Allometric equations to predict pinus palustris biomass in the southeastern United States
Autor(a) principal: | |
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Data de Publicação: | 2019 |
Outros Autores: | , , , |
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. |
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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_ |
1815439188227522560 |