Summary
Published in Forestry 1-13. https://doi.org/10.1093/forestry/cpx043
Northern hardwoods are an ecologically and economically important forest type in eastern North America. Historically, the hardwood supply came from old-growth forests dominated by large-diameter trees. Unfortunately, the repeated removal of high-quality trees has substantially degraded hardwood forests and reduced the profitability of the primary manufacturing sector. In this context, forest managers need tools to guide silvicultural investment decisions and to estimate pre-harvest stand value based on forest inventories. The objective of this study was to evaluate the performance of classification systems and measured variables used at the tree level to predict sawn product volumes of sugar maple (Acer saccharum Marsh.), yellow birch (Betula alleghaniensis Britton) and American beech (Fagus grandifolia Ehrh.). We developed statistical models to estimate the volume of lumber products, pulpwood, sawdust and residues based on tree DBH, species, tree grades in different combinations and tree height. Results show that the tree grade variable increased the explained variation in product volumes. As expected, the accuracy of product volumes estimation, based on root mean square error (RMSE), was poor for an individual tree, but improved as the number of trees increased.
Sector(s):
Forests
Categorie(s):
Scientific Article
Theme(s):
Forestry Research, Forests, Silviculture
Departmental author(s):
Author(s)
BÉDARD, Steve, Isabelle DUCHESNE, François GUILLEMETTE and Josianne DEBLOIS
Year of publication :
2017
Format :
PDF available upon request
How to get the publication :
Keywords :
Acer saccharum, Fagus grandifolia, Betula alleghaniensis, silviculture and yield of natural forests - hardwood stands, tree classification, lumber products, two-part conditional model, sugar maple, yellow birch, american beech, forestry research scientific article
