Articles | Volume 17, issue 7
https://doi.org/10.5194/gmd-17-2547-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-17-2547-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
05 Apr 2024
Development and technical paper |
| 05 Apr 2024
| 05 Apr 2024
Modeling the effects of tropospheric ozone on the growth and yield of global staple crops with DSSAT v4.8.0
Center for Climate Systems Research, Columbia Climate School, Columbia University, New York, NY 10025, USA
NASA Goddard Institute for Space Studies, New York, NY 10025, USA
Jonas Jägermeyr
Center for Climate Systems Research, Columbia Climate School, Columbia University, New York, NY 10025, USA
NASA Goddard Institute for Space Studies, New York, NY 10025, USA
Elizabeth A. Ainsworth
Global Change and Photosynthesis Research Unit, United States Department of Agriculture, Agricultural Research Service, Urbana, IL 61801, USA
Fabio A. A. Oliveira
Department of Agricultural and Biological Engineering, University of Florida, Gainesville, FL 32611, USA
Senthold Asseng
School of Life Sciences, HEF World Agricultural Systems Center, Technical University of Munich, Freising, 85354, Germany
Kenneth Boote
Department of Agricultural and Biological Engineering, University of Florida, Gainesville, FL 32611, USA
Joshua Elliott
Center for Robust Decision-making on Climate and Energy Policy (RDCEP), University of Chicago, Chicago, IL 60637, USA
Lisa Emberson
Environment & Geography Dept., University of York, York, YO10 5NG, UK
Ian Foster
Department of Computer Science, University of Chicago, Chicago, IL 60637, USA
Gerrit Hoogenboom
Department of Agricultural and Biological Engineering, University of Florida, Gainesville, FL 32611, USA
David Kelly
Department of Computer Science, University of Chicago, Chicago, IL 60637, USA
Alex C. Ruane
NASA Goddard Institute for Space Studies, New York, NY 10025, USA
Katrina Sharps
UK Centre for Ecology & Hydrology, Environment Centre Wales, Bangor, LL57 2UW, UK
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Gabriella Everett, Øivind Hodnebrog, Madhoolika Agrawal, Durgesh Singh Yadav, Connie O'Neill, Chubamenla Jamir, Jo Cook, Pritha Pande, Sam Bland, and Lisa Emberson
Biogeosciences, 22, 4203–4219, https://doi.org/10.5194/bg-22-4203-2025, https://doi.org/10.5194/bg-22-4203-2025, 2025
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Ground-level ozone (O3), heat, and water stress (WS) reduce wheat yields, threatening food security in India. O3, heat, and WS interact as stressed plants close stomata, limiting O3 entry and damage. This study models O3 uptake under rainfed (WS) and irrigated conditions for current and future climates. Results show little O3-related yield loss under WS but higher losses with irrigation. Both climate scenarios increase O3-related losses, highlighting risks to India’s wheat productivity.
Lily-belle Sweet, Christoph Müller, Jonas Jägermeyr, and Jakob Zscheischler
EGUsphere, https://doi.org/10.5194/egusphere-2025-3006, https://doi.org/10.5194/egusphere-2025-3006, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
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This study presents a method to identify climate drivers of an impact, such as agricultural yield failure, from high-resolution weather data. The approach systematically generates, selects and combines predictors that generalise across different environments. Tested on crop model simulations, the identified drivers are used to create parsimonious models that achieve high predictive performance over long time horizons, offering a more interpretable alternative to black-box models.
Anam M. Khan, Olivia E. Clifton, Jesse O. Bash, Sam Bland, Nathan Booth, Philip Cheung, Lisa Emberson, Johannes Flemming, Erick Fredj, Stefano Galmarini, Laurens Ganzeveld, Orestis Gazetas, Ignacio Goded, Christian Hogrefe, Christopher D. Holmes, László Horváth, Vincent Huijnen, Qian Li, Paul A. Makar, Ivan Mammarella, Giovanni Manca, J. William Munger, Juan L. Pérez-Camanyo, Jonathan Pleim, Limei Ran, Roberto San Jose, Donna Schwede, Sam J. Silva, Ralf Staebler, Shihan Sun, Amos P. K. Tai, Eran Tas, Timo Vesala, Tamás Weidinger, Zhiyong Wu, Leiming Zhang, and Paul C. Stoy
Atmos. Chem. Phys., 25, 8613–8635, https://doi.org/10.5194/acp-25-8613-2025, https://doi.org/10.5194/acp-25-8613-2025, 2025
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Vegetation removes tropospheric ozone through stomatal uptake, and accurately modeling the stomatal uptake of ozone is important for modeling dry deposition and air quality. We evaluated the stomatal component of ozone dry deposition modeled by atmospheric chemistry models at six sites. We find that models and observation-based estimates agree at times during the growing season at all sites, but some models overestimated the stomatal component during the dry summers at a seasonally dry site.
Per Erik Karlsson, Patrick Büker, Sam Bland, David Simpson, Katrina Sharps, Felicity Hayes, and Lisa D. Emberson
Biogeosciences, 22, 3563–3582, https://doi.org/10.5194/bg-22-3563-2025, https://doi.org/10.5194/bg-22-3563-2025, 2025
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Stomatal ozone uptake and the negative impacts on forest growth rates were estimated for European forests. This was translated to annual increments in the forest living biomass carbon stocks, with and without ozone exposure. In the absence of O3 exposure, on average, European forest growth rates would increase by 9%, but the sequestration to the living-biomass carbon stocks would increase by 31% since the sequestration depends on the difference between growth and harvest rates.
