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Predicting the branching properties of Sitka Spruce grown in Great Britain.

Gardiner, Barry A; Achim, A; Daquitaine, R; Leban, Jean-Michel

Authors

Barry A Gardiner

A Achim

R Daquitaine

Jean-Michel Leban



Abstract

Predictions of the branching characteristics of Sitka spruce (Picea sitchensis(Bong.) Carr.) were made as part of the development of a timber properties simulation tool. For each annual growth unit, non-linear modelling was used to describe the average number of branches and their associated diameter,insertion angle, and probability of being alive. The parameters for the model were obtained using the branching characteristics of 60 trees collected froma range of locations across Scotland and northern England. The non-linear equations describing the branching properties gave an adequate representation of the mean of each branch property from the top to the base of the tree.Analysis of the residuals around the stem revealed that branches grew bigger on the south side but were more numerous on the north side. The predictions used a total of only six predictor variables that can be obtained from normal mensurational data and from the height growth history of the trees. Yield tables could hence be used to run two simulations of typical Sitka spruce stands managed under a thinning or no-thinning regime. As expected, the effect of thinning was to increase branch diameter, to lower the height at which branches die, and to increase the number of branches without having any effect on their insertion angle. After incorporation of clear-wood properties, the model will be used to predict the properties of sawn battens.

Citation

Gardiner, B. A., Achim, A., Daquitaine, R., & Leban, J.-M. (2006). Predicting the branching properties of Sitka Spruce grown in Great Britain. The New Zealand journal of forestry, 36, 246-264

Journal Article Type Article
Publication Date Jun 1, 2006
Deposit Date Jun 10, 2008
Print ISSN 0028-8284
Peer Reviewed Peer Reviewed
Volume 36
Pages 246-264
Keywords branching; knots; wood quality modelling;
Public URL http://researchrepository.napier.ac.uk/id/eprint/1978



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