yang H, Luo K, Wang X, Yang F, Yong T, Yang W (2022b) Soil Organic Matter, Aggregates, and Microbial Characteristics of Intercropping Soybean under Straw Incorporation and N Input. Agriculture 12:1409–1409. 10.3390/agriculture12091409 Zhu W, Zhao H, Wang Y, Butterly CR, Chen H, Yuan J, Liu M, Chen Q, Zhang L, Wang L (2024) Optimal organic fertilization enhances the phytoavailability of phosphorus in the root zone of rice. Eur J Soil Sci 75. 10.1111/ejss.13588 Zou Q, Zhao L, Guan L, Chen P, Zhao J, Zhao Y, Du Y, Xie Y (2024) The synergistic interaction effect between biochar and plant growth-promoting rhizobacteria on beneficial microbial communities in soil. Front Plant Sci 15:1501400–1501400. 10.3389/fpls.2024.1501400 Tables Table 1 Underground interspecific competition intensity index for each treatment in different soil depths. Growth stage Soil depth (cm) Underground interspecific competition intensity index M1 M2 M3 Vigorous growth stage 0-20 0.59 0.54 0.76 20-40 0.66 0.67 0.90 40-60 1.00 0.33 0.33 mean value 0.75aA 0.51aB 0.66aA Bud development stage 0-20 0.73 0.65 0.89 20-40 0.87 0.91 0.90 40-60 1.00 1.00 0.67 mean value 0.87aA 0.85aA 0.82aA Harvest stage 0-20 0.82 0.89 0.74 20-40 0.96 0.85 0.50 40-60 1.00 1.00 1.00 mean value 0.93aA 0.91aA 0.75aA Note: Different lowercase letters indicate significant differences between the treatments in the same stage ( p < 0.05). Different uppercase letters indicate significant differences of the same treatment between the stages ( p < 0.05). Table 2 Underground interspecific competition intensity index for each treatment in different distances from the rubber tree. Growth stage Distance from the tree (cm) Underground interspecific competition intensity index M1 M2 M3 Vigorous growth stage 30 0.11 0.08 0.08 60 0.28 0.16 0.11 90 0.30 0.07 0.10 120 0.26 0.18 0.32 150 0.00 0.33 0.33 mean value 0.19aA 0.16aAB 0.19aA Bud development stage 30 0.22 0.07 0.18 60 0.19 0.15 0.18 90 0.37 0.29 0.20 120 0.00 0.09 0.21 150 0.00 0.00 0.00 mean value 0.16aA 0.12aB 0.16aA Harvest stage 30 0.18 0.14 0.20 60 0.26 0.25 0.21 90 0.31 0.45 0.13 120 0.15 0.25 0.33 150 0.33 0.33 0.33 mean value 0.25aA 0.28aA 0.24aA Note: Different lowercase letters indicate significant differences between the treatments in the same stage ( p <0.05). Different uppercase letters indicate significant differences of the same treatment between the stages ( p <0.05). Supplementary Files GA.tif Highlights.docx Supplymentdocument.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8835228","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":594459255,"identity":"af3f6228-5cd2-47e6-9c24-69f7ca325f1d","order_by":0,"name":"Dongqi Jin","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Dongqi","middleName":"","lastName":"Jin","suffix":""},{"id":594459256,"identity":"04883f5d-717f-4d6b-9288-ca52d590bd92","order_by":1,"name":"Hongzhu Yang","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Hongzhu","middleName":"","lastName":"Yang","suffix":""},{"id":594459257,"identity":"46978558-722c-4007-9fd7-e8c825a5a123","order_by":2,"name":"Yujie Tan","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Yujie","middleName":"","lastName":"Tan","suffix":""},{"id":594459258,"identity":"4d7e50db-5d0f-4b83-a55b-4c93fbda6156","order_by":3,"name":"Lingxuan Qiu","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Lingxuan","middleName":"","lastName":"Qiu","suffix":""},{"id":594459259,"identity":"726a6082-11cf-4021-a6da-fff5e957f55b","order_by":4,"name":"Binyao Chen","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Binyao","middleName":"","lastName":"Chen","suffix":""},{"id":594459260,"identity":"d7c831fd-e6d2-480e-bb9d-4fa64aa74cbe","order_by":5,"name":"Bi Tao","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Bi","middleName":"","lastName":"Tao","suffix":""},{"id":594459261,"identity":"030ad2fd-87a1-49aa-ad45-a60d18296d13","order_by":6,"name":"Wei Luo","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Wei","middleName":"","lastName":"Luo","suffix":""},{"id":594459262,"identity":"ef628aff-8338-4db2-b42f-841f47946717","order_by":7,"name":"Zhengzao Cha","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Zhengzao","middleName":"","lastName":"Cha","suffix":""},{"id":594459263,"identity":"da6863bd-8c0b-42db-893d-0c410eb024c3","order_by":8,"name":"Hailin Liu","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Hailin","middleName":"","lastName":"Liu","suffix":""},{"id":594459264,"identity":"e5e17dd6-3db8-42e1-9be3-ff1a1b22dfc2","order_by":9,"name":"Qinghuo Lin","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAw0lEQVRIiWNgGAWjYDACZjBikOEnWQuPZAMDYwMpuhh4DA4Qq4XvOO/h14VtNjzGxw8/f/DjD4O8OSEtkof50qxntqXxmJ1JM2zsbWMw3EnILoPDPGbGvG1A8gaDYQNvA0MC0IVEajGewf6x8c8f4rQYPwZpMZDgMWzmYSNCiyTQFmaec2k8EmdyCmfLtkkYbiCkhe/8GePPPGU2cvztxzd8fPPHRp6gLQwHGNgkkLgSOBUia2H+QISyUTAKRsEoGMkAAAhmPHU268ggAAAAAElFTkSuQmCC","orcid":"","institution":"Chinese Academy of Tropical Agricultural Sciences Rubber Research Institute","correspondingAuthor":true,"prefix":"","firstName":"Qinghuo","middleName":"","lastName":"Lin","suffix":""}],"badges":[],"createdAt":"2026-02-10 01:40:26","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8835228/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8835228/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":103477228,"identity":"9fe9d9b5-c7d2-4ff0-987f-073d45ab1c7a","added_by":"auto","created_at":"2026-02-26 07:21:05","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":139437,"visible":true,"origin":"","legend":"\u003cp\u003eDaily temperature and rainfall during the banana growth stage. a represents the vigorous stage of banana, b represents the bud pregnancy stage of banana, c represents the harvest stage of banana.\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8835228/v1/db5965009bead98b8150bf3a.jpg"},{"id":103507447,"identity":"4312b759-a264-469f-a171-2d201648293a","added_by":"auto","created_at":"2026-02-26 13:41:18","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":96319,"visible":true,"origin":"","legend":"\u003cp\u003eSketch of sampling procedure for rubber tree and banana soil under each treatment.\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8835228/v1/85c8e67a7dc68ff94d492c5a.jpg"},{"id":103508094,"identity":"64267dce-b561-42f3-a0d7-24959c3ebc17","added_by":"auto","created_at":"2026-02-26 13:47:10","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":102860,"visible":true,"origin":"","legend":"\u003cp\u003ePlant growth and leaf chlorophyll content at harvest stage. (a) Plant height; (b) Stem girth; (c) Leaf chlorophyll content. CK, control treatment with young rubber tree monoculture; M1, conventional chemical fertilizer treatment; M2, 30% organic nitrogen substitution treatment; M3, controlled-release nitrogen fertilizer combined with 45% organic nitrogen substitution treatment.\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8835228/v1/2ea69b1ba65a5c02a184d88a.jpg"},{"id":103477224,"identity":"bbbe2b05-9ec8-4dfb-809b-ec50ee891a1a","added_by":"auto","created_at":"2026-02-26 07:21:04","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":229188,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution of root biomass. Vigorous growth stage (a, d, g, j), bud development stage (b, e, h, k), harvest stage (c, f, i, l), from top to bottom are CK, M1, M2, M3. CK, control treatment as young rubber tree monoculture; M1, conventional chemical fertilizer treatment; M2, 30% organic nitrogen substitution treatment; M3, controlled released nitrogen fertilizer combined with 45% treatment.\u003c/p\u003e","description":"","filename":"4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8835228/v1/34bcb5f4ba1727009195a3e8.jpg"},{"id":103507293,"identity":"747da92e-4069-4d91-a529-af6959ca7c2d","added_by":"auto","created_at":"2026-02-26 13:40:54","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":235681,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution of root length destiny (RLD). Vigorous growth stage (a, d, g, j), bud development stage (b, e, h, k), harvest stage (c, f, i, l), from top to bottom are CK, M1, M2, M3. CK, control treatment as young rubber tree monoculture; M1, conventional chemical fertilizer treatment; M2, 30% organic nitrogen substitution treatment; M3, controlled released nitrogen fertilizer combined with 45% treatment.\u003c/p\u003e","description":"","filename":"5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8835228/v1/969e9d49650a9d5125c40330.jpg"},{"id":103508086,"identity":"2703f5ec-7926-44c8-8bfb-0f8347505899","added_by":"auto","created_at":"2026-02-26 13:47:09","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":256020,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution of root surface area destiny (RSAD). Vigorous growth stage (a, d, g, j), bud development stage (b, e, h, k), harvest stage (c, f, i, l), from top to bottom are CK, M1, M2, M3. CK, control treatment as young rubber tree monoculture; M1, conventional chemical fertilizer treatment; M2, 30% organic nitrogen substitution treatment; M3, controlled released nitrogen fertilizer combined with 45% treatment.\u003c/p\u003e","description":"","filename":"6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8835228/v1/80e65146c66e600e5d269a20.jpg"},{"id":103477226,"identity":"61b675e8-5478-4555-adeb-397bd39f7984","added_by":"auto","created_at":"2026-02-26 07:21:04","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":275574,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution of soil available nitrogen content. Vigorous growth stage (a, d, g, f), bud development stage (b, e, h, k), harvest stage (c, f, i, l), from top to bottom are CK, M1, M2, M3. CK, control treatment as young rubber tree monoculture; M1, conventional chemical fertilizer treatment; M2, 30% organic nitrogen substitution treatment; M3, controlled released nitrogen fertilizer combined with 45% treatment.\u003c/p\u003e","description":"","filename":"7.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8835228/v1/8e35f64deb76e65a79304da0.jpg"},{"id":103477229,"identity":"5b2cf078-ef38-40fb-b42b-2991881f350a","added_by":"auto","created_at":"2026-02-26 07:21:05","extension":"jpg","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":180328,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution of soil available phosphorus content. Vigorous growth stage (a, d, g, f), bud development stage (b, e, h, k), harvest stage (c, f, i, l), from top to bottom are CK, M1, M2, M3. CK, control treatment as young rubber tree monoculture; M1, conventional chemical fertilizer treatment; M2, 30% organic nitrogen substitution treatment; M3, controlled released nitrogen fertilizer combined with 45% treatment.\u003c/p\u003e","description":"","filename":"8.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8835228/v1/6a90b4c01109ca9538dcdd80.jpg"},{"id":103477230,"identity":"2b7a47f5-b431-411c-ac21-693c11c84823","added_by":"auto","created_at":"2026-02-26 07:21:05","extension":"jpg","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":235476,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution of soil available potassium content. Vigorous growth stage (a, d, g, f), bud development stage (b, e, h, k), harvest stage (c, f, i, l), from top to bottom are CK, M1, M2, M3. CK, control treatment as young rubber tree monoculture; M1, conventional chemical fertilizer treatment; M2, 30% organic nitrogen substitution treatment; M3, controlled released nitrogen fertilizer combined with 45% treatment.\u003c/p\u003e","description":"","filename":"9.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8835228/v1/e0cf14c31ed3c08d7aee07f4.jpg"},{"id":103507989,"identity":"df642590-177c-41d9-8414-cd9a08a32c7a","added_by":"auto","created_at":"2026-02-26 13:46:47","extension":"jpg","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":229922,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution of soil organic matter content. Vigorous growth stage (a, d, g, f), bud development stage (b, e, h, k), harvest stage (c, f, i, l), from top to bottom are CK, M1, M2, M3. CK, control treatment as young rubber tree monoculture; M1, conventional chemical fertilizer treatment; M2, 30% organic nitrogen substitution treatment; M3, controlled released nitrogen fertilizer combined with 45% treatment.\u003c/p\u003e","description":"","filename":"10.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8835228/v1/cb1f14572414806c7dc015e7.jpg"},{"id":104808158,"identity":"23bc117b-b493-4439-b0e2-778d334393ef","added_by":"auto","created_at":"2026-03-17 12:23:23","extension":"jpg","order_by":11,"title":"Figure 11","display":"","copyAsset":false,"role":"figure","size":155669,"visible":true,"origin":"","legend":"\u003cp\u003eEffects of different fertilization treatments on the alpha diversity of rhizosphere microbial communities in rubber tree and banana at different spatial locations. a–d: Shannon index of bacterial communities; e–h: Chao1 index of bacterial communities; i–l: Shannon index of fungal communities; m–p: Chao1 index of fungal communities. a, e, i, m: Rubber tree rhizosphere (0-30 cm from rubber tree); b, f, j, n: Rubber tree rhizosphere in the interaction zone (60-90 cm from rubber tree); c, g, k, o: Banana rhizosphere in the interaction zone (60-90 cm from rubber tree); d, h, l, p: Banana rhizosphere (120-150 cm from rubber tree). CK, control treatment as young rubber tree monoculture; M1, conventional chemical fertilizer treatment; M2, 30% organic nitrogen substitution treatment; M3, controlled released nitrogen fertilizer combined with 45% treatment.\u003c/p\u003e","description":"","filename":"11.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8835228/v1/158f9e23b68a8a6c00da9f98.jpg"},{"id":103477234,"identity":"87035580-2cf8-4fd9-a9f3-e0bce73ba6ab","added_by":"auto","created_at":"2026-02-26 07:21:05","extension":"jpg","order_by":12,"title":"Figure 12","display":"","copyAsset":false,"role":"figure","size":169895,"visible":true,"origin":"","legend":"\u003cp\u003eEffects of different fertilization treatments on the composition of rhizosphere bacterial communities in rubber tree and banana at different spatial locations. a: Rubber tree rhizosphere (0-30 cm from rubber tree); b: Rubber tree rhizosphere in the interaction zone (60-90 cm from rubber tree); c: Banana rhizosphere in the interaction zone (60-90 cm from rubber tree); d: Banana rhizosphere (120-150 cm from rubber tree). CK, control treatment as young rubber tree monoculture; M1, conventional chemical fertilizer treatment; M2, 30% organic nitrogen substitution treatment; M3, controlled released nitrogen fertilizer combined with 45% treatment.\u003c/p\u003e","description":"","filename":"12.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8835228/v1/400a73e997e8036f0624d8f8.jpg"},{"id":103477237,"identity":"ebcdbed5-f544-42b4-a0f8-300de17803a8","added_by":"auto","created_at":"2026-02-26 07:21:05","extension":"jpg","order_by":13,"title":"Figure 13","display":"","copyAsset":false,"role":"figure","size":174330,"visible":true,"origin":"","legend":"\u003cp\u003eEffects of different fertilization treatments on the composition of rhizosphere fungal communities in rubber tree and banana at different spatial locations. a: Rubber tree rhizosphere (0-30 cm from rubber tree); b: Rubber tree rhizosphere in the interaction zone (60-90 cm from rubber tree); c: Banana rhizosphere in the interaction zone (60-90 cm from rubber tree); d: Banana rhizosphere (120-150 cm from rubber tree). CK, control treatment as young rubber tree monoculture; M1, conventional chemical fertilizer treatment; M2, 30% organic nitrogen substitution treatment; M3, controlled released nitrogen fertilizer combined with 45% treatment.\u003c/p\u003e","description":"","filename":"13.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8835228/v1/7ecb97deea56d1952f342a90.jpg"},{"id":103477238,"identity":"3fa02003-30ec-4480-be6f-f828e273f4cb","added_by":"auto","created_at":"2026-02-26 07:21:05","extension":"jpg","order_by":14,"title":"Figure 14","display":"","copyAsset":false,"role":"figure","size":143386,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelation analysis between rhizosphere bacterial communities and root/soil factors under different fertilization treatments. a: Rubber tree rhizosphere (0-30 cm from rubber tree); b: Rubber tree rhizosphere in the interaction zone (60-90 cm from rubber tree); c: Banana rhizosphere in the interaction zone (60-90 cm from rubber tree); d: Banana rhizosphere (120-150 cm from rubber tree). CK, control treatment as young rubber tree monoculture; M1, conventional chemical fertilizer treatment; M2, 30% organic nitrogen substitution treatment; M3, controlled released nitrogen fertilizer combined with 45% treatment.