Graduate Thesis Or Dissertation
 

Simulating Wood Properties in the Context of a Growth and Yield Model for Planted Douglas-fir

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  • Forest growth and yield models are critical to supporting decision making in forestry, but often lack considerations for wood properties. The feasibility of simulating wood properties in the context of a Douglas-fir individual tree growth and yield model was evaluated. This assessment explored the effect of predicted sapwood width, stem taper, branch size and juvenile wood proportion on recovery of utility poles and sawn lumber. Results from the assessment indicated wood properties can be simulated in the context of growth and yield modeling systems with biologically reasonable results. The same assessment indicated recovery of wood products may be overestimated in the absence of penalties for stem defects. Two critical Douglas-fir wood attributes, knot geometry and wood density, were targeted for modeling after the feasibility analysis. A model for Douglas-fir knot pith curvature was developed based on predicted branch angle and growth ring position over time. Based on the predicted knot pith curvature, knot geometry could be implied from branch radius predicted at the stem surface. Medical computed tomography was identified as one way to rapidly and efficiently estimate Douglas-fir wood density from the proxy of X-ray attenuation. In support of deploying this technology, the effect of wood moisture content and other scanner settings on the relationship of X-ray attenuation and wood density was modeled. Results indicated that X-ray attenuation explains most of the variation in predicting wood density, but moisture content and other scanner settings have a small but significant effect. A number of knowledge gaps should be resolved to sufficiently and robustly simulate wood properties in the context of Douglas-fir growth and yield simulation. Models for sawing simulation and for addressing deficits in existing wood properties models should be an important focus for future research in this field.
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