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Article

Rice-Fish Co-Culture Promotes Soil Carbon Sequestration Through Alterations in Soil Microbial Community Structure

by
Daolin Sun
1,2,3,
Hongjun Zheng
1,2,3,
Zhaoji Shi
1,2,3,
Jiaen Zhang
1,2,3,4,*,
Qi Jia
1,2,3,
Xing Liu
1,2,3,
Min Zhao
5,
Yuting Chen
1,2,3,
Qi Chen
1,2,3 and
Mingzhu Luo
5
1
Guangdong Engineering Technology Research Center of Modern Eco-Agriculture and Circular Agriculture, South China Agricultural University, Guangzhou 510642, China
2
Guangdong Laboratory for Lingnan Modern Agriculture, Guangdong Provincial Key Laboratory of Eco-Circular Agriculture, South China Agricultural University, Guangzhou 510642, China
3
Department of Ecology, College of Natural Resources and Environment, South China Agricultural University, Guangzhou 510642, China
4
Key Laboratory of Agro-Environment in the Tropics, Ministry of Agriculture and Rural Affairs, South China Agricultural University, Guangzhou 510642, China
5
College of Agriculture, South China Agricultural University, Guangzhou 510642, China
*
Author to whom correspondence should be addressed.
Agronomy 2025, 15(5), 1054; https://doi.org/10.3390/agronomy15051054
Submission received: 10 February 2025 / Revised: 24 March 2025 / Accepted: 26 March 2025 / Published: 27 April 2025
(This article belongs to the Section Farming Sustainability)
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Abstract

:
The high-input production mode of rice monoculture (RM) has caused severe soil degradation and biodiversity loss, necessitating a transition toward more sustainable practices. The traditional rice-fish co-culture (RF) may provide valuable insights for this situation. However, it remains elusive how long-term RF system influences soil microbial community structure, enzyme activities, and carbon (C) sequestration. Here, a study was conducted at two representative RF areas in Lianshan Zhuang and Yao Autonomous County. At Shatian (P1), three treatments included rice monoculture (RM1) and 2-year and 5-year RF (RF2, RF5). At Gaoliao (P2), the experimental treatments included rice monoculture (RM2) and 15 and 30 years of RF (RF15, RF30). We collected the surface layer (0–20 cm) soils. Then, we analyzed the chemical properties, phospholipid fatty acids (PLFA), and enzyme activities to investigate the effects of their variation on soil C sequestration. The results showed that RF treatments significantly increased soil organic C (SOC) content. Specifically, RF2 and RF5 treatments promoted the SOC content by 4.82% and 13.60% compared with RM1 treatment at P1, respectively; RF15 and RF30 treatments increased the SOC content by 23.41% and 31.93% compared with RM2 treatment at P2, respectively. Additionally, RF5 treatment significantly increased the biomass of the soil microbial community in comparison with RM1 treatment, as did RF15 treatment and RF30 treatment compared with RM2 treatment, including total the contents of PLFA and the PLFA of gram-positive bacteria (G+), gram-negative bacteria (G−), actinomycetes, fungi, and bacteria. Activities of β-glucosidase, cellobiohydrolase, β-1,4-N-acetylglucosaminidase, and urease significantly increased in RF5 and RF30 treatments. The piecewise SEM results indicated that the changes of total PLFA content and the PLFA content ratio of fungi to bacteria were related to contents of dissolved organic C (DOC) and total N (TN) under different RF durations, which are key indicators affecting SOC content. Overall, SOC storage increases with the RF durations, and soil microbial community structure may drive soil C sequestration under long-term RF, which provides a scientific significance and practical value in promoting the sustainability of agricultural ecosystems, enhancing the potential of soil as a carbon sink, and addressing global climate change.