\u003c/p\u003e","description":"","filename":"14.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8835228/v1/de11f9aa983a72f3732dac7b.jpg"},{"id":103507462,"identity":"478d1563-2263-400c-883a-c1a548609c95","added_by":"auto","created_at":"2026-02-26 13:41:23","extension":"jpg","order_by":15,"title":"Figure 15","display":"","copyAsset":false,"role":"figure","size":146141,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelation analysis between rhizosphere fungal communities and root/soil factors under different fertilization treatments. a: Rubber tree rhizosphere (0-30 cm from rubber tree); b: Rubber tree rhizosphere in the interaction zone (60-90 cm from rubber tree); c: Banana rhizosphere in the interaction zone (60-90 cm from rubber tree); d: Banana rhizosphere (120-150 cm from rubber tree). CK, control treatment as young rubber tree monoculture; M1, conventional chemical fertilizer treatment; M2, 30% organic nitrogen substitution treatment; M3, controlled released nitrogen fertilizer combined with 45% treatment.\u003c/p\u003e","description":"","filename":"15.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8835228/v1/77954e9720b958d670c0aa63.jpg"},{"id":106726168,"identity":"8affa1d1-fd2d-47a5-a074-80ad725230ae","added_by":"auto","created_at":"2026-04-12 18:35:28","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4066292,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8835228/v1/a87ab187-2feb-4275-b468-d2a25a9a5e70.pdf"},{"id":103477239,"identity":"1e00bc6a-48c7-4a41-8a52-0714a88287e2","added_by":"auto","created_at":"2026-02-26 07:21:06","extension":"tif","order_by":7,"title":"","display":"","copyAsset":false,"role":"supplement","size":73667220,"visible":true,"origin":"","legend":"","description":"","filename":"GA.tif","url":"https://assets-eu.researchsquare.com/files/rs-8835228/v1/d46154b9a691aae7d91cc90f.tif"},{"id":103477232,"identity":"588c93b1-ec14-4e58-a104-1cb78011c3e8","added_by":"auto","created_at":"2026-02-26 07:21:05","extension":"docx","order_by":8,"title":"","display":"","copyAsset":false,"role":"supplement","size":19194,"visible":true,"origin":"","legend":"","description":"","filename":"Highlights.docx","url":"https://assets-eu.researchsquare.com/files/rs-8835228/v1/94bf0c7bcd780ddc48682dc2.docx"},{"id":103477235,"identity":"8cf41754-cb86-4f95-aa69-0463ddd1b0cf","added_by":"auto","created_at":"2026-02-26 07:21:05","extension":"docx","order_by":9,"title":"","display":"","copyAsset":false,"role":"supplement","size":20969,"visible":true,"origin":"","legend":"","description":"","filename":"Supplymentdocument.docx","url":"https://assets-eu.researchsquare.com/files/rs-8835228/v1/997fa3630ae81cce6c771812.docx"}],"financialInterests":"","formattedTitle":"Optimizing Belowground Interactions in Young Rubber Tree−Banana Intercropping via Partial Organic Fertilizer Substitution: Root Competition, Soil Nutrients, and Microbial Communities","fulltext":[{"header":"Introduction","content":"\u003cp\u003eNatural rubber, a key polymer material with exceptional properties, is widely utilized across various industrial applications. It is primarily sourced from rubber tree plantations(Oouchi et al. \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Silva et al. 2023). A significant challenge in global rubber production lies in the fact that rubber trees require an initial growth period of approximately six years before they begin to produce latex, during which no income is generated(Michels et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Rodrigo et al. \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). To address this income gap in the early stages of rubber production, farmers have adopted intercropping practices, integrating rubber trees with short\u0026minus;term annual and perennial crops such as tea, coffee, and bananas(Rodrigo et al. \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Wu et al. \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2016a\u003c/span\u003e; Yuan et al. \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Research suggests that native rubber tree agroforestry systems intercropped with other crops not only diversify income streams but also enable multi\u0026minus;variety and multi\u0026minus;level combinations, thereby optimizing resource utilization, including sunlight, soil moisture, and nutrients(Qi et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Qi et al. \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIntercropping offers a potentially effective strategy for enhancing farm profitability by increasing crop yields, improving soil fertility, and reducing environmental impact(Li and Lin \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2021b\u003c/span\u003e; Yang et al. \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2020b\u003c/span\u003e). The full realization of these advantages relies critically on rational nutrient management and its regulation of root systems. The application of appropriate fertilization strategies and effective nutrient management can stimulate root growth and influence root morphology and architecture(Huang et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Liu et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Mengmeng et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Moreover, the dynamic interplay between fertilization treatments and rhizosphere soil microorganisms also drive key biogeochemical processes, including nitrogen (N) fixation, phosphorus (P) solubilization, and carbon (C) cycling(Asghar et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Roohi et al. \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Yu et al. \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). For instance, legume\u0026minus;based intercropping systems demonstrate significant shifts in microbial diversity and abundance under varying N and P fertilization regimes, with low\u0026thinsp;\u0026minus;\u0026thinsp;N treatments often favoring nitrogen\u0026minus;fixing bacteria like \u003cem\u003eBradyrhizobium\u003c/em\u003e and \u003cem\u003eAllorhizobium\u0026minus;Neorhizobium\u0026minus;Pararhizobium\u0026minus;Rhizobium\u003c/em\u003e(Cheng et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Conversely, excessive N application can suppress these beneficial taxa, highlighting the need for balanced fertilization strategies to maintain microbial\u0026minus;mediated ecosystem services(A et al. 2021; Cheng et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). However, if the interaction between tree and crop root systems becomes excessively competitive, resource shortages may arise, undermining the potential benefits of intercropping and preventing optimal nutrient utilization. The competition for soil resources is influenced by the spatial distribution of roots, and the intensity of this competition can alter root spatial arrangement(Cardinael et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Therefore, optimizing root system architecture may help regulate interspecific interactions within cropping systems(Liu et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). In intercropping systems, strategic nitrogen application can modify crop growth dynamics by enhancing or mitigating interspecific competition(Gong et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eResearch demonstrates that the nutrient release characteristics of organic nitrogen and controlled\u0026minus;release nitrogen, when applied in appropriate proportions alongside chemical nitrogen, can improve both crop yield and stability. Innovative fertilization approaches, such as integrated organic\u0026minus;inorganic amendments (e.g., NPK\u0026minus;enriched compost or pig manure), have been shown to enhance microbial biomass and enzyme activities (e.g., sucrase, β\u0026thinsp;\u0026minus;\u0026thinsp;1,4\u0026thinsp;\u0026minus;\u0026thinsp;glucosidase, and phosphatases), which are critical for nutrient mobilization and soil health(Jiang et al. 2022; Roohi et al. \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Wu et al. \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2016c\u003c/span\u003e). It is critical for fertilization systems to adapt nitrogen management practices to optimize the temporal and spatial relationship between nitrogen supply and crop demand(Hu et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). In intercropping systems involving rubber trees and calla lilies, calla lilies enhance their competitive advantage for soil nitrogen by increasing root length and preferentially allocating root biomass(Li et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Although rubber trees possess deep, extensive root systems, intercropped species typically concentrate their roots closer to the soil surface, thereby increasing competition for nutrients and water(Yang et al. \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Root competition between rubber trees and intercropped species presents a significant challenge in assessing the viability of rubber agroforestry systems(Wu et al. \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2016b\u003c/span\u003e). The functional redundancy and niche differentiation of microbial communities under intercropping further complicate their response to fertilization. For example, ammonia\u0026minus;oxidizing archaea (AOA) and bacteria (AOB) exhibit distinct preferences for soil microhabitats, with their abundances strongly correlated with soil pH and organic C content(Han et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Zheng et al. \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2022b\u003c/span\u003e). Prior to the widespread implementation of rubber tree agroforestry, selecting intercropping species with complementary root strategies to mitigate competition is essential(Langenberger et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Thus, effective nitrogen fertilizer management strategies in rubber\u0026minus;based agroforestry systems can significantly enhance soil nutrient levels, optimize the spatial and temporal distribution of roots, and promote the sustainable development of the system.\u003c/p\u003e \u003cp\u003eBanana, a staple food crop grown in over 130 countries, is of particular importance in China as a tropical fruit. While some studies have examined the intercropping of rubber trees and bananas, research on the spatial and temporal distribution of root morphology, soil nutrient dynamics, and root competition under various fertilization patterns remains limited. Furthermore, how the rhizosphere microbial community in this system responds to partial organic nitrogen substitution, and how microbial processes interact with root distribution and soil nutrients, is currently unclear. This study posits that substituting 30% of chemical nitrogen fertilizer with organic nitrogen could positively influence rubber tree\u0026minus;banana intercropping systems. The goal of this research is to propose a science\u0026minus;based fertilization strategy for these systems, utilizing organic nitrogen to improve root morphology distribution, mitigate interspecific root competition, enhance soil nutrient levels, and further investigate the changes in rhizosphere microbial community structure and its association with system functioning. The study compared monoculture native rubber trees with three fertilization treatments in the rubber tree/banana intercropping system. The specific objectives are: (1) to analyze differences in the spatiotemporal distribution of roots between native rubber trees and bananas in monoculture and intercropping systems with varying fertilization approaches; (2) to assess how modifications in root distribution can reduce interspecific competition in intercropping systems with different fertilization regimes; (3) to evaluate soil nutrient levels in both monoculture and intercropping systems under the three fertilization treatments; and (4) to elucidate the impact of fertilization on the rhizosphere microbial community structure and explore its intrinsic links with soil nutrients and root distribution. This study aims to provide practical recommendations for optimizing nitrogen fertilizer management in native rubber tree\u0026minus;banana intercropping systems by enhancing root distribution, improving soil nutrient status, and regulating the rhizosphere microbial community, thereby establishing a pathway to the sustainable development of intercropping systems.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eExperimental site\u003c/h2\u003e \u003cp\u003eField experiments were conducted from October 2021 to August 2022 at the Tropical Fruit Tree Variety Improvement Base, Tropical Crops Genetic Resources Institute, Chinese Academy of Tropical Agricultural Sciences, located in Danzhou County, Hainan Province, China (109.5\u0026deg;E, 19.5\u0026deg;N). The experimental site is situated in a hot and humid climate, with a mean annual temperature of 23.3\u0026deg;C and annual precipitation of 1826 mm (Fig.\u0026nbsp;1).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003e[Insert Fig. 1]\u003c/h3\u003e\n\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eExperimental materials\u003c/h2\u003e \u003cp\u003eThe soil at the experimental site was classified as brick\u0026thinsp;\u0026minus;\u0026thinsp;red loam, with a pH of 5.16, organic matter content of 8.74 g\u0026middot;kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, total nitrogen content of 0.76 g\u0026middot;kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, and available nitrogen content of 100.85 mg\u0026middot;kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. The available phosphorus content was 7.32 mg\u0026middot;kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, and the available potassium content was 90.83 mg\u0026middot;kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e at the beginning of the experiment. The fertilizers used in the experiment included diammonium phosphate (N\u0026thinsp;\u0026ge;\u0026thinsp;20.8%, P\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e5\u003c/sub\u003e\u0026thinsp;\u0026ge;\u0026thinsp;53%), urea (N\u0026thinsp;\u0026ge;\u0026thinsp;46%), potassium dihydrogen phosphate (P\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e5\u003c/sub\u003e\u0026thinsp;\u0026ge;\u0026thinsp;52%, K\u003csub\u003e2\u003c/sub\u003eO\u0026thinsp;\u0026ge;\u0026thinsp;34%), potassium chloride (K\u003csub\u003e2\u003c/sub\u003eO\u0026thinsp;\u0026ge;\u0026thinsp;60%), polyurethane\u0026minus;coated urea with a fertilizer efficacy period of three months (N\u0026thinsp;\u0026ge;\u0026thinsp;43%), organic fertilizer (organic matter\u0026thinsp;\u0026ge;\u0026thinsp;45%, N\u0026minus;P\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e5\u003c/sub\u003e\u0026minus;K\u003csub\u003e2\u003c/sub\u003eO\u0026thinsp;\u0026ge;\u0026thinsp;5%), and water\u0026minus;soluble organic fertilizer (organic matter\u0026thinsp;\u0026ge;\u0026thinsp;320 g/L; N\u0026minus; P\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e5\u003c/sub\u003e\u0026minus; K\u003csub\u003e2\u003c/sub\u003eO\u0026thinsp;\u0026ge;\u0026thinsp;80 g/L). The seedlings tested included one\u0026minus;year\u0026thinsp;\u0026minus;\u0026thinsp;old tissue culture rubber tree Reyan 7\u0026thinsp;\u0026minus;\u0026thinsp;33\u0026minus;97 seedlings and Jiali banana tissue culture seedlings with 8\u0026ndash;9 leaves.