Abstract

(Introduction):  Forest tree plantations are an important carbon sink and reservoir while providing other important environmental goods and services.

(Objective):  In this research, we developed models to estimate biomass and carbon for Cupressus lusitanica Mill trees and its components in forest plantations in Costa Rica.

(Methodology):  Through the destructive sampling of 43 trees, a sample of each component was obtained to determine dry matter and carbon content. The models were built through linear regression analysis and ordinary least squares, using the normal diameter as the independent variable. Models were selected through the weighted sum of the calculated statistics and the graphical analysis of the residuals.

(Results):  The coefficient of determination (R2) was greater than 83.8 % and the estimation error or bias was less than 7.2 %. The leaf and root fraction were more difficult to model, given their lower fit and higher error. The stem represents 61.7 % of total tree biomass, the branches 17.1% and the roots 9.1 %. The biomass expansion factor was 1.54 (1.3 and 1.24 for branches and foliage) and 1.12 for roots.

(Conclusions):  Allometric models accurately predict biomass and carbon, are easy to use, and are useful tools to quantify the ecologic and greenhouse gas emission mitigation functions of these forests.

Keywords: allometry; Costa Rica; biomass expansion factors; regression models; environmental services