Modelagem para prognose do crescimento e produção de eucalipto em diferentes níveis de abordagem

Detalhes bibliográficos
Autor(a) principal: Fraga Filho, Clayton Vieira
Data de Publicação: 2016
Tipo de documento: Tese
Idioma: por
Título da fonte: Repositório Institucional da Universidade Federal do Espírito Santo (riUfes)
Texto Completo: http://repositorio.ufes.br/handle/10/7713
Resumo: Growth and yield models are efficient and reliable to describe forests dynamics and perform the prediction of long-term production. There are different approach levels for these models, such as whole-stand models, diameter distribution, and individualtree. This work aimed to compare different levels for the modeling of the growth and production in terms of the accuracy and bias level of the production estimates in eucalyptus stands, with fixed and mixed models. Two criteria were used for dividing the data. In criterion 1, the data were splited into two groups: the first for fitting plots with future age between 24 and 60 months, and the second for projection, having plots with future age between 72 and 96 months. In the second criterion, 70% of the plots were used to models fitting and 30% for the validation of these models. Alternatives at the whole-stand level were proposed, being two of them fixed model alternatives to criterion 1, and two for criterion 2. In addition, three mixed modeling alternatives were proposed for criterion 1 and seven alternatives for criterion 2. According to analyzes for fixed models, the Logistics model was more accurate and less biased. Mixed modeling projection presented superior results compared to fixed effects modeling. Furthermore, an evaluation was performed with fixed and mixed modeling alternatives for diameter distribution level. A fixed model was evaluated for both criteria: an alternative using mixed modeling was proposed for criterion 1 and three alternatives for criterion 2. The conclusion was that alternatives adjusted and validated with criterion 2 data proved better, and the diameters distribution with mixed model was more accurate and less biased compared with approaches with fixed effects models. From these results, fixed and mixed alternatives were evaluated at the individual-tree level. Two fixed models were analyzed for criterion 1 and one fixed model for criterion 2. Five mixed models were proposed for criterion 1 and six models for criterion 2. Among the fixed models, the linear model (criterion 1) was better; however, it was outperformed by mixed modeling in both fit and validation (criteria 1 and 2). Finally, the most accurate and less biased models previously obtained were compared. For performing the projection (criterion 1) using fixed modeling, the Logistic model is more accurate and less biased. The linear mixed model of individual-tree proposed in this work was better than Logistic model. For criterion 2, the Clutter’s adapted mixed model was better. Thus, it was concluded in this work that modeling at individual-tree level produced similar results as the wholestand level, being both more accurate than the results found for the diameter distribution models. It was also concluded that the mixed modeling at these three levels provided gains in accuracy and lack of bias in prognosis of growth and yield modeling for eucalyptus stands.
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spelling Mendonça, Adriano Ribeiro deSilva, Gilson Fernandes daFraga Filho, Clayton VieiraLeite, Hélio GarciaSoares, Carlos Pedro BoechatBinoti, Daniel Henrique Breda2018-08-01T22:56:22Z2018-08-012018-08-01T22:56:22Z2016-02-04Growth and yield models are efficient and reliable to describe forests dynamics and perform the prediction of long-term production. There are different approach levels for these models, such as whole-stand models, diameter distribution, and individualtree. This work aimed to compare different levels for the modeling of the growth and production in terms of the accuracy and bias level of the production estimates in eucalyptus stands, with fixed and mixed models. Two criteria were used for dividing the data. In criterion 1, the data were splited into two groups: the first for fitting plots with future age between 24 and 60 months, and the second for projection, having plots with future age between 72 and 96 months. In the second criterion, 70% of the plots were used to models fitting and 30% for the validation of these models. Alternatives at the whole-stand level were