Site index for Prosopis alba plantations in the semi-arid chaco through mixed models

Autores
Senilliani, Maria Gracia; Bruno, Cecilia Ines; Brassiolo, Miguel Marcelo
Año de publicación
2019
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
The classification of sites through curves of Site Index allows to predict the yield of the planted forests at a certain age of the stand and to plan cultural treatments. The goal of this research was to compare linear and non-linear models of fixed effects vs. mixed non-linear models to estimate the site index in plantations of Prosopis alba var Griseb in the irrigated area of the province of Santiago del Estero, Argentina using the guide curve method. The data used comes from temporary plots, permanent plots and growth data from the stem analysis of selected individuals based on their greater growth in height within the sampled areas. The registered variable for the evaluation of the site was the dominant Height (HD), defined as the average height of the 100 thickest trees per hectare. Considering that the source of data from repeated measurements on the same subject implies the presence of correlation and/or heteroscedasticity, it was proposed to evaluate statistical models that allow to properly representing the structure of the variance-covariance matrix, improving the accuracy in the adjustment. From the analysis of the results, it appears that the models non-linear mixed models have had better performance in the adjustment of the Site Index than linear and non-linear models of fixed effects. The most accurate model (smallest AIC and BIC) in the site index estimation was the mixed non-linear regression model of 'Gompertz', with structure of composite symmetry correlation and exponential heteroscedasticity.v.25 n.2 2019
Fil: Senilliani, Maria Gracia. Universidad Nacional de Santiago del Estero. Facultad de Ciencias Forestales; Argentina
Fil: Bruno, Cecilia Ines. Instituto Nacional de Tecnologia Agropecuaria. Centro de Investigaciones Agropecuarias. Unidad de Fitopatologia y Modelizacion Agricola. Grupo Vinculado Catedra de Estadistica y Biometria de la Facultad de Ciencias Agropecuarias de la Universidad Nacional de Cordoba Al Ufyma | Consejo Nacional de Investigaciones Cientificas y Tecnicas. Centro Cientifico Tecnologico Conicet - Cordoba. Unidad de Fitopatologia y Modelizacion Agricola. Grupo Vinculado Catedra de Estadistica y Biometria de la Facultad de Ciencias Agropecuarias de la Universidad Nacional de Cordoba Al Ufyma.; Argentina
Fil: Brassiolo, Miguel Marcelo. Universidad Nacional de Santiago del Estero. Facultad de Ciencias Forestales; Argentina
Materia
Dominant height
Forestry
Site quality
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/106550
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/106550
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Site index for Prosopis alba plantations in the semi-arid chaco through mixed modelsSenilliani, Maria GraciaBruno, Cecilia InesBrassiolo, Miguel MarceloDominant heightForestrySite qualityhttps://purl.org/becyt/ford/4.1https://purl.org/becyt/ford/4The classification of sites through curves of Site Index allows to predict the yield of the planted forests at a certain age of the stand and to plan cultural treatments. The goal of this research was to compare linear and non-linear models of fixed effects vs. mixed non-linear models to estimate the site index in plantations of Prosopis alba var Griseb in the irrigated area of the province of Santiago del Estero, Argentina using the guide curve method. The data used comes from temporary plots, permanent plots and growth data from the stem analysis of selected individuals based on their greater growth in height within the sampled areas. The registered variable for the evaluation of the site was the dominant Height (HD), defined as the average height of the 100 thickest trees per hectare. Considering that the source of data from repeated measurements on the same subject implies the presence of correlation and/or heteroscedasticity, it was proposed to evaluate statistical models that allow to properly representing the structure of the variance-covariance matrix, improving the accuracy in the adjustment. From