Statistical models predict lumber volume and value in young-growth fir trees, suggesting efficient resource management.
Statistical models were developed for predicting the lumber volume and value of young-growth red, white, and grand fir trees. Equations were derived to predict gross tree volume and cubic recovery percent and then combined to predict lumber volume. Two methods were used to predict lumber value; one predicts the lumber volume in each of three lumber grades using nonlinear regression, and the other predicts an indexed value using linear regression. Field data from recovery studies in Idaho, Oregon, and California were used to develop regression equations. Forest Sci. 30:871-882.
No takes yet. Share an insight, caveat, or question.
Ernst et al. (1984) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: