The stabilizing effect of water-drought rotation on soil microbial communities: potential for resisting obstacles in continuous cropping

Introduction: Continuous soil monocropping typically disrupts microecological equilibrium, leading to reduced crop yield and quality degradation, whereas crop rotation often mitigates these issues. However, understanding of the microbial mechanism behind this rotation practice is still limited.

Methods: A three-year field experiment was conducted comparing tobacco continuous monocropping and tobacco-rice rotation. The bacterial community structure, assembly processes, and functional profiles were analyzed within three tobacco growing periods.

Results: While most soil physicochemical parameters, such as pH, total phosphorus, and available phosphorus, were not significantly different between the two systems, tobacco monoculture specifically resulted in elevated contents of total nitrogen and alkali-hydrolyzable nitrogen compared to tobacco-rice rotation systems. Although α-diversity also showed no significant differences between systems, bacterial community composition diverged significantly, with Proteobacteria, Acidobacteria, and Actinobacteria dominating. Deterministic processes governed community assembly, with βMNTD and βNTI exhibiting significant correlations with soil available nitrogen, phosphorus, potassium, and pH exclusively in the rotation system-contrasting sharply with the absence of such correlations in monoculture. Tobacco-rice rotation exhibited more complex co-occurrence networks anchored by 22 topological connector taxa than tobacco monocropping. Functionally, the rotation significantly suppressed nitrifying bacteria abundance, whereas monocropping enriched dark sulfide-oxidizing bacteria. Notably, despite the absence of significant overall differences in pathogen abundance between the two cropping systems, a high variation was observed of plant pathogen abundance in the vigorous growth stage of tobacco monocropping, which indicates that certain locations possess a considerably elevated susceptibility to potential disease epidemics.

Discussion: Compared to continuous monocropping, tobacco-rice rotation caused minimal shifts in soil α-diversity and physicochemical properties. However, our three years field study reveals that it profoundly restructured the composition and interaction networks of the soil bacterial community. This highlights the divergent impacts of cropping systems on the soil microbiome and indicates that the benefit of rotation may stem primarily from its ability to rewire microbial interactions, thereby alleviating continuous cropping obstacles.

GRAPHICAL ABSTRACT

Graphical Abstract. Crop rotation alleviates monocropping obstacles by remodeling soil microbial interaction networks.

1 Introduction

Increasing crop yield and quality sustainably is a crucial challenge for global agriculture. Intensive monoculture systems usually led to detrimental changes in soil chemical properties (Pérez-Brandán et al., 2014), reduced enzyme activity (Yan et al., 2012), accumulation of soil-borne diseases (Bai et al., 2015), and buildup of autotoxic substances (Zhan et al., 2004), which known as “continuous cropping obstacles”. A set of previous studies showed that crop rotation can significantly enhance soil microecology by boosting enzyme activity, increasing microbial diversity, and improving soil structure, all of which support long-term soil fertility (Feng et al., 2023; Liu et al., 2023). Moreover, rotation diversifies the root exudate profile, thereby disrupting pathogen life cycles and reducing the prevalence of specific soil−borne pathogens (Fang et al., 2016). It also promotes the accumulation of organic matter and improves nutrient cycling, leading to higher nutrient use efficiency and reduced reliance on synthetic fertilizers (Gaudin et al., 2015). The rotation approach is widely implemented in various agricultural systems, such as the wheat-rice rotation in South and East Asia and the corn-soybean rotation in North America (McDonald et al., 2022; Fu et al., 2025; Farmaha et al., 2016).

Soil microbes are essential to soil health and crop productivity based on the function in processes of soil organic matter turnover and nutrient cycling (van der Heijden et al., 2008; Paul, 2015). Crop rotation, as opposed to monoculture, can profoundly influence soil microbial communities, with impacts that vary based on crop types, cropping systems, and environmental conditions. For instance, legume-based rotations are known to enrich nitrogen-fixing bacteria, which can improve soil nitrogen levels and benefit subsequent crops (Drinkwater et al., 1998). In agricultural systems, fertilization and crop rotation usually combined to shape soil microbial communities and the finding often inconsistent (Bei et al., 2018; Wang et al., 2018; Xie et al., 2020). In upland rotation systems, fertilization practices usually had the more effects soil microbiome than crop rotation (Guo et al., 2020). Conversely, in upland-paddy rotation systems, the crop rotation stage has been shown to exert a greater influence on soil microbial communities than fertilization. This is primarily attributed to changes in soil moisture that occur during different crop stages (Wang et al., 2018). Despite the recognized importance of upland-paddy rotation in sustainable agriculture, there remains a need for more research to microbial community.

