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Article

Mechanisms of Cultivation Chronosequence on Distribution Characteristics of Arbuscular Mycorrhizal Fungi in Tea Plantations, South Henan, China

by
Xiangchao Cui
1,*,
Dongmeng Xu
1,
Shuping Huang
1,
Wei Wei
1,
Ge Ma
1,
Mengdi Li
1 and
Junhui Yan
1,2
1
Henan Key Laboratory for Synergistic Prevention of Water and Soil Environmental Pollution, School of Geographic Sciences, Xinyang Normal University, Xinyang 464000, China
2
North-South Transitional Zone Typical Vegetation Phenology Observation and Research Station of Henan Province, Xinyang Normal University, Xinyang 464000, China
*
Author to whom correspondence should be addressed.
Microbiol. Res. 2025, 16(8), 188; https://doi.org/10.3390/microbiolres16080188
Submission received: 30 June 2025 / Revised: 29 July 2025 / Accepted: 9 August 2025 / Published: 12 August 2025
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Abstract

The vital role of arbuscular mycorrhizal (AM) fungi in tea plant growth is well established; however, the mechanisms underlying how increasing cultivation chronosequence (CC) influences AM fungal distribution remain unclear. An investigation was conducted to investigate the temporal dynamics of AM fungal indices and soil properties across a 100-year tea CC (10-, 30-, 60-, and 100-year CC) in Xinyang Maojian tea (Camellia sinensis L.) plantations (Xinyang, Henan Province, China). Principal coordinate analysis was conducted to reveal the significant reorganization of AM fungal indices during early-to-mid stages (PCoA1: 89.2%, p < 0.05), with triphasic development. Mycorrhizal colonization (MC), hypha biomass (hypha), and spore density (SD) surged by 100% during 10–30 years; SD peaked at 60 years (164 spores g−1) before declining, while glomalin-related soil protein (GRSP) accumulated significantly only at 100 years (p < 0.05). Concurrently, soil acidification (pH decreased from 6.37 to 4.84) and phosphorus depletion (AP from 119.6 mg kg−1 to 32 mg kg−1) intensified by 60 years, contrasting with the significant accumulations of soil organic organisms (SOM) (from 10.6 g kg−1 to 36.4 g kg−1), electrical conductivity (EC) (from 0.019 to 0.050 mS·cm−1), and microaggregate accumulation (MAR) (from 25.8% to 40.3%) during the period. The linear regression model was performed to validate the significant effects (p < 0.05) of CC on the AM indices (MC, SD, hypha, and GRSP) and soil physiochemical characteristics (EC, moisture, and SOM). Variance partitioning attributed 97.4% of the total variation, while interactions among cultivation ages, nutrient characteristics (SOM and AP), and non-nutrient characteristics (pH, EC, moisture, and aggregates) accounted for 23.0%. To identify the driving factors of AM fungi indices, Pearson correlation and redundancy analysis (RDA) were performed, and EC (26.5%) and pH (20.9%) were identified as the paramount regulators of hyphal integrity and colonization efficiency. It was found that 60 years worked as a critical transition point for targeted interventions (e.g., organic amendments and pH buffering) to mitigate rhizosphere dysfunction and optimize mycorrhizal services in perennial monocultures.

