Evaluating tree competition indices as predictors of basal area increment in western Montana forests

Fire hazard reduction treatments are commonly applied to mixed-species coniferous forests in western Montana, USA, to modify fuels structures and alter the competitive environments of individual trees. An improved understanding of how competition can be measured and how it conditions individual tree growth is needed for projecting the development of these forests, with and without treatment. Numerous studies have evaluated how competition affects tree growth and many indices have been developed to quantify the competition an individual tree experiences. These studies suggest that no single competition index or a single class of indices is universally superior; indices perform differently according to forest type and forest conditions. We chose several widely used distance-independent and distance-dependent competition indices, and also derived anisotropic distance-dependent indices from estimates of light interception by tree crowns. We evaluated the effectiveness of these competition measures for predicting basal area increment (BAI) of Pinus ponderosa, Pseudotsuga menziesii, and Larix occidentalis in western Montana. The best distance-dependent competition indices explained a larger proportion of growth variation than the best distance-independent indices (64% vs. 56%). This result indicates that competition is an important growth determinant in these forests and that competition varies locally, with variable tree densities and relatively complex stand structures creating heterogeneous neighborhood conditions. Competition indices derived from light interception models were only weakly correlated with other indices and performed poorly in terms of predicting tree growth. This result accords with previous observations that competition for light is not the primarily growth limitation for trees in the semi-arid conditions of western Montana. More sophisticated light availability models could be used to better assess variability in light interception and its marginal contribution to predictive accuracy of radial tree growth. Diameter and distance-dependent BAI models were developed for growth prediction at the species level and for all species combined.