Abstract
Reducing Emissions from Deforestation and forest Degradation (REDD+) aims to avoid forest conversion to alternative land-uses through financial incentives. Oil-palm has high opportunity costs, which according to current literature questions the financial competitiveness of REDD+ in tropical lowlands. To understand this more, we undertook regional fine-scale and coarse-scale analyses (through carbon mapping and economic modelling) to assess the financial viability of REDD+ in safeguarding unprotected forest (30,173 ha) in the Lower Kinabatangan floodplain in Malaysian Borneo. Results estimate 4.7 million metric tons of carbon (MgC) in unprotected forest, with 64% allocated for oil-palm cultivations. Through fine-scale mapping and carbon accounting, we demonstrated that REDD+ can outcompete oil-palm in regions with low suitability, with low carbon prices and low carbon stock. In areas with medium oil-palm suitability, REDD+ could outcompete oil palm in areas with: very high carbon and lower carbon price; medium carbon price and average carbon stock; or, low carbon stock and high carbon price. Areas with high oil palm suitability, REDD+ could only outcompete with higher carbon price and higher carbon stock. In the coarse-scale model, oil-palm outcompeted REDD+ in all cases. For the fine-scale models at the landscape level, low carbon offset prices (US $3 MgCO2e) would enable REDD+ to outcompete oil-palm in 55% of the unprotected forests requiring US $27 million to secure these areas for 25 years. Higher carbon offset price (US $30 MgCO2e) would increase the competitiveness of REDD+ within the landscape but would still only capture between 69%-74% of the unprotected forest, requiring US $380-416 million in carbon financing. REDD+ has been identified as a strategy to mitigate climate change by many countries (including Malaysia). Although REDD+ in certain scenarios cannot outcompete oil palm, this research contributes to the global REDD+ debate by: highlighting REDD+ competitiveness in tropical floodplain landscapes; and, providing a robust approach for identifying and targeting limited REDD+ funds.