Using a large dataset compiled from studies over the years covering 23 tree species, we developed methods to estimate total and components (stem, bark, branch, and foliage) of aboveground live tree biomass. Missing components in the dataset were imputed using species-specific or generalized (species combined into softwood and hardwood groups) Dirichlet imputation. Geometric means of the imputed stem wood proportions were 8% and 9% higher than the observed geometric mean of stem wood proportions in softwood and hardwood species, respectively. For other components, the differences were within 1%. On average, the component ratio method (CRM), used for the official United States forest carbon inventories, underestimated the aboveground biomass (AGB, kg) predictions by 3.7% with a very wide range (–70.3% to 31.6%). Compared with the CRM approach, equations developed in this study reduced RMSE of AGB by as much as 145.0%. On average, new equations reduced RMSE in predicting individual-tree AGB by 15.5% compared with the CRM approach and by 3.9% compared with a calibration of CRM AGB. Predicting AGB as a function of stem volume was not as accurate as using direct AGB equations. Generalized component ratio equations may be suitable for the stem wood component but were highly biased for other components.
Poudel, Krishna P.; Temesgen, Hailemariam; Radtke, Philip J.; Gray, Andrew N. 2019. Estimating individual-tree aboveground biomass of tree species in the western U.S.A.. Canadian Journal of Forest Research. 49(6): 701-714. https://doi.org/10.1139/cjfr-2018-0361.