Spatiotemporal dynamics of ecosystem fires and biomass burning-induced carbon emissions in China over the past two decades

Anping Chen , Rongyun Tang , Jiafu Mao , Chao Yue , Xiran Li , Mengdi Gao , Xiaoying Shi , Mingzhou Jin , Daniel Ricciuto , Sam Rabin , Phillippe Ciais , Shilong Piao

Geography and Sustainability ›› 2020, Vol. 1 ›› Issue (1) : 47 -58.

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Geography and Sustainability ›› 2020, Vol. 1 ›› Issue (1) :47 -58. DOI: 10.1016/j.geosus.2020.03.002
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Spatiotemporal dynamics of ecosystem fires and biomass burning-induced carbon emissions in China over the past two decades

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Abstract

Fire is a major type of disturbance that has important influences on ecosystem dynamics and carbon cycles. Yet our understanding of ecosystem fires and their carbon cycle consequences is still limited, largely due to the difficulty of large-scale fire monitoring and the complex interactions between fire, vegetation, climate, and anthropogenic factors. Here, using data from satellite-derived fire observations and ecosystem model simulations, we performed a comprehensive investigation of the spatial and temporal dynamics of China's ecosystem fire disturbances and their carbon emissions over the past two decades (1997-2016). Satellite-derived results showed that on average about 3.47 - 4.53 × 104 km2 of the land was burned annually during the past two decades, among which annual burned forest area was about 0.81 - 1.25 × 104 km2, accounting for 0.33-0.51% of the forest area in China. Biomass burning emitted about 23.02 TgC per year. Compared to satellite products, simulations from the Energy Exascale Earth System Land Model (ELM) strongly overestimated China's burned area and fire-induced carbon emissions. Annual burned area and fire-induced carbon emissions were high for boreal forest in Northeast China's Daxing'anling region and subtropical dry forest in South Yunnan, as revealed by both the satellite product and the model simulations. Our results suggest that climate and anthropogenic factors play critical roles in controlling the spatial and seasonal distribution of China's ecosystem fire disturbances. Our findings highlight the importance of multiple complementary approaches in assessing ecosystem fire disturbance and its carbon consequences. Further studies are required to improve the methods of observing and modelling China's ecosystem fire disturbances, which will provide valuable information for fire management and ecosystem sustainability in an era when both human activities and the natural environment are rapidly changing.

Keywords

Fire emission / Burned area / Fire models / China

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Anping Chen, Rongyun Tang, Jiafu Mao, Chao Yue, Xiran Li, Mengdi Gao, Xiaoying Shi, Mingzhou Jin, Daniel Ricciuto, Sam Rabin, Phillippe Ciais, Shilong Piao. Spatiotemporal dynamics of ecosystem fires and biomass burning-induced carbon emissions in China over the past two decades. Geography and Sustainability, 2020, 1(1): 47-58 DOI:10.1016/j.geosus.2020.03.002

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Declaration Competing of Interest

The authors declare no conflict of interest.

Acknowledgements

Part of the funding was provided by the Carbon Mitigation Initiative (CMI) of the Princeton Environmental Institute, and by an Oak Ridge National Lab research subcontract to A.C. C. Y. and P. C. were supported by the fire_cci project (http://www.esa-fire-cci.org/) funded by the European Space Agency. S.R. was supported by a Graduate Research Fellowship from the U.S. National Science Foundation. R.T., J.M., X.S. and D.R. were supported by the Terrestrial Ecosystem Science Scientific Focus Area (TES SFA) project and the Reducing Uncertainties in Biogeochemical Interactions through Synthesis and Computing Scientific Focus Area (RUBISCO SFA) project funded by the US Department of Energy, Office of Science, Office of Biological and Environmental Research. Oak Ridge National Laboratory is supported by the Office of Science of the US Department of Energy under Contract No. DE-AC05-00OR22725.

Supplementary materials

Supplementary material associated with this article can be found, in the online version, at doi: 10.1016/j.geosus.2020.03.002.

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