1. Introduction

Arbuscular mycorrhizal (AM) fungi constitute one of the most vital soil microbial groups in terrestrial ecosystems, forming symbiotic associations with over 80% of vascular plant species [1]. This symbiosis profoundly enhances plant growth and ecosystem functionality through several key mechanisms: improved mineral nutrient uptake, particularly phosphorus (P) [2]; increased host plant drought resistance [3]; and enhanced soil aggregate stability through glomalin-related soil protein (GRSP) [4,5]. Furthermore, AM fungi significantly contribute to plant community succession and ecosystem restoration processes [6]. In mycorrhizal colonization (MC), hypha biomass (hypha) is the functional foundation, enhancing plant absorption of mineral nutrients and water and promoting the formation of soil aggregates [7], while spore density (SD) serves as an indicator of AM fungi growth status. MC, hypha, SD, and GRSP are commonly used to reflect the functioning conditions of AM fungi. In agricultural systems, soil management practices like fertilization, tillage, and crop rotation exert substantial influence on AM fungal colonization and functionality [8]. However, within perennial cropping systems, such as orchards and tea plantations, prolonged continuous cultivation drives complex alterations in soil microbial communities, including those of AM fungi [9].
Tea (Camellia sinensis L.) is a crucial economic crop in China, typically cultivated under long-term monoculture. The practice induces significant shifts in soil physiochemical properties, including a decline in pH, increased aluminum (Al) toxicity, accumulation of organic matter, and nutrient imbalances [10]. In addition, some tea plantations are located in hilly and mountainous areas with rugged topography and poor accessibility [11]; thus, smallholder tea farmers face limitations in fertilizer application, leading to further reductions in tea production. AM fungi have been reported to mitigate Al toxicity and its detrimental effects on growth and photosynthesis in plants like barley and lotus grown in acidic soils [12]. AM fungi extensively colonize tea roots, potentially aiding the host’s adaptation to acidic soil conditions and improving phosphorus use efficiency via their extensive hyphal networks [13,14]. Despite this potential benefit, the long-term cultivation of tea plants may negatively impact AM fungal communities, as progressive soil acidification, sustained chemical fertilizer application, and the accumulation of root exudates present significant stressors [15,16,17]. Current research on AM fungal dynamics in agricultural soils has predominantly centered on annual crops or short-term rotation systems [12,18,19]. In contrast, the perennial monoculture nature of tea plantations, coupled with their inherent acidic soil conditions, leads to reduced soil disturbance while imposing strong selective pressures on the resident soil microbiota [20,21]. Consequently, tea soils exhibit unique microbial dynamics [22,23]. It has been reported that the influence of varying cultivation ages (10–100 years) on overall soil fungal community composition and diversity is primarily linked to altered soil chemistry in Yunan Province, China [24]. The spatiotemporal variability of microbial communities also shifts with the soil heterogeneity and significant climatic specificity-induced variations in the microbial communities of tea plantation soils [25]. Thus, the specific dynamics of AM fungal colonization and sporulation across these different tea cultivation ages remain poorly characterized.
Moreover, the distribution and functioning of AM fungi are not dictated solely by cultivation ages. Key environmental and management factors, such as altitude, climate, soil type, fertilization, and mulching, also modulate them significantly [26]. For instance, prolonged application of chemical P-fertilizers (especially phosphorus and nitrogen) can suppress AM fungal abundance, while elevated CO2 levels may enhance it [27]. Therefore, understanding of AM fungal dynamical shifts within long-term tea cultivation necessitates the integration of analyses focusing on soil physicochemical properties alongside these critical environmental variables.
Based on the vital role of MC, SD, hypha, and GRSP in the function of AM fungi, these four indices were chosen to characterize their distribution patterns in tea plantations with different CCs. Principal component analysis (PCA) was performed to assess whether AM fungal characteristics varied significantly across different cultivation ages. Based on the AM fungal indices and soil physicochemical properties, the linear regression model was chosen to validate the significant effects of CC on AM fungi and soil properties. Then, variation partitioning analysis (VPA), Pearson correlation, and redundancy analysis (RDA) were conducted to quantitatively assess the relative contributions of cultivation ages, environmental factors, and soil properties to the observed variability in AM fungal characteristics. Our findings aim to provide novel insights into the long-term impacts of agricultural practices on soil microbial characteristics and offer scientific guidance for the sustainable management of tea plantations.

2. Materials and Methods

2.1. Study Site

This study was conducted in Tianpu Town, Xinxian County, Xinyang City, Henan Province, China (31°29′ N, 114°59′ E; Figure 1), which is well known as the main production region of one of China’s top ten famous teas—Xinyang Maojian. The area features hilly terrain with an average elevation of 350 m, situated in a transitional climatic zone between northern subtropical and warm temperate regions. The mean annual temperature is approximately 15 °C, with annual precipitation averaging 1200 mm [28]. The meteorological data was obtained from the local weather bureau and is displayed in Table S1. The soil is identified as red soil, categorized under the Ferrisols order (Typic Hapli-Ferrisols) in the Chinese Soil Taxonomy, with diagnostic properties including a well-developed argic horizon (clay content > 30%), low base saturation (<30%), and acidity (pH 4.0~6.5). Due to rugged topography and poor accessibility in hilly and mountainous tea-growing regions, it is difficult for the local tea farmers to apply fertilizers. As a result, tea plantations with different CCs exhibit significant differences, providing an excellent platform for this study.

