Evaluating the Capacity of Forest Governance System for Effective and Efficient REDD-plus Policies in the State of Pahang, Peninsular Malaysia
REDD-plus is one of the most important policy tools for promoting sustainable forest management, especially in tropical countries where significantly large net losses of forest area have been observed in recent years. Malaysia is considered as a potential participant country in REDD-plus project particularly in reducing emission from forest degradation. Before engaging the mechanism the country needs to evaluate the capacity of its forest governance in particular because governance issues are emerging concern which could effects the efficiency and effectiveness of REDD-plus policies. In this study we take a particular note on the issue by analyzed the institutional and policy framework of forest governance system of the country using some case study with the focus is on the state of Pahang, peninsular Malaysia. The implication of such forest governance system on the relationship between development, forest and indigenous people conservation was also analyzed. Its implication on biodiversity conservation was explored by assessing the effectiveness of protected areas to restrict deforestation and displacement of deforestation to relatively unprotected area.
Methodology of assessing protected area effectiveness contributes to evaluate emissions reduction and economic incentives for developing countries more correctly, and development of an appropriate governance framework based on participatory approach for forest management makes a good role for decreasing the risks of biodiversity and indigenous life. The results of this study are useful for planners and decision makers to improve framework land use development, protected area establishment and REDD-plus policies.
Osamu Higashi - Hiroshima University, Japan
Saiful A. Abdullah - Universiti Kebangsaan Malaysia, Malaysia
Nobukazu Nakagoshi - Hiroshima University, Japan
Hiroaki Shirakawa - Nagoya University, Japan
Patricia San Miguel - Vox Populi Ltd. Liab. Co.