Modeling lumber value recovery in relation to selected tree characteristics in black spruce using the Optitek sawing simulator

Relationships between tree characteristics and tree-level product value from two types of sawmills (stud mill and optimized random mill) in black spruce (Picea mariana) were investigated. A sample of 172 trees (age 90 to 100 yrs) from black spruce natural stands showed large variations in tree characteristics and tree product value. Models were developed and compared according to selected statistical criteria (i.e., R 2 and the mean absolute mean error of predictions). The best fitted models for predicting tree-level lumber value recovery were considered to be the following forms for the two types of sawmills: 1) the second-order polynomial function with diameter at breast height (DBH) alone, 2) the polynomial function with only the cross product term of squared DBH and tree height, and 3) the power function with DBH, tree height, and tree taper. For both types of sawmills, the three final fitted model forms accounted for more than 92 percent of the total variation in lumber value recovery. The relationships in the models, including input-output and interaction factors, were further analyzed by calculating the elasticities of production and scale and the cross partial derivative of output with respect to the inputs. The analyses indicated that tree DBH had the greatest and most positive influence on the tree-level product value, followed by tree height; however, stem taper had a negative effect. The models were useful for estimating lumber value of individual trees and a forest stand before the trees are harvested.