2.2. Experimental Design and Soil Sampling

The investigation was conducted in April 2017. Before the investigation, information on tea plantations with different CCs was acquired through local tea plantation owners. Four tea plantation cultivation ages were chosen for investigation: 10 years (10a), 30 years (30a), 60 years (60a), and 100 years (100a). The sampling sites are located on the same hill, thus reducing the interference of other environmental factors. The altitude and temperature information of the sampling sites is displayed in Table 1. Since the tea plantations are distributed from the base to the top of the same hill, the precipitation data is not different, so only total precipitation is provided in Table S1. The tea plants were planted with a 45~50 cm interval in 10a tea plantations, a 1 m interval in the 30a and 60a tea plantations, and a 1.5 m interval in 100a tea plantations. At each study site, rhizosphere soil sampling was conducted using a spatially randomized distribution pattern, with three replicate plots (5 m × 5 m) established in each study site. After removing the 0~5 cm topsoil to eliminate interference from external environmental factors, five subsamples (5~15 cm depth) per plot were collected diagonally within each plot using a stainless-steel auger (with a 5 cm diameter). Subsamples from the same plot were homogenized and brought back to the laboratory for analysis. The root samples, consisting of fine tender tea roots (1~2 mm diameter, 1~1.5 cm length), were randomly collected from the corresponding soil sampling pots, placed in plastic embedded boxes (Jiangsu CITOTEST Experimental Equipment Co., Ltd., Nanjing, China), and transported to the laboratory. A total of 12 composite samples (4 plantations × 3 replicates) were obtained for further analysis.
Microbiolres 16 00188 g001
Figure 1. The geographic location of the study area and soil sampling sites. A: tea plantations with 10 years of cultivation; B: tea plantations with 30 years of cultivation; C: tea plantations with 60 years of cultivation; D: tea plantations with 100 years of cultivation.
Figure 1. The geographic location of the study area and soil sampling sites. A: tea plantations with 10 years of cultivation; B: tea plantations with 30 years of cultivation; C: tea plantations with 60 years of cultivation; D: tea plantations with 100 years of cultivation.
Microbiolres 16 00188 g001
Table 1. The information of the sampling sites.
Table 1. The information of the sampling sites.
Sampling SitesElevation (m)Average Temperature (°C)
10a Tea Age15119.0
30a Tea Age26118.5
60a Tea Age30817.9
100a Tea Age27618.3

2.3. AM Fungal Indices

AM fungal spore density (SD) was determined using fresh soil by the wet sieving and decanting method [29]. AM fungal colonization rate (MC) was assessed using the sampling roots by staining root segments with Trypan blue (Shanghai Yuanye Bio-Technology Co., Ltd., Shanghai, China) and quantifying the frequency of colonization via the grid-line intersect method [30,31]. Hyphal biomass (hypha) was quantified using fresh soils by subjecting hyphae to water immersion for dispersion, followed by collection via microporous membrane filtration under suction; the collected material was subsequently oven-dried and weighed using an analytical balance with a precision of 0.01 mg [32]. The easily extractable GRSP content, which is secreted by AM fungi and functions in improving soil aggregates [4], was determined using dry soils by the Coomassie Brilliant Blue G-250 (Shanghai Macklin Biochemical Co., Ltd., Shanghai, China) method [33].

2.4. Soil Physicochemical Properties

Soil pH was measured potentiometrically in a soil–water suspension (1:2.5 w/w) [34], while soil electrical conductivity (EC) was determined in a soil–water suspension at a 1:5 (w/w) ratio, both with measurements conducted after 30 min of equilibration [35]. The soil gravimetric water content (moisture) was determined by mass loss after oven-drying at 105 °C until constant weight (±0.01 g) [36]. For soil aggregate fractionation, samples of 50 g dry soil were first sieved through an 8 mm sieve; macroaggregates (>0.25 mm, MaAR) and microaggregates (<0.25 mm, MAR) were subsequently separated by wet-sieving through a 0.25 mm sieve [37]. Soil available phosphorus contents in bulk soils (AP) and microaggregates (MAP) were extracted using the Bray-I method (0.03 mol·L−1 NH4F + 0.025 mol·L−1 HCl) (Nanjing Chemical Reagent Co., Ltd., Nanjing, China) and quantified via molybdenum–antimony colorimetry [36]. Soil organic matter contents in bulk soils (SOM) and microaggregates (MSOM) were quantified using the potassium dichromate (K2Cr2O7) (Nanjing Chemical Reagent Co., Ltd., China) oxidation method [36].

2.5. Data Analysis

Statistical analyses and graphical representations were performed using Origin 2021 to visualize AM fungal parameters and soil physicochemical properties. Significant differences among groups were evaluated using Duncan’s multiple range test (p < 0.05) in IBM SPSS Statistics 21.0. Analyses of driving mechanisms were conducted in R version 4.4.1 (https://cran.r-project.org/, accessed on 15 June 2024). The linear regression model was conducted using the ggpmisc package version 0.6.1 (https://github.com/aphalo/ggpmisc, accessed on 14 September 2024), and the scatter plots were drawn using the ggplot2 package version 3.5.2 (https://ggplot2.tidyverse.org/, accessed on 9 April 2025). Principal coordinate analysis (PCoA), redundancy analysis (RDA), and variance partitioning analysis (VPA) were performed using the vegan package version 2.6-8 (https://vegandevs.github.io/vegan/, accessed on 28 August 2024). The significance of PCoA results was assessed via permutational multivariate analysis of variance (PERMANOVA) within vegan. Pearson correlation analyses were implemented using the corrplot package version 0.95 (https://github.com/taiyun/corrplot, accessed on 14 October 2024). Variance partitioning of the RDA results was computed using the rdacca.hp package version 1.1-1 (https://github.com/laijiangshan/rdacca.hp, 24 August 2024).

