Implementation of trait-based ozone plant sensitivity in the Yale Interactive terrestrial Biosphere model v1.0 to assess global vegetation damage
<p>A major limitation in modeling global ozone (O<span class="inline-formula"><sub>3</sub></span>) vegetation damage has long been the reliance on empirical O<span class="inline-formula"><sub>3</sub></span> sensitivity paramet...
| Main Authors: | , , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2023-04-01
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| Series: | Geoscientific Model Development |
| Online Access: | https://gmd.copernicus.org/articles/16/2261/2023/gmd-16-2261-2023.pdf |
| _version_ | 1797838927566995456 |
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| author | Y. Ma Y. Ma X. Yue S. Sitch N. Unger J. Uddling L. M. Mercado L. M. Mercado C. Gong Z. Feng H. Yang H. Zhou H. Zhou C. Tian C. Tian Y. Cao Y. Cao Y. Lei A. W. Cheesman A. W. Cheesman Y. Xu M. C. Duran Rojas |
| author_facet | Y. Ma Y. Ma X. Yue S. Sitch N. Unger J. Uddling L. M. Mercado L. M. Mercado C. Gong Z. Feng H. Yang H. Zhou H. Zhou C. Tian C. Tian Y. Cao Y. Cao Y. Lei A. W. Cheesman A. W. Cheesman Y. Xu M. C. Duran Rojas |
| author_sort | Y. Ma |
| collection | DOAJ |
| description | <p>A major limitation in modeling global ozone (O<span class="inline-formula"><sub>3</sub></span>) vegetation damage has
long been the reliance on empirical O<span class="inline-formula"><sub>3</sub></span> 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 O<span class="inline-formula"><sub>3</sub></span> plant injury by linking the trait leaf mass per area
(LMA) and plant O<span class="inline-formula"><sub>3</sub></span> 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 O<span class="inline-formula"><sub>3</sub></span> with a unified sensitivity parameter for all plant species.
Simulations suggest a contemporary global mean reduction of 4.8 % in gross
primary productivity by O<span class="inline-formula"><sub>3</sub></span>, with a range of 1.1 %–12.6 % for varied
PFTs. Hotspots with damage <span class="inline-formula">>10 <i>%</i></span> are found in agricultural
areas in the eastern US, western Europe, eastern China, and India,
accompanied by moderate to high levels of surface O<span class="inline-formula"><sub>3</sub></span>. Furthermore, we
simulate the distribution of plant sensitivity to O<span class="inline-formula"><sub>3</sub></span>, 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.</p> |
| first_indexed | 2024-04-09T15:50:01Z |
| format | Article |
| id | doaj.art-aaa86cd1870347d6bc150175c624992a |
| institution | Directory Open Access Journal |
| issn | 1991-959X 1991-9603 |
| language | English |
| last_indexed | 2024-04-09T15:50:01Z |
| publishDate | 2023-04-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Geoscientific Model Development |
| spelling | doaj.art-aaa86cd1870347d6bc150175c624992a2023-04-26T12:30:17ZengCopernicus PublicationsGeoscientific Model Development1991-959X1991-96032023-04-01162261227610.5194/gmd-16-2261-2023Implementation of trait-based ozone plant sensitivity in the Yale Interactive terrestrial Biosphere model v1.0 to assess global vegetation damageY. Ma0Y. Ma1X. Yue2S. Sitch3N. Unger4J. Uddling5L. M. Mercado6L. M. Mercado7C. Gong8Z. Feng9H. Yang10H. Zhou11H. Zhou12C. Tian13C. Tian14Y. Cao15Y. Cao16Y. Lei17A. W. Cheesman18A. W. Cheesman19Y. Xu20M. C. Duran Rojas21Climate Change Research Center, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, ChinaCollege of Earth and Planetary Science, University of Chinese Academy of Sciences, Beijing, 100049, ChinaJiangsu 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, ChinaFaculty of Environment, Science and Economy, University of Exeter, Exeter, EX4 4RJ, UKJiangsu 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, ChinaDepartment of Biological and Environmental Sciences, University of Gothenburg, Gothenburg, P.O. Box 461, 40530, SwedenFaculty of Environment, Science and Economy, University of Exeter, Exeter, EX4 4RJ, UKUK Centre for Ecology and Hydrology, Benson Lane, Wallingford, OX10 8BB, UKState Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, ChinaSchool of