proposed, being two of them fixed model alternatives to criterion 1, and two for criterion 2. In addition, three mixed modeling alternatives were proposed for criterion 1 and seven alternatives for criterion 2. According to analyzes for fixed models, the Logistics model was more accurate and less biased. Mixed modeling projection presented superior results compared to fixed effects modeling. Furthermore, an evaluation was performed with fixed and mixed modeling alternatives for diameter distribution level. A fixed model was evaluated for both criteria: an alternative using mixed modeling was proposed for criterion 1 and three alternatives for criterion 2. The conclusion was that alternatives adjusted and validated with criterion 2 data proved better, and the diameters distribution with mixed model was more accurate and less biased compared with approaches with fixed effects models. From these results, fixed and mixed alternatives were evaluated at the individual-tree level. Two fixed models were analyzed for criterion 1 and one fixed model for criterion 2. Five mixed models were proposed for criterion 1 and six models for criterion 2. Among the fixed models, the linear model (criterion 1) was better; however, it was outperformed by mixed modeling in both fit and validation (criteria 1 and 2). Finally, the most accurate and less biased models previously obtained were compared. For performing the projection (criterion 1) using fixed modeling, the Logistic model is more accurate and less biased. The linear mixed model of individual-tree proposed in this work was better than Logistic model. For criterion 2, the Clutter’s adapted mixed model was better. Thus, it was concluded in this work that modeling at individual-tree level produced similar results as the wholestand level, being both more accurate than the results found for the diameter distribution models. It was also concluded that the mixed modeling at these three levels provided gains in accuracy and lack of bias in prognosis of growth and yield modeling for eucalyptus stands.Modelos de crescimento e produção são eficientes e confiáveis para descrever a dinâmica de florestas e realizar a previsão da produção de longo prazo. Existem diferentes níveis de abordagens para estes modelos, tais como modelos em nível de povoamento, distribuição de diâmetros e árvores individuais. Este trabalho teve como objetivo geral comparar diferentes níveis para modelagem do crescimento e produção quanto à acurácia e à tendenciosidade das estimativas de produção em povoamentos de eucalipto, com e sem efeitos aleatórios. Foram utilizados dois critérios para a divisão de dados. No critério 1, dividiu-se os dados em dois grupos: o primeiro para ajuste, com parcelas com idade futura entre 24 e 60 meses, e o segundo para a projeção, com parcelas com idade futura entre 72 e 96 meses. No segundo critério, 70% das parcelas foram usadas no ajuste e 30% para a validação destes modelos. Foram propostas alternativas em nível de povoamento, sendo duas alternativas de modelagem fixa avaliadas para o critério 1, e duas para o critério 2. Além dessas, foram propostas três alternativas de modelagem mista para o critério 1 e sete alternativas para o critério 2. De acordo com análises realizadas para os modelos fixos, o mais acurado e menos viesado foi o Logístico. A modelagem mista para projeção foi superior à modelagem de efeitos fixos. Em seguida, foi realizada uma avaliação de alternativas de modelagem de distribuição de diâmetros com e sem efeito aleatório. Um modelo fixo foi avaliado para ambos os critérios: uma alternativa usando modelagem mista foi proposta para o critério 1 e três alternativas para o critério 2. Concluiu-se que as alternativas ajustadas e validadas com dados do critério 2 foram superiores, sendo a modelagem mista de distribuição de diâmetros a mais acurada e menos enviesada. A partir destes resultados, foram avaliadas alternativas fixas e mistas em nível de árvores individuais. Foram utilizados dois modelos fixos avaliados para o critério 1 e um modelo fixo avaliado para o critério 2. Cinco modelos mistos foram propostos com dados do critério 1 e seis modelos para o critério 2. Dos modelos fixos, o modelo linear (critério 1) foi superior, contudo superado pela modelagem mista, tanto no ajuste quanto na validação (critérios 1 e 2). Por fim, os modelos mais acurados e menos enviesados obtidos previamente foram comparados. Para realizar a projeção (critério 1) utilizando a modelagem