Assessing the impacts of species composition, top height and density on individual tree height prediction of quaking aspen in boreal mixedwoods

In this study we developed an individual tree height prediction model for quaking aspen (Populus tremuloides Michx.) grown in boreal mixedwood forests in Alberta using the nonlinear mixed model (NLMM) approach. We examined the impacts of density, species composition, and top height on aspen height predictions. Statistically significant stand level variables were incorporated into the base height–diameter model to increase the predictive ability and accuracy of the model at both the population and subject-specific levels. Our analyses showed that top height and density impacted height growth, but species composition did not. More importantly, we found that the inclusion of additional variables into the base model, despite improving model fitting statistics on the modelling data, did not improve the model's predictive ability and accuracy when cross-validated and when tested on an independent testing data set. Under the NLMM framework the base model performed as well as or better than the expanded models that contained other stand level variables. This has important theoretical and practical implications because, other than for biological reasons, more accurate local tree height predictions for aspen can be achieved simply by using the base height–diameter model fitted with the NLMM approach without the inclusion of other variables.