An Agent-Based Model of a Sustainable Forest Operation in a Theoretical Lowland Dipterocarp Forest Modeled after Mount Makiling Forest Reserve, Philippines

Abstract

This study investigates the integration of assisted natural regeneration (ANR) and selective logging (SL) to guarantee a sustainable forest operation in the Philippines using agent-based modeling. To assess the sustainability of the operation in light of the revenue from timber harvesting and the health of the forest in terms of the total number of trees, various simulations were run on a theoretical forest modeled after the Mount Makiling Forest Reserve in the Philippines. The findings of the simulation have shown that, even after many years of continuous use, the performance of SL on a healthy forest similar to the theoretical forest is substantially identical with and without ANR. The “with ANR” setup, however, was able to demonstrate a considerably better and more stable harvest value over the final 100 years than the “without ANR” setup. In terms of ensuring sustainable forest cover, simulation findings showed that even after 500 years of continuous SL activity, the forest cover could be maintained to up to 80% with ANR. The model has shown that with the right combination of reforestation efforts and timber harvesting methods, a sustainable forest operation can contribute to the country’s economic needs for timber production while ensuring that the forest is actively managed.