Shifts in a microbial community in the crop rotation are controlled by microbial assembly processes (Stegen et al., 2012). Deterministic processes arise from environmental filtering including both abiotic factors and biotic factors which directly shape species abundances and functional traits, whereas stochastic processes involve unpredictable events such as ecological drift such as ecological drift and dispersal (Dini-Andreote et al., 2015; Evans et al., 2017). Upland-paddy rotation fundamentally alters the selective pressures on the soil microbiome by modifying the soil’s physicochemical properties including pH, nutrient status, redox conditions and also by changing the quality of residue inputs, thereby redefining microbial ecological niches and creating a more diverse habitat (Zhang et al., 2025). Long−term field experiments have demonstrated that increasing the diversity of crop rotations can markedly shift bacterial community composition and enrich functional genes associated with disease suppression (e.g., the prnD gene) (Peralta et al., 2018). These studies indicate that crop diversity improves soil health not only from boosting overall microbial diversity which result the general suppression but also from altered microbe−microbe interactions. Previous study suggests that early in plant development, microbial communities are often governed by stochastic colonization, whereas deterministic selection becomes increasingly dominant as plants modify the soil environment (Bell et al., 2022). However, the drivers of short-term microbial assembly remain poorly understood, particularly in comparative farming systems. Specifically, how fluctuations in root exudates and nutrient availability across growth stages underpin assembly processes in monoculture versus crop rotation is unclear. Time-series analyses are therefore needed to elucidate the interconnections among cropping regime, plant growth stage and microbial assembly.

In this study, a three-year field experiment was conducted to compare tobacco monoculture, which leads to continuous cropping obstacles, with tobacco-rice rotation systems that can alleviate such issues. During the tobacco growing season, we assessed soil physicochemical properties, microbial diversity, and community structure along the plant growth stage using high-throughput sequencing, and examined the relationships among these variables. Our objectives were to (i) evaluate how the two cropping regimes affect soil nutrient dynamics and microbial communities, and (ii) identify key micro-ecological indicators associated with sustainable cropping. By comparing microbial assembly processes across different tobacco growth stages under both cropping systems, we aimed to find the microbial interaction drivers that alleviate the obstacles linked to monoculture. The results can provide new insights into how tobacco−rice rotation can overcome continuous-tobacco cropping challenges by modulating soil microbial assembly and metabolic functions.

2 Materials and methods article types

2.1 Experimental design and soil sampling

The field experiment was conducted on farmland in Chang Ning, Hunan Province, China (112°26′15″E, 26°17′24″N), which has a subtropical monsoon climate with an average annual temperature of 18.1°C and an average annual precipitation of 1440 mm. The field experiment included two treatment groups with the five replicates: an upland monoculture system focusing solely on tobacco and an upland-paddy rotation system that alternated between tobacco and rice. Prior to the experiment, the selected field had been continuously cultivated with rice. Considering the farming practical feasibility of the farming system, 200 m² (8 m×25 m) for each replicate was design for both tobacco monoculture and tobacco-rice rotation. A randomized design was employed to ensure that replicate sites within each treatment were not spatially clustered. We focus on tobacco primarily because this species exhibits significant continuous cropping obstacles, and farmers typically use tobacco-rice rotation to mitigate the negative impact of tobacco continuous cropping obstacles. The experiment was conducted for three years. In the third year of the experimental field, we collected the soil samples at the tobacco season in both tobacco monoculture and tobacco-rice rotation at three key growth stages: the root extension stage, the vigorous growth stage, and the maturity stage in April to June, 2023. A randomized ten-point sampling method was applied to each 200 m² plot to ensure consistent sampling and reduce variability. In each plot, ten soil cores were extracted to a depth of 20 cm using a 5 cm diameter auger, and the cores were then homogenized into a single composite soil sample. After sieved (2 mm sieve) to remove rocks and other debris, the soil separated into two subsamples. One subsample was frozen at -80°C for DNA analysis, another was air-dried at room temperature for determination of soil chemo-physical properties.

