Relationships between white spruce vulnerability to the white pine weevil and ecological site conditions in the interior of British Columbia

A correlation study was conducted on 80 forest sites in 1995 to develop an empirical model to rate stands of white spruce for their susceptibility to spruce weevil (Pissodes strobi (Peck)) attack based on ecological, stand and vegetation variables. In total, 15 ecological and stand variables were assessed, as were 14 vegetation species. Various strategies were used to reduce the number of independent variables including: bivariate analyses of independent variables with the dependent variable (current weevil attack), Pearson product-moment correlations, principal component analyses, all-possible subset regressions and step-wise regression. The criteria to select the "best" regression models included: maximization of the coefficient of multiple determination; maximization of the F-ratio; minimization of the standard error of the estimate; and minimization of model complexity. The "best" multiple regression solution included the independent variables: stand age, stand density and elevation (F (3, 71) = 18.025, p = 0.001). Two variable ordering techniques both confirmed that stand density was the least important variable and that elevation and stand age were the most important. Further, the preliminary analyses also indicated that future experimental work may show that slope position, slope percent, humus content and perhaps one or two vegetation species may serve as useful predictors of weevil attack. Finally, the following "simple rules" are presented that allow the practitioner to define a high weevil hazard in this subzone: -at stand densities > 1600 stems per ha, a high weevil hazard exists below 775 m in elevation; -at stand densities between 1200 to 1600 stems per ha, a high weevil hazard exists below 800 m; and -at stand densities < 1200 stems per ha, a high weevil hazard exists below 825 m. A technique is described in the text which allows these rules to be verified through ground surveys.