Calibration of volume equation in stands of Acacia mearnsii De Wild.

Detalhes bibliográficos
Autor(a) principal: Santos, Amanda Pereira
Data de Publicação: 2023
Outros Autores: Koehler, Henrique Soares, Sanquetta, Carlos Roberto, Netto, Sylvio Péllico, Behling, Alexandre
Tipo de documento: Artigo
Idioma: por
Título da fonte: Ciência Florestal (Online)
Texto Completo: https://periodicos.ufsm.br/cienciaflorestal/article/view/64859
Resumo: The fitting of volume models by the traditional method (data obtained by means of scaling several trees), is the most used way to obtain volume equations. This method requires a lot of effort and is quite costly, therefore some alternatives have been developed to decrease the sampling of the number of trees and obtain results of estimates similar to that obtained by the traditional method, highlighting the mixed modeling applied to calibrate equations. In this work, the general objective of the research was to calibrate the Schumacher-Hall volume model by predicting random effects at the stand level and comparing it with the equations obtained using the traditional approach. The database is made up of 670 trees with ages varying from 1 to 10.75 years. The calibrations tested in the mixed model were using: (i) the largest tree of variable d for each stand; (ii) the two largest trees of variable d for each stand; (iii) the three largest trees in d for each stand; (iv) the four largest trees in d for each stand; (v) the five largest trees in d for each stand; (vi) the median tree for variable d in each stand; vii) one random tree in each stand; viii) three trees, being the smallest tree, the mean tree and the largest tree for the variable d for each stand; ix) three trees, being the mean tree, the mean tree minus two standard deviations and the mean tree plus two standard deviations for the variable d in each stand. The statistics for evaluating the equations were the coefficient of determination, the standard error of the estimate, the analysis of residuals, and the graphical analysis of the observed and estimated values. The results show that the volume equations can be calibrated at the stand level by sampling three trees: the average tree, the average tree plus two standard deviations, and the average tree minus two standard deviations. Considering that in the traditional method, 50 trees on average are measured in the forest inventory, the reduction of sampling in a new stand would be 94%.
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spelling Calibration of volume equation in stands of Acacia mearnsii De Wild.Calibração de equações de volume em povoamentos de Acacia mearnsii De Wild.CubagemModelos mistosEBLUPEfeito aleatórioTree scalingMixed modelsBLUPRandom effectThe fitting of volume models by the traditional method (data obtained by means of scaling several trees), is the most used way to obtain volume equations. This method requires a lot of effort and is quite costly, therefore some alternatives have been developed to decrease the sampling of the number of trees and obtain results of estimates similar to that obtained by the traditional method, highlighting the mixed modeling applied to calibrate equations. In this work, the general objective of the research was to calibrate the Schumacher-Hall volume model by predicting random effects at the stand level and comparing it with the equations obtained using the traditional approach. The database is made up of 670 trees with ages varying from 1 to 10.75 years. The calibrations tested in the mixed model were using: (i) the largest tree of variable d for each stand; (ii) the two largest trees of variable d for each stand; (iii) the three largest trees in d for each stand; (iv) the four largest trees in d for each stand; (v) the five largest trees in d for each stand; (vi) the median tree for variable d in each stand; vii) one random tree in each stand; viii) three trees, being the smallest tree, the mean tree and the largest tree for the variable d for each stand; ix) three trees, being the mean tree, the mean tree minus two standard deviations and the