Articles | Volume 22, issue 1
https://doi.org/10.5194/bg-22-181-2025
© Author(s) 2025. 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-22-181-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
10 Jan 2025
Research article |
| 10 Jan 2025
| 10 Jan 2025
Development of the DO3SE-Crop model to assess ozone effects on crop phenology, biomass, and yield
Stockholm Environment Institute at York, Department of Environment and Geography, University of York, YO10 5DD, York, UK
Sam Bland
Stockholm Environment Institute at York, Department of Environment and Geography, University of York, YO10 5DD, York, UK
Nathan Booth
Department of Environment and Geography, University of York, YO10 5DD, York, UK
Department of Environment and Geography, University of York, YO10 5DD, York, UK
Zhaozhong Feng
Key Laboratory of Agrometeorology of Jiangsu Province, School of Ecology and Applied Meteorology, Nanjing University of Information Science and Technology, Nanjing, China
Lisa Emberson
Department of Environment and Geography, University of York, YO10 5DD, York, UK
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Gabriella Everett, Øivind Hodnebrog, Madhoolika Agrawal, Durgesh Singh Yadav, Connie O'Neill, Chubamenla Jamir, Jo Cook, Pritha Pande, and Lisa Emberson
EGUsphere, https://doi.org/10.5194/egusphere-2024-3371, https://doi.org/10.5194/egusphere-2024-3371, 2024
This preprint is open for discussion and under review for Biogeosciences (BG).
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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 wWS but higher losses with irrigation. Both climate scenarios increase O3-related losses, highlighting risks to India’s wheat productivity.
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.
Jo Cook, Durgesh Singh Yadav, Felicity Hayes, Nathan Booth, Sam Bland, Pritha Pande, Samarthia Thankappan, and Lisa Emberson
EGUsphere, https://doi.org/10.5194/egusphere-2024-2968, https://doi.org/10.5194/egusphere-2024-2968, 2024
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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.
Per Erik Karlsson, Patrick Büker, Sam Bland, David Simpson, Katrina Sharps, Felicity Hayes, and Lisa Emberson
EGUsphere, https://doi.org/10.5194/egusphere-2024-3742, https://doi.org/10.5194/egusphere-2024-3742, 2024
This preprint is open for discussion and under review for Biogeosciences (BG).
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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, European forest growth rates would on average 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.
Gabriella Everett, Øivind Hodnebrog, Madhoolika Agrawal, Durgesh Singh Yadav, Connie O'Neill, Chubamenla Jamir, Jo Cook, Pritha Pande, and Lisa Emberson
EGUsphere, https://doi.org/10.5194/egusphere-2024-3371, https://doi.org/10.5194/egusphere-2024-3371, 2024
This preprint is open for discussion and under review for Biogeosciences (BG).
Short summary
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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 wWS but higher losses with irrigation. Both climate scenarios increase O3-related losses, highlighting risks to India’s wheat productivity.
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
Short summary
Short summary
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.
Jo Cook, Durgesh Singh Yadav, Felicity Hayes, Nathan Booth, Sam Bland, Pritha Pande, Samarthia Thankappan, and Lisa Emberson
EGUsphere, https://doi.org/10.5194/egusphere-2024-2968, https://doi.org/10.5194/egusphere-2024-2968, 2024
Short summary
Short summary
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.
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, Laszlo Horvath, Vincent Huijnen, Qian Li, Paul A. Makar, Ivan Mammarella, Giovanni Manca, J. William Munger, Juan L. Perez-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, Tamas Weidinger, Zhiyong Wu, Leiming Zhang, and Paul C. Stoy
EGUsphere, https://doi.org/10.5194/egusphere-2024-3038, https://doi.org/10.5194/egusphere-2024-3038, 2024
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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.
Fang Li, Zhimin Zhou, Samuel Levis, Stephen Sitch, Felicity Hayes, Zhaozhong Feng, Peter B. Reich, Zhiyi Zhao, and Yanqing Zhou
Geosci. Model Dev., 17, 6173–6193, https://doi.org/10.5194/gmd-17-6173-2024, https://doi.org/10.5194/gmd-17-6173-2024, 2024
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A new scheme is developed to model the surface ozone damage to vegetation in regional and global process-based models. Based on 4210 data points from ozone experiments, it accurately reproduces statistically significant linear or nonlinear photosynthetic and stomatal responses to ozone in observations for all vegetation types. It also enables models to implicitly capture the variability in plant ozone tolerance and the shift among species within a vegetation type.
