Agent-based model reveals a sustainable method of forest tree harvesting
Research & Innovation | September 5, 2023
The Philippines requires 6 million cubic meters of wood annually, based on its 2006–2014 average wood consumption. However, due to years of unsustainable forest practices, various policies were enacted in the country that restricted timber harvesting starting in the late 1980s, culminating in Executive Order No. 23 in 2011. This moratorium imposed a total ban on the cutting and harvesting of timber in natural and residual forests nationwide. These government bans on forest operations have led to a serious shortage of local wood supply, with local sources able to provide only 25% percent of wood demand while the rest are sourced through imports.
In this work, we study a potential sustainable method of forest tree harvesting using agent-based modeling. Agent-based models are computer simulations that demonstrate how several important actors interact within a given environment. In our context, the environment is a hypothetical forest that is based on the Mt. Makiling Forest Reserve. We built a model of the forest with several tree species that grow in accordance with predetermined growth equations. The primary activities within the forest are harvesting and planting, which follows the Selective Harvesting (SL) and Assisted Natural Regeneration (ANR) approaches, respectively. The simulation findings revealed that if SL is supplemented with ANR, a sustainable harvest may be maintained with a stable average of 80 percent forest cover even after 500 years. The simulations also showed that while employing ANR does not always result in better harvest profits, it was able to provide a more stable harvest over a longer period of time. The model described in our study demonstrated how a sustainable forest operation could support the nation’s economic needs for timber supply while also ensuring that the forest was actively managed.
Read the full paper: https://www.mdpi.com/1999-4907/14/2/428