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

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...

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Main Authors: Caballe, Gonzalo, Santaclara, Oscar, Diez, Juan Pablo, Letourneau, Federico Jorge, Merlo, Esther, Martinez Meier, Alejandro
Format: info:ar-repo/semantics/artículo
Language:Inglés
Published: Elsevier 2020
Subjects:
Online Access: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
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author Caballe, Gonzalo
Santaclara, Oscar
Diez, Juan Pablo
Letourneau, Federico Jorge
Merlo, Esther
Martinez Meier, Alejandro
author_browse Caballe, Gonzalo
Diez, Juan Pablo
Letourneau, Federico Jorge
Martinez Meier, Alejandro
Merlo, Esther
Santaclara, Oscar
author_facet Caballe, Gonzalo
Santaclara, Oscar
Diez, Juan Pablo
Letourneau, Federico Jorge
Merlo, Esther
Martinez Meier, Alejandro
author_sort Caballe, Gonzalo
collection INTA Digital
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.
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institution Instituto Nacional de Tecnología Agropecuaria (INTA -Argentina)
language Inglés
publishDate 2020
publishDateRange 2020
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spelling INTA69172020-03-11T10:50:57Z Where to find structural grade timber: a case study in ponderosa pine based on stand and tree level factors Caballe, Gonzalo Santaclara, Oscar Diez, Juan Pablo Letourneau, Federico Jorge Merlo, Esther Martinez Meier, Alejandro Pinus Ponderosa Madera Elasticidad Pinus Wood Elasticity Pino Ponderosa Región Patagónica 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 2020-03-11T10:41:17Z 2020-03-11T10:41:17Z 2020-03-01 info:ar-repo/semantics/artículo info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion 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 eng info:eu-repo/semantics/restrictedAccess application/pdf Elsevier Forest Ecology and Management 459 : 117849 (Marzo 2020)
spellingShingle Pinus Ponderosa
Madera
Elasticidad
Pinus
Wood
Elasticity
Pino Ponderosa
Región Patagónica
Caballe, Gonzalo
Santaclara, Oscar
Diez, Juan Pablo
Letourneau, Federico Jorge
Merlo, Esther
Martinez Meier, Alejandro
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
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_short 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
topic Pinus Ponderosa
Madera
Elasticidad
Pinus
Wood
Elasticity
Pino Ponderosa
Región Patagónica
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
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