1. Introduction

Rice, a staple food, accounts for 28.78% of the world’s major food production [1] and provides food for about four billion people globally [2]. As a predominant rice producer, China contributes 28.10% to worldwide rice production [1]. Intensive rice monoculture (RM) has relied on long-term and high-input (fertilizers and pesticides) to maintain rice productivity and address the increasing food demand. However, this approach has led to several agri-environmental challenges, such as the diminution of soil fertility [3], aggravation of the greenhouse effect [4], and eutrophication of water bodies [5]. Moreover, 90% of the world’s paddy fields are submerged to varying extents [6], and rice cultivation consumes 34–43% of the global irrigation water [7]. In response, the ancient Chinese practice of rice-fish co-culture (RF) offers a sustainable alternative. By integrating rice cultivation with aquaculture, RF enhances ecological balance while delivering significant economic benefits [8,9,10,11].
Soil quality and health are fundamental in determining the sustainability of soil productivity [12]. Soil organic carbon (SOC) plays a crucial role in defining soil functionality and quality and serves as an indicator to evaluate soil health [13]. This interdependence implies that quantifying SOC dynamics becomes imperative when evaluating how agricultural management practices influence soil productivity sustainability. Although rice-animal co-culture systems have been demonstrated to enhance carbon (C) sequestration, this benefit may be affected through the duration of the integrated rice and aquatic animal co-culture. Zhao et al. [14] revealed that the short-term (1 year) RF reduced the soil organic matter content, whereas 5-year RF increased the content. Furthermore, a continuous seven-year study by Guo et al. [15] has confirmed that RF consistently promotes the accumulation of soil organic matter. Additionally, a thirteen-year study by Chen et al. [16] has demonstrated that rice-crab co-culture significantly augmented soil organic matter content compared with RM during the initial three to four years, and the change was more moderate over the subsequent decade, eventually reaching a relatively stable state. So, it is essential to analyze SOC dynamics across different RF durations in order to understand how temporal management scales influence the sustainability and productivity of RF systems.
SOC dynamics are a complex process driven by soil microorganisms, involving its formation and decomposition. Bacteria and fungi are two predominant microbial groups that constitute approximately 90% of the soil microbial biomass [17]. However, they exhibit varied roles in C cycle regulation through substrate-specific metabolic strategies. Specifically, bacteria prefer substrates with a low ratio of C to nitrogen (N), whereas fungi are more likely to decompose substrates with a high ratio of C to N [18]. This difference in ecological niches has a significant impact on C cycling. Moreover, fungi are more resistant to decomposition compared with bacteria due to their longer C cycling periods and unique cell wall composition [19], suggesting that the C sequestration might be more effective in fungal-dominated microbial communities. Li et al. [20] conducted a long-term study on rice-crayfish-turtle co-culture to analyze the genomes of soil fungi and bacteria and found that minimal differences in the composition of soil fungi and bacteria after 7 years of cultivation compared with RM. However, a significant alteration was observed after 12 years, suggesting that RF duration may potentially augment SOC storage by influencing the soil microbial community structure. Additionally, soil microorganisms not only directly utilize organic matter but also improve its decomposition by secreting extracellular enzymes [21]. β-glucosidase (BG) could catalyze cellobiose conversion to glucose, which serves dual roles as a microbial energy substrate and a plant-available nutrient [22]. Bhattacharyya et al. [23] reported that RF improved BG activity. Consequently, a more comprehensive understanding of the intrinsic mechanisms of soil C sequestration requires a deeper knowledge of the variations in soil microbial communities and enzyme activities under different RF durations.
Hence, the objectives of this study are to (1) quantify the SOC storage under different RF durations (2, 5, 15, and 30 years), (2) investigate the effects of RF durations on soil microbial community structure and C-cycling enzyme activities to reveal the key biochemical factors, and (3) elucidate the potential mechanisms of C sequestration by evaluating the role of fungal and bacterial dominance and microbial-mediated C stabilization pathways in RF system. Based on above objectives, we hypothesize that (1) the SOC content is influenced by the RF durations, exhibiting an increasing trend over time; (2) the availability of C and N affects the soil microbial community structure; (3) long-term RF promotes C sequestration by enhancing the fungal dominance.

2. Materials and Methods

2.1. Study Site and Experimental Design

The study sites are located in Lianshan Zhuang and Yao Autonomous County, Qingyuan City, Guangdong Province, China. This region is characterized by a subtropical hilly terrain, with a mean annual temperature of 21.7 °C and precipitation of 1512.6 mm in 2021. Despite the long-standing history of the RF in Lianshan, certain areas persist with RM. In recent years, owing to its ecological benefits, the RF mode has been widely promoted by agricultural authorities and extensively adopted within the traditional RM areas of Lianshan. To minimize potential confounding factors, we conducted field surveys and archival analyses of agricultural records and established the following selection criteria: (1) all sampling plots were confined to 1 km2 area with identical soil type and irrigation source; (2) each study area contained more than 2 types of RF durations and RM, and each treatment was repeated three times at least; (3) prior to the RF adoption, both planting systems and fertilization management of sample treatments had been maintained uniformly for 10 years; (4) RF management practices were uniform; (5) sample plots were more than 100 m2. Based on these criteria, we selected two villages with varied RF histories in Lianshan to study the soil ecological effects of long-term and short-term RF (Figure 1). The first site (P1, 112°04′ E, 24°60′ N) is situated in Shatian Village, where local farmers have recently adopted RF. At P1, we conducted experimental treatments that included RM (RM1) and RF practiced for 2 years and 5 years (RF2, RF5). Furthermore, the second site (P2, 112°08′ E, 24°70′ N) is located in Gaoliao Village, an area with a substantial historical background. The experimental treatments comprised rice monoculture (RM2) and long-established RF that have been in operation for 15 years (RF15) and 30 years (RF30) at P2.
The managements of RM and RF referred to the practices of local farmers (Figure S1). The planting system was medium-season rice with organic manure (15 t hm−2) as the basal fertilizer application before tilling. In early June, the rice seedlings were transplanted with the same plant and row spacing (20 cm × 25 cm). The carp (Cyprinus carpio) used in the experiment was a special local species and cultivated at a density of 7500 individuals per hectare within a paddy field. These fish were introduced in the late tillering stage of rice and harvested prior to the beginning of rice collection in early October. Throughout the entire symbiotic process, no additional feed was provided for the fish. Instead, the fish relied on rice flowers, weeds, insects, and other resources from the paddy fields to meet their nutritional needs for growth. After the rice harvest, these experimental fields were idle.

