The Chinese sturgeon (Acipenser sinensis), designated as a Class I Protected Species in China and classified as Critically Endangered (CR) on the IUCN Red List, remains at risk despite expanding artificial breeding efforts. While stock enhancement programs have successfully increased captive populations, persistent health challenges in both broodstock and juveniles continue to compromise reproductive efficiency and post-release survival, underscoring the urgent need for a non-invasive health assessment system capable of early anomaly detection, timely warnings, and effective intervention. To address these critical needs, our research team has conducted systematic investigations across three key aspects: (1) Characterization of physiological responses to multi-dimensional stressors, (2) Identification of health biomarkers for early warning, (3) Quantification of health-associated behavioral characteristics. Our future research will focus on integrating big data analytics with multi-modal sensing technologies to establish an intelligent healthy monitoring system. This AI-driven platform will combine wearable biosensors (equipped with microsensors, BIA, and eDNA sampling capabilities) with comprehensive biomarker and behavioral databases. We aim to develop a predictive health management system that transforms current reactive approaches into proactive, data-driven conservation strategies for this endangered species. The resulting Digital Sturgeon Management System is expected to provide unprecedented precision in monitoring physiological-behavioral responses while creating scalable methodologies applicable to other threatened aquatic species.

Chinese sturgeon,Health assessment,Non-invasive monitoring,Healthy biomarkers,Intelligent early-warning system