From Hive Sensors to Environmental DNA: Toward a Systems Biology Framework for Honeybee-Based Early Warning of Colony and Ecosystem Health

) serve as biological sentinels because their foraging behavior links colony health to environmental conditions. Traditional hive inspections are invasive, observer-dependent, and often detect problems only after symptoms appear. This review synthesizes advances in precision beekeeping, environmental DNA (eDNA) metabarcoding, exposomics, and artificial intelligence to propose the Honeybee-Based Early Warning System (H-BEWS), a unified framework that integrates digital sensors, molecular and chemical monitoring, and ecological data into a predictive early warning system for both colony and ecosystem health. By linking anomalies detected by hive sensors to targeted molecular and chemical analyses, H-BEWS enables proactive interventions and environmental surveillance, supporting a One Health perspective. Unlike previous reviews that focus on individual technologies, H-BEWS emphasizes multi-layered integration, predictive risk assessment, and ecosystem-level insights, providing a novel conceptual framework for early detection of colony stress and environmental hazards. The approach offers practical applications for beekeepers, researchers, and policymakers by converting real-time data into actionable insights and informing management decisions. Challenges include sensor standardization, data integration, AI validation, and equitable access for small-scale beekeepers. Future directions will focus on real-time sequencing, multimodal AI models, digital twin creation, and the development of global surveillance networks. H-BEWS demonstrates how an integrative, multi-layered approach can transform honeybee colonies into living biosensors, providing actionable insights for both apiculture management and ecosystem monitoring.