Modeling nutrient cycling and sustainable forest growth in a changing world

It took 70-80 years to realize the width of the impact of industrialization on the forest ecosystems since a forest ecosystem is a "slow system" as seen from a human perspective. An anticipated future climate change and increasing carbon dioxide and ozone levels will change the conditions even more with time and the widely used statistical forest growth models will not be applicable anymore. Computer-based, dynamic ecosystem models are needed to predict the long-term impacts of our present actions. Currently, these ecosystem models have had a tendency to be un-balanced in the level of details; either the vegetation or the soil is described in detailed, which is a major drawback. ForSAFE is a process-based forest ecosystem model system, consisting of four well-known sub-models, created to explore the impacts of climate change, changing air pollution and forest management on the vegetation, the soil and the nutrient cycling in a long-term sustainability perspective. In this thesis the modeling philosophy and the fundamental ideas behind the ForSAFE model system are presented. ForSAFE is developed using a system dynamics approach and is based on concepts of "natural sustainability" and "Liebig’s law of the minimum". The modeled system and its sub-models are explored by the use of system dynamics tools such as causal loop diagrams and feedback loop analysis. Simulation results from Swedish and German forests show that the integrated model is able to consider the influences of feedbacks between the vegetation and the soil under changing climate conditions. This suggests that ForSAFE is suitable as a tool for assessment of the influence of climate change, pollution change and forest management changes on forest sustainability