Alex C. Ruane, Charlotte L. Pascoe, Claas Teichmann, David J. Brayshaw, Carlo Buontempo, Ibrahima Diouf, Jesus Fernandez, Paula L. M. Gonzalez, Birgit Hassler, Vanessa Hernaman, Ulas Im, Doroteaciro Iovino, Martin Juckes, Iréne L. Lake, Timothy Lam, Xiaomao Lin, Jiafu Mao, Negin Nazarian, Sylvie Parey, Indrani Roy, Wan-Ling Tseng, Briony Turner, Andrew Wiebe, Lei Zhao, and Damaris Zurell
EGUsphere, https://doi.org/10.5194/egusphere-2025-3408, https://doi.org/10.5194/egusphere-2025-3408, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
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This paper describes how the Coupled Model Intercomparison Project organized its 7th phase (CMIP7) to encourage the production of Earth system model outputs relevant for impacts and adaptation. Community engagement identified 13 opportunities for application across human and natural systems, 60 variable groups and 539 unique variables. We also show how simulations can more efficiently meet applications needs by targeting appropriate resolution, time slices, experiments and variable groups.
Dilli Paudel, Michiel Kallenberg, Stella Ofori-Ampofo, Hilmy Baja, Ron van Bree, Aike Potze, Pratishtha Poudel, Abdelrahman Saleh, Weston Anderson, Malte von Bloh, Andres Castellano, Oumnia Ennaji, Raed Hamed, Rahel Laudien, Donghoon Lee, Inti Luna, Michele Meroni, Janet Mumo Mutuku, Siyabusa Mkuhlani, Jonathan Richetti, Alex C. Ruane, Ritvik Sahajpal, Guanyuan Shai, Vasileios Sitokonstantinou, Rogério de Souza Nóia Júnior, Amit Kumar Srivastava, Robert Strong, Lily-belle Sweet, Petar Vojnovic, and Ioannis N. Athanasiadis
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-83, https://doi.org/10.5194/essd-2025-83, 2025
Preprint under review for ESSD
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Improving crop yield predictions is crucial for food security. Prior research relied on case studies, making it hard to compare methods & track progress. We introduce CY-Bench, a global dataset for forecasting maize and wheat yields across diverse farming systems in over 25 countries. It includes standardized weather, soil, and satellite data, curated by a diverse set of experts. CY-Bench supports the development of better forecasting tools to help decision-makers plan for global food security.
Jo Cook, Durgesh Singh Yadav, Felicity Hayes, Nathan Booth, Sam Bland, Pritha Pande, Samarthia Thankappan, and Lisa Emberson
Biogeosciences, 22, 1035–1056, https://doi.org/10.5194/bg-22-1035-2025, https://doi.org/10.5194/bg-22-1035-2025, 2025
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Ozone (O3) pollution reduces wheat yields and quality in India, affecting amino acids essential for nutrition, like lysine and methionine. Here, we improve the DO3SE-CropN model to simulate wheat’s protective processes against O3 and their impact on protein and amino acid concentrations. While the model captures O3-induced yield losses, it underestimates amino acid reductions. Further research is needed to refine the model, enabling future risk assessments of O3's impact on yields and nutrition.
Tamara Emmerichs, Abdulla Al Mamun, Lisa Emberson, Huiting Mao, Leiming Zhang, Limei Ran, Clara Betancourt, Anthony Wong, Gerbrand Koren, Giacomo Gerosa, Min Huang, and Pierluigi Guaita
EGUsphere, https://doi.org/10.5194/egusphere-2025-429, https://doi.org/10.5194/egusphere-2025-429, 2025
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The risk of ozone pollution to plants is estimated based on the flux through the plant pores which still has uncertainties. In this study, we estimate this quantity with 9 models at different land types worldwide. The input data stems from a database. The models estimated mostly reasonable summertime ozone deposition. The different results of the models varied by land cover which were mostly related to the moisture deficit. This is an important step for assessing the ozone impact on vegetation.
Detlef van Vuuren, Brian O'Neill, Claudia Tebaldi, Louise Chini, Pierre Friedlingstein, Tomoko Hasegawa, Keywan Riahi, Benjamin Sanderson, Bala Govindasamy, Nico Bauer, Veronika Eyring, Cheikh Fall, Katja Frieler, Matthew Gidden, Laila Gohar, Andrew Jones, Andrew King, Reto Knutti, Elmar Kriegler, Peter Lawrence, Chris Lennard, Jason Lowe, Camila Mathison, Shahbaz Mehmood, Luciana Prado, Qiang Zhang, Steven Rose, Alexander Ruane, Carl-Friederich Schleussner, Roland Seferian, Jana Sillmann, Chris Smith, Anna Sörensson, Swapna Panickal, Kaoru Tachiiri, Naomi Vaughan, Saritha Vishwanathan, Tokuta Yokohata, and Tilo Ziehn
EGUsphere, https://doi.org/10.5194/egusphere-2024-3765, https://doi.org/10.5194/egusphere-2024-3765, 2025
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We propose a set of six plausible 21st century emission scenarios, and their multi-century extensions, that will be used by the international community of climate modeling centers to produce the next generation of climate projections. These projections will support climate, impact and mitigation researchers, provide information to practitioners to address future risks from climate change, and contribute to policymakers’ considerations of the trade-offs among various levels of mitigation.