2.2. Soil Sampling and Measurements

Sampling was conducted on 26 May 2022 before tilling at P1 and P2, avoiding the retention effect of fish farming and assessing the soil status prior to rice transplantation. All sampling procedures were systematically executed between 9:00 and 11:00 local time across both sites to control for diurnal variations in microbial communities, ensure temporal consistency, and minimize meteorological interference on soil biogeochemical parameters. First, we used the five-point sampling method in each plot to collect the topsoil (0–20 cm) with a 5 cm diameter soil drill. Then, the collected soil samples were mixed, bagged, and placed in a −20 °C cooler. After removing rocks and plant roots, a portion of the soil subsamples was naturally air-dried to measure pH, SOC, and total N (TN), and another portion of fresh soil subsamples was used to determine contents of dissolved organic C (DOC), ammonium N (NH4+-N), microbial biomass C and N (MBC and MBN), phospholipid fatty acid (PLFA), and the activities of BG, cellobiohydrolase (CBH), β-1,4-N-acetylglucosaminidase (NAG), and urease.
The soil pH was measured in a soil/water suspension with a ratio of 1:2.5. The contents of SOC, DOC, and TN were determined by using an elemental analyzer (Elementar Vario III, Elementar Analysensysteme GmbH, Hanau, Germany). The NH4+-N content was estimated by the Nesslerization method [24]. The MBC and MBN contents were determined using the chloroform fumigation-K2SO4 extraction and chloroform fumigation-total N measurement methods, respectively [25].

2.3. PLFA Analysis

PLFA analysis was used to identify the microbial community through the sum of one or more diagnostic lipid markers according to Frostegård and Bååth [26] and Wang, et al. [27]. The detailed classification information is as follows: the biomarkers of gram-positive bacteria (G+) (i14:0, i15:0, a15:0, i16:0, i17:0, and a17:0); the biomarkers of gram-negative bacteria (G−) (16:1ω7c, 17:1ω8c, 18:1ω7c, cy17:0); fungal biomarkers (18:1ω9c and 18:2ω6c); and actinomycete biomarkers (10Me16:0, 10Me17:0, and 10Me18:0). Additionally, the PLFA content ratio of fungi to bacteria (F/B) and the PLFA content ratio of G+ to G− (G+/G−) were calculated.

2.4. Soil Enzyme Assays

The activities of four hydrolytic enzymes involved in soil C and N cycling were measured: BG, CBH, NAG, and urease. BG, CBH, and NAG were selected to assess the decomposition efficiency of labile plant- and fungal-derived substrates (cellulose and chitin) [28], while urease was chosen to evaluate the sustained supply capacity of NH4+-N [29]. Briefly, BG, CBH, and NAG were isolated from fresh soil using sodium acetate buffer and detected in a microplate through fluorescence, as described by German et al. [30]. The activities of BG, CBH, and NAG were expressed as nmol g−1 h−1. In addition, the activity of urease was assessed colorimetrically with the indophenol blue method described by Sekaran et al. [31] and was reported as μg g−1 h−1.

2.5. Statistical Analysis

A one-way analysis of variance (ANOVA) was used to assess the differences between the data at P1 and P2, respectively. Duncan’s multiple range test was applied for data exhibiting homogeneity of variances, whereas the Games-Howell post hoc test was utilized for data with heterogeneity of variances. This analysis was conducted at a significance level of p < 0.05 using SPSS 25.0. The results are presented as mean ± standard deviation (n = 3) in the figures, which were generated by Origin Pro 2021 9.8.0.200. A piecewise structural equation model (SEM) was conducted using the “piecewise SEM” package (version 2.3.0.1) with a mixed linear model in R 4.2.1 to determine the direct and indirect effects on SOC. The results were visualized by the “ggplot2” package (version 3.3.3).

