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Article

Tea Plant/Ophiopogon japonicus Intercropping Drives the Reshaping of Soil Microbial Communities in Terraced Tea Plantation’s Micro-Topographical Units

by
Yangxin Li
1,†,
Le Sun
1,†,
Jialin Zhang
2,
Hongxue Zhao
1,
Tejia Su
1,
Wenhui Li
1,
Linkun Wu
3,
Pumo Cai
1,
Christopher Rensing
4,
Yuanping Li
1,4,
Jianming Zhang
1,
Feiquan Wang
1 and
Qisong Li
1,*
1
College of Tea and Food Science, Wuyi University, Wuyishan 354300, China
2
College of Tourism, Xinyang Vocational and Technical College, Xinyang 464000, China
3
College of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou 350002, China
4
Institute of Environmental Microbiology, Fujian Agriculture and Forestry University, Fuzhou 350002, China
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Agriculture 2025, 15(11), 1150; https://doi.org/10.3390/agriculture15111150
Submission received: 30 April 2025 / Revised: 25 May 2025 / Accepted: 25 May 2025 / Published: 27 May 2025
(This article belongs to the Section Agricultural Soils)
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Abstract

:
The monoculture planting in terraced tea plantations has led to severe soil degradation, which poses a significant threat to the growth of tea plants. However, the mechanisms by which intercropping systems improve soil health through the regulation of soil microbial communities at the micro-topographical scale of terraced tea plantations (i.e., terrace surface, inter-row, and terrace wall) remain unclear. This study investigates the effects of intercropping Ophiopogon japonicus in a five-year tea plantation on the soil physicochemical properties, enzyme activities, and microbial community structure and functions across different micro-topographical features of terraced tea plantations in Wuyi Mountain. The results indicate that intercropping significantly improved the soil organic matter, available nutrients, and redox enzyme activities in the inter-row, terrace surface, and terrace wall, with the effects gradually decreasing with increasing distance from the tea plant rhizosphere. In the intercropping group, tea leaf yield increased by 13.17% (fresh weight) and 19.29% (dry weight) compared to monoculture, and the disease indices of new and old leaves decreased by 40.63% and 38.7%, respectively. Intercropping strengthened the modularity of bacterial networks and the role of stochasticity in shaping bacterial communities in different micro-topographic environments, in contrast to the patterns observed in fungal communities. The importance of microbial phyla such as Proteobacteria and Ascomycota in different micro-topographical features was significantly regulated by intercropping. In different micro-topographical zones of the terraced tea plantation, beneficial bacterial genera such as Sinomonas, Arthrobacter, and Ferruginibacter were significantly enriched, whereas potential fungal pathogens like Nigrospora, Microdochium, and Periconia were markedly suppressed. Functional annotations revealed that nitrogen cycling functions were particularly enhanced in inter-row soils, while carbon cycling functions were more prominent on the terrace surface and wall. This study sheds light on the synergistic regulatory mechanisms between micro-topographical heterogeneity and intercropping systems, offering theoretical support for mitigating soil degradation and optimizing management strategies in terraced tea agroecosystems.

1. Introduction

Tea plant (Camellia sinensis), as a globally significant economic crop, exhibits distinct geographic distribution characteristics [1]. China, as the world’s largest tea producer, has most of its tea plantations located in the southern hilly regions [2], where tea plants are planted in terraced layouts. Benefiting from unique geographic conditions, the hilly regions (elevation ranging from 200 to 2500 m) have good drainage and large diurnal temperature variations. Research by Wen [3] indicates that low-latitude regions, due to temperature differences driving the allocation of photosynthates, accumulate more free amino acids in tea leaves. Additionally, high-altitude tea plantations promote the accumulation of secondary metabolites in tea leaves, such as flavonoids and amino acids, which, in turn, influence the formation of tea quality [4]. However, the long-term intensive monoculture in tea plantations leads to soil erosion, along with declining nutrient content and imbalanced microbial diversity, severely threatening the sustainable development of terraced tea plantations [5].
By artificially reshaping hillside topography and configuring vegetation, soil erosion can be mitigated, and nutrient cycling can be influenced [6]. Among these strategies, intercropping, as a high-yield and sustainable planting system, has been widely applied in tea plantations. The advantages of intercropping are primarily reflected in its ability to enhance resource use efficiency by utilizing ecological niche differences between different crops for resource acquisition, while also promoting the improvement of the soil’s microecological environment [7,8]. For instance, studies have shown that intercropping peas with tea plants can regulate the changes in soil microbiota, such as Acidobacteria and Proteobacteria, in the tea soil, and by enriching soil microbes involved in carbon and nitrogen cycling, it can improve tea quality [9]. Wang [10] pointed out that in the intercropping system of tea plants and green manure, under the influence of soil nutrients and enzyme activities, significant changes in the composition of tea soil microbial communities occurred, with a notable increase in the relative abundance of microorganisms such as Acidobacteriota and Firmicutes. As an important component of agricultural ecosystems, soil microbes can significantly influence plant growth through organic matter decomposition and involvement in carbon and nitrogen cycles [11]. The mechanisms of soil microbial community assembly refer to the processes that govern species coexistence and the formation and maintenance of species diversity. Current research generally suggests that the assembly of soil microbial communities is jointly regulated by stochastic and deterministic factors [12,13]. Previous studies have shown that the micro-topography of monsoon evergreen broad-leaved forests regulates the spatial differences in soil physicochemical properties, which, in turn, control the diversity of soil fungi and the assembly of functional microbial communities [14]. Li et al. [15] also noted that in alpine meadows, the spatial scale differences of micro-topography, such as on sunny slopes, valley bottoms, and shady slopes, caused different changes in soil bacterial and fungal communities during the assembly process and co-occurrence networks, and functional microbial communities also underwent varying degrees of reconstruction. Therefore, in the terraced tea plantation ecosystem, different micro-topographies, due to variations in root distribution density and topography, result in significant differences in microbial communities. Previous research on tea plantation intercropping has largely focused on the flat scale [16,17], neglecting the differential impact of the spatial heterogeneity of micro-topographical units, such as inter-row, terrace surface, and terrace wall, on soil environments. This limitation makes it difficult to reveal the dynamic response mechanisms of soil physicochemical properties and microbial functional communities under the synergistic effects of micro-topography and intercropping systems. Therefore, this study focuses on the micro-topography of terraced tea plantations (terrace surface/inter-row/terrace wall) as the research subject and investigates the impact of different planting modes on the structure of microbial communities in these micro-topographies.
Ophiopogon japonicus, a perennial herbaceous plant with both ecological and medicinal value, has been increasingly used in tea plantation intercropping and soil erosion control in recent years [18]. O. japonicus possesses a well-developed shallow root network and exhibits strong adaptability to the soil conditions of terraced fields [19], Its high shade tolerance allows it to thrive in the relatively low-light environments typical of mountainous tea plant plantations in southern China, highlighting its suitability as a shade-tolerant green manure species coexisting with tea plants in terraced systems. Furthermore, its dense and extensive root system enhances soil structure and reduces surface runoff, thereby effectively minimizing soil erosion on terraced slopes [20]. Our previous research found that intercropping O. japonicus in tea plantations can regulate the soil microbial community of tea plants and improve soil carbon and nitrogen cycling through root exudates [18]. However, whether this effect exhibits spatial heterogeneity in the inter-row, terrace surface, and terrace wall areas due to micro-topographical differences in terraced fields, and the specific processes and underlying mechanisms, remain unclear. Therefore, this study investigates the changes in soil physicochemical properties and enzyme activities under the combined influence of micro-topographical units and planting modes through a five-year field experiment. It also employs high-throughput analysis to examine the changes in soil microbial community structure and functional microbial groups. This study provides new insights into the ecological regulation mechanisms of intercropping systems in terraced tea plantations and offers theoretical support for the sustainable management of terraced agricultural ecosystems.

