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
- Institución
- Instituto Nacional de Tecnología Agropecuaria
- OAI Identificador
- oai:localhost:20.500.12123/6917
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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/restrictedAccess2025-09-04T09:48:23Zoai: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:l2025-09-04 09:48:23.477INTA 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 |
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1842341376811859968 |
score |
12.623145 |