3. Results

3.1. The Response of Soil Chemical Properties to RF Durations

The effects of RF durations on soil chemical properties were illustrated in Figure 2. At P1, RF2 treatment showed an insignificant change in pH (Figure 2a), while RF5 treatment significantly increased pH by 0.1. At P2, RF15 and RF30 treatments significantly enhanced pH in comparison with RM2 treatment. RF treatments were found to significantly increase the SOC content (Figure 2b), and the SOC contents were observed to follow the order of RM1 < RF2 < RF5 and RM2 < RF15 < RF30. Notably, the annual growth rates of SOC content showed an initial increase followed by a subsequent decrease. Specifically, the annual growth rates of SOC content were quantified as 0.56 g kg−1 year−1 for the 0–2-year period, 0.68 g kg−1 year−1 for the 2–5-year period, 0.37 g kg−1 year−1 for the 0–15-year period, and 0.16 g kg−1 year−1 for the 15–30-year period (Table S1). DOC contents were observed to follow the order of RM1 < RF2 < RF5 and RM2 < RF15 < RF30 (Figure 2c). Furthermore, RF was found to be beneficial in enhancing the accumulation and availability of the N (Figure 2d,e). TN content increased by 18.5% under RF5 treatment and followed the order of RM2 < RF15 < RF30 at P2. NH4+-N content increased under the RF duration prolongation, specifically showing a pattern where NH4+-N content followed the order RM1 < RF2 < RF5 and RM2 < RF15 < RF30. MBC and MBN contents exhibited a close correlation with RF durations (Figure 2f,g). RF5 treatment significantly increased MBC and MBN contents compared with RM1 and RF2 at P1; MBC and MBN contents were significantly improved by RF treatments at P2 and followed the sequence of RM2 < RF15 < RF30. RF5 treatment significantly decreased the content ratio of MBC to MBN (MBC/MBN) compared with RM1 and RF2 treatments, and this trend was also observed in the RF15 and RF30 treatments compared with the RM2 treatment (Figure 2h).

3.2. The Effects of RF Durations on the Soil Microbial Community Structure

Figure 3 illustrated the effects of RF durations on soil microbial community structure. RF5 treatment significantly increased the total PLFA content by 18.69% compared with RM1 at P1 (Figure 3a). RF15 and RF30 treatments significantly increased the total PLFA content by 32.38% and 48.55% in comparison with RM2 treatment at P2 (Figure 3a), respectively. Compared with the RM1 treatment, the RF2 treatment did not induce a significant alteration in the PLFA content of G+, whereas the RF5 treatment significantly increased the PLFA content of G+ by 13.75% (Figure 3b). RF treatments significantly increased the PLFA content of G+ at P2 (Figure 3b). RF treatments significantly promoted the PLFA content of G− compared with RM treatments at both P1 and P2, and following the order of RM1 < RF2 < RF5 and RM2 < RF15 < RF30 (Figure 3c). Additionally, RF5 treatment significantly reduced G+/G− compared with both RM1 and RF2 treatments at P1, RF30 and RF15 treatments significantly reduced G+/G− in comparison with RM2 treatment at P2, while the lowest ratio was observed in the RF30 treatment (Figure 3d). RF treatment significantly increased the PLFA content of actinomycetes compared with RM treatments, and RF5 treatment showed a higher PLFA content of actinomycetes than that in RF2 treatment (Figure 3e). RF5 and RF30 treatments showed the highest PLFA content of fungi at P1 and P2 (Figure 3f), respectively. The RF durations significantly influenced the PLFA content of bacteria, and there was a trend of RM1 < RF2 < RF5 and RM2 < RF15 < RF30 (Figure 3g). Although RF treatments increased the PLFA contents of fungi and bacteria compared with RM treatments, F/B in RF treatments showed a declining trend compared with RM treatments (Figure 3h). Specifically, RF5 treatment showed a lower F/B than that in both RM1 and RF2 treatments, while RF15 and RF30 treatments showed a significant reduction of F/B by 18.92% and 25.22% compared with RM2 treatment, respectively.

3.3. The Effects of RF Durations on Soil Enzyme Activities

BG and CBH contribute to the C cycle. In our study, RF treatments significantly affected the BG activity at P2, with the order of RF30 > RF15 > RM2 (Figure 4a). RF5 treatment showed the highest CBH activity at P1, while RF15 and RF30 treatments significantly increased CBH activity by 43.03% and 45.63% compared with RM2 treatment at P2 (Figure 4b), respectively. NAG and urease, as the key enzymes involved in the N cycle, showed an increase under the RF treatments (Figure 4c). Specifically, RF5 treatment increased NAG activity by 8.09% compared with RM1 treatment at P1, and RF15 and RF30 treatments increased NAG activity by 12.94% and 15.73% compared with RM2 at P2. Furthermore, RF treatments significantly increased urease activity, showing the pattern of RF5 > RF2 > RM1 and RF30 > RF15 > RM2 at P1 and P2 (Figure 4d), respectively.

3.4. Relationships of C Sequestration with Microbial Community Under Different RF Durations

The piecewise SEM explained 79% of the variation in C sequestration (Figure 5). RF durations indirectly regulated microbial community structure (total PLFA and F/B) by affecting the requirement of microbial nutritious (TN and DOC). The effects of microbial communities on C sequestration were delineated along two distinct mechanisms. One mechanism involved microbial biomass, which indirectly affected C sequestration through influencing the MBC (standardized effect sizes of 0.92). The other mechanism entailed a direct and significant negative impact of F/B on C sequestration (standardized effect sizes of −0.21).