Tong Sha, Siyu Yang, Qingcai Chen, Liangqing Li, Xiaoyan Ma, Yan-Lin Zhang, Zhaozhong Feng, K. Folkert Boersma, and Jun Wang
Atmos. Chem. Phys., 24, 8441–8455, https://doi.org/10.5194/acp-24-8441-2024, https://doi.org/10.5194/acp-24-8441-2024, 2024
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Using an updated soil reactive nitrogen emission scheme in the Unified Inputs for Weather Research and Forecasting coupled with Chemistry (UI-WRF-Chem) model, we investigate the role of soil NO and HONO (Nr) emissions in air quality and temperature in North China. Contributions of soil Nr emissions to O3 and secondary pollutants are revealed, exceeding effects of soil NOx or HONO emission. Soil Nr emissions play an important role in mitigating O3 pollution and addressing climate change.
Jose Rafael Guarin, Jonas Jägermeyr, Elizabeth A. Ainsworth, Fabio A. A. Oliveira, Senthold Asseng, Kenneth Boote, Joshua Elliott, Lisa Emberson, Ian Foster, Gerrit Hoogenboom, David Kelly, Alex C. Ruane, and Katrina Sharps
Geosci. Model Dev., 17, 2547–2567, https://doi.org/10.5194/gmd-17-2547-2024, https://doi.org/10.5194/gmd-17-2547-2024, 2024
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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.
Jia Mao, Amos P. K. Tai, David H. Y. Yung, Tiangang Yuan, Kong T. Chau, and Zhaozhong Feng
Atmos. Chem. Phys., 24, 345–366, https://doi.org/10.5194/acp-24-345-2024, https://doi.org/10.5194/acp-24-345-2024, 2024
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Surface ozone (O3) is well-known for posing great threats to both human health and agriculture worldwide. However, a multidecadal assessment of the impacts of O3 on public health and agriculture in China is lacking without sufficient O3 observations. We used a hybrid approach combining a chemical transport model and machine learning to provide a robust dataset of O3 concentrations over the past 4 decades in China, thereby filling the gap in the long-term O3 trend and impact assessment in China.
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.
Yimian Ma, Xu Yue, Stephen Sitch, Nadine Unger, Johan Uddling, Lina M. Mercado, Cheng Gong, Zhaozhong Feng, Huiyi Yang, Hao Zhou, Chenguang Tian, Yang Cao, Yadong Lei, Alexander W. Cheesman, Yansen Xu, and Maria Carolina Duran Rojas
Geosci. Model Dev., 16, 2261–2276, https://doi.org/10.5194/gmd-16-2261-2023, https://doi.org/10.5194/gmd-16-2261-2023, 2023
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Plants have been found to respond differently to O3, but the variations in the sensitivities have rarely been explained nor 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.
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).
Martina Franz, Rocio Alonso, Almut Arneth, Patrick Büker, Susana Elvira, Giacomo Gerosa, Lisa Emberson, Zhaozhong Feng, Didier Le Thiec, Riccardo Marzuoli, Elina Oksanen, Johan Uddling, Matthew Wilkinson, and Sönke Zaehle
Biogeosciences, 15, 6941–6957, https://doi.org/10.5194/bg-15-6941-2018, https://doi.org/10.5194/bg-15-6941-2018, 2018
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Four published ozone damage functions previously used in terrestrial biosphere models were evaluated regarding their ability to simulate observed biomass dose–response relationships using the O-CN model. Neither damage function was able to reproduce the observed ozone-induced biomass reductions. Calibrating a plant-functional-type-specific relationship between accumulated ozone uptake and leaf-level photosynthesis did lead to a good agreement between observed and modelled ozone damage.
