MODELLING SELECTION HARVESTING IN TROPICAL RAIN FORESTS

Abstract

Long term yield estimates for natural forests require a harvesting model to enable future yields to be estimated reliably. The model should predict the felled stems, the proportion of these which are merchantable, and any damage to the residual stand. Regression analyses was used to develop a model of current logging practice in the rain forests of north Queensland. Logistic functions predict the probability of any tree being marked for logging, the probability of a felled tree being merchantable, and the probability of any tree in the residual stand being damaged by logging. Important predictor variables included tree species and size, merchantable basal area, basal area logged, logging history, and topography. There was no evidence to suggest that soil type or site quality influenced current treemarking practice. The approach is applicable to other mixed forest types managed for selection logging.