Tropical forests are home to an astonishing number of tree species, but many of them are rare. This diversity poses a major challenge for forest researchers who need to predict future tree growth: how do you build a growth model for a species you have barely seen before?
A new study from researchers at the University of Georgia and the U.S. Forest Service provides answers. Published in Forest Ecosystems , the study evaluates four different strategies for projecting tree diameters for "unobserved" species that were not included when a growth model was originally developed.
Using 20 years of forest inventory data from Puerto Rico and the U.S. Virgin Islands, the team tested four common approaches:
Approach I —Fixed-effects only predictions
Approach II —Post-hoc species-specific adjustments
Approach III —Separate models with/without species effects
Approach IV —Hybrid data grouping with mixed modeling
The results showed that all four strategies can reliably project future tree diameters for new species . However, approaches that incorporate species-level information tended to produce more precise predictions.
Among the four strategies, the researchers suggest that post-hoc calculation of species-specific adjustments (Approach II) is particularly useful because predictions can be calibrated. The trade-off is that this method requires at least one repeated measurement for the new species.
For situations where no repeated measurements are available, the study found that grouping rare species into an "others" category (Approach IV) also works well. The researchers determined that a threshold of 25 observations per species was optimal for defining which species should be grouped together (i.e., species with fewer than 25 observations were grouped into an “others” group).
The study also revealed broader patterns in Caribbean forest growth. Trees in Puerto Rico generally showed greater diameter growth than those in the U.S. Virgin Islands, likely reflecting differences in climate and forest conditions. Moist and wet forests tended to support faster growth than dry forests, while forest diversity and competition among trees also influenced long-term growth rates.
According to the research team, improving tree growth prediction is becoming increasingly important as Caribbean forests face intensifying environmental pressures, including stronger hurricanes, prolonged droughts, and climate change.
"This work provides a working example for selecting the proper methodology to handle rare species," said Sheng-I Yang, the lead author of the study. "That's critical for the continuous monitoring of diverse and vulnerable forest resources, not just in the Caribbean, but in tropical forests worldwide."
As climate change and more frequent hurricanes threaten tropical forests, the ability to accurately project tree growth becomes increasingly important for predicting forest recovery, carbon storage, and ecosystem resilience. The study suggested that further research is needed to evaluate the proposed methods across different forest types and environmental conditions in other tropical forests.
D OI Link:
https://doi.org/10.1016/j.fecs.2026.100458
Forest Ecosystems
Examining strategies to project tree diameter for unobserved species in diverse tropical forests using mixed-effects models
7-Apr-2026