A LiDAR-Based Method for Incorporating Foliar Biomass in Aboveground Carbon Estimates in Tropical Forest Enrichment Plantations

Accurately quantifying aboveground biomass (AGB) in tropical forest enrichment plantations remains challenging, particularly in managed regenerating stands where tree crown architecture, size structure, and species composition differ from the datasets used to calibrate classical allometric equations. Here, we assess whether AGB in tropical forest enrichment plantations can be estimated more accurately by combining tree-specific woody volume reconstructed from mobile laser scanning (MLS) with an explicit foliar-biomass component. We combined destructive measurements from 83 trees with high-resolution MLS point clouds to quantify biomass components, calibrate leaf-mass models, and assess the contribution of foliage to total AGB. Stems accounted for most of the biomass (65%), whereas leaves contributed only 3% on average. Among the models tested, Model 3, which included DBH, projected crown area, and wood density, showed the best performance (R² = 54.4%; RMSE = 2.43 kg). The main gain relative to regional (-20.4%) and pantropical (-25.6%) allometric equations came from the use of MLS-derived woody volume combined with species wood density, whereas the inclusion of predicted leaf biomass provided a moderate additional correction to the remaining bias. These results highlight the importance of canopy structure for biomass estimation in enrichment plantations and managed regenerating stands and support the use of LiDAR data as a robust alternative for AGB assessment in this context.