Emprego de funções de densidade de probabilidade na modelagem da distribuição diamétrica de clones de Eucalyptus spp. no polo gesseiro do Araripe

• Ano de defesa: 2018
• Autor(a) principal: ABREU, Yara Karolynne Lopes
• Orientador(a): SILVA, José Antônio Aleixo da
• Banca de defesa: SILVA, José Antônio Aleixo da, SILVA, Antônio Samuel Alves da, GADELHA, Fernando Henrique de Lima
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal Rural de Pernambuco
• Programa de Pós-Graduação: Programa de Pós-Graduação em Biometria e Estatística Aplicada
• Departamento: Departamento de Estatística e Informática
• País: Brasil
• Palavras-chave em Português: Distribuição diamétrica; Análise de variância; Eucalyptus; Eucalipto
• Área do conhecimento CNPq: CIENCIAS EXATAS E DA TERRA::PROBABILIDADE E ESTATISTICA
• Link de acesso: http://www.tede2.ufrpe.br:8080/tede2/handle/tede2/7241

When plating energy forests, it is interesting to quantify and predict its stock. The diameter distribution is a simple and powerful tool to characterize the structure of a forest and serves as an indicator of the growth stock structure. Therefore, the objective of this work is to apply different probability density functions (pdf) to explain the behavior of the diametric distribution of the Eucalyptus spp. clones according to different ages and population densities in the Gypsum Pole of Araripe. Therefore, it was adjusted the diametric distribution of three clones at five planting densities (2m x 1m; 2m x 2m; 2m x 3m; 3m x 3m; 4m x 2m) by the pdfs Beta, Dagum, Gamma, Normal, Johnson SB and Weibull at ages 48, 54 and 60 months. The choice of the best model was based on the results of two methodologies: statistical ranking and analysis of variance with Tukey test (5% significance). It was found that the function that best described the diameter distribution of Eucalyptus spp. clones was Dagum, while Gamma presented the worst adjustments for most of the scenarios analyzed. The method of selection by rankings, although widely used in the forest science, tends to assign different weights to statistics that do not differ, whereas the comparison of means by the Tukey test, although it does not take into account the number of parameters used in each function, is an alternative to understand the general behavior of the estimates and to verify if there are tendencies of underestimation or overestimation of values.