Current issue: 58(4)
Management of Scots pine (Pinus sylvestris L.) in Norway requires a forest growth and yield model suitable for describing stand dynamics of even-aged forests under contemporary climatic conditions with and without the effects of silvicultural thinning. A system of equations forming such a stand-level growth and yield model fitted to long-term experimental data is presented here. The growth and yield model consists of component equations for (i) dominant height, (ii) stem density (number of stems per hectare), (iii) total basal area, (iv) and total stem volume fitted simultaneously using seemingly unrelated regression. The component equations for stem density, basal area, and volume include a thinning modifier to forecast stand dynamics in thinned stands. It was shown that thinning significantly increased basal area and volume growth while reducing competition related mortality. No significant effect of thinning was found on dominant height. Model examination by means of various fit statistics indicated no obvious bias and improvement in prediction accuracy in comparison to existing models in general. An application of the developed stand-level model comparing different management scenarios exhibited plausible long-term behavior and we propose this is therefore suitable for national deployment.
We determined empirical models for estimating total aboveground as well as stem, branches, and foliage dry biomass of young (age up to 16 years) silver birch (Betula pendula Roth.) growing on the post-agricultural lands. Two sets of allometric models for trees with a height below or above 1.3 m (small and large trees respectively) were developed. Simplified models were elaborated based exclusively on appropriate tree diameter (diameter at ground level for small trees, diameter at breast height for large trees), while expanded models also included tree height. Total aboveground biomass was estimated as the sum of biomass of all tree components. To assure additivity of the developed equations, the seemingly unrelated regression approach for the final model fitting was used. Expanded models in both tree groups were characterized by a better fit to the data (R2 for total aboveground biomass for small and large trees equaled 0.8768 and 0.9752, respectively). Diameter at breast height appeared to be a better predictor than diameter at ground level – simplified models had better fit for large trees (R2 for total aboveground biomass equals 0.9611) than for small ones (R2 = 0.7516). The developed equations provide biomass predictions consistent with available Latvian, Estonian, Finnish, Swedish, and Norwegian models for silver birch.