2. Materials and Methods

2.1. Site Description and Experimental Design

The experimental tea plantation is located in Wuyishan, Nanping City, Fujian Province, China (27°44′ N, 117°59′ E, with an annual average temperature of 21.1 °C and an average annual total precipitation of 1674 mm). The plantation receives approximately 1629.5 h of sunlight per year, with an elevation of about 250 m. The tea variety used in the experiment is Wuyi Rougui (Camellia sinensis L. Rougui), which was planted in February 2017, with manual weeding and routine management practices applied. The tea plantation is laid out in a terraced style, with a terrace width of 1.2 m and a terrace wall height of 0.8 m, typical of terraced tea plantations. Three experimental plots, each measuring 10 m by 10 m, were randomly set up within the plantation, with a distance of more than 30 m between plots. In April 2019, O. japonicus was planted on the terrace surface and terrace wall of the intercropping plots, with the minimum distance from the tea plants being 0.3 m (as shown in Figure 1). Every year, a compound fertilizer (N:P:K = 21:8:16) was applied at 700 kg per hectare in late October. Soil samples were collected in mid-April 2024 using a five-point sampling method to obtain inter-row soil (RP), terrace surface soil (RS), and terrace wall soil (RW) [21]. Soil samples were also collected from monoculture tea plots located in various micro-topographical units as control groups (MP, MS, MW). After collection, the samples were stored at 4 °C and −80 °C for subsequent testing.

2.2. Soil Physicochemical Properties and Enzyme Activity Measurements

Soil pH was determined using the electrode potential method (1:2.5, soil-to-water ratio); total soil organic carbon (SOM) was measured by potassium dichromate oxidation spectrophotometry; soil moisture content (MC) was determined by the drying method; alkaline hydrolyzable nitrogen (AHN) was measured using the alkaline hydrolysis diffusion method; available potassium (AK) was measured by flame photometry; available phosphorus (AP) was determined by the sodium bicarbonate extraction molybdenum-antimony colorimetric method; polyphenol oxidase (PPO) activity was measured using the o-phenylenediamine colorimetric method; peroxidase (POD) activity was determined by potassium permanganate titration; protease (ACPT) activity was measured by the Folin-Ciocslteu colorimetric method; acid phosphatase (ACP) activity was measured by phenylphosphate colorimetry; cellulase (CE) activity was determined by anthrone colorimetry; sucrase activity was measured by the DNS colorimetric method. All of the above indices were measured using the methods of Guan et al. [22].

2.3. Tea Plant Yield Measurement and Disease Survey

Tea yield was measured during the spring tea harvesting period (April–May) in the fifth year after intercropping O. japonicus. Following the method of Zhang et al. [23], a 1 m × 1 m quadrat was placed over the tea canopy to count the number of visible one-bud-three-leaf shoots per unit area. After the harvested fresh leaves were brought back to the laboratory, they were immediately placed in an oven at 120 °C for 30 min for blanching, then the temperature was reduced to 80 °C for constant-temperature drying until a constant weight was achieved, and the dry weight was recorded.
To minimize interference from abiotic factors, only leaf spots exhibiting typical pathogenic characteristics were recorded during the field investigation. Figure S1 presents representative leaf samples corresponding to each scoring level, ensuring that the survey data primarily reflect the incidence of pathogen-related diseases. A disease survey was conducted on the leaves, with the disease severity rated on a 5-point scale: 0, no symptom; 1, spots covering less than 1/4 of the leaf surface; 2, spots covering from 1/4 to 1/2 of the leaf surface; 3, spots covering from 1/2 to 3/4 of the leaf surface; 4, spots covering more than 3/4 of the leaf surface. All leaves were observed, distinguishing between old and new leaves, and the number of leaves in each disease severity category was recorded. The disease incidence rate and disease index were then calculated. The disease situation was evaluated based on the conditions of monoculture and intercropped tea plants in the tea plantation.
Disease incidence rate (%) = (Number of diseased leaves/Total number of surveyed leaves) × 100
Disease index = [Σ (Number of leaves in each disease severity category × corresponding disease severity level)/(Total number of surveyed leaves × 4)] × 100

2.4. Total Soil DNA Extraction

In this study, total DNA was extracted from soil samples using the BioFast Soil Genomic DNA Extraction Kit (BioFlux, Hangzhou, China). The DNA concentration of the extracted products was subsequently quantified using a NanoDrop 2000C UV spectrophotometer (Thermo Scientific, Waltham, MA, USA). DNA samples that passed the quality control check were retained for subsequent amplicon sequencing and downstream microbial community analysis.