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eExperimental design\u003c/h3\u003e\n\u003cp\u003eThe experiment employed a single\u0026minus;factor random block design with four treatments: monoculture rubber trees (CK), rubber tree\u0026minus;banana intercropping with conventional fertilization (M1), rubber tree\u0026minus;banana intercropping with a 30% organic nitrogen substitution treatment (M2), and rubber tree\u0026minus;banana intercropping with a 45% controlled\u0026minus;release nitrogen fertilizer combined with conventional chemical nitrogen treatment (M3). Each plot contained 7 rubber trees planted at a spacing of 2 m \u0026times; 4 m \u0026times; 20 m, and 54 banana plants spaced 1.5 m \u0026times; 1.5 m. Each treatment was replicated three times, yielding a total of 12 experimental plots, each with an area of 126 m\u003csup\u003e2\u003c/sup\u003e (10.5 m \u0026times; 12.0 m). In the initial year, the rubber trees in all treatments received the following fertilizer application: N 50 g\u0026middot;tree\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, P\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e5\u003c/sub\u003e 20 g\u0026middot;tree\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, K\u003csub\u003e2\u003c/sub\u003eO 55 g\u0026middot;tree\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. For the banana plants, treatments M1, M2, and M3 received a total nutrient dosage throughout their growth period of N 180 g, P\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e5\u003c/sub\u003e 80 g, and K\u003csub\u003e2\u003c/sub\u003eO 400 g. Nitrogen (N) was applied according to the following distribution: 10% at the seedling stage, 20% during vigorous growth, 20% at flower bud differentiation, 25% during bud development, 20% at bud emergence, and 5% at fruit expansion. Phosphorus (P) application followed this schedule: 20% at the seedling stage, 20% during vigorous growth, 20% at flower bud differentiation, 20% during bud development, 15% at bud emergence, and 5% at fruit expansion. Potassium (K) was distributed as follows: 5% at the seedling stage, 10% during vigorous growth, 20% at flower bud differentiation, 25% during bud development, 30% at bud emergence, and 10% at fruit expansion. In the M2 treatment, 50% of the organic fertilizer was applied as powdered organic fertilizer at the base, with the remaining 50% applied as water\u0026minus;soluble organic fertilizer, in line with the nitrogen application schedule for each growth stage. The M1and M2 treatment employed fertigation, while the M3 treatment involved six split applications of fertilizers via furrow application. Detailed quantities of fertilizer for banana cultivation are presented in Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e.\u003c/p\u003e\n\u003ch3\u003eTree height and stem girth\u003c/h3\u003e\n\u003cp\u003eThe height of each rubber tree and banana plant was measured at the banana harvest stage using a hypsometer. Stem girth was recorded 100 cm above the soil surface for each plant within the plot (N\u0026thinsp;=\u0026thinsp;5).\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eLeaf chlorophyll content\u003c/h2\u003e \u003cp\u003eDuring the banana harvest stage, mature leaves from the second leaf of both rubber trees and banana plants were selected for sampling. A 1:1 mixture of acetone and ethanol was used for a 24\u0026thinsp;\u0026minus;\u0026thinsp;hour light\u0026minus;proof extraction. The photosynthetic pigment content, including chlorophyll a, chlorophyll b, and total chlorophyll, was quantified using a UV\u0026minus;visible spectrophotometer (Wellburn, 1994).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eRoots and soil sampling and analysis\u003c/h3\u003e\n\u003cp\u003eThe rubber trees selected from each plot showed consistent growth, and a stratified excavation method was employed to sample the intercropping zones of rubber trees and bananas in the vigorous growth stage of bananas, the bud development stage, and the harvest stage. The rubber tree\u0026minus;banana intercropping area was divided into five equal sections, each 30 cm apart, with reference to the rubber tree. Sampling blocks, each measuring 60 cm \u0026times; 30 cm \u0026times; 20 cm (volume\u0026thinsp;=\u0026thinsp;3.6 \u0026times; 10\u003csup\u003e4\u003c/sup\u003e cm\u003csup\u003e3\u003c/sup\u003e), were excavated at depths of 0\u0026thinsp;\u0026minus;\u0026thinsp;20 cm, 20\u0026thinsp;\u0026minus;\u0026thinsp;40 cm, and 40\u0026thinsp;\u0026minus;\u0026thinsp;60 cm (Fig.\u0026nbsp;2). Root systems were carefully retrieved from each soil block. The bulk soil loosely adhering to the roots was removed and mixed to form a composite non-rhizosphere soil sample. This soil was then sealed in bags and transported to the laboratory for the determination of available nitrogen, available phosphorus, available potassium, and organic matter content. All collected roots were thoroughly rinsed with water and stored at \u0026minus;\u0026thinsp;4\u0026deg;C for further analysis. The rhizosphere soil was collected and preserved in centrifuge tubes, immediately frozen in liquid nitrogen, transferred to a \u0026minus;\u0026thinsp;80\u0026deg;C ultra-low temperature freezer upon arrival at the laboratory, and subsequently used for microbial analysis.\u003c/p\u003e\n\u003ch3\u003e[Insert Fig. 2]\u003c/h3\u003e\n\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eDetermination of morphological measurements and soil nutrients\u003c/h2\u003e \u003cdiv id=\"Sec12\" class=\"Section3\"\u003e \u003ch2\u003eRoot morphological measurements\u003c/h2\u003e \u003cp\u003eThe root shape index was determined by gently drying the clean rubber and banana roots using soft paper, followed by measuring their fresh weight. The roots were then scanned using an Epson scanner, and the obtained data, including root length and root surface area, were analyzed with WinRHIZO\u0026trade; software (Regent Instruments Inc., Quebec, Canada).\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eData processing\u003c/h2\u003e \u003cp\u003eThe root length density (RLD, cm\u0026middot;cm\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e) was calculated using Eq.\u0026nbsp;(1):\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eRLD\u0026thinsp;=\u0026thinsp;RL/SV (1)\u003c/h2\u003e \u003cp\u003eIn this equation, RL represents root length (cm) and SV denotes soil volume (cm\u003csup\u003e3\u003c/sup\u003e). The root surface area density (RSAD, cm\u003csup\u003e2\u003c/sup\u003e\u0026middot;cm\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e) was determined using Eq.\u0026nbsp;(2):\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eRSAD\u0026thinsp;=\u0026thinsp;RSA/SV (2)\u003c/h2\u003e \u003cp\u003eIn this equation, RSA refers to the root surface area (cm\u003csup\u003e2\u003c/sup\u003e) and SV is the soil volume (cm\u003csup\u003e3\u003c/sup\u003e).\u003c/p\u003e \u003cp\u003eThe underground interspecific competition intensity index (UICII) was calculated by Eq.\u0026nbsp;(3):\u003cdiv id=\"Equ1\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ1\" name=\"EquationSource\"\u003e\n$$\\:UICII=\\frac{\\sum\\:_{i=1}^{n}\\:{P}_{Ri}{P}_{Bi}}{\\sqrt{\\sum\\:_{i=1}^{n}\\:{P}_{Ri}^{2}\\sum\\:_{i=1}^{n}\\:{P}_{Bi}^{2}}}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e3\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eThe intensity of soil nutrient competition between the roots of rubber trees and bananas was quantified by quantifying the degree of overlap between the ecological niches occupied by each species (Levins, 1968). The formula of \u003cem\u003eUICII\u003c/em\u003e (0\u0026thinsp;\u0026le;\u0026thinsp;UICII\u0026thinsp;\u0026le;\u0026thinsp;1) is as follows (Pianka \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e1973\u003c/span\u003e):, where \u003cem\u003en\u003c/em\u003e represents the number of soil layers, and \u003cem\u003eP\u003c/em\u003e\u003csub\u003e\u003cem\u003eRi\u003c/em\u003e\u003c/sub\u003e and \u003cem\u003eP\u003c/em\u003e\u003csub\u003e\u003cem\u003eBi\u003c/em\u003e\u003c/sub\u003e denote the root proportion of rubber trees and bananas, respectively, in the \u003cem\u003ei\u003c/em\u003eth soil layer, relative to the total root distribution across all layers (soil depth 0\u0026thinsp;\u0026minus;\u0026thinsp;60 cm, distance from the tree 0\u0026thinsp;\u0026minus;\u0026thinsp;150 cm).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eSoil nutrition measurements\u003c/h2\u003e \u003cp\u003eSoil properties were determined as follows: soil organic matter content was quantified using the potassium dichromate volumetric method with external heating; available nitrogen was measured through distillation using a semi\u0026minus;micro Kjeldahl apparatus; available phosphorus was determined by HCl\u0026minus;NH\u003csub\u003e4\u003c/sub\u003eF molybdenum blue colorimetry; and available potassium was analyzed \u003cem\u003evia\u003c/em\u003e flame photometry following ammonia acetate extraction. These analytical methods were adapted from Bao (2000).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eMicrobiome Analysis\u003c/h2\u003e \u003cp\u003eThe bacterial and fungal community structures in the rhizosphere soil of rubber trees and bananas were analyzed using 16S rRNA and ITS amplicon sequencing, respectively. The detailed experimental procedure was as follows:\u003c/p\u003e \u003cp\u003e(1) DNA Extraction and Amplicon Sequencing\u003c/p\u003e \u003cp\u003eTotal DNA was extracted from the collected rhizosphere soil samples using a commercial kit. The V3\u0026thinsp;\u0026minus;\u0026thinsp;V4 hypervariable region of the bacterial 16S rRNA gene was amplified using the specific primers 338F (5\u0026prime;\u0026minus;ACTCCTACGGGAGGCAGCAG\u0026thinsp;\u0026minus;\u0026thinsp;3\u0026prime;) and 806R (5\u0026prime;\u0026minus;GGACTACHVGGGTWTCTAAT\u0026thinsp;\u0026minus;\u0026thinsp;3\u0026prime;). The ITS1 region of the fungal ITS gene was amplified using the primers ITS1F (5\u0026prime;\u0026minus;CTTGGTCATTTAGAGGAAGTAA\u0026thinsp;\u0026minus;\u0026thinsp;3\u0026prime;) and ITS2R (5\u0026prime;\u0026minus;GCTGCGTTCTTCATCGATGC\u0026thinsp;\u0026minus;\u0026thinsp;3\u0026prime;). The PCR reactions were carried out in a 15 \u0026micro;L mixture containing Phusion\u0026reg; High\u0026minus;Fidelity PCR Master Mix, 0.2 \u0026micro;M of each forward and reverse primer, and approximately 10 ng of template DNA. The thermal cycling conditions consisted of an initial denaturation at 98\u0026deg;C for 1 min; followed by 30 cycles of denaturation at 98\u0026deg;C for 10 s, annealing at 50\u0026deg;C for 30 s, and elongation at 72\u0026deg;C for 30 s; with a final extension at 72\u0026deg;C for 5 min.\u003c/p\u003e \u003cp\u003e(2) Library Construction and Sequencing\u003c/p\u003e \u003cp\u003eThe PCR products were detected by electrophoresis on a 2% agarose gel. Subsequently, the PCR products were pooled in equimolar ratios and purified. Sequencing libraries were constructed, and the quality of the libraries was assessed using Qubit for quantification and a bioanalyzer for size distribution detection. The qualified libraries were finally paired\u0026thinsp;\u0026minus;\u0026thinsp;end sequenced on an Illumina platform according to the effective library concentration and the required data volume.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analyses\u003c/h2\u003e \u003cp\u003eData are presented as the mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard error (SE) from triplicate measurements. Statistical analysis was performed using one\u0026thinsp;\u0026minus;\u0026thinsp;way ANOVA followed by Duncan\u0026rsquo;s multiple range test (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). All computations, including comparisons of the relative abundances of microbial taxa and alpha diversity indices (Shannon and Chao1), were carried out using SPSS 29.0 (IBM Corporation, USA). Experimental figures were generated using Origin 2021 (Origin Lab, USA). For microbial community analysis, Spearman correlation analysis was conducted to evaluate relationships between the relative abundance of dominant microbial phyla and root morphological or soil nutrient parameters. These analyses and associated visualizations were performed using R software (version 3.4.2) with the vegan and ggplot2 packages.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003ePlant Growth and Leaf Chlorophyll Content\u003c/h2\u003e \u003cp\u003eThe rubber tree/banana intercropping system with different fertilization strategies significantly influenced both plant growth and leaf chlorophyll content. For rubber trees, plant height increased by 4.83% under M1 and 16.26% under M2 compared to the monoculture control (CK), with M2 showing statistical significance while M3 resulted in a non-significant reduction (Fig.\u0026nbsp;3a). Stem girth of rubber trees increased by 8.17% under M2 compared to CK, whereas M1 and M3 showed minor non-significant decreases (Fig.\u0026nbsp;3b). In bananas, both M1 and M2 significantly enhanced plant height by 5.32% and 8.66%, respectively, compared to M3 (Fig.\u0026nbsp;3a), while stem girth increased by 8.34% and 10.93% under the same treatments (Fig.\u0026nbsp;3b). Regarding leaf chlorophyll content, rubber trees under M1 and M2 showed increased chlorophyll a by 5.42% and 3.61%, and total chlorophyll by 4.94% and 6.77% compared to CK, while M3 decreased total chlorophyll by 4.62% (Fig.\u0026nbsp;3c). No significant differences in chlorophyll content were observed in banana leaves across treatments (Fig.\u0026nbsp;3c). These findings demonstrate that the M2 treatment (30% organic nitrogen substitution) in the intercropping system most effectively promoted plant growth and leaf chlorophyll content in both crops.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003e[Insert Fig.\u0026nbsp;3]\u003c/h2\u003e \u003cdiv id=\"Sec22\" class=\"Section3\"\u003e \u003ch2\u003eSpatial and temporal distribution of root system\u003c/h2\u003e \u003cdiv id=\"Sec23\" class=\"Section4\"\u003e \u003ch2\u003eRoot biomass\u003c/h2\u003e \u003cp\u003eThe temporal and spatial distribution of root biomass for rubber tree monoculture and three different fertilization treatments in rubber\u0026minus;banana intercropping systems is presented in Fig.\u0026nbsp;4. Over time, from the banana vigorous growth stage to the bud development stage, the rubber tree root biomass decreased in the CK, M1, and M2 treatments, while it increased in the M3 treatment. At the banana bud development stage, the rubber root biomass was highest in the M2 treatment, reaching 21.78 g. From the banana bud development stage to the banana harvest stage, rubber root biomass generally increased in all treatments, except for a slight decrease in the M2 treatment. Nonetheless, by the banana harvest stage, the rubber tree root biomass in the M2 treatment remained the highest, at 19.70 g. In terms of banana root biomass, the M1 and M3 treatments peaked during the harvest period, reaching 177.69 g and 140.48 g, respectively, while the M2 treatment showed its peak at 203.02 g during the bud development stage. Regarding vertical spatial variation, during the banana bud development stage, rubber tree root biomass in the M2 treatment was higher than in other treatments. Specifically, in the 0\u0026thinsp;\u0026minus;\u0026thinsp;20 cm soil layer, biomass increased by 66.91% to 115.84%, while in the 20\u0026thinsp;\u0026minus;\u0026thinsp;40 cm layer, it increased by 140.08% to 625.47%. In the 40\u0026thinsp;\u0026minus;\u0026thinsp;60 cm layer, the increase ranged from 113.10% to 239.40%. Comparatively, banana root biomass in the M2 treatment in the 0\u0026thinsp;\u0026minus;\u0026thinsp;20 cm layer increased by 47.51% to 85.67% over the M1 and M3 treatments, while in the 20\u0026thinsp;\u0026minus;\u0026thinsp;40 cm layer, the increase was 11.10%, and in the 40\u0026thinsp;\u0026minus;\u0026thinsp;60 cm layer, it increased by 20.17% and 92.80%, respectively. In the horizontal distribution, during the banana harvest stage, within a 0\u0026thinsp;\u0026minus;\u0026thinsp;30 cm radius from the rubber tree, the rubber tree root biomass in the M2 treatment increased by 7.09% to 29.17% compared to other treatments.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003e[Insert Fig.\u0026nbsp;4]\u003c/h2\u003e \u003cdiv id=\"Sec25\" class=\"Section3\"\u003e \u003ch2\u003eRoot length destiny (RLD)\u003c/h2\u003e \u003cp\u003eThe temporal and spatial distribution of RLD in rubber tree monoculture and three different fertilization modes in rubber\u0026minus;banana intercropping systems is presented in Fig.