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  • 标题:CO2 emissions from forest degradation in Brazilian Amazon
  • 本地全文:下载
  • 作者:Talita Oliveira Assis ; Ana Paula Dutra de Aguiar ; Celso von Randow
  • 期刊名称:Environmental Research Letters
  • 印刷版ISSN:1748-9326
  • 电子版ISSN:1748-9326
  • 出版年度:2020
  • 卷号:15
  • 期号:10
  • 页码:104035
  • DOI:10.1088/1748-9326/ab9cfc
  • 出版社:IOP Publishing Ltd
  • 摘要:Forest degradation is widespread around the world, due to multiple factors such as unsustainable logging, agriculture, invasive species, fire, fuelwood gathering, and livestock grazing. In the Brazilian Amazon forest degradation from August 2006 to July 2016 reached 1,1 869 800 ha. The processes of forest degradation are still poorly understood, being a missing component in anthropogenic CO2 emission estimates in tropical forests. In this work, we analyzed temporal trajectories of forest degradation from August 2006 to July 2016 in the Brazilian Amazon and assessed their impact on the regional carbon balance. We combined the degradation process with deforestation-related processes (clear-cut deforestation and secondary vegetation dynamics), using the spatially-explicit INPE-EM carbon emission model. The trajectory analysis showed that 13% of the degraded area ended up being cleared and converted in the period and 61% of the total degraded area experienced only one event of degradation throughout the whole period. Net emissions added up to 5.4 GtCO2, considering the emissions from forest degradation and deforestation, absorption from degraded forest recovery, and secondary vegetation dynamics. The results show an increase in the contribution of forest degradation to net emissions towards the end of the period, related to the decrease in clear-cut deforestation rates, decoupled from the forest degradation rates. The analysis also indicates that the regeneration of degraded forests absorbed 1.8 GtCO2 from August 2006 and July 2016- A component typically overlooked in the regional carbon balance.
  • 关键词:Carbon balance; Emission model; Fire; Selective logging; Trajectories
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