C. Hardacre, O. Wild, and L. Emberson
Atmos. Chem. Phys., 15, 6419–6436, https://doi.org/10.5194/acp-15-6419-2015, https://doi.org/10.5194/acp-15-6419-2015, 2015
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The dry deposition of ozone to the Earth's surface is an important process as it controls both the removal of this potent pollutant from the atmosphere and its uptake by vegetation. It is necessary to use numerical models to study this process at the global scale, but many models to represent dry deposition lag behind current understanding. In this paper we study the dry deposition process in global models and highlight measures that will allow these models to be critically evaluated.
L. D. Emberson, N. Kitwiroon, S. Beevers, P. Büker, and S. Cinderby
Atmos. Chem. Phys., 13, 6741–6755, https://doi.org/10.5194/acp-13-6741-2013, https://doi.org/10.5194/acp-13-6741-2013, 2013
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The movement of water, carbon, and energy from the Earth's surface to the atmosphere, or flux, is an important process to understand because it impacts our lives. Here, we outline a method called FLUXCOM-X to estimate global water and CO2 fluxes based on direct measurements from sites around the world. We go on to demonstrate how these new estimates of net CO2 uptake/loss, gross CO2 uptake, total water evaporation, and transpiration from plants compare to previous and independent estimates.
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Biogeosciences, 21, 4285–4300, https://doi.org/10.5194/bg-21-4285-2024, https://doi.org/10.5194/bg-21-4285-2024, 2024
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Biogeosciences, 21, 4195–4227, https://doi.org/10.5194/bg-21-4195-2024, https://doi.org/10.5194/bg-21-4195-2024, 2024
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Stefano Manzoni and M. Francesca Cotrufo
Biogeosciences, 21, 4077–4098, https://doi.org/10.5194/bg-21-4077-2024, https://doi.org/10.5194/bg-21-4077-2024, 2024
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Huajie Zhu, Xiuli Xing, Mousong Wu, Weimin Ju, and Fei Jiang
Biogeosciences, 21, 3735–3760, https://doi.org/10.5194/bg-21-3735-2024, https://doi.org/10.5194/bg-21-3735-2024, 2024
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Ecosystem carbonyl sulfide (COS) fluxes were employed to optimize GPP estimation across ecosystems with the Biosphere-atmosphere Exchange Process Simulator (BEPS), which was developed for simulating the canopy COS uptake under its state-of-the-art two-leaf modeling framework. Our results showcased the efficacy of COS in improving model prediction and reducing prediction uncertainty of GPP and enhanced insights into the sensitivity, identifiability, and interactions of parameters related to COS.
Moritz Laub, Magdalena Necpalova, Marijn Van de Broek, Marc Corbeels, Samuel Mathu Ndungu, Monicah Wanjiku Mucheru-Muna, Daniel Mugendi, Rebecca Yegon, Wycliffe Waswa, Bernard Vanlauwe, and Johan Six
Biogeosciences, 21, 3691–3716, https://doi.org/10.5194/bg-21-3691-2024, https://doi.org/10.5194/bg-21-3691-2024, 2024
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We used the DayCent model to assess the potential impact of integrated soil fertility management (ISFM) on maize production, soil fertility, and greenhouse gas emission in Kenya. After adjustments, DayCent represented measured mean yields and soil carbon stock changes well and N2O emissions acceptably. Our results showed that soil fertility losses could be reduced but not completely eliminated with ISFM and that, while N2O emissions increased with ISFM, emissions per kilogram yield decreased.
Hazel Cathcart, Julian Aherne, Michael D. Moran, Verica Savic-Jovcic, Paul A. Makar, and Amanda Cole
EGUsphere, https://doi.org/10.5194/egusphere-2024-2371, https://doi.org/10.5194/egusphere-2024-2371, 2024
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Deposition from sulfur and nitrogen pollution can harm ecosystems, and recovery from this type of pollution can take decades or longer. To identify risk to Canadian soils, we created maps showing sensitivity to sulfur and nitrogen pollution. Results show that some ecosystems are at risk from acid and nutrient nitrogen deposition; 10 % of protected areas are receiving acid deposition beyond their damage threshold and 70 % may be receiving nitrogen deposition that could cause biodiversity loss.
