CORVALLIS, Ore. – Forest modeling by Oregon State University scientists shows that a site’s productivity – an indicator of how fast trees grow and how much biomass they accumulate – is the main factor ...

Researchers have shown how random forest algorithms can be applied to complex ecological models to uncover the mechanisms driving system behavior. By analyzing a stage‑structured consumer‑resource ...

Development of forest and landscape modeling approaches / David J. Mladenoff and William L. Baker -- Modeling the competitive dynamics and distribution of tree species along moisture gradients / John ...

The study, published in Forest Ecosystems, presents a refined update to the 3-PG (Physiological Processes Predicting Growth) model. Its major innovation is adding a carbon storage pool specifically ...

Random forest regression is a tree-based machine learning technique to predict a single numeric value. A random forest is a collection (ensemble) of simple regression decision trees that are trained ...