Agent-based modelling application for social forestry policy evaluation. Issue 1 (1st December 2022)

• Record Type: Journal Article
• Authors: Abdulah, L; Subarudi, ; Lestari, N S; Qirom, M A; Yulianti, M; Wicaksono, D; Krisnawati, H; Lisnawati, Y; Astana, S
• Is Part Of: IOP conference series. Volume 1115:Issue 1(2022)
• Publication Date: 2022-12-01
• Subjects: Earth sciences -- Periodicals; Environmental sciences -- Congresses; Environmental sciences -- Periodicals; 550.5
• DOI: 10.1088/1755-1315/1115/1/012057
• Languages: English
• ISSNs: 1755-1307

Abstract

Abstract: Social forestry (SF) as a community involvement program in forest areas needs to be frequently evaluated, particularly on policy aspects considering the dynamics of program implementation. Policy issues related to SF program have not been well identified. As a result, the implementation of SF policies may not achieve the target and recurrently lead to new problems. This research aims to develop the best scenario to support the achievement of SF target but is limited to SF areas adjacent to oil palm plantations. The actor-based modelling was developed using Netlogo 6.2 analytical tool. The results showed that the implementation of SF program should include the economic welfare improvement of local communities as a main consideration. The best scenario to achieve SF target is providing full access for local communities to manage forest areas and developing a mechanism to market the commodities by considering domestic wood consumption. The model simulation indicates that this management approach would be able to maintain forest cover as well as increase the community's income. Therefore, information on wood consumption level needs to be promoted as an investment opportunity in the forestry sector, which has not been well considered previously in SF program. This strategy can be used to increase the participation of local communities in SF program by providing sufficient economic benefit as well as improving the inclusion of local communities in sustainable forest management.