Erik Schwarz, Samia Ghersheen, Salim Belyazid, and Stefano Manzoni
Biogeosciences, 21, 3441–3461, https://doi.org/10.5194/bg-21-3441-2024, https://doi.org/10.5194/bg-21-3441-2024, 2024
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The occurrence of unstable equilibrium points (EPs) could impede the applicability of microbial-explicit soil organic carbon models. For archetypal model versions we identify when instability can occur and describe mathematical conditions to avoid such unstable EPs. We discuss implications for further model development, highlighting the important role of considering basic ecological principles to ensure biologically meaningful models.
Sian Kou-Giesbrecht, Vivek K. Arora, Christian Seiler, and Libo Wang
Biogeosciences, 21, 3339–3371, https://doi.org/10.5194/bg-21-3339-2024, https://doi.org/10.5194/bg-21-3339-2024, 2024
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Terrestrial biosphere models can either prescribe the geographical distribution of biomes or simulate them dynamically, capturing climate-change-driven biome shifts. We isolate and examine the differences between these different land cover implementations. We find that the simulated terrestrial carbon sink at the end of the 21st century is twice as large in simulations with dynamic land cover than in simulations with prescribed land cover due to important range shifts in the Arctic and Amazon.
Elizabeth S. Duan, Luciana Chavez Rodriguez, Nicole Hemming-Schroeder, Baptiste Wijas, Habacuc Flores-Moreno, Alexander W. Cheesman, Lucas A. Cernusak, Michael J. Liddell, Paul Eggleton, Amy E. Zanne, and Steven D. Allison
Biogeosciences, 21, 3321–3338, https://doi.org/10.5194/bg-21-3321-2024, https://doi.org/10.5194/bg-21-3321-2024, 2024
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Understanding the link between climate and carbon fluxes is crucial for predicting how climate change will impact carbon sinks. We estimated carbon dioxide (CO2) fluxes from deadwood in tropical Australia using wood moisture content and temperature. Our model predicted that the majority of deadwood carbon is released as CO2, except when termite activity is detected. Future models should also incorporate wood traits, like species and chemical composition, to better predict fluxes.
Daniel Nadal-Sala, Rüdiger Grote, David Kraus, Uri Hochberg, Tamir Klein, Yael Wagner, Fedor Tatarinov, Dan Yakir, and Nadine K. Ruehr
Biogeosciences, 21, 2973–2994, https://doi.org/10.5194/bg-21-2973-2024, https://doi.org/10.5194/bg-21-2973-2024, 2024
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A hydraulic model approach is presented that can be added to any physiologically based ecosystem model. Simulated plant water potential triggers stomatal closure, photosynthesis decline, root–soil resistance increases, and sapwood and foliage senescence. The model has been evaluated at an extremely dry site stocked with Aleppo pine and was able to represent gas exchange, soil water content, and plant water potential. The model also responded realistically regarding leaf senescence.
Patrick Neri, Lianhong Gu, and Yang Song
Biogeosciences, 21, 2731–2758, https://doi.org/10.5194/bg-21-2731-2024, https://doi.org/10.5194/bg-21-2731-2024, 2024
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A first-of-its-kind global-scale model of temperature resilience and tolerance of photosystem II maximum quantum yield informs how plants maintain their efficiency of converting light energy to chemical energy for photosynthesis under temperature changes. Our finding explores this variation across plant functional types and habitat climatology, highlighting diverse temperature response strategies and a method to improve global-scale photosynthesis modeling under climate change.
Liyuan He, Jorge L. Mazza Rodrigues, Melanie A. Mayes, Chun-Ta Lai, David A. Lipson, and Xiaofeng Xu
Biogeosciences, 21, 2313–2333, https://doi.org/10.5194/bg-21-2313-2024, https://doi.org/10.5194/bg-21-2313-2024, 2024
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Soil microbes are the driving engine for biogeochemical cycles of carbon and nutrients. This study applies a microbial-explicit model to quantify bacteria and fungal biomass carbon in soils from 1901 to 2016. Results showed substantial increases in bacterial and fungal biomass carbon over the past century, jointly influenced by vegetation growth and soil temperature and moisture. This pioneering century-long estimation offers crucial insights into soil microbial roles in global carbon cycling.
