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. Half of Asiantropical forests were disturbed in the last century resulting in thedominance of secondary forests in Southeast Asia. However, the rate at whichbiomass accumulates during the recovery process in these forests is poorlyunderstood. We studied a forest landscape located in Khao Yai National Park(Thailand) that experienced strong disturbances in the last century due toclearance by swidden farmers. Combining recent field and airborne laserscanning (ALS) data, we first built a high-resolution aboveground biomass(AGB) map of over 60 km2 of forest landscape. We then used therandom forest algorithm and Landsat time series (LTS) data to classifylandscape patches as non-forested versus forested on an almost annual basisfrom 1972 to 2017. The resulting chronosequence was then used in combinationwith the AGB map to estimate forest carbon recovery rates in secondary forestpatches during the first 42 years of succession. The ALS-AGB model predictedAGB with an error of 14 % at 0.5 ha resolution (RMSE=45 Mg ha−1) using the mean top-of-canopy height as a singlepredictor. The mean AGB over the landscape was 291 Mg ha−1,showing a high level of carbon storage despite past disturbance history. Wefound that AGB recovery varies non-linearly in the first 42 years of thesuccession, with an increasing rate of accumulation through time. Wepredicted a mean AGB recovery rate of 6.9 Mgha-1yr-1, witha mean AGB gain of 143 and 273 Mg ha−1 after 20 and 40 years,respectively. This rate estimate is about 50 % larger than the rateprescribed for young secondary Asian tropical rainforests in the 2019refinement of the 2006 IPCC guidelines for national greenhouse gasinventories. Our study hence suggests that the new IPCC rates, which werebased on limited data from Asian tropical rainforests, strongly underestimatethe carbon potential of forest regrowth in tropical Asia. Our recoveryestimates are also within the range of those reported for the well-studiedLatin American secondary forests under similar climatic conditions. Thisstudy illustrates the potential of ALS data not only for scaling up field AGBmeasurements but also for predicting AGB recovery dynamics when combined withlong-term satellite data. It also illustrates that tropical forest landscapesthat were disturbed in the past are of utmost importance for the regionalcarbon budget and thus for implementing international programs such as REDD+.

Forest aboveground biomass stock and resilience in a tropical landscape of Thailand