Spatial Heterogeneity in Soil Microbial Communities Impacts Their Suitability as Bioindicators for Evaluating Productivity in Agricultural Practices.

Soil microorganisms are increasingly recognized as critical regulators of farmland soil fertility and crop productivity. However, the impacts of spatial heterogeneity in soil microbial communities on bioindicators for evaluating agricultural practices remain poorly understood and warrant further validation. Through field experiments, this study investigated the differential effects of agricultural practice treatments on soil properties and bacterial communities between two main farmland soil compartments: intra-row and inter-row. Additionally, we explored the potential correlations between key taxa and soil properties, as well as maize biomass. Results revealed marked disparities in soil properties, bacterial community compositions, and co-occurrence network patterns between intra-row and inter-row soils. Agricultural practice treatments exerted significant impacts on bacterial community structures and network topological features in both intra-row and inter-row soils. Subsequent correlation analysis demonstrated strong relationships between soil properties and most keystone species. In addition, 42 and 41 indicator species were identified in intra-row and inter-row soils, respectively, including shared genera such as Solirubrobacter, Blastococcus, Iamia, Conexibacter, and Lysobacter. Notably, 22 key indicator species in intra-row soils displayed significant positive/negative correlations with maize biomass, whereas only 4 key indicator species showed negative correlations in inter-row soils. These findings highlight differential responses of bacterial communities to agricultural practices in distinct soil compartments. The intra-row soils harbored more bacterial taxa significantly associated with maize biomass, while the inter-row soils better reflected the effects of agricultural interventions. This study confirms the spatial variability of microbial communities as effective bioindicators for evaluating agricultural practice strategies. Identification of compartment-specific indicators provides novel microbiological insights into supporting precision agriculture practices.