The tobacco variety Yunyan 87 was selected for our experiment. Tobacco seeds were surface-sterilized by for 10 minutes, thoroughly rinsed with clear water, air-dried, and subsequently germinated prior to sowing. Sowing was performed using the tobacco float seedling system. Transplanting was carried out at the 5–6 leaf stage at a spacing of 0.5 m × 1.2 m. Basal fertilizer application was performed 10–15 days prior to transplanting using a deep banding method. The basal fertilizer mixture comprised the following per 667 m²: 50 kg of fermented rapeseed cake fertilizer, 60 kg of specialized base fertilizer (N: P₂O₅:K₂O =8:10:11), and 10 kg of potassium magnesium sulfate fertilizer. The topdressing fertilizer was applied multiple times according to the nutrient requirements of tobacco. At the time of transplanting, fertilizer application was performed using a diluted solution of a 20:9:0 N: P₂O₅:K₂O compound at a dosage of 1 kg per 667 m². Approximately 7 days after transplanting, the fertilizer was reapplied at 4 kg/667m². During the vigorous growth stage: a specialized fertilizer (N:P₂O₅:K₂O=10:5:29) was applied at 35 kg/667m². Around 40 days after transplanting, an additional 25 kg/667m² of K₂SO₄ was applied. Sufficient soil moisture was maintained throughout the vegetative growth period and water supply was strictly controlled during the maturation stage to prevent accelerated leaf maturation and facilitate scheduled harvesting. All other agronomic practices were conducted in accordance with local standardized tobacco production protocols. In the rice season for tobacco-rice rotation, the rice variety Taiyou553 was selected for the study due to its high quality and suitability as a widely cultivated indica hybrid in this region. A total of 100 kg N ha^-1 was applied in a split ratio of 5:3:2 as basal, tiller, and heading fertilizers. Potassium was applied at 100 kg K₂O ha^-1, split equally between basal and heading applications. Phosphorus was applied as 30 kg P₂O₅ ha^-1 entirely in the basal fertilizer. The sources used were urea, potassium sulfate, and calcium superphosphate for N, P, and K fertilizers, respectively. The same fertilization and planting cycle was repeated in the next year. For the fallow period of the tobacco monoculture, no agricultural management practices were implemented.

2.2 Characterization of soil physico-chemical properties

Soil organic carbon (SOC) was assayed according to the Walkley-Black dichromate oxidation procedure (Page et al., 1982). Soil pH was measured in a 1: 2.5 (v/v) soil: water suspension with a digital pH meter (PHS-3C, Shanghai Lida Instrument Company, China). Soil available phosphorus (AP) was assayed according to the method described by Olsen et al. (1954). Soil available nitrogen (AN) was measured by the alkaline hydrolysis method (Cornfield, 1960). Soil total nitrogen was determined by Kjeldahl nitrogen method (Bradstreet, 1954). Soil total phosphorus was measured by the molybdenum blue methods after digestion by H₂SO₄ and HClO₄ (Olsen et al., 1954). Soil total potassium (K) was quantified by digesting the samples in a mixture of HF and HClO₄, and soil available K was measured via the neutral ammonium acetate extraction method (Bolland et al., 2002). Then the concentration of K was measured by Flare Photometer (M410, Sherwood Scientific Ltd., United Kingdom).

2.3 DNA extraction, Illumina, and data analysis PCR

Microbial DNA was extracted from 0.5 g soil samples using the MagPure Soil DNA LQ Kit (Magen, Shanghai, China) according to the manufacturer’s instructions. The quality and quantity of the extracted DNA were assessed using a NanoDrop 2000 spectrophotometer (Thermo Fisher Scientific, USA) and agarose gel electrophoresis. The DNA was then diluted to a concentration of 1 ng/μL for subsequent PCR amplification. The V3-V4 region of the 16S rRNA gene was amplified using Takara Ex Taq (Takara, Beijing, China) and barcoded primers 343F (5’-TACGGRAGGCAGCAG-3’) and 798R (5’-AGGGTATCTAATCCT-3’). The PCR amplification cycle consisted of an initial denaturation at 94°C for 5 minutes, followed by 30 cycles of 94°C for 30 seconds, 52°C for 30 seconds, and 72°C for 30 seconds, ending with a final extension at 72°C for 10 minutes. Amplicons were visualized via agarose gel electrophoresis and purified using Agencourt AMPure XP beads (Beckman Coulter, Pasadena, USA). After purification, the DNA was quantified using Qubit dsDNA assay kit (Yeasen, Shanghai, China). Equal amounts of purified DNA were pooled for sequencing on the NovaSeq 6000 platform (Illumina Inc, USA) at Shanghai OEbiotech (Shanghai, China).

