Where to find structural grade timber: a case study in ponderosa pine based on stand and tree level factors

Autores
Caballe, Gonzalo; Santaclara, Oscar; Diez, Juan Pablo; Letourneau, Federico Jorge; Merlo, Esther; Martinez Meier, Alejandro
Año de publicación
2020
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Using portable acoustic tools, measurements of dynamic modulus of elasticity (Ed) were made in standing ponderosa pine (Pinus ponderosa (Dougl. ex Laws)) trees (n =437) growing in 22 stands encompassing the range of environmental site conditions and ages of the plantations that have been established in NW Patagonia, Argentina. The objectives of this research were to (i) identify the stand and tree-level factors associated with the variation in Ed and, with the most suitable variables (ii) develop a descriptive model to Ed for ponderosa pine grown in NW Patagonia Argentina as the first step of a predictive model. Tree and stand variables showed a wide range of variation and Ed ranged ten-fold, from 2.13 GPa to 22.1 GPa, with a mean value of 11.2 Gpa. The cross-correlations analysis performed among Ed and independent tree and stand variables showed almost all variables to be significantly related to Ed. The main positive and significant correlation was found for total tree height (H, r = 0.78, p < 0.001), top height of the stand (H100, r = 0.78, p < 0.001) and basal area of the stand (G, r = 0.68, p < 0.001). Nevertheless, the most suitable independent variables for modelling Ed were two stand variables: age at breast height (ABH) and site index (SI20) and two tree variables: stem slenderness (S, tree height/diameter at breast height) and social status or relative height (RH = H/H100). In combination, ABH, SI20, S and RH accounted for 68.4% of the variation in Ed within the sample population. This model could be readily applied by managers to estimate stand-level Ed, giving them greater understanding of how they can manipulate stands to achieve desired end product outcomes.
Estación Experimental Agropecuaria Bariloche
Fil: Caballe, Gonzalo. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Bariloche; Argentina
Fil: Santaclara, Oscar. S.L. Parque Tecnológico de Galicia. Madera Plus Calidad Forestal; España
Fil: Diez, Juan Pablo. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Bariloche; Argentina
Fil: Letourneau, Federico Jorge. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Bariloche. Campo Forestal Anexo San Martin; Argentina
Fil: Merlo, Esther. S.L. Parque Tecnológico de Galicia. Madera Plus Calidad Forestal; España
Fil: Martinez Meier, Alejandro. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Bariloche. Área de Recursos Forestales. Grupo de Ecología Forestal; Argentina
Fuente
Forest Ecology and Management 459 : 117849 (Marzo 2020)
Materia
Pinus Ponderosa
Madera
Elasticidad
Pinus
Wood
Elasticity
Pino Ponderosa
Región Patagónica
Nivel de accesibilidad
acceso restringido
Condiciones de uso
Repositorio
INTA Digital (INTA)
Institución
Instituto Nacional de Tecnología Agropecuaria
OAI Identificador
oai:localhost:20.500.12123/6917
Acceder
id INTADig_2f149c57951ca07c5561849b504da00f
oai_identifier_str oai:localhost:20.500.12123/6917
network_acronym_str INTADig
repository_id_str l
network_name_str INTA Digital (INTA)
spelling Where to find structural grade timber: a case study in ponderosa pine based on stand and tree level factorsCaballe, GonzaloSantaclara, OscarDiez, Juan PabloLetourneau, Federico JorgeMerlo, EstherMartinez Meier, AlejandroPinus PonderosaMaderaElasticidadPinusWoodElasticityPino PonderosaRegión PatagónicaUsing portable acoustic tools, measurements of dynamic modulus of elasticity (Ed) were made in standing ponderosa pine (Pinus ponderosa (Dougl. ex Laws)) trees (n =437) growing in 22 stands encompassing the range of environmental site conditions and ages of the plantations that have been established in NW Patagonia, Argentina. The objectives of this research were to (i) identify the stand and tree-level factors associated with the variation in Ed and, with the most suitable variables (ii) develop a descriptive model to Ed for ponderosa pine grown in NW Patagonia Argentina as the first step of a predictive model. Tree and stand variables showed a wide range of variation and Ed ranged ten-fold, from 2.13 GPa to 22.1 GPa, with a mean value of 11.2 Gpa. The cross-correlations analysis performed among Ed and independent tree and stand variables showed almost all variables to be significantly related to Ed. The main positive and significant correlation was found for total tree height (H, r = 0.78, p < 0.001), top height of the stand (H100, r = 0.78, p < 0.001) and basal area of the stand (G, r = 0.68, p < 0.001). Nevertheless, the most suitable independent variables for modelling Ed were two stand variables: age at breast height (ABH) and site index (SI20) and two tree variables: stem slenderness (S, tree height/diameter at breast height) and social status or relative height (RH = H/H100). In combination, ABH, SI20, S and RH accounted for 68.4% of the variation in Ed within the sample population. This model could be readily applied by managers to estimate stand-level Ed, giving them greater understanding of how they can manipulate stands to achieve desired end product outcomes.Estación Experimental Agropecuaria BarilocheFil: Caballe, Gonzalo. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Bariloche; ArgentinaFil: Santaclara, Oscar. S.L. Parque Tecnológico de Galicia. Madera Plus Calidad Forestal; EspañaFil: Diez, Juan Pablo. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Bariloche; ArgentinaFil: Letourneau, Federico Jorge. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Bariloche. Campo Forestal Anexo San Martin; ArgentinaFil: Merlo, Esther. S.L. Parque Tecnológico de Galicia. Madera Plus Calidad Forestal; EspañaFil: Martinez Meier, Alejandro. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Bariloche. Área de Recursos Forestales. Grupo de Ecología Forestal; ArgentinaElsevier2020-03-11T10:41:17Z2020-03-11T10:41:17Z2020-03-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfhttp://hdl.handle.net/20.500.12123/6917https://www.sciencedirect.com/science/article/pii/S03781127193204070378-1127https://doi.org/10.1016/j.foreco.2019.117849Forest Ecology and Management 459 : 117849 (Marzo 2020)reponame:INTA Digital (INTA)instname:Instituto Nacional de Tecnología Agropecuariaenginfo:eu-repo/semantics/restrictedAccess2025-09-29T13:44:53Zoai:localhost:20.500.12123/6917instacron:INTAInstitucionalhttp://repositorio.inta.gob.ar/Organismo científico-tecnológicoNo correspondehttp://repositorio.inta.gob.ar/oai/requesttripaldi.nicolas@inta.gob.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:l2025-09-29 13:44:54.048INTA Digital (INTA) - Instituto Nacional de Tecnología Agropecuariafalse
dc.title.none.fl_str_mv Where to find structural grade timber: a case study in ponderosa pine based on stand and tree level factors
title Where to find structural grade timber: a case study in ponderosa pine based on stand and tree level factors
spellingShingle Where to find structural grade timber: a case study in ponderosa pine based on stand and tree level factors
Caballe, Gonzalo
Pinus Ponderosa
Madera
Elasticidad
Pinus
Wood
Elasticity
Pino Ponderosa
Región Patagónica
title_short Where to find structural grade timber: a case study in ponderosa pine based on stand and tree level factors
title_full Where to find structural grade timber: a case study in ponderosa pine based on stand and tree level factors
title_fullStr Where to find structural grade timber: a case study in ponderosa pine based on stand and tree level factors
title_full_unstemmed Where to find structural grade timber: a case study in ponderosa pine based on stand and tree level factors
title_sort Where to find structural grade timber: a case study in ponderosa pine based on stand and tree level factors
dc.creator.none.fl_str_mv Caballe, Gonzalo
Santaclara, Oscar
Diez, Juan Pablo
Letourneau, Federico Jorge
Merlo, Esther
Martinez Meier, Alejandro
author Caballe, Gonzalo
author_facet Caballe, Gonzalo
Santaclara, Oscar
Diez, Juan Pablo
Letourneau, Federico Jorge
Merlo, Esther
Martinez Meier, Alejandro
author_role author
author2 Santaclara, Oscar
Diez, Juan Pablo
Letourneau, Federico Jorge
Merlo, Esther
Martinez Meier, Alejandro
author2_role author
author
author
author
author
dc.subject.none.fl_str_mv Pinus Ponderosa
Madera
Elasticidad
Pinus
Wood
Elasticity
Pino Ponderosa
Región Patagónica
topic Pinus Ponderosa
Madera
Elasticidad
Pinus
Wood
Elasticity
Pino Ponderosa
Región Patagónica
dc.description.none.fl_txt_mv Using portable acoustic tools, measurements of dynamic modulus of elasticity (Ed) were made in standing ponderosa pine (Pinus ponderosa (Dougl. ex Laws)) trees (n =437) growing in 22 stands encompassing the range of environmental site conditions and ages of the plantations that have been established in NW Patagonia, Argentina. The objectives of this research were to (i) identify the stand and tree-level factors associated with the variation in Ed and, with the most suitable variables (ii) develop a descriptive model to Ed for ponderosa pine grown in NW Patagonia Argentina as the first step of a predictive model. Tree and stand variables showed a wide range of variation and Ed ranged ten-fold, from 2.13 GPa to 22.1 GPa, with a mean value of 11.2 Gpa. The cross-correlations analysis performed among Ed and independent tree and stand variables showed almost all variables to be significantly related to Ed. The main positive and significant correlation was found for total tree height (H, r = 0.78, p < 0.001), top height of the stand (H100, r = 0.78, p < 0.001) and basal area of the stand (G, r = 0.68, p < 0.001). Nevertheless, the most suitable independent variables for modelling Ed were two stand variables: age at breast height (ABH) and site index (SI20) and two tree variables: stem slenderness (S, tree height/diameter at breast height) and social status or relative height (RH = H/H100). In combination, ABH, SI20, S and RH accounted for 68.4% of the variation in Ed within the sample population. This model could be readily applied by managers to estimate stand-level Ed, giving them greater understanding of how they can manipulate stands to achieve desired end product outcomes.
