Allometric equations to predict pinus palustris biomass in the southeastern United States

Detalhes bibliográficos
Autor(a) principal: Farias, Aline Araújo
Data de Publicação: 2019
Outros Autores: Gezan, Salvador A., Carvalho, Melissa Pisaroglo de, Ferraz Filho, Antonio Carlos, Soares, Carlos Pedro Boechat
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UFLA
Texto Completo: http://repositorio.ufla.br/jspui/handle/1/40142
Resumo: Pinus palustris Mill. ecosystem is considered one of the most threatened of North America. In this context, studies on biomass quantification are fundamental for forest management plans. Thus, the objective of this study was to develop a set of allometric equations to predict total P. palustris stump-biomass. Biomass data were collected at different locations in the southeastern United States. A total of 119 allometric equations were fitted from the combination of explanatory variables: diameter at breast height (DBH), height (H), age (I), basal area (G), number of trees per hectare (N), site index (S) and quadratic diameter (Dq). One of the models that presented the lowest residual standard error (Sy.x) and root mean square error (RMSE) was ln(W) = -0.9978+0.7082.(H)+0.1009.ln(H.DBH)-0.5310.(N)-0.0003.ln(Dq). Therefore, the insertion of dendrometric variables characteristic of forest stands has great efficacy in biomass prediction for trees from different sites.
id UFLA_d8e07c85bf2df2f9135b0612b94f7e3e
oai_identifier_str oai:localhost:1/40142
network_acronym_str UFLA
network_name_str Repositório Institucional da UFLA
repository_id_str
spelling Allometric equations to predict pinus palustris biomass in the southeastern United StatesForest managementRegressionPinus palustris Mill. ecosystem is considered one of the most threatened of North America. In this context, studies on biomass quantification are fundamental for forest management plans. Thus, the objective of this study was to develop a set of allometric equations to predict total P. palustris stump-biomass. Biomass data were collected at different locations in the southeastern United States. A total of 119 allometric equations were fitted from the combination of explanatory variables: diameter at breast height (DBH), height (H), age (I), basal area (G), number of trees per hectare (N), site index (S) and quadratic diameter (Dq). One of the models that presented the lowest residual standard error (Sy.x) and root mean square error (RMSE) was ln(W) = -0.9978+0.7082.(H)+0.1009.ln(H.DBH)-0.5310.(N)-0.0003.ln(Dq). Therefore, the insertion of dendrometric variables characteristic of forest stands has great efficacy in biomass prediction for trees from different sites.Instituto de Florestas da Universidade Federal Rural do Rio de Janeiro2020-04-17T15:20:25Z2020-04-17T15:20:25Z2019info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfFARIAS, A. A. et al. Allometric equations to predict pinus palustris biomass in the southeastern United States. Floresta e Ambiente, Seropédica, v. 26, 2019.http://repositorio.ufla.br/jspui/handle/1/40142Floresta e Ambientereponame:Repositório Institucional da UFLAinstname:Universidade Federal de Lavras (UFLA)instacron:UFLAAttribution 4.0 Internationalhttp://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessFarias, Aline AraújoGezan, Salvador A.Carvalho, Melissa Pisaroglo deFerraz Filho, Antonio CarlosSoares, Carlos Pedro Boechateng2020-04-17T15:20:25Zoai:localhost:1/40142Repositório InstitucionalPUBhttp://repositorio.ufla.br/oai/requestnivaldo@ufla.br || repositorio.biblioteca@ufla.bropendoar:2020-04-17T15:20:25Repositório Institucional da UFLA - Universidade Federal de Lavras (UFLA)false
dc.title.none.fl_str_mv Allometric equations to predict pinus palustris biomass in the southeastern United States
title Allometric equations to predict pinus palustris biomass in the southeastern United States
spellingShingle Allometric equations to predict pinus palustris biomass in the southeastern United States
Farias, Aline Araújo
Forest management
Regression
title_short Allometric equations to predict pinus palustris biomass in the southeastern United States
title_full Allometric equations to predict pinus palustris biomass in the southeastern United States
title_fullStr Allometric equations to predict pinus palustris biomass in the southeastern United States
title_full_unstemmed Allometric equations to predict pinus palustris biomass in the southeastern United States
title_sort Allometric equations to predict pinus palustris biomass in the southeastern United States
author Farias, Aline Araújo
author_facet Farias, Aline Araújo
Gezan, Salvador A.
Carvalho, Melissa Pisaroglo de
Ferraz Filho, Antonio Carlos
Soares, Carlos Pedro Boechat
author_role author
author2 Gezan, Salvador A.
Carvalho, Melissa Pisaroglo de
Ferraz Filho, Antonio Carlos
Soares, Carlos Pedro Boechat
author2_role author
author
author
author
dc.contributor.author.fl_str_mv Farias, Aline Araújo
Gezan, Salvador A.
Carvalho, Melissa Pisaroglo de
Ferraz Filho, Antonio Carlos
Soares, Carlos Pedro Boechat
dc.subject.por.fl_str_mv Forest management
Regression
topic Forest management
Regression
description Pinus palustris Mill. ecosystem is considered one of the most threatened of North America. In this context, studies on biomass quantification are fundamental for forest management plans. Thus, the objective of this study was to develop a set of allometric equations to predict total P. palustris stump-biomass. Biomass data were collected at different locations in the southeastern United States. A total of 119 allometric equations were fitted from the combination of explanatory variables: diameter at breast height (DBH), height (H), age (I), basal area (G), number of trees per hectare (N), site index (S) and quadratic diameter (Dq). One of the models that presented the lowest residual standard error (Sy.x) and root mean square error (RMSE) was ln(W) = -0.9978+0.7082.(H)+0.1009.ln(H.DBH)-0.5310.(N)-0.0003.ln(Dq). Therefore, the insertion of dendrometric variables characteristic of forest stands has great efficacy in biomass prediction for trees from different sites.
publishDate 2019
dc.date.none.fl_str_mv 2019
2020-04-17T15:20:25Z
2020-04-17T15:20:25Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv FARIAS, A. A. et al. Allometric equations to predict pinus palustris biomass in the southeastern United States. Floresta e Ambiente, Seropédica, v. 26, 2019.
http://repositorio.ufla.br/jspui/handle/1/40142
identifier_str_mv FARIAS, A. A. et al. Allometric equations to predict pinus palustris biomass in the southeastern United States. Floresta e Ambiente, Seropédica, v. 26, 2019.
url http://repositorio.ufla.br/jspui/handle/1/40142
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
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
reponame:Repositório Institucional da UFLA
instname:Universidade Federal de Lavras (UFLA)
instacron:UFLA
instname_str Universidade Federal de Lavras (UFLA)
instacron_str UFLA
institution UFLA
reponame_str Repositório Institucional da UFLA
collection Repositório Institucional da UFLA
repository.name.fl_str_mv Repositório Institucional da UFLA - Universidade Federal de Lavras (UFLA)
repository.mail.fl_str_mv nivaldo@ufla.br || repositorio.biblioteca@ufla.br
_version_ 1807835152789798912