2.5. 16S/ITS rDNA High-Throughput Sequencing Analysis

In this study, polymerase chain reaction (PCR) technology was used to amplify bacterial 16S rDNA and eukaryotic ITS rDNA target gene fragments. The primer sequences and amplification program parameters involved in the experiment are detailed in Table S1. The amplification reactions were completed using an ABI Gene Amp® 9700 thermal cycler (Applied Biosystems, Foster City, CA, USA), and the amplified products were purified before being subjected to paired-end sequencing using the Illumina HiSeq 2500 high-throughput sequencing system (Illumina, San Diego, CA, USA). The raw sequencing data were preprocessed using the Qiime bioinformatics platform (v1.9.1), with strict quality control standards: sequences with an average quality score below 20 (Phred score < 20) and short sequences less than 100 bp were removed, and a high-quality clean tags dataset was constructed. Based on the UPARSE algorithm (v7.0.1001), effective tags from all samples were clustered using a 97% nucleotide sequence similarity threshold to obtain operational taxonomic units (OTUs). The BLAST algorithm (v2.12.0+) was applied on the Qiime platform to annotate the OTU representative sequences using the Silva 16S rDNA reference database (v138) for bacteria. Fungal taxonomic annotation was performed based on the Unite ITS reference database (v7.2). The composition and relative abundance distribution of the soil microbial community were analyzed at various taxonomic levels, including phylum, class, order, family, and genus.

2.6. Data Analysis

Soil physicochemical properties and enzyme activity data were initially processed using Microsoft Excel 2016. One-way analysis of variance (ANOVA) was conducted using SPSS 26.0, and Duncan’s multiple comparison method was used to analyze the significance of differences between groups, with a significance level of p < 0.05. Based on the Bray–Curtis distance matrix, microbial diversity (Shannon index) and richness (ACE index) were analyzed using Mothur (v1.48.0) and R software (v 4.3). The non-linear least squares (NLS) method was used to fit the neutral community model (NCM). Spearman’s correlation analysis was performed using the vegan package in R, and strongly correlated genera were selected with |r| > 0.8 and p < 0.05. Gephi (v0.9.7) was used for visualization to construct species co-occurrence network analysis (Network) and calculate associated network topology parameters. Functional annotation of soil bacterial and fungal OTU abundance matrices was performed based on the FAPROTAX bacterial functional annotation database (v1.2.4) and the FUNGuild fungal functional annotation database (v1.3). Redundancy analysis (RDA) was conducted using the vegan package in R. The Mantel test and Pearson correlation analysis were completed using the dplyr, ggcor, and ggplot2 packages in R.

3. Results

3.1. The Impact of O. japonicus Intercropping on Soil Physicochemical Properties in Different Micro-Topographical Units of Tea Plantations

Soil physicochemical properties and enzyme activities are core indicators reflecting soil health. In the terraced tea plantation intercropping system with O. japonicus, the soil organic matter content (SOM), peroxidase activity (POD), acid phosphatase activity (ACP), cellulase activity (CE), and sucrase activity (Sucrase) in the intercropping groups (RP, RS, RW) were significantly higher than those in the monoculture groups (MP, MS, MW) in different topographical units (Figure 2B,H,J–L) (p < 0.05). There were no significant differences in soil pH, alkaline hydrolyzable nitrogen (AHN), polyphenol oxidase activity (PPO), or cellulase activity (CE) on the terrace surface (p > 0.05), but the intercropping groups (RP, RW) showed significantly higher values than the monoculture groups (MP, MW) in the inter-row and terrace wall areas. In the inter-row, the RP group had higher AK, AP, and ACPT than the MP group, with overall group differences decreasing on the terrace surface and terrace wall (Figure 2E,F,I). Except for ACP, which showed no significant difference, the other indicators exhibited a gradient decrease as the distance from the tea plant trunk increased (p < 0.05). Therefore, organic matter, available nutrients, and enzyme activities in the soil of different micro-topographies in the tea plantation were significantly improved after intercropping O. japonicus, with a gradient decrease observed in the inter-row, terrace surface, and terrace wall areas.

3.2. Tea Plant Yield Measurement and Disease Survey in Monoculture and O. japonicus Intercropping Systems

The results of the yield and disease surveys indicated that the fresh weight and dry weight of new leaves significantly increased by 13.17% and 19.29%, respectively, after intercropping (Figure 3A). The disease index of new leaves and old leaves significantly decreased by 45.06% and 65.15%, respectively (p < 0.01) (Figure 3B). Regarding the disease incidence rate of tea plants, the disease rates of new and old leaves decreased by 27.71% and 48.87%, respectively, after intercropping O. japonicus (Figure 3C). Therefore, long-term intercropping with O. japonicus significantly increased tea leaf yield and reduced the occurrence of diseases in the tea plantation.

3.3. Analysis of Soil Microbial Diversity in Terraced Tea Plantations Under O. japonicus Intercropping

The diversity of soil microbial communities is influenced by the planting mode and the spatial heterogeneity of tea plantation soils. As shown in Figure 4A,B, intercropping O. japonicus slightly reduced the α diversity of the soil bacterial community, with no significant differences observed between groups at different terraced locations. Regarding fungal α diversity, both the Ace index and Shannon index exhibited similar trends (Figure 4D,E). In the inter-row, both indices showed a significant increase of 22.67% and 4.53%, respectively, for RP compared to MP. In the terrace wall, RW exhibited a significant decrease of 13.7% and 18.62%, respectively, compared to MW, while no significant differences were observed on the terrace surface.
Principal coordinates analysis (PCoA) was used to further explore the characteristics of the soil microbial communities in the tea plantation. PCoA1 and PCoA2 explained 30.41% of the variation in the bacterial community and 62.28% of the variation in the fungal community, respectively (Figure 4C). Monoculture and intercropping were clearly differentiated along the vertical axis, while the terrace surface and terrace wall under different treatments formed distinct clusters (R2 = 0.877, p < 0.01). Additionally, the fungal community showed more pronounced dispersion (Figure 4F), with the intercropping groups in the inter-row, terrace surface, and terrace wall being separated along the PCoA1 axis, indicating significant differences in community composition (R2 = 0.975, p < 0.01).

