No abstract

No abstract

The objective of the present study was to develop recruitment models for Norway spruce, Scots pine, birch and other broadleaves in young growth forests in Norway. The models were developed from permanent sample plots established by the National Forest Inventory, and they will be included in a growth simulator that is part of a large-scale forestry scenario model. The modelling was therefore restricted to independent variables directly or indirectly available from inventories for practical forest management planning. A two-stage modelling approach that suited the stochastic nature of recruitment in boreal forests was used. Models predicting the probability of recruitment were estimated in a first stage, and conditional models for the number of recruits were developed in a second. The probability models as well as the conditional models were biologically realistic and logical. The goodness of fit tests revealed that the probability models fitted the data well, while the coefficients of determination for the conditional models were relatively low. No independent test data were available, but comparisons of predicted and observed number of recruits in different sub-groups of the data revealed few large deviations. The high level of large random errors was probably due to the great variability observed in number of recruits rather than inappropriate specifications of the models. Provided the generally high level of uncertainty connected to analysis performed with large-scale forestry scenario models and the stochastic nature of recruitment, the presented models seem to give satisfactory levels of accuracy.

No abstract

The aim of this paper is to describe a bioeconomic forest simulator based on models for individual trees. At present, the forest simulator can be applied only to stand-level analyses, but in future it is planned to be a part of a software system that may be used for decision support for large forest areas. The focus is on a flexible platform facilitating future development, and the biological submodels, i.e. distance-independent individual-tree growth and mortality models and area-based regeneration and recruitment models, are based on permanent sample plots from the Norwegian National Forest Inventory. The economic submodels estimate timber prices and harvesting costs from individual trees. For each management unit (i.e. stand), the simulator produces treatment schedules with all feasible combinations of user-defined treatment and regeneration options (e.g. precommercial thinning, thinning, different kinds of regeneration cutting with different kinds of regeneration options and selective cutting). A net present value is calculated for all treatment schedules. From the treatment schedules various aspects of forest dynamics and economics can be analysed and visualized. A case study is presented to demonstrate some of the functionality and behaviour of the simulator.