Responses of Soil Microbial Communities to Biogas Slurry Irrigation in Paddy Fields: Interactions with Environmental Factors

Abstract

Biogas slurry (BS), a nutrient-rich byproduct of anaerobic digestion, is increasingly utilized in agriculture to enhance soil fertility and crop productivity. However, the long-term effects of BS on soil microbial communities in paddy fields have not been thoroughly investigated. This study investigated the impacts of continuous BS irrigation over 0–3 years on soil microbial diversity, community composition, and their relationships with environmental factors in southeastern China. The results showed that bacterial diversity (Shannon index) significantly decreased from 6.96 (0 year) to 6.58 (3 years) (p < 0.05), while fungal diversity displayed a U-shaped trend, initially declining to 4.13 (1 year) and subsequently recovering to 4.86 (3 years) (p < 0.05). Dominant bacterial phyla such as Chloroflexi and Bacteroidetes increased in abundance under BS treatment, whereas Gemmatimonadetes decreased. Fungal communities shifted, with Mortierellomycota replacing Basidiomycota as the dominant phylum. Redundancy analysis (RDA) accounted for 91% and 74.9% of the variance in bacterial and fungal communities, respectively. Correlation analysis further indicated that soil available nitrogen and Cr were the primary drivers of bacterial community composition (p < 0.001), whereas soil available potassium and Cd were the key factors influencing the fungal community structure (p < 0.001). This study highlights that BS application alters microbial dynamics, favoring anaerobic bacteria and suppressing pathogenic fungi like Fusarium, thereby supporting sustainable soil management in rice cultivation systems.

1. Introduction

Biogas slurry (BS), a nutrient-rich byproduct of anaerobic digestion, has emerged as a promising sustainable alternative to synthetic fertilizers for enhancing soil fertility and crop productivity. Studies have shown that BS application can increase rice yield by 15–20% through organic nitrogen stabilization and phosphorus mobilization [1,2]. Moreover, recycling BS not only reduces wastewater discharge but also supports circular agricultural practices [3]. However, long-term irrigation with BS introduces environmental risks, such as heavy metal accumulation (e.g., Cr and Cd) from livestock manure inputs and altered soil redox conditions, which may impair microbial activity [4,5,6]. These dual effects, boosting productivity while posing contamination risks, highlight the necessity of defining thresholds for BS application that balance agronomic benefits with ecosystem health.

Soil microbial communities, key drivers of nutrient cycling and organic matter decomposition, are highly sensitive to BS-induced environmental changes [7,8,9,10]. Short-term experiments indicate that BS promotes copiotrophic bacteria (e.g., Bacteroidetes), accelerating organic carbon turnover [11], while suppressing pathogenic fungi like Fusarium via nutrient competition [12]. Long-term studies further reveal that soil nutrients (e.g., available nitrogen) and heavy metals (e.g., Cd) are critical regulators of microbial diversity [13]. For instance, metagenomic analyses demonstrate that the decline in Gemmatimonadetes abundance under prolonged BS irrigation is linked to Cd-induced metabolic inhibition [14]. Fungal communities, however, exhibit a recovery trajectory under BS treatment, suggesting adaptive resilience to anaerobic conditions [15]. Despite these insights, existing research predominantly relies on short-term pot trials or small-scale experiments [16,17], neglecting field-scale variables such as fluctuating water regimes and crop–microbe interactions. Consequently, the mechanisms underlying microbial community dynamics under continuous BS irrigation, particularly the interplay between fungal resilience and heavy metal toxicity, remain poorly understood.

To address these gaps, this study investigates the effects of 0–3 years of continuous BS irrigation on microbial communities in paddy fields in southeastern China. We hypothesize that (1) prolonged BS irrigation reduces bacterial diversity but triggers fungal community recovery via anaerobic adaptation, and (2) soil nutrients and heavy metals synergistically drive microbial assembly. Using high-throughput sequencing and redundancy analysis, we aim to (1) quantify the temporal shifts in bacterial and fungal diversity and (2) elucidate the roles of soil nutrients and heavy metals in shaping microbial structure. This work provides a mechanistic framework for optimizing BS application strategies, ensuring both agricultural productivity and ecosystem stability.

2. Materials and Methods

2.1. Site Description and Soil Sampling

The study site is located in Jinhua City, Zhejiang Province (29.03° N, 119.44° E). This region has a subtropical monsoon climate, characterized by an average annual temperature of 17.3 °C to 18.2 °C and an annual precipitation of 1109.0 mm to 1305.2 mm. It is a double-season rice cultivation area where straw is incorporated into the soil during both growing seasons.

Biogas slurry is annually applied via pipelines and irrigated concurrently with the first irrigation water before the transplantation of early rice (around March each year), with an average application rate of 450 tons per hectare, serving as both irrigation water and basal fertilizer. In regions without BS, the same volume of surface water is employed for irrigation, and an equivalent quantity of chemical fertilizer is applied as the basal fertilizer. Based on regional management practices for biogas slurry application in paddy fields, neighboring farms have established fields that vary in the number of years irrigated with biogas slurry. The biogas slurry properties were as follows: total organic carbon (C) of 1200 mg/L, total nitrogen (N) of 500 mg/L, total phosphorus (P) of 80 mg/L, and total potassium (K) of 300 mg/L.

Paddy soil samples were systematically collected in March 2024 from areas representing 0, 1, 2, and 3 years of biogas irrigation, labeled as ZG 0, ZG 1, ZG 2, and ZG 3, respectively. For each treatment, 15 soil samples were collected from the topsoil layer (0–20 cm) using the chessboard layout method and then uniformly mixed to form one composite sample according to GB/T 36197 [18]. A portion of the composite sample was air-dried for the analysis of basic physical and chemical properties, while another part was stored at −80 °C to preserve the DNA integrity for microbial community analysis, a method validated for minimal microbial activity alteration [19].

2.2. Soil Physicochemical Analyses

The soil pH was assessed using a pH electrode at a soil-to-water ratio of 1:2.5 (Mettler Toledo, Columbus, OH, USA). The available nitrogen (AN) content was quantified via alkaline hydrolysis diffusion in 1 mol L⁻¹ NaOH at 40 °C for 24 h, followed by titration with HCl [20]. Available phosphorus (AP) was measured using the Olsen method [21], whereas available potassium (AK) was extracted with 1 mol L⁻¹ NH₄OAc and quantified using a flame photometer (BWB-XP, Cambridge, UK). Soil organic carbon (SOC) and total nitrogen (TN) levels were determined using an elemental analyzer (Thermo Fisher Scientific, Waltham, MA, USA). The total concentrations of heavy metals, such as copper (Cu), lead (Pb), zinc (Zn), cadmium (Cd), nickel (Ni), and chromium (Cr), were obtained by digesting the samples with a mixture of HF, HNO₃, and HClO₄, followed by analysis with ICP-MS (Analytik Jena, Plasma Quant MS Elite, Jena, Germany). The detection limit of Cd for ICP-MS analysis was 0.0015 mg/kg. After solvent extraction and anti-extraction, the total concentrations of mercury (Hg) and arsenic (As) were measured using an atomic fluorescence spectrophotometer (AFS-9230, Titan Instruments, Beijing, China).

2.3. DNA Extraction and Illumina Sequencing

DNA extraction was performed on each composite of ~1.0 g of soil sample using the E.Z.N.A.^® soil DNA kit (Omega, GA, USA) according to the instruction manual. The extracted DNA was quantified using a Nanodrop 2000Uv-Vis spectrophotometer (ThermoScientific, Waltham, MA, USA). The extracted DNA was analyzed using Illumina MiSeq sequencing (Illumina, San Diego, CA, USA). Polymerase chain reaction (PCR) amplification was conducted using the primer set of 27F (5′-ACACTGACGACATGGTT-3′) [19] and 533R (5′-TTACCGCGGCTGCTGGCAC-3′) [22] for the V1–V3 region of the bacterial 16S rRNA gene and the primer set of ITS1 (5′-CTTGGTCATTTAGAGGAAGAGAA-3′) and ITS2 (5′-GCTGCGTTCTTCATCG ATGC-3′) for the ITS region of fungi [23]. After amplification, the triplicate amplicons were pooled and purified using the PCR cleanup kit. Sequencing was conducted by Majorbio Bioinformatics Technology Co., Ltd. (Shanghai, China) on an Illumina Miseq system.