Tao Chen, Félicien Meunier, Marc Peaucelle, Guoping Tang, Ye Yuan, and Hans Verbeeck
Biogeosciences, 21, 2253–2272, https://doi.org/10.5194/bg-21-2253-2024, https://doi.org/10.5194/bg-21-2253-2024, 2024
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Chinese subtropical forest ecosystems are an extremely important component of global forest ecosystems and hence crucial for the global carbon cycle and regional climate change. However, there is still great uncertainty in the relationship between subtropical forest carbon sequestration and its drivers. We provide first quantitative estimates of the individual and interactive effects of different drivers on the gross primary productivity changes of various subtropical forest types in China.
Ke Liu, Yujie Wang, Troy S. Magney, and Christian Frankenberg
Biogeosciences, 21, 1501–1516, https://doi.org/10.5194/bg-21-1501-2024, https://doi.org/10.5194/bg-21-1501-2024, 2024
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Stomata are pores on leaves that regulate gas exchange between plants and the atmosphere. Existing land models unrealistically assume stomata can jump between steady states when the environment changes. We implemented dynamic modeling to predict gradual stomatal responses at different scales. Results suggested that considering this effect on plant behavior patterns in diurnal cycles was important. Our framework also simplified simulations and can contribute to further efficiency improvements.
Melanie A. Thurner, Silvia Caldararu, Jan Engel, Anja Rammig, and Sönke Zaehle
Biogeosciences, 21, 1391–1410, https://doi.org/10.5194/bg-21-1391-2024, https://doi.org/10.5194/bg-21-1391-2024, 2024
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Due to their crucial role in terrestrial ecosystems, we implemented mycorrhizal fungi into the QUINCY terrestrial biosphere model. Fungi interact with mineral and organic soil to support plant N uptake and, thus, plant growth. Our results suggest that the effect of mycorrhizal interactions on simulated ecosystem dynamics is minor under constant environmental conditions but necessary to reproduce and understand observed patterns under changing conditions, such as rising atmospheric CO2.
Jinyun Tang and William J. Riley
Biogeosciences, 21, 1061–1070, https://doi.org/10.5194/bg-21-1061-2024, https://doi.org/10.5194/bg-21-1061-2024, 2024
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A chemical kinetics theory is proposed to explain the non-monotonic relationship between temperature and biochemical rates. It incorporates the observed thermally reversible enzyme denaturation that is ensured by the ceaseless thermal motion of molecules and ions in an enzyme solution and three well-established theories: (1) law of mass action, (2) diffusion-limited chemical reaction theory, and (3) transition state theory.
Nina Raoult, Louis-Axel Edouard-Rambaut, Nicolas Vuichard, Vladislav Bastrikov, Anne Sofie Lansø, Bertrand Guenet, and Philippe Peylin
Biogeosciences, 21, 1017–1036, https://doi.org/10.5194/bg-21-1017-2024, https://doi.org/10.5194/bg-21-1017-2024, 2024
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Observations are used to reduce uncertainty in land surface models (LSMs) by optimising poorly constraining parameters. However, optimising against current conditions does not necessarily ensure that the parameters treated as invariant will be robust in a changing climate. Manipulation experiments offer us a unique chance to optimise our models under different (here atmospheric CO2) conditions. By using these data in optimisations, we gain confidence in the future projections of LSMs.
Kelsey T. Foster, Wu Sun, Yoichi P. Shiga, Jiafu Mao, and Anna M. Michalak
Biogeosciences, 21, 869–891, https://doi.org/10.5194/bg-21-869-2024, https://doi.org/10.5194/bg-21-869-2024, 2024
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Assessing agreement between bottom-up and top-down methods across spatial scales can provide insights into the relationship between ensemble spread (difference across models) and model accuracy (difference between model estimates and reality). We find that ensemble spread is unlikely to be a good indicator of actual uncertainty in the North American carbon balance. However, models that are consistent with atmospheric constraints show stronger agreement between top-down and bottom-up estimates.
