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Tropical forests continue to undergo a rapid transformation. The expansion of rubber tree (Hevea brasiliensis) plantations has been reported as a major driver of forest loss, linked to a boom in market demand. Distant commodity markets have spurred a surge of large-scale economic land concessions granted throughout tropical Southeast Asia. Using satellite imagery, we show the impact of rubber tree plantations on Cambodian forest cover and analyse how annual forest-to-rubber conversion rates relate to global rubber prices from 2001 to 2015. We found that 23.5 ± 1.8% of national forest cover was cleared in this period, with 23.2 ± 3.6% of cleared forest converted to rubber plantations. Annual forest-to-rubber conversion rates closely correlated with global rubber prices, with a time lag of 8–9 months (Pearson’s r= 0.93). Our results reveal a strong link between global commodity markets and tropical forest loss, particularly in countries with land policies geared towards rapid development.

ABSTRACTForest reference levels (FRLs) provide a benchmark for assessing reduced emissions from deforestation and forest degradation (REDD+), and they are central to demonstrate additionality of REDD+. Attaining realistic FRLs, however, is challenging, especially in complex mosaic landscapes. We established FRLs in northern Laos for different reference periods and tested them against actual carbon stock changes. Annual time series of Landsat satellite images were used to capture the subtle changes in carbon stocks in complex landscapes characterized by shifting cultivation. We found that FRLs differ considerably depending on the reference period chosen. Abrupt land-use changes occurred when hybrid maize replaced traditional shifting cultivation and forests, and this invalidated carbon stock trends that would have been predicted had the FRL been projected into the future. We conclude that demonstrating additionality of REDD+ in fast developing areas is difficult and that payment systems rewarding potential emission reductions against hypothetical extrapolation of FRLs are unlikely to be a cost-effective strategy.