2.4. Statistical Analyses

All statistical analyses were conducted using SPSS 21.0 (SPSS Inc., Chicago, IL, USA). Analysis of variance (ANOVA) and Tukey’s HSD (Honest Significant Difference) test were applied to evaluate the soil’s physicochemical properties, heavy metal content and microbial diversity. Redundancy analysis (RDA) was performed using CANOCO for Windows 4.5 (Microcomputer Power Inc., Ithaca, NY, USA) to investigate the influence of the soil’s physicochemical properties and heavy metal content on the microbial community composition. Environmental variables (pH, AN, AP, AK, TN, SOM) and heavy metals (Cu, Pb, Cd, Cr, Zn, As, Hg, Ni) were standardized (Z-score) to minimize scale effects. Spearman correlation analysis was employed to assess the statistical significance of the relationships between the variations in bacterial and fungal community structures and the soil’s physicochemical properties, as well as the heavy metal content. Heatmaps and correlation coefficients were generated using R version 3.6.1.

3. Results and Discussion

3.1. Soil Properties and Heavy Metals

Biogas slurry (BS) irrigation significantly altered the soil nutrient dynamics over the 0–3-year period (Figure S1). Soil organic matter (SOM) increased from 12.3 g·kg⁻¹ (ZG0) to 28.5 g·kg⁻¹ (ZG3), reflecting continuous organic carbon input from BS. Total nitrogen (TN) rose by 35% (from 1.2 g·kg⁻¹ at ZG0 to 1.6 g·kg⁻¹ at ZG3), driven by ammonium and organic nitrogen enrichment in BS. Available phosphorus (AP) exhibited a sustained increase (from 15.2 mg·kg⁻¹ at ZG0 to 42.8 mg·kg⁻¹ at ZG3). In contrast, available potassium (AK) peaked at ZG2 (280 mg·kg⁻¹) but declined at ZG3 (245 mg·kg⁻¹). These trends are consistent with prior studies. The SOM accumulation aligns with findings by Li et al. [13], who linked BS application to microbial necromass-driven carbon sequestration. The AK decline is similar [4], emphasizing potassium mobility in BS-amended soils. Notably, the TN rise contrasts with mineral fertilizer systems, which often exhibit nitrogen losses, underscoring BS’s role in stabilizing nitrogen via organic–inorganic synergy [15].

The shifts in heavy metal concentrations were induced by biogas slurry (BS) irrigation over the 0–3-year period (Table S1). Chromium (Cr) significantly accumulated in ZG3 (82.93 mg·kg⁻¹ vs. ZG0: 80.97 mg·kg⁻¹, p < 0.05), likely sourced from livestock manure in BS. Cadmium (Cd) declined in ZG1/ZG3 (0.13 mg·kg⁻¹ vs. ZG0: 0.26 mg·kg⁻¹) due to organic complexation but rebounded in ZG2 (0.22 mg·kg⁻¹), suggesting transient DOM-mediated release [16]. These trends are consistent with prior studies. The Cr accumulation aligns with findings in manure-amended soils [15], while the Cd dynamics reflect organic–inorganic interactions [13].

3.2. Soil Microbial Alpha Diversity

The alpha diversity indices include both richness (Chao1) and evenness (Shannon/Simpson), providing insights into the species distribution and characteristics of local ecological niches. Alpha diversity quantifies the richness and evenness of microbial communities, whereas the Shannon and Simpson indices measure the extent of diversity within these communities. The Simpson index emphasizes the dominance of prevalent species, while a higher Shannon index indicates greater community diversity. Conversely, a lower Simpson index signifies a more diverse community. The Chao index assesses species richness, with a higher value indicating greater richness. The coverage index reflects the proportion of the microbial community captured by the sample library.

