Estimation of the biomass and carbon in Cupressus lusitanica Mill. trees in Costa Rica

 

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Autores: Fonseca González, William, Rojas Vargas, Marilyn, Villalobos Chacón, Ronny, Alice Guier, Federico
Formato: artículo original
Estado:Versión publicada
Fecha de Publicación:2023
Descripción:[Introduction]: Forest plantations are an important carbon sinks and reservoirs while providing other important environmental goods and services. [Objective]: In this research, we developed models to estimate the biomass and carbon content of Cupressus lusitanica Mill trees and its components or fractions, 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 fractions 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 aerial 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 content, are easy to use, and become useful low-cost tools to quantify the ecologic and greenhouse gas emission mitigation functions of these forests.
País:Portal de Revistas UNA
Institución:Universidad Nacional de Costa Rica
Repositorio:Portal de Revistas UNA
Lenguaje:Español
Inglés
OAI Identifier:oai:ojs.www.una.ac.cr:article/18330
Acceso en línea:https://www.revistas.una.ac.cr/index.php/ambientales/article/view/18330
Access Level:acceso abierto
Palabra clave:Allometry;
Costa Rica;
biomass expansion factors;
regression models;
environmental services.
Alometría;
factores expansión biomasa;
modelos de regresión;
servicios ambientales.
Alometria;
fatores de expansão da biomassa;
modelos de regressão;
serviços ambientais.