Modelling the growth of Pinus sylvestris L. monocultures in Sweden depending on the absorbed light

Abstract: Stand growth models are an important aid in contemporary sustainable forest management as a major planning and decision-making tool. However, climate change influencing growth conditions worldwide is a challenge to commonly used empirical models as they do not provide enough flexibility, which can result in inaccurate predictions and thus wrong decisions and sub-optimal results. Climate sensitive models based on plant physiology are a solution that provides greater adaptability, but they are computationally demanding and require often unavailable input data, and therefore they are rarely used in practice. For this reason, simple growth models for Scots pine (Pinus sylvestris L.) monocultures based on the concept of Light-Use Efficiency (LUE) were developed in this thesis. They use the yearly sums of absorbed photosynthetically active radiation (APAR), readily available climate data (annual precipitation and mean air temperature), and basic stand characteristics (age, number of trees, and site index) to predict the annual stem volume increment. For model fitting and validation, stand data from a long-term thinning and fertilization experiment established in Sweden and climate data from the Swedish Meteorological and Hydrological Institute were used. Two approaches differing in the method of data preparation were analysed. Model 1 (M1) was based on averaged variables and Model 2 (M2) used variables from the beginning of the measurement periods. Both models fit reasonably well with the data, but the RMSE exceeded 20% and they proved to provide reliable estimates for only the part of the productivity range included in this study. The unsatisfactory performance can be attributed to the change of the dependent variable in the LUE model to stem volume increment, the lack of good quality APAR data, and the low degree of model hybridization.