Pritha Pande, Sam Bland, Nathan Booth, Jo Cook, Zhaozhong Feng, and Lisa Emberson
Biogeosciences, 22, 181–212, https://doi.org/10.5194/bg-22-181-2025, https://doi.org/10.5194/bg-22-181-2025, 2025
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The DO3SE-Crop model extends the DO3SE to simulate ozone's impact on crops with modules for ozone uptake, damage, and crop growth from JULES-crop. It's versatile, suits China's varied agriculture, and improves yield predictions under ozone stress. It is essential for policy, water management, and climate response, and it integrates into Earth system models for a comprehensive understanding of agriculture's interaction with global systems.
Jo Cook, Clare Brewster, Felicity Hayes, Nathan Booth, Sam Bland, Pritha Pande, Samarthia Thankappan, Håkan Pleijel, and Lisa Emberson
Biogeosciences, 21, 4809–4835, https://doi.org/10.5194/bg-21-4809-2024, https://doi.org/10.5194/bg-21-4809-2024, 2024
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At ground level, the air pollutant ozone (O3) damages wheat yield and quality. We modified the DO3SE-Crop model to simulate O3 effects on wheat quality and identified onset of leaf death as the key process affecting wheat quality upon O3 exposure. This aligns with expectations, as the onset of leaf death aids nutrient transfer from leaves to grains. Breeders should prioritize wheat varieties resistant to protein loss from delayed leaf death, to maintain yield and quality under O3 exposure.
David Gackstetter, Parid Varoshi, and Senthold Asseng
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-4-2024, 197–204, https://doi.org/10.5194/isprs-archives-XLVIII-4-2024-197-2024, https://doi.org/10.5194/isprs-archives-XLVIII-4-2024-197-2024, 2024
Olivia E. Clifton, Donna Schwede, Christian Hogrefe, Jesse O. Bash, Sam Bland, Philip Cheung, Mhairi Coyle, Lisa Emberson, Johannes Flemming, Erick Fredj, Stefano Galmarini, Laurens Ganzeveld, Orestis Gazetas, Ignacio Goded, Christopher D. Holmes, László Horváth, Vincent Huijnen, Qian Li, Paul A. Makar, Ivan Mammarella, Giovanni Manca, J. William Munger, Juan L. Pérez-Camanyo, Jonathan Pleim, Limei Ran, Roberto San Jose, Sam J. Silva, Ralf Staebler, Shihan Sun, Amos P. K. Tai, Eran Tas, Timo Vesala, Tamás Weidinger, Zhiyong Wu, and Leiming Zhang
Atmos. Chem. Phys., 23, 9911–9961, https://doi.org/10.5194/acp-23-9911-2023, https://doi.org/10.5194/acp-23-9911-2023, 2023
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A primary sink of air pollutants is dry deposition. Dry deposition estimates differ across the models used to simulate atmospheric chemistry. Here, we introduce an effort to examine dry deposition schemes from atmospheric chemistry models. We provide our approach’s rationale, document the schemes, and describe datasets used to drive and evaluate the schemes. We also launch the analysis of results by evaluating against observations and identifying the processes leading to model–model differences.
Stefanie Falk, Ane V. Vollsnes, Aud B. Eriksen, Lisa Emberson, Connie O'Neill, Frode Stordal, and Terje Koren Berntsen
Biogeosciences Discuss., https://doi.org/10.5194/bg-2021-260, https://doi.org/10.5194/bg-2021-260, 2021
Revised manuscript not accepted
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Subarctic vegetation is threatened by climate change and ozone. We assess essential climate variables in 2018/19. 2018 was warmer and brighter than usual in Spring with forest fires and elevated ozone in summer. Visible damage was observed on plant species in 2018. We find that generic parameterizations used in modeling ozone dose do not suffice. We propose a method to acclimate these parameterizations and find an ozone-induced biomass loss of 2.5 to 17.4 % (up to 6 % larger than default).
James A. Franke, Christoph Müller, Joshua Elliott, Alex C. Ruane, Jonas Jägermeyr, Abigail Snyder, Marie Dury, Pete D. Falloon, Christian Folberth, Louis François, Tobias Hank, R. Cesar Izaurralde, Ingrid Jacquemin, Curtis Jones, Michelle Li, Wenfeng Liu, Stefan Olin, Meridel Phillips, Thomas A. M. Pugh, Ashwan Reddy, Karina Williams, Ziwei Wang, Florian Zabel, and Elisabeth J. Moyer
Geosci. Model Dev., 13, 3995–4018, https://doi.org/10.5194/gmd-13-3995-2020, https://doi.org/10.5194/gmd-13-3995-2020, 2020
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Improving our understanding of the impacts of climate change on crop yields will be critical for global food security in the next century. The models often used to study the how climate change may impact agriculture are complex and costly to run. In this work, we describe a set of global crop model emulators (simplified models) developed under the Agricultural Model Intercomparison Project. Crop model emulators make agricultural simulations more accessible to policy or decision makers.
Cited articles
Adams, R. M., Glyer, J. D., Johnson, S. L., and McCarl, B. A.: A reassessment of the economic effects of ozone on United States agriculture, J. Air Waste Manage. A., 39, 960–968, https://doi.org/10.1080/08940630.1989.10466583, 1989.
Ahmed, M., Stockle, C. O., Nelson, R., and Higgins, S.: Assessment of Climate Change and Atmospheric CO2 Impact on Winter Wheat in the Pacific Northwest Using a Multimodel Ensemble, Front. Ecol. Evol., 5, https://doi.org/10.3389/fevo.2017.00051, 2017.