\u0026nbsp;5. In terms of temporal variation, from the vigorous growth stage to the bud development stage of banana, the total RLD of rubber trees in the CK treatment decreased, while in the M1, M2, and M3 treatments, it increased. At the bud development stage, the total RLD of rubber trees in the M2 treatment peaked at 0.364 cm\u0026middot;cm\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e. Moving from the bud development stage to the harvest stage, the total RLD of rubber trees increased in the CK, M1, and M3 treatments, while it decreased in the M2 treatment. At the harvest stage, the highest total RLD of rubber trees was observed in the CK treatment, at 0.380 cm\u0026middot;cm\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e. Regarding banana RLD, the total RLD of the M1 and M3 treatments showed an increasing trend throughout banana growth, reaching peaks of 0.673 cm\u0026middot;cm\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e and 0.764 cm\u0026middot;cm\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e, respectively, at the harvest stage. In contrast, the highest total RLD for bananas in the M2 treatment occurred at the bud development stage, at 0.963 cm\u0026middot;cm\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e. In terms of vertical spatial variation, during the banana bud development stage, in the 0\u0026thinsp;\u0026minus;\u0026thinsp;20 cm soil layer, the total RLD of rubber trees in the M2 treatment increased by 213.44%, 44.78%, and 171.84% compared to the CK, M1, and M3 treatments, respectively. The total banana RLD in the M2 treatment increased by 88.50% and 79.98% compared to the M1 and M3 treatments, respectively. In the horizontal distribution, during the banana bud development stage, within a 0\u0026thinsp;\u0026minus;\u0026thinsp;30 cm distance from the rubber tree, the RLD of rubber trees in the M2 treatment increased by 203.37%, 34.53%, and 124.02% compared to the CK, M1, and M3 treatments, respectively. At a distance of 120\u0026thinsp;\u0026minus;\u0026thinsp;150 cm from the rubber tree, the RLD of bananas in the M2 treatment increased by 135.52% and 89.12% compared to the M1 and M3 treatments.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec26\" class=\"Section3\"\u003e \u003ch2\u003e[Insert Fig.\u0026nbsp;5]\u003c/h2\u003e \u003cdiv id=\"Sec27\" class=\"Section4\"\u003e \u003ch2\u003eRoot surface area destiny (RSAD)\u003c/h2\u003e \u003cp\u003eThe temporal and spatial distribution of RSAD in rubber tree monoculture and three different fertilization modes in rubber\u0026minus;banana intercropping systems is illustrated in Fig.\u0026nbsp;6. From the banana vigorous growth stage to the bud development stage, the RSAD of rubber trees decreased in the CK treatment, while it increased in the M1, M2, and M3 treatments. The highest RSAD value for rubber trees during the bud development stage was recorded in the M2 treatment, at 0.138 cm\u003csup\u003e2\u003c/sup\u003e\u0026middot;cm\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e. At the harvest stage, the RSAD of rubber trees in the M2 treatment slightly decreased, while it increased in the other treatments. The RSAD in the CK treatment was 0.116 cm\u003csup\u003e2\u003c/sup\u003e\u0026middot;cm\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e, the highest among all treatments. Regarding banana RSAD, the peak values in the M1 and M3 treatments occurred during the harvest stage, at 0.424 cm\u003csup\u003e2\u003c/sup\u003e\u0026middot;cm\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e and 0.469 cm\u003csup\u003e2\u003c/sup\u003e\u0026middot;cm\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e, respectively, while the maximum RSAD in the M2 treatment was observed during the bud development stage, at 0.534 cm\u003csup\u003e2\u003c/sup\u003e\u0026middot;cm\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e. From the perspective of vertical spatial variation during the banana bud development stage, in the 0\u0026thinsp;\u0026minus;\u0026thinsp;20 cm soil layer, the RSAD of rubber trees in the M2 treatment increased by 187.48%, 77.08%, and 162.10% compared to the CK, M1, and M3 treatments, respectively. Additionally, the RSAD of banana plants in the M2 treatment was higher than in the M1 and M3 treatments, with increases of 58.48% and 72.63%, respectively. In the horizontal distribution, at a distance of 0\u0026thinsp;\u0026minus;\u0026thinsp;30 cm from the rubber tree, the RSAD of rubber trees treated with M2 increased by 182.84%, 70.01%, and 133.58% compared to the CK, M1, and M3 treatments. At a distance of 120\u0026thinsp;\u0026minus;\u0026thinsp;150 cm from the rubber tree, the RSAD of banana plants in the M2 treatment was higher than in the M1 and M3 treatments, with increases of 98.06% and 89.45%, respectively.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec28\" class=\"Section2\"\u003e \u003ch2\u003e[Insert Fig.\u0026nbsp;6]\u003c/h2\u003e \u003cdiv id=\"Sec29\" class=\"Section3\"\u003e \u003ch2\u003eUnderground interspecific competition intensity index (UICII)\u003c/h2\u003e \u003cdiv id=\"Sec30\" class=\"Section4\"\u003e \u003ch2\u003eUnderground interspecific competition intensity index for each treatment and different soil depths\u003c/h2\u003e \u003cp\u003eThe root competition dynamics in the rubber tree\u0026minus;banana intercropping system, influenced by various fertilization treatments, exhibited distinct patterns across different soil layers and growth stages of the rubber tree (Table\u0026nbsp;1). During the vigorous growth stage, the highest UICII for the M1 treatment was observed in the 40\u0026thinsp;\u0026minus;\u0026thinsp;60 cm soil layer, while the M2 and M3 treatments peaked in the 20\u0026thinsp;\u0026minus;\u0026thinsp;40 cm soil layer. Notably, the UICII for the M2 treatment was 31.65% and 22.69% lower than that of the M1 and M3 treatments, respectively. In the bud development stage, both M1 and M2 treatments showed their highest UICII values in the 40\u0026thinsp;\u0026minus;\u0026thinsp;60 cm soil layer, while the M3 treatment peaked in the 20\u0026thinsp;\u0026minus;\u0026thinsp;40 cm soil layer, indicating the weakest root competition during this period, with reductions of 5.45% and 4.10% compared to M1 and M2, respectively. By the harvest stage, the highest UICII for all treatments was recorded in the 40\u0026thinsp;\u0026minus;\u0026thinsp;60 cm soil layer, each achieving a value of 1. However, the M3 treatment showed a reduction in root competition by 19.58% and 18.34% compared to M1 and M2 treatments. These results suggest that a 30% substitution of organic nitrogen mitigates root competition across all soil layers during the banana's vigorous growth stage, while a 45% substitution of slow\u0026minus;release nitrogen effectively reduces root competition during the bud development and harvest stages within the intercropping system.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec31\" class=\"Section2\"\u003e \u003ch2\u003e[Insert Table\u0026nbsp;1]\u003c/h2\u003e \u003cdiv id=\"Sec32\" class=\"Section3\"\u003e \u003ch2\u003eUnderground interspecific competition intensity index for each treatment and different distance from tree\u003c/h2\u003e \u003cp\u003eIn terms of interspecific root competition during the banana growth periods, the UICII across various distances from the rubber tree also showed notable differences depending on the fertilization treatment (Table\u0026nbsp;2). During the vigorous growth stage, the UICII for the M1 treatment peaked at a distance of 90 cm from the rubber tree, while the M2 and M3 treatments reached their highest values at 150 cm. In this phase, the UICII of the M2 treatment was 14.91% and 13.14% lower than that of M1 and M3 treatments, respectively. During the banana bud development stage, the highest UICII for both M1 and M2 treatments was observed at 90 cm from the rubber tree, while the M3 treatment peaked at 120 cm. The M2 treatment recorded UICII values that were 23.00% and 22.92% lower than those of M1 and M3 treatments, respectively. By the banana harvest period, the highest UICII for M1 and M3 treatments was found again at 150 cm from the rubber tree, whereas the M2 treatment peaked at 90 cm. Compared to the M1 and M3 treatments, the UICII of the M2 treatment increased by 14.84% and 18.12%, respectively. These results suggest that a 30% substitution of organic nitrogen effectively alleviates root competition intensity during the banana\u0026rsquo;s vigorous growth and bud development stages while promoting interspecific root competition during the harvest period.\u003c/p\u003e \u003cdiv id=\"Sec33\" class=\"Section4\"\u003e \u003ch2\u003e[Insert Table\u0026nbsp;1]\u003c/h2\u003e \u003cp\u003e \u003cem\u003eSoil nutrient\u003c/em\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e\n\u003ch3\u003eAvailable N\u003c/h3\u003e\n\u003cp\u003eThe distribution of soil available nitrogen content in monoculture and intercropped rubber/banana systems under varying fertilization regimes is depicted (Fig.\u0026nbsp;7). Overall, soil available nitrogen initially increased and then declined, reaching its peak during the banana bud development stage. Vertically, the highest nitrogen content was observed in the 0\u0026thinsp;\u0026minus;\u0026thinsp;20 cm layer for both monoculture and intercropped systems, with a gradual decrease at greater depths. During the vigorous growth stage (Fig.\u0026nbsp;7a, 7d, 7g, 7j), intercropping systems employing the three fertilization treatments resulted in increases in available nitrogen content by 14.49%, 16.93%, and 7.59% in the 0\u0026thinsp;\u0026minus;\u0026thinsp;20 cm layer, 21.57%, 15.41%, and 3.84% in the 20\u0026thinsp;\u0026minus;\u0026thinsp;40 cm layer, and 16.02%, 13.36%, and 10.04% in the 40\u0026thinsp;\u0026minus;\u0026thinsp;60 cm layer, relative to the CK treatment. By the bud development stage (Fig.\u0026nbsp;7b, 7e, 7h, 7k), the M2 treatment demonstrated increases of 4.30%, 3.83%, and 3.96% in soil nitrogen content at the 0\u0026thinsp;\u0026minus;\u0026thinsp;20 cm, 20\u0026thinsp;\u0026minus;\u0026thinsp;40 cm, and 40\u0026thinsp;\u0026minus;\u0026thinsp;60 cm depths, respectively, compared to the CK treatment. At the harvest stage (Fig.\u0026nbsp;7c, 7f, 7i, 7l), the M1 treatment resulted in increases of 1.60%, 10.91%, and 5.30%, the M2 treatment in increases of 14.43%, 26.49%, and 21.32%, and the M3 treatment in increases of 4.41%, 9.61%, and 7.48% at the 0\u0026thinsp;\u0026minus;\u0026thinsp;20 cm, 20\u0026thinsp;\u0026minus;\u0026thinsp;40 cm, and 40\u0026thinsp;\u0026minus;\u0026thinsp;60 cm layers, respectively, compared to the CK treatment. These results highlight the capacity of the rubber/banana intercropping system to enhance soil nitrogen availability relative to monoculture rubber, with the M2 fertilization mode proving to be the most effective.\u003c/p\u003e\n\u003ch3\u003e[Insert Fig. 7]\u003c/h3\u003e\n\u003cdiv id=\"Sec36\" class=\"Section2\"\u003e \u003ch2\u003eAvailable P\u003c/h2\u003e \u003cp\u003eThe distribution of soil available phosphorus content in monoculture and intercropped rubber/banana systems under various fertilization modes is presented (Fig.\u0026nbsp;8). Generally, the available phosphorus content initially decreased and then increased with increasing distance from the rubber trees. At the vigorous growth stage (Fig.\u0026nbsp;8a, 8d, 8g, 8j), the soil available phosphorus content in the 0\u0026thinsp;\u0026minus;\u0026thinsp;20 cm layer was 6.94%, 70.31%, and 28.15% lower in the CK treatment compared to M1, M2, and M3 treatments, respectively. By the bud development stage (Fig.\u0026nbsp;8b, 8e, 8h, 8k), available phosphorus content in the 0\u0026thinsp;\u0026minus;\u0026thinsp;20 cm depth increased by 24.12%, 25.89%, and 12.29% in the M1, M2, and M3 treatments, respectively, compared to CK. In terms of horizontal distribution, at the closest distance from the banana, the M2 treatment exhibited significant increases of 119.80%, 149.58%, and 147.97% in the 0\u0026thinsp;\u0026minus;\u0026thinsp;20 cm soil layer relative to CK, M1, and M3 treatments, respectively. At the harvest stage (Fig.\u0026nbsp;8c, 8f, 8i, 8l), soil available phosphorus content in the 0\u0026thinsp;\u0026minus;\u0026thinsp;20 cm layer of intercropping systems M2 and M3 treatments increased by 12.72% and 4.80%, respectively, compared to the CK treatment. At a 30 cm distance from the rubber tree, M2 and M3 treatments showed increases of 11.32% and 22.53%, respectively, relative to CK. Overall, at the vigorous growth stage, the M1 treatment increased available phosphorus content by 6.35% compared to CK. During the bud development stage, intercropping treatments M1 to M3 resulted in yield increases ranging from 2.16% to 23.29% compared to CK. At the harvest stage, available phosphorus content in the M2 and M3 treatments rose by 16.66% to 19.45% relative to CK, with the M2 treatment exhibiting the highest level. These results suggest that intercropping treatments generally enhance soil available phosphorus content relative to monocropping, with the 30% organic nitrogen substitution treatment (M2) showing significant advantages during the banana bud development and harvest stages.\u003c/p\u003e \u003cdiv id=\"Sec37\" class=\"Section3\"\u003e \u003ch2\u003e[Insert Fig.\u0026nbsp;8]\u003c/h2\u003e \u003c/div\u003e \u003cdiv id=\"Sec38\" class=\"Section3\"\u003e \u003ch2\u003eAvailable K\u003c/h2\u003e \u003cp\u003eThe distribution of soil available potassium content in monoculture and intercropped rubber/banana systems under three different fertilization regimes is shown (Fig.\u0026nbsp;9). Generally, the soil available potassium content in intercropping systems was lower than in monoculture systems. At the vigorous growth stage (Fig.\u0026nbsp;9a, 9d, 9g, 9j), in the 0\u0026thinsp;\u0026minus;\u0026thinsp;20 cm soil layer, only the M1 treatment exhibited a 10.17% increase compared to the CK treatment, while the M2 and M3 treatments showed decreases of 26.32% and 25.58%, respectively. At both the bud development stage (Fig.\u0026nbsp;9b, 9e, 9h, 9k) and the harvest stage (Fig.\u0026nbsp;9c, 9f, 9i, 9l), available potassium content in the 0\u0026thinsp;\u0026minus;\u0026thinsp;20 cm depth decreased by 7.47%\u0026minus;43.82% for M1, 34.05%\u0026minus;60.84% for M2, and 69.02%\u0026minus;78.37% for M3, compared to the CK treatment.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec39\" class=\"Section3\"\u003e \u003ch2\u003e[Insert Fig.\u0026nbsp;9]\u003c/h2\u003e \u003cp\u003e \u003cem\u003eOrganic matter\u003c/em\u003e \u003c/p\u003e \u003cp\u003eThe distribution of soil organic matter content in monoculture and intercropped rubber/banana systems under three different fertilization regimes is presented (Fig.\u0026nbsp;10). Vertically, the highest soil organic matter content was observed in the 0\u0026thinsp;\u0026minus;\u0026thinsp;20 cm layer for both monoculture and intercropping systems. Horizontally, the content was higher at the outer edges and lower at the center. At the vigorous growth stage (Fig.\u0026nbsp;10a, 10d, 10g, 10j), soil organic matter content in the 0\u0026thinsp;\u0026minus;\u0026thinsp;20 cm layer increased by 6.22% and 17.71% in the M1 and M2 treatments, respectively, compared to the CK treatment. By the bud development stage (Fig.\u0026nbsp;10b, 10e, 10h, 10k), the M2 treatment exhibited the highest soil organic matter content in the 0\u0026thinsp;\u0026minus;\u0026thinsp;20 cm layer, with a 2.34% increase compared to the CK treatment. At the harvest stage (Fig.\u0026nbsp;10c, 10f, 10i, 10l), M2 treatment showed a 7.77% increase in soil organic matter content relative to the CK treatment. These results suggest that the M2 treatment effectively enhances soil organic matter content compared to monoculture rubber cultivation.\u003c/p\u003e \u003cp\u003e \u003cb\u003e[Insert Fig.\u0026nbsp;10]\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003eResponse of rhizosphere microbial community structure and diversity to fertilization treatments\u003c/em\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003eEffects of Different Fertilization Treatments on the Alpha Diversity of Rhizosphere Microbial Communities\u003c/em\u003e \u003c/p\u003e \u003cp\u003eDifferent fertilization treatments significantly affected the alpha diversity of rhizosphere microbial communities in rubber trees and banana plants (Fig.\u0026nbsp;11a\u0026ndash;p). Analysis of bacterial communities showed that the Shannon index was highest under the M1 treatment in both the 0\u0026ndash;30 cm rubber tree rhizosphere (Fig.\u0026nbsp;11a) and the intercropping zone rubber rhizosphere (Fig.\u0026nbsp;11b), with values of 7.02 and 6.73, respectively\u0026mdash;the former representing an 18.84% increase compared to CK. In contrast, the intercropping zone banana rhizosphere (Fig.\u0026nbsp;11c) and the 0\u0026ndash;30 cm banana rhizosphere (Fig.