TreeNet is an international monitoring and research network that links research findings from carbon flux sites with dendrometer data across entire landscapes to better understand forest ecosystem responses to climate change. A continuous stream of microclimate and tree physiology data provides real-time insights into tree water relations and growth dynamics. The ORD project is developing a machine learning model that integrates with the real-time TreeNet data collection infrastructure, as illustrated in the figure. The model automatically fills gaps in measured time-series data, enabling TreeNet users to work with complete and consistent datasets.