Ahmed, M., Stockle, C. O., Nelson, R., Higgins, S., Ahmad, S., and Raza, M. A.: Novel multimodel ensemble approach to evaluate the sole effect of elevated CO2 on winter wheat productivity, Sci. Rep., 9, 7813., https://doi.org/10.1038/s41598-019-44251-x, 2019.
Ainsworth, E. A.: Understanding and improving global crop response to ozone pollution, Plant J., 90, 886–897, https://doi.org/10.1111/tpj.13298, 2017.
Arias, P. A., Bellouin, N., Coppola, E., Jones, R. G., Krinner, G., Marotzke, J., Naik, V., Palmer, M. D., Plattner, G.-K., Rogelj, J., Rojas, M., Sillmann, J., Storelvmo, T., Thorne, P. W., Trewin, B., Achuta Rao, K., Adhikary, B., Allan, R. P., Armour, K., Bala, G., Barimalala, R., Berger, S., Canadell, J. G., Cassou, C., Cherchi, A., Collins, W., Collins, W. D., Connors, S. L., Corti, S., Cruz, F., Dentener, F. J., Dereczynski, C., Di Luca, A., Diongue Niang, A., Doblas-Reyes, F. J., Dosio, A., Douville, H., Engelbrecht, F., Eyring, V., Fischer, E., Forster, P., Fox-Kemper, B., Fuglestvedt, J. S., Fyfe, J. C., Gillett, N. P., Goldfarb, L., Gorodetskaya, I., Gutierrez, J. M., Hamdi, R., Hawkins, E., Hewitt, H. T., Hope, P., Islam, A. S., Jones, C., Kaufman, D. S., Kopp, R. E., Kosaka, Y., Kossin, J., Krakovska, S., Lee, J.-Y., Li, J., Mauritsen, T., Maycock, T. K., Meinshausen, M., Min, S.-K., Monteiro, P. M. S., Ngo-Duc, T., Otto, F., Pinto, I., Pirani, A., Raghavan, K., Ranasinghe, R., Ruane, A. C., Ruiz, L., Sallée, J.-B., Samset, B. H., Sathyendranath, S., Seneviratne, S. I., Sörensson, A. A., Szopa, S., Takayabu, I., Tréguier, A.-M., van den Hurk, B., Vautard, R., von Schuckmann, K., Zaehle, S., Zhang, X., and Zickfeld, K.: Technical Summary, in: Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Masson-Delmotte, V., Zhai, P., Pirani, A., Connors, S. L., Péan, C., Berger, S., Caud, N., Chen, Y., Goldfarb, L., Gomis, M. I., Huang, M., Leitzell, K., Lonnoy, E., Matthews, J. B. R., Maycock, T. K., Waterfield, T., Yelekçi, O., Yu, R., and Zhou, B., Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 33–144, https://doi.org/10.1017/9781009157896.002, 2021.
Asseng, S. and van Herwaarden, A. F.: Analysis of the benefits to wheat yield from assimilates stored prior to grain filling in a range of environments, Plant Soil, 256, 217–229, https://doi.org/10.1023/a:1026231904221, 2003.
Asseng, S., Jamieson, P. D., Kimball, B., Pinter, P., Sayre, K., Bowden, J. W., and Howden, S. M.: Simulated wheat growth affected by rising temperature, increased water deficit and elevated atmospheric CO2, Field Crops Res., 85, 85–102, https://doi.org/10.1016/s0378-4290(03)00154-0, 2004.
Asseng, S., Ewert, F., Martre, P., Rotter, R. P., Lobell, D. B., Cammarano, D., Kimball, B. A., Ottman, M. J., Wall, G. W., White, J. W., Reynolds, M. P., Alderman, P. D., Prasad, P. V. V., Aggarwal, P. K., Anothai, J., Basso, B., Biernath, C., Challinor, A. J., De Sanctis, G., Doltra, J., Fereres, E., Garcia-Vile, M., Gayler, S., Hoogenboom, G., Hunt, L. A., Izaurralde, R. C., Jabloun, M., Jones, C. D., Kersebaum, K. C., Koehler, A. K., Muller, C., Kumar, S. N., Nendel, C., O'Leary, G., Olesen, J. E., Palosuo, T., Priesack, E., Rezaei, E. E., Ruane, A. C., Semenov, M. A., Shcherbak, I., Stockle, C., Stratonovitch, P., Streck, T., Supit, I., Tao, F., Thorburn, P. J., Waha, K., Wang, E., Wallach, D., Wolf, I., Zhao, Z., and Zhu, Y.: Rising temperatures reduce global wheat production, Nat. Clim. Change, 5, 143–147, https://doi.org/10.1038/nclimate2470, 2015.
Bassu, S., Brisson, N., Durand, J. L., Boote, K., Lizaso, J., Jones, J. W., Rosenzweig, C., Ruane, A. C., Adam, M., Baron, C., Basso, B., Biernath, C., Boogaard, H., Conijn, S., Corbeels, M., Deryng, D., De Sanctis, G., Gayler, S., Grassini, P., Hatfield, J., Hoek, S., Izaurralde, C., Jongschaap, R., Kemanian, A. R., Kersebaum, K. C., Kim, S. H., Kumar, N. S., Makowski, D., Muller, C., Nendel, C., Priesack, E., Pravia, M. V., Sau, F., Shcherbak, I., Tao, F., Teixeira, E., Timlin, D., and Waha, K.: How do various maize crop models vary in their responses to climate change factors?, Global Change Biol., 20, 2301–2320, https://doi.org/10.1111/gcb.12520, 2014.