4. Discussion

4.1. RF Promotes Soil Fertility

Previous studies have demonstrated that RF can enhance the soil N levels, including TN and available N [20,32]. Here, we further revealed that RF durations positively impacted TN and NH4+-N contents (Figure 2d,e). The increase in TN may be attributed to a reduction in N loss due to alterations in the food web of the RF system. Chen et al. [33] reported that rice-animal co-culture could reduce N runoff by 17.72%. Specifically, fish consume aquatic flora and fauna, pests, rice flowers, and senescent leaves in the RF system, and this consumption strategy prevents these potential N sources from being unutilized. After ingestion, a portion of the N is assimilated by the fish to support their growth, while the unassimilated N is excreted into the paddy. These secretions in the upper layers migrate to the lower soil strata through bioturbation activity of the fish [34], thus promoting the accumulation of previously difficult to utilize N sources in soil and increasing the soil TN content. Furthermore, the increase in NH4+-N content may be partly related to the excretion of fish feces, which contain approximately 75–85% of N in the form of NH4+-N [35]. Moreover, microbial-mediated organic N mineralization plays a critical role in the increase of NH4+-N content, as evidenced by the significant positive correlation between NH4+-N content and urease activity (p < 0.001, Figure S2). Consistent with our findings, Pan et al. [36] reported similar results. Urease catalyzes the hydrolysis of urea, converting organic nitrogen sources—such as fish excretions and plant residues—into NH4+-N [29]. This enzymatic process is essential for N stabilization, as NH4+-N is more strongly adsorbed onto soil colloids compared with NO3−-N [37], thereby reducing leaching losses. Furthermore, the increase in urease activity reflects the growth in microbial N demand, supporting the point that RF may promote the conversion of organic N to inorganic N [29]. Overall, the combined effects of fish excretion, bioturbation, and microbial activity enhance soil N levels in RF systems, particularly by stabilizing TN and increasing NH4+-N content.
DOC is an essential energy source for soil microorganisms and serves as a pivotal indicator of soil fertility [38,39]. The elevated level of DOC is primarily attributable to the liberation of soluble organic matter from C input or crop residues [40]. Our research found that the RF enhanced the DOC content, with the highest DOC content in RF5 and RF30 treatments at P1 and P2 (Figure 2c), respectively, suggesting that long-term RF could constantly promote the DOC content through the decomposition of organic matter. In the RF system, the increase of DOC content may be related to the production of fish excreta, rice root residues, and root exudates. Furthermore, studies have identified that flooding may accelerate the disruption of soil aggregates, thereby promoting the DOC release [41].

4.2. RF Changes the Soil Microbial Community Structure

Soil microbial community structure can be affected by various factors, including land use, fertilization regime, soil type, water status, agricultural practice, and nutrient availability [42,43,44]. According to the results from Zhao et al. [14] studies, the soil microbial diversity was similar in the RF and RM systems during the first year of farming. However, a significant change in soil microbial diversity was observed between the RF system and RM system after five years of farming. Moreover, Li et al. [20] suggested that the variations of microbial community structure in rice-fish-turtle fields require up to 12 years. In our experiment, RF5, RF15, and RF30 treatments increased the contents of total PLFA and the PLFA of G+, G−, actinomycete, fungi, and bacteria compared with RM1 and RM2 treatments (Figure 3), respectively. Notably, RF5 and RF30 demonstrated the highest biomass at P1 and P2, suggesting that prolonged RF durations could improve the soil microbial community abundance. The growth of soil microorganisms may be limited by the availability of C and N [45,46,47,48]. Our study found that DOC and TN significantly increased the total PLFA content (p < 0.05, Figure 5a). RF stimulated the growth and metabolism of microorganisms through the enhancement of soil nutrient conditions, ultimately leading to an increase in soil microbial biomass.
RF not only altered the soil microbial community abundance but also affected the microbial community composition. The F/B is an essential indicator of the relative abundance of the microbial populations and reflects the buffering capacity, as well as the potential for sustainable land use of a soil ecosystem [49,50]. Our study found that RF2 treatment insignificantly affected the F/B at P1, and RF5, RF15, and RF30 treatments significantly decreased the F/B (Figure 2h). This may be associated with the availability of substrates for microorganisms in paddy fields. The piecewise SEM results suggested that RF durations indirectly influenced F/B by affecting microbial nutrients (TN and DOC) (p < 0.005, Figure 5a). Fungi prefer substrates with a high C/N rather than those with a low ratio [51] and tend to survive better in nutrient-poor soils compared with bacteria [52]. In our study, long-term RF increased the available C and N in the soil, strengthening the dominance of bacteria, which led to a decrease in F/B. In the experiment conducted by Si et al. [53] on rice-crayfish co-culture, similar research findings were obtained, which concluded that prolonged flooding enhanced the growth of anaerobic bacteria, resulting in a lower F/B of rice-crayfish co-culture compared with RM. It is necessary to maintain a field water level of 15–25 cm after releasing the fish for aquaculture in the RF system, which leads to a diminished capacity for air exchange between the soil and the atmosphere. Such a hypoxic environment facilitated the reproduction of anaerobic bacteria, subsequently affecting the F/B.
G+ and G− have been observed to exhibit contrasting preferences for C sources, with G− showing a preference for fresh plant inputs, while G+ appears to favor older and more microbially-processed soil organic matter [54,55,56]. Our study revealed that RF5 treatment significantly decreased the G+/G− compared with RM1, with a similar trend observed in RF15 and RF30 treatments (Figure 3d), suggesting that prolonged RF durations could enhance the predominance of G−. This may be related to the increase of plant C resources from fish excrement, rice root residues, and root secretions.