mean tree plus two standard deviations for the variable d in each stand. The statistics for evaluating the equations were the coefficient of determination, the standard error of the estimate, the analysis of residuals, and the graphical analysis of the observed and estimated values. The results show that the volume equations can be calibrated at the stand level by sampling three trees: the average tree, the average tree plus two standard deviations, and the average tree minus two standard deviations. Considering that in the traditional method, 50 trees on average are measured in the forest inventory, the reduction of sampling in a new stand would be 94%.O ajuste dos modelos de volume pelo método tradicional (dados obtidos por meio de cubagem de várias árvores) é a maneira mais utilizada para obter equações de volume. Este método demanda muito esforço e é bastante oneroso, portanto algumas alternativas têm sido desenvolvidas para diminuir a amostragem do número de árvores e obter resultados de estimativas semelhantes ao obtido pelo método tradicional, destacando-se a modelagem mista aplicada para calibrar equações. Neste trabalho, o objetivo da pesquisa foi calibrar o modelo de volume de Schumacher-Hall por meio da predição de efeitos aleatórios em nível de povoamento e compará-lo com as equações obtidas pela abordagem tradicional. A base de dados é composta de 670 árvores com idades variando de 1 a 10,75 anos. As calibrações testadas no modelo misto foram: i) a maior árvore da variável d para cada povoamento; ii) as duas maiores árvores da variável d para cada povoamento; iii) as três maiores árvores em d para cada povoamento; iv) as quatro maiores árvores em d para cada povoamento; v) as cinco maiores árvores em d para cada povoamento; vi) a árvore mediana para a variável d em cada povoamento; vii) uma árvore aleatória em cada povoamento; viii) três árvores, sendo a menor árvore, a árvore média e a maior da variável d para cada povoamento; ix) três árvores, sendo a árvore média, a árvore média menos dois desvios padrões e a árvore média mais dois desvios padrões para a variável d em cada povoamento. As estatísticas para avaliação das equações foram o coeficiente de determinação, o erro padrão da estimativa, a análise de resíduos e a análise gráfica dos valores observados e estimados. Os resultados evidenciam que as equações de volume podem ser calibradas em nível de povoamento por meio da amostragem de três árvores sendo elas, a árvore média, a árvore média mais dois desvios padrões e a árvore média menos dois desvios padrões, considerando que no método tradicional são cubadas 50 árvores em média no inventário florestal, a redução da amostragem em um novo povoamento seria de 94%.Universidade Federal de Santa Maria2023-03-28info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://periodicos.ufsm.br/cienciaflorestal/article/view/6485910.5902/1980509864859Ciência Florestal; Vol. 33 No. 1 (2023): Publicação Contínua; e64859Ciência Florestal; v. 33 n. 1 (2023): Publicação Contínua; e648591980-50980103-9954reponame:Ciência Florestal (Online)instname:Universidade Federal de Santa Maria (UFSM)instacron:UFSMporhttps://periodicos.ufsm.br/cienciaflorestal/article/view/64859/51869Copyright (c) 2023 Ciência Florestalhttp://creativecommons.org/licenses/by-nc/4.0info:eu-repo/semantics/openAccessSantos, Amanda PereiraKoehler, Henrique SoaresSanquetta, Carlos RobertoNetto, Sylvio PéllicoBehling, Alexandre2023-06-07T17:41:16Zoai:ojs.pkp.sfu.ca:article/64859Revistahttp://www.ufsm.br/cienciaflorestal/ONGhttps://old.scielo.br/oai/scielo-oai.php||cienciaflorestal@ufsm.br|| cienciaflorestal@gmail.com|| cf@smail.ufsm.br1980-50980103-9954opendoar:2023-06-07T17:41:16Ciência Florestal (Online) - Universidade Federal de Santa Maria (UFSM)false
dc.title.none.fl_str_mv Calibration of volume equation in stands of Acacia mearnsii De Wild.
Calibração de equações de volume em povoamentos de Acacia mearnsii De Wild.
title Calibration of volume equation in stands of Acacia mearnsii De Wild.
spellingShingle Calibration of volume equation in stands of Acacia mearnsii De Wild.
