Current issue: 53(4)
Two dynamic models predicting the development of frost hardiness of Finnish Scots pine (Pinus sylvestris L.) were tested with frost hardiness data obtained from trees growing in the natural conditions of Finland and from an experiment simulating the predicted climatic warming. The input variables were temperature in the first model, and temperature and night length in the second. The model parameters were fixed on the basis of previous independent studies. The results suggested that the model which included temperature and photoperiod as input variables was more accurate than the model using temperature as the only input variable to predict the development of frost hardiness in different environmental conditions. Further requirements for developing the frost hardiness models are discussed.
With developing possibilities to analyse data automatically there is a need to develop the mathematical and statistical practices for calculations. The article presents the basis about the growth of trees and the existing models of growth, the basics on growth functions, and the construction of a regression model to analysis the growth. The theoretical model development has been tested with three existing data sets.
The analysis of growth should be considered with dynamic models. The model need to take into account various aspects and growth factors. The model should have practical implications.
The PDF contains a summary in German.