\u0026nbsp;11d) reached their maximum values under M2, at 6.88 and 6.95, reflecting increases of 18.14% and 20.08% compared to M3, respectively. Chao1 index analysis indicated that the 0\u0026ndash;30 cm rubber tree rhizosphere (Fig.\u0026nbsp;11e) and intercropping zone rubber rhizosphere (Fig.\u0026nbsp;11f) also exhibited the highest values under M1, at 1903.67 and 1551.33, respectively, with the former showing a significant 42.67% increase compared to CK. The intercropping zone banana rhizosphere (Fig.\u0026nbsp;11g) reached its maximum under M2 (1726), increasing by 10.93% compared to M1, while the 0\u0026ndash;30 cm banana rhizosphere (Fig.\u0026nbsp;11h) was highest under M3 (2186.55). Analysis of fungal communities revealed that the Shannon index reached its maximum under M2 in both the intercropping zone rubber rhizosphere (Fig.\u0026nbsp;11j) and banana rhizosphere (Fig.\u0026nbsp;11k), with values of 4.31 and 4.06, representing increases of 18.50% and 19.03% compared to M3, respectively (the latter being significant at P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). In contrast, the 0\u0026ndash;30 cm rubber tree rhizosphere (Fig.\u0026nbsp;11i) and banana rhizosphere (Fig.\u0026nbsp;11l) showed the highest values under M3. The Chao1 index indicated that the 0\u0026ndash;30 cm rubber tree rhizosphere (Fig.\u0026nbsp;11m) and the intercropping zone banana rhizosphere (Fig.\u0026nbsp;11o) both reached their maximum under M2, with values of 651.67 and 532, reflecting significant increases of 36.71% (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) and 36.29% compared to the control treatment, respectively. The intercropping zone rubber rhizosphere (Fig.\u0026nbsp;11n) and 0\u0026ndash;30 cm banana rhizosphere (Fig.\u0026nbsp;11p), however, showed the highest values under M1. These results indicate that the M2 treatment has a significant advantage in enhancing bacterial diversity in the banana rhizosphere and fungal community richness in the intercropping zone, suggesting that this fertilization approach plays a positive role in improving the rhizosphere micro\u0026minus;ecological environment.\u003c/p\u003e \u003cp\u003e \u003cb\u003e[Insert Fig.\u0026nbsp;11]\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003eEffects of Different Fertilization Treatments on the Rhizosphere Bacterial Community Characteristics of Rubber Trees and Banana Plants\u003c/em\u003e \u003c/p\u003e \u003cp\u003eDifferent fertilization treatments significantly altered the rhizosphere bacterial community structure of both rubber trees and banana plants (Fig.\u0026nbsp;12a\u0026ndash;d), with the M2 treatment showing a notable advantage in increasing the relative abundance of multiple beneficial bacterial phyla. In the rubber tree rhizosphere (Fig.\u0026nbsp;12a), M2 significantly increased the relative abundance of Bacteroidota and Firmicutes, with Bacteroidota increasing by 66.40% compared to M1 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) and Firmicutes increasing by 131.00% and 45.58% compared to M1 and M3, respectively. In the intercropping zone rubber tree rhizosphere (Fig.\u0026nbsp;12b), Crenarchaeota reached its highest relative abundance under M2, increasing by 24.00% and 107.00% compared to M1 and M3. The intercropping zone banana rhizosphere (Fig.\u0026nbsp;12c) exhibited particularly pronounced responses under M2, where Proteobacteria increased by 11.26% and 68.61% compared to M1 and M3, Actinobacteria increased by 20.96% and 49.54%, and Chloroflexi increased by 37.09% compared to M3. In the banana rhizosphere (Fig.\u0026nbsp;12d), M2 also significantly enhanced the relative abundance of several phyla: Acidobacteriota increased by 152.00% compared to M3 (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05), Firmicutes increased by 92.54% compared to M3, Crenarchaeota increased by 69.84% compared to M1, and Myxococcota increased by 37.70% and 43.37% compared to M1 and M3. In summary, the M2 treatment demonstrated a significant advantage in promoting the assembly of beneficial rhizosphere bacterial communities.\u003c/p\u003e \u003cp\u003e \u003cb\u003e[Insert Fig.\u0026nbsp;12]\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003eEffects of Different Fertilization Treatments on the Rhizosphere Fungal Community Characteristics of Rubber Trees and Banana Plants\u003c/em\u003e \u003c/p\u003e \u003cp\u003eDifferent fertilization treatments significantly influenced the rhizosphere fungal community structure of rubber trees and banana plants at the phylum level (Fig.\u0026nbsp;13a\u0026ndash;d), with the M2 treatment demonstrating notable advantages in increasing the relative abundance of several key fungal phyla. In the rubber tree rhizosphere (Fig.\u0026nbsp;13a), the relative abundance of Ascomycota under M2 reached 87.15%, representing a 28.36% increase compared to M1, while Basidiomycota was highest under M1 (21.58%). In the intercropping zone rubber tree rhizosphere (Fig.\u0026nbsp;13b), Mortierellomycota showed the highest relative abundance under M2 (3.51%), with a significant increase of 205.00% compared to M3 (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). In the intercropping zone banana rhizosphere (Fig.\u0026nbsp;13c), the relative abundance of Mortierellomycota under M2 was 2.07%, reflecting a 38.08% increase compared to M1. In the banana rhizosphere (Fig.\u0026nbsp;13d), all observed phyla performed optimally under M2: the relative abundance of Ascomycota was 73.76%, increasing by 6.31% compared to M3; the relative abundance of Basidiomycota was 8.11%, with significant increases of 24.62% and 111.00% compared to M1 and M3, respectively; and the relative abundance of Mortierellomycota was 2.69%, increasing by 27.42% and 65.53% compared to M1 and M3. In summary, the M2 treatment exhibited a clear advantage in promoting the establishment of beneficial rhizosphere fungal communities.\u003c/p\u003e \u003cp\u003e \u003cb\u003e[Insert Fig.\u0026nbsp;13]\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003eInteractions Between Rhizosphere Microbial Communities and Root\u0026minus;Soil System Factors\u003c/em\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003eCorrelation Analysis Between Bacterial Communities and Root/Soil Factors\u003c/em\u003e \u003c/p\u003e \u003cp\u003eCorrelation analysis between rhizosphere bacterial communities and root indices as well as soil factors under different fertilization treatments is shown in Fig.\u0026nbsp;14. In the 0\u0026ndash;30 cm rubber tree rhizosphere (Fig.\u0026nbsp;14a), the relative abundance of Proteobacteria showed a significant positive correlation with root biomass (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). In the intercropping zone rubber tree rhizosphere (Fig.\u0026nbsp;14b), Bacteroidota was significantly positively correlated with root length density and root surface area density, while Proteobacteria was highly significantly positively correlated with root length density (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) and significantly positively correlated with root surface area density. Analysis in the intercropping zone banana rhizosphere (Fig.\u0026nbsp;14c) indicated that Acidobacteriota and Chloroflexi were significantly negatively correlated with root biomass, root length density, and root surface area density, with Chloroflexi showing highly significant negative correlations with these root indices and a significant negative correlation with soil available phosphorus. Firmicutes was significantly positively correlated with soil available potassium, while \u003cem\u003eProteobacteria\u003c/em\u003e was highly significantly positively correlated with available potassium. Bacteroidota showed significant positive correlations with available potassium, root biomass, root length density, and root surface area density, and Myxococcota was significantly positively correlated with soil available phosphorus. In the 0\u0026ndash;30 cm banana rhizosphere (Fig.\u0026nbsp;14d), Actinobacteria and Bacteroidota were significantly negatively correlated with soil alkaline hydrolyzable nitrogen, and Chloroflexi was significantly negatively correlated with root biomass. It is worth noting that beneficial bacterial groups such as Proteobacteria and Bacteroidota, which were significantly enriched in the M2 treatment, exhibited significant positive correlations with both root development indices and soil nutrient availability, revealing the potential mechanism by which this fertilization approach promotes plant growth from a microbial ecological perspective.\u003c/p\u003e \u003cp\u003e \u003cb\u003e[Insert Fig.\u0026nbsp;14]\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003eCorrelation Analysis Between Fungal Communities and Root/Soil Factors\u003c/em\u003e \u003c/p\u003e \u003cp\u003eCorrelation analysis between fungal community structure at the phylum level and root indices as well as soil factors is shown in Fig.\u0026nbsp;15. In the 0\u0026thinsp;\u0026minus;\u0026thinsp;30 cm rubber tree rhizosphere (Fig.\u0026nbsp;15a), no significant correlations were observed between any fungal phyla and the root or environmental factors. Analysis in the intercropping zone rubber tree rhizosphere (Fig.\u0026nbsp;16b) indicated that Chytridiomycota showed a significant positive correlation with root biomass, whereas Rozellomycota was significantly negatively correlated with root biomass, root length density, and root surface area density, and exhibited highly significant negative correlations with soil available phosphorus, alkaline hydrolyzable nitrogen, and organic matter content. In the intercropping zone banana rhizosphere (Fig.\u0026nbsp;15c), the relative abundance of Calcarisporiellomycota was significantly negatively correlated with soil available phosphorus and highly significantly negatively correlated with alkaline hydrolyzable nitrogen and organic matter. Analysis in the 0\u0026thinsp;\u0026minus;\u0026thinsp;30 cm banana rhizosphere (Fig.\u0026nbsp;15d) revealed that Blastocladiomycota was significantly positively correlated with soil available potassium, alkaline hydrolyzable nitrogen, and organic matter; Ascomycota was significantly positively correlated with available potassium; and Mortierellomycota was significantly negatively correlated with available phosphorus. It is worth noting that fungal taxa such as Blastocladiomycota, which were significantly enriched in the M2 treatment, showed significant positive correlations with soil nutrient availability, indicating that this fertilization approach may improve soil fertility by regulating the structure of fungal communities.\u003c/p\u003e \u003cp\u003e \u003cb\u003e[Insert Fig.\u0026nbsp;15]\u003c/b\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003e \u003cem\u003eRoots morphology in intercropping\u003c/em\u003e \u003c/p\u003e \u003cp\u003eCompetition for underground resources in agroforestry systems is influenced by the distribution and density of root systems (Noordwijk et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). However, research on the root system characteristics of rubber trees intercropped with other crops under varying fertilization regimes remains limited. A study on nitrogen fertilization levels for intercropped rubber trees and calla lilies revealed that intercropping only inhibited calla lily growth when nitrogen application was below 200 kg\u0026middot;ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, while it enhanced root system development by increasing root number and length and promoting dry matter allocation to the root system (Li and Lin \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2021a\u003c/span\u003e). In the present study, during the banana bud development stage, both rubber tree and banana root biomass showed increases at various soil depths under the M2 treatment compared to other treatments. Specifically, within the 0\u0026ndash;30 cm range from the rubber tree, root biomass in the M2 treatment was 7.09% to 29.17% higher than in the other treatments (Fig.\u0026nbsp;4b, e, h, k). Furthermore, during the banana harvest period, monoculture rubber trees exhibited superior RLD compared to the intercropping treatments. Analysis of vertical spatial changes revealed that, during the budding stage, the total banana RLD in the 0\u0026ndash;20 cm soil layer increased by 88.50% and 79.98% under the M2 treatment compared to the M1 and M3 treatments, respectively (Fig.\u0026nbsp;5f, i, l). Additionally, within the 0\u0026ndash;30 cm range from the rubber tree during the bud development stage, rubber tree RLD under the M2 treatment exceeded that of the CK, M1, and M3 treatments, with increases of 203.37%, 34.53%, and 124.02%, respectively (Fig.\u0026nbsp;5b, e, h, k). Moreover, during the banana harvest period, the RSAD was highest under monoculture rubber trees, with a value of 0.116 cm\u003csup\u003e2\u003c/sup\u003e\u0026middot;cm\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e (Fig.\u0026nbsp;6c, f, i, l). These findings indicate that the temporal and spatial distribution of root system morphology is influenced by growth stages, underscoring the benefits of both monoculture and intercropping systems. The M2 fertilization regime in rubber/banana intercropping systems plays a pivotal role in optimizing root system competition and spatial niche adaptation, demonstrating significant advantages in complementarity.\u003c/p\u003e \u003cp\u003eResearch on intercropping rubber trees with other crops has demonstrated that in deeper soil layers, the fine RLD of rubber trees intercropped with kudzu reaches 0.92 cm\u0026middot;cm\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e, with a biomass density of 0.74 g\u0026middot;dm\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e. This represents a significant increase of 26.03% and 89.74%, respectively, compared to monoculture (Clermont-Dauphin et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Similarly, rubber trees in agroforestry systems intercropped with perennial galangal, tea, and cocoa exhibited average root length densities of 0.18 cm\u0026middot;cm\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e, 0.18 cm\u0026middot;cm\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e, and 0.13 cm\u0026middot;cm\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e, respectively, indicating varying degrees of decline compared to monoculture. A substantial portion of fine rubber tree roots (60.7%\u0026ndash;72.5%) were concentrated in the 0\u0026ndash;20 cm soil layer across all treatments (Yang et al. \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2020a\u003c/span\u003e). Studies on other intercrops reveal that intercropped corn and soybeans exhibit significantly greater RLD and RSAD compared to monoculture, while intercropped peanuts experience restricted root systems with lower densities (Zheng et al. \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2022a\u003c/span\u003e). Intercropping wheat and corn resulted in a reduction in root biomass density, RLD, and RSAD of intercropped corn by 53%, 81%, and 70%, respectively, compared to monocrop corn (Wang et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Furthermore, intercropping walnuts and wheat led to a significant decrease in RLD, RSAD, and other root morphological indicators compared to monoculture (Duan et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Overall, this study demonstrates that the treatment involving 30% organic nitrogen substitution (M2) yielded favorable outcomes in terms of root morphology plasticity and spatial distribution within the young rubber tree/banana intercropping system. It appears that competition for underground resources between trees and crops in agroforestry systems is influenced by root distribution and spatial allocation (Forey et al., 2017). By strategically organizing root distribution within the system, competition can be minimized, thereby enhancing the productivity of the entire agroforestry system (Li et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Wei et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cem\u003eUnderground interspecific competition intensity index in intercropping systems\u003c/em\u003e \u003c/p\u003e \u003cp\u003eCrop roots compete for nutrient resources in the soil, and when the demand for these resources exceeds their availability, interspecific competition