As shown in

Table 1. Bacterial and fungal alpha diversity in paddy fields irrigated with BS over different years.

	Shannon		Simpson		Chao1		Coverage
	Bacteria	Fungi	Bacteria	Fungi	Bacteria	Fungi	Bacteria	Fungi
ZG0	6.9571 ± 0.0462 b	4.6176 ± 0.0616 d	0.0023 ± 0.0001 a	0.0365 ± 0.0080 b	3759.9757 ± 150.5584 c	1050.8603 ± 57.0251 c	0.9687 ± 0.0114 a	0.9982 ± 0.0003 a
ZG1	6.5355 ± 0.0192 a	4.1278 ± 0.0429 a	0.0046 ± 0.00003 c	0.0537 ± 0.0027 c	3549.9966 ± 119.4239 b	684.0991 ± 15.4494 a	0.9823 ± 0.0020 b	0.9991 ± 0.0002 c
ZG2	6.5709 ± 0.0511 a	4.4639 ± 0.0218 b	0.0034 ± 0.0006 b	0.0298 ± 0.0011 b	3199.5067 ± 52.3983 a	829.8786 ± 32.5932 b	0.9789 ± 0.0020 ab	0.9985 ± 0.0002 ab
ZG3	6.5847 ± 0.0484 a	4.8571 ± 0.0285 c	0.0037 ± 0.0001 b	0.0167 ± 0.0004 a	3654.2542 ± 66.7986 bc	828.6809 ± 14.4812 b	0.9787 ± 0.0008 ab	0.9989 ± 0.0007 bc

Note: Values are presented as the mean ± standard deviation (n = 3). Different lowercase letters in the same column indicate a significant difference at p < 0.05.

, the bacterial Coverage index across different treatment groups ranged from 0.9687 to 0.9823, while the fungal Coverage index ranged from 0.9982 to 0.9991. These values suggest that the sequencing depth of the soil samples was adequate and representative of the actual conditions. The bacterial Shannon index of the ZG3, ZG1, and ZG2 groups was significantly lower than that of the ZG0 group (p < 0.05), indicating that the application of digestate significantly reduced bacterial diversity. Additionally, the Simpson index of the ZG2 group was significantly lower than that of the ZG0 group, suggesting a decrease in the diversity of dominant bacterial species over the two-year period of digestate irrigation. The Chao index of the ZG1 group was also significantly lower than that of the ZG0 group, indicating an initial reduction in bacterial richness following the application of digestate, which subsequently increased with prolonged irrigation.

For fungi, the Shannon and Simpson indices of the ZG3 group were significantly higher than those of the other treatment groups, indicating that three years of continuous digestate application had a more pronounced effect on the diversity of dominant fungal species in the soil. Furthermore, the Chao index of the ZG0 group was significantly higher than those of the other treatment groups, suggesting that digestate irrigation may reduce soil fungal richness.

Following slurry irrigation, the soil may enter an anaerobic and eutrophic condition, resulting in a decrease in aerobic and oligotrophic bacterial populations [13]. This leads to a notable increase in the total biomass of soil microorganisms while simultaneously causing a reduction in microbial diversity. As the duration of slurry irrigation increases, soil tillage practices and the interactions within soil microbial communities, including both coordination and competition, will gradually establish a relatively stable ecological system for soil microorganisms [1,2].

3.3. Soil Microbial Community Composition

The phylum level was chosen for species classification, and the abundance of bacteria and fungi in different samples was quantified and presented as bar charts (Figure 1). As shown in Figure 1a, the dominant bacterial genera with a relative abundance exceeding 5% in the soil were Chloroflexi, Proteobacteria, Acidobacteria, and Actinobacteria. Irrigation with BS led to a decrease in the relative abundance of Gemmatimonadetes and an increase in the relative abundance of Chloroflexi, Bacteroidetes, and Nitrospirae. The proportion of Gemmatimonadetes in the soil decreased following the BS irrigation in paddy fields due to the exacerbation of eutrophication in the paddy field water bodies, resulting in reduced dissolved oxygen and soil oxygen levels [13]. This, in turn, diminished the activity of certain strictly aerobic or facultatively anaerobic microorganisms. Conversely, the proportion of Chloroflexi gradually increased, as many Chloroflexi microorganisms are strictly anaerobic and capable of fermenting sugars and polysaccharides into organic acids and hydrogen, thus accelerating the decomposition of organic matter in paddy fields [24]. After one year of paddy field drainage, the proportion of Bacteroidetes experienced a sudden increase, possibly attributed to the introduction of substantial organic matter through BS application, which provided ample carbon and nitrogen sources for bacterial growth and proliferation [8].

