%0 Articles
%T Modelling tree biomasses in Finland
%A Repola, Jaakko
%D 2013
%J Dissertationes Forestales
%V 2013
%N 158
%R doi:10.14214/df.158
%U http://dissertationesforestales.fi/article/1941
%X Biomass equations for above- and below-ground tree components of Scots pine (Pinus sylvestris L), Norway spruce (Picea abies [L.] Karst) and birch (Betula pendula Roth and Betula pubescens Ehrh.) were compiled using empirical material from a total of 102 stands (908 pine, 613 spruce and 127 birch trees). These stands located mainly on mineral soil sites representing a large part of Finland.

Biomass equations were derived for the total aboveground biomass and for the individual tree components (stem wood, stem bark, living and dead branches, needles, stump, and roots). Three multivariate models with different number of independent variables for above-ground biomass and one for below-ground biomass were constructed. The simplest model formulations, multivariate models (1) were based mainly on tree diameter and height as independent variables. In more elaborated multivariate models (2) and (3) additional commonly measured tree variables such age, crown length, bark thickness and radial growth rate were added.

In the modelling approach, the basic assumption was that the biomasses of the tree components on the same site and in the same tree are dependent. This statistical dependency was taken into account when simultaneously estimating parameter estimates for all biomass components, by applying a multivariate procedure. Based on the verified statistical dependence among the biomass components, the multivariate procedure had a number of advantages compared to the traditionally independently estimated equations by enabling more flexible application of the equations, ensuring better biomass additivity, and giving the more reliable parameter estimates.

The generalization and applicability of the models may be restricted by the fact that the study material was not an objective, representative sample, and some tree components were poorly represented. Despite these shortcomings, the models provided logical biomass predictions for individual tree components in Finland.