Calibration of volume equation in stands of Acacia mearnsii De Wild.
Autor(a) principal: | |
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Data de Publicação: | 2023 |
Outros Autores: | , , , |
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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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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1799944135902232576 |