Department of Mathematics and Computer Science, University of Osnabrück, 49074 Osnabrück, GERMANY.
Sustainable use of species-rich moist forests is hampered by an insufficient understanding of their dynamics and long-term response to different wood harvesting strategies. This thesis contributes to a better understanding of natural forest dynamics, explores the productivity of native forests subjected to different management strategies, and quantifies the ecological impacts of these strategies. The thesis focuses on two study regions: tropical montane cloud forest (TMCF ) in central Veracruz, Mexico, and Valdivian temperate rain forest (VTRF ) in northern Chiloé Island, Chile. The process-based forest growth model FORMIND is applied to study natural forest succession, to assess long-term ecological implications of fuelwood extraction on TMCF , to explore the potential of secondary TMCF for provision of ecosystem services and fuelwood, and to compare potential harvesting strategies for VTRF regarding forest productivity and ecological consequences.
Simulation results show that both forest types have a high potential for wood production. As wood extraction increases, the forest structure becomes simplified because large old trees disappear from the forest. The species composition shifts to tree species that are favoured by the respective harvesting strategy. The overall ecological impact increases linearly with the amount of extracted wood. Simulation results allow to define management strategies that balance conservation and production objectives, promote the regeneration of desired tree species, or minimise shifts in the species composition of the forest. Process-based forest models enhance our understanding of the dynamics of species-rich moist forests and are indispensable tools to assess long-term implications of anthropogenic disturbances on forest ecosystems. Thereby they contribute to the conservation and sustainable use of native forests outside protected areas.