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Modelling wood property variation among Tasmanian Eucalyptus nitens plantations


Vega, M and Harrison, P and Hamilton, M and Musk, R and Adams, P and Potts, B, Modelling wood property variation among Tasmanian Eucalyptus nitens plantations, Forest Ecology and Management, 491 Article 119203. ISSN 0378-1127 (2021) [Refereed Article]

Copyright Statement

2021 Elsevier B.V.

DOI: doi:10.1016/j.foreco.2021.119203


Characterisation of forest resources is increasingly focused on tree wood properties as they are important drivers of economic value. We used the Random Forests machine learning algorithm to model variability among plantations of Eucalyptus nitens in key wood properties affecting the value of solid-wood products. Using breast-height disk samples from 46 even-aged stands of different ages across the island of Tasmania, Australia, we modelled site variation in SilviScan-3TM derived estimates of wood density, microfibril angle and modulus of elasticity. Regional-scale models were developed with respect to plantation age, environmental and climatic variables. Wood density and MOE increased, and MFA decreased with age. Wood density and MOE decreased and MFA increased with elevation. Increasing elevation is associated with increasing annual precipitation and decreasing temperature, but the variation in wood properties was mainly associated with precipitation. Wood density decreased and MFA increased with annual precipitation. MOE was positively related to wood density and negatively related to MFA, thus as expected, increased with annual precipitation. Using the Random Forests climate models we demonstrate the potential for predicting and mapping wood properties relevant for solid wood products at a scale that is relevant to strategic planning by the forest industry. Such models allow quantification of the impact of different growing conditions on the wood properties of harvested logs and therefore on wood products. When coupled with genetic, growth and economic models, these wood property models have the potential to assist in characterisation of standing forest resources and future estate planning.

Item Details

Item Type:Refereed Article
Keywords:wood density, microfibril angle, modulus of elasticity, non-parametric models, forest resource characterization, plasticity
Research Division:Agricultural, Veterinary and Food Sciences
Research Group:Forestry sciences
Research Field:Forestry management and environment
Objective Division:Plant Production and Plant Primary Products
Objective Group:Forestry
Objective Field:Hardwood plantations
UTAS Author:Vega, M (Dr Mario Vega Rivero)
UTAS Author:Harrison, P (Dr Peter Harrison)
UTAS Author:Potts, B (Professor Brad Potts)
ID Code:145972
Year Published:2021
Funding Support:Australian Research Council (IC150100004)
Web of Science® Times Cited:6
Deposited By:Plant Science
Deposited On:2021-08-14
Last Modified:2021-09-02

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