Abstract:

Against the backdrop of the national strategic framework for ecological conservation and high-quality development in the Yellow River Basin, the sustainability and health of agricultural ecosystems in the Yellow River Irrigation Districts have become a critical concern, particularly regarding soil quality and micro-ecological environment of paddy fields. These districts, serving as vital agricultural production bases, face increasing challenges related to soil degradation and micro-ecological imbalance due to long-term intensive cultivation, water resource fluctuations, and varied land management practices. Within this complex environment, soil fungi, as fundamental components of the terrestrial ecosystem, play indispensable roles in nutrient cycling, organic matter decomposition, soil structure formation, and plant health maintenance, making them excellent biological indicators for assessing soil health and ecosystem functioning. This comprehensive study aims to systematically investigate the spatial differentiation patterns of soil fungal communities and their environmental drivers in the paddy fields of Dongying City’s Yellow River Irrigation District through an integrated approach combining high-throughput sequencing, advanced statistical analysis, and spatial assessment techniques. Based on a carefully designed stratified random sampling strategy following the “irrigation district×soil type” framework, we established 48 representative soil sampling sites across 12 major irrigation districts, ensuring geographical representativeness and accounting for variations in land use patterns, distance to irrigation canals, and farming practices. At each sampling site, surface soil samples (0‒20 cm depth) were collected using a five-point mixing method during the same agricultural season and immediately preserved at low temperatures for subsequent analysis. Our methodological approach encompassed comprehensive soil physicochemical characterization using standardized protocols: Soil pH was measured potentiometrically in a 1꞉2.5 soil-water suspension; organic matter content was determined by the Walkley-Black method; soil moisture content was measured by the gravimetric method; total nitrogen was analyzed using the Kjeldahl method; available phosphorus was extracted with 0.5 mol·L⁻¹ NaHCO₃ and determined by molybdenum-antimony anti-spectrophotometry; available potassium was extracted with ammonium acetate and measured by flame photometry; while heavy metals including Cu, Cd, Pb, Cr, As, Hg, Ni, and Zn were quantified using inductively coupled plasma mass spectrometry after digestion with HNO₃-HCl-HF mixed acid, ensuring high sensitivity and accuracy. For fungal community analysis, we employed Illumina MiSeq high-throughput sequencing targeting the fungal ITS1 region, with total genomic DNA extracted from soil samples and amplified using specific primers. The raw sequencing data were processed through the QIIME2 pipeline, incorporating rigorous quality filtering, denoising, chimera removal, and clustering of sequences into operational taxonomic units at 97% similarity threshold, followed by taxonomic assignment against the UNITE database and functional guild prediction using the FUNGuild database to infer ecological roles. Our multidimensional analytical framework included calculation of alpha diversity indices, multivariate statistical methods such as redundancy analysis and co-occurrence network analysis to explore fungus-environment relationships, and spatial analysis using the Geographic Information System technology to visualize and interpret spatial patterns. The results revealed substantial spatial heterogeneity in soil physicochemical properties across the irrigation districts: soil moisture content varied from 17.9% to 28.6%, with highest values in Yihao and Wangzhuang and lowest in Luzhuang; soil pH ranged from 7.29 to 8.02, indicating slightly alkaline conditions throughout the study area; organic matter content showed considerable variation (28.6‒55.3 g·kg⁻¹) with Yihao, Shibahu, and Shuanghe districts exhibiting higher levels; nutrient availability displayed distinct spatial patterns with available phosphorus ranging from 29.6 to 104.6 mg·kg⁻¹ and available potassium from 20.6 to 35.9 mg·kg⁻¹; while heavy metal analysis identified Cd, Ni, and Hg as elements of particular concern, with Cd concentrations consistently exceeding the national standard across all districts. Fungal diversity indices exhibited significant spatial variation, with Shannon diversity index ranging from 1.85 to 4.13, observed species count varying from 425.3 to 674.7, and distinct phylum-level distributions showing Ascomycota dominance across most districts, particularly in Luzhuang, Caodian, and Dongshuiyuan, while Basidiomycota showed notably high relative abundance in Guanjia and Mawwan. The predicted functional composition revealed saprotrophic fungi as the dominant functional group across all districts with highest abundances in Shuanghe and Yihao, multifunctional fungi showing considerable variation with notably high relative abundances in Shuanghe, Shibahu, and Yihao, symbiotic fungi exhibiting higher proportions in Mawwan and Wuqi, and pathotrophic fungi maintaining relatively stable levels across districts. Co-occurrence network analysis identified soil pH, organic matter, available potassium, and Cd concentration as significant factors influencing fungal community composition and distribution, with specific taxonomic groups showing distinct environmental responses: Ascomycota demonstrated significant positive correlations with available potassium in several districts, while Basidiomycota exhibited variable responses to heavy metals. Crucially, our analysis revealed that fungal communities in districts with higher heavy metal concentrations tended to have more multifunctional fungi, suggesting potential adaptive strategies to environmental stress. The spatial patterns of fungal communities reflect complex interactions between environmental factors and microbial ecology, where the dominance of saprotrophic fungi highlights their fundamental role in organic matter decomposition and nutrient cycling, while the elevated abundances of multifunctional fungi in districts with higher heavy metal concentrations indicate that environmental stress may select for taxa with broader metabolic capabilities and ecological plasticity, aligning with ecological theory predicting that stressful environments favor generalist species with multiple functional traits. The spatial variation in symbiotic fungi appears linked to specific agricultural practices including rice cultivation patterns and crop rotation systems that create distinct rhizosphere microenvironments conducive to fungal-plant mutualisms, while the relative stability of pathotrophic fungi across districts may indicate a baseline level of plant-pathogen interactions potentially regulated by overall soil health and management practices. The identified key environmental drivers represent both resource availability and stress factors that collectively shape fungal community assembly, underscoring the multifactorial nature of microbial community regulation in agricultural landscapes and highlighting the importance of considering both nutrient dynamics and contaminant pressures in soil management. This study provides compelling evidence that fungal community structure, diversity, and functional composition vary significantly across irrigation districts, primarily driven by spatial gradients in soil properties, with the prevalence of multifunctional fungi in areas with higher environmental stress suggesting potential adaptive mechanisms of soil fungal communities to complex agricultural environments. These insights substantially contribute to our understanding of soil microbial ecology in irrigated agricultural systems and provide a scientific basis for developing targeted soil management strategies, while also establishing foundational knowledge for future research directions including longitudinal studies to track temporal dynamics and manipulative experiments to establish causal relationships between specific management practices and fungal community responses, ultimately supporting the development of more sustainable agricultural practices in the Yellow River Basin and similar irrigated agroecosystems worldwide.