3.4. The Impact of O. japonicus Intercropping on Microbial Community Assembly and Diffusion in Terraced Tea Plantations

Further, by constructing co-occurrence networks, the effect of intercropping with O. japonicus on microbial community relationships in different micro-topographic units of terraced tea plantations was evaluated. The results show that the greater the distance was from the base of the tea plant to the micro-topography, the lower the modularity of the bacterial co-occurrence network iswas with the modularity index of the intercropping group being higher than that of the monoculture group (Figure 5A–C). In the fungal co-occurrence network, the number of points, edges, and modularity index in the monoculture group showed an increasing trend in the inter-row, terrace surface, and terrace wall. After intercropping, the number of points, edges, and modularity index of fungi increased only in the inter-row, while no significant changes were observed in other micro-topographies (Figure 5D–F).
The neutral community model (NCM) was used to assess the influence of deterministic and stochastic factors on the assembly of different soil microbial communities. The results indicated that in monoculture system, stochastic factors contributed to 67.6%, 68%, and 72.6% of the variation in the bacterial communities in the inter-row, terrace surface, and terrace wall soils, respectively, compared to 56%, 62.3%, and 64.7% in the intercropping soils. Overall, the Rsqr values for the monoculture groups were higher than those for the O. japonicus intercropping groups (Rsqr represents the goodness of fit of the model and evaluates the influence of stochastic factors on species distribution). Additionally, in all micro-topographical units, the Nm values for monoculture NCM were higher than those for intercropped soil bacteria (Nm = N × m), with values of 27,478 > 14,912, 34,627 > 25,767, and 37,556 > 17,780. Therefore, stochastic factors were the main drivers of bacterial community assembly in the inter-row, terrace surface, and terrace wall soils under monoculture treatments, and the influence of stochastic factors increased as the distance from the tea plant rhizosphere increased (Figure 6A–F). Intercropping, however, enhanced the deterministic factors in the assembly process of soil microbial communities across different micro-topographical units. The neutral community model (NCM) results for the tea plantation soil fungal community showed that the Rsqr values (0.228 < Rsqr < 0.443) followed a similar trend to that of soil bacteria across different micro-topographical units, with intercropping treatments increasing the Rsqr values in each micro-topography (Figure 6G–L). This result indicates that the fungal community is more strongly influenced by deterministic factors, with the influence of these factors becoming more significant as the distance to the tea plant rhizosphere decreases. Moreover, the intercropping treatment increased the randomness in the microbial community construction process in soils of different micro-topographic units.

3.5. The Impact of O. japonicus Intercropping on Core Functional Microbial Groups in the Micro-Topographical Units of Terraced Tea Plantations

A random forest model was further established for the soil microbial communities in different micro-topographical units of the terraced tea plantation, and the top 20 key bacterial and fungal genera contributing to inter-group differences are shown in Figure 7. In the bacterial random forest model, Proteobacteria, Actinobacteria, and Firmicutes were the three bacterial phyla with the highest abundance in the soil samples (Figure 7A–C). Among them, Proteobacteria-associated bacteria played a key role in the inter-row, and as the distance from the tea plant rhizosphere increased, other bacterial phyla became more prominent in the terrace wall.
For the fungal random forest model, Ascomycota dominated in the inter-row and terrace surface, while in the terrace wall, the importance of Basidiomycota and other fungi gradually increased (Figure 7D–F). Sinomonas, a genus with a large contribution to the differences across various micro-topographies, showed a significant increase in abundance in the intercropping O. japonicus groups compared to monoculture: 246.41%, 141.87%, and 268.28% higher in the inter-row, terrace surface, and terrace wall, respectively (Figure 7G). Conversely, the abundance of Microdochium and Periconia significantly decreased in different micro-topographies compared to monoculture (p < 0.05) (Figure 7H).
This study classified the functional groups of soil bacterial communities based on FAPROTAX, focusing on functions related to soil carbon and nitrogen cycling (Figure 8A). The results indicated that the bacterial community in the inter-row had stronger nitrogen cycling-related functions compared to the terrace surface and terrace wall. Additionally, intercropping treatments significantly enhanced nitrogen cycling-related functions compared to monoculture. Furthermore, the bacterial microbes in the terrace surface and terrace wall were primarily involved in carbon cycling-related functions such as methanotrophy, cellulolysis, ligninolysis, and chitinolysis, with the intercropping groups (RS, RW) showing higher activity than the monoculture groups (MS, MW).
FUNGuild was used to predict and classify the ecological functions of fungal communities into three functional groups: Symbiotrophy, Saprotroph, and Pathotroph (Figure 8B, Table S3). The effects of different micro-topographical units and O. japonicus intercropping treatments on the abundance of fungal functional groups varied. The results indicated that the co-occurrence function in the monoculture groups on the terrace surface and inter-row (MS, MW) was significantly higher than in the intercropping groups (RS, RW) (p < 0.01). Furthermore, plant pathogens, including various pathogenic fungi, were significantly more abundant in monoculture tea plant areas compared to O. japonicus intercropping areas. The abundance of pathogens decreased as the distance from the tea plant roots increased.

3.6. Correlation Between Soil Microbial Community Structure and Soil Physicochemical Properties

To further clarify the dynamic changes in the soil microbial community characteristics in terraced tea plantations and their driving factors, redundancy analysis (RDA) was performed to analyze the relationships between bacterial and fungal communities and soil physicochemical indicators and enzyme activities. For the bacterial and fungal communities under different treatments, the total explanatory power of the RDA1 axis and RDA2 axis were 46.72% and 40.01%, respectively (Figure 9B). Among these, CE was significantly correlated with Sucrase, and POD was significantly correlated with SOM. Additionally, the bacterial communities related to the C cycle were significantly correlated with key enzyme activities, including AP, PPO, and ACPT (p < 0.01) (Figure 9C). In the fungal community, symbiotic fungi showed significant correlations with AHN, AP, SOM, pH, and most enzyme activities, except ACP (p < 0.01). Saprophytic fungi were significantly correlated with SOM and MC. Pathogenic fungi showed significant correlations with AHN, AP, SOM, and other soil nutrients and enzyme activities (p < 0.001) (Figure 9D).