Santos, Amanda Pereira
Cubagem
Modelos mistos
EBLUP
Efeito aleatório
Tree scaling
Mixed models
BLUP
Random effect
title_short Calibration of volume equation in stands of Acacia mearnsii De Wild.
title_full Calibration of volume equation in stands of Acacia mearnsii De Wild.
title_fullStr Calibration of volume equation in stands of Acacia mearnsii De Wild.
title_full_unstemmed Calibration of volume equation in stands of Acacia mearnsii De Wild.
title_sort Calibration of volume equation in stands of Acacia mearnsii De Wild.
author Santos, Amanda Pereira
author_facet Santos, Amanda Pereira
Koehler, Henrique Soares
Sanquetta, Carlos Roberto
Netto, Sylvio Péllico
Behling, Alexandre
author_role author
author2 Koehler, Henrique Soares
Sanquetta, Carlos Roberto
Netto, Sylvio Péllico
Behling, Alexandre
author2_role author
author
author
author
dc.contributor.author.fl_str_mv Santos, Amanda Pereira
Koehler, Henrique Soares
Sanquetta, Carlos Roberto
Netto, Sylvio Péllico
Behling, Alexandre
dc.subject.por.fl_str_mv Cubagem
Modelos mistos
EBLUP
Efeito aleatório
Tree scaling
Mixed models
BLUP
Random effect
topic Cubagem
Modelos mistos
EBLUP
Efeito aleatório
Tree scaling
Mixed models
BLUP
Random effect
description The fitting of volume models by the traditional method (data obtained by means of scaling several trees), is the most used way to obtain volume equations. This method requires a lot of effort and is quite costly, therefore some alternatives have been developed to decrease the sampling of the number of trees and obtain results of estimates similar to that obtained by the traditional method, highlighting the mixed modeling applied to calibrate equations. In this work, the general objective of the research was to calibrate the Schumacher-Hall volume model by predicting random effects at the stand level and comparing it with the equations obtained using the traditional approach. The database is made up of 670 trees with ages varying from 1 to 10.75 years. The calibrations tested in the mixed model were using: (i) the largest tree of variable d for each stand; (ii) the two largest trees of variable d for each stand; (iii) the three largest trees in d for each stand; (iv) the four largest trees in d for each stand; (v) the five largest trees in d for each stand; (vi) the median tree for variable d in each stand; vii) one random tree in each stand; viii) three trees, being the smallest tree, the mean tree and the largest tree for the variable d for each stand; ix) three trees, being the mean tree, the mean tree minus two standard deviations and the mean tree plus two standard deviations for the variable d in each stand. The statistics for evaluating the equations were the coefficient of determination, the standard error of the estimate, the analysis of residuals, and the graphical analysis of the observed and estimated values. The results show that the volume equations can be calibrated at the stand level by sampling three trees: the average tree, the average tree plus two standard deviations, and the average tree minus two standard deviations. Considering that in the traditional method, 50 trees on average are measured in the forest inventory, the reduction of sampling in a new stand would be 94%.
publishDate 2023
dc.date.none.fl_str_mv 2023-03-28
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://periodicos.ufsm.br/cienciaflorestal/article/view/64859
10.5902/1980509864859
url https://periodicos.ufsm.br/cienciaflorestal/article/view/64859
identifier_str_mv 10.5902/1980509864859
dc.language.iso.fl_str_mv por
language por
dc.relation.none.fl_str_mv https://periodicos.ufsm.br/cienciaflorestal/article/view/64859/51869
dc.rights.driver.fl_str_mv Copyright (c) 2023 Ciência Florestal
http://creativecommons.org/licenses/by-nc/4.0
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2023 Ciência Florestal
http://creativecommons.org/licenses/by-nc/4.0
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universidade Federal de Santa Maria
publisher.none.fl_str_mv Universidade Federal de Santa Maria
dc.source.none.fl_str_mv Ciência Florestal; Vol. 33 No. 1 (2023): Publicação Contínua; e64859
Ciência Florestal; v. 33 n. 1 (2023): Publicação Contínua; e64859
1980-5098
0103-9954
reponame:Ciência Florestal (Online)
instname:Universidade Federal de Santa Maria (UFSM)
instacron:UFSM
instname_str Universidade Federal de Santa Maria (UFSM)
instacron_str UFSM
institution UFSM
reponame_str Ciência Florestal (Online)
collection Ciência Florestal (Online)
repository.name.fl_str_mv Ciência Florestal (Online) - Universidade Federal de Santa Maria (UFSM)
repository.mail.fl_str_mv ||cienciaflorestal@ufsm.br|| cienciaflorestal@gmail.com|| cf@smail.ufsm.br
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