@article{fdi:010077772,
  title = {{F}orest aboveground biomass stock and resilience in a tropical landscape of {T}hailand},
  author = {{J}ha, {N}. and {T}ripathi, {N}. {K}. and {C}hanthorn, {W}. and {B}rockelman, {W}. and {N}athalang, {A}. and {P}{\'e}lissier, {R}apha{\¨e}l and {P}immasarn, {S}. and {P}loton, {P}ierre and {S}asaki, {N}. and {V}irdis, {S}. {G}. {P}. and {R}{\'e}jou-{M}{\'e}chain, {M}axime},
  editor = {},
  language = {{ENG}},
  abstract = {{H}alf of {A}sian tropical forests were disturbed in the last century resulting in the dominance of secondary forests in {S}outheast {A}sia. {H}owever, the rate at which biomass accumulates during the recovery process in these forests is poorly understood. {W}e studied a forest landscape located in {K}hao {Y}ai {N}ational {P}ark ({T}hailand) that experienced strong disturbances in the last century due to clearance by swidden farmers. {C}ombining recent field and airborne laser scanning ({ALS}) data, we first built a high-resolution aboveground biomass ({AGB}) map of over 60 km(2) of forest landscape. {W}e then used the random forest algorithm and {L}andsat time series ({LTS}) data to classify landscape patches as non-forested versus forested on an almost annual basis from 1972 to 2017. {T}he 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. {T}he {ALS}-{AGB} model predicted {AGB} with an error of 14 % at 0.5 ha resolution ({RMSE} = 45 {M}g ha(-1)) using the mean top-of-canopy height as a single predictor. {T}he mean {AGB} over the landscape was 291 {M}g ha(-1), showing a high level of carbon storage despite past disturbance history. {W}e found that {AGB} recovery varies non-linearly in the first 42 years of the succession, with an increasing rate of accumulation through time. {W}e predicted a mean {AGB} recovery rate of 6.9 {M}g ha(-1) yr(-1), with a mean {AGB} gain of 143 and 273 {M}g ha(-1) after 20 and 40 years, respectively. {T}his rate estimate is about 50 % larger than the rate prescribed for young secondary {A}sian tropical rainforests in the 2019 refinement of the 2006 {IPCC} guidelines for national greenhouse gas inventories. {O}ur study hence suggests that the new {IPCC} rates, which were based on limited data from {A}sian tropical rainforests, strongly underestimate the carbon potential of forest regrowth in tropical {A}sia. {O}ur recovery estimates are also within the range of those reported for the well-studied {L}atin {A}merican secondary forests under similar climatic conditions. {T}his 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. {I}t 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}+.},
  keywords = {{THAILANDE} ; {ZONE} {TROPICALE}},
  booktitle = {},
  journal = {{B}iogeosciences},
  volume = {17},
  numero = {1},
  pages = {121--134},
  ISSN = {1726-4170},
  year = {2020},
  DOI = {10.5194/bg-17-121-2020},
  URL = {https://www.documentation.ird.fr/hor/fdi:010077772},
}