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Biogeosciences An interactive open-access journal of the European Geosciences Union
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Volume 14, issue 22 | Copyright
Biogeosciences, 14, 5053-5067, 2017
https://doi.org/10.5194/bg-14-5053-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 14 Nov 2017

Research article | 14 Nov 2017

Land-use and land-cover change carbon emissions between 1901 and 2012 constrained by biomass observations

Wei Li1, Philippe Ciais1, Shushi Peng1,2, Chao Yue1, Yilong Wang1, Martin Thurner3, Sassan S. Saatchi4, Almut Arneth5, Valerio Avitabile6, Nuno Carvalhais7,8, Anna B. Harper9, Etsushi Kato10, Charles Koven11, Yi Y. Liu12, Julia E.M.S. Nabel13, Yude Pan14, Julia Pongratz13, Benjamin Poulter15, Thomas A. M. Pugh5,16, Maurizio Santoro17, Stephen Sitch18, Benjamin D. Stocker19,20, Nicolas Viovy1, Andy Wiltshire21, Rasoul Yousefpour13,a, and Sönke Zaehle7 Wei Li et al.
  • 1Laboratoire des Sciences du Climat et de l'Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, 91191 Gif-sur-Yvette, France
  • 2Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
  • 3Department of Environmental Science and Analytical Chemistry (ACES) and the Bolin Centre for Climate Research, Stockholm University, 106 91 Stockholm, Sweden
  • 4Jet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Drive, Pasadena, CA 91109, USA
  • 5Karlsruhe Institute of Technology, Institute of Meteorology and Climate Research – Atmospheric Environmental Research (IMK-IFU), Garmisch-Partenkirchen, Germany
  • 6Centre for Geo-Information and Remote Sensing, Wageningen University & Research, Droevendaalsesteeg 3, 6708PB Wageningen, the Netherlands
  • 7Department for Biogeochemical Integration, Max-Planck-Institute for Biogeochemistry, Jena, Germany
  • 8CENSE, Departamento de Ciências e Engenharia do Ambiente, Faculdade de Ciências e Tecnologia, Universidade NOVA de Lisboa, Caparica, Portugal
  • 9College of Engineering, Mathematics, and Physical Sciences, University of Exeter, Exeter, UK
  • 10Institute of Applied Energy, Minato, Tokyo 105-0003, Japan
  • 11Climate and Ecosystem Sciences Department, Lawrence Berkeley Lab, Berkeley, CA, USA
  • 12ARC Centre of Excellence for Climate Systems Science & Climate Change Research Centre, University of New South Wales, Sydney, New South Wales 2052, Australia
  • 13Max Planck Institute for Meteorology, Hamburg, Germany
  • 14USDA Forest Service, Durham, New Hampshire, USA
  • 15Department of Ecology, Montana State University, Bozeman, MT 59717, USA
  • 16School of Geography, Earth & Environmental Science and Birmingham Institute of Forest Research, University of Birmingham, Birmingham, B15 2TT, UK
  • 17GAMMA Remote Sensing, 3073 Gümligen, Switzerland
  • 18College of Life and Environmental Sciences, University of Exeter, Exeter, UK
  • 19Climate and Environmental Physics, and Oeschger Centre for Climate Change Research, University of Bern, Bern, Switzerland
  • 20Imperial College London, Life Science Department, Silwood Park, Ascot, Berkshire SL5 7PY, UK
  • 21Met Office Hadley Centre, Exeter, Devon, EX1 3PB, UK
  • acurrent address: Chair of Forestry Economics and Forest Planning, University of Freiburg, 79106 Freiburg, Germany

Abstract. The use of dynamic global vegetation models (DGVMs) to estimate CO2 emissions from land-use and land-cover change (LULCC) offers a new window to account for spatial and temporal details of emissions and for ecosystem processes affected by LULCC. One drawback of LULCC emissions from DGVMs, however, is lack of observation constraint. Here, we propose a new method of using satellite- and inventory-based biomass observations to constrain historical cumulative LULCC emissions (ELUCc) from an ensemble of nine DGVMs based on emerging relationships between simulated vegetation biomass and ELUCc. This method is applicable on the global and regional scale. The original DGVM estimates of ELUCc range from 94 to 273PgC during 1901–2012. After constraining by current biomass observations, we derive a best estimate of 155±50PgC (1σ Gaussian error). The constrained LULCC emissions are higher than prior DGVM values in tropical regions but significantly lower in North America. Our emergent constraint approach independently verifies the median model estimate by biomass observations, giving support to the use of this estimate in carbon budget assessments. The uncertainty in the constrained ELUCc is still relatively large because of the uncertainty in the biomass observations, and thus reduced uncertainty in addition to increased accuracy in biomass observations in the future will help improve the constraint. This constraint method can also be applied to evaluate the impact of land-based mitigation activities.

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We used several observation-based biomass datasets to constrain the historical land-use change carbon emissions simulated by models. Compared to the range of the original modeled emissions (from 94 to 273 Pg C), the observationally constrained global cumulative emission estimate is 155 ± 50 Pg C (1σ Gaussian error) from 1901 to 2012. Our approach can also be applied to evaluate the LULCC impact of land-based climate mitigation policies.
We used several observation-based biomass datasets to constrain the historical land-use change...
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