Assessing aboveground carbon stocks and forest structure metrics in the Mouila Oil Palm Concession Lot 2, Gabon

Abstract

Growing demand for oil palm is driving its rapid expansion into the African tropics. While palm agriculture can be profitable, the conversion of tropical forests to oil palm monocultures tends to induce environmental degradation, loss of biodiversity, and significant carbon emissions. In this study, we evaluate the potential loss of biomass and the carbon emissions from conversion of a previously logged Gabonese forest to an oil palm plantation. We use a combination of field and LiDAR (Light Detection and Ranging) data to quantify and spatially model aboveground biomass (AGB), carbon stocks, and forest structure in the Mouila Lot 2 (ML2) oil palm concession in the Ngounié Province of Gabon. We established 30 1-ha plots using a stratified, random design. Mean AGB was 257.3 ± 73.8 and 345.8 ± 114.0 Mg ha-1 for 20 plains and 10 plateau plots. Using a multiple linear regression model calibrated with field measurements to predict the spatial distribution of AGB from LiDAR metrics, we estimate the plains forest contain 4.15 Tg AGB (2.07 Tg C) and the plateau forests to contain 4.48 Tg AGB (2.24 Tg C). Using a conservative estimate of biomass saturation in oil palm monocultures (100 Mg ha-1), we estimate that 1.19 Tg C would be emitted from conversion of the plains forest. The carbon density of these forests, even after selective logging, thus exceeds limits proposed by the Roundtable on Sustainable Palm Oil (RSPO). Due to the economic viability of oil palm agriculture and concessions already granted, oil palm development is not likely to stop in Central Africa. Creating regional standards for carbon emissions will allow the balancing of economic development and environmental objectives, while maintaining the framework of economic incentives for socially and environmentally responsible development.