Abstract: The oxygen content in the soil of tree root zones is a crucial environmental factor influencing the growth of trees. The study aimed to develop a novel sensor system for monitoring oxygen content in tree xylem and sap flow velocity, with the goal of investigating the relationship between oxygen levels in the root zone soil and those in the water transfer pathway. This research sought to address the limitations of direct soil oxygen measurements, which are often hindered by the complex spatial distribution of oxygen. By leveraging the dynamics of water movement within trees, the study provided a technical foundation for optimizing tree growth environments and enhancing water-oxygen management. A composite sensor was developed based on fluorescence quenching and thermal diffusion sap flow measurement principles to simultaneously detect oxygen content in tree xylem and sap flow velocity. Calibration experiments were conducted to ensure accuracy, with temperature correction applied to minimize environmental interference. The sensor's performance was evaluated through outdoor comparative tests against commercial fiber-optic oxygen sensors and sap flow sensors. Data from the sensor were integrated with micrometeorological parameters and analyzed using a tree water uptake model and a root-soil oxygen diffusion model to derive oxygen distribution patterns at different root depths. The calibration results demonstrated the sensor's high precision, with relative errors of less than 1.34% for oxygen content measurements below 21% and less than 5% for sap flow velocity. Outdoor comparative tests further validated the sensor's performance, showing strong correlations with commercial sensors. The correlation coefficients were 0.947 for oxygen content and 0.958 for sap flow velocity, confirming the sensor's reliability and accuracy. The integration of sensor data with micrometeorological parameters, such as temperature and humidity, enabled the derivation of oxygen distribution patterns at various root depths. The analysis revealed that oxygen content decreased with increasing root depth, reflecting the challenges of oxygen diffusion in denser soil layers. For example, oxygen levels in the upper root zone were significantly higher than those in deeper layers, highlighting the impact of soil structure on oxygen availability. The sensor system also captured temporal variations in oxygen content, showing fluctuations corresponding to changes in soil moisture and temperature. These findings provided detailed insights into the dynamic interplay between soil oxygen availability and tree physiological processes. By linking oxygen levels in the root zone to those in the water transfer pathway, the study demonstrated the sensor's ability to monitor root zone oxygen environments effectively. This capability is crucial for understanding how oxygen availability influences tree growth and health, particularly in environments where soil oxygen is a limiting factor. The results also underscored the potential of the sensor for large-scale applications, such as forest ecosystem monitoring and precision agriculture, where real-time data on water and oxygen dynamics can inform management decisions. Overall, the study highlighted the sensor's potential as a reliable tool for advancing research on tree physiology and optimizing growth environments. The study successfully developed and validated a composite sensor system for monitoring oxygen content and sap flow velocity in tree xylem, providing a reliable tool to investigate root zone oxygen dynamics. By linking oxygen levels in the root zone to those in the water transfer pathway, the research offers a scientific basis for optimizing tree growth environments and improving water-oxygen management. The findings highlight the sensor's potential for dynamic monitoring of root zone oxygen, enhancing tree health and productivity. This advancement addresses the limitations of traditional soil oxygen measurement methods and opens new research avenues into water-oxygen interactions in tree physiology. Future applications include forest ecosystem monitoring, precision agriculture, and urban tree management, supporting sustainable environmental practices.