Betzelberger, A. M., Yendrek, C. R., Sun, J. D., Leisner, C. P., Nelson, R. L., Ort, D. R., and Ainsworth, E. A.: Ozone Exposure Response for U.S. Soybean Cultivars: Linear Reductions in Photosynthetic Potential, Biomass, and Yield, Plant Physiol., 160, 1827–1839, https://doi.org/10.1104/pp.112.205591, 2012.
Biswas, D. K., Xu, H., Li, Y. G., Ma, B. L., and Jiang, G. M.: Modification of photosynthesis and growth responses to elevated CO2 by ozone in two cultivars of winter wheat with different years of release, J. Exp. Bot., 64, 1485–1496, https://doi.org/10.1093/jxb/ert005, 2013.
Boote, K. J. and Pickering, N. B.: Modeling photosynthesis of row crop canopies, Hortscience, 29, 1423–1434, https://doi.org/10.21273/hortsci.29.12.1423, 1994.
Calabrese, E. J.: Hormesis: a fundamental concept in biology, Microb. Cell, 1, 145–149, https://doi.org/10.15698/mic2014.05.145, 2014.
Choquette, N. E., Ainsworth, E. A., Bezodis, W., and Cavanagh, A. P.: Ozone tolerant maize hybrids maintain Rubisco content and activity during long-term exposure in the field, Plant Cell Environ., 43, 3033–3047, https://doi.org/10.1111/pce.13876, 2020.
Cooper, O. R., Parrish, D. D., Ziemke, J., Balashov, N. V., Cupeiro, M., Galbally, I. E., Gilge, S., Horowitz, L., Jensen, N. R., Lamarque, J.-F., Naik, V., Oltmans, S. J., Schwab, J., Shindell, D. T., Thompson, A. M., Thouret, V., Wang, Y., and Zbinden, R. M.: Global distribution and trends of tropospheric ozone: An observation-based review, Elementa Science of the Anthropocene, 2, 000029, https://doi.org/10.12952/journal.elementa.000029, 2014.
Elliott, J., Kelly, D., Chryssanthacopoulos, J., Glotter, M., Jhunjhnuwala, K., Best, N., Wilde, M., and Foster, I.: The parallel system for integrating impact models and sectors (pSIMS), Environ. Model. Softw., 62, 509–516, https://doi.org/10.1016/j.envsoft.2014.04.008, 2014.
Emberson, L.: Effects of ozone on agriculture, forests and grasslands, Philos. T. Roy. Soc. A, 378, 27, https://doi.org/10.1098/rsta.2019.0327, 2020.
Emberson, L. D., Pleijel, H., Ainsworth, E. A., van den Berg, M., Ren, W., Osborne, S., Mills, G., Pandey, D., Dentener, F., Buker, P., Ewert, F., Koeble, R., and Van Dingenen, R.: Ozone effects on crops and consideration in crop models, Eur. J. Agron., 100, 19–34, https://doi.org/10.1016/j.eja.2018.06.002, 2018.
Feng, Z. Z. and Kobayashi, K.: Assessing the impacts of current and future concentrations of surface ozone on crop yield with meta-analysis, Atmos. Environ., 43, 1510–1519, https://doi.org/10.1016/j.atmosenv.2008.11.033, 2009.
Feng, Z. Z., Xu, Y. S., Kobayashi, K., Dai, L. L., Zhang, T. Y., Agathokleous, E., Calatayud, V., Paoletti, E., Mukherjee, A., Agrawal, M., Park, R. J., Oak, Y. J., and Yue, X.: Ozone pollution threatens the production of major staple crops in East Asia, Nature Food, 3, 47, https://doi.org/10.1038/s43016-021-00422-6, 2022.
Griffiths, P. T., Murray, L. T., Zeng, G., Shin, Y. M., Abraham, N. L., Archibald, A. T., Deushi, M., Emmons, L. K., Galbally, I. E., Hassler, B., Horowitz, L. W., Keeble, J., Liu, J., Moeini, O., Naik, V., O'Connor, F. M., Oshima, N., Tarasick, D., Tilmes, S., Turnock, S. T., Wild, O., Young, P. J., and Zanis, P.: Tropospheric ozone in CMIP6 simulations, Atmos. Chem. Phys., 21, 4187–4218, https://doi.org/10.5194/acp-21-4187-2021, 2021.
Guarin, J. R., Kassie, B., Mashaheet, A. M., Burkey, K., and Asseng, S.: Modeling the effects of tropospheric ozone on wheat growth and yield, Eur. J. Agron., 105, 13–23, https://doi.org/10.1016/j.eja.2019.02.004, 2019.
Guarin, J. R., Jägermeyr, J., Ainsworth, E. A., Oliveira, F. A. A., Asseng, S., Boote, K., Elliott, J., Emberson, L., Foster, I., Hoogenboom, G., Kelly, D., Ruane, A. C., and Sharps, K.: Data for modeling the effects of tropospheric ozone on the growth and yield of global staple crops with DSSAT v4.8.0, V2, Harvard Dataverse [data set], https://doi.org/10.7910/DVN/0NN9MH, 2023.
Heck, W. W., Cure, W. W., Rawlings, J. O., Zaragoza, L. J., Heagle, A. S., Heggestad, H. E., Kohut, R. J., Kress, L. W., and Temple, P. J.: Assessing impacts of ozone on agricultural crops: 2. Crop yield functions and alternative exposure statistics, J. Air Pollut. Control A., 34, 810–817, https://doi.org/10.1080/00022470.1984.10465815, 1984.
