Evaluation of Logging in a Dipterocarp Rain Forest Using the Formind Forest Model and Multicriteria Decision Analysis

Sixty-four different logging scenarios for an initially undisturbed forest stand at Deramakot (Malaysia) were simulated with rain forest growth model FORMIND. The scenarios differ regarding the logging cycle, logging method, cutting limit and logging intensities. We characterise the impacts with four criteria describing the yield, canopy opening and changes in species composition. Multicriteria decision analysis was used to evaluate the scenarios and identify the efficient ones. Our results plainly show that reduced-impact logging scenarios are more ‘efficient’ than the others, since in these scenarios forest damage is minimised without significantly reducing yield. Nevertheless there is a trade-off between yield and achieving a desired ecological state of logged forest; the ecological state of the logged forests can only be improved by reducing yields and enlarging the logging cycles. Our study also demonstrates that high cutting limits or low logging intensities cannot compensate for the high damage caused by conventional logging techniques.