Please use this identifier to cite or link to this item: http://repositorio.ufla.br/jspui/handle/1/42816
metadata.artigo.dc.title: On the use of the Weibull distribution in modeling and describing diameter distributions of clonal eucalypt stands
metadata.artigo.dc.creator: Schmidt, Luciane Naimeke
Sanquetta, Mateus Niroh Inoue
McTague, John Paul McTague
Silva, Gilson Fernandes da
Fraga Filho, Clayton Vieira
Sanquetta, Carlos Roberto
Scolforo, José Roberto Soares
metadata.artigo.dc.subject: Truncated distributions
Fast-growing
Short rotation
Growth and yield system
Parameter prediction methods
Eucalipto - Predição de crescimento
Eucalipto - Povoamentos clonais
Distribuições Truncadas
Sistema de crescimento e produção
Método de predição de parâmetros
metadata.artigo.dc.publisher: Canadian Science Publishing
metadata.artigo.dc.date.issued: Apr-2020
metadata.artigo.dc.identifier.citation: SCHMIDT, L. N. et al. On the use of the Weibull distribution in modeling and describing diameter distributions of clonal eucalypt stands. Canadian Journal of Forest Research, Ottawa, p. 1-14, Apr. 2020. DOI: https://doi.org/10.1139/cjfr-2020-0051.
metadata.artigo.dc.description.abstract: Weibull distributions have been widely used to describe tree stem diameter distributions. However, there is a scarcity of studies that suggest the best Weibull formulation. The parameters of the Weibull distribution are usually predicted by either the parameter prediction method (PPM) or the parameter recovery method (PRM), although other methods have been proposed. Thus, this study aimed to evaluate the performance of eight Weibull formulations and compare methods of parameter prediction to describe diameter distributions of clonal eucalypt stands in Brazil. Data originated from remeasurements of 56 plots at ages 3, 5, and 6 years. Weibull distributions were fitted using the maximum likelihood method and evaluated in a goodness-of-fit indicators ranking. The right-truncated two-parameter formulation showed the best results and was used to evaluate the methods of parameter prediction. Stand attributes showed a strong relationship with shape and scale parameters. Regression models were developed and resulted in accurate estimates using PPM. PRM used a growth and yield system to estimate the stand attributes, followed by the moment-based method. The modified cumulative distribution function regression (CDFR) approach was also evaluated, and it presented the poorest results. Although the PPM showed excellent results, PRM is recommended in older stands with inventory because it implicitly promotes compatibility among stand attributes.
metadata.artigo.dc.identifier.uri: https://doi.org/10.1139/cjfr-2020-0051
http://repositorio.ufla.br/jspui/handle/1/42816
metadata.artigo.dc.language: en
Appears in Collections:DCF - Artigos publicados em periódicos

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