Hoogenboom, G., Porter, C. H., Boote, K. J., Shelia, V., Wilkens, P. W., Singh, U., White, J. W., Asseng, S., Lizaso, J. I., Moreno, L. P., Pavan, W., Ogoshi, R., Hunt, L. A., Tsuji, G. Y., and Jones, J. W.: The DSSAT crop modeling ecosystem, in: Advances in Crop Modeling for a Sustainable Agriculture, edited by: Boote, K. J., Burleigh Dodds Science Publishing, Cambridge, United Kingdom, 173–216, https://doi.org/10.19103/AS.2019.0061.10, 2019.
Hoogenboom, G., Porter, C. H., Shelia, V., Boote, K. J., Singh, U., White, J. W., Pavan, W., Oliveira, F. A. A., Moreno-Cadena, L. P., Lizaso, J. I., Asseng, S., Pequeno, D. N. L., Kimball, B. A., Alderman, P. D., Thorp, K. R., Jones, M. R., Cuadra, S. V., Vianna, M. S., Villalobos, F. J., Ferreira, T. B., Batchelor, W. D., Koo, J., Hunt, L. A., and Jones, J. W.: Decision Support System for Agrotechnology Transfer (DSSAT) Version 4.8, DSSAT Foundation, Gainesville, Florida, USA [code], http://www.DSSAT.net (last access: 28 March 2024), 2021.
Hou, P. and Wu, S. L.: Long-term Changes in Extreme Air Pollution Meteorology and the Implications for Air Quality, Sci. Rep., 6, 23792, https://doi.org/10.1038/srep23792, 2016.
Hunsaker, D. J., Kimball, B. A., Pinter, P. J., LaMorte, R. L., and Wall, G. W.: Carbon dioxide enrichment and irrigation effects on wheat evapotranspiration and water use efficiency, Transactions of the Asae, 39, 1345–1355, 1996.
IPCC: Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Masson-Delmotte, V., Zhai, P., Pirani, A., Connors, S. L., Péan, C., Berger, S., Caud, N., Chen, Y., Goldfarb, L., Gomis, M. I., Huang, M., Leitzell, K., Lonnoy, E., Matthews, J. B. R., Maycock, T. K., Waterfield, T., Yelekçi, O., Yu, R., and Zhou, B., Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 2391, https://doi.org/10.1017/9781009157896, 2021.
Jagermeyr, J., Muller, C., Ruane, A. C., Elliott, J., Balkovic, J., Castillo, O., Faye, B., Foster, I., Folberth, C., Franke, J. A., Fuchs, K., Guarin, J. R., Heinke, J., Hoogenboom, G., Iizumi, T., Jain, A. K., Kelly, D., Khabarov, N., Lange, S., Lin, T. S., Liu, W. F., Mialyk, O., Minoli, S., Moyer, E. J., Okada, M., Phillips, M., Porter, C., Rabin, S. S., Scheer, C., Schneider, J. M., Schyns, J. F., Skalsky, R., Smerald, A., Stella, T., Stephens, H., Webber, H., Zabel, F., and Rosenzweig, C.: Climate impacts on global agriculture emerge earlier in new generation of climate and crop models, Nature Food, 2, 875, https://doi.org/10.1038/s43016-021-00400-y, 2021.
Jones, C. A. and Kiniry, J. R. (Eds.): CERES-Maize: A simulation model of maize growth and development, Texas A&M University Press, College Station, TX, ISBN 0890962693, 1986.
Jones, J. W., Hoogenboom, G., Porter, C. H., Boote, K. J., Batchelor, W. D., Hunt, L. A., Wilkens, P. W., Singh, U., Gijsman, A. J., and Ritchie, J. T.: The DSSAT cropping system model, Eur. J. Agron., 18, 235–265, https://doi.org/10.1016/s1161-0301(02)00107-7, 2003.
Khan, S. and Soja, G.: Yield responses of wheat to ozone exposure as modified by drought-induced differences in ozone uptake, Water Air Soil Pollut., 147, 299–315, https://doi.org/10.1023/a:1024577429129, 2003.
Kimball, B. A., LaMorte, R. L., Pinter, P. J., Wall, G. W., Hunsaker, D. J., Adamsen, F. J., Leavitt, S. W., Thompson, T. L., Matthias, A. D., and Brooks, T. J.: Free-air CO2 enrichment and soil nitrogen effects on energy balance and evapotranspiration of wheat, Water Resour. Res., 35, 1179–1190, https://doi.org/10.1029/1998wr900115, 1999.
Kimball, B. A., Pinter Jr., P. J., LaMorte, R. L., Leavitt, S. W., Hunsaker, D. J., Wall, G. W., Wechsung, F., Wechsung, G., Bloom, A. J., and White, J. W.: Data from the Arizona FACE (free-air CO2 enrichment) experiments on wheat at ample and limiting levels of water and nitrogen, Open Data J. Agric. Res., 3, 29–38, https://doi.org/10.18174/odjar.v3i1.15826, 2017.
