Determining the Effects of Biogeoclimatic Properties on Different Site Index Systems of Douglas-fir in the Coastal Pacific Northwest

Douglas-fir (Pseudotsuga menziesii [Mirb.] Franco) site index is commonly used as a measure of site productivity in many regions of the world, including the US Pacific Northwest. However, site index presents numerous limitations as a measure of site productivity because it is based on top height growth potential, which has been estimated in stands managed under many alternative silvicultural regimes. Three alternative site index systems (King's, Nigh's, and Flewelling's) and a forest company-reported site index were examined and compared according to biogeoclimatic variables from 71 Douglas-fir installations throughout the coastal Pacific Northwest. Climate, physiographic, soil water, and soil nitrogen (N) properties and stand variables from mapped sources and from field measurements were examined as predictors of site index. The best site and soil productivity variables for predicting Douglas-fir growth using these site indices were identified by Pearson correlations and boosted regression tree models based on mapped predictors and a combination of mapped and measured predictors. All three site indices predicted greater height growth on stands with lower elevations, greater soil available water supply, lower surface soil and forest floor carbon to N ratios, and high stand relative densities. Models based on a combination of mapped and field-measured data tended to perform better than those from only mapped data, suggesting the importance of at least some field measurements for accurately assessing Douglas-fir site index. For these juvenile stands, all three site indices produced comparable height predictions and had similar effects from biogeoclimatic variables. The fact that the measured site index methods were more related to each other than to the company-reported site index suggests that site indices of intensively Douglas-fir plantations should be reassessed to improve volume growth and harvesting predictions.