4.3. RF Promotes the Soil Enzyme Activities

Soil enzymes play a key role in the process of soil nutrient cycling, and the majority of enzymes are secreted by soil microorganisms [57], such as BG, CBH, NAG, and urease. BG and CBH are classified as C-acquiring enzymes responsible for the decomposition of polysaccharides [58]. Our research showed RF5, RF15, and RF30 treatments increased BG and CBH activities compared with RM treatments (Figure 4a,b). This observation suggested that RF could enhance the ability of decomposition polysaccharides, which may be attributed to the increase of the enzyme substrates derived from the organic matter inputs, such as fish excrement, rice residues, and root secretions. NAG and urease are N-acquiring enzymes, and their substrates are chitin and urea, respectively [58]. In our study, RF5, RF15, and RF30 treatments significantly increased the NAG and urease activities (Figure 4c,d). The increase of NAG activity was associated with its substrate (chitin), which mainly originates from fungal cell walls [59,60]. The results of the mixed linear model indicate a significant positive correlation between NAG activity and fungal PLFA content (p < 0.001, Figure S3). 10–20% of fish excreta are in the form of urea [35], and continuous input of urea from fish excrement will stimulate microorganisms to produce more urease for decomposition. Bihari et al. [61] reported an increase in urease activity in the RF system in comparison with the RM system.
Heterotrophic microorganisms use organic matter as their C source and can secrete large amounts of C-acquiring and N-acquiring enzymes to degrade carbohydrates, cellulose, lignin, and other unstable C fractions [62]. Soil organic matter constitutes the precursor of MBC and energy, consisting of humus, nonhumus substances, soluble substances, and other forms of organic matter. The continual rise in organic matter within the RF system may serve as an energy source for heterotrophic microorganisms and contribute to the production and functioning of enzymes [63]. Moreover, soil organic carbon serves as the substrate for numerous soil enzymes and protects them through the formation of enzyme complexes with clay and humus [64]. Bhattacharyya et al. [23] confirmed that RF increased BG activity compared with RM, which was attributed to the higher content of unstable C in the soil of RF systems (a suitable substance for the presence of BG). In addition, Sekaran et al. [31] proved that increased returns of labile C and N sources could significantly enhance soil enzyme activities.

4.4. RF Promotes the C Sequestration

In our study, RF treatments significantly increased SOC content compared with RM treatments at P1 and P2 (Figure 2b), respectively. Specifically, RF5 and RF30 treatments were found to have the highest SOC content. These results confirmed our hypothesis and suggested that long-term RF is beneficial for soil C sequestration. Microorganisms are important regulators of the terrestrial C budget through their effects on the decomposition and incorporation of organic matter in soil [65]. SOC content is influenced both directly and indirectly by the dynamics of soil microbial communities, microbial activities, and microbial decomposition [66]. Our research supports these observations, showing that the alteration of soil microbial community structure directly and indirectly drove the SOC accumulation with different RF durations (Figure 5). Specifically, long-term RF practice enhances MBC content, thereby indirectly increasing SOC reserves. Furthermore, it enhances the bacterial dominance, which directly promotes the C sequestration.
MBC shows a rapid response to changes in agronomic management and is often used as a preliminary indicator of SOC dynamics [67]. Although MBC represents only 1% to 3% of SOC, it plays an essential role in the active C pool [68]. Our study showed that MBC serves as a significant driver of C sequestration (p < 0.05, Figure 5). This is likely attributed to the enhancement of an effective C source, which consequently promoted the development of microbial biomass. The MBC stabilization, coupled with its association with minerals or its encapsulation by precipitation with elements such as iron or silicon, reduces the SOC mineralization and thus enhances SOC storage [69].
Microbial necromass, as the main source of recalcitrant organic compounds in soil [70], contributes to organic C stocks at a level approximately three orders of magnitude higher than that of MBC [71], reaching over 50% [72]. In our experiment, the RF increased total PLFA content, which likely contributed to the SOC content enhancement. Contrary to our initial hypothesis, a lower F/B ratio promoted C sequestration in our study (p < 0.05, Figure 5). This unexpected result may be attributed to differences in carbon use efficiency (CUE) between fungi and bacteria. Specifically, a higher CUE indicates that microorganisms exhibit lower carbon dioxide emissions during the decomposition of organic matter while assimilating a greater proportion of carbon, thereby facilitating the retention of more microbial necromass carbon in the soil [73]. Previous studies have demonstrated that higher F/B was associated with reduced CUE [74,75]. Our findings are consistent with these observations, as a significant negative correlation between the F/B and SOC content (p < 0.05, Figure 5). Thus, RF enhances the rate of SOC accumulation in the short term by promoting microbial necromass C accumulation and high CUE. However, long-term RF leads to the increasing dominance of soil bacteria, which reduces CUE and, consequently, slows the rate of SOC accumulation. The SOC dynamics under different RF durations indicate that microbial abundance serves as a crucial determinant in facilitating C sequestration, and the rate of SOC accumulation was modulated by the soil microbial community composition.

