Preprints
https://doi.org/10.5194/gmd-2022-227
https://doi.org/10.5194/gmd-2022-227
Submitted as: development and technical paper
19 Sep 2022
Submitted as: development and technical paper | 19 Sep 2022
Status: this preprint is currently under review for the journal GMD.

Implementation of trait-based ozone plant sensitivity in the Yale Interactive terrestrial Biosphere model v1.0 to assess global vegetation damage

Yimian Ma1,2, Xu Yue3, Stephen Sitch4, Nadine Unger3, Johan Uddling5, Lina Mercado4,6, Cheng Gong7, Zhaozhong Feng8, Huiyi Yang9, Hao Zhou1,2, Chenguang Tian1,2, Yang Cao1,2, Yadong Lei10, Alexander Cheesman4,11, Yansen Xu8, and Maria Duran Rojas12 Yimian Ma et al.
  • 1Climate Change Research Center, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China
  • 2University of Chinese Academy of Sciences, Beijing, 100029, China
  • 3Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, Nanjing, 210044, China
  • 4Faculty of Environment, Science and Economy, University of Exeter, Exeter, EX4 4RJ, UK
  • 5Department of Biological and Environmental Sciences, University of Gothenburg, Gothenburg, P.O. Box 461, 40530, Sweden
  • 6UK Centre for Ecology and Hydrology, Benson Lane, Wallingford, OX10 8BB, UK
  • 7State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China
  • 8School of Applied Meteorology, Nanjing University of Information Science and Technology, Nanjing, 210044, China
  • 9Livelihoods and Institutions Department, Natural Resources Institute, University of Greenwich, Kent, ME4 4TB, UK
  • 10Chinese Academy of Meteorological Sciences, Beijing, 100081, China
  • 11Centre for Tropical Environmental and Sustainability Science, College of Science & Engineering, James Cook University, Cairns, Queensland, 4870 Australia
  • 12College of Engineering, Mathematics, and Physical Sciences, University of Exeter, Exeter, EX4 4PY, UK

Abstract. A major limitation in modeling global ozone (O3) vegetation damage has long been the reliance on empirical O3 sensitivity parameters derived from a limited number of species and applied at the level of plant functional types (PFTs), which ignore the large interspecific variations within the same PFT. Here, we present a major advance in large-scale assessments of O3 plant injury by linking the trait leaf mass per area (LMA) and plant O3 sensitivity in a broad and global perspective. Application of the new approach and a global LMA map in a dynamic global vegetation model reasonably represents the observed interspecific responses to O3 with a unified sensitivity parameter for all plant species. Simulations suggest a contemporary global mean reduction of 4.8 % in gross primary productivity by O3, with a range of 1.1 %–12.6 % for varied PFTs. Hotspots with damages > 10 % are found in agricultural areas in the eastern U.S., western Europe, eastern China, and India, accompanied by moderate to high levels of surface O3. Furthermore, we simulate the distribution of plant sensitivity to O3, which is highly linked with the inherent leaf trait trade-off strategies of plants, revealing high risks for fast-growing species with low LMA, such as crops, grasses and deciduous trees.

Yimian Ma et al.

Status: open (until 14 Nov 2022)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse

Yimian Ma et al.

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Short summary
Plants have been found to respond differently to O3, but the variations in the sensitivities have rarely been explained, neither fully implemented in large scale assessment. This study proposes a new O3 damage scheme with leaf mass per area to unify varied sensitivities for all plant species. Our assessment reveals an O3-induced reduction of 4.8 % in global GPP with the highest reduction of >10 % for cropland, suggesting an emerging risk of crop yield loss under the threat of O3 pollution.