As shown in Figure 1b, the dominant fungal genera with a relative abundance exceeding 5% in the soil were Ascomycota and Basidiomycota. After one year with BS irrigation, Mortierellomycota replaced Basidiomycota as the dominant fungal genus. The relative abundance of Ascomycota began to decline following the application of BS. The nutritional mode of Ascomycota is predominantly saprotrophic, and the application of BS has demonstrated certain inhibitory effects on this fungal phylum [5]. Glomeromycota, primarily comprising arbuscular mycorrhizal fungi, play a crucial role as symbionts in plant root systems. The environmental impact of BS irrigation on this phylum warrants further investigation.

The microbial dominance of paddy fields with different BS irrigation years is shown in Figure 2. Among bacteria, the genera norank_f_Gemmatimonadaceae and Anaerolinea were notably abundant. Compared to ZG0, the relative abundance of Anaerolinea in ZG1, ZG2, and ZG3 showed a significant increase, suggesting that BS application may have stimulated the growth of anaerobic bacteria. After excluding the unidentified genus, Anaerolinea emerged as the predominant bacterial genus, primarily observed in soils subjected to BS irrigation. This phenomenon could be attributed to its ability to degrade carbohydrates under anaerobic conditions and its involvement in the biological cycles of carbon (C), nitrogen (N), sulfur (S), and iron (Fe) in paddy fields. Additionally, Anaerolinea can interact with nitrogen-fixing bacteria, thereby enhancing soil fertility [2,9].

In fungi, the genera Echria, Fusarium, Westerdykella, Epicoccum, and Pseudaleuria are relatively abundant. Mortierella is predominantly observed in the ZG1, ZG2, and ZG3 treatments, indicating that the application of BS increased its relative abundance. Fusarium exhibits the highest proportion in the ZG0 treatment, with a significant decrease in ZG1, ZG2, and ZG3, indicating that the application of BS markedly reduces the proportion of the Fusarium genus. Epicoccum exhibited the highest proportion in ZG3, followed by ZG1, ZG0, and ZG2, implying that its abundance initially increased in the first year after biogas slurry application, decreased in the second year, and then reached its peak in the third year.

The genus Mortierella encompasses both biocontrol fungi and plant pathogens [8,25]. The findings indicate that the continuous application of BS may enhance the abundance of specific beneficial fungal taxa in paddy soil. Certain species within Mortierella function as litter saprotrophs, playing essential roles in the decomposition of plant litter [26]. Previous studies have demonstrated that high nitrogen (N) input may exacerbate the impact of Fusarium on rice in southeast China [5,6,12,27,28]. Liu et al. (2017) reported that a decade of N fertilization increased the relative abundance of Fusarium in wheat fields on the Loess Plateau [27]. Cao et al. (2016) found that the application of pig biogas slurry significantly reduced the incidence of Fusarium wilt in watermelon [12]. It is well established that certain Fusarium species are typical plant pathogens, capable of causing root rot and other diseases in crops [4,25,28]. In this study, we observed that irrigation with BS substantially decreased the abundance of Fusarium, thereby mitigating the risk of fungal pathogenicity.

3.4. Relationship Between Soil Microbial Community Structure and Soil Environmental Factors

Redundancy analysis (RDA) was a statistical method employed to quantify the extent to which environmental variables, such as nutrients and heavy metals, explain the variation in the structure of biological communities. It was employed to understand the relationship between soil environmental factors and the changes in the structural diversity of bacterial and fungal communities (Figure 3). The two principal axes in Figure 3a,b collectively accounted for 91% of the variance in bacterial microbial communities, with the first axis explaining 57% and the second axis explaining 34%. In Figure 3c,d, the two principal axes collectively explained 74.9% of the variance in fungal microbial communities, with the first axis accounting for 43% and the second axis for 31.9%.

