Abstract
Height growth was modelled for spruce-dominated, even-aged stands in the Sub-Boreal Spruce biogeoclimatic zone of British Columbia, Canada, using both stem analysis (SA) and permanent sample plot (PSP) data. The model is based on a stochastic differential equation (SDE) formulation of the Bertalanffy–Richards growth equation. The SDE approach accounts for serial correlation and heterogeneous variance and makes hypothesis testing possible. Statistically significant differences in height–age trends between SA and PSP data were found that may be attributed to bias caused by dominance changes in SA trees. Error structure in SA and PSPs was also significantly different. Combining both data sources in a way that respects these different error structures reduced bias and increased precision. Four parametrizations were tested; the best was a polymorphic version. The final model fit the data well with no appreciable bias over the full range of ages and site qualities. The currently used spruce site-index model was found to underestimate growth and overestimate site index in young stands. The new model can be recommended for height prediction and site-quality assessment in interior spruce.
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