Dynamic stand growth model for Norway spruce forests based on long-term experiments in Germany

Abstract

In the present study a dynamic stand growth model for Norway spruce (Picea abies (L.) Karst.) forests was developed from data of 99 research plots, which had been measured between one and seventeen times in northwestern and southern Germany. In this model, the initial stand conditions at any point in time are defined by three state variables (dominant height, basal area and number of trees per hectare), and they are used to estimate stand volume for a given projection age. The model uses three transition functions to project the stand state variables at any particular time and a state function to estimate the stand volume. Two of these transition functions were derived by expanding a base model and considering two sitespecific parameters and the third one was derived considering one site-specific parameter. All the functions were fitted simultaneously using full information maximum likelihood and the base-age-invariant dummy variables method. The values of the critical error statistic for stand volume and the RMSE relative to the mean stand volume indicated that the overall model provides satisfactory predictions for time intervals up to 25 years