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https://doi.org/10.5194/egusphere-2024-1179
https://doi.org/10.5194/egusphere-2024-1179
29 May 2024
 | 29 May 2024

Reviews and syntheses: One forest carbon model to rule them all? Utilizing ensembles of forest cover and biomass datasets to determine carbon budgets of the world’s forest ecosystems

Emil Alexander Cherrington, Christine Amelia Evans, Ashutosh S. Limaye, Eric Ross Anderson, and Africa Ixmucane Flores-Anderson

Abstract. Understanding global forest carbon stocks is necessary to assess the world’s global carbon budget, with land cover change being estimated to contribute roughly 20 % of the emissions of greenhouse gases to the atmosphere. In the last decade or so, remote sensing has contributed estimates of above ground stocks of biomass – a key part of forest carbon stocks – with over twenty biomass maps available at pan-tropical and global scales. To further the understanding of forest carbon stocks, this research seeks to synthesize the findings of disparate data sources on: (i) forest cover, (ii) forest cover change, (iii) above ground biomass (AGB) / above ground carbon (AGC) stocks in forests. Satellite-derived forest cover and AGB estimates have substantial variability. In 2020, forests were estimated to cover between 22.6 million and 49.7 million km2 of the Earth’s land surface, thus ranging from 17.1 % to 37.6 % of total land cover. Likewise, examining forest cover change from available datasets, the estimated change in global forest cover between 2000 and 2020 was loss of approximately 88,734 to 124,184 km2 per year, combined with regrowth of forest cover of approximately 58,628 to 169,912 km2 per year. Combining that forest cover data with remotely sensed AGB estimates, total stocks of AGB for the year 2000 were estimated to be 325–697 Gt, while for the year 2020, the range was 401–580 Gt. The equivalent quantity of CO2 (i.e., CO2e) of that stock of forest biomass was therefore estimated to be 560 to 1,200 Gt for the year 2000, and 692–999 Gt for the year 2020. Our analysis found that the forest cover loss in tropics was the largest, at the rate of 1.4 % to 3.5 % net reduction between 2000 and 2020, whereas for the same time period, the temperate and boreal zones showed substantially lower forest cover loss (-2.5 % to 0.5 % and 1 % to 5.3 % respectively). This synthesis paper demonstrates that there is a fairly wide range of variability in estimates related to forest cover, forest cover change, and above ground biomass stocks, which are the main inputs for estimating forest carbon stocks and greenhouse gas emissions from land cover change.

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Emil Alexander Cherrington, Christine Amelia Evans, Ashutosh S. Limaye, Eric Ross Anderson, and Africa Ixmucane Flores-Anderson

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2024-1179', Anonymous Referee #1, 17 Jun 2024
    • AC1: 'Reply on RC1', Emil Cherrington, 10 Jul 2024
  • RC2: 'Comment on egusphere-2024-1179', Anonymous Referee #2, 12 Aug 2024
    • AC2: 'Reply on RC2', Emil Cherrington, 30 Aug 2024

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2024-1179', Anonymous Referee #1, 17 Jun 2024
    • AC1: 'Reply on RC1', Emil Cherrington, 10 Jul 2024
  • RC2: 'Comment on egusphere-2024-1179', Anonymous Referee #2, 12 Aug 2024
    • AC2: 'Reply on RC2', Emil Cherrington, 30 Aug 2024
Emil Alexander Cherrington, Christine Amelia Evans, Ashutosh S. Limaye, Eric Ross Anderson, and Africa Ixmucane Flores-Anderson
Emil Alexander Cherrington, Christine Amelia Evans, Ashutosh S. Limaye, Eric Ross Anderson, and Africa Ixmucane Flores-Anderson

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Short summary
This study compares a wide range of public biomass spatial datasets, available for circa 2000–2020 at the pan-tropical and global scales, as well as datasets of forest cover extent. The main conclusions are that the datasets – which have been generated using different input remote sensing data and modeling techniques – present different conclusions regarding global stocks of carbon sequestered in forest ecosystems.