4. Discussion

4.1. Spatial Heterogeneity in Microbial Functional Community Assembly Driven by O. japonicus Intercropping in Terraced Tea Plantations

Terracing is widely used in tea plantations as an effective measure for controlling soil erosion on slopes and accumulating nutrients. This study, after five years of intercropping O. japonicus, found that intercropping significantly improved tea plant yield and disease resistance (Figure 3A and Figure 7H). This suggests that intercropping O. japonicus not only improves the soil environment in the tea plant rhizosphere but also helps enhance the microclimate of terraced tea plantations, reducing soil erosion and maintaining soil stability [24]. By regulating the microclimate of tea plantations, O. japonicus can alleviate heat stress during high-temperature periods and mitigate cold damage under low-temperature conditions, thereby improving the growing environment for tea plants. As tea plants are taller than O. japonicus, the resulting shading effect and light scattering enhance photosynthetic activity in the middle and lower canopy leaves of the tea plants, ultimately contributing to improved growth and increased yield [25]. However, the impact of intercropping on the soil microbial communities in different micro-topographical units of terraced tea plantations remains unclear.
Given the inherent spatial distribution differences in terraced tea plantations, the soil environment is inevitably further influenced by intercropping O. japonicus. This study found that intercropping O. japonicus significantly improved the physicochemical properties and enzyme activities of soil in different micro-topographical units of the terraced tea plantation, exhibiting spatial heterogeneity (the impact was greatest in the inter-row > terrace surface > terrace wall). Among these, the inter-row, as the micro-topography with the most intense root interaction between tea plants and O. japonicus, accumulated root exudates and litter from both plants, leading to a stronger nutrient accumulation capacity, particularly for organic matter content (Figure 2B). This facilitated the gradual formation of a nutrient-enriched ecological niche advantage in the inter-row. Moreover, root exudates, as key mediators of plant-plant signal transmission, are regulated by plant spacing. Increasing the distance between O. japonicus and tea plants on the terrace surface and terrace wall leads to a reduction in root density [26,27]. The reduced spatial diffusion capacity of plant exudates and litter may result in a diminishing effect of intercropping O. japonicus on the levels of cellulase, sucrase, and organic matter in the terrace surface and terrace wall soils. In this study, the O. japonicus intercropping treatment resulted in increases of 25.63%, 28.39%, and 13.34% in peroxidase, catalase, and sucrase activities, respectively, compared to the monoculture group (Figure 2H,K,L). These enzyme activities exhibited a decreasing trend from inter-row spaces to terrace surfaces and terrace walls, supporting the notion that root exudates play a regulatory role in enzyme activity across intercropped units and micro-topographical positions.
In agroforestry soil ecosystems, microbial community–soil enzyme activity–soil degradation interactions have significant synergies [28]. Therefore, soil microorganisms, as key participants in organic matter decomposition, have their enrichment of primary functional microbial groups regulated by differential inputs of organic carbon sources. However, the impact of intercropping on the soil microbial communities of different micro-topographical units in terraced tea plantations remains unclear. In this study, the differences in bacterial and fungal α diversity were not significant. Notably, in the PCoA results, the terrace surface and terrace wall of the two treatments formed distinct clusters, with significant differences from the inter-row soils. Moreover, intercropping further altered the community structure of different micro-topographies, showing significant differences compared to monoculture. Previous studies have shown that the advantages of intercropping are more related to the enrichment of functional microbial communities that alter soil nutrient cycling, rather than merely affecting diversity [29]. Therefore, we speculate that the advantage of tea plant and O. japonicus intercropping is primarily formed through the reshaping of functional microbial communities rather than changes in diversity.
Microbial distribution in natural habitats is not uniform, and their abundance varies across different spatial scales, showing either aggregation or dispersion along environmental gradients [30,31]. The neutral community model suggests that the bacterial community assembly in the inter-row, terrace surface, and terrace wall soils of the tea plantation is mainly dominated by stochastic factors (such as diffusion limitation, birth, and death), and intercropping O. japonicus enhances the role of stochastic factors in the microbial community assembly process in different micro-topographical units. In contrast, deterministic factors (such as interspecific competition and resource allocation) dominate the assembly of fungal communities. Previous studies have shown that there are significant differences in the assembly mechanisms of bacterial and fungal communities, and the effects of stochastic and deterministic factors on microbial community assembly are significantly mediated by spatial location [32,33]. It is evident that under the influence of deterministic factors like O. japonicus intercropping, the assembly of bacteria and fungi in different micro-topographical soils is affected. Co-occurrence network analysis also shows that intercropping O. japonicus reduces the microbial structural differences between the inter-row soil and other micro-topographical soils (Figure 5) [34,35,36]. This impact reflects the rapid response of microbial communities to planting systems and micro-topographical environments, and the differences in microbial community structure contribute to the ecological niche complementarity (i.e., nutrient uptake differences) in the intercropping advantage, thereby optimizing the productivity of the plant–soil spatial system [37]. Therefore, tea plant and O. japonicus intercropping improves the soil environment of tea plantations by reshaping the microbial community structure and functions in different micro-topographical soils.

4.2. O. japonicus Intercropping Drives the Differentiation of Soil Microbial Carbon and Nitrogen Cycling Functions and Ecological Regulation in Tea Plantation Micro-Topographies

