Models for Predicting Clearwood Mechanical Properties of Scots Pine

• Published in: Forest science Vol. 62; no. 4; pp. 403 - 413
• Main Authors: Auty, David, Achim, Alexis, Macdonald, Elspeth, Cameron, Andrew D, Gardiner, Barry A
• Format: Journal Article
• Language: English
• Published: Bethesda Oxford University Press 30.08.2016; Society of American Foresters
• Subjects: Age; Environmental Sciences; Growth models; Growth rate; Life Sciences; Mechanical properties; Pinus sylvestris; Timber; Trees; British Isles, Scotland; models; Pinus sylvestris L; modulus of elasticity; nonlinear mixed-effects; modulus of rupture; simulation
• ISSN: 0015-749X; 1938-3738
• DOI: 10.5849/forsci.15-092

Wood mechanical properties, such as modulus of elasticity (MOE) and modulus of rupture (MOR), are important determinants of solid lumber performance and value. These properties vary systematically at different scales owing to multiple, potentially confounding, factors. Therefore, a statistical modeling approach may be an effective way to predict the impact of silvicultural practices on mechanical properties. The aim of this study was to develop models for predicting MOE and MOR in Scots pine (Pinus sylvestris L.), as functions of cambial age, height in the stem, wood density, and microfibril angle (MFA). Thirty-six trees were sampled from four mature Scots pine plantations in Scotland, UK. Longitudinal MOE and MOR were determined in static bending on 513 small (300 × 20 × 20 mm) defect-free samples. Nonlinear mixed-effects models based on an exponential function of cambial age were developed to predict the within-stem patterns of variation. The best model for MOR included cambial age, height in the stem, and sample density as explanatory variables, whereas the best MOE model also included a density/MFA term in the predictors. In growth simulations over a range of typical scenarios, the largest effect of silvicultural interventions was on the proportion of juvenile wood in the stem, but these had a negligible impact on mean tree MOE and MOR. The models will be incorporated into a growth, yield, and wood quality simulation system.