HOW TO ESTIMATE BLACK WATTLE ABOVEGROUND BIOMASS FROM HETEROSCEDASTIC DATA?

Autores

  • Thiago Wendling Gonçalves de Oliveira Universidade Federal do Paraná
  • Vinícius Morais Coutinho Universidade Federal do Paraná
  • Luan Demarco Fiorentin Universidade Federal do Paraná
  • Mateus Niroh Inoue Sanquetta Universidade Federal do Paraná
  • Carlos Roberto Sanquetta Universidade Federal do Paraná
  • Ana Paula Dalla Corte Universidade Federal do Paraná

DOI:

https://doi.org/10.5380/rf.v51i1.65236

Palavras-chave:

Simultaneous adjustment, nonlinear regression, weighted regression, black wattle, allometric models.

Resumo

This study developed a system of equations for predicting total aboveground and component biomass in black wattle trees. A total of 140 black wattle trees at age 10 years were measured regarding their diameter at 1.30 m height above the ground (d), total tree height (h), basic wood density (branches and stem), and biomass (stem, crown, and aboveground). We evaluated the performance of linear and nonlinear allometric models by comparing the statistics of R2adj., RRMSE%, and BIC. Nonlinear models performed better when predicting crown biomass (using only d as an independent variable), and stem and aboveground biomass (using d and h as independent variables). Adding basic density did not significantly improve biomass modeling. The residuals had non-homogeneous variance; thus, the fitted equations were weighted, with weights derived from a function containing the same independent variables of the fitted biomass function. Subsequently, we used a simultaneous set of equations to ensure that the sum of each component's estimated biomass values was equal to the total biomass values. Simultaneous fitting improved the performance of the equations by guaranteeing the components' additivity, and weighted regression allowed to stabilize error variance, ensuring the homoscedasticity of the residuals.

Biografia do Autor

Thiago Wendling Gonçalves de Oliveira, Universidade Federal do Paraná

Engenheiro Florestal, graduado pela Universidade Federal do Paraná e mestre pela Universidade de São Paulo. Atualmente é aluno de doutorado na área de concentração em Manejo Florestal pela Universidade Federal do Paraná.

Vinícius Morais Coutinho, Universidade Federal do Paraná

Engenheiro Florestal, graduado pela Universidade Federal do Paraná e mestre pela mesma Universidade. Atualmente é aluno de doutorado na área de concentração em Manejo Florestal pela Universidade Federal do Paraná.

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Publicado

29-12-2020

Como Citar

Gonçalves de Oliveira, T. W., Coutinho, V. M., Fiorentin, L. D., Inoue Sanquetta, M. N., Sanquetta, C. R., & Dalla Corte, A. P. (2020). HOW TO ESTIMATE BLACK WATTLE ABOVEGROUND BIOMASS FROM HETEROSCEDASTIC DATA?. Floresta, 51(1), 028–036. https://doi.org/10.5380/rf.v51i1.65236

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