Overall, plant species suitable for intercropping with tea plants typically exhibit strong ecological adaptability, well-developed root systems, and the ability to regulate the microclimate. In contrast, unsuitable intercropping species may compete with tea plants for nutrients during early growth stages or negatively impact soil health [17]. Therefore, selecting appropriate intercropping species is critical for optimizing tea plantation management, enhancing soil quality, and improving crop productivity. Research by Huang et al. demonstrated that intercropping tea plants with green manure species such as soybean and Astragalus sinicus significantly increased total nitrogen and organic matter content in the soil, while also exerting notable effects on bacterial community composition [38]. RDA and the Mantel test were used to reveal the dynamic changes in the soil microbial community structure and functions in terraced tea plantations. The results showed that, under intercropping with O. japonicus, the microbial community structure characteristics (bacteria and fungi) in different micro-topographies were significantly positively correlated with soil physicochemical properties and enzyme activities (Figure 9A,B). The random forest analysis indicated that Proteobacteria was the major contributor to the significant changes in the microbial community in the inter-row soil caused by intercropping. Multiple studies have shown that Proteobacteria, as a dominant phylum in soil microbial communities, has its abundance regulated by various environmental factors and is closely related to soil nitrogen cycling functions [39,40,41].
Functional predictions revealed that the abundance of nitrogen cycling-related functional microbes in the inter-row soil was significantly higher than in soils at other locations, and intercropping further enhanced this function. In the terrace surface and terrace wall soils, the bacterial community functions of the intercropping group mainly focused on carbon cycling functions, such as methanotrophy and cellulolysis, and intercropping also promoted these functions. At the genus level, in the random forest models for different spatial scales, the abundance of beneficial microbes related to plant growth processes and soil nutrient cycling, such as Sinomonas, Arthrobacter, and Ferruginibacter, was significantly increased under intercropping conditions. Additionally, fungal functional annotation indicated that the abundance of plant pathogens in the monoculture group was significantly higher than in the intercropping group and gradually decreased with increasing distance from the tea plant trunk (Figure 8). Potential pathogenic fungi, such as Nigrospora, Microdochium, and Periconia, were significantly reduced in the intercropping treatments. The health and yield of tea plants are influenced by various factors, among which plant diseases represent a major constraint on growth and quality [42]. Nigrospora has been identified as a causal agent of tea leaf blight, characterized by grayish-brown semicircular necrotic spots that, under severe conditions, can lead to extensive defoliation [43]. Other fungal genera such as Microdochium and Periconia have also been reported as plant pathogens. To mitigate the impact of these diseases, the introduction of intercropping plants can help suppress pathogenic microorganisms and enhance both ecological health and productivity in tea plantations. Many studies have shown that intercropping systems can enrich specific functional microbial groups through plant–microbe interactions, such as the significant increase in the relative abundance of beneficial bacteria in tea plant/legume intercropping, including Bradyrhizobium and Mycobacterium, which support tea plant growth [9,44]. This study further verifies a similar mechanism for O. japonicus intercropping. This difference reflects the impact of intercropping systems on resource allocation: in the inter-row soil, the strong interaction between the two plants leads to more enrichment of easily degradable nutrients, improving the soil nutritional environment. In the terrace surface and terrace wall soils, more litter is present, enhancing the carbon cycling-related functions in the soil. In addition, O. japonicus holds significant value as a traditional medicinal herb and can be harvested as a valuable by-product while simultaneously enhancing tea yield and quality. Moreover, the intercropping system reduces reliance on chemical fertilizers and pesticides, thereby promoting a more sustainable and environmentally friendly mode of tea plantation management [45].
The Mantel test further clarified the interaction between functional groups and environmental factors. In bacteria, groups involved in carbon cycling showed a highly significant positive correlation with AP (r = 0.90) and PPO (r = 0.79, p < 0.001). The association between saprotrophic fungi and SOM and MC suggests that saprotrophic fungi may maintain metabolic activity by decomposing carbon sources. Notably, the Mantel test analysis revealed a strong correlation between pathogenic fungi and soil physicochemical properties and enzyme activities, which may result from eutrophication promoting the proliferation of pathogens in monoculture inter-row soils [46]. However, intercropping O. japonicus improves soil organic matter content and peroxidase activity, recruits beneficial microbial communities with antagonistic effects to suppress pathogens [47], and limits their ecological niche through resource competition [48], thereby collaboratively inhibiting pathogen proliferation. In summary, the spatial heterogeneity of micro-topographical units in terraced tea plantations, under the synergistic effects of stochastic and deterministic factors, influences the assembly processes of bacteria and fungi by altering soil nutrient availability. The intercropping system promotes ecological regulation by facilitating the colonization of beneficial microbes and inhibiting pathogens, thereby enhancing microbial-mediated carbon and nitrogen cycling functions and changing the trend of modularity in the co-occurrence networks of micro-topographies.

5. Conclusions

This study, based on a five-year field experiment, elucidated the regulatory mechanisms of Camellia sinensis/Ophiopogon japonicus intercropping on soil ecology across distinct micro-topographical units in terraced tea plantations. Under intercropping, both tea plantation yield and disease resistance were improved to varying degrees, and the physicochemical properties and enzyme activities of the soil were significantly enhanced, with the effects decreasing as the distance from the tea plant rhizosphere increased. Additionally, intercropping strengthened the stochastic factors in bacterial community assembly in the inter-row and terrace wall soils, while fungal communities were primarily driven by deterministic factors. Functional microbial groups such as Sinomonas and Arthrobacter were significantly enriched under intercropping, while pathogenic fungi such as Cladophialophora and Microdochium significantly declined. Therefore, tea plant/O. japonicus intercropping enhances nutrient cycling efficiency in different micro-topographies by improving enzyme activity and promoting functional microbial groups. This indicates that terraced intercropping systems can drive the synergistic interaction between micro-topography and microorganisms to improve the soil environment, optimizing the spatial configuration of intercropping patterns in terraced tea plantations.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/agriculture15111150/s1, Table S1: Primers and pcr thermal cycling procedures; Table S2: Analysis of Co-occurrence networks of different soil microbial communities; Table S3: The abundance of fungal functional annotations in different treatments. Figure S1: Leaf samples corresponding to different disease severity levels.

Author Contributions

Conceptualization, Y.L. (Yangxin Li) and L.S.; methodology, Y.L. (Yangxin Li); software, Y.L. (Yangxin Li); validation, H.Z., Y.L. (Yuanping Li) and T.S.; formal analysis, Y.L. (Yangxin Li) and W.L.; investigation, T.S. and J.Z. (Jialin Zhang); resources, F.W.; data curation, L.S.; writing—original draft preparation, Y.L. (Yangxin Li) and L.S.; writing—review and editing, C.R. and Q.L.; visualization, P.C. and L.W.; supervision, Q.L.; project administration, J.Z. (Jianming Zhang); funding acquisition, Q.L. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by the Nanping City Science and Technology Plan Project Assignment (No. N2023Z005); Project of the National Natural Science Foundation of China (No. 82474035); Key Technological Innovation and Industrialization Project (No. 2023XQ019); Science and Technology Commissioner Innovation and Entrepreneurship Competition Project (No. N2022T002); Central Leading Local Science and Technology Development Project (No. 2021L3058); and The Project of Science and Technology Plan of Nanping City (No. N2024Z007).

Institutional Review Board Statement

Not applicable.