Key words: Yellow River diversion irrigation area, soil fungi, spatial differentiation, influencing factors

摘要：

在黄河流域生态保护和高质量发展战略背景下，引黄灌区水田的土壤质量与微生态环境问题日益突出。作为生态系统中的关键组成，土壤真菌在养分循环与生态调节中发挥重要作用，是衡量水田健康水平的重要生物学指标。基于东营市12个典型灌区的48个土壤样本，采用Illumina MiSeq高通量测序与土壤理化分析方法，系统揭示了真菌群落的多样性特征、空间分异规律及其驱动机制。结果显示，1）真菌Shannon多样性指数在1.85－4.13之间，子囊菌门（Ascomycota）平均占比为54.6%，担子菌门为（Basidiomycota）19.7%，罗氏菌门（Rozellomycota）为8.2%。2）土壤pH值（7.31－8.95）、有机质（8.52－21.46 g·kg⁻¹）、速效钾（48.3－186.7 mg·kg⁻¹）及Cd、Ni、Hg等重金属呈现显著空间梯度，奠定了真菌群落的多样性格局。3）真菌群落结构与功能型构成在不同灌区间差异显著，腐生型和复合功能型真菌为主导类型，反映出环境因子与耕作管理的复合作用。4）共现网络分析表明，pH、有机质、速效钾与Cd是驱动真菌群落演替的关键因子（p<0.05）。该研究揭示了引黄灌区土壤微生态系统的空间响应机制，为精准改善水田质量和绿色农业管理提供了理论支持与技术路径。

关键词: 引黄灌区, 土壤真菌, 空间分异, 影响因素