Kothari, K., Battisti, R., Boote, K. J., Archontoulis, S. V., Confalone, A., Constantin, J., Cuadra, S. V., Debaeke, P., Faye, B., Grant, B., Hoogenboom, G., Jing, Q., van der Laan, M., da Silva, F. A. M., Marin, F. R., Nehbandani, A., Nendel, C., Purcell, L. C., Qian, B. D., Ruane, A. C., Schoving, C., Silva, E., Smith, W., Soltani, A., Srivastava, A., Vieira, N. A., Slone, S., and Salmeron, M.: Are soybean models ready for climate change food impact assessments?, Eur. J. Agron., 135, 15, https://doi.org/10.1016/j.eja.2022.126482, 2022.
Lesser, V. M., Rawlings, J. O., Spruill, S. E., and Somerville, M. C.: Ozone effects on agricultural crops: Statistical methodologies and estimated dose-response relationships, Crop Sci., 30, 148–155, https://doi.org/10.2135/cropsci1990.0011183X003000010033x, 1990.
Leung, F., Williams, K., Sitch, S., Tai, A. P. K., Wiltshire, A., Gornall, J., Ainsworth, E. A., Arkebauer, T., and Scoby, D.: Calibrating soybean parameters in JULES 5.0 from the US-Ne2/3 FLUXNET sites and the SoyFACE-O3 experiment, Geosci. Model Dev., 13, 6201–6213, https://doi.org/10.5194/gmd-13-6201-2020, 2020.
Li, T., Hasegawa, T., Yin, X. Y., Zhu, Y., Boote, K., Adam, M., Bregaglio, S., Buis, S., Confalonieri, R., Fumoto, T., Gaydon, D., Marcaida, M., Nakagawa, H., Oriol, P., Ruane, A. C., Ruget, F., Singh, B., Singh, U., Tang, L., Tao, F. L., Wilkens, P., Yoshida, H., Zhang, Z., and Bouman, B.: Uncertainties in predicting rice yield by current crop models under a wide range of climatic conditions, Global Change Biol., 21, 1328–1341, https://doi.org/10.1111/gcb.12758, 2015.
Mills, G., Sharps, K., Simpson, D., Pleijel, H., Broberg, M., Uddling, J., Jaramillo, F., Davies, W. J., Dentener, F., Van den Berg, M., Agrawal, M., Agrawal, S. B., Ainsworth, E. A., Buker, P., Emberson, L., Feng, Z. Z., Harmens, H., Hayes, F., Kobayashi, K., Paoletti, E., and Van Dingenen, R.: Ozone pollution will compromise efforts to increase global wheat production, Global Change Biol., 24, 3560–3574, https://doi.org/10.1111/gcb.14157, 2018a.
Mills, G., Sharps, K., Simpson, D., Pleijel, H., Frei, M., Burkey, K., Emberson, L., Uddling, J., Broberg, M., Feng, Z. Z., Kobayashi, K., and Agrawal, M.: Closing the global ozone yield gap: Quantification and cobenefits for multistress tolerance, Global Change Biol., 24, 4869–4893, https://doi.org/10.1111/gcb.14381, 2018b.
Morris, M. D.: Factorial sampling plans for preliminary computational experiments, Technometrics, 33, 161–174, https://doi.org/10.2307/1269043, 1991.
Mulchi, C. L., Lee, E., Tuthill, K., and Olinick, E. V.: Influence of ozone stress on growth-processes, yields and grain quality characteristics among soybean cultivars, Environ. Pollut., 53, 151–169, https://doi.org/10.1016/0269-7491(88)90031-0, 1988.
NRCS, S. S. S.: Natural Resources Conservation Service, United States Department of Agriculture, Web Soil Survey [data set], https://websoilsurvey.nrcs.usda.gov/app/ (last access: 20 January 2023), 2023.
Osborne, S. A., Mills, G., Hayes, F., Ainsworth, E. A., Buker, P., and Emberson, L.: Has the sensitivity of soybean cultivars to ozone pollution increased with time? An analysis of published dose-response data, Global Change Biol., 22, 3097–3111, https://doi.org/10.1111/gcb.13318, 2016.
Porter, C., Hoogenboom, G., Murilodsv, Pavan, W., Ferreira, T. B., Zhang, M., palderman, Thorp, K., Guarin, J., Mulugetaifdc, Vásquez-Jiménez, J., Villalobos, C., Clifford, D., YujingGao-git, singhu, and vshelia: jguarin4/dssat-csm-os: v4.8.0.27-pDSSAT-archive (v4.8.0.27_pDSSAT-archive), Zenodo [code], https://doi.org/10.5281/zenodo.8284732, 2023.
R Core Team: R: a language and environment for statistical computing, R Core Team [code], https://www.R-project.org/ (last access: 28 March 2024), 2023.
RDCEP: pSIMS, RDCEP [code], http://www.rdcep.org/research-projects/psims (last access: 28 March 2024), 2024.
Ritchie, J. T., Alocilja, E. C., Singh, U., and Uehara, G.: IBSNAT and the CERES-RICE model, in: Weather and Rice, Proceedings of the International Workshop on The Impact of Weather Parameters on Growth and Yield of Rice, IRRI, Philippines, 271–283, 1987.
Rosenzweig, C., Jones, J. W., Hatfield, J. L., Ruane, A. C., Boote, K. J., Thorburne, P., Antle, J. M., Nelson, G. C., Porter, C., Janssen, S., Asseng, S., Basso, B., Ewert, F., Wallach, D., Baigorria, G., and Winter, J. M.: The Agricultural Model Intercomparison and Improvement Project (AgMIP): Protocols and pilot studies, Agric. Forest Meteorol., 170, 166–182, https://doi.org/10.1016/j.agrformet.2012.09.011, 2013.
