Articles | Volume 15, issue 1
https://doi.org/10.5194/bg-15-91-2018
https://doi.org/10.5194/bg-15-91-2018
Research article
 | 
05 Jan 2018
Research article |  | 05 Jan 2018

Gross changes in forest area shape the future carbon balance of tropical forests

Wei Li, Philippe Ciais, Chao Yue, Thomas Gasser, Shushi Peng, and Ana Bastos

Related authors

Modeling biochar effects on soil organic carbon on croplands in a microbial decomposition model (MIMICS-BC_v1.0)
Mengjie Han, Qing Zhao, Xili Wang, Ying-Ping Wang, Philippe Ciais, Haicheng Zhang, Daniel S. Goll, Lei Zhu, Zhe Zhao, Zhixuan Guo, Chen Wang, Wei Zhuang, Fengchang Wu, and Wei Li
Geosci. Model Dev., 17, 4871–4890, https://doi.org/10.5194/gmd-17-4871-2024,https://doi.org/10.5194/gmd-17-4871-2024, 2024
Short summary
The impacts of elevated CO2 on forest growth, mortality, and recovery in the Amazon rainforest
Yitong Yao, Philippe Ciais, Emilie Joetzjer, Wei Li, Lei Zhu, Yujie Wang, Christian Frankenberg, and Nicolas Viovy
Earth Syst. Dynam., 15, 763–778, https://doi.org/10.5194/esd-15-763-2024,https://doi.org/10.5194/esd-15-763-2024, 2024
Short summary
Evaluating the vegetation–atmosphere coupling strength of ORCHIDEE land surface model (v7266)
Yuan Zhang, Devaraju Narayanappa, Philippe Ciais, Wei Li, Daniel Goll, Nicolas Vuichard, Martin G. De Kauwe, Laurent Li, and Fabienne Maignan
Geosci. Model Dev., 15, 9111–9125, https://doi.org/10.5194/gmd-15-9111-2022,https://doi.org/10.5194/gmd-15-9111-2022, 2022
Short summary
Oil palm modelling in the global land surface model ORCHIDEE-MICT
Yidi Xu, Philippe Ciais, Le Yu, Wei Li, Xiuzhi Chen, Haicheng Zhang, Chao Yue, Kasturi Kanniah, Arthur P. Cracknell, and Peng Gong
Geosci. Model Dev., 14, 4573–4592, https://doi.org/10.5194/gmd-14-4573-2021,https://doi.org/10.5194/gmd-14-4573-2021, 2021
Short summary
A 30 m terrace mapping in China using Landsat 8 imagery and digital elevation model based on the Google Earth Engine
Bowen Cao, Le Yu, Victoria Naipal, Philippe Ciais, Wei Li, Yuanyuan Zhao, Wei Wei, Die Chen, Zhuang Liu, and Peng Gong
Earth Syst. Sci. Data, 13, 2437–2456, https://doi.org/10.5194/essd-13-2437-2021,https://doi.org/10.5194/essd-13-2437-2021, 2021
Short summary

Related subject area

Biogeochemistry: Modelling, Terrestrial
Development of the DO3SE-Crop model to assess ozone effects on crop phenology, biomass, and yield
Pritha Pande, Sam Bland, Nathan Booth, Jo Cook, Zhaozhong Feng, and Lisa Emberson
Biogeosciences, 22, 181–212, https://doi.org/10.5194/bg-22-181-2025,https://doi.org/10.5194/bg-22-181-2025, 2025
Short summary
Future methane fluxes of peatlands are controlled by management practices and fluctuations in hydrological conditions due to climatic variability
Vilna Tyystjärvi, Tiina Markkanen, Leif Backman, Maarit Raivonen, Antti Leppänen, Xuefei Li, Paavo Ojanen, Kari Minkkinen, Roosa Hautala, Mikko Peltoniemi, Jani Anttila, Raija Laiho, Annalea Lohila, Raisa Mäkipää, and Tuula Aalto
Biogeosciences, 21, 5745–5771, https://doi.org/10.5194/bg-21-5745-2024,https://doi.org/10.5194/bg-21-5745-2024, 2024
Short summary
Understanding and simulating cropland and non-cropland burning in Europe using the BASE (Burnt Area Simulator for Europe) model
Matthew Forrest, Jessica Hetzer, Maik Billing, Simon P. K. Bowring, Eric Kosczor, Luke Oberhagemann, Oliver Perkins, Dan Warren, Fátima Arrogante-Funes, Kirsten Thonicke, and Thomas Hickler
Biogeosciences, 21, 5539–5560, https://doi.org/10.5194/bg-21-5539-2024,https://doi.org/10.5194/bg-21-5539-2024, 2024
Short summary
Representation of the terrestrial carbon cycle in CMIP6
Bettina K. Gier, Manuel Schlund, Pierre Friedlingstein, Chris D. Jones, Colin Jones, Sönke Zaehle, and Veronika Eyring
Biogeosciences, 21, 5321–5360, https://doi.org/10.5194/bg-21-5321-2024,https://doi.org/10.5194/bg-21-5321-2024, 2024
Short summary
Does dynamically modeled leaf area improve predictions of land surface water and carbon fluxes? Insights into dynamic vegetation modules
Sven Armin Westermann, Anke Hildebrandt, Souhail Bousetta, and Stephan Thober
Biogeosciences, 21, 5277–5303, https://doi.org/10.5194/bg-21-5277-2024,https://doi.org/10.5194/bg-21-5277-2024, 2024
Short summary

Cited articles

Angelsen, A., Brown, S., Loisel, C., Peskett, L., Streck, C., and Zarin, D.: Reducing Emissions from Deforestation and Forest Degradation (REDD): An Options Assessment Report, available at: http://www.redd-oar.org/links/REDD-OAR_en.pdf (last access: June 2017), 2009. 
Baccini, A., Goetz, S. J., Walker, W. S., Laporte, N. T., Sun, M., Sulla-Menashe, D., Hackler, J., Beck, P. S. A., Dubayah, R., Friedl, M. A., Samanta, S., and Houghton, R. A.: Estimated carbon dioxide emissions from tropical deforestation improved by carbon-density maps, Nat. Clim. Change, 2, 182–185, https://doi.org/10.1038/nclimate1354, 2012. 
Bayer, A. D., Lindeskog, M., Pugh, T. A. M., Anthoni, P. M., Fuchs, R., and Arneth, A.: Uncertainties in the land-use flux resulting from land-use change reconstructions and gross land transitions, Earth Syst. Dynam., 8, 91–111, https://doi.org/10.5194/esd-8-91-2017, 2017. 
Ciais, P., Sabine, C., Bala, G., Bopp, L., Brovkin, V., Canadell, J., Chhabra, A., DeFries, R., Galloway, J., Heimann, M., Jones, C., Le Quéré, C., Myneni, R. B., Piao, S., and Thornton, P.: Carbon and Other Biogeochemical Cycles, in: Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Stocker, T. F., Qin, D., Plattner, G.-K., Tignor, M., Allen, S. K., Boschung, J., Nauels, A., Xia, Y., Bex, V., and Midgley, P. M., Cambridge University Press, Cambridge, UK and New York, NY, USA, 2013. 
Download
Short summary
We compared the biomass recovery curves from a recent field-based study with those used in bookkeeping models and demonstrated the importance of considering gross forest changes rather than net forest changes. We also derived a critical gross-to-net forest area change ratio, beyond which the sign of carbon flux will be reversed. This critical ratio was further applied to the high-resolution satellite data in the Amazon to distinguish the sensitive regions.
Altmetrics
Final-revised paper
Preprint