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Forest management has become a more complex issue than it has ever been before. Foresters need to fulfill the demands of several interest groups, often which are conflicting. Finding the balance between different management objectives can be facilitated with the use of decision support systems. Since no decision support systems have been developed in Estonia, the aim of this study is to assess the applicability of the Finnish stand growth simulator MOTTI in Estonia. The evaluation focuses on the basal area growth models; the data used originates from the Estonian network of permanent forest growth plots. Tree-level bias models were constructed for all major tree species in order to assess model performance. Also, bias was examined visually with the use of residual plots. Results show that bias levels and variables which contribute to bias differ by species. Based on the fit statistics of the bias models, Common aspen shows the highest bias level whereas the growth of Gray alder seems to be predicted most accurately. Although model performance is decent for a model that is used outside of its application limits, calibration should still be considered as a prerequisite to implement the MOTTI system in Estonian forestry practice.

metsanduslikud uurimused./metsanduslikud uurimused

Evaluation of the basal area growth models in the Finnish stand simulator MOTTI with data from the Estonian network of permanent forest growth plots / Soome puistukasvusimulaatori MOTTI rinnaspindala juurdekasvumudelite prognoositäpsuse hindamine Eesti metsa kasvukäigu püsiproovitükkide võrgustiku mõõtmisandmete põhjal