SPECIES-SPECIFIC EQUATIONS: GREATER PRECISION IN COMMERCIAL VOLUME ESTIMATION IN MANAGED FORESTS IN THE AMAZON

Detalhes bibliográficos
Autor(a) principal: Santos, Misael Freitas dos
Data de Publicação: 2020
Outros Autores: Figueiredo Filho, Afonso, Gama, João Ricardo Vasconcellos, Retslaff, Fabiane Aparecida de Souza, Costa, Daniele Lima da
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Cerne (Online)
Texto Completo: https://cerne.ufla.br/site/index.php/CERNE/article/view/2529
Resumo: The objective of this study was to analyze the performance of species-specific equations (SSEs)  concerning  generic  ones  in  Annual  Production  Units  (GEAPUs)  and  in  a  Forest  Management  Area  (GEFMA)  in  the  Brazilian  Amazon.  A  total  of  29,119  trees  from  43  species  were  inventoried,  harvested,  and  volumetric  measurements  were  taken  in ten APUs, with 10% of this total being separated for validation and comparison of the selected equations. After selection and validation of the equations (GEFMA, GEAPUs and  SSEs)  they  were  compared  using  precision  statistics,  by  contrasting  estimated  and  observed volumes and by residual analysis. Precision statistics were clearly lower for the SSEs. Trend lines near the average observed volume were shown for the SSEs when the estimates were contrasted with the observations. The residuals generated by the SSEs  were  smaller  and  statistically  different  than  those  of  GEFMA  and  GEAPUs  for  the  majority of cases. The most important commercial species (M.  huberi) had its volume overestimated by 10.6, 9.3 and 3.0% when the GEFMA, the GEAPUs, and the SSEs were applied, respectively. Among the species that generally had very large trees, H. petraeumhad its volume underestimated by 15.7, 16.6 and 4.4% by the GEFMA, GEAPUs and SSEs, respectively. The greater precision of the SSEs is reflected in better forest management planning  decisions  with  respect  to  operational  and  economic  aspects.  These  results  show that besides being statistically valid, the SSEs are recommended for obtaining more precise estimates of commercial volume, especially since there is a great demand for reliable estimates for each individual species in forest management areas in the Amazon.
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spelling SPECIES-SPECIFIC EQUATIONS: GREATER PRECISION IN COMMERCIAL VOLUME ESTIMATION IN MANAGED FORESTS IN THE AMAZONSPECIES-SPECIFIC EQUATIONS: GREATER PRECISION IN COMMERCIAL VOLUME ESTIMATION IN MANAGED FORESTS IN THE AMAZONcommercial species, dendrometry, forest management, tropical forest, volumetric models.The objective of this study was to analyze the performance of species-specific equations (SSEs)  concerning  generic  ones  in  Annual  Production  Units  (GEAPUs)  and  in  a  Forest  Management  Area  (GEFMA)  in  the  Brazilian  Amazon.  A  total  of  29,119  trees  from  43  species  were  inventoried,  harvested,  and  volumetric  measurements  were  taken  in ten APUs, with 10% of this total being separated for validation and comparison of the selected equations. After selection and validation of the equations (GEFMA, GEAPUs and  SSEs)  they  were  compared  using  precision  statistics,  by  contrasting  estimated  and  observed volumes and by residual analysis. Precision statistics were clearly lower for the SSEs. Trend lines near the average observed volume were shown for the SSEs when the estimates were contrasted with the observations. The residuals generated by the SSEs  were  smaller  and  statistically  different  than  those  of  GEFMA  and  GEAPUs  for  the  majority of cases. The most important commercial species (M.  huberi) had its volume overestimated by 10.6, 9.3 and 3.0% when the GEFMA, the GEAPUs, and the SSEs were applied, respectively. Among the species that generally had very large trees, H. petraeumhad its volume underestimated by 15.7, 16.6 and 4.4% by the GEFMA, GEAPUs and SSEs, respectively. The greater precision of the SSEs is reflected in better forest management planning  decisions  with  respect  to  operational  and  economic  aspects.  