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Modelling the effects of site factors and silviculture on Sitka spruce timber quality

Sawn timber stacked at a sawmill
The timber quality model will help understand the effect of forest management decisions on the properties of the sawmill products

A model predicting Sitka spruce wood properties is being developed with three main aims:

  • To predict the timber properties of the existing Sitka spruce resource, on the basis of inventory data
  • To quantify the interaction between timber quality, site factors and silvicultural regime, which will enable forest managers to evaluate the effects of different management options
  • To estimate the impact on timber utilisation of changes in wood properties brought about by selection and breeding programmes.

Background

During 2003 Dr Jean-Michel Leban of INRA (Institut National de la Recherche Agronomique), Nancy in France was awarded a John Eadie fellowship by the Scottish Forestry Trust to adapt an existing Norway spruce timber quality model to Sitka spruce. Data collected by staff of Forest Research and Bangor University from a range of Sitka spruce stands throughout Britain were used to develop models predicting wood density and branching characteristics on the basis of tree height, diameter and age.

Software prototype

Example output from software model
Output from the software model showing predicted wood density distribution in the stem of an 80-year-old Sitka spruce growing at Yield Class 20, after planting at 2.6 m spacing and with no thinning. In relative terms green is the highest wood density with dark blue lowest and other shades intermediate. Note the comparatively large area of low density timber towards the base of the stem as a consequence of having been grown at wide spacing on a fertile site.

A prototype computer software programme has been developed which integrates the density and branching model relationships with growth models for Sitka spruce to enable simulations to be run for a range of scenarios.

The yield class, thinning treatment, initial spacing and age of the stand to be modelled can be selected from dropdown lists. The software then gives estimates of ring widths up the entire stem, i.e:

  • Taper on an annual basis
  • Wood density distribution within the stem
  • Number, size and insertion angle of branches at different heights up the tree.

Future work

At present the growth models available enable predictions to be made for the average tree in an even-aged stand. As more complex growth models are developed, these will be incorporated into the software to allow for the different diameter classes present in a stand. This will enable a more realistic assessment of the wood properties of various types of potential products, such as sawlogs and pulpwood, and will facilitate the modelling of uneven-aged stands.

Plans are also in place to extend the software to include predictions of grain angle and compression wood.

The next important step will be to link the timber quality model with sawing simulation software and batten performance models developed by the Building Research Establishment. This will allow estimates of batten mechanical properties and drying behaviour to be made for different silvicultural scenarios.

Software release

The prototype will be presented to the scientific community at the Fifth IUFRO workshop 5.01.04, New Zealand in November 2005. We are planning to release a PC Windows-based version for researchers in March 2006.