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Microbial Community Assembly Rules and Predictive Modeling Frameworks

Agricultural Microbiology

Microbial Community Shifts During Crop Rotation

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Temporal Dynamics of Bacterial Community Succession Patterns Fungal Network Restructuring Under Legume-Cereal Rotation Systems Microbial Functional Gene Expression Profiles Across Rotation Transitions Phage-Bacteria Coevolutionary Dynamics in Rotational Agroecosystems Root Exudate Chemistry Drives Microbial Selection and Assembly Mechanisms Pathogenic Microorganism Population Control Through Rotation-Induced Competition Soil Organic Matter Decomposition Kinetics and Microbial Enzyme Production Microbial Metabolite Production and Plant Immunity Enhancement Pathways Horizontal Gene Transfer and Antibiotic Resistance Gene Dynamics in Rotation

Agricultural Microbiology › Microbial Community Shifts During Crop Rotation

Microbial Community Assembly Rules and Predictive Modeling Frameworks

This research develops quantitative assembly rules and predictive algorithms that forecast microbial community composition changes based on crop type, soil properties, and environmental variables using machine learning and ecological modeling. The contribution establishes a theoretical framework for optimizing crop rotation designs that achieve targeted microbial community states.

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