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稻渔复合系统水体细菌群落结构的时空变化和组装机制

Spatiotemporal variations and assembly mechanisms of bacterial communities in the rice-fish water aquaculture systems

  • 摘要: 为探究池塘-稻田复合种养系统循环水体中细菌群落的动态变化和演替规律,将复合系统分为进水段、田间段和出水段3部分,每段设2个采样点,于2022年4—8月每月采样1次。采用16S rRNA高通量测序技术分析循环水体浮游细菌的群落结构特征,研究细菌共现网络及其组装机制,揭示细菌群落在池塘尾水净化过程中的相互作用和演化趋势。结果表明,稻田对池塘尾水中的TP、TN、NH3-N、NO3-N、NO2-N的平均去除率分别为65.5%、47.3%、51.2%、56.4%和53.3%,显著改善了水质;细菌群落结构在时间维度上表现出显著变化(P<0.05),在空间维度上相对稳定,但群落均匀度在局部区域有所波动;田间段细菌群落与环境因子的相关性最为显著,且其群落互作关系最为复杂,细菌显现出特殊的群落特征;NH3-N、NO3-N和NO2-N等氮素因子是驱动细菌群落结构变化的主要因素;随着水流方向,随机过程在细菌群落组装中的作用逐渐增大。研究结果可为稻渔共作系统的优化与管理提供科学依据和理论支持。

     

    Abstract: Sustainable aquaculture has gained much attention in recent years. It is still lacking in the ecological dynamics of the microbial communities in the pond-rice field recirculating systems. The integrated systems can combine aquaculture with the constructed wetlands in the nutrient cycling and water quality. However, only a little is known about the succession of the microbial communities, their interaction patterns, and the process shaping their assembly over time and space. In this study, a systematic investigation was carried out to explore the spatiotemporal variation in the planktonic bacterial communities in such systems. An attempt was also made on their responses to environmental changes and the relative contributions of the deterministic and stochastic factors in the community assembly. A representative rice–fish co-culture system was selected as the experimental model. The recirculating water flow was divided into three functional zones: the inlet section (receiving nutrient-rich pond effluent), the field section (a rice paddy wetland functioning as a biofilter), and the outlet section (a discharge area with reduced nutrient concentrations). Two fixed sampling sites were established in each zone. The water samples were collected monthly in the peak period of the rice cultivation and fish farming from April to August 2022. Temporal dynamics were captured after sampling. High-throughput sequencing targeting the 16S rRNA gene was employed to identify the bacterial taxa. The community composition, richness, and evenness were assessed after comprehensive bioinformatic and statistical analysis. Furthermore, the alpha and beta diversity indices, principal coordinate analysis (PCoA) with Bray–Curtis dissimilarity, and canonical correspondence analysis (CCA) were utilized to explore the relationships between bacterial communities and environmental variables. In addition, the bacterial co-occurrence networks were constructed to examine the microbial interaction patterns. Ecological assembly was then inferred using both neutral community models and niche-based frameworks. The relative influence of the stochastic and deterministic factors was evaluated to shape the bacterial community structure. The results indicated that the rice field and constructed wetland played a crucial role in the nutrient removal and water quality. The average removal rates of the total phosphorus (TP), total nitrogen (TN), ammonia nitrogen (NH3-N), nitrate nitrogen (NO3-N), and nitrite nitrogen (NO2-N) were 65.5%, 47.3%, 51.2%, 56.4%, and 53.3%, respectively, indicating the strong purification of the system. Temporally, there was a significantly seasonal variation in the composition of the bacterial community (P<0.05), particularly in response to the environmental gradients, such as the temperature and nutrient concentrations. Spatially, the overall structure of the bacterial community remained relatively consistent across the three sections; However, the bacterial taxa shared the localized changes in the relative abundance and community evenness. Proteobacteria, Actinobacteria, and Bacteroidetes were the dominant phyla in most samples. Co-occurrence network analysis revealed that the field section also exhibited the most complex network of the bacterial interaction, indicating the high modularity, centrality, and clustering coefficients. There was the strong environmental filtering and pronounced ecological niche differentiation in the rice wetland. The environmental variables, NH3-N, NO3-N, and NO2-N were measured to identify them as the key driving factors on the bacterial community shifts. Moreover, the ecological modeling showed a gradual increase in the contribution of the stochastic factors along the direction of water flow. There was a shift from the predominantly deterministic assembly near the inlet to the more random community assembly downstream. The environmental filtering intensity was reduced to increase the microbial dispersal or ecological drift. In conclusion, this finding can provide a comprehensive overview of the spatiotemporal patterns and ecological assembly of the bacterial communities in an integrated rice-fish farming system. The theoretical insights can be offered to understand the influence of the environmental factors on the bacterial community structure in the recirculating agricultural wetlands. As such, the microbial community can also be optimized to support the ecological design and management of the integrated rice-fish farming systems.

     

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