4.7 Article Data Paper

A map of African humid tropical forest aboveground biomass derived from management inventories

Journal

SCIENTIFIC DATA
Volume 7, Issue 1, Pages -

Publisher

NATURE PORTFOLIO
DOI: 10.1038/s41597-020-0561-0

Keywords

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Funding

  1. 3DForMod post-doctoral grant
  2. ERA-NET FACCE ERA-GAS from European Union's Horizon 2020 research and innovation program [ANR-17-EGAS-0002-01, 696356]
  3. IFS [D/5621-1]
  4. European Union Climate KIC grant Agreement [EIT/CLIMATE KIC/SGA2016/1]
  5. Global Environment Facility by the World Bank [TF010038]
  6. Shell Gabon
  7. Smithsonian Conservation Biology Institute [197]
  8. Agence Nationale de la Recherche (ANR) [ANR-17-EGAS-0002] Funding Source: Agence Nationale de la Recherche (ANR)
  9. H2020 Societal Challenges Programme [696356] Funding Source: H2020 Societal Challenges Programme

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Forest biomass is key in Earth carbon cycle and climate system, and thus under intense scrutiny in the context of international climate change mitigation initiatives (e.g. REDD+). In tropical forests, the spatial distribution of aboveground biomass (AGB) remains, however, highly uncertain. There is increasing recognition that progress is strongly limited by the lack of field observations over large and remote areas. Here, we introduce the Congo basin Forests AGB (CoFor-AGB) dataset that contains AGB estimations and associated uncertainty for 59,857 1-km pixels aggregated from nearly 100,000 ha ofin situforest management inventories for the 2000 - early 2010s period in five central African countries. A comprehensive error propagation scheme suggests that the uncertainty on AGB estimations derived from c. 0.5-ha inventory plots (8.6-15.0%) is only moderately higher than the error obtained from scientific sampling plots (8.3%). CoFor-AGB provides the first large scale view of forest AGB spatial variation from field data in central Africa, the second largest continuous tropical forest domain of the world.

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