5. Conclusions

Our study revealed that the SOC storage increases with the RF durations, and the differences exist between short-term and long-term RF co-culture. Although SOC storage is promoted in the short-term and long-term RF systems, the rate of SOC accumulation is higher in short-term RF systems than in long-term RF systems. Moreover, SOC storage can be regulated through the variation of soil microbial biomass and F/B; this may be due to the presence of fish activating the substrates of microbes over the farming duration, which, in turn, shifts the microbial community structure. This is characterized by an increase in microbial biomass and a lower F/B ratio, ultimately facilitating the C sequestration. Therefore, this research validates the sustainability of RF system from the perspective of soil C sequestration and provides a scientific reference for long-term RF application and widespread adoption.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/agronomy15051054/s1. Figure S1: The management practices of Rice-fish co-culture and rice monoculture modes. The beginning of the month (B), mid of the month (M), and end of the month (E); Figure S2: The mixed linear model analysis of urease activity and ammonium nitrogen. Colored lines refer to different places: red indicates Shatian (P1), and blue—green indicates Gaoliao (P2), with 95% confidence intervals in the shades. Ammonium nitrogen (NH4+-N), conditional R2 (R2c), marginal R2 (R2m); Figure S3: The mixed linear model analysis of the β-1,4-N-acetylglucosaminidase activity and the phospholipid fatty acid of fungi. Colored lines refer to different places: red indicates Shatian (P1), and blue‒green indicates Gaoliao (P2), with 95% confidence intervals in the shades. β-1,4-N-acetylglucosaminidase (NAG), conditional R2 (R2c), marginal R2 (R2m); Table S1: Growth rates of SOC.

Author Contributions

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

Funding

This study was funded by the Key-Area Research and Development Program of Guangdong Province (Grant No. 2021B0202030002); the Science and Technology Planning Project of Guangdong Province of China (Grant No. 2019B030301007); the Guangdong Provincial Special Project of Rural Revitalization Strategy (Document No. (2021) 12); the Innovation Team Construction Project of Modern Agricultural Industry Technology System of Guangdong Province (2022KJ105); and the Joint Team Project of Guangdong Laboratory for Lingnan Modern Agriculture (Grant No. NT2021010); and the National Key Research and Development Program (Grant Nos. 2024YFD2300500 and 2024YFD2300502).

Data Availability Statement

The datasets generated during and/or analyzed during the current study are available from the corresponding author upon reasonable request.

Conflicts of Interest

The authors declare no competing interests.

