IMPROVING FOREST MANAGEMENT PRESCRIPTION FOR NATURAL FOREST

Detalhes bibliográficos
Autor(a) principal: Rangel, Mauro Sérgio
Data de Publicação: 2015
Outros Autores: Calegario, Natalino, Mello, Anabel Aparecida de, Lemos, Poliana Costa
Tipo de documento: Artigo
Idioma: por
Título da fonte: Cerne (Online)
Texto Completo: https://cerne.ufla.br/site/index.php/CERNE/article/view/410
Resumo: This study was carried out in an estational semideciduous montana forest, located in the Forest Reserve at Federal University of Lavras. The main propose was to improve the prescription for forest management, comparing the linear and non-linear adjusting of diametric distribution. In order to generate the prescriptions, 17 species with greater population density were selected and the nonlinear and linear functions were fitted. After the frequency estimates by diameter class, the De Liocourt quotient q was used for obtaining the management prescriptions. Based on the results, it was observed that the estimated frequency, by nonlinear function and by specie, had values closer to observed frequency, generating lower residual standard error. Therefore, the nonlinear method is more precise and exact in estimating the wood stock of the species, generating better prediction of the production.
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spelling IMPROVING FOREST MANAGEMENT PRESCRIPTION FOR NATURAL FORESTForest managementnonlinear regressionnatural forestdiametric distributionThis study was carried out in an estational semideciduous montana forest, located in the Forest Reserve at Federal University of Lavras. The main propose was to improve the prescription for forest management, comparing the linear and non-linear adjusting of diametric distribution. In order to generate the prescriptions, 17 species with greater population density were selected and the nonlinear and linear functions were fitted. After the frequency estimates by diameter class, the De Liocourt quotient q was used for obtaining the management prescriptions. Based on the results, it was observed that the estimated frequency, by nonlinear function and by specie, had values closer to observed frequency, generating lower residual standard error. Therefore, the nonlinear method is more precise and exact in estimating the wood stock of the species, generating better prediction of the production.CERNECERNE2015-09-21info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://cerne.ufla.br/site/index.php/CERNE/article/view/410CERNE; Vol. 12 No. 2 (2006); 145-156CERNE; v. 12 n. 2 (2006); 145-1562317-63420104-7760reponame:Cerne (Online)instname:Universidade Federal de Lavras (UFLA)instacron:UFLAporhttps://cerne.ufla.br/site/index.php/CERNE/article/view/410/351Copyright (c) 2015 CERNEinfo:eu-repo/semantics/openAccessRangel, Mauro SérgioCalegario, NatalinoMello, Anabel Aparecida deLemos, Poliana Costa2015-10-22T10:20:18Zoai:cerne.ufla.br:article/410Revistahttps://cerne.ufla.br/site/index.php/CERNEPUBhttps://cerne.ufla.br/site/index.php/CERNE/oaicerne@dcf.ufla.br||cerne@dcf.ufla.br2317-63420104-7760opendoar:2024-05-21T19:53:49.405228Cerne (Online) - Universidade Federal de Lavras (UFLA)true
dc.title.none.fl_str_mv IMPROVING FOREST MANAGEMENT PRESCRIPTION FOR NATURAL FOREST
title IMPROVING FOREST MANAGEMENT PRESCRIPTION FOR NATURAL FOREST
spellingShingle IMPROVING FOREST MANAGEMENT PRESCRIPTION FOR NATURAL FOREST
Rangel, Mauro Sérgio
Forest management
nonlinear regression
natural forest
diametric distribution
title_short IMPROVING FOREST MANAGEMENT PRESCRIPTION FOR NATURAL FOREST
title_full IMPROVING FOREST MANAGEMENT PRESCRIPTION FOR NATURAL FOREST
title_fullStr IMPROVING FOREST MANAGEMENT PRESCRIPTION FOR NATURAL FOREST
title_full_unstemmed IMPROVING FOREST MANAGEMENT PRESCRIPTION FOR NATURAL FOREST
title_sort IMPROVING FOREST MANAGEMENT PRESCRIPTION FOR NATURAL FOREST
author Rangel, Mauro Sérgio
author_facet Rangel, Mauro Sérgio
Calegario, Natalino
Mello, Anabel Aparecida de
Lemos, Poliana Costa
author_role author
author2 Calegario, Natalino
Mello, Anabel Aparecida de
Lemos, Poliana Costa
author2_role author
author
author
dc.contributor.author.fl_str_mv Rangel, Mauro Sérgio
Calegario, Natalino
Mello, Anabel Aparecida de
Lemos, Poliana Costa
dc.subject.por.fl_str_mv Forest management
nonlinear regression
natural forest
diametric distribution
topic Forest management
nonlinear regression
natural forest
diametric distribution
description This study was carried out in an estational semideciduous montana forest, located in the Forest Reserve at Federal University of Lavras. The main propose was to improve the prescription for forest management, comparing the linear and non-linear adjusting of diametric distribution. In order to generate the prescriptions, 17 species with greater population density were selected and the nonlinear and linear functions were fitted. After the frequency estimates by diameter class, the De Liocourt quotient q was used for obtaining the management prescriptions. Based on the results, it was observed that the estimated frequency, by nonlinear function and by specie, had values closer to observed frequency, generating lower residual standard error. Therefore, the nonlinear method is more precise and exact in estimating the wood stock of the species, generating better prediction of the production.
publishDate 2015
dc.date.none.fl_str_mv 2015-09-21
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://cerne.ufla.br/site/index.php/CERNE/article/view/410
url https://cerne.ufla.br/site/index.php/CERNE/article/view/410
dc.language.iso.fl_str_mv por
language por
dc.relation.none.fl_str_mv https://cerne.ufla.br/site/index.php/CERNE/article/view/410/351
dc.rights.driver.fl_str_mv Copyright (c) 2015 CERNE
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2015 CERNE
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv CERNE
CERNE
publisher.none.fl_str_mv CERNE
CERNE
dc.source.none.fl_str_mv CERNE; Vol. 12 No. 2 (2006); 145-156
CERNE; v. 12 n. 2 (2006); 145-156
2317-6342
0104-7760
reponame:Cerne (Online)
instname:Universidade Federal de Lavras (UFLA)
instacron:UFLA
instname_str Universidade Federal de Lavras (UFLA)
instacron_str UFLA
institution UFLA
reponame_str Cerne (Online)
collection Cerne (Online)
repository.name.fl_str_mv Cerne (Online) - Universidade Federal de Lavras (UFLA)
repository.mail.fl_str_mv cerne@dcf.ufla.br||cerne@dcf.ufla.br
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