%0 Research article
%T Modeling mortality of individual trees in drained peatland sites in Finland
%A Jutras, Sylvain
%A Hökkä, Hannu
%A Alenius, Virpi
%A Salminen, Hannu
%D 2003
%J Silva Fennica
%V 37
%N 2
%R doi:10.14214/sf.504
%U https://silvafennica.fi/article/504
%X Multilevel logistic regression models were constructed to predict the  5-year mortality of Scots pine (Pinus sylvestris L.) and pubescent birch  (Betula pubescens Ehrh.) growing in drained peatland stands in northern  and central Finland. Data concerning tree mortality were obtained from  two successive measurements of the National Forest Inventory-based  permanent sample plot data base covering pure and mixed stands of Scots  pine and pubescent birch. In the modeling data, Scots pine showed an  average observed mortality of 2.73% compared to 2.98% for pubescent  birch. In the model construction, stepwise logistic regression and  multilevel models methods were applied, the latter making it possible to  address the hierarchical data, thus obtaining unbiased estimates for  model parameters. For both species, mortality was explained by tree  size, competitive position, stand density, species admixture, and site  quality. The expected need for ditch network maintenance or  re-paludification did not influence mortality. The multilevel models  showed the lowest bias in the modeling data. The models were further  validated against independent test data and by embedding them in a stand  simulator. In 100-year simulations with different initial stand  conditions, the models resulted in a 72% and 66% higher total mortality  rate for the stem numbers of pine and birch, respectively, compared to  previously used mortality models. The developed models are expected to  improve the accuracy of stand forecasts in drained peatland sites.