Canadian Forest Service Publications
Modeling lumber yield of white spruce in Alberta, Canada: a comparative approach. 2016. Li, C.; Huang, S.; Barclay, H.; Sidders, D. Journal of Forest Research 21(6):271-279.
Issued by: Northern Forestry Centre
Catalog ID: 37315
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Estimation of lumber yield from a forest inventory is important in determining the optimal utilization of available regional wood supply. In this study, we review existing approaches of lumber yield estimation, including knowledge-based empirical board-foot log rules used in the United States and some regions of Canada, survey-based wood conversion factors, and optimization technologybased computer simulations. Lumber yields estimated from different approaches are then compared using six datasets from a white spruce commercial thinning experiment in Alberta, Canada. Our results indicated that (1) estimated lumber yield can be significantly different when different methods are employed; (2) board-foot log rules often underestimate lumber yield; (3) wood conversion factors represent regional average of lumber yield as a constant and thus are unsuitable for forest inventory-based lumber yield estimation; and (4) optimization technology-based computer simulations can provide the best estimate of lumber yield for a given forest inventory as long as the mill conditions and lumber dimensions from market demand are specified. Forestry investment in applying computer simulation methods should be encouraged in sawmill operations to improve lumber yield and enhance environmental protection, because, for a given amount of lumber, improving lumber yield means reduced demand for harvest operations.
Plain Language Summary
A forest inventory is a survey of a forest area to help determine the condition of the area and timber (including the volume and species) for specific purposes such as evaluating, planning, purchasing, managing, or harvesting. Estimating lumber yield from a forest inventory is important in determining the best use of available regional wood supply. However, there are several methods used to estimate lumber yield, different expressions of lumber yield, and different systems of measuring lumber yield. These variations might cause confusion and could present challenges to forest managers and practitioners who are trying to determine which method is appropriate to use. In this study, we reviewed existing methods of estimating lumber yield including board-foot log rules, wood conversion factors, and computer simulations. The estimated lumber yields from these different methods are then compared using six sets of data from a commercial thinning experiment that used white spruce in Alberta, Canada. Our results showed that estimated lumber yields can vary widely when different methods are used; board-foot log rules often underestimate lumber yield and estimates must be corrected; wood conversion factors use regional averages of lumber yields as a constant and thus are unsuitable for estimating forest-inventory based lumber yield; and as long as the mill conditions and lumber dimensions from market demand are specified, computer model simulations provide the best estimate of lumber yield for a given forest inventory.