These  results  show that besides being statistically valid, the SSEs are recommended for obtaining more precise estimates of commercial volume, especially since there is a great demand for reliable estimates for each individual species in forest management areas in the Amazon.The objective of this study was to analyze the performance of species-specific equations (SSEs)  concerning  generic  ones  in  Annual  Production  Units  (GEAPUs)  and  in  a  Forest  Management  Area  (GEFMA)  in  the  Brazilian  Amazon.  A  total  of  29,119  trees  from  43  species  were  inventoried,  harvested,  and  volumetric  measurements  were  taken  in ten APUs, with 10% of this total being separated for validation and comparison of the selected equations. After selection and validation of the equations (GEFMA, GEAPUs and  SSEs)  they  were  compared  using  precision  statistics,  by  contrasting  estimated  and  observed volumes and by residual analysis. Precision statistics were clearly lower for the SSEs. Trend lines near the average observed volume were shown for the SSEs when the estimates were contrasted with the observations. The residuals generated by the SSEs  were  smaller  and  statistically  different  than  those  of  GEFMA  and  GEAPUs  for  the  majority of cases. The most important commercial species (M.  huberi) had its volume overestimated by 10.6, 9.3 and 3.0% when the GEFMA, the GEAPUs, and the SSEs were applied, respectively. Among the species that generally had very large trees, H. petraeumhad its volume underestimated by 15.7, 16.6 and 4.4% by the GEFMA, GEAPUs and SSEs, respectively. The greater precision of the SSEs is reflected in better forest management planning  decisions  with  respect  to  operational  and  economic  aspects.  These  results  show that besides being statistically valid, the SSEs are recommended for obtaining more precise estimates of commercial volume, especially since there is a great demand for reliable estimates for each individual species in forest management areas in the Amazon.CERNECERNE2020-11-17info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://cerne.ufla.br/site/index.php/CERNE/article/view/2529CERNE; Vol 26 No 3 (2020); 315-330CERNE; Vol 26 No 3 (2020); 315-3302317-63420104-7760reponame:Cerne (Online)instname:Universidade Federal de Lavras (UFLA)instacron:UFLAenghttps://cerne.ufla.br/site/index.php/CERNE/article/view/2529/1202Copyright (c) 2020 CERNEinfo:eu-repo/semantics/openAccessSantos, Misael Freitas dosFigueiredo Filho, AfonsoGama, João Ricardo VasconcellosRetslaff, Fabiane Aparecida de SouzaCosta, Daniele Lima da2021-01-12T03:12:26Zoai:cerne.ufla.br:article/2529Revistahttps://cerne.ufla.br/site/index.php/CERNEPUBhttps://cerne.ufla.br/site/index.php/CERNE/oaicerne@dcf.ufla.br||cerne@dcf.ufla.br2317-63420104-7760opendoar:2024-05-21T19:54:45.578673Cerne (Online) - Universidade Federal de Lavras (UFLA)true
dc.title.none.fl_str_mv SPECIES-SPECIFIC EQUATIONS: GREATER PRECISION IN COMMERCIAL VOLUME ESTIMATION IN MANAGED FORESTS IN THE AMAZON
SPECIES-SPECIFIC EQUATIONS: GREATER PRECISION IN COMMERCIAL VOLUME ESTIMATION IN MANAGED FORESTS IN THE AMAZON
title SPECIES-SPECIFIC EQUATIONS: GREATER PRECISION IN COMMERCIAL VOLUME ESTIMATION IN MANAGED FORESTS IN THE AMAZON
spellingShingle SPECIES-SPECIFIC EQUATIONS: GREATER PRECISION IN COMMERCIAL VOLUME ESTIMATION IN MANAGED FORESTS IN THE AMAZON
Santos, Misael Freitas dos
commercial species, dendrometry, forest management, tropical forest, volumetric models.
