Articles | Volume 20, issue 7
https://doi.org/10.5194/bg-20-1357-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/bg-20-1357-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
06 Apr 2023
Research article |
| 06 Apr 2023
| 06 Apr 2023
Post-flooding disturbance recovery promotes carbon capture in riparian zones
Yihong Zhu
College of Earth and Planetary Sciences, University of Chinese Academy of Sciences (UCAS), Beijing, 100049, China
Yale School of the Environment, Yale University, New Haven, 06511, USA
Department of Environmental Science, Policy and Management, University of California, Berkeley, 94704, USA
Ruihua Liu
College of Earth and Planetary Sciences, University of Chinese Academy of Sciences (UCAS), Beijing, 100049, China
Yale School of the Environment, Yale University, New Haven, 06511, USA
Huai Zhang
CORRESPONDING AUTHOR
College of Earth and Planetary Sciences, University of Chinese Academy of Sciences (UCAS), Beijing, 100049, China
Shaoda Liu
CORRESPONDING AUTHOR
State Key Laboratory for Water Environment Simulation, School of Environment, Beijing Normal University, Beijing, 100875, China
Zhengfeng Zhang
College of Earth and Planetary Sciences, University of Chinese Academy of Sciences (UCAS), Beijing, 100049, China
Fei-Hai Yu
Institute of Wetland Ecology & Clone Ecology/Zhejiang Provincial Key Laboratory of Plant Evolutionary Ecology and Conservation,
Taizhou University, Taizhou, 318000, Zhejiang, China
Timothy G. Gregoire
Yale School of the Environment, Yale University, New Haven, 06511, USA
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Preprint under review for ESSD
Short summary
Short summary
We developed the first 30 m, wall-to-wall annual dataset of national grassland canopy cover from 1990 to 2023. By integrating drone and Landsat-series imagery, our model generates high predictive accuracy and robust temporal transferability compared to historical validation dataset. This dataset provides a critical foundation for advancing the understanding of grassland ecosystem dynamics and for supporting evidence-based conservation and sustainable management strategies.
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Short summary
With global warming, the risk of flooding is rising, but the response of the carbon cycle of aquatic and associated riparian systems
to flooding is still unclear. Based on the data collected in the Lijiang, we found that flooding would lead to significant carbon emissions of fluvial areas and riparian areas during flooding, but carbon capture may happen after flooding. In the riparian areas, the surviving vegetation, especially clonal plants, played a vital role in this transformation.
With global warming, the risk of flooding is rising, but the response of the carbon cycle of...
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