3. Results

3.1. Distribution of AM Fungal Indices Under Different Tea Cultivation Chronosequences

PCoA was conducted to explore the distribution of AM fungal indices (Figure 2). The first two principal coordinates (PCoA1: 89.2% and PCoA2: 8.4%) explained 97.6% of the total variance. The ordination plot revealed that AM fungal indices of 10a, 30a, and 60a were significantly segregated from one another (p < 0.05). However, the indices of 30a and 100a plantations showed no significant distributional difference.
AM fungal indices, including MC, SD, hypha, and GRSP, in tea plantations across different tea cultivation ages are presented in Figure 3. MC, SD, and hypha in ten years of tea plantations (10a) were 36%, 92 g kg−1, and 44.3 n g−1 dry soil, respectively. All three indices in 30a exhibited significant increases (p < 0.05) compared to 10a, reaching values of 72% (MC), 164 g kg−1 (SD), and 77.7 n g−1 dry soil (hypha). MC and hypha showed no significant differences between 30a, 60a, and 100a. In contrast, SD continued to increase significantly (p < 0.05), peaking at 60 years and remaining significantly higher than 30a. GRSP contents were consistently higher in the 30a, 60a, and 100a soils compared to the 10a baseline (0.281 mg g−1 dry soil), with the increase becoming statistically significant (p < 0.05) only in the 100a soil.

3.2. Soil Physiochemical Characteristics Under Different Tea Cultivation Chronosequences

Soil physiochemical characteristics, including pH, EC, moisture, SOM, MSOM, AP, and MAP across different tea cultivation chronosequences, are presented in Table 2 and Figure 4. Compared to 10a (pH: 6.36; AP: 119.6 mg g−1 dry soil; MAP: 190.3 mg g−1 dry soil), significant decreases (p < 0.05) in soil pH, AP, and MAP contents were observed in both 30a and 60a sites. Conversely, the contents of moisture, SOM, and MSOM exhibited significant increases (p < 0.05) from initial 10a values (9.3%, 10.6 g kg−1, and 11.8 g kg−1) to 13~17.3%, 24.7~36.4%, and 23.4~36.0% by 60a, respectively. Concurrently, EC and MAR rose significantly (p < 0.05) from 0.0193 mS cm−1 and 25.8% (10a) to 0.0500 mS cm−1 and 40.3% (60a). In 100a plantations, EC, moisture, SOM, and MSOM were significantly elevated (p < 0.05) relative to 10a, whereas AP and MAP remained suppressed (p < 0.05).
Collectively, these shifts demonstrate consistent declining trends for pH and AP with increasing cultivation age, contrasting with increasing trajectories for EC, moisture, MAR, and SOM. Notably, the reverse occurred between the 60–100a and 30–60a phases for pH, EC, MAP, and MOM, indicating divergent responses during late-stage cultivation.

3.3. Linear Regression Analysis of Cultivation Chronosequence with AM Fungal Indices and Soil Physiochemical Characteristics

Linear regression analysis was employed to quantify the relationships between CC and AM fungal parameters as well as selected soil physicochemical properties. The results revealed distinct patterns of association. (Figure 5).
Regarding AM fungal indicators, CC exhibited significant positive correlations with all measured parameters (MC: R2 = 0.41, p < 0.05; hypha: R2 = 0.33, p < 0.05; SD: R2 = 0.54, p < 0.05; GRSP: R2 = 0.52, p < 0.05). The results indicate that AM fungi are significantly and positively influenced by cultivation ages.
The results of soil properties showed a more complex relationship with CC. Significant positive correlations were observed for soil EC (R2 = 0.43, p < 0.05), moisture (R2 = 0.38, p < 0.05), SOM (R2 = 0.65, p < 0.05), and MSOM (R2 = 0.57, p < 0.05). In contrast, no significant correlations were found between CC and soil pH (R2 = 0.05, p > 0.05), MAR (R2 = 0.12, p > 0.05), AP (R2 = 0.12, p > 0.05), or MAP (R2 = 0.20, p > 0.05). It is suggested that CC has a significant correlation with soil EC, moisture, and SOM.

3.4. Variance Partitioning Analysis (VPA) of AM Fungal Indices and Environmental Factors

VPA of the environmental factors for AM fungal indices identified tea cultivation age (EV1), soil nutrient characteristics (EV2: SOM, MSOM, AP, and MAP), and non-nutrient characteristics (EV3: pH, EC, moisture, and MAR) as primary predictor groups, collectively explaining 97.4% of the total variation (Figure 6). Independent contributions of these factors were quantified as 0% for EV1, 1.2% for EV2, and 22.3% for EV3. Interactions between predictor groups explained substantial additional variation: EV2 and EV3 jointly contributed 46.2%, while the three-way interaction among EV1, EV2, and EV3 accounted for 23.0%. Notably, interactions involving EV1 specifically explained 4.8% (EV1–EV3) and 0% (EV1–EV2) of the variance.