title_short SPECIES-SPECIFIC EQUATIONS: GREATER PRECISION IN COMMERCIAL VOLUME ESTIMATION IN MANAGED FORESTS IN THE AMAZON
title_full SPECIES-SPECIFIC EQUATIONS: GREATER PRECISION IN COMMERCIAL VOLUME ESTIMATION IN MANAGED FORESTS IN THE AMAZON
title_fullStr SPECIES-SPECIFIC EQUATIONS: GREATER PRECISION IN COMMERCIAL VOLUME ESTIMATION IN MANAGED FORESTS IN THE AMAZON
title_full_unstemmed SPECIES-SPECIFIC EQUATIONS: GREATER PRECISION IN COMMERCIAL VOLUME ESTIMATION IN MANAGED FORESTS IN THE AMAZON
title_sort SPECIES-SPECIFIC EQUATIONS: GREATER PRECISION IN COMMERCIAL VOLUME ESTIMATION IN MANAGED FORESTS IN THE AMAZON
author Santos, Misael Freitas dos
author_facet Santos, Misael Freitas dos
Figueiredo Filho, Afonso
Gama, João Ricardo Vasconcellos
Retslaff, Fabiane Aparecida de Souza
Costa, Daniele Lima da
author_role author
author2 Figueiredo Filho, Afonso
Gama, João Ricardo Vasconcellos
Retslaff, Fabiane Aparecida de Souza
Costa, Daniele Lima da
author2_role author
author
author
author
dc.contributor.author.fl_str_mv Santos, Misael Freitas dos
Figueiredo Filho, Afonso
Gama, João Ricardo Vasconcellos
Retslaff, Fabiane Aparecida de Souza
Costa, Daniele Lima da
dc.subject.por.fl_str_mv commercial species, dendrometry, forest management, tropical forest, volumetric models.
topic commercial species, dendrometry, forest management, tropical forest, volumetric models.
description The objective of this study was to analyze the performance of species-specific equations (SSEs)  concerning  generic  ones  in  Annual  Production  Units  (GEAPUs)  and  in  a  Forest  Management  Area  (GEFMA)  in  the  Brazilian  Amazon.  A  total  of  29,119  trees  from  43  species  were  inventoried,  harvested,  and  volumetric  measurements  were  taken  in ten APUs, with 10% of this total being separated for validation and comparison of the selected equations. After selection and validation of the equations (GEFMA, GEAPUs and  SSEs)  they  were  compared  using  precision  statistics,  by  contrasting  estimated  and  observed volumes and by residual analysis. Precision statistics were clearly lower for the SSEs. Trend lines near the average observed volume were shown for the SSEs when the estimates were contrasted with the observations. The residuals generated by the SSEs  were  smaller  and  statistically  different  than  those  of  GEFMA  and  GEAPUs  for  the  majority of cases. The most important commercial species (M.  huberi) had its volume overestimated by 10.6, 9.3 and 3.0% when the GEFMA, the GEAPUs, and the SSEs were applied, respectively. Among the species that generally had very large trees, H. petraeumhad its volume underestimated by 15.7, 16.6 and 4.4% by the GEFMA, GEAPUs and SSEs, respectively. The greater precision of the SSEs is reflected in better forest management planning  decisions  with  respect  to  operational  and  economic  aspects.  These  results  show that besides being statistically valid, the SSEs are recommended for obtaining more precise estimates of commercial volume, especially since there is a great demand for reliable estimates for each individual species in forest management areas in the Amazon.
publishDate 2020
dc.date.none.fl_str_mv 2020-11-17
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/2529
url https://cerne.ufla.br/site/index.php/CERNE/article/view/2529
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv https://cerne.ufla.br/site/index.php/CERNE/article/view/2529/1202
dc.rights.driver.fl_str_mv Copyright (c) 2020 CERNE
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2020 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 26 No 3 (2020); 315-330
CERNE; Vol 26 No 3 (2020); 315-330
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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