LINEAR AND NONLINEAR MODELS WITH USE OF COVARIATES FOR HYPSOMETRIC RELATIONSHIP OF TWO TROPICAL PINE SPECIES
Autor(a) principal: | |
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Data de Publicação: | 2015 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | por |
Título da fonte: | Ciência Florestal (Online) |
Texto Completo: | https://periodicos.ufsm.br/cienciaflorestal/article/view/20651 |
Resumo: | http://dx.doi.org/10.5902/1980509820651Traditionally, most studies use linear models to adjust the hypsometric relationship using diameter at breast height (DBH) as the only independent variable. However, it is known that the linearity does not characterizes faithfully biological growth and other variables related to forest stand, or individual trees, influence in height growth. The aim of this study was to evaluate linear and nonlinear models’ performance for hypsometric relationship of two tropical pine species, as well as the effect of covariates adding in models’ parameters estimation. The data used provided from Pinus caribaea var. hondurensis and Pinus oocarpa stands, with different ages and site index, located in the counties of Nova Ponte and Indianápolis, Minas Gerais state. Linear and nonlinear models were fitted in its original form and including the covariates age, site index and species in the estimation of each models’ parameter. The models were compared using the following statistical criteria: residual standard error (Syx), Akaike Information Criteria (AIC), Bayesian Information Criteria (BIC) and also by graphical analysis of standardized residuals. It was found that nonlinear models show greater ability to describe height behavior, and the inclusion of covariates in models’ parameters improved its fit quality, considering the statistical accuracy criteria adopted. |
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LINEAR AND NONLINEAR MODELS WITH USE OF COVARIATES FOR HYPSOMETRIC RELATIONSHIP OF TWO TROPICAL PINE SPECIESMODELOS LINEARES E NÃO LINEARES COM USO DE COVARIANTES PARA RELAÇÃO HIPSOMÉTRICA DE DUAS ESPÉCIES DE PINUS TROPICAISh/d curvestropical pinesheight-diameter relationshipcovariates.curvas h/dpinus tropicaisrelação altura-diâmetrocovariáveis.http://dx.doi.org/10.5902/1980509820651Traditionally, most studies use linear models to adjust the hypsometric relationship using diameter at breast height (DBH) as the only independent variable. However, it is known that the linearity does not characterizes faithfully biological growth and other variables related to forest stand, or individual trees, influence in height growth. The aim of this study was to evaluate linear and nonlinear models’ performance for hypsometric relationship of two tropical pine species, as well as the effect of covariates adding in models’ parameters estimation. The data used provided from Pinus caribaea var. hondurensis and Pinus oocarpa stands, with different ages and site index, located in the counties of Nova Ponte and Indianápolis, Minas Gerais state. Linear and nonlinear models were fitted in its original form and including the covariates age, site index and species in the estimation of each models’ parameter. The models were compared using the following statistical criteria: residual standard error (Syx), Akaike Information Criteria (AIC), Bayesian Information Criteria (BIC) and also by graphical analysis of standardized residuals. It was found that nonlinear models show greater ability to describe height behavior, and the inclusion of covariates in models’ parameters improved its fit quality, considering the statistical accuracy criteria adopted.http://dx.doi.org/10.5902/1980509820651Tradicionalmente, a maior parte dos estudos utiliza modelos lineares para o ajuste da relação hipsométrica, tendo o diâmetro a 1,30 m do solo (DAP) como única variável independente. Entretanto, sabe-se que a linearidade não caracteriza fielmente o crescimento biológico e que outras variáveis relativas ao povoamento, ou às árvores individuais, exercem influência sobre o crescimento em altura. O objetivo deste trabalho foi avaliar o desempenho de modelos lineares e não lineares no ajuste da relação hipsométrica de duas espécies de Pinus tropicais, bem como verificar o efeito da adição de covariantes na estimativa dos parâmetros destes modelos. Os dados utilizados provêm de plantios de Pinus caribaea var. hondurensis e Pinus oocarpa, com diferentes idades e localizados em áreas com diferentes índices de sítio, nos municípios de Nova Ponte e Indianópolis, estado de Minas Gerais. Modelos lineares e não lineares foram ajustados em suas formas originais e com a inclusão das covariáveis idade, sítio e espécie nas estimativas de cada parâmetro dos modelos. Os modelos foram comparados por meio dos critérios estatísticos: erro padrão da estimativa (Syx), Critério de Informação de Akaike (AIC), Critério de Informação Bayesiano (BIC) e também pela análise gráfica de resíduos padronizados. Constatou-se que modelos não lineares demonstram maior capacidade de descrever o comportamento da variável altura, e que a inclusão das covariáveis tornou superior a qualidade dos ajustes, considerando os critérios estatísticos de precisão adotados. Universidade Federal de Santa Maria2015-12-30info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://periodicos.ufsm.br/cienciaflorestal/article/view/2065110.5902/1980509820651Ciência Florestal; Vol. 25 No. 4 (2015); 969-980Ciência Florestal; v. 25 n. 4 (2015); 969-9801980-50980103-9954reponame:Ciência Florestal (Online)instname:Universidade Federal de Santa Maria (UFSM)instacron:UFSMporhttps://periodicos.ufsm.br/cienciaflorestal/article/view/20651/12276Sena, Ayuni Larissa MendesSilva Neto, Antônio José daOliveira, Gabriel Marcos VieiraCalegario, Natalinoinfo:eu-repo/semantics/openAccess2017-04-10T13:37:32Zoai:ojs.pkp.sfu.ca:article/20651Revistahttp://www.ufsm.br/cienciaflorestal/ONGhttps://old.scielo.br/oai/scielo-oai.php||cienciaflorestal@ufsm.br|| cienciaflorestal@gmail.com|| cf@smail.ufsm.br1980-50980103-9954opendoar:2017-04-10T13:37:32Ciência Florestal (Online) - Universidade Federal de Santa Maria (UFSM)false |
