The Regenerative Compute Protocol: Using Agricultural Ecosystem Recovery Signals to Govern the Energy Consumption and Workload of Local Artificial Intelligence Systems

This conceptual research paper introduces the Regenerative Compute Protocol (RCP), a proposed cyber-physical framework that allows measured agricultural ecosystem conditions to govern discretionary artificial intelligence workloads. Unlike conventional carbon-aware computing, RCP incorporates soil, crop, water, biodiversity and local energy indicators into an uncertainty-adjusted ecological reserve. This reserve determines when nonessential computing may run, slow down, migrate or be deferred while protecting critical agricultural services. The paper presents the system architecture, mathematical formulation, ecological indicator model, workload classification, safety requirements and experimental methodology and falsification criteria. It proposes a multi-site randomized crossover study comparing conventional, carbon-aware and regenerative computing schedules. This publication presents a conceptual framework and prospective research protocol. It does not report completed field trials or experimentally validated performance.