Soil nutrients and heavy metals exerted pronounced influences on the structure of bacterial communities. Specifically, AN, AP, and AK had the most significant impact on both bacterial and fungal communities. Among the heavy metals, Ni, Cr, and Cd showed the most substantial effects.

Furtherly, a heatmap of the Pearson correlation analysis was created to examine the relationship between soil environmental factors and the relative abundance of dominant phyla in the soil (Figure 4). Eight bacterial phyla exhibited significant correlations with soil environmental factors. Bacteroidetes and Mortierellomycota showed a significant positive correlation with AN (p < 0.001) and Bacteroidetes, while Firmicutes showed a significant negative correlation with Cr (p < 0.001). The most notable positive correlation with Cd (p < 0.001) was observed for Gemmatimonadetes.

The positive correlation between Bacteroidetes and available nitrogen (AN) is consistent with the fact that they thrive under high organic inputs [11,13]. Nutrients derived from biogas slurry (BS) promote the proliferation of Bacteroidetes in such environments. In contrast, the negative association with Cr may reflect the toxicity-induced suppression of sensitive taxa [29]. Compared to studies on Cd-polluted soils, Cr’s stronger oxidative potential likely amplifies its impact on microbial communities, underscoring the context-dependent nature of metal effects [15]. Gemmatimonadota evolved as an organotrophic species relying on oxygen and exhibited high sensitivity to Cd owing to their limited metal resistance mechanisms, such as the absence of efficient efflux pumps or detoxification genes [14]. Cd exposure disrupts their metabolic pathways, resulting in a reduced abundance in contaminated soils [15]. This observation aligns with findings in Cd-polluted agricultural soils, where the abundance of Gemmatimonadetes inversely correlates with Cd bioavailability [4].

Three fungal phyla also demonstrated significant correlations with soil environmental factors, where Basidiomycota and Rozellomycota exhibited a significant negative correlation with AK (p < 0.001). Moreover, Mortierellomycota and Rozellomycota displayed a significant negative correlation with Cd (p < 0.001).

Rozellomycota is an obligate parasitic fungus that relies exclusively on its host for survival. The negative correlations between Rozellomycota and available potassium (AK)/Cd are likely attributable to AK-facilitated bacterial competition, which suppresses its fungal hosts [4], and Cd-induced toxicity, which compromises spore viability [15]. Nevertheless, the specific dynamics of host–parasite interactions and the complex interplay between Cd and dissolved organic matter (DOM) remain underexplored. Future research should incorporate metagenomic analyses to elucidate host–parasite interaction networks and conduct long-term field trials to evaluate the intricate metal–organic interactions, thereby addressing critical knowledge gaps in the current models of nutrient-heavy metal synergies [12,27]. The negative correlation between Mortierellomycota abundance and Cd contamination may arise from cadmium-induced oxidative stress, which suppresses fungal activity [15], as well as the dominance of bacteria such as Bacteroidetes under nutrient enrichment conditions [4,13].

4. Conclusions

Long-term biogas slurry (BS) irrigation significantly reshaped soil microbial communities in paddy fields. Bacterial diversity consistently declined with increasing irrigation duration, while fungal diversity exhibited a U-shaped trend, recovering after three years. Key microbial shifts included an increased abundance of Chloroflexi and Bacteroidetes (bacteria) and Mortierellomycota (fungi), alongside reduced Fusarium levels, potentially mitigating plant pathogen risks. Soil nutrient availability (AN, AP, AK) and heavy metal concentrations (Ni, Cr, Cd) were identified as primary factors influencing the microbial community structure. These findings underscore the dual role of BS in enhancing soil fertility while necessitating the careful monitoring of heavy metal accumulation. The study provides a theoretical basis for optimizing BS application strategies to balance agricultural productivity and soil ecosystem health in rice-growing regions.