Western larch (Larix occidentalis Nutt.) is a locally important species in the Nelson Forest Region, and to a lesser extent, in the Kamloops Forest Region. Its range extends from west of the Rockies to Okanagan Lake, and north to Salmon Arm, in the IDF, ICH, MS, and ESSF biogeoclimatic zones. Prior to this study, the site index curves developed for western larch in western Montana were used to model height and estimate site index in British Columbia. It has been suggested that these curves may not adequately reflect the height growth patterns of western larch in BC. Differences could arise from genetics, different methods of selecting sample trees, or climatic differences. The objective of this project was to produce accurate height growth models for western larch in BC.

Accurate and reliable predictions of site index (height of dominant trees at a reference age, usually 50 years at breast-height) for timber crop species is essential for silvicultural site-specific decision making. Site index can be predicted from site quality once the relationship between site index and site quality has been quantified. Site quality is defined as the sum of all environmental factors affecting the biotic community, such as the factors directly influencing the growth of vascular plants (light, heat, soil moisture, soil nutrients, and soil aeration). Since these factors vary greatly in time, indirect estimates of site quality have widely been used as predictors for site index in various multiple regression models. Trembling aspen (Populus tremuloides Michx.) is the most widely distributed broadleaf species in British Columbia, especially in the Boreal White and Black Spruce (BWBS) biogeoclimatic zone. Growing this species for sustainable timber production requires a good understanding of its productivity attributes and accurate predictions of its growth. This extension note presents (1) relationships between trembling aspen site index and some indirect measures of site quality, and (2) site index prediction models using the indirect measures of site quality as predictors.