The tree height estimated by non-power models on volumetric models provides reliable predictions of wood volume: The Amazon species height modelling issue.

Detalhes bibliográficos
Autor(a) principal: NASCIMENTO, R. G. M.
Data de Publicação: 2020
Outros Autores: VANCLAY, J. K., FIGUEIREDO FILHO, A., MACHADO, S. do A., RUSCHEL, A. R., HIRAMATSU, N. A., FREITAS, L. J. M. de
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)
Texto Completo: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1125280
https://doi.org/10.1016/j.tfp.2020.100028
Resumo: Allometries that include height as independent variable usually provide greater accuracy on estimates of volume, biomass or individual carbon than other prediction strategies that rely only diameter at breast height as independent variable. However, when these models are applied in Amazon Forest Inventories, it is common to use estimated heights rather than measured heights to prepare volume, biomass or carbon estimates. This practice is common, but rarely discussed and the effect on predictions and precision is usually overlooked. The aim of this study was to examine hypsometric models and evaluate the effect of estimated height on merchantable volume prediction in Eastern Amazonian forests. The study area was a 3,786 ha Forest Management Unit owned by Jari Florestal S.A., in the Jari Valley Region of the State of Pará, Brazil. The data includes 16,099 trees of 25 species, measured and harvested in 2006. Ten percent of the data were reserved for validation of the hypsometric and volumetric estimates. Five hypsometric models and two modelling techniques (linear regression and mixed-effects model) were examined. The choice of best model was based on graphical analyses of residuals, distribution of residuals, heteroscedasticity of error and presence of outliers as assessed by h-values, DFFITS and Cook's distance. The hypsometric relationship and volumetric estimates using DBH and DBH with estimated height were validated with Graybill's test, Theil's error decomposition, Efficiency, Equivalence test and Tukey's test for species estimates level. Heights estimated using a semi-logarithmic mixed-effects model can improve predictions from volume equations. The results show that exploratory data analysis and validation process helped to provide estimates with greater efficiency and should be adopted in related studies. The prediction of height associated with volumetric models for six different species provided volumetric estimates with an error below 5% for the global average volume. The estimated height by the mixed-effect non-power law model should be included in double input models previously developed for volume prediction.
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spelling The tree height estimated by non-power models on volumetric models provides reliable predictions of wood volume: The Amazon species height modelling issue.FlorestaInventário FlorestalFloresta TropicalMadeiraAllometries that include height as independent variable usually provide greater accuracy on estimates of volume, biomass or individual carbon than other prediction strategies that rely only diameter at breast height as independent variable. However, when these models are applied in Amazon Forest Inventories, it is common to use estimated heights rather than measured heights to prepare volume, biomass or carbon estimates. This practice is common, but rarely discussed and the effect on predictions and precision is usually overlooked. The aim of this study was to examine hypsometric models and evaluate the effect of estimated height on merchantable volume prediction in Eastern Amazonian forests. The study area was a 3,786 ha Forest Management Unit owned by Jari Florestal S.A., in the Jari Valley Region of the State of Pará, Brazil. The data includes 16,099 trees of 25 species, measured and harvested in 2006. Ten percent of the data were reserved for validation of the hypsometric and volumetric estimates. Five hypsometric models and two modelling techniques (linear regression and mixed-effects model) were examined. The choice of best model was based on graphical analyses of residuals, distribution of residuals, heteroscedasticity of error and presence of outliers as assessed by h-values, DFFITS and Cook's distance. The hypsometric relationship and volumetric estimates using DBH and DBH with estimated height were validated with Graybill's test, Theil's error decomposition, Efficiency, Equivalence test and Tukey's test for species estimates level. Heights estimated using a semi-logarithmic mixed-effects model can improve predictions from volume equations. The results show that exploratory data analysis and validation process helped to provide estimates with greater efficiency and should be adopted in related studies. The prediction of height associated with volumetric models for six different species provided volumetric estimates with an error below 5% for the global average volume. The estimated height by the mixed-effect non-power law model should be included in double input models previously developed for volume prediction.Rodrigo Geroni Mendes Nascimento, UFRA; Jerome Klaas Vanclay, Southern Cross University; Afonso Figueiredo Filho, UNICENTRO; Sebastião do Amaral Machado, UFPR; ADEMIR ROBERTO RUSCHEL, CPATU; Nelson Akira Hiramatsu, Eucatex - Industry and Commerce; LUCAS JOSE MAZZEI DE FREITAS, CPATU.NASCIMENTO, R. G. M.VANCLAY, J. K.FIGUEIREDO FILHO, A.MACHADO, S. do A.RUSCHEL, A. R.HIRAMATSU, N. A.FREITAS, L. J. M. de2020-10-06T09:13:49Z2020-10-06T09:13:49Z2020-10-052020info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleTrees, Forests and People, v. 2, Article 100028, Dec. 2020.http://www.alice.cnptia.embrapa.br/alice/handle/doc/1125280https://doi.org/10.1016/j.tfp.2020.100028enginfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa)instacron:EMBRAPA2020-10-06T09:13:56Zoai:www.alice.cnptia.embrapa.br:doc/1125280Repositório InstitucionalPUBhttps://www.alice.cnptia.embrapa.br/oai/requestopendoar:21542020-10-06T09:13:56falseRepositório InstitucionalPUBhttps://www.alice.cnptia.embrapa.br/oai/requestcg-riaa@embrapa.bropendoar:21542020-10-06T09:13:56Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa)false
dc.title.none.fl_str_mv The tree height estimated by non-power models on volumetric models provides reliable predictions of wood volume: The Amazon species height modelling issue.
title The tree height estimated by non-power models on volumetric models provides reliable predictions of wood volume: The Amazon species height modelling issue.
spellingShingle The tree height estimated by non-power models on volumetric models provides reliable predictions of wood volume: The Amazon species height modelling issue.
NASCIMENTO, R. G. M.
Floresta
Inventário Florestal
Floresta Tropical
Madeira
title_short The tree height estimated by non-power models on volumetric models provides reliable predictions of wood volume: The Amazon species height modelling issue.
title_full The tree height estimated by non-power models on volumetric models provides reliable predictions of wood volume: The Amazon species height modelling issue.
title_fullStr The tree height estimated by non-power models on volumetric models provides reliable predictions of wood volume: The Amazon species height modelling issue.
title_full_unstemmed The tree height estimated by non-power models on volumetric models provides reliable predictions of wood volume: The Amazon species height modelling issue.
title_sort The tree height estimated by non-power models on volumetric models provides reliable predictions of wood volume: The Amazon species height modelling issue.
author NASCIMENTO, R. G. M.
author_facet NASCIMENTO, R. G. M.
VANCLAY, J. K.
FIGUEIREDO FILHO, A.
MACHADO, S. do A.
RUSCHEL, A. R.
HIRAMATSU, N. A.
FREITAS, L. J. M. de
author_role author
author2 VANCLAY, J. K.
FIGUEIREDO FILHO, A.
MACHADO, S. do A.
RUSCHEL, A. R.
HIRAMATSU, N. A.
FREITAS, L. J. M. de
author2_role author
author
author
author
author
author
dc.contributor.none.fl_str_mv Rodrigo Geroni Mendes Nascimento, UFRA; Jerome Klaas Vanclay, Southern Cross University; Afonso Figueiredo Filho, UNICENTRO; Sebastião do Amaral Machado, UFPR; ADEMIR ROBERTO RUSCHEL, CPATU; Nelson Akira Hiramatsu, Eucatex - Industry and Commerce; LUCAS JOSE MAZZEI DE FREITAS, CPATU.
dc.contributor.author.fl_str_mv NASCIMENTO, R. G. M.
VANCLAY, J. K.
FIGUEIREDO FILHO, A.
MACHADO, S. do A.
RUSCHEL, A. R.
HIRAMATSU, N. A.
FREITAS, L. J. M. de
dc.subject.por.fl_str_mv Floresta
Inventário Florestal
Floresta Tropical
Madeira
topic Floresta
Inventário Florestal
Floresta Tropical
Madeira
description Allometries that include height as independent variable usually provide greater accuracy on estimates of volume, biomass or individual carbon than other prediction strategies that rely only diameter at breast height as independent variable. However, when these models are applied in Amazon Forest Inventories, it is common to use estimated heights rather than measured heights to prepare volume, biomass or carbon estimates. This practice is common, but rarely discussed and the effect on predictions and precision is usually overlooked. The aim of this study was to examine hypsometric models and evaluate the effect of estimated height on merchantable volume prediction in Eastern Amazonian forests. The study area was a 3,786 ha Forest Management Unit owned by Jari Florestal S.A., in the Jari Valley Region of the State of Pará, Brazil. The data includes 16,099 trees of 25 species, measured and harvested in 2006. Ten percent of the data were reserved for validation of the hypsometric and volumetric estimates. Five hypsometric models and two modelling techniques (linear regression and mixed-effects model) were examined. The choice of best model was based on graphical analyses of residuals, distribution of residuals, heteroscedasticity of error and presence of outliers as assessed by h-values, DFFITS and Cook's distance. The hypsometric relationship and volumetric estimates using DBH and DBH with estimated height were validated with Graybill's test, Theil's error decomposition, Efficiency, Equivalence test and Tukey's test for species estimates level. Heights estimated using a semi-logarithmic mixed-effects model can improve predictions from volume equations. The results show that exploratory data analysis and validation process helped to provide estimates with greater efficiency and should be adopted in related studies. The prediction of height associated with volumetric models for six different species provided volumetric estimates with an error below 5% for the global average volume. The estimated height by the mixed-effect non-power law model should be included in double input models previously developed for volume prediction.
publishDate 2020
dc.date.none.fl_str_mv 2020-10-06T09:13:49Z
2020-10-06T09:13:49Z
2020-10-05
2020
dc.type.driver.fl_str_mv info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv Trees, Forests and People, v. 2, Article 100028, Dec. 2020.
http://www.alice.cnptia.embrapa.br/alice/handle/doc/1125280
https://doi.org/10.1016/j.tfp.2020.100028
identifier_str_mv Trees, Forests and People, v. 2, Article 100028, Dec. 2020.
url http://www.alice.cnptia.embrapa.br/alice/handle/doc/1125280
https://doi.org/10.1016/j.tfp.2020.100028
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.source.none.fl_str_mv reponame:Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)
instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa)
instacron:EMBRAPA
instname_str Empresa Brasileira de Pesquisa Agropecuária (Embrapa)
instacron_str EMBRAPA
institution EMBRAPA
reponame_str Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)
collection Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)
repository.name.fl_str_mv Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa)
repository.mail.fl_str_mv cg-riaa@embrapa.br
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