Estación Experimental Agropecuaria Bariloche
Fil: Caballe, Gonzalo. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Bariloche; Argentina
Fil: Santaclara, Oscar. S.L. Parque Tecnológico de Galicia. Madera Plus Calidad Forestal; España
Fil: Diez, Juan Pablo. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Bariloche; Argentina
Fil: Letourneau, Federico Jorge. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Bariloche. Campo Forestal Anexo San Martin; Argentina
Fil: Merlo, Esther. S.L. Parque Tecnológico de Galicia. Madera Plus Calidad Forestal; España
Fil: Martinez Meier, Alejandro. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Bariloche. Área de Recursos Forestales. Grupo de Ecología Forestal; Argentina
description Using portable acoustic tools, measurements of dynamic modulus of elasticity (Ed) were made in standing ponderosa pine (Pinus ponderosa (Dougl. ex Laws)) trees (n =437) growing in 22 stands encompassing the range of environmental site conditions and ages of the plantations that have been established in NW Patagonia, Argentina. The objectives of this research were to (i) identify the stand and tree-level factors associated with the variation in Ed and, with the most suitable variables (ii) develop a descriptive model to Ed for ponderosa pine grown in NW Patagonia Argentina as the first step of a predictive model. Tree and stand variables showed a wide range of variation and Ed ranged ten-fold, from 2.13 GPa to 22.1 GPa, with a mean value of 11.2 Gpa. The cross-correlations analysis performed among Ed and independent tree and stand variables showed almost all variables to be significantly related to Ed. The main positive and significant correlation was found for total tree height (H, r = 0.78, p < 0.001), top height of the stand (H100, r = 0.78, p < 0.001) and basal area of the stand (G, r = 0.68, p < 0.001). Nevertheless, the most suitable independent variables for modelling Ed were two stand variables: age at breast height (ABH) and site index (SI20) and two tree variables: stem slenderness (S, tree height/diameter at breast height) and social status or relative height (RH = H/H100). In combination, ABH, SI20, S and RH accounted for 68.4% of the variation in Ed within the sample population. This model could be readily applied by managers to estimate stand-level Ed, giving them greater understanding of how they can manipulate stands to achieve desired end product outcomes.
publishDate 2020
dc.date.none.fl_str_mv 2020-03-11T10:41:17Z
2020-03-11T10:41:17Z
2020-03-01
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/20.500.12123/6917
https://www.sciencedirect.com/science/article/pii/S0378112719320407
0378-1127
https://doi.org/10.1016/j.foreco.2019.117849
url http://hdl.handle.net/20.500.12123/6917
https://www.sciencedirect.com/science/article/pii/S0378112719320407
https://doi.org/10.1016/j.foreco.2019.117849
identifier_str_mv 0378-1127
dc.language.none.fl_str_mv eng
language eng
dc.rights.none.fl_str_mv info:eu-repo/semantics/restrictedAccess
eu_rights_str_mv restrictedAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv Forest Ecology and Management 459 : 117849 (Marzo 2020)
reponame:INTA Digital (INTA)
instname:Instituto Nacional de Tecnología Agropecuaria
reponame_str INTA Digital (INTA)
collection INTA Digital (INTA)
instname_str Instituto Nacional de Tecnología Agropecuaria
repository.name.fl_str_mv INTA Digital (INTA) - Instituto Nacional de Tecnología Agropecuaria
repository.mail.fl_str_mv tripaldi.nicolas@inta.gob.ar
_version_ 1844619142713311232
score 12.558318

Publicaciones similares