Victoria R. Dutch, Nick Rutter, Leanne Wake, Oliver Sonnentag, Gabriel Hould Gosselin, Melody Sandells, Chris Derksen, Branden Walker, Gesa Meyer, Richard Essery, Richard Kelly, Phillip Marsh, Julia Boike, and Matteo Detto
Biogeosciences, 21, 825–841, https://doi.org/10.5194/bg-21-825-2024, https://doi.org/10.5194/bg-21-825-2024, 2024
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We undertake a sensitivity study of three different parameters on the simulation of net ecosystem exchange (NEE) during the snow-covered non-growing season at an Arctic tundra site. Simulations are compared to eddy covariance measurements, with near-zero NEE simulated despite observed CO2 release. We then consider how to parameterise the model better in Arctic tundra environments on both sub-seasonal timescales and cumulatively throughout the snow-covered non-growing season.
Bertrand Guenet, Jérémie Orliac, Lauric Cécillon, Olivier Torres, Laura Sereni, Philip A. Martin, Pierre Barré, and Laurent Bopp
Biogeosciences, 21, 657–669, https://doi.org/10.5194/bg-21-657-2024, https://doi.org/10.5194/bg-21-657-2024, 2024
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Heterotrophic respiration fluxes are a major flux between surfaces and the atmosphere, but Earth system models do not yet represent them correctly. Here we benchmarked Earth system models against observation-based products, and we identified the important mechanisms that need to be improved in the next-generation Earth system models.
Shuyue Li, Bonnie Waring, Jennifer Powers, and David Medvigy
Biogeosciences, 21, 455–471, https://doi.org/10.5194/bg-21-455-2024, https://doi.org/10.5194/bg-21-455-2024, 2024
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We used an ecosystem model to simulate primary production of a tropical forest subjected to 3 years of nutrient fertilization. Simulations parameterized such that relative allocation to fine roots increased with increasing soil phosphorus had leaf, wood, and fine root production consistent with observations. However, these simulations seemed to over-allocate to fine roots on multidecadal timescales, affecting aboveground biomass. Additional observations across timescales would benefit models.
Stephen Björn Wirth, Arne Poyda, Friedhelm Taube, Britta Tietjen, Christoph Müller, Kirsten Thonicke, Anja Linstädter, Kai Behn, Sibyll Schaphoff, Werner von Bloh, and Susanne Rolinski
Biogeosciences, 21, 381–410, https://doi.org/10.5194/bg-21-381-2024, https://doi.org/10.5194/bg-21-381-2024, 2024
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In dynamic global vegetation models (DGVMs), the role of functional diversity in forage supply and soil organic carbon storage of grasslands is not explicitly taken into account. We introduced functional diversity into the Lund Potsdam Jena managed Land (LPJmL) DGVM using CSR theory. The new model reproduced well-known trade-offs between plant traits and can be used to quantify the role of functional diversity in climate change mitigation using different functional diversity scenarios.
Joe R. McNorton and Francesca Di Giuseppe
Biogeosciences, 21, 279–300, https://doi.org/10.5194/bg-21-279-2024, https://doi.org/10.5194/bg-21-279-2024, 2024
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Wildfires have wide-ranging consequences for local communities, air quality and ecosystems. Vegetation amount and moisture state are key components to forecast wildfires. We developed a combined model and satellite framework to characterise vegetation, including the type of fuel, whether it is alive or dead, and its moisture content. The daily data is at high resolution globally (~9 km). Our characteristics correlate with active fire data and can inform fire danger and spread modelling efforts.
Brooke A. Eastman, William R. Wieder, Melannie D. Hartman, Edward R. Brzostek, and William T. Peterjohn
Biogeosciences, 21, 201–221, https://doi.org/10.5194/bg-21-201-2024, https://doi.org/10.5194/bg-21-201-2024, 2024
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We compared soil model performance to data from a long-term nitrogen addition experiment in a forested ecosystem. We found that in order for soil carbon models to accurately predict future forest carbon sequestration, two key processes must respond dynamically to nitrogen availability: (1) plant allocation of carbon to wood versus roots and (2) rates of soil organic matter decomposition. Long-term experiments can help improve our predictions of the land carbon sink and its climate impact.