dc.title.none.fl_str_mv |
LINEAR AND NONLINEAR MODELS WITH USE OF COVARIATES FOR HYPSOMETRIC RELATIONSHIP OF TWO TROPICAL PINE SPECIES MODELOS LINEARES E NÃO LINEARES COM USO DE COVARIANTES PARA RELAÇÃO HIPSOMÉTRICA DE DUAS ESPÉCIES DE PINUS TROPICAIS |
title |
LINEAR AND NONLINEAR MODELS WITH USE OF COVARIATES FOR HYPSOMETRIC RELATIONSHIP OF TWO TROPICAL PINE SPECIES |
spellingShingle |
LINEAR AND NONLINEAR MODELS WITH USE OF COVARIATES FOR HYPSOMETRIC RELATIONSHIP OF TWO TROPICAL PINE SPECIES Sena, Ayuni Larissa Mendes h/d curves tropical pines height-diameter relationship covariates. curvas h/d pinus tropicais relação altura-diâmetro covariáveis. |
title_short |
LINEAR AND NONLINEAR MODELS WITH USE OF COVARIATES FOR HYPSOMETRIC RELATIONSHIP OF TWO TROPICAL PINE SPECIES |
title_full |
LINEAR AND NONLINEAR MODELS WITH USE OF COVARIATES FOR HYPSOMETRIC RELATIONSHIP OF TWO TROPICAL PINE SPECIES |
title_fullStr |
LINEAR AND NONLINEAR MODELS WITH USE OF COVARIATES FOR HYPSOMETRIC RELATIONSHIP OF TWO TROPICAL PINE SPECIES |
title_full_unstemmed |
LINEAR AND NONLINEAR MODELS WITH USE OF COVARIATES FOR HYPSOMETRIC RELATIONSHIP OF TWO TROPICAL PINE SPECIES |
title_sort |
LINEAR AND NONLINEAR MODELS WITH USE OF COVARIATES FOR HYPSOMETRIC RELATIONSHIP OF TWO TROPICAL PINE SPECIES |
author |
Sena, Ayuni Larissa Mendes |
author_facet |
Sena, Ayuni Larissa Mendes Silva Neto, Antônio José da Oliveira, Gabriel Marcos Vieira Calegario, Natalino |
author_role |
author |
author2 |
Silva Neto, Antônio José da Oliveira, Gabriel Marcos Vieira Calegario, Natalino |
author2_role |
author author author |
dc.contributor.author.fl_str_mv |
Sena, Ayuni Larissa Mendes Silva Neto, Antônio José da Oliveira, Gabriel Marcos Vieira Calegario, Natalino |
dc.subject.por.fl_str_mv |
h/d curves tropical pines height-diameter relationship covariates. curvas h/d pinus tropicais relação altura-diâmetro covariáveis. |
topic |
h/d curves tropical pines height-diameter relationship covariates. curvas h/d pinus tropicais relação altura-diâmetro covariáveis. |
description |
http://dx.doi.org/10.5902/1980509820651Traditionally, most studies use linear models to adjust the hypsometric relationship using diameter at breast height (DBH) as the only independent variable. However, it is known that the linearity does not characterizes faithfully biological growth and other variables related to forest stand, or individual trees, influence in height growth. The aim of this study was to evaluate linear and nonlinear models’ performance for hypsometric relationship of two tropical pine species, as well as the effect of covariates adding in models’ parameters estimation. The data used provided from Pinus caribaea var. hondurensis and Pinus oocarpa stands, with different ages and site index, located in the counties of Nova Ponte and Indianápolis, Minas Gerais state. Linear and nonlinear models were fitted in its original form and including the covariates age, site index and species in the estimation of each models’ parameter. The models were compared using the following statistical criteria: residual standard error (Syx), Akaike Information Criteria (AIC), Bayesian Information Criteria (BIC) and also by graphical analysis of standardized residuals. It was found that nonlinear models show greater ability to describe height behavior, and the inclusion of covariates in models’ parameters improved its fit quality, considering the statistical accuracy criteria adopted. |
publishDate |
2015 |
dc.date.none.fl_str_mv |
2015-12-30 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://periodicos.ufsm.br/cienciaflorestal/article/view/20651 10.5902/1980509820651 |
url |
https://periodicos.ufsm.br/cienciaflorestal/article/view/20651 |
identifier_str_mv |
10.5902/1980509820651 |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.relation.none.fl_str_mv |
https://periodicos.ufsm.br/cienciaflorestal/article/view/20651/12276 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Universidade Federal de Santa Maria |
publisher.none.fl_str_mv |
Universidade Federal de Santa Maria |
dc.source.none.fl_str_mv |
Ciência Florestal; Vol. 25 No. 4 (2015); 969-980 Ciência Florestal; v. 25 n. 4 (2015); 969-980 1980-5098 0103-9954 reponame:Ciência Florestal (Online) instname:Universidade Federal de Santa Maria (UFSM) instacron:UFSM |
instname_str |
Universidade Federal de Santa Maria (UFSM) |
instacron_str |
UFSM |
institution |
UFSM |
reponame_str |
Ciência Florestal (Online) |
collection |
Ciência Florestal (Online) |
repository.name.fl_str_mv |
Ciência Florestal (Online) - Universidade Federal de Santa Maria (UFSM) |
repository.mail.fl_str_mv |
||cienciaflorestal@ufsm.br|| cienciaflorestal@gmail.com|| cf@smail.ufsm.br |
_version_ |
1799944130480046080 |