Abstract
Abstract. Half of Asian tropical forests were disturbed in the last century resulting in the dominance of secondary forests in Southeast Asia. However, the rate at which biomass accumulates during the recovery process in these forests is poorly understood. We studied a forest landscape located in Khao Yai National Park (Thailand) that experienced strong disturbances in the last century due to clearance by swidden farmers. Combining recent field and airborne laser scanning (ALS) data, we first built a high-resolution aboveground biomass (AGB) map of over 60 km2 of forest landscape. We then used the random forest algorithm and Landsat time series (LTS) data to classify landscape patches as non-forested versus forested on an almost annual basis from 1972 to 2017. The resulting chronosequence was then used in combination with the AGB map to estimate forest carbon recovery rates in secondary forest patches during the first 42 years of succession. The ALS-AGB model predicted AGB with an error of 14 % at 0.5 ha resolution (RMSE=45 Mg ha−1) using the mean top-of-canopy height as a single predictor. The mean AGB over the landscape was 291 Mg ha−1, showing a high level of carbon storage despite past disturbance history. We found that AGB recovery varies non-linearly in the first 42 years of the succession, with an increasing rate of accumulation through time. We predicted a mean AGB recovery rate of 6.9 Mgha-1yr-1, with a 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 rate prescribed for young secondary Asian tropical rainforests in the 2019 refinement of the 2006 IPCC guidelines for national greenhouse gas inventories. Our study hence suggests that the new IPCC rates, which were based on limited data from Asian tropical rainforests, strongly underestimate the carbon potential of forest regrowth in tropical Asia. Our recovery estimates are also within the range of those reported for the well-studied Latin American secondary forests under similar climatic conditions. This study illustrates the potential of ALS data not only for scaling up field AGB measurements but also for predicting AGB recovery dynamics when combined with long-term satellite data. It also illustrates that tropical forest landscapes that were disturbed in the past are of utmost importance for the regional carbon budget and thus for implementing international programs such as REDD+.
Highlights
Tropical forest disturbances and subsequent biomass recovery through time significantly affect the global carbon cycle (Harris et al, 2012)
We showed that the integration of field inventory, Landsat archives and lidar data provides a powerful approach for characterizing the spatio-temporal dynamics of aboveground biomass in tropical forests
Contrary to the results found by Feldpausch et al (2007), the rates of aboveground biomass (AGB) accumulation inferred with our approach provided estimates similar to those obtained from long-term field plot surveys (Fig. 5), validating the chronosequence approach in our study area
Summary
Tropical forest disturbances and subsequent biomass recovery through time significantly affect the global carbon cycle (Harris et al, 2012). Most studies of carbon dynamics along tropical forest successions are concentrated in Latin America (Chave et al, 2020; Letcher and Chazdon, 2009; Norden et al, 2015; Poorter et al, 2016a; Rozendaal et al, 2017; Rozendaal and Chazdon, 2015, but see N’Guessan et al, 2019, for Africa). This work led to a recent refinement of the 2006 IPCC guidelines for national greenhouse gas inventories (Requena Suarez et al, 2019; IPCC, 2019) Whether these new estimates are representative of Asian tropical rainforests is highly uncertain, due to a critical lack of data for this region. This issue is especially crucial for Asian tropical forests where half of the forests have been disturbed during the last century, resulting in the dominance of secondary forests throughout the region (Achard et al, 2014; Mitchard et al, 2013; Stibig et al, 2014)
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