Understanding the role of forest simulation models in sustainable forest management

Abstract

Sustainable forest management (SFM) represents a new paradigm for forestry. Traditional forestry objectives aimed at sustainable yield management are being replaced with those of a sustainable ecosystem management. This paradigm shift in forest management requires an effective transfer of results from researchers to forest managers. To predict the potential impacts of future changes in global environment (such as climate, land use, fire disturbance, and forest harvesting) on the sustainability of forest ecosystems, forest resource managers will require forest simulation models. There have been two basic approaches to modeling forest vegetation growth and dynamics: empirical and mechanistic forest simulation models. This paper reviews and compares three major types of forest simulation models: (1) growth and yield models (empirical approach); (2) succession models (empirical–mechanistic hybrid approach); and (3) process models (mechanistic approach), and describes three case studies as examples. The advantages and disadvantages of the different modeling approaches are discussed. The case studies deal with predicting future forest stocks under different management options, simulating the potential effects of climate change, and effects of fire disturbance on structure and function of forest ecosystems in Canada. There is still a gap between foresters and ecologists in developing and using forest simulation models. Diversified modeling approaches integrated into a decision–support system, which will become an important tool for evaluating the sustainability of forest ecosystem in a changing environment, is emphasized.