Improving Carbon Estimation of Large Tropical Trees by Linking Airborne Lidar Crown Size to Field Inventory

Quantifying tropical aboveground biomass (agb) is an outstanding challenge that requires knowledge on the 3D structure of forests. Recent studies suggest that the uncertainty in estimating agb of large trees is significantly reduced if tree height and crown size are accounted for in addition to the traditional trunk diameter and wood density. Due to the fact that field inventory techniques are not adapted to characterize the 3D forest structure, crown size metrics (e.g. height and radius) are commonly estimated as a function of trunk diameter using allometric models with limitations in explaining crown variability. Airborne lidar techniques have the potential for characterizing tree height and crown size but are not adapted to estimate trunk diameter, which is a strong predictor of agb. Here, we investigate the synergy of field inventory and airborne lidar techniques to characterize the forest structure by assessing the uncertainty introduced by the field-based allometric models in the estimation of agb at the tree-level. We focus in 1454 large individual trees (trunk diameter > 60 cm) located within the La Selva Biological Station for which we dispose of field observations (trunk diameter and wood density) and lidar derived metrics (tree height and crown radius). We show that the field-based allometric models overestimate tree height and underestimate crown radius. As a result, the allometric approach overestimates the tree-level agb in 0.8 Mg when considering the 1454 individuals and the errors can reach more than 50% of the agb of individual trees. These errors on the large trees agb highly impact on the plot-level results and then propagate to the estimation of carbon stocks at the regional and national-levels.