Implementation of trait-based ozone plant sensitivity in the Yale Interactive terrestrial Biosphere model v1.0 to assess global vegetation damage
Ma, Y; Yue, X; Sitch, S; et al.Unger, N; Uddling, J; Mercado, LM; Gong, C; Feng, Z; Yang, H; Zhou, H; Tian, C; Cao, Y; Lei, Y; Chesman, AW; Xu, Y; Duran Rojas, MC
Date: 26 April 2023
Article
Journal
Geoscientific Model Development (GMD)
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European Geosciences Union / Copernicus Publications
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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 ...
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 damage >10 % are found in agricultural areas in the eastern US, 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.
Mathematics and Statistics
Faculty of Environment, Science and Economy
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