%0 Research article
%T Local prediction of stand structure using linear prediction theory in Scots pine-dominated stands in Finland
%A Siipilehto, Jouni
%D 2011
%J Silva Fennica
%V 45
%N 4
%R doi:10.14214/sf.99
%U https://silvafennica.fi/article/99
%X This study produced a family of models for eight standard stand  characteristics, frequency and basal area-based diameter distributions,  and a height curve for stands in Finland dominated by Scots pine (Pinus  sylvestris L.). The data consisted of 752 National Forest  Inventory-based sample plots, measured three times between 1976 and  2001. Of the data, 75% were randomly selected for modelling and 25% left  out for model evaluation. Base prediction models were constructed as  functions of stand age, location and site providing strongly average  expectations. These expectations were then calibrated with the known  stand variables using linear prediction theory when estimating the best  linear unbiased predictor (BLUP). Three stand variables, typically  assessed in Finnish forest management planning fieldwork, were quite  effective for calibrating the expectation for the unknown variable. In  the case of optional distributions, it was essential to choose the  weighting of the diameter distribution model such that the available  input variables and the model applied were based on the same scale (e.g.  arithmetic stand variables for frequency distribution). Additional  input variables generally improved the accuracy of the validated  characteristics, but the improvements in the predicted distributions  were most noteworthy when the arithmetic mean and basal area-weighted  median were simultaneously included in the BLUP estimation. The BLUP  method provided a flexible approach for characterising relationships  among stand variables, alternative size distributions and the  height–diameter curve. Models are intended for practical use in the  MOTTI simulator.