the analysis of the results, it appears that the models non-linear mixed models have had better performance in the adjustment of the Site Index than linear and non-linear models of fixed effects. The most accurate model (smallest AIC and BIC) in the site index estimation was the mixed non-linear regression model of 'Gompertz', with structure of composite symmetry correlation and exponential heteroscedasticity.v.25 n.2 2019Fil: Senilliani, Maria Gracia. Universidad Nacional de Santiago del Estero. Facultad de Ciencias Forestales; ArgentinaFil: Bruno, Cecilia Ines. Instituto Nacional de Tecnologia Agropecuaria. Centro de Investigaciones Agropecuarias. Unidad de Fitopatologia y Modelizacion Agricola. Grupo Vinculado Catedra de Estadistica y Biometria de la Facultad de Ciencias Agropecuarias de la Universidad Nacional de Cordoba Al Ufyma | Consejo Nacional de Investigaciones Cientificas y Tecnicas. Centro Cientifico Tecnologico Conicet - Cordoba. Unidad de Fitopatologia y Modelizacion Agricola. Grupo Vinculado Catedra de Estadistica y Biometria de la Facultad de Ciencias Agropecuarias de la Universidad Nacional de Cordoba Al Ufyma.; ArgentinaFil: Brassiolo, Miguel Marcelo. Universidad Nacional de Santiago del Estero. Facultad de Ciencias Forestales; ArgentinaUniversidade Federal de Lavras2019-06info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/106550Senilliani, Maria Gracia; Bruno, Cecilia Ines; Brassiolo, Miguel Marcelo; Site index for Prosopis alba plantations in the semi-arid chaco through mixed models; Universidade Federal de Lavras; Cerne; 25; 2; 6-2019; 195-2020104-7760CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/http://cerne.ufla.br/site/index.php/CERNE/article/view/2035/1132info:eu-repo/semantics/altIdentifier/doi/10.1590/01047760201925022622info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-10T13:20:08Zoai:ri.conicet.gov.ar:11336/106550instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-10 13:20:08.735CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Site index for Prosopis alba plantations in the semi-arid chaco through mixed models
title Site index for Prosopis alba plantations in the semi-arid chaco through mixed models
spellingShingle Site index for Prosopis alba plantations in the semi-arid chaco through mixed models
Senilliani, Maria Gracia
Dominant height
Forestry
Site quality
title_short Site index for Prosopis alba plantations in the semi-arid chaco through mixed models
title_full Site index for Prosopis alba plantations in the semi-arid chaco through mixed models
title_fullStr Site index for Prosopis alba plantations in the semi-arid chaco through mixed models
title_full_unstemmed Site index for Prosopis alba plantations in the semi-arid chaco through mixed models
title_sort Site index for Prosopis alba plantations in the semi-arid chaco through mixed models
dc.creator.none.fl_str_mv Senilliani, Maria Gracia
Bruno, Cecilia Ines
Brassiolo, Miguel Marcelo
author Senilliani, Maria Gracia
author_facet Senilliani, Maria Gracia
Bruno, Cecilia Ines
Brassiolo, Miguel Marcelo
author_role author
author2 Bruno, Cecilia Ines
Brassiolo, Miguel Marcelo
author2_role author
author
dc.subject.none.fl_str_mv Dominant height
Forestry
Site quality
topic Dominant height
Forestry
Site quality
purl_subject.fl_str_mv https://purl.org/becyt/ford/4.1
https://purl.org/becyt/ford/4
dc.description.none.fl_txt_mv The classification of sites through curves of Site Index allows to predict the yield of the planted forests at a certain age of the stand and to plan cultural treatments. The goal of this research was to compare linear and non-linear models of fixed effects vs. mixed non-linear models to estimate the site index in plantations of Prosopis alba var Griseb in the irrigated area of the province of Santiago del Estero, Argentina using the guide curve method. The data used comes from temporary plots, permanent plots and growth data from the stem analysis of selected individuals based on their greater growth in height within the sampled areas. The registered variable for the evaluation of the site was the dominant Height (HD), defined as the average height of the 100 thickest trees per hectare. Considering that the source of