Diameter Increment Modeling in an Araucaria Forest Fragment Using Cluster Analysis

Detalhes bibliográficos
Autor(a) principal: Roik,Mailson
Data de Publicação: 2018
Outros Autores: Machado,Sebastião do Amaral, Figueiredo Filho,Afonso, Sanquetta,Carlos Roberto, Roveda,Marcelo, Stepka,Thiago Floriani
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Floresta e Ambiente
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S2179-80872018000300113
Resumo: ABSTRACT The aims of the present study were to test the hypothesis that data stratification by cluster analysis and the use of other variables, in addition to DBH, can improve the precision of the estimates in diametric increment modeling for Mixed Ombrophilous Forest species. The study was carried out in the Irati National Forest. Data from 25 permanent sample plots of 1 ha each were used with all individuals presenting DBH equal to or greater than 10 cm being identified and measured. The increment modeling was performed for the whole forest (non-stratified data), ecological groups and species subgroups (stratified data) defined by cluster analysis. DBH presented a low correlation with the diametric increment and the use of other independent variables had a positive effect on the fitting, reducing the standard error of estimate and increasing the coefficient of determination. The data stratification did not make the models suitable to estimate the diametric increment; however, it provided improvements by reducing the standard error of estimate, suggesting that this technique can be better applied in the search for improvements to diametric modeling in natural forests.
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spelling Diameter Increment Modeling in an Araucaria Forest Fragment Using Cluster Analysisdata stratificationgrowthMixed Ombrophilous Forestmultivariate analysisABSTRACT The aims of the present study were to test the hypothesis that data stratification by cluster analysis and the use of other variables, in addition to DBH, can improve the precision of the estimates in diametric increment modeling for Mixed Ombrophilous Forest species. The study was carried out in the Irati National Forest. Data from 25 permanent sample plots of 1 ha each were used with all individuals presenting DBH equal to or greater than 10 cm being identified and measured. The increment modeling was performed for the whole forest (non-stratified data), ecological groups and species subgroups (stratified data) defined by cluster analysis. DBH presented a low correlation with the diametric increment and the use of other independent variables had a positive effect on the fitting, reducing the standard error of estimate and increasing the coefficient of determination. The data stratification did not make the models suitable to estimate the diametric increment; however, it provided improvements by reducing the standard error of estimate, suggesting that this technique can be better applied in the search for improvements to diametric modeling in natural forests.Instituto de Florestas da Universidade Federal Rural do Rio de Janeiro2018-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S2179-80872018000300113Floresta e Ambiente v.25 n.3 2018reponame:Floresta e Ambienteinstname:Universidade Federal do Rio de Janeiro (UFRJ)instacron:UFRJ10.1590/2179-8087.062517info:eu-repo/semantics/openAccessRoik,MailsonMachado,Sebastião do AmaralFigueiredo Filho,AfonsoSanquetta,Carlos RobertoRoveda,MarceloStepka,Thiago Florianieng2018-07-17T00:00:00Zoai:scielo:S2179-80872018000300113Revistahttps://www.floram.org/PUBhttps://old.scielo.br/oai/scielo-oai.phpfloramjournal@gmail.com||floram@ufrrj.br||2179-80871415-0980opendoar:2018-07-17T00:00Floresta e Ambiente - Universidade Federal do Rio de Janeiro (UFRJ)false
dc.title.none.fl_str_mv Diameter Increment Modeling in an Araucaria Forest Fragment Using Cluster Analysis
title Diameter Increment Modeling in an Araucaria Forest Fragment Using Cluster Analysis
spellingShingle Diameter Increment Modeling in an Araucaria Forest Fragment Using Cluster Analysis
Roik,Mailson
data stratification
growth
Mixed Ombrophilous Forest
multivariate analysis
title_short Diameter Increment Modeling in an Araucaria Forest Fragment Using Cluster Analysis
title_full Diameter Increment Modeling in an Araucaria Forest Fragment Using Cluster Analysis
title_fullStr Diameter Increment Modeling in an Araucaria Forest Fragment Using Cluster Analysis
title_full_unstemmed Diameter Increment Modeling in an Araucaria Forest Fragment Using Cluster Analysis
title_sort Diameter Increment Modeling in an Araucaria Forest Fragment Using Cluster Analysis
author Roik,Mailson
author_facet Roik,Mailson
Machado,Sebastião do Amaral
Figueiredo Filho,Afonso
Sanquetta,Carlos Roberto
Roveda,Marcelo
Stepka,Thiago Floriani
author_role author
author2 Machado,Sebastião do Amaral
Figueiredo Filho,Afonso
Sanquetta,Carlos Roberto
Roveda,Marcelo
Stepka,Thiago Floriani
author2_role author
author
author
author
author
dc.contributor.author.fl_str_mv Roik,Mailson
Machado,Sebastião do Amaral
Figueiredo Filho,Afonso
Sanquetta,Carlos Roberto
Roveda,Marcelo
Stepka,Thiago Floriani
dc.subject.por.fl_str_mv data stratification
growth
Mixed Ombrophilous Forest
multivariate analysis
topic data stratification
growth
Mixed Ombrophilous Forest
multivariate analysis
description ABSTRACT The aims of the present study were to test the hypothesis that data stratification by cluster analysis and the use of other variables, in addition to DBH, can improve the precision of the estimates in diametric increment modeling for Mixed Ombrophilous Forest species. The study was carried out in the Irati National Forest. Data from 25 permanent sample plots of 1 ha each were used with all individuals presenting DBH equal to or greater than 10 cm being identified and measured. The increment modeling was performed for the whole forest (non-stratified data), ecological groups and species subgroups (stratified data) defined by cluster analysis. DBH presented a low correlation with the diametric increment and the use of other independent variables had a positive effect on the fitting, reducing the standard error of estimate and increasing the coefficient of determination. The data stratification did not make the models suitable to estimate the diametric increment; however, it provided improvements by reducing the standard error of estimate, suggesting that this technique can be better applied in the search for improvements to diametric modeling in natural forests.
publishDate 2018
dc.date.none.fl_str_mv 2018-01-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S2179-80872018000300113
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S2179-80872018000300113
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/2179-8087.062517
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv text/html
dc.publisher.none.fl_str_mv Instituto de Florestas da Universidade Federal Rural do Rio de Janeiro
publisher.none.fl_str_mv Instituto de Florestas da Universidade Federal Rural do Rio de Janeiro
dc.source.none.fl_str_mv Floresta e Ambiente v.25 n.3 2018
reponame:Floresta e Ambiente
instname:Universidade Federal do Rio de Janeiro (UFRJ)
instacron:UFRJ
instname_str Universidade Federal do Rio de Janeiro (UFRJ)
instacron_str UFRJ
institution UFRJ
reponame_str Floresta e Ambiente
collection Floresta e Ambiente
repository.name.fl_str_mv Floresta e Ambiente - Universidade Federal do Rio de Janeiro (UFRJ)
repository.mail.fl_str_mv floramjournal@gmail.com||floram@ufrrj.br||
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