Data Availability Statement

The data presented in this study are available upon request from the corresponding author.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

The following abbreviations are used in this manuscript:
SOMSoil organic matter
MCMoisture content
AHNAlkaline hydrolyzable nitrogen
AKAvailable potassium
APAvailable phosphorus
PPOPolyphenol oxidase
PODPeroxidase
ACPTProtease
ACPAcid phosphatase
CECellulase
OTUsOperational taxonomic units

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Figure 1. Overview of the experimental area for this study.
Figure 1. Overview of the experimental area for this study.
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Figure 2. Determination results of key soil physicochemical indicators and enzyme activities at different spatial scales in the tea plant—O. japonicus intercropping terraced tea plantation ecosystem. (A): soil pH (pH); (B): soil organic matter content (SOM); (C): soil moisture content (MC); (D): alkaline hydrolyzable nitrogen (AHN); (E): available potassium (AK); (F): available phosphorus (AP); (G): polyphenol oxidase activity (PPO); (H): peroxidase activity (POD); (I): protease activity (ACPT); (J): acid phosphatase activity (ACP); (K): cellulase activity (CE); (L): sucrase activity (Sucrase). MP: monoculture inter-row; RP: intercropping inter-row; MS: monoculture terrace surface; RS: intercropping terrace surface; MW: monoculture terrace wall; RW: Intercropping terrace wall. The blue and yellow boxes represent the monoculture group and intercropping group, respectively. Error bars represent standard deviation, and different lowercase letters indicate significant differences between groups (p < 0.05).
Figure 2. Determination results of key soil physicochemical indicators and enzyme activities at different spatial scales in the tea plant—O. japonicus intercropping terraced tea plantation ecosystem. (A): soil pH (pH); (B): soil organic matter content (SOM); (C): soil moisture content (MC); (D): alkaline hydrolyzable nitrogen (AHN); (E): available potassium (AK); (F): available phosphorus (AP); (G): polyphenol oxidase activity (PPO); (H): peroxidase activity (POD); (I): protease activity (ACPT); (J): acid phosphatase activity (ACP); (K): cellulase activity (CE); (L): sucrase activity (Sucrase). MP: monoculture inter-row; RP: intercropping inter-row; MS: monoculture terrace surface; RS: intercropping terrace surface; MW: monoculture terrace wall; RW: Intercropping terrace wall. The blue and yellow boxes represent the monoculture group and intercropping group, respectively. Error bars represent standard deviation, and different lowercase letters indicate significant differences between groups (p < 0.05).
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Figure 3. Yield assessment and disease investigation. (A): Tea plant yield measurements. FW refers to the fresh weight of new leaves, and DW refers to the dry weight of new leaves. (B): Tea plant disease index. YDI represents the disease index of new leaves, and ODI represents the disease index of old leaves. (C): Disease incidence rate. YLD represents the disease incidence rate of new leaves, and OLD represents the disease incidence rate of old leaves. The number of asterisks (*) indicates the level of significance: * = p < 0.05, ** = p < 0.01, *** = p < 0.001.
Figure 3. Yield assessment and disease investigation. (A): Tea plant yield measurements. FW refers to the fresh weight of new leaves, and DW refers to the dry weight of new leaves. (B): Tea plant disease index. YDI represents the disease index of new leaves, and ODI represents the disease index of old leaves. (C): Disease incidence rate. YLD represents the disease incidence rate of new leaves, and OLD represents the disease incidence rate of old leaves. The number of asterisks (*) indicates the level of significance: * = p < 0.05, ** = p < 0.01, *** = p < 0.001.
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Figure 4. α Diversity and PCoA analysis of different planting modes and micro-topographical units in terraced tea plantations. (A,B) show the ACE and Shannon indices of the bacterial community; (C) shows the PCoA analysis of the bacterial community. (D,E) show the ACE and Shannon indices of the fungal community; (F) shows the PCoA analysis of the fungal community. In the α diversity analysis, different colors represent different planting patterns. In the PCoA analysis, the color of the points represents different planting modes, and different shapes represent different terraced micro-topographical units (inter-row, terrace surface, terrace wall).
Figure 4. α Diversity and PCoA analysis of different planting modes and micro-topographical units in terraced tea plantations. (A,B) show the ACE and Shannon indices of the bacterial community; (C) shows the PCoA analysis of the bacterial community. (D,E) show the ACE and Shannon indices of the fungal community; (F) shows the PCoA analysis of the fungal community. In the α diversity analysis, different colors represent different planting patterns. In the PCoA analysis, the color of the points represents different planting modes, and different shapes represent different terraced micro-topographical units (inter-row, terrace surface, terrace wall).
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Figure 5. Co-occurrence networks of soil microbial bacterial and fungal communities under different planting modes and micro-topographical units. (A,D) show the co-occurrence networks of bacterial and fungal communities in the soil of monoculture tea plants and O. japonicus intercropping in the inter-row, terrace surface, and terrace wall of terraced tea plantations. (B,C) show the nodes and modularity index of the bacterial co-occurrence network. (E,F) show the nodes and modularity index of the fungal co-occurrence network. Different colors in the co-occurrence network represent different modules, while different colors in the bar chart indicate different planting patterns.
Figure 5. Co-occurrence networks of soil microbial bacterial and fungal communities under different planting modes and micro-topographical units. (A,D) show the co-occurrence networks of bacterial and fungal communities in the soil of monoculture tea plants and O. japonicus intercropping in the inter-row, terrace surface, and terrace wall of terraced tea plantations. (B,C) show the nodes and modularity index of the bacterial co-occurrence network. (E,F) show the nodes and modularity index of the fungal co-occurrence network. Different colors in the co-occurrence network represent different modules, while different colors in the bar chart indicate different planting patterns.
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Figure 6. The neutral community model (NCM) was used to evaluate the assembly process of soil bacterial and fungal communities under different planting systems and different micro-topographical units of the terraced tea plantation. (A–F) represent the NCM of bacterial communities, and (G–L) represent the NCM of fungal communities. MP: monoculture inter-row; MS: monoculture terrace surface; MW: monoculture terrace wall; RP: intercropping inter-row; RS: intercropping terrace surface; RW: intercropping terrace wall. Rsqr represents the goodness of fit of the model. Nm is the product of the metacommunity size (N) and migration rate (m) (Nm = N ∗ m), quantifying the degree of diffusion between communities, which determines the correlation between occurrence frequency and regional relative abundance. The blue solid line indicates the point that best fits the NCM, and the dashed line represents the 95% confidence interval. Green and red points represent OTUs occurrence frequencies higher or lower than those predicted by NCM, while black points represent OTUs occurrence frequencies that match those predicted by NCM.
Figure 6. The neutral community model (NCM) was used to evaluate the assembly process of soil bacterial and fungal communities under different planting systems and different micro-topographical units of the terraced tea plantation. (A–F) represent the NCM of bacterial communities, and (G–L) represent the NCM of fungal communities. MP: monoculture inter-row; MS: monoculture terrace surface; MW: monoculture terrace wall; RP: intercropping inter-row; RS: intercropping terrace surface; RW: intercropping terrace wall. Rsqr represents the goodness of fit of the model. Nm is the product of the metacommunity size (N) and migration rate (m) (Nm = N ∗ m), quantifying the degree of diffusion between communities, which determines the correlation between occurrence frequency and regional relative abundance. The blue solid line indicates the point that best fits the NCM, and the dashed line represents the 95% confidence interval. Green and red points represent OTUs occurrence frequencies higher or lower than those predicted by NCM, while black points represent OTUs occurrence frequencies that match those predicted by NCM.
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Figure 7. The random forest model was used to evaluate the microbial taxonomic differences (top 20 key bacterial genera) in different micro-topographies. (A–C) represent the key differential bacterial genera between monoculture and intercropping in the inter-row, terrace surface, and terrace wall, respectively. (D–F) represent the key differential fungal genera between monoculture and intercropping in the inter-row, terrace surface, and terrace wall, respectively. (G) shows the abundance of beneficial microorganisms related to plant growth in different micro-topographies, while (H) shows the abundance of plant pathogenic microorganisms in different micro-topographies. In the boxplots, different letters indicate significant differences (p < 0.05).
Figure 7. The random forest model was used to evaluate the microbial taxonomic differences (top 20 key bacterial genera) in different micro-topographies. (A–C) represent the key differential bacterial genera between monoculture and intercropping in the inter-row, terrace surface, and terrace wall, respectively. (D–F) represent the key differential fungal genera between monoculture and intercropping in the inter-row, terrace surface, and terrace wall, respectively. (G) shows the abundance of beneficial microorganisms related to plant growth in different micro-topographies, while (H) shows the abundance of plant pathogenic microorganisms in different micro-topographies. In the boxplots, different letters indicate significant differences (p < 0.05).
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Figure 8. Functional prediction analysis of soil microbial communities in different micro-topographical units and O. japonicus intercropping treatments. (A): Functional annotation and prediction of bacterial communities using FAPROTAX. The x-axis shows the relative abundance in different samples, while the y-axis represents the various groups or samples. (B): Functional annotation and prediction of fungal communities using FUNGuild. In the bubble plot, the size of the bubbles and the letters on the bar chart indicate significant differences. The different percentages represent the mean relative abundance of functional annotations.
Figure 8. Functional prediction analysis of soil microbial communities in different micro-topographical units and O. japonicus intercropping treatments. (A): Functional annotation and prediction of bacterial communities using FAPROTAX. The x-axis shows the relative abundance in different samples, while the y-axis represents the various groups or samples. (B): Functional annotation and prediction of fungal communities using FUNGuild. In the bubble plot, the size of the bubbles and the letters on the bar chart indicate significant differences. The different percentages represent the mean relative abundance of functional annotations.
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Figure 9. Redundancy analysis (RDA) and Mantel test correlation analysis of the relationship between microbial communities and soil physicochemical factors in O. japonicus intercropping tea plantations. (A): RDA analysis of bacterial communities and soil physicochemical factors. (B): RDA analysis of fungal communities and soil physicochemical factors. (C): Mantel test analysis of bacteria with C and N cycling-related functions and soil physicochemical factors. (D): Mantel test analysis of symbiotic, saprotrophic, and pathogenic fungi with soil physicochemical factors.
Figure 9. Redundancy analysis (RDA) and Mantel test correlation analysis of the relationship between microbial communities and soil physicochemical factors in O. japonicus intercropping tea plantations. (A): RDA analysis of bacterial communities and soil physicochemical factors. (B): RDA analysis of fungal communities and soil physicochemical factors. (C): Mantel test analysis of bacteria with C and N cycling-related functions and soil physicochemical factors. (D): Mantel test analysis of symbiotic, saprotrophic, and pathogenic fungi with soil physicochemical factors.
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MDPI and ACS Style