Jan De Pue, Sebastian Wieneke, Ana Bastos, José Miguel Barrios, Liyang Liu, Philippe Ciais, Alirio Arboleda, Rafiq Hamdi, Maral Maleki, Fabienne Maignan, Françoise Gellens-Meulenberghs, Ivan Janssens, and Manuela Balzarolo
Biogeosciences, 20, 4795–4818, https://doi.org/10.5194/bg-20-4795-2023, https://doi.org/10.5194/bg-20-4795-2023, 2023
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The gross primary production (GPP) of the terrestrial biosphere is a key source of variability in the global carbon cycle. To estimate this flux, models can rely on remote sensing data (RS-driven), meteorological data (meteo-driven) or a combination of both (hybrid). An intercomparison of 11 models demonstrated that RS-driven models lack the sensitivity to short-term anomalies. Conversely, the simulation of soil moisture dynamics and stress response remains a challenge in meteo-driven models.
Chad A. Burton, Luigi J. Renzullo, Sami W. Rifai, and Albert I. J. M. Van Dijk
Biogeosciences, 20, 4109–4134, https://doi.org/10.5194/bg-20-4109-2023, https://doi.org/10.5194/bg-20-4109-2023, 2023
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Australia's land-based ecosystems play a critical role in controlling the variability in the global land carbon sink. However, uncertainties in the methods used for quantifying carbon fluxes limit our understanding. We develop high-resolution estimates of Australia's land carbon fluxes using machine learning methods and find that Australia is, on average, a stronger carbon sink than previously thought and that the seasonal dynamics of the fluxes differ from those described by other methods.
Yuan Yan, Anne Klosterhalfen, Fernando Moyano, Matthias Cuntz, Andrew C. Manning, and Alexander Knohl
Biogeosciences, 20, 4087–4107, https://doi.org/10.5194/bg-20-4087-2023, https://doi.org/10.5194/bg-20-4087-2023, 2023
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A better understanding of O2 fluxes, their exchange ratios with CO2 and their interrelations with environmental conditions would provide further insights into biogeochemical ecosystem processes. We, therefore, used the multilayer canopy model CANVEG to simulate and analyze the flux exchange for our forest study site for 2012–2016. Based on these simulations, we further successfully tested the application of various micrometeorological methods and the prospects of real O2 flux measurements.
Jie Zhang, Elisabeth Larsen Kolstad, Wenxin Zhang, Iris Vogeler, and Søren O. Petersen
Biogeosciences, 20, 3895–3917, https://doi.org/10.5194/bg-20-3895-2023, https://doi.org/10.5194/bg-20-3895-2023, 2023
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Manure application to agricultural land often results in large and variable N2O emissions. We propose a model with a parsimonious structure to investigate N transformations around such N2O hotspots. The model allows for new detailed insights into the interactions between transport and microbial activities regarding N2O emissions in heterogeneous soil environments. It highlights the importance of solute diffusion to N2O emissions from such hotspots which are often ignored by process-based models.
Jukka Alm, Antti Wall, Jukka-Pekka Myllykangas, Paavo Ojanen, Juha Heikkinen, Helena M. Henttonen, Raija Laiho, Kari Minkkinen, Tarja Tuomainen, and Juha Mikola
Biogeosciences, 20, 3827–3855, https://doi.org/10.5194/bg-20-3827-2023, https://doi.org/10.5194/bg-20-3827-2023, 2023
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In Finland peatlands cover one-third of land area. For half of those, with 4.3 Mha being drained for forestry, Finland reports sinks and sources of greenhouse gases in forest lands on organic soils following its UNFCCC commitment. We describe a new method for compiling soil CO2 balance that follows changes in tree volume, tree harvests and temperature. An increasing trend of emissions from 1.4 to 7.9 Mt CO2 was calculated for drained peatland forest soils in Finland for 1990–2021.
Siqi Li, Bo Zhu, Xunhua Zheng, Pengcheng Hu, Shenghui Han, Jihui Fan, Tao Wang, Rui Wang, Kai Wang, Zhisheng Yao, Chunyan Liu, Wei Zhang, and Yong Li
Biogeosciences, 20, 3555–3572, https://doi.org/10.5194/bg-20-3555-2023, https://doi.org/10.5194/bg-20-3555-2023, 2023
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Physical soil erosion and particulate carbon, nitrogen and phosphorus loss modules were incorporated into the process-oriented hydro-biogeochemical model CNMM-DNDC to realize the accurate simulation of water-induced erosion and subsequent particulate nutrient losses at high spatiotemporal resolution.