is inevitable (Wang et al., 2020; Shen et al., 2022). The nature of this competition\u0026mdash;whether complementary or competitive\u0026mdash;depends largely on the distribution and density of root systems (Noordwijk et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Additionally, the dynamics of root competition are influenced by the spatial arrangement of crops. For instance, when crops are planted in close proximity, their roots are likely to compete more intensely for the same volume of soil, potentially reducing nutrient uptake for both species. In contrast, when root systems are differentiated by depth and spread, they can access distinct soil layers, thereby reducing competition and improving overall resource utilization efficiency (Li et al., 2023; Liu et al., 2022). In this study, the M3 treatment exhibited a lower root competition intensity index (UICII) during the harvest stage compared to the bud development stage, reflecting a reduction in vertical root competition. In contrast, UICII values for both the M1 and M2 treatments increased as rubber trees and bananas progressed through their growth stages. Specifically, the M2 treatment showed a lower UICII during the vigorous growth stage, whereas the M3 treatment recorded the lowest values during both the bud development and harvest stages (Table\u0026nbsp;1). In terms of horizontal root competition, the M2 treatment demonstrated lower UICII values during the vigorous growth and bud development stages, while the M3 treatment exhibited a lower index during the harvest stage. This is likely attributed to the slower nutrient release and prolonged efficacy of organic and controlled\u0026minus;release fertilizers (Table\u0026nbsp;2). The 30% organic fertilizer substitution combined with 45% controlled\u0026minus;release nitrogen significantly reduced root competition throughout the banana growth cycle, thereby improving ecological niche complementarity. Previous research has shown that excessive root competition in agroforestry systems exacerbates resource competition, leading to shortages that hinder efficient resource utilization in intercropping systems (Dai et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Liu et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Moreover, interspecific competition within such systems affects the root growth of fruit trees, with crops competing for essential resources, ultimately influencing system\u0026minus;wide yields (Zhao et al., 2022). For example, the concentration of roots from multiple crops can intensify belowground competition, potentially reducing crop yields (Zhang et al., 2013). This highlights that the advantages of intercropping extend beyond mere resource competition and include complex root interactions that can enhance plant health and productivity. Root competition in intercropping systems presents a multifaceted challenge, influenced by factors such as root structure and spatial arrangement. A comprehensive understanding of these factors is critical for optimizing intercropping practices to improve crop yields and bolster the sustainability of agricultural systems. Effective agronomic interventions, such as rational fertilization, are essential for mitigating the negative impacts of root competition.\u003c/p\u003e \u003cp\u003e \u003cem\u003eSoil nutrients in intercropping\u003c/em\u003e \u003c/p\u003e \u003cp\u003eIntercropping enhances soil fertility, improves soil quality, and optimizes nutrient utilization (Duan et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Li et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Previous studies have demonstrated that intercropping systems can increase the availability of essential macronutrients\u0026mdash;nitrogen, phosphorus, and potassium\u0026mdash;which are critical for plant growth (Zhang et al., 2018; Shen et al., 2024). The current study reveals that, compared to rubber monoculture, the rubber/banana intercropping system significantly increased soil nitrogen availability, with the M2 fertilization treatment proving most effective (Fig.\u0026nbsp;7). Regarding soil phosphorus content, the M1 treatment showed certain advantages over the CK treatment during the vigorous growth stage. In both the bud development and harvest stages, the M2 treatment outperformed monoculture and other intercropping fertilization treatments (Fig.\u0026nbsp;8). Additionally, the M2 treatment consistently exhibited superior outcomes in soil organic matter content, reaching its peak value across various banana growth stages (Fig.\u0026nbsp;10). In contrast, intercropping generally led to a decrease in soil potassium content (Fig.\u0026nbsp;9). Previous research has indicated that transitioning rubber trees from monoculture to agroforestry systems resulted in significant increases in soil nitrogen and phosphorus by 38.5% and 48.2%, respectively, suggesting that rubber tree intercropping improves the physical and chemical properties of soil, thereby contributing to the sustainable development of agriculture and the environment (Chen et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Multiple studies have reported that intercropping enhances soil organic matter content (Cong et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Li et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Wei et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). However, studies on rubber tree and calla lily intercropping indicate that such practices may reduce soil potassium levels (Li and Lin \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2021a\u003c/span\u003e). Organic fertilizers, rich in nutrients and organic matter, have been shown to significantly improve soil fertility and fertilizer efficiency (Ma et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Saudy et al. \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), which may explain the observed relationship between soil available nitrogen, phosphorus, and the M2 treatment in this study. The higher organic matter content observed in this study, compared to monoculture and other fertilization treatments, is likely attributed to these factors. In conclusion, intercropping is a sustainable agricultural practice that integrates diverse plant species, enabling optimized nutrient cycling, enhanced soil health, and increased crop yields. This approach is therefore a valuable strategy for sustainable agriculture, offering benefits beyond nutrient acquisition, such as long\u0026minus;term improvements in soil fertility and ecosystem health.\u003c/p\u003e \u003cp\u003e \u003cem\u003eFertilization Effects on Rhizosphere Microbial Communities\u003c/em\u003e \u003c/p\u003e \u003cp\u003eThis study demonstrated that the M2 treatment (combined organic\u0026minus;inorganic fertilization) most effectively enhanced the rhizosphere microbial community structure and diversity in the rubber tree\u0026minus;banana intercropping system. For bacteria, M2 significantly increased the relative abundance of beneficial phyla such as Bacteroidota and Firmicutes in the rubber tree rhizosphere, and Proteobacteria, Actinobacteria, and Chloroflexi in the intercropped banana rhizosphere (Fig.\u0026nbsp;11), which are pivotal for nutrient cycling and soil health (Liu et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Ning et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Notable increases in Acidobacteriota and Myxococcota under M2 further highlighted the role of organic inputs in shaping microbial assembly (Liu et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Yang et al. \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Concurrently, M2 enhanced the fungal community by boosting the relative abundance of Ascomycota, Basidiomycota, and Mortierellomycota (Fig.\u0026nbsp;12), taxa essential for organic matter decomposition and pathogen suppression (Jianhong et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Zhao et al. \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The significant enrichment of Mortierellomycota suggests a role in phosphorus solubilization, supported by findings that organic fertilizers stimulate P\u0026minus;cycling microbes (Asif et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Zhu et al. \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The enhanced bacterial alpha diversity in the banana rhizosphere under M2 (Fig.\u0026nbsp;13c\u0026ndash;d) confirms that this fertilization approach fosters a more stable and functionally diverse rhizosphere micro\u0026minus;ecology, resonating with the benefits of integrated NPKM practices observed in other systems (Asif et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Xu et al. \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe positive influence of the M2 treatment on plant\u0026minus;microbe\u0026minus;soil interactions was further elucidated through correlation analysis. Key bacterial taxa enriched by M2, specifically Proteobacteria and Bacteroidota, showed significant positive correlations with root development indices (root length density, root surface area) and soil available potassium (Fig.\u0026nbsp;14), indicating their potential role in promoting banana growth and K utilization. Similarly, the fungal phylum Blastocladiomycota, which was positively correlated with soil nutrients (Fig.\u0026nbsp;15), suggests a mechanism through which M2 improves soil fertility by regulating the fungal community (Guo et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Yang et al. \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). In summary, the M2 treatment optimized both the composition and diversity of bacterial and fungal communities, enhancing the efficiency of plant\u0026minus;soil system interactions. This aligns with conclusions from long\u0026minus;term experiments that advocate the \u0026ldquo;manure\u0026thinsp;+\u0026thinsp;chemical fertilizer\u0026rdquo; model to enhance microbial functions and crop productivity (Asif et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Ren et al. \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Xu et al. \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Future research should integrate metagenomics and metabolomics to unravel the precise functional mechanisms of these key microbial taxa, thereby informing the design of precision fertilization strategies for sustainable intercropping systems (Chen et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Zhao et al. \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Zou et al. \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe intercropping system of young rubber trees and bananas, under various fertilization regimes, significantly impacts both the temporal and spatial distribution of their root systems, interspecific competition, soil nutrient availability, and rhizosphere microbial communities. Notably, the strategy of replacing 30% of chemical nitrogen with organic fertilizer (M2) offers distinct advantages. This approach alleviates root competition and ecological challenges across most growth stages while enhancing complementary effects and improving soil nitrogen, phosphorus, and organic matter content. Critically, the M2 treatment was most effective in modulating the rhizosphere micro\u0026minus;ecological environment, fostering a more beneficial microbial community structure and enhancing bacterial diversity in the banana rhizosphere. The observed positive correlations between these optimized microbial communities, root development indices, and soil nutrient availability underscore the role of microbial regulation in the improved plant growth and system performance under the M2 regimen. The findings of this study provide both theoretical and practical insights for optimizing fertilization strategies in young rubber tree\u0026ndash;banana intercropping systems under the specified experimental conditions. Furthermore, these results lay the groundwork for future investigations into the mechanisms of interspecific interactions and plant\u0026minus;microbe\u0026minus;soil feedbacks facilitated by this fertilization approach. Future research should focus on unraveling the molecular mechanisms that underpin the benefits of the rubber\u0026minus;banana intercropping system within this fertilization framework, particularly the functional roles of key microbial taxa in facilitating nutrient cycling and plant health.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAcknowledgments\u003c/h2\u003e \u003cp\u003eThis work was financially supported by the National Key R\u0026amp;D Program of China (Grant no. 2023YFD1901400), the National Natural Science Foundation of China (Grant no. 32460811), the Central Public\u0026minus;interest Scientific Institution Basal Research Fund, China (Grant no. 1630022022002), the China Agriculture Research System (Grant no. CARS\u0026thinsp;\u0026minus;\u0026thinsp;33\u0026thinsp;\u0026minus;\u0026thinsp;ZP2).\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eCredit authorship contribution statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDongqi Jin:\u003c/strong\u003e Methodology, Investigation, Data curation, Writing\u0026minus;Original draft preparation. \u003cstrong\u003eHongzhu Yang:\u0026nbsp;\u003c/strong\u003eData curation, Methodology, Investigation, Writing\u0026minus;Original draft preparation. \u003cstrong\u003eYujie Tan:\u0026nbsp;\u003c/strong\u003eMethodology, Investigation, Writing\u0026minus;Original draft preparation. \u003cstrong\u003eLingxuan Qiu:\u003c/strong\u003e Investigation, Writing\u0026minus;Original draft preparation. \u003cstrong\u003eBinyao Chen:\u0026nbsp;\u003c/strong\u003eData curation, Investigation. \u003cstrong\u003eTao Bi:\u0026nbsp;\u003c/strong\u003eData curation, Investigation. \u003cstrong\u003eWei Luo:\u0026nbsp;\u003c/strong\u003eSupervision, Conceptualization. \u003cstrong\u003eZhengzao Cha:\u0026nbsp;\u003c/strong\u003eMethodology, Investigation. \u003cstrong\u003eHailin Liu:\u003c/strong\u003e Funding acquisition, Data curation, Writing\u0026nbsp;\u0026ndash;\u0026nbsp;review \u0026amp; editing. \u003cstrong\u003eQinghuo Lin:\u0026nbsp;\u003c/strong\u003eFunding acquisition, Supervision, Writing \u0026ndash; review \u0026amp; editing.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eA MM GLM, Ming G, C RSMRHJ, Jinliang SJRAJ Y (2021) Rhizosphere Microbiomes in a Historical Maize-Soybean Rotation System Respond to Host Species and Nitrogen Fertilization at the Genus and Subgenus Levels. Appl Environ Microbiol 87:e0313220\u0026ndash;e0313220. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1128/aem.03132-20\u003c/span\u003e\u003cspan address=\"10.1128/aem.03132-20\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAsghar W, Craven KD, Swenson JR, Kataoka R, Mahmood A, Farias JG (2024) Enhancing the Resilience of Agroecosystems Through Improved Rhizosphere Processes: A Strategic Review. Int J Mol Sci 26:109\u0026ndash;109. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/ijms26010109\u003c/span\u003e\u003cspan address=\"10.3390/ijms26010109\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAsif K, Gaoning Z, Tianyang L, Binghui H (2023) Fertilization and cultivation management promotes soil phosphorus availability by enhancing soil P-cycling enzymes and the phosphatase encoding genes in bulk and rhizosphere soil of a maize crop in sloping cropland. Ecotoxicol Environ Saf 264:115441\u0026ndash;115441. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.Ecoenv.2023.115441\u003c/span\u003e\u003cspan address=\"10.1016/j.Ecoenv.2023.115441\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCardinael R, Mao Z, Prieto I, Stokes A, Dupraz C, Kim JH, Jourdan C (2015) Competition with winter crops induces deeper rooting of walnut trees in a Mediterranean alley cropping agroforestry system. Plant Soil 391:219\u0026ndash;235. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s11104-015-2422-8\u003c/span\u003e\u003cspan address=\"10.1007/s11104-015-2422-8\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen C, Liu W, Wu J, Jiang X, Zhu X (2019) Can intercropping with the cash crop help improve the soil physico-chemical properties of rubber plantations? Geoderma 335:149\u0026ndash;160. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.geoderma.2018.08.023\u003c/span\u003e\u003cspan address=\"10.1016/j.geoderma.2018.08.023\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen P, Chaoyang M, Chao H, Hao C, Jingdong L, Jingping Y (2021) Shift of microbial turnover time and metabolic efficiency strongly regulates rhizosphere priming effect under nitrogen fertilization in paddy soil. Sci Total Environ 800:149590\u0026ndash;149590. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.Scitotenv.2021.149590\u003c/span\u003e\u003cspan address=\"10.1016/j.Scitotenv.2021.149590\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCheng Z, Meng L, Yin T, Li Y, Zhang Y, Li S (2023) Changes in Soil Rhizobia Diversity and Their Effects on the Symbiotic Efficiency of Soybean Intercropped with Maize. Agronomy 13:997. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/agronomy13040997\u003c/span\u003e\u003cspan address=\"10.3390/agronomy13040997\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eClermont-Dauphin C, Dissataporn C, Suvannang N, Pongwichian P, Maeght J-l, Hammecker C, Jourdan C (2018) Intercrops improve the drought resistance of young rubber trees. Agron Sustain Dev 38. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s13593-018-0537-z\u003c/span\u003e\u003cspan address=\"10.1007/s13593-018-0537-z\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCong WF, Hoffland E, Li L, Six J, Sun JH, Bao XG, Zhang FS, Van Der Werf W (2015) Intercropping enhances soil carbon and nitrogen. Glob Chang Biol 21:1715\u0026ndash;1726. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/gcb.12738\u003c/span\u003e\u003cspan address=\"10.1111/gcb.12738\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDai YS, Yang T, Shen L, Wang XY, Zhang WL, Liu TT, Lu WH, Li LH, Zhang W (2021) Root growth, distribution, and physiological characteristics of alfalfa in a poplar/alfalfa silvopastoral system compared to sole-cropping in northwest Xinjiang, China. Agrofor Syst 95:1137\u0026ndash;1153. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s10457-021-00639-1\u003c/span\u003e\u003cspan address=\"10.1007/s10457-021-00639-1\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDuan Y, Shen J, Zhang X, Wen B, Ma Y, Wang Y, Fang W, Zhu X (2019) Effects of soybean\u0026ndash;tea intercropping on soil-available nutrients and tea quality. Acta Physiol Plant 41. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s11738-019-2932-8\u003c/span\u003e\u003cspan address=\"10.1007/s11738-019-2932-8\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDuan ZP, Gan YW, Wang BJ, Hao XD, Xu WL, Zhang W, Li LH (2017) Interspecific interaction alters root morphology in young walnut/wheat agroforestry systems in northwest China. Agrofor Syst 93:419\u0026ndash;434. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s10457-017-0133-2\u003c/span\u003e\u003cspan address=\"10.1007/s10457-017-0133-2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGong X, Dang K, Lv S, Zhao G, Wang H, Feng B (2021) Interspecific competition and nitrogen application alter soil ecoenzymatic stoichiometry, microbial nutrient status, and improve grain yield in broomcorn millet/mung bean intercropping systems. Field Crops Res 270. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.fcr.2021.108227\u003c/span\u003e\u003cspan address=\"10.1016/j.fcr.2021.108227\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGuo Z, Zhang J, Fan J, Yang X, Yi Y, Han X, Wang D, Zhu P, Peng X (2019) Does animal manure application improve soil aggregation? Insights from nine long-term fertilization experiments. Sci Total Environ 660:1029\u0026ndash;1037. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.scitotenv.2019.01.051\u003c/span\u003e\u003cspan address=\"10.1016/j.scitotenv.2019.01.051\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHan S, Luo X, Tan S, Wang J, Chen W, Huang Q (2020) Soil aggregates impact nitrifying microorganisms in a vertisol under diverse fertilization regimes. Eur J Soil Sci 71:536\u0026ndash;547. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/ejss.12881\u003c/span\u003e\u003cspan address=\"10.1111/ejss.12881\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHu F, Tan Y, Yu A, Zhao C, Fan Z, Yin W, Chai Q, Coulter JA, Cao W (2020) Optimizing the split of N fertilizer application over time increases grain yield of maize-pea intercropping in arid areas. Eur J Agron 119. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.eja.2020.126117\u003c/span\u003e\u003cspan address=\"10.1016/j.eja.2020.126117\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHuang H, Wu H, Rosana L, Yin D, Shen H, Zhang P (2022) Effects of Pre-Hardening and Autumn Fertilization on Biomass Allocation and Root Morphology of Pinus koraiensis Seedlings. Forests 14:59\u0026ndash;59. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/f14010059\u003c/span\u003e\u003cspan address=\"10.3390/f14010059\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJiang Y, Zhang R, Zhang C, Su J, Wen F, Deng X (2022) Long-term organic fertilizer additions elevate soil extracellular enzyme activities and tobacco quality in a tobacco-maize rotation. Frontiers in Plant Science 13: 973639\u0026ndash;973639. doi: 10.3389/fpls.2022.973639\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJianhong R, Xiaoli L, Wenping Y, Xiaoxiao Y, Wenguang L, Qing X, Junhui L, Zhiqiang G, Zhenping Y (2021) Rhizosphere soil properties, microbial community, and enzyme activities: Short-term responses to partial substitution of chemical fertilizer with organic manure. J Environ Manage 299:113650\u0026ndash;113650. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.Jenvman.2021.113650\u003c/span\u003e\u003cspan address=\"10.1016/j.Jenvman.2021.113650\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLangenberger G, Cadisch G, Martin K, Min S, Waibel H (2016) Rubber intercropping: a viable concept for the 21st century? Agrofor Syst 91:577\u0026ndash;596. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s10457-016-9961-8\u003c/span\u003e\u003cspan address=\"10.1007/s10457-016-9961-8\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi J, Lin W (2021a) Effects of nitrogen fertilizer rates on the growth and nutrient utilization of calla lily intercropped with rubber trees. Soil Tillage Res 211. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.still.2021.105031\u003c/span\u003e\u003cspan address=\"10.1016/j.still.2021.105031\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi J, Lin W (2021b) Effects of nitrogen fertilizer rates on the growth and nutrient utilization of calla lily intercropped with rubber trees. Soil Tillage Res 211. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.Still.2021.105031\u003c/span\u003e\u003cspan address=\"10.1016/j.Still.2021.105031\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi J, Zhou L, Lin W (2018) Competitive characteristics related to nitrogen utilization and calla lily growth in rubber\u0026ndash;calla lily intercropping systems. Industrial Crops Prod 125:567\u0026ndash;572. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.indcrop.2018.09.032\u003c/span\u003e\u003cspan address=\"10.1016/j.indcrop.2018.09.032\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi X-F, Wang Z-G, Bao X-G, Sun J-H, Yang S-C, Wang P, Wang C-B, Wu J-P, Liu X-R, Tian X-L, Wang Y, Li J-P, Wang Y, Xia H-Y, Mei P-P, Wang X-F, Zhao J-H, Yu R-P, Zhang W-P, Che Z-X, Gui L-G, Callaway RM, Tilman D, Li L (2021) Long-term increased grain yield and soil fertility from intercropping. Nat Sustain 4:943\u0026ndash;950. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/s41893-021-00767-7\u003c/span\u003e\u003cspan address=\"10.1038/s41893-021-00767-7\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu C, Gong X, Dang K, Li J, Yang P, Gao X, Deng X, Feng B (2020) Linkages between nutrient ratio and the microbial community in rhizosphere soil following fertilizer management. Environ Res 184:109261. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.envres.2020.109261\u003c/span\u003e\u003cspan address=\"10.1016/j.envres.2020.109261\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu P, Li X, Hu S, He W, Zhou Y, Wang Y (2024) Effects of Nitrogen Forms on Root Morphology and Nitrogen Accumulation inPinus tabuliformiscarr. Seedlings under Exponential Fertilization. Forests 15. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/f15020271\u003c/span\u003e\u003cspan address=\"10.3390/f15020271\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu T, Wang X, Shen L, Wei W, Zhang S, Wang M, Zhu Y, Tuertia T, Zhang W (2023) Apricot can improve root system characteristics and yield by intercropping with alfalfa in semi-arid areas. Plant Soil 506:1\u0026ndash;18. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s11104-023-05919-6\u003c/span\u003e\u003cspan address=\"10.1007/s11104-023-05919-6\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu Y-X, Sun J-H, Zhang F-F, Li L (2019) The plasticity of root distribution and nitrogen uptake contributes to recovery of maize growth at late growth stages in wheat/maize intercropping. Plant Soil 447:39\u0026ndash;53. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s11104-019-04034-9\u003c/span\u003e\u003cspan address=\"10.1007/s11104-019-04034-9\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMa P, Nan S, Yang X, Qin Y, Ma T, Li X, Yu Y, Bodner G (2022) Macroaggregation is promoted more effectively by organic than inorganic fertilizers in farmland ecosystems of China\u0026mdash;A meta-analysis. Soil Tillage Res 221. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.still.2022.105394\u003c/span\u003e\u003cspan address=\"10.1016/j.still.2022.105394\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMengmeng C, Zhang S, Liu L, Wu L, Ding X (2021) Combined organic amendments and mineral fertilizer application increase rice yield by improving soil structure, P availability and root growth in saline-alkaline soil. Soil Tillage Res 212. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.Still.2021.105060\u003c/span\u003e\u003cspan address=\"10.1016/j.Still.2021.105060\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMichels T, Eschbach J-M, Lacote R, Benneveau A, Papy F (2012) Tapping panel diagnosis, an innovative on-farm decision support system for rubber tree tapping. Agron Sustain Dev 32:791\u0026ndash;801. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s13593-011-0069-2\u003c/span\u003e\u003cspan address=\"10.1007/s13593-011-0069-2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNing R, Yang W, Youliang Y, Yanan Z, Yufang H, Wen F, Xv C (2020) Effects of Continuous Nitrogen Fertilizer Application on the Diversity and Composition of Rhizosphere Soil Bacteria. Front Microbiol 11:1948\u0026ndash;1948. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3389/fmicb.2020.01948\u003c/span\u003e\u003cspan address=\"10.3389/fmicb.2020.01948\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNoordwijk MV, Lawson G, Hairiah K, Wilson J (2015) Root distribution of trees and crops Competition andor complementarity. In Tree-Crop Interactions Agroforestry in a Changing Climate\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOouchi M, Ukawa J, Ishii Y, Maeda H (2019) Structural Analysis of the Terminal Groups in Commercial Hevea Natural Rubber by 2D-NMR with DOSY Filters and Multiple-WET Methods Using Ultrahigh-Field NMR. Biomacromolecules 20:1394\u0026ndash;1400. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1021/acs.biomac.8b01771\u003c/span\u003e\u003cspan address=\"10.1021/acs.biomac.8b01771\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePianka ER (1973) The structure of lizard communities. Annu Rev Ecol Syst 4:53\u0026ndash;74\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eQi D, Wu Z, Chen B, Zhang X, Yang C, Fu Q (2024) Integrative cultivation pattern, distribution, yield and potential benefit of rubber based agroforestry system in China. Industrial Crops Prod 220:119228\u0026ndash;119228. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.Indcrop.2024.119228\u003c/span\u003e\u003cspan address=\"10.1016/j.Indcrop.2024.119228\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eQi D, Wu Z, Yang C, Xie G, Li Z, Yang X, Li D (2021) Can intercropping with native trees enhance structural stability in young rubber (Hevea brasiliensis) agroforestry system? Eur J Agron 130. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.Eja.2021.126353\u003c/span\u003e\u003cspan address=\"10.1016/j.Eja.2021.126353\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRen J, Xiaoli L, Wenping Y, Xiaoxiao Y, Wenguang L, Qing X, Junhui L, Zhiqiang G, Zhenping Y (2021) Rhizosphere soil properties, microbial community, and enzyme activities: Short-term responses to partial substitution of chemical fertilizer with organic manure. J Environ Manage 299:113650\u0026ndash;113650. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.Jenvman.2021.113650\u003c/span\u003e\u003cspan address=\"10.1016/j.Jenvman.2021.113650\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRodrigo VHL, Stirling CM, Silva TUK, Pathirana PD (2004) The growth and yield of rubber at maturity is improved by intercropping with banana during the early stage of rubber cultivation. Field Crops Res 91:23\u0026ndash;33. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.fcr.2004.05.005\u003c/span\u003e\u003cspan address=\"10.1016/j.fcr.2004.05.005\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRoohi M, Arif MS, Yasmeen T, Riaz M, Rizwan M, Shahzad SM, Ali S, Bragazza L (2020) Effects of cropping system and fertilization regime on soil phosphorous are mediated by rhizosphere-microbial processes in a semi-arid agroecosystem. J Environ Manage 271:111033\u0026ndash;111033. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jenvman.2020.111033\u003c/span\u003e\u003cspan address=\"10.1016/j.jenvman.2020.111033\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSaudy HS, Hamed MF, Abd El-Momen WR, Hussein H (2020) Nitrogen use Rationalization and Boosting Wheat Productivity by Applying Packages of Humic, Amino Acids, and Microorganisms. Commun Soil Sci Plant Anal 51:1036\u0026ndash;1047. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1080/00103624.2020.1744631\u003c/span\u003e\u003cspan address=\"10.1080/00103624.2020.1744631\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSilva MJ, J. DY LYA (2023) Electrically-assisted supersonic solution blowing and solution blow spinning of fibrous materials from natural rubber extracted from havea brasilienses. Industrial Crops Prod 192. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.Indcrop.2022.116101\u003c/span\u003e\u003cspan address=\"10.1016/j.Indcrop.2022.116101\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang Y, Qin Y, Chai Q, Feng F, Zhao C, Yu A (2018) Interspecies Interactions in Relation to Root Distribution Across the Rooting Profile in Wheat-Maize Intercropping Under Different Plant Densities. Front Plant Sci 9:483. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3389/fpls.2018.00483\u003c/span\u003e\u003cspan address=\"10.3389/fpls.2018.00483\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWei W, Liu T, Zhang S, Shen L, Wang X, Li L, Zhu Y, Zhang W (2024) Root spatial distribution and belowground competition in an apple/ryegrass agroforestry system. Agric Syst 215. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.agsy.2024.103869\u003c/span\u003e\u003cspan address=\"10.1016/j.agsy.2024.103869\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWu J, Liu W, Chen C (2016a) Can intercropping with the world's three major beverage plants help improve the water use of rubber trees? J Appl Ecol 53:1787\u0026ndash;1799. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/1365-2664.12730\u003c/span\u003e\u003cspan address=\"10.1111/1365-2664.12730\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWu J, Liu W, Chen C, Bennett J (2016b) Can intercropping with the world's three major beverage plants help improve the water use of rubber trees? J Appl Ecol 53:1787\u0026ndash;1799. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/1365-2664.12730\u003c/span\u003e\u003cspan address=\"10.1111/1365-2664.12730\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWu X, Wu F, Zhou X, Fu X, Tao Y, iXu W, Pan K, Liu S (2016c) Effects of Intercropping with Potato Onion on the Growth of Tomato and Rhizosphere Alkaline Phosphatase Genes Diversity. Front Plant Sci 7:846. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3389/fpls.2016.00846\u003c/span\u003e\u003cspan address=\"10.3389/fpls.2016.00846\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXu L, Min Y, Huilan Y, Erhu G, Aiying Z (2017) Manure and mineral fertilization change enzyme activity and bacterial community in millet rhizosphere soils. World J Microbiol Biotechnol 34:8. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s11274-017-2394-3\u003c/span\u003e\u003cspan address=\"10.1007/s11274-017-2394-3\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYang B, Meng X, Singh AK, Wang P, Song L, Zakari S, Liu W (2020a) Intercrops improve surface water availability in rubber-based agroforestry systems. Agric Ecosyst Environ 298. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.agee.2020.106937\u003c/span\u003e\u003cspan address=\"10.1016/j.agee.2020.106937\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYang B, Meng X, Singh AK, Wang P, Song L, Zakari S, Liu W (2020b) Intercrops improve surface water availability in rubber-based agroforestry systems. Agric Ecosyst Environ 298. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.agee.2020.106937\u003c/span\u003e\u003cspan address=\"10.1016/j.agee.2020.106937\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYang B, Meng X, Zhu X, Zakari S, Singh AK, Bibi F, Mei N, Song L, Liu W (2021) Coffee performs better than amomum as a candidate in the rubber agroforestry system: Insights from water relations. Agric Water Manage 244. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.agwat.2020.106593\u003c/span\u003e\u003cspan address=\"10.1016/j.agwat.2020.106593\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYang Y, Yao F, Sun Y, Yang Z, Li R, Bai G, Lin W, Chen H (2024) Appropriately Reduced Nitrogen and Increased Phosphorus in Ratooning Rice Increased the Yield and Reduced the Greenhouse Gas Emissions in Southeast China. Plants (Basel Switzerland) 13:438. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/plants13030438\u003c/span\u003e\u003cspan address=\"10.3390/plants13030438\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYu L, Luo S, Xu X, Gou Y, Wang J (2020) The soil carbon cycle determined by GeoChip 5.0 in sugarcane and soybean intercropping systems with reduced nitrogen input in South China. Appl Soil Ecol 155. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.apsoil.2020.103653\u003c/span\u003e\u003cspan address=\"10.1016/j.apsoil.2020.103653\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYuan X, Yang B, Liu W, Wu J, Li X (2024) Intercropping with cash crops promotes sustainability of rubber agroforestry: Insights from litterfall production and associated carbon and nutrient fluxes. Eur J Agron 154:127071. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.Eja.2023.127071\u003c/span\u003e\u003cspan address=\"10.1016/j.Eja.2023.127071\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhao Y, Wang S, Zhang M, Zeng L, Zhang L, Huang S, Zhang R, Zhou W, Ai C (2024) Nitrogen Application and Rhizosphere Effect Exert Opposite Effects on Key Straw-Decomposing Microorganisms in Straw-Amended Soil. Microorganisms 12. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/microorganisms12030574\u003c/span\u003e\u003cspan address=\"10.3390/microorganisms12030574\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZheng B-c, Ying Z, Ping C, Xiao-na Z, Qing DU, Huan Y, Xiao-chun W, Feng Y, Te X, Long LI, Wen-yu Y, Tai-wen Y (2022a) Maize\u0026ndash;legume intercropping promote N uptake through changing the root spatial distribution, legume nodulation capacity, and soil N availability. J Integr Agric 21:1755\u0026ndash;1771. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/s2095-3119(21)63730-9\u003c/span\u003e\u003cspan address=\"10.1016/s2095-3119(21)63730-9\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZheng B, Chen P, Du Q, Yang H, Luo K, Wang X, Yang F, Yong T, Yang W (2022b) Soil Organic Matter, Aggregates, and Microbial Characteristics of Intercropping Soybean under Straw Incorporation and N Input. Agriculture 12:1409\u0026ndash;1409. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/agriculture12091409\u003c/span\u003e\u003cspan address=\"10.3390/agriculture12091409\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhu W, Zhao H, Wang Y, Butterly CR, Chen H, Yuan J, Liu M, Chen Q, Zhang L, Wang L (2024) Optimal organic fertilization enhances the phytoavailability of phosphorus in the root zone of rice. Eur J Soil Sci 75. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/ejss.13588\u003c/span\u003e\u003cspan address=\"10.1111/ejss.13588\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZou Q, Zhao L, Guan L, Chen P, Zhao J, Zhao Y, Du Y, Xie Y (2024) The synergistic interaction effect between biochar and plant growth-promoting rhizobacteria on beneficial microbial communities in soil. Front Plant Sci 15:1501400\u0026ndash;1501400. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3389/fpls.2024.1501400\u003c/span\u003e\u003cspan address=\"10.3389/fpls.2024.1501400\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eUnderground interspecific competition intensity index for each treatment in different soil depths.\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"558\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 132px;\"\u003e\n \u003cp\u003eGrowth stage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 142px;\"\u003e\n \u003cp\u003eSoil depth (cm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 284px;\"\u003e\n \u003cp\u003eUnderground interspecific competition intensity index\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003eM1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003eM2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003eM3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003eVigorous growth stage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e0-20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e0.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e0.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e0.76\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 132px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e20-40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e0.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e0.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e0.90\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 132px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e40-60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 132px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003emean value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e0.75aA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e0.51aB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e0.66aA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003eBud development stage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e0-20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e0.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e0.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e0.89\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 132px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e20-40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e0.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e0.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e0.90\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 132px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e40-60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e0.67\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 132px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003emean value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e0.87aA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e0.85aA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e0.82aA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003eHarvest stage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e0-20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e0.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e0.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e0.74\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 132px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e20-40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e0.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e0.50\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 132px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e40-60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003emean value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e0.93aA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e0.91aA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e0.75aA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNote: Different lowercase letters indicate significant differences between the treatments in the same stage (\u003cem\u003ep\u0026nbsp;\u003c/em\u003e\u0026lt; 0.05). Different uppercase letters indicate significant differences of the same treatment between the stages (\u003cem\u003ep\u0026nbsp;\u003c/em\u003e\u0026lt; 0.05).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eUnderground interspecific competition intensity index for each treatment in different distances from the rubber tree.\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"558\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 132px;\"\u003e\n \u003cp\u003eGrowth stage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 142px;\"\u003e\n \u003cp\u003eDistance from the tree (cm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 284px;\"\u003e\n \u003cp\u003eUnderground interspecific competition intensity index\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003eM1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003eM2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003eM3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003eVigorous growth stage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 132px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e0.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 132px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e0.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e0.10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 132px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e120\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e0.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e0.32\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 132px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e150\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 132px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003emean value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e0.19aA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e0.16aAB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e0.19aA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003eBud development stage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e0.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 132px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 132px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e0.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e0.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e0.20\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 132px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e120\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e0.21\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 132px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e150\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 132px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003emean value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e0.16aA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e0.12aB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e0.16aA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003eHarvest stage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e0.20\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 132px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e0.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e0.21\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 132px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e0.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e0.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 132px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e120\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 132px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003e150\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 132px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 142px;\"\u003e\n \u003cp\u003emean value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e0.25aA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e0.28aA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e0.24aA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNote: Different lowercase letters indicate significant differences between the treatments in the same stage (\u003cem\u003ep\u003c/em\u003e\u0026lt;0.05). Different uppercase letters indicate significant differences of the same treatment between the stages (\u003cem\u003ep\u003c/em\u003e\u0026lt;0.05).\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":"Young rubber tree−banana intercropping, root spatial and temporal distribution, root competition, soil nutrients, microbial community","lastPublishedDoi":"10.21203/rs.3.rs-8835228/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8835228/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eAims\u003c/h2\u003e \u003cp\u003eOptimal fertilization strategies for rubber tree-banana intercropping systems and their comprehensive impacts on belowground interactions remain inadequately characterized. This study systematically evaluated the effects of different fertilization regimes on root distribution, interspecific competition, and rhizosphere properties.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThe experimental design included conventional chemical fertilization (M1), 30% organic nitrogen substitution (M2), 45% controlled-release nitrogen combined with chemical nitrogen (M3), and rubber tree monoculture as control (CK).\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eResults demonstrated that the M2 treatment produced the most significant improvements, enhancing rubber tree height by 16.26% and stem girth by 8.66% compared to CK, while simultaneously supporting optimal banana growth within the intercropping system. Detailed analysis of root spatial-temporal distribution revealed that M2 treatment improved root niche complementarity and enhanced system adaptability to subsurface competition. Furthermore, M2 significantly modified rhizosphere microbial community structure by increasing microbial diversity and enriching beneficial bacterial and fungal phyla. These microbial community shifts showed strong positive correlations with improved soil fertility indicators and plant growth performance. Importantly, this fertilization strategy effectively reduced root competition intensity across different soil layers during critical banana developmental stages, including the vigorous growth and bud development phases.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eOur integrated analysis demonstrates that substituting 30% of chemical nitrogen with organic nitrogen represents an optimal fertilization approach, as it simultaneously enhances plant productivity, alleviates belowground competition, and improves soil ecological conditions. Therefore, this study provides a scientifically-grounded and sustainable management strategy for enhancing the productivity and ecological sustainability of rubber tree-banana intercropping systems.\u003c/p\u003e","manuscriptTitle":"Optimizing Belowground Interactions in Young Rubber Tree−Banana Intercropping via Partial Organic Fertilizer Substitution: Root Competition, Soil Nutrients, and Microbial Communities","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-26 07:20:53","doi":"10.21203/rs.3.rs-8835228/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":"3776f2c8-d535-4aab-b5aa-10ebd413ed67","owner":[],"postedDate":"February 26th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-04-10T07:43:29+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-26 07:20:53","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8835228","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8835228","identity":"rs-8835228","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}