3.5. Pearson Correlation and Redundancy Analysis (RDA) of AM Fungal Indices and Soil Physiochemical Characteristics

Pearson correlation analysis identified significant relationships between AM fungal indices and soil physiochemical characteristics (Figure 7). MC, SD, and hypha exhibited negative correlations with AP and MAP (p < 0.05) but positive correlations with moisture, SOM, and MSOM (p < 0.05). Specifically, SD additionally correlated with MAR and EC, while hypha showed a positive correlation with EC (p < 0.05). Easily extractable GRSP correlated solely with SOM (p < 0.05).
Redundancy analysis (RDA) with hierarchical partitioning (HP) revealed that tea cultivation chronosequence influenced AM fungal dynamics predominantly through physiochemical properties—EC (26.5%), pH (20.9%), moisture (16.7%), and MSOM (15.9%)—collectively explaining the observed variance (Figure 8 and Table 3). Notably, moisture and MSOM were identified as primary drivers for MC, whereas EC, moisture, and MSOM governed hypha, and EC, pH, moisture, and MSOM shaped SD. SOM alone primarily controlled GRSP variation.

4. Discussion

The distinct shifts in AM fungal indices along with the cultivation durations revealed by PCoA (Figure 2) demonstrate significant reorganization of AM fungi during early-to-mid tea cultivation stages. The pronounced spatial segregation between 10-, 30-, and 60-year plantations (p < 0.05) aligns with documented succession patterns in perennial agroecosystems, where prolonged monoculture drives directional selection in soil microbiota [38,39].
It has been reported that as the cultivation or stand age increases, microbiological characteristics are affected by nutrient availability due to different quantities and qualities of litter and root inputs [40,41,42]. The trajectory of AM fungal development in our study is consistent with previous research on Xanthoceras sorbifolium plantations. The initial establishment phase (≤10 years) was characterized by low colonization and sporulation, consistent with immature symbiosis in newly planted perennials [39,43]. The rapid proliferation phase (10–30 years) showed significant increases (p < 0.05) in MC (from 36% to 72%), SD (from 92 to 164 spores g−1), and hyphal biomass (from 44.3 to 77.7 ng g−1), likely driven by root system maturation, which enhanced host carbon allocation to fungal partners [44]. From 10 to 60 years, as tea cultivation age increased, soil acidization, characterized by the decline in soil pH, increased aluminum toxicity [45], and nutrient imbalance [46], enhanced the dependence of tea plants on AM fungi, as reflected by a gradual increase in the MC, hypha, and SD of AM fungi. At 100-year CC, SD of AM fungi decreased. This may indicate the decreased dependence of tea on AM fungi, caused by the rise of pH value in 100-year CC, which alleviated the aluminum toxicity and increased AP. Spore density may indicate a more sensitive response to environmental changes [47]. Notably, GRSP significantly increased only at 100 years (p < 0.05), underscoring glomalin’s role as a recalcitrant carbon pool that integrates long-term fungal activity [33], progressively contributing to soil structural stability in aging plantations.
Based on the documented soil physicochemical shifts along the chronosequence, our findings demonstrate that prolonged tea cultivation drives a fundamental reorganization of soil properties, characterized by progressive acidification (pH decline from 6.36 to ~5.2 by 60a) and phosphorus depletion (AP reduction from 119.6 to ~50 mg kg−1), consistent with rhizosphere-driven mineral weathering and tea-specific nutrient demands [48]. Concurrently, the significant accumulation of SOM and MSOM by 60a reflects tea-primed carbon sequestration through root exudation and litter deposition [49]. The observed reversal in pH and MSOM trajectories at late stages (60–100a) suggests destabilization of the soil characteristics when exceeding critical cultivation thresholds.
The strong positive correlations observed from the linear regression analysis between CC and all measured AM fungal parameters (MC, hypha, SD, and GRSP) underscore the cumulative, beneficial effect of extended tea monoculture on AM fungal development and activity within the rhizosphere. This suggests that, despite potential soil degradation pressures like acidification and phosphorus depletion as noted earlier, the AM symbiosis remains robust and even intensifies over decades. Conversely, the selective influence of CC on soil properties is striking. While CC significantly drives the accumulation of organic matter (SOM and MSOM) and increases moisture and EC, it exhibits no significant relationship with soil pH, MAR, or phosphorus availability (AP and MAP). This dichotomy highlights that long-term tea cultivation primarily shapes the soil environment through organic enrichment and associated physical/hydrological changes (EC and moisture) [50] rather than directly altering pH or P status, which appear to be governed by other factors or processes not linearly dependent on cultivation age alone. This reinforces the complex interplay between chronosequence, soil conditioning, and AM fungal dynamics.
The VPA results reveal that the dynamics of AM fungal characteristics are predominantly governed by synergistic interactions between cultivation age and soil properties, with non-nutrient factors (pH/EC/moisture/MAR) contributing the highest independent explanatory power (22.3%). Crucially, the negligible direct effect of cultivation age (EV1: 0%) coupled with its substantial interaction effects with soil nutrients (EV1 × EV2 × EV3: 23.0%) demonstrates that chronosequence impacts operate primarily through physicochemical mediation—a pattern aligned with pedogenic threshold theory, where long-term monoculture alters edaphic filters, which subsequently reshape microbial niches [51]. It was found that AM fungal shifts from CC were mainly due to changes in soil physicochemical properties over CC [52]. The dominance of EV2–EV3 interactions (46.2%) further underscores that carbon–nutrient stoichiometry and ionic balance jointly create deterministic selection pressures on AM fungi.
Strong negative correlations between AP/MAP and MC/SD/hypha (p < 0.05) reflect phosphorus limitation-driven AM fungal adaptation, where host carbon allocation to symbionts increases under P scarcity—consistent with the trade-off between direct P uptake and mycorrhizal P acquisition pathways [2]. Conversely, positive correlations with SOM/MSOM indicate fungal dependence on organic matter for hyphal network development, as validated by RDA showing MSOM’s primacy in explaining MC (15.9%) and hypha (15.9%) variances. The unique association of GRSP solely with SOM confirms glomalin’s origin as a fungal-derived carbon polymer whose accumulation requires substantial organic substrates [33].
RDA-HP quantifies the hierarchical control of physicochemical factors. EC (26.5%) and pH (20.9%) emerge as paramount regulators, likely through modulating ionic toxicity and aluminum mobility in acidic tea soils [53]. Moisture (16.7%) and MSOM (15.9%) constitute secondary drivers by mediating oxygen diffusion and carbon accessibility. This cascade explains SD’s sensitivity to EC/pH (hyphal integrity) versus MC’s reliance on moisture/MSOM (colonization efficiency), ultimately proving that tea cultivation age acts as a chronosequence proxy by integrating these physicochemical forces rather than acting as a direct biological driver. The findings in this research identify the critical transition point (60-year) in long-term tea plantation. Targeted interventions—such as organic amendments and pH buffering—can mitigate rhizosphere dysfunction at this stage for sustainable tea cultivation management. Such practices optimize mycorrhizal ecosystem services while advancing precision agriculture in perennial monocultures under global change.