Sampedro, J., Waldhoff, S. T., Van de Ven, D. J., Pardo, G., Van Dingenen, R., Arto, I., del Prado, A., and Sanz, M. J.: Future impacts of ozone driven damages on agricultural systems, Atmos. Environ., 231, 11, https://doi.org/10.1016/j.atmosenv.2020.117538, 2020.
Schauberger, B., Rolinski, S., Schaphoff, S., and Muller, C.: Global historical soybean and wheat yield loss estimates from ozone pollution considering water and temperature as modifying effects, Agric. Forest Meteorol., 265, 1–15, https://doi.org/10.1016/j.agrformet.2018.11.004, 2019.
Schiferl, L. D. and Heald, C. L.: Particulate matter air pollution may offset ozone damage to global crop production, Atmos. Chem. Phys., 18, 5953–5966, https://doi.org/10.5194/acp-18-5953-2018, 2018.
Simpson, D., Arneth, A., Mills, G., Solberg, S., and Uddling, J.: Ozone – the persistent menace: interactions with the N cycle and climate change, Curr. Opin. Env. Sust., 9–10, 9–19, https://doi.org/10.1016/j.cosust.2014.07.008, 2014.
Szopa, S., Naik, V., Adhikary, B., Artaxo, P., Berntsen, T., Collins, W. D., Fuzzi, S., Gallardo, L., Kiendler-Scharr, A., Klimont, Z., Liao, H., Unger, N., and Zanis, P.: 2021: Short-Lived Climate Forcers, in: Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Masson-Delmotte, V., Zhai, P., Pirani, A., Connors, S. L., Péan, C., Berger, S., Caud, N., Chen, Y., Goldfarb, L., Gomis, M. I., Huang, M., Leitzell, K., Lonnoy, E., Matthews, J. B. R., Maycock, T. K., Waterfield, T., Yelekçi, O., Yu, R., and Zhou, B., Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 817–922, https://doi.org/10.1017/9781009157896.008, 2021.
Tai, A. P. K., Sadiq, M., Pang, J. Y. S., Yung, D. H. Y., and Feng, Z. Z.: Impacts of Surface Ozone Pollution on Global Crop Yields: Comparing Different Ozone Exposure Metrics and Incorporating Co-effects of CO2, Front. Sust. Food Syst., 5, 18, https://doi.org/10.3389/fsufs.2021.534616, 2021.
Toreti, A., Deryng, D., Tubiello, F. N., Muller, C., Kimball, B. A., Moser, G., Boote, K., Asseng, S., Pugh, T. A. M., Vanuytrecht, E., Pleijel, H., Webber, H., Durand, J. L., Dentener, F., Ceglar, A., Wang, X. H., Badeck, F., Lecerf, R., Wall, G. W., van den Berg, M., Hoegy, P., Lopez-Lozano, R., Zampieri, M., Galmarini, S., O'Leary, G. J., Manderscheid, R., Contreras, E. M., and Rosenzweig, C.: Narrowing uncertainties in the effects of elevated CO2 on crops, Nature Food, 1, 775–782, https://doi.org/10.1038/s43016-020-00195-4, 2020.
USDA NASS: Field crops usual planting and harvest dates (October 2010), Agricultural Handbook Number 628, https://usda.library.cornell.edu/concern/publications/vm40xr56k (last access: 20 January 2023), 2010.
Wang, X. P. and Mauzerall, D. L.: Characterizing distributions of surface ozone and its impact on grain production in China, Japan and South Korea: 1990 and 2020, Atmos. Environ., 38, 4383–4402, https://doi.org/10.1016/j.atmosenv.2004.03.067, 2004.
Wickham, H.: ggplot2: Elegant Graphics for Data Analysis, Springer-Verlag NY [code], ISBN 978-3-319-24277-4, https://ggplot2.tidyverse.org (last access: 28 March 2024), 2016.
Wickham, H., François, R., Henry, L., Müller, K., and Vaughan, D.: dplyr: A Grammar of Data Manipulation, R package version 1.1.2, GitHub [code], https://github.com/tidyverse/dplyr (last access: 28 March 2024), 2023.
Wilkerson, G. G., Jones, J. W., Boote, K. J., Ingram, K. T., and Mishoe, J. W.: Modeling soybean growth for crop management, Transactions of the Asae, 26, 63–73, 1983.
Xia, L. L., Lam, S. K., Kiese, R., Chen, D. L., Luo, Y. Q., van Groenigen, K. J., Ainsworth, E. A., Chen, J., Liu, S. W., Ma, L., Zhu, Y. H., and Butterbach-Bahl, K.: Elevated CO2 negates O3 impacts on terrestrial carbon and nitrogen cycles, One Earth, 4, 1752–1763, https://doi.org/10.1016/j.oneear.2021.11.009, 2021.
Zhang, Y. Z. and Wang, Y. H.: Climate-driven ground-level ozone extreme in the fall over the Southeast United States, P. Natl. Acad. Sci. USA, 113, 10025–10030, https://doi.org/10.1073/pnas.1602563113, 2016.
Short summary
The effects of ozone (O3) stress on crop photosynthesis and leaf senescence were added to maize, rice, soybean, and wheat crop models. The modified models reproduced growth and yields under different O3 levels measured in field experiments and reported in the literature. The combined interactions between O3 and additional stresses were reproduced with the new models. These updated crop models can be used to simulate impacts of O3 stress under future climate change and air pollution scenarios.
The effects of ozone (O3) stress on crop photosynthesis and leaf senescence were added to maize,...
