Researchers combined forest inventory data, satellite observations, and machine learning to estimate tree density across North America and evaluate the uncertainty of those estimates. The study suggests the continent contains between 339 billion and 514 billion trees with DBH＞10 cm and shows that estimates can vary substantially depending on forest definitions and tree size thresholds. The framework provides a consistent approach for large-scale forest monitoring, biodiversity assessment, and carbon accounting.

Researchers from the University of Georgia and the USDA Forest Service evaluated four strategies for predicting future tree diameters for "unobserved" species. They found that all four strategies can produce reliable predictions. However, approaches that incorporate species-specific information, such as post-hoc calibration using at least one repeated measurement or grouping rare species into an "others" category, tend to provide more precise results. The study offers practical guidance for forest managers working in species-rich tropical forests, where rare and unobserved species are common.