High-throughput sequence analysis was performed using QIIME2 with the default parameters (Bolyen et al., 2019). Brief, raw paired-end reads were preprocessed using Cutadapt software to detect and cut off the adapter (Martin, 2011). The sequences were then subjected to quality filtering, denoising, merging, and chimera removal via the DADA2 plugin (Callahan et al., 2016). Sequences were clustered using the “dada2” algorithm to generate non-singleton amplicon sequence variants (ASVs) and taxonomy was assigned to ASVs using SILVA 16S database (version 12_8). Each soil bacterial 16S gene sequence was normalized to the same sequencing depth, with 9851 sequences per sample.

2.4 Statistical analysis

A two-way ANOVA was conducted to evaluate the effects of cropping patterns and sampling time, along with their interaction. One-way ANOVA was also applied to compere the difference between each treatment. To find the best discriminant microbial ASVs in the two planting systems, classification random forest analysis was applied by “randomForest” packages in R v3.4.3. The “NST,” “picante,” and “ggplot2” packages were used to calculate the βMNTD and βNTI values of the taxa in the cropping systems to evaluate the community assembly processes of different subgroups (Wang et al., 2024). A global co-occurrence network was firstly constructed based on interactions between genera with a relative abundance of at least 0.1% using Sparse Correlations for Compositional data (SparCC) (Friedman and Alm, 2012). The correlation coefficient threshold of 0.7 and a P−value cutoff of 0.05 were applied to retain only robust correlations. Then, the single−sample networks were extracted from this global network using the induced_subgraph function from the igraph package. The topological parameters of these single−sample networks were subsequently used to compare differences between the two planting systems. The co-occurrence network was visualized in Gephi (V0.92, https://gephi.org/). The keystone taxa (Network hubs, module hubs, and connectors) in the network were identified with z-score and c-score (Li et al., 2024). The FAPROTAX was used to predict ASVs function (Xiao et al., 2025). LEfSe analysis (LDA Effect Size) was performed to identify functional microbial taxa that exhibited significant differences between the two cropping systems (Ma et al., 2023). Spearman correlations were used to estimate the relationships between the top 20 ASVs, βMNTD and βNTI of bacterial community in two farming systems, network module, network connector, functional bacteria and the environmental variables. When the data (including α-diversity, βMNTD, βNTI, and network parameters) met the assumptions of normality and homoscedasticity, one-way ANOVA employed to assess statistical significance between the two planting systems. Otherwise, the Kruskal-Wallis test along with the KwWlx2 function in the “EasyStat” package were used to evaluate overall and pairwise differences. The principal coordinates analysis (PCoA) was used to analyze the differences in bacterial community β-diversity and functional bacterial community β-diversity between the two cropping models. “tidyverse” (v2.0.0) package was used to analyze relative abundance of soil bacteria in the tobacco monoculture system and the tobacco-rice rotation system at the phylum level. Mantel test was used to analysis the influence of soil physicochemical properties on bacterial community, bacterial functions, and bacterial diversity.

3 Results

3.1 Physicochemical properties

The results demonstrated that in the tobacco monoculture system, sampling time had a significant effect on soil available potassium and soil organic matter, but no significant impact on other soil properties. In contrast, under the tobacco-rice rotation system, sampling time significantly influenced soil total nitrogen and soil available potassium, while showing no significant effects on the other soil properties. Furthermore, the cropping pattern significantly affected soil total nitrogen, hydrolyzable nitrogen, available phosphorus, pH, and soil organic matter (Figures 1A–H). However, the interaction between sampling time and cropping pattern did not exert a significant influence on any of the eight soil properties examined (Figure 1).

Figure 1

Figure 1. Effects of cropping patterns and sampling time on soil physicochemical properties including total nitrogen (A), total phosphorus (B), total potassium (C), hydrolyzable nitrogen (D), available phosphorus (E), available potassium (F), pH (G) and soil organic matter (H). A two-way ANOVA was conducted to evaluate the effects of cropping patterns and sampling time, along with their interaction. One-way ANOVA was also applied to compere the difference between each treatment. Data are presented as mean ± standard deviation (n=5). The F-value and P-value indicate significant differences. T represents tobacco monoculture and TR represents tobacco-rice rotation.