fixa, o modelo Logístico apresentou maior acurácia e menor tendenciosidade. O modelo linear misto de árvores individuais proposto neste trabalho foi superior ao resultado do modelo Logístico. Para o critério 2, o modelo misto adaptado de Clutter foi superior. Assim, conclui-se neste trabalho que a modelagem em nível de árvores individuais produziu resultados similares aos encontrados para os modelos em nível de povoamento, sendo ambos mais acurados que os resultados encontrados para os modelos de distribuição de diâmetros. Conclui-se também que a modelagem mista nestes três níveis proporcionou ganhos em acurácia e ausência de viés na prognose do crescimento e da produção de povoamentos florestais de eucalipto.TextFRAGA FILHO, Clayton Vieira. Modelagem para prognose do crescimento e produção de eucalipto em diferentes níveis de abordagem. 2016. 281 f. Tese (Doutorado em Ciências Florestais) – Universidade Federal do Espírito Santo, Jerônimo Monteiro, 2016.http://repositorio.ufes.br/handle/10/7713porUniversidade Federal do Espírito SantoDoutorado em Ciências FlorestaisPrograma de Pós-Graduação em Ciências FlorestaisUFESBRCentro de Ciências Agrárias e EngenhariasForest managementGrowth and yield modelsMixed modelsMensuração florestalModelos de crescimento e produçãoModelos mistosEucaliptoProdutividade florestalRecursos Florestais e Engenharia Florestal630Modelagem para prognose do crescimento e produção de eucalipto em diferentes níveis de abordagemGrowth and yield prognosis modeling of eucalyptus at different approach levelsinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/doctoralThesisinfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da Universidade Federal do Espírito Santo (riUfes)instname:Universidade Federal do Espírito Santo (UFES)instacron:UFESORIGINALCLAYTONVIEIRAFRAGAFILHO-2016-trabalho.pdfapplication/pdf28028158http://repositorio.ufes.br/bitstreams/0a32b1f4-be62-4412-ada8-c6ad658f4dfe/download9d52c4e9bcd20c8df07de05dc5d628e5MD5110/77132024-06-21 15:46:42.716oai:repositorio.ufes.br:10/7713http://repositorio.ufes.brRepositório InstitucionalPUBhttp://repositorio.ufes.br/oai/requestopendoar:21082024-07-11T14:36:14.156890Repositório Institucional da Universidade Federal do Espírito Santo (riUfes) - Universidade Federal do Espírito Santo (UFES)false
dc.title.none.fl_str_mv Modelagem para prognose do crescimento e produção de eucalipto em diferentes níveis de abordagem
dc.title.alternative.none.fl_str_mv Growth and yield prognosis modeling of eucalyptus at different approach levels
title Modelagem para prognose do crescimento e produção de eucalipto em diferentes níveis de abordagem
spellingShingle Modelagem para prognose do crescimento e produção de eucalipto em diferentes níveis de abordagem
Fraga Filho, Clayton Vieira
Forest management
Growth and yield models
Mixed models
Mensuração florestal
Modelos de crescimento e produção
Modelos mistos
Recursos Florestais e Engenharia Florestal
Eucalipto
Produtividade florestal
630
title_short Modelagem para prognose do crescimento e produção de eucalipto em diferentes níveis de abordagem
title_full Modelagem para prognose do crescimento e produção de eucalipto em diferentes níveis de abordagem
title_fullStr Modelagem para prognose do crescimento e produção de eucalipto em diferentes níveis de abordagem
title_full_unstemmed Modelagem para prognose do crescimento e produção de eucalipto em diferentes níveis de abordagem
title_sort Modelagem para prognose do crescimento e produção de eucalipto em diferentes níveis de abordagem
author Fraga Filho, Clayton Vieira
author_facet Fraga Filho, Clayton Vieira
author_role author
dc.contributor.advisor-co1.fl_str_mv Mendonça, Adriano Ribeiro de
dc.contributor.advisor1.fl_str_mv Silva, Gilson Fernandes da
dc.contributor.author.fl_str_mv Fraga Filho, Clayton Vieira
dc.contributor.referee1.fl_str_mv Leite, Hélio Garcia
dc.contributor.referee2.fl_str_mv Soares, Carlos Pedro Boechat
dc.contributor.referee3.fl_str_mv Binoti, Daniel Henrique Breda
contributor_str_mv Mendonça, Adriano Ribeiro de
Silva, Gilson Fernandes da
Leite, Hélio Garcia
Soares, Carlos Pedro Boechat
Binoti, Daniel Henrique Breda
dc.subject.eng.fl_str_mv Forest management
Growth and yield models
Mixed models
topic Forest management
Growth and yield models
Mixed models
Mensuração florestal
Modelos de crescimento e produção
Modelos mistos
Recursos Florestais e Engenharia Florestal
Eucalipto
Produtividade florestal
630
dc.subject.por.fl_str_mv Mensuração florestal
