Central African biomass carbon losses and gains during 2010–2019

Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt

  • Zhe Zhao
  • Philippe Ciais
  • Jean Pierre Wigneron
  • Maurizio Santoro
  • Brandt, Martin Stefan
  • Fritz Kleinschroth
  • Simon L. Lewis
  • Jerome Chave
  • Fensholt, Rasmus
  • Nadine Laporte
  • Denis Jean Sonwa
  • Sassan S. Saatchi
  • Lei Fan
  • Hui Yang
  • Xiaojun Li
  • Mengjia Wang
  • Lei Zhu
  • Yidi Xu
  • Jiaying He
  • Wei Li
Disturbance, vegetation productivity, and recovery are crucial for aboveground biomass carbon (AGC) dynamics. Here, we use multiple satellite-based datasets to analyze the drivers of AGC dynamics in Central Africa. During 2010–2019, deforestation induced a gross AGC loss of 102.2 ± 17.1 Tg C year−1, which was counterbalanced by an AGC increase of 116.9 ± 41.1 Tg C year−1, leading to a net gain of 14.6 ± 3.8 Tg C year−1. Compared to anthropogenic and soil factors, changes in climate-related factors (e.g., radiation) are more important for the non-deforestation AGC changes. A large AGC increase was found in the northern savannas. In moist forests, strong biomass recovery and growth largely compensated the carbon loss from deforestation and degradation. Considering the increasing resource demand due to rapid population growth, reconciling natural conservation and economic development in Central Africa remains challenging and depends on climate changes and country-specific social-economic conditions.
OriginalsprogEngelsk
TidsskriftOne Earth
Vol/bind7
Udgave nummer3
Sider (fra-til)506-519
Antal sider14
ISSN2590-3330
DOI
StatusUdgivet - 2024

Bibliografisk note

Funding Information:
This study was supported by the Yunnan Major Scientific and Technological Projects (grant number: 202302AO370001 ), the National Natural Science Foundation of China (grant numbers: 42175169 , 72348001 ), the Hainan Institute of National Park Research Program (grant number: KY-23ZK01 ), the National Key R&D Program of China (no. 2019YFA0606604 ), and the Tsinghua University Initiative Scientific Research Program (grant number: 20223080041 ). This work is a contribution to the CALIPSO (Carbon Loss In Plants, Soils and Oceans) project, funded through the generosity of Eric and Wendy Schmidt by recommendation of the Schmidt Futures program. S.L.L. is supported by NERC Large Grant NE/R016860/1 . J.C. is supported by ESA , CNES , and Programme Investissement d’Avenir (CEBA, ref. ANR-10-LABX-25-01 ; TULIP, ref. ANR-10-LABX-0041 ; ANAEE-France, ANR-11-INBS-0001 ). M.B. was supported by the European Research Council under the European Union’s Horizon 2020 Research and Innovation Programme (grant agreement no. 947757 TOFDRY ) and DFF Sapere Aude (grant no. 9064-00049B ). R.F. acknowledges support by the Villum Fonden through the project Deep Learning and Remote Sensing for Unlocking Global Ecosystem Resource Dynamics (DeReEco).

Funding Information:
This study was supported by the Yunnan Major Scientific and Technological Projects (grant number: 202302AO370001), the National Natural Science Foundation of China (grant numbers: 42175169, 72348001), the Hainan Institute of National Park grant (grant number: KY-23ZK01), the National Key R&D Program of China (no. 2019YFA0606604), and the Tsinghua University Initiative Scientific Research Program (grant number: 20223080041). This work is a contribution to the CALIPSO project supported by Schmidt Sciences. S.L.L. is supported by NERC Large Grant NE/R016860/1. J.C. is supported by ESA, CNES, and Programme Investissement d'Avenir (CEBA, ref. ANR-10-LABX-25-01; TULIP, ref. ANR-10-LABX-0041; ANAEE-France, ANR-11-INBS-0001). M.B. was supported by the European Research Council under the European Union's Horizon 2020 Research and Innovation Programme (grant agreement no. 947757 TOFDRY) and DFF Sapere Aude (grant no. 9064-00049B). R.F. acknowledges support by the Villum Fonden through the project Deep Learning and Remote Sensing for Unlocking Global Ecosystem Resource Dynamics (DeReEco). W.L. and P.C. designed the research. Z.Z. performed analysis. M.S. F.K. S.S.S. H.Y. X.L. and M.W. processed the data. Z.Z. and W.L. drafted the paper. All authors contributed to the interpretation of the results and to the text. The authors declare no competing interests.

Publisher Copyright:
© 2024 Elsevier Inc.

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