3.2 Diversity and structure of soil bacterial community

Soil bacterial alpha diversity including richness, Shannon index and Chao1 index generally showed that there is no significant difference between monoculture and cropping rotation system (Figures 2A–C). The results showed these dominant ASVs were mainly affiliated within phyla Proteobacteria, Acidobacteria, and Actinobacteria, with a relative abundance of 38-42%, 31-34% and 18-23%. The Proteobacteria contain the largest number of ASVs which was classified to seven families. We found significant difference in bacterial community using ASVs profiling between tobacco monoculture system and tobacco-rice rotation based on Anosim analysis (R = 0.459; P = 0.001) (Figure 2D). The results showed these dominant ASVs were mainly affiliated within phyla Proteobacteria, Acidobacteria, and Actinobacteria, with a relative abundance of 38-42%, 31-34% and 18-23% (Figures 2E–F). The random forest model identified the ASV380, ASV129 and ASV116 were the most important species for the bacterial community (Figure 3A). ASV129 and ASV614 were identified as showing significant differences between the tobacco monoculture and tobacco-rice rotation systems among the top 20 ASVs (Figure 3B). The most of top 20 ASVs was positively corrected with soil pH, while only ASV_1897 negatively corrected with pH (Figure 3C).

Figure 2

Figure 2. The differences in soil bacterial α-diversity based on the ASVs profiles between tobacco monoculture system and tobacco-rice rotation system. (A) Richness; (B) Shannon; (C) Chao1. The principal coordinates analysis (PCoA) plot of soil bacterial community beta diversity (D). Relative abundance of soil bacteria in the tobacco monoculture system and the tobacco-rice rotation system at the phylum (E) and genus (F) level. T: tobacco monoculture system; TR: tobacco-rice rotation system.

Figure 3

Figure 3. Key ASVs in soil bacterial communities and their association with soil physicochemical properties. The top 20 important ASVs for the bacterial community identified by Random Forest model (A). The significant difference in abundance of key ASVs between tobacco monoculture and the tobacco-rice rotation system (B). Correlation between key ASV abundance and soil physicochemical properties (C). *p < 0.05; **p < 0.01; ***p < 0.001.

3.3 Assembly processes of bacterial communities

The βMNTD and βNTI metrics of soil bacterial communities exhibited significant differences between tobacco monoculture and tobacco-rice rotation systems (Figures 4A, B). Notably, βNTI values in both cropping systems were consistently below-2, suggesting strong deterministic processes in community assembly. In the tobacco-rice rotation system, both βMNTD and βNTI were significantly correlated with most soil nutrient indicators including available nitrogen, phosphorus, potassium, as well as soil pH (Figure 4C). In contrast, neither metric showed significant correlations with any of the measured soil parameters in the tobacco monoculture system. Importantly, βMNTD and βNTI did not exhibit significant associations with soil organic matter content under either cropping system (Figure 4C).

Figure 4

Figure 4. The differences of soil bacterial βMNTD (A) and βNTI (B) in the tobacco monoculture and the tobacco-rice rotation system.βMNTD calculates the mean phylogenetic distance between community samples, where larger values indicate greater phylogenetic divergence. Ecological processes were interpreted via βNTI thresholds (|βNTI|>2: deterministic; βNTI>+2: variable selection; βNTI<−2: homogeneous selection; |βNTI|<2: stochastic). The correlations between bacterial βMNTD, βNTI and soil physicochemical properties in the tobacco monoculture system and the tobacco-rice rotation system (C). *p < 0.05; **p < 0.01; ***p < 0.001.

3.4 Global co-occurrence patterns of bacterial communities

Molecular ecological network analysis of soil bacterial communities revealed major modules predominantly composed of Proteobacteria (Figures 5A, B). Importantly, twenty-two bacterial taxa were identified as connectors within the network, indicating potential keystone roles in community structure and stability (Figure 5C). Distinct differences in network topology were observed between the tobacco monoculture and the tobacco-rice rotation systems. The tobacco-rice rotation system exhibited a significantly higher number of nodes compared to the monoculture, along with a trend toward increased edge numbers in the maturity stage. In contrast, both the transitivity and the average degree were significantly lower in the tobacco-rice rotation system than in the tobacco monoculture system (Figures 5D–I). The modularity analysis revealed that modules 1, 2, 4 and 6 were positively associated with pH (Figure 6A). Among these modules, Proteobacteria was identified as the most important phylum (Figure 6B). Furthermore, an overall assessment of the co-occurrence network demonstrated that a greater proportion of keystone species were negatively correlated with soil phosphorus and potassium content (Figure 6C).

