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Simulating wood quality in forest management models
Abstract: The raw material properties of wood develop as the tree grows, laying down wood cells with specific properties, and forming the stem structure that is focal for timber quality. This development is influenced by genetic and environmental factors and forest management practices. It is desirable in growth and yield models intended for the economic assessment of management practices to include some indication of wood quality and how it is affected by genetics, environmental factors and silvicultural measures. This paper reviews approaches and models that allow us to consider the development of wood quality in combination with tree growth, and thus to include wood quality in the assessment of the value of the yield. We present such models as classified into three categories based on their complexity and information needs: quality indicators, static quality models, and dynamic quality models. We illustrate three advanced dynamic quality models and their applications with example case studies. These include empirical, hybrid, and mechanistic models applied to predictions of both sawn timber and fibre properties. Finally, we consider the current challenges for wood quality modelling in connection with growth models.
Simulating wood quality in forest management models
Abstract: The raw material properties of wood develop as the tree grows, laying down wood cells with specific properties, and forming the stem structure that is focal for timber quality. This development is influenced by genetic and environmental factors and forest management practices. It is desirable in growth and yield models intended for the economic assessment of management practices to include some indication of wood quality and how it is affected by genetics, environmental factors and silvicultural measures. This paper reviews approaches and models that allow us to consider the development of wood quality in combination with tree growth, and thus to include wood quality in the assessment of the value of the yield. We present such models as classified into three categories based on their complexity and information needs: quality indicators, static quality models, and dynamic quality models. We illustrate three advanced dynamic quality models and their applications with example case studies. These include empirical, hybrid, and mechanistic models applied to predictions of both sawn timber and fibre properties. Finally, we consider the current challenges for wood quality modelling in connection with growth models.
Simulating wood quality in forest management models
Mäkelä, A. (author) / Grace, J.C. (author) / Deckmyn, Gaby (author) / Kantola, A. (author) / Campioli, Matteo (author)
2010-01-01
2171-5068 ; Forest systems
Article (Journal)
Electronic Resource
English
DDC:
690
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