data from repeated measurements on the same subject implies the presence of correlation and/or heteroscedasticity, it was proposed to evaluate statistical models that allow to properly representing the structure of the variance-covariance matrix, improving the accuracy in the adjustment. From the analysis of the results, it appears that the models non-linear mixed models have had better performance in the adjustment of the Site Index than linear and non-linear models of fixed effects. The most accurate model (smallest AIC and BIC) in the site index estimation was the mixed non-linear regression model of 'Gompertz', with structure of composite symmetry correlation and exponential heteroscedasticity.v.25 n.2 2019
Fil: Senilliani, Maria Gracia. Universidad Nacional de Santiago del Estero. Facultad de Ciencias Forestales; Argentina
Fil: Bruno, Cecilia Ines. Instituto Nacional de Tecnologia Agropecuaria. Centro de Investigaciones Agropecuarias. Unidad de Fitopatologia y Modelizacion Agricola. Grupo Vinculado Catedra de Estadistica y Biometria de la Facultad de Ciencias Agropecuarias de la Universidad Nacional de Cordoba Al Ufyma | Consejo Nacional de Investigaciones Cientificas y Tecnicas. Centro Cientifico Tecnologico Conicet - Cordoba. Unidad de Fitopatologia y Modelizacion Agricola. Grupo Vinculado Catedra de Estadistica y Biometria de la Facultad de Ciencias Agropecuarias de la Universidad Nacional de Cordoba Al Ufyma.; Argentina
Fil: Brassiolo, Miguel Marcelo. Universidad Nacional de Santiago del Estero. Facultad de Ciencias Forestales; Argentina
description The classification of sites through curves of Site Index allows to predict the yield of the planted forests at a certain age of the stand and to plan cultural treatments. The goal of this research was to compare linear and non-linear models of fixed effects vs. mixed non-linear models to estimate the site index in plantations of Prosopis alba var Griseb in the irrigated area of the province of Santiago del Estero, Argentina using the guide curve method. The data used comes from temporary plots, permanent plots and growth data from the stem analysis of selected individuals based on their greater growth in height within the sampled areas. The registered variable for the evaluation of the site was the dominant Height (HD), defined as the average height of the 100 thickest trees per hectare. Considering that the source of data from repeated measurements on the same subject implies the presence of correlation and/or heteroscedasticity, it was proposed to evaluate statistical models that allow to properly representing the structure of the variance-covariance matrix, improving the accuracy in the adjustment. From the analysis of the results, it appears that the models non-linear mixed models have had better performance in the adjustment of the Site Index than linear and non-linear models of fixed effects. The most accurate model (smallest AIC and BIC) in the site index estimation was the mixed non-linear regression model of 'Gompertz', with structure of composite symmetry correlation and exponential heteroscedasticity.v.25 n.2 2019
publishDate 2019
dc.date.none.fl_str_mv 2019-06
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/106550
Senilliani, Maria Gracia; Bruno, Cecilia Ines; Brassiolo, Miguel Marcelo; Site index for Prosopis alba plantations in the semi-arid chaco through mixed models; Universidade Federal de Lavras; Cerne; 25; 2; 6-2019; 195-202
0104-7760
CONICET Digital
CONICET
url http://hdl.handle.net/11336/106550
identifier_str_mv Senilliani, Maria Gracia; Bruno, Cecilia Ines; Brassiolo, Miguel Marcelo; Site index for Prosopis alba plantations in the semi-arid chaco through mixed models; Universidade Federal de Lavras; Cerne; 25; 2; 6-2019; 195-202
0104-7760
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://cerne.ufla.br/site/index.php/CERNE/article/view/2035/1132
info:eu-repo/semantics/altIdentifier/doi/10.1590/01047760201925022622
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Universidade Federal de Lavras
publisher.none.fl_str_mv Universidade Federal de Lavras
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 12.48226

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