Figure 5

Figure 5. The co-occurrence network of soil bacteria at the module level (A) and phylum level (B). Topological roles of microbial taxa in the soil bacterial co-occurrence network (C). The edges (D), nodes (E), Trans transitivity (F), average path length (G), average degree (H) and betweenness centralization (I) of the soil bacterial network. T, tobacco monoculture system; TR, tobacco-rice rotation system.

Figure 6

Figure 6. The correlation between soil physicochemical properties and bacterial co-occurrence network module (A). The relative abundance of the bacterial co-occurrence network module at the phylum level (B). The correlation between soil physicochemical properties and connectors within the bacterial network (C). *p < 0.05; **p < 0.01; ***p < 0.001.

3.5 Functional prediction of bacterial communities

The predicted functional profile revealed pronounced disparities between the two cropping systems (Figure 7A). Linear discriminant analysis (LDA) revealed that the tobacco-rice rotation system significantly reduced the relative abundance of both nitrite-oxidizing and nitrifying bacteria, LDA score > 3.0, q < 0.01), tobacco monoculture showed a increase in the relative abundance of dark sulfide-oxidizing bacteria (LDA score >3.5, q < 0.01) (Figure 7B). The functional bacterial communities exhibited significantly higher β-diversity variability in the tobacco-rice rotation system compared to tobacco monoculture (Figure 7C). No significant differences were observed in the composition of plant pathogen communities between the cropping systems. However, tobacco plants in monoculture exhibited higher phenotypic variation during the rapid vegetative growth stage (Figure 7D). Total soil phosphorus significantly influenced microbial communities involved in carbon and nitrogen cycling (Figure 8A), and both bacterial species composition and functional communities showed significant correlations with soil pH (Figure 8B).

Figure 7

Figure 7. The Heatmap of bacterial functional taxa related to carbon, nitrogen, and sulfur cycle in the tobacco monoculture system and the tobacco-rice rotation system (A). The differences of functional taxa of bacterial communities as determined by linear discriminant analysis (LDA, p < 0.05) between the tobacco monoculture and the tobacco-rice rotation system (B). Divergence in FAPROTAX-predicted microbial functional β-diversity between tobacco monoculture and tobacco-tice rotation systems (C). Differences in soil plant pathogen relative abundance between tobacco monoculture and tobacco-rice rotation systems (D).

Figure 8

Figure 8. The relationship between soil physicochemical properties and functional taxa related to soil carbon, nitrogen, and sulfur cycle processes (A). The relationship between soil physicochemical properties on bacterial community, bacterial functions, bacterial diversity (B). *p < 0.05; **p < 0.01; ***p < 0.001.

4 Discussion

Among these soil bacterial communities, Proteobacteria, Acidobacteria, and Actinobacteria exhibited relatively high abundances. This can be attributed to their relatively broad ecological ranges. In nature, they account for only about 2% of bacterial phylotypes but nearly half of their abundance (Feng et al., 2024). Furthermore, many studies have also shown that Proteobacteria, Acidobacteria, and Actinobacteria are dominant bacteria in the soil of agricultural ecosystems (Romdhane et al., 2022; Mei et al., 2021). The significant differences at the ASV level, particularly within the dominant phylum, indicate that the different microhabitats established by the two management approaches have surpassed the natural buffering capacity of the microbial community, thereby resulting in a fundamental reorganization of community composition. The significant differences in the abundance of ASV_614, ASV_31, and, ASV_129 in the tobacco monoculture system and the tobacco-rice rotation system might be caused by the change of the habitat from an aerobic environment to an anaerobic environment. The reason why ASV_1897 negatively corrected with pH is that it belongs to Acidobacteriae, which are acidophilic bacteria. The results showed that compared with the tobacco monoculture system, bacterial richness, Shannon index and Chao1 index in tobacco-rice rotation system did not vary significantly, which is similar to the findings of Kaloterakis et al. (2025). One possible reason could be the presence of multiple microorganisms in the soil that are capable of performing identical ecological functions, such as carbon decomposition and nitrogen cycling. The new resources or pressures introduced by crop rotation may be effectively managed by the existing bacterial community, thereby obviating the need for additional species (Louca et al., 2018).