Modelos de crescimento e produção
Modelos mistos
dc.subject.cnpq.fl_str_mv Recursos Florestais e Engenharia Florestal
dc.subject.br-rjbn.none.fl_str_mv Eucalipto
Produtividade florestal
dc.subject.udc.none.fl_str_mv 630
description Growth and yield models are efficient and reliable to describe forests dynamics and perform the prediction of long-term production. There are different approach levels for these models, such as whole-stand models, diameter distribution, and individualtree. This work aimed to compare different levels for the modeling of the growth and production in terms of the accuracy and bias level of the production estimates in eucalyptus stands, with fixed and mixed models. Two criteria were used for dividing the data. In criterion 1, the data were splited into two groups: the first for fitting plots with future age between 24 and 60 months, and the second for projection, having plots with future age between 72 and 96 months. In the second criterion, 70% of the plots were used to models fitting and 30% for the validation of these models. Alternatives at the whole-stand level were proposed, being two of them fixed model alternatives to criterion 1, and two for criterion 2. In addition, three mixed modeling alternatives were proposed for criterion 1 and seven alternatives for criterion 2. According to analyzes for fixed models, the Logistics model was more accurate and less biased. Mixed modeling projection presented superior results compared to fixed effects modeling. Furthermore, an evaluation was performed with fixed and mixed modeling alternatives for diameter distribution level. A fixed model was evaluated for both criteria: an alternative using mixed modeling was proposed for criterion 1 and three alternatives for criterion 2. The conclusion was that alternatives adjusted and validated with criterion 2 data proved better, and the diameters distribution with mixed model was more accurate and less biased compared with approaches with fixed effects models. From these results, fixed and mixed alternatives were evaluated at the individual-tree level. Two fixed models were analyzed for criterion 1 and one fixed model for criterion 2. Five mixed models were proposed for criterion 1 and six models for criterion 2. Among the fixed models, the linear model (criterion 1) was better; however, it was outperformed by mixed modeling in both fit and validation (criteria 1 and 2). Finally, the most accurate and less biased models previously obtained were compared. For performing the projection (criterion 1) using fixed modeling, the Logistic model is more accurate and less biased. The linear mixed model of individual-tree proposed in this work was better than Logistic model. For criterion 2, the Clutter’s adapted mixed model was better. Thus, it was concluded in this work that modeling at individual-tree level produced similar results as the wholestand level, being both more accurate than the results found for the diameter distribution models. It was also concluded that the mixed modeling at these three levels provided gains in accuracy and lack of bias in prognosis of growth and yield modeling for eucalyptus stands.
publishDate 2016
dc.date.issued.fl_str_mv 2016-02-04
dc.date.accessioned.fl_str_mv 2018-08-01T22:56:22Z
dc.date.available.fl_str_mv 2018-08-01
2018-08-01T22:56:22Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
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dc.identifier.citation.fl_str_mv FRAGA FILHO, Clayton Vieira. Modelagem para prognose do crescimento e produção de eucalipto em diferentes níveis de abordagem. 2016. 281 f. Tese (Doutorado em Ciências Florestais) – Universidade Federal do Espírito Santo, Jerônimo Monteiro, 2016.
dc.identifier.uri.fl_str_mv http://repositorio.ufes.br/handle/10/7713
identifier_str_mv FRAGA FILHO, Clayton Vieira. Modelagem para prognose do crescimento e produção de eucalipto em diferentes níveis de abordagem. 2016. 281 f. Tese (Doutorado em Ciências Florestais) – Universidade Federal do Espírito Santo, Jerônimo Monteiro, 2016.
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dc.publisher.none.fl_str_mv Universidade Federal do Espírito Santo
Doutorado em Ciências Florestais
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dc.publisher.department.fl_str_mv Centro de Ciências Agrárias e Engenharias
publisher.none.fl_str_mv Universidade Federal do Espírito Santo
Doutorado em Ciências Florestais
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