Current issue: 55(2)
A process-oriented tree and stand growth model is extended to be applicable to the analysis of timber quality, and how it is influenced by silvicultural treatments. The tree-level model is based on the carbon balance and it incorporates the dynamics of five biomass variables as well as tree height, crown base, and breast height diameter. Allocation of carbon is based on the conservation of structural relationships, in particular, the pipe model. The pipe-model relationships are extended to the whorl level, but in order to avoid a 3-dimensional model of entire crown structure, the branch module is largely stochastic and aggregated. In model construction, a top-down hierarchy is used where at each step down, the upper level sets constraints for the lower level. Some advantages of this approach are model consistency and efficiency of calculations, but probably at the cost of reduced flexibility. The detailed structure related with the branching module is preliminary and will be improved when more data becomes available. Model parameters are identified for Scots pine (Pinus sylvestris L.) in Southern Finland, and example simulations are carried out to compare the development of quality characteristics in different stocking densities.
A computer model was developed for predicting knottiness of wood material of Scots pine (Pinus sylvestris L.), Norway spruce (Picea abies (L.) H. Karst.) and birch (Betula sp). The prediction included location of knots, their size and quality, i.e. if they are dead or living knots. The model suits best for tree species where branches are born at the base of shoots, in Finland such tree species is Scots pine.
The usefulness of the model was tested in the prediction of knots in wooden elements of joinery industry. According to the results, the shape of cross section affects the surface quality of elements. Especially useful is a quadratic cross section as it increases the probability to get a knotless surface.
The PDF includes an abstract in English.
The purpose of this study was that of providing a long-term timber production model (Kilkki and Pökkälä 1975) with growing stock models. The paper is divided into two parts; the first is concerned with generation of the stand data through Monte-Carlo simulation. The growing stock of each stand was described by a DBH-height distribution. The necessary information on the relationships between the stand characteristics was derived from sample plots measured in the national forest inventory of Finland. A total of 1,500 Scots pine (Pinus sylvestris L.), Norway spruce (Picea abies (L.) H. Karst), and birch (Betula sp.) stands, each comprising 100 trees were provided by simulation.
In the second part, models predicting the form factor, timber assortment distribution, and value of the growing stock were derived through regression analysis for each species of tree. The predicting variables included the form factor of the basal area median tree, basal area median diameter, and height in the form factor models. In the timber assortment and value models, the only predicting variable was the volume of the basal area median tree. The Matchcurve-technique (Jensen 1973) was employed in derivation of the regression models.
The PDF includes a summary in English.