Ivan Cornut, Nicolas Delpierre, Jean-Paul Laclau, Joannès Guillemot, Yann Nouvellon, Otavio Campoe, Jose Luiz Stape, Vitoria Fernanda Santos, and Guerric le Maire
Biogeosciences, 20, 3093–3117, https://doi.org/10.5194/bg-20-3093-2023, https://doi.org/10.5194/bg-20-3093-2023, 2023
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Potassium is an essential element for living organisms. Trees are dependent upon this element for certain functions that allow them to build their trunks using carbon dioxide. Using data from experiments in eucalypt plantations in Brazil and a simplified computer model of the plantations, we were able to investigate the effect that a lack of potassium can have on the production of wood. Understanding nutrient cycles is useful to understand the response of forests to environmental change.
Ivan Cornut, Guerric le Maire, Jean-Paul Laclau, Joannès Guillemot, Yann Nouvellon, and Nicolas Delpierre
Biogeosciences, 20, 3119–3135, https://doi.org/10.5194/bg-20-3119-2023, https://doi.org/10.5194/bg-20-3119-2023, 2023
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After simulating the effects of low levels of potassium on the canopy of trees and the uptake of carbon dioxide from the atmosphere by leaves in Part 1, here we tried to simulate the way the trees use the carbon they have acquired and the interaction with the potassium cycle in the tree. We show that the effect of low potassium on the efficiency of the trees in acquiring carbon is enough to explain why they produce less wood when they are in soils with low levels of potassium.
Xiaojuan Yang, Peter Thornton, Daniel Ricciuto, Yilong Wang, and Forrest Hoffman
Biogeosciences, 20, 2813–2836, https://doi.org/10.5194/bg-20-2813-2023, https://doi.org/10.5194/bg-20-2813-2023, 2023
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We evaluated the performance of a land surface model (ELMv1-CNP) that includes both nitrogen (N) and phosphorus (P) limitation on carbon cycle processes. We show that ELMv1-CNP produces realistic estimates of present-day carbon pools and fluxes. We show that global C sources and sinks are significantly affected by P limitation. Our study suggests that introduction of P limitation in land surface models is likely to have substantial consequences for projections of future carbon uptake.
Kevin R. Wilcox, Scott L. Collins, Alan K. Knapp, William Pockman, Zheng Shi, Melinda D. Smith, and Yiqi Luo
Biogeosciences, 20, 2707–2725, https://doi.org/10.5194/bg-20-2707-2023, https://doi.org/10.5194/bg-20-2707-2023, 2023
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The capacity for carbon storage (C capacity) is an attribute that determines how ecosystems store carbon in the future. Here, we employ novel data–model integration techniques to identify the carbon capacity of six grassland sites spanning the US Great Plains. Hot and dry sites had low C capacity due to less plant growth and high turnover of soil C, so they may be a C source in the future. Alternately, cooler and wetter ecosystems had high C capacity, so these systems may be a future C sink.
Ara Cho, Linda M. J. Kooijmans, Kukka-Maaria Kohonen, Richard Wehr, and Maarten C. Krol
Biogeosciences, 20, 2573–2594, https://doi.org/10.5194/bg-20-2573-2023, https://doi.org/10.5194/bg-20-2573-2023, 2023
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Carbonyl sulfide (COS) is a useful constraint for estimating photosynthesis. To simulate COS leaf flux better in the SiB4 model, we propose a novel temperature function for enzyme carbonic anhydrase (CA) activity and optimize conductances using observations. The optimal activity of CA occurs below 40 °C, and Ball–Woodrow–Berry parameters are slightly changed. These reduce/increase uptakes in the tropics/higher latitudes and contribute to resolving discrepancies in the COS global budget.
Yunyao Ma, Bettina Weber, Alexandra Kratz, José Raggio, Claudia Colesie, Maik Veste, Maaike Y. Bader, and Philipp Porada
Biogeosciences, 20, 2553–2572, https://doi.org/10.5194/bg-20-2553-2023, https://doi.org/10.5194/bg-20-2553-2023, 2023
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We found that the modelled annual carbon