Li, Y.; Sun, L.; Zhang, J.; Zhao, H.; Su, T.; Li, W.; Wu, L.; Cai, P.; Rensing, C.; Li, Y.; et al. Tea Plant/Ophiopogon japonicus Intercropping Drives the Reshaping of Soil Microbial Communities in Terraced Tea Plantation’s Micro-Topographical Units. Agriculture 2025, 15, 1150. https://doi.org/10.3390/agriculture15111150

AMA Style

Li Y, Sun L, Zhang J, Zhao H, Su T, Li W, Wu L, Cai P, Rensing C, Li Y, et al. Tea Plant/Ophiopogon japonicus Intercropping Drives the Reshaping of Soil Microbial Communities in Terraced Tea Plantation’s Micro-Topographical Units. Agriculture. 2025; 15(11):1150. https://doi.org/10.3390/agriculture15111150

Chicago/Turabian Style

Li, Yangxin, Le Sun, Jialin Zhang, Hongxue Zhao, Tejia Su, Wenhui Li, Linkun Wu, Pumo Cai, Christopher Rensing, Yuanping Li, and et al. 2025. "Tea Plant/Ophiopogon japonicus Intercropping Drives the Reshaping of Soil Microbial Communities in Terraced Tea Plantation’s Micro-Topographical Units" Agriculture 15, no. 11: 1150. https://doi.org/10.3390/agriculture15111150

APA Style

Li, Y., Sun, L., Zhang, J., Zhao, H., Su, T., Li, W., Wu, L., Cai, P., Rensing, C., Li, Y., Zhang, J., Wang, F., & Li, Q. (2025). Tea Plant/Ophiopogon japonicus Intercropping Drives the Reshaping of Soil Microbial Communities in Terraced Tea Plantation’s Micro-Topographical Units. Agriculture, 15(11), 1150. https://doi.org/10.3390/agriculture15111150

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