T. Ditzer

Long-term impacts of logging in a tropical rain forest — a simulation study

Abstract Simulation models for growth of tropical forest can be a useful tool to investigate the long-term impacts of logging. In this paper the rain forest growth model FORMIX3 is used for such a study. As main processes, the FORMIX3 model includes tree growth, mortality, regeneration and competition. The calculation of tree growth is based on a carbon balance approach. Trees compete for light and space; dying large trees fall down and create gaps in the forest. Different logging scenarios for an initially undisturbed forest stand at Deramakot (Malaysia) were simulated. Two different logging methods (conventional and low impact logging) in combination with different cutting cycles (from 20 to 100 years) were investigated for their long-term impact on the forest. We characterize the impacts with four indicators: total yield, yield per cut, species composition, and canopy opening. Our simulation results indicate that too short logging cycles (

Concepts for the aggregation of tropical tree species into functional types and the application to Sabah's lowland rain forests.

For analysing field data as well as for modelling purposes it is useful to classify tree species into a few functional types. In this paper a new aggregation of tree species of the dipterocarp rain forests in Sabah (Borneo), Malaysia, is developed. The aggregation is based on the two criteria successional status and potential maximum height. Three classes of successional status (early, mid and late successional species) and five classes of potential maximum heights ( 36 m) lead to a combination of 15 functional types. The criteria of the developed classification are chosen to suit for applications with process-based models, such as FORMIx3 and FORMIND, which are based on photo- synthesis production as the main process determining tree growth. The concept is universal and can easily be applied to other areas. With this new method of group- ing a more realistic parametrization of process-based rain forest growth models seems to be possible.