Our field study results showed that soil bacterial βMNTD was significantly higher in the tobacco-rice rotation system than in the tobacco monoculture system. The alternating waterlogging and drought conduction significantly alters the soil environment and drives systematic succession of microbial communities, manifested as a significant increase in βMNTD. Essentially, this reflects periodic shifts and dynamic changes of functionally distant groups such as aerobic/anaerobic and acidophilic/basophilic along with the cropping cycle. Such periodic disturbance based on temporal heterogeneity helps maintain functional diversity of microbes, thereby enhancing the functional stability of the ecosystem. This could be the key to effectively alleviating the tobacco monoculture and continuous-cropping obstacles. Deterministic processes dominated soil bacterial community assembly under both tillage patterns. The reason for this might be that environmental selection is usually the driving factor for the construction of abundant groups and common species (Riddley et al., 2025). Compared with the tobacco monoculture system, the deterministic processes of soil bacterial community assembly in the tobacco-rice rotation system were significantly reduced. Because the flooding conditions make the habitat connectivity better and the internal environment becomes more moderate, the influence of stochastic processes increases (Stegen et al., 2012). Furthermore, the anaerobic environment caused by flooding restricts the decomposition of organic matter, allowing soil fertility to accumulate. This reduces the nutrient source pressure on soil microorganisms and thereby increases the proportion of random processes in their community assembly (Feng et al., 2017, 2018). Similar to our findings, Liu et al. (2021) discovered that the proportion of deterministic processes in microbial community assembly was higher in the drought system than in water-drought rotation systems.

The intense alternation of dry and wet in the crop rotation system creates a highly heterogeneous and dynamic environment, which greatly enhances the role of environmental filtering (Zhou et al., 2017). Soil nutrients and pH are direct and sensitive indicators of such drastic environmental changes and their selective pressure on microorganisms, and thus are significantly correlated with βMNTD/βNTI, which reflects the process of phylogenetic differentiation and construction of the community. However, the relatively stable environment in the mono-cropping system weakens the environmental selection pressure. The spatial or temporal differences of the main soil nutrients and pH currently measured are insufficient to drive the detectable phylogenetic structural changes, or the microbial community has adapted to the steady state, resulting in no significant correlation. The universal uncorrelation of organic matter indicates that regardless of the planting pattern, its changes are difficult to directly and rapidly drive the microbial phylogenetic structure (βMNTD) or significantly affect the relative contribution of deterministic/random processes (βNTI) at the community level. The underlying reason may be that soil organic matter with characteristics such as total complexity, stability, and non-direct availability (Jones et al., 2023). This finding highlights the limitations of soil organic matter’s role in influencing variation in the phylogenetic structure and community assembly of soil microorganisms.

Compared to the tobacco monoculture system, the soil bacterial network in the tobacco-rice rotation system exhibited an increased number of nodes, alongside lower transitivity and average degree. This combination of features indicates a shift toward a network architecture characterized by higher taxonomic diversity, sparser interconnectivity, and greater modularity. Such a structural configuration is considered to provide a robust foundation for community stability and is widely regarded as a hallmark of stable microbial assemblages. This finding aligns with the broader understanding that agricultural diversification promotes complex microbial networks. For instance, Yang et al. (2023) reported a significant positive correlation between soil microbial network complexity and crop diversity indices. Furthermore, in our study, the tobacco-rice rotation enhanced the complexity of the soil bacterial network without significantly altering its average path length. This suggests that the rotation system facilitated an expansion of the network scale while maintaining an efficient balance in functional connectivity and potential metabolic costs. Such insight provides a mechanistic basis for designing targeted microbiome management strategies, such as optimizing crop rotation schemes or developing direct microbial interventions, to enhance agricultural sustainability and soil health. Thus, by bridging statistical association with biological causality, this work represents a step toward predictive microbial ecology. It is important to note that the networks here were inferred from species abundance correlations using SparCC, which captures co−occurrence patterns rather than verified mechanistic interactions such as symbiosis or metabolic cross−feeding. Thus, while such networks reveal potential ecological associations, they may include spurious links driven by shared environmental responses or stochastic noise. This limitation highlights the need for experimental validation, for example through co−culture or synthetic microbial community, to confirm direct interactions and assess their strength and context dependence. Integrating robust computational inference with direct experimental verification will help move the field from descriptive network mapping toward a more mechanistic understanding of microbial community dynamics.

