Predicting lodgepole pine site index from climatic parameters in Alberta

We sought to evaluate the impact of climatic variables on site productivity of lodgepole pine (Pinus contorta var. latifolia Engelm.) for the province of Alberta. Climatic data were obtained from the Alberta Climate Model, which is based on 30-year normals from the provincial weather station network. Mapping methods were based on ANUSPLIN, Hutchinson's thin-plate smoothing spline in four dimensions (latitude, longitude, elevation, climatic variable). Site indices based on stem analysis (observed dominant height at an index age of 50 years at breast height) were used as a measure of forest site productivity. A total of 1145 site index plots were available for lodgepole pine, the major forest species in Alberta. Regression analyses were used to predict site index as a function of climatic variables for each plot. The strongest linear predictors of site index were growing degree days > 5 degrees (GDD5), the Julian date when GDD5 reaches 100 (D100), and July mean temperature (MTWM). A nonlinear model with D100 as the predictor variable was chosen as the final model. Both the observed and the predicted site indices from the 1145 locations were interpolated using ANUSPLIN and mapped using ArcView. We concluded that climate is an important component of site productivity, accounting for about one quarter of the variation in lodgepole pine site index across the province.