%0 Research article
%T Empirical prediction models for Vaccinium myrtillus and V. vitis-idaea berry yields in North Karelia, Finland
%A Ihalainen, Marjut
%A Salo, Kauko
%A Pukkala, Timo
%D 2003
%J Silva Fennica
%V 37
%N 1
%R doi:10.14214/sf.513
%U https://silvafennica.fi/article/513
%X Forest berries and the outdoor experiences related to berry collection  are important goods and services provided by Finnish forests.  Consequently, there is a need for models which facilitate the prediction  of the impacts of alternative forest management options on berry  yields. Very few such models are available. In particular, empirical  models are lacking. Models used in forest management should express the  effect of variables altered in forest management such as stand density  and mean tree size. This study developed empirical models for bilberry  and cowberry yields in North Karelia. The data consisted of 362  measurements of 40 m2 sample plots. The plots were located in clusters.  The same plot was measured over 1 to 4 years. Besides berry yield some  site and growing stock characteristics of each plot were measured. A  random parameter model was used to express the berry yield as a function  of site fertility, growing stock characteristics, and random  parameters. The random part of the models accounted for the effect of  plot, measurement year, and cluster. The fixed predictors of the model  for bilberry were stand age and forest site type. Stand basal area, mean  tree diameter and forest site type were used to predict cowberry  yields. The most significant random parameter was the plot factor. The  fixed model part explained only a few per cent of the variation in berry  yields. The signs of regression coefficients were logical and the model  predictions correlated rather well with the predictions of earlier  models.