Compared to continuous tobacco monoculture, the tobacco-rice rotation system supported soil bacterial communities with higher variability at both functional and genus levels. This is likely driven by the dynamic soil gradients created through rotation, which involves alternating water regimes (from anaerobic waterlogging to aerobic upland conditions) and shifts in root exudates (e.g., organic acids/phenols from rice vs. alkaloids from tobacco) (Wei et al., 2021; Cheng et al., 2024). This heterogeneity drives continuous bacterial community reconfiguration, characterized by the alternating dominance of anaerobic bacteria (e.g., methanogens) and aerobic bacteria (e.g., nitrogen-fixing species). In our study, the crop rotation system did not significantly reduce the abundance of pathogenic microorganisms in the soil, which was inconsistent with the results of some previous studies (Hong et al., 2023; Zhou et al., 2023). One possible explanation is that the rotational disturbances applied here were insufficient to disrupt certain resilient pathogen reservoirs, such as those protected within dormant structures or occupying stable ecological niches. It should be also noted that lack of detectable shifts in the composition of plant-pathogen community between two cropping system, suggesting that the rotation does not fundamentally reshape the pathogen pool. Similar observations have been reported in other long-term rotation experiments where bacterial community structure remained unchanged despite altered cropping sequences (Town et al., 2023). Interestingly, the high variation in pathogen abundance was observed during the vigorous growth stage of mono-cropped tobacco, indicating an elevated and heterogeneous disease risk across the field sites. The elevated disease risk aligns with the well-established mechanism that monoculture exacerbates plant stress and susceptibility by promoting soil allelopathy and nutrient imbalances. The pronounced spatial heterogeneity in pathogen abundance, however, may further reflect localized variations in soil properties or root health under these stressful conditions.

5 Conclusion

Based on the findings of this three-year field study, it can be concluded that tobacco-rice rotation significantly restructures soil bacterial community composition and interaction networks compared to continuous monocropping, despite minimal changes in overall α-diversity and most soil physicochemical properties. The rotation system enhances microbial connectivity through keystone taxa and strengthens deterministic assembly processes linked to soil nutrient availability, while functionally suppressing nitrifying bacteria and reducing spatial variability in pathogen abundance during critical growth stages. These results demonstrate that crop rotation alleviates continuous cropping obstacles primarily by modulating microbial community assembly and network stability rather than through broad changes in taxonomic diversity or general soil chemistry.

Data availability statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Author contributions

LC: Investigation, Writing – original draft, Resources, Visualization, Validation, Formal analysis, Data curation, Supervision, Project administration, Writing – review & editing, Methodology, Conceptualization. CF: Writing – original draft, Writing – review & editing, Conceptualization, Investigation, Methodology, Formal analysis. LS: Writing – original draft, Project administration, Writing – review & editing, Validation, Supervision. DZ: Writing – review & editing, Conceptualization, Writing – original draft, Methodology. CZ: Supervision, Writing – review & editing, Validation, Writing – original draft, Methodology, Conceptualization, Investigation. WF: Writing – original draft, Project administration, Supervision, Writing – review & editing. JZ: Project administration, Supervision, Writing – review & editing, Writing – original draft. JC: Investigation, Writing – review & editing, Writing – original draft. XD: Investigation, Writing – review & editing, Writing – original draft. SS: Formal analysis, Data curation, Conceptualization, Project administration, Writing – review & editing, Writing – original draft, Investigation.

Funding

The author(s) declared that financial support was received for this work and/or its publication. This work was funded by the: Hengyang City Company, Hunan Provincial Tobacco Company Project #HYYC2023KJ28. Hunan Agricultural Science and Technology Innovation Fund Project #2024CX36 and #2024CX67. The funders were not involved in the study design, collection, analysis, interpretation of data, the writing of this article, or the decision to submit it for publication.

Acknowledgments

We are thankful to the College of Agronomy of Hunan Agricultural University, and the Institute of Plant Protection, Hunan Academy of Agricultural Sciences, for their support. At the same time, we also thank everyone for their hard work.

Conflict of interest

Authors LC, CF, WF and JZ were employed by the company Hunan Tobacco Company.Author LS was employed by the company Jilin Tobacco Industry Co., Ltd.

The remaining author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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The author(s) declared that generative AI was not used in the creation of this manuscript.

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