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Figure 1. Distribution of experimental sites in Lianshan Zhuang and Yao Autonomous County. Shatian Village (P1), Gaoliao Village (P2).
Figure 1. Distribution of experimental sites in Lianshan Zhuang and Yao Autonomous County. Shatian Village (P1), Gaoliao Village (P2).
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Figure 2. Effects of rice-fish co-culture durations on soil chemical properties. (a) pH, (b) Soil organic carbon (SOC), (c) dissolved organic carbon (DOC), (d) total nitrogen (TN), (e) ammonium nitrogen (NH4+-N), (f) microbial biomass carbon (MBC), (g) microbial biomass nitrogen (MBN), and (h) content ratio of MBC/MBN (MBC/MBN). Different lowercase letters indicate the significance among rice-fish co-culture durations at P1 and P2 (p < 0.05), respectively.
Figure 2. Effects of rice-fish co-culture durations on soil chemical properties. (a) pH, (b) Soil organic carbon (SOC), (c) dissolved organic carbon (DOC), (d) total nitrogen (TN), (e) ammonium nitrogen (NH4+-N), (f) microbial biomass carbon (MBC), (g) microbial biomass nitrogen (MBN), and (h) content ratio of MBC/MBN (MBC/MBN). Different lowercase letters indicate the significance among rice-fish co-culture durations at P1 and P2 (p < 0.05), respectively.
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Figure 3. Effect of rice-fish co-culture durations on soil microbial community structure. (a) total phospholipid fatty acid (PLFA), (b) PLFA of gram-positive bacteria (G+), (c) PLFA of gram-negative bacteria (G−), (d) PLFA ratio of G+ to G− (G+/G−), (e) PLFA of actinomycete, (f) PLFA of fungi, (g) PLFA of bacteria, and (h) PLFA ratio of fungi to bacteria (F/B). Different lowercase letters indicate the significance among rice-fish co-culture durations at P1 and P2 (p < 0.05), respectively.
Figure 3. Effect of rice-fish co-culture durations on soil microbial community structure. (a) total phospholipid fatty acid (PLFA), (b) PLFA of gram-positive bacteria (G+), (c) PLFA of gram-negative bacteria (G−), (d) PLFA ratio of G+ to G− (G+/G−), (e) PLFA of actinomycete, (f) PLFA of fungi, (g) PLFA of bacteria, and (h) PLFA ratio of fungi to bacteria (F/B). Different lowercase letters indicate the significance among rice-fish co-culture durations at P1 and P2 (p < 0.05), respectively.
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Figure 4. The effect of rice-fish co-culture durations on soil enzyme activities. (a) β-glucosidase (BG), (b) cellobiohydrolase (CBH), (c) β-1,4-N-acetylglucosaminidase (NAG), and (d) urease. Different lowercase letters indicate the significance among rice-fish co-culture durations at P1 and P2 (p < 0.05).
Figure 4. The effect of rice-fish co-culture durations on soil enzyme activities. (a) β-glucosidase (BG), (b) cellobiohydrolase (CBH), (c) β-1,4-N-acetylglucosaminidase (NAG), and (d) urease. Different lowercase letters indicate the significance among rice-fish co-culture durations at P1 and P2 (p < 0.05).
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Figure 5. Piecewise structural equation model depicting the direct and indirect effects of substrate and soil microbial community on C sequestration under different rice-fish co-culture durations. (a) piecewise SEM on SOC, (b) standardized effects on SOC. The standardized path estimates are provided next to each path with line thickness scaled based on the magnitude of the estimate. Red and blue arrows indicate significant positive and negative relationships (p < 0.05), respectively, with rice-fish co-culture (RF) durations, dissolved organic carbon (DOC), total nitrogen (TN), PLFA ratio of fungi to bacteria (F/B), soil organic carbon (SOC), conditional R2 (R2c), marginal R2 (R2m).
Figure 5. Piecewise structural equation model depicting the direct and indirect effects of substrate and soil microbial community on C sequestration under different rice-fish co-culture durations. (a) piecewise SEM on SOC, (b) standardized effects on SOC. The standardized path estimates are provided next to each path with line thickness scaled based on the magnitude of the estimate. Red and blue arrows indicate significant positive and negative relationships (p < 0.05), respectively, with rice-fish co-culture (RF) durations, dissolved organic carbon (DOC), total nitrogen (TN), PLFA ratio of fungi to bacteria (F/B), soil organic carbon (SOC), conditional R2 (R2c), marginal R2 (R2m).
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MDPI and ACS Style

Sun, D.; Zheng, H.; Shi, Z.; Zhang, J.; Jia, Q.; Liu, X.; Zhao, M.; Chen, Y.; Chen, Q.; Luo, M. Rice-Fish Co-Culture Promotes Soil Carbon Sequestration Through Alterations in Soil Microbial Community Structure. Agronomy 2025, 15, 1054. https://doi.org/10.3390/agronomy15051054

AMA Style

Sun D, Zheng H, Shi Z, Zhang J, Jia Q, Liu X, Zhao M, Chen Y, Chen Q, Luo M. Rice-Fish Co-Culture Promotes Soil Carbon Sequestration Through Alterations in Soil Microbial Community Structure. Agronomy. 2025; 15(5):1054. https://doi.org/10.3390/agronomy15051054

Chicago/Turabian Style

Sun, Daolin, Hongjun Zheng, Zhaoji Shi, Jiaen Zhang, Qi Jia, Xing Liu, Min Zhao, Yuting Chen, Qi Chen, and Mingzhu Luo. 2025. "Rice-Fish Co-Culture Promotes Soil Carbon Sequestration Through Alterations in Soil Microbial Community Structure" Agronomy 15, no. 5: 1054. https://doi.org/10.3390/agronomy15051054

APA Style

Sun, D., Zheng, H., Shi, Z., Zhang, J., Jia, Q., Liu, X., Zhao, M., Chen, Y., Chen, Q., & Luo, M. (2025). Rice-Fish Co-Culture Promotes Soil Carbon Sequestration Through Alterations in Soil Microbial Community Structure. Agronomy, 15(5), 1054. https://doi.org/10.3390/agronomy15051054

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