Applied Meteorology, Nanjing University of Information Science and Technology, Nanjing, 210044, ChinaLivelihoods and Institutions Department, Natural Resources Institute, University of Greenwich, Kent, ME4 4TB, UKClimate Change Research Center, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, ChinaCollege of Earth and Planetary Science, University of Chinese Academy of Sciences, Beijing, 100049, ChinaClimate Change Research Center, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, ChinaCollege of Earth and Planetary Science, University of Chinese Academy of Sciences, Beijing, 100049, ChinaClimate Change Research Center, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, ChinaCollege of Earth and Planetary Science, University of Chinese Academy of Sciences, Beijing, 100049, ChinaState Key Laboratory of Severe Weather and Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing, 100081, ChinaFaculty of Environment, Science and Economy, University of Exeter, Exeter, EX4 4RJ, UKCentre for Tropical Environmental and Sustainability Science, College of Science & Engineering, James Cook University, Cairns, 4878, AustraliaSchool of Applied Meteorology, Nanjing University of Information Science and Technology, Nanjing, 210044, ChinaCollege of Engineering, Mathematics, and Physical Sciences, University of Exeter, Exeter, EX4 4PY, UK<p>A major limitation in modeling global ozone (O<span class="inline-formula"><sub>3</sub></span>) vegetation damage has long been the reliance on empirical O<span class="inline-formula"><sub>3</sub></span> 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 O<span class="inline-formula"><sub>3</sub></span> plant injury by linking the trait leaf mass per area (LMA) and plant O<span class="inline-formula"><sub>3</sub></span> 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 O<span class="inline-formula"><sub>3</sub></span> with a unified sensitivity parameter for all plant species. Simulations suggest a contemporary global mean reduction of 4.8 % in gross primary productivity by O<span class="inline-formula"><sub>3</sub></span>, with a range of 1.1 %–12.6 % for varied PFTs. Hotspots with damage <span class="inline-formula">>10 <i>%</i></span> are found in agricultural areas in the eastern US, western Europe, eastern China, and India, accompanied by moderate to high levels of surface O<span class="inline-formula"><sub>3</sub></span>. Furthermore, we simulate the distribution of plant sensitivity to O<span class="inline-formula"><sub>3</sub></span>, 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.</p>https://gmd.copernicus.org/articles/16/2261/2023/gmd-16-2261-2023.pdf |
| spellingShingle | Y. Ma Y. Ma X. Yue S. Sitch N. Unger J. Uddling L. M. Mercado L. M. Mercado C. Gong Z. Feng H. Yang H. Zhou H. Zhou C. Tian C. Tian Y. Cao Y. Cao Y. Lei A. W. Cheesman A. W. Cheesman Y. Xu M. C. Duran Rojas Implementation of trait-based ozone plant sensitivity in the Yale Interactive terrestrial Biosphere model v1.0 to assess global vegetation damage Geoscientific Model Development |
| title | Implementation of trait-based ozone plant sensitivity in the Yale Interactive terrestrial Biosphere model v1.0 to assess global vegetation damage |
| title_full | Implementation of trait-based ozone plant sensitivity in the Yale Interactive terrestrial Biosphere model v1.0 to assess global vegetation damage |
| title_fullStr | Implementation of trait-based ozone plant sensitivity in the Yale Interactive terrestrial Biosphere model v1.0 to assess global vegetation damage |
| title_full_unstemmed | Implementation of trait-based ozone plant sensitivity in the Yale Interactive terrestrial Biosphere model v1.0 to assess global vegetation damage |
| title_short | Implementation of trait-based ozone plant sensitivity in the Yale Interactive terrestrial Biosphere model v1.0 to assess global vegetation damage |
| title_sort | implementation of trait based ozone plant sensitivity in the yale interactive terrestrial biosphere model v1 0 to assess global vegetation damage |
| url | https://gmd.copernicus.org/articles/16/2261/2023/gmd-16-2261-2023.pdf |
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