Canadian Forest Service Publications
Modeling wood fiber attributes using forest inventory and environmental data for Newfoundland’s boreal forest. 2014. Lessard, E.; Fournier, R.A.; Luther, J.E.; Mazerolle, M.J.; van Lier, O.R. Forest Ecology and Management 313: 307-318.
Year: 2014
Issued by: Atlantic Forestry Centre
Catalog ID: 35313
Language: English
Availability: PDF (request by e-mail)
Available from the Journal's Web site. †
DOI: 10.1016/j.foreco.2013.10.030
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Abstract
We explore the possibility of predicting wood fiber attributes across Newfoundland for two commercial species: black spruce (Picea mariana (Mill.) B.S.P.) and balsam fir (Abies balsamea (L.) Mill.). Estimates of key fiber attributes (including wood density, coarseness, fiber length, and modulus of elasticity) were derived from measurements of wood cores taken from sample plots representing a wide structural gradient of forest stands. Candidate models for predicting fiber attributes at plot and landscape scales were developed using an information-theoretical approach and compared based on Akaike’s information criterion. The most influential variables were stand age and the presence of precommercial thinning. Other significant explanatory variables included those that characterize vegetation structure (mean diameter at breast height, dominant height), climate (annual precipitation, mean temperature of the growing season), and geography (elevation, latitude) depending on the species and fiber attribute being modeled. At the plot level, model inference gave root mean square errors of 5.3–11.9% for all attributes. At the landscape level, prediction errors were similar (5.4–12.1%), with the added benefit of being suitable for mapping fiber attributes across the landscape. The results obtained demonstrate the potential for predicting and mapping fiber attributes over a large region of boreal forest in Newfoundland, Canada.
Plain Language Summary
Forest industry and forest managers require information regarding variation in wood fibre attributes over large areas in order to expand the economic benefits from wood raw materials and to optimize forest value. This paper assesses the capability to predict a suite of wood fibre attributes of balsam fir and black spruce forests using environmental variables and forest variables measured at inventory plots or available from stand-level maps. The paper develops models for predicting fibre attributes using measurements of wood cores taken from sample plots across Newfoundland representing a wide structural gradient of forest stands. Significant explanatory variables depend on the species and fiber attribute being modeled including those that characterize vegetation structure (stand age, mean diameter at breast height, dominant height), disturbance (presence of precommercial thinning), climate (annual precipitation, mean temperature of the growing season), and geography (elevation, latitude). The results obtained demonstrate the potential for predicting and mapping fiber attributes over a large region of boreal forest in Newfoundland, Canada.