5. Conclusions

This century-scale chronosequence study (10, 30, 60, and 100 years of tea plantations) integrated with multivariate statistics reveals that tea cultivation age positively drives the reorganization of AM fungal distributions. MC and hypha peaked at 30 years (72%, 77.7 n g−1), while SD peaked at 60 years (164 spores g−1) before declining due to aluminum toxicity and phosphorus depletion. Soils exhibited progressive acidification (pH: from 6.37 to 4.84) and phosphorus depletion (AP: from 119.6 to 32 mg kg−1), alongside increased SOM (from 10.6 to 36.4 g kg−1) and EC (from 0.019 to 0.050 mS cm−1) at 60 years. Linear regression analysis validated the significantly positive effects (p < 0.05) of CC on the AM indices (MC, SD, hypha, and GRSP) and the comprehensive effects of CC on soil physiochemical characteristics (EC, moisture, and SOM). VPA and RDA results also confirmed non-nutrient factors (pH/EC/moisture) as primary drivers, contributing 22.3% independent explanatory power, with EC (26.5%) and pH (20.9%) governing hyphal networks. SD significantly correlated with MAR (p < 0.05). The 60-year critical threshold (pH < 5.2, phosphorus occlusion) triggered rhizosphere functional shifts, providing an empirical basis for precision tea plantation management.

Supplementary Materials

The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/microbiolres16080188/s1, Table S1: The specific meteorological data in the study area during 2016~2017.

Author Contributions

Conceptualization, X.C.; methodology, X.C. and D.X.; software, X.C. and D.X.; validation, X.C. and D.X.; formal analysis, D.X. and X.C.; investigation, X.C. and S.H.; resources, W.W., G.M., M.L. and J.Y.; data curation, X.C., D.X. and S.H.; writing—original draft preparation, X.C.; writing—review and editing, X.C. and D.X.; visualization, D.X.; supervision, X.C.; project administration, X.C.; funding acquisition, X.C., S.H. and J.Y. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the National Natural Science Foundation of China (grant number 41807038), the Natural Science Foundation of Henan (grant number 232300420444), and the Soft Science Research Program of Henan (grant number 252400411087).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Data are contained within the article.

Acknowledgments

We are grateful to Leilei Jiang and Rui Wang for their support in the study.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

The following abbreviations are used in this manuscript:
CCCultivation chronosequence
MCMycorrhizal colonization of AM fungi
SDAM fungal spore density
HyphaHypha biomass of AM fungi
GRSPGlomalin-related soil protein
pHSoil pH
ECSoil electrical conductivity
MoistureSoil gravimetric water content
MARSoil microaggregates
APSoil available phosphorus contents in bulk soils
MAPSoil available phosphorus contents in the microaggregates
SOMSoil organic matter contents in bulk soils
MSOMSoil organic matter contents in the microaggregates.
SVStandard value
PCoAPrincipal coordinate analysis
PERMANOVAPermutational multivariate analysis of variance
HPHierarchical partitioning
RDARedundancy analysis
VPAVariance partitioning analysis

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Figure 2. The principal coordinate analysis (PCoA) of AM fungi indices in tea plantations with different cultivation chronosequences. 10a: tea plantations with 10 years of cultivation; 30a: tea plantations with 30 years of cultivation; 60a: tea plantations with 60 years of cultivation; 100a: tea plantations with 100 years of cultivation. The same below.
Figure 2. The principal coordinate analysis (PCoA) of AM fungi indices in tea plantations with different cultivation chronosequences. 10a: tea plantations with 10 years of cultivation; 30a: tea plantations with 30 years of cultivation; 60a: tea plantations with 60 years of cultivation; 100a: tea plantations with 100 years of cultivation. The same below.
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Figure 3. (a) The mycorrhizal colonization (MC) and spore density (SD) of AM fungi in tea plantations with different cultivation chronosequences (CCs). (b) The hypha biomass (hypha) and glomalin-related soil protein (GRSP) content of AM fungi in tea plantations with different CCs. Different letters mean significance at the 0.05 level.
Figure 3. (a) The mycorrhizal colonization (MC) and spore density (SD) of AM fungi in tea plantations with different cultivation chronosequences (CCs). (b) The hypha biomass (hypha) and glomalin-related soil protein (GRSP) content of AM fungi in tea plantations with different CCs. Different letters mean significance at the 0.05 level.
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Figure 4. (a) Soil pH and electrical conductivity (EC) in tea plantations with different cultivation chronosequences (CCs). (b) The soil gravimetric water content (moisture) and soil microaggregates (MAR) in tea plantations with different CCs. (c) Soil available phosphorus contents in bulk soils (AP) and microaggregates (MAP) of tea plantations with different CCs. (d) Soil organic matter contents in bulk soils (SOM) and microaggregates (MSOM) of tea plantations with different CCs. Different letters mean significance at the 0.05 level.
Figure 4. (a) Soil pH and electrical conductivity (EC) in tea plantations with different cultivation chronosequences (CCs). (b) The soil gravimetric water content (moisture) and soil microaggregates (MAR) in tea plantations with different CCs. (c) Soil available phosphorus contents in bulk soils (AP) and microaggregates (MAP) of tea plantations with different CCs. (d) Soil organic matter contents in bulk soils (SOM) and microaggregates (MSOM) of tea plantations with different CCs. Different letters mean significance at the 0.05 level.
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Figure 5. (a) Linear regression analysis of mycorrhizal colonization (MC) and cultivation chronosequence (CC). (b) Linear regression analysis of spore density (SD) and CC. (c) Linear regression analysis of hypha biomass (hypha) and CC. (d) Linear regression analysis of glomalin-related soil protein (GRSP) and CC. (e) Linear regression analysis of soil pH and CC. (f) Linear regression analysis of electrical conductivity (EC) and CC. (g) Linear regression analysis of soil gravimetric water content (moisture) and CC. (h) Linear regression analysis of soil microaggregates (MAR) and CC. (i) Linear regression analysis of soil organic matter contents in bulk soils (SOM) and CC. (j) Linear regression analysis of microaggregates (MSOM) and CC. (k) Linear regression analysis of soil available phosphorus contents in bulk soils (AP) and CC. (l) Linear regression analysis of microaggregates (MAP) and CC. The x-axis represents the value of CC, and the y-axis represents the standardized values (SVs) of AM fungal indices and soil physicochemical characteristics.
Figure 5. (a) Linear regression analysis of mycorrhizal colonization (MC) and cultivation chronosequence (CC). (b) Linear regression analysis of spore density (SD) and CC. (c) Linear regression analysis of hypha biomass (hypha) and CC. (d) Linear regression analysis of glomalin-related soil protein (GRSP) and CC. (e) Linear regression analysis of soil pH and CC. (f) Linear regression analysis of electrical conductivity (EC) and CC. (g) Linear regression analysis of soil gravimetric water content (moisture) and CC. (h) Linear regression analysis of soil microaggregates (MAR) and CC. (i) Linear regression analysis of soil organic matter contents in bulk soils (SOM) and CC. (j) Linear regression analysis of microaggregates (MSOM) and CC. (k) Linear regression analysis of soil available phosphorus contents in bulk soils (AP) and CC. (l) Linear regression analysis of microaggregates (MAP) and CC. The x-axis represents the value of CC, and the y-axis represents the standardized values (SVs) of AM fungal indices and soil physicochemical characteristics.
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Figure 6. The variance partitioning analysis (VPA) of environmental factors on AM fungal indices in tea plantations with different cultivation chronosequences. Tea cultivation ages: 10, 30, 60, and 100 years of tea cultivation; nutrient characteristics, EC, SOM, MSOM, AP, and MAP; non-nutrient characteristics, pH, moisture, and MAR.
Figure 6. The variance partitioning analysis (VPA) of environmental factors on AM fungal indices in tea plantations with different cultivation chronosequences. Tea cultivation ages: 10, 30, 60, and 100 years of tea cultivation; nutrient characteristics, EC, SOM, MSOM, AP, and MAP; non-nutrient characteristics, pH, moisture, and MAR.
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Figure 7. The Pearson correlation of AM fungal indices and soil physiochemical characteristics of tea plantations with different cultivation ages. * Significance at the 0.05 level; ** significance at the 0.01 level.
Figure 7. The Pearson correlation of AM fungal indices and soil physiochemical characteristics of tea plantations with different cultivation ages. * Significance at the 0.05 level; ** significance at the 0.01 level.
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Figure 8. The redundancy analysis (RDA) plots of AM fungal indices with soil physiochemical characteristics in tea plantations with different cultivation chronosequences.
Figure 8. The redundancy analysis (RDA) plots of AM fungal indices with soil physiochemical characteristics in tea plantations with different cultivation chronosequences.
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Table 2. Soil physiochemical characteristics of different samples under different cultivation chronosequences.
Table 2. Soil physiochemical characteristics of different samples under different cultivation chronosequences.
SamplespHEC
/mS cm−1		Moisture
/%		MAR
/%		SOM
/g kg−1		MSOM
/g kg−1		AP
/mg kg−1		MAP
/mg kg−1
10a6.320.0209.426.510.310.8114.0170.0
10a6.410.0239.325.210.612.8136.8210.6
10a6.370.0159.225.810.911.8108.2190.3
30a6.040.02317.330.424.723.450.073.9
30a5.860.02617.628.723.924.230.127.8
30a5.780.02017.032.225.622.727.750.9
60a4.860.04912.435.339.636.024.611.9
60a4.910.05113.445.334.032.121.736.2
60a4.740.05013.440.335.740.049.960.4
100a6.340.03931.439.933.534.565.889.4
100a5.930.03729.028.932.827.056.862.8
100a6.140.03430.250.933.230.883.8116.0
Table 3. The hierarchical partitioning (HP) results of the redundancy analysis (RDA) on AM fungal indices.
Table 3. The hierarchical partitioning (HP) results of the redundancy analysis (RDA) on AM fungal indices.
Soil Physicochemical PropertiesUniqueAverage ShareIndividualIndividual Percentage (%)R2p-Valuepadj-Value
EC0.0850.1410.22626.50.8800.0010.003
pH0.0120.1660.17820.90.7780.0030.005
Moisture0.0320.110.14216.70.9170.0010.003
MAR0.0560.080.13615.90.5850.0160.019
MSOM0.0410.0710.11213.10.8430.0020.004
MAP0.0010.0580.0670.5330.0400.040
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Cui, X.; Xu, D.; Huang, S.; Wei, W.; Ma, G.; Li, M.; Yan, J. Mechanisms of Cultivation Chronosequence on Distribution Characteristics of Arbuscular Mycorrhizal Fungi in Tea Plantations, South Henan, China. Microbiol. Res. 2025, 16, 188. https://doi.org/10.3390/microbiolres16080188

AMA Style

Cui X, Xu D, Huang S, Wei W, Ma G, Li M, Yan J. Mechanisms of Cultivation Chronosequence on Distribution Characteristics of Arbuscular Mycorrhizal Fungi in Tea Plantations, South Henan, China. Microbiology Research. 2025; 16(8):188. https://doi.org/10.3390/microbiolres16080188

Chicago/Turabian Style

Cui, Xiangchao, Dongmeng Xu, Shuping Huang, Wei Wei, Ge Ma, Mengdi Li, and Junhui Yan. 2025. "Mechanisms of Cultivation Chronosequence on Distribution Characteristics of Arbuscular Mycorrhizal Fungi in Tea Plantations, South Henan, China" Microbiology Research 16, no. 8: 188. https://doi.org/10.3390/microbiolres16080188

APA Style

Cui, X., Xu, D., Huang, S., Wei, W., Ma, G., Li, M., & Yan, J. (2025). Mechanisms of Cultivation Chronosequence on Distribution Characteristics of Arbuscular Mycorrhizal Fungi in Tea Plantations, South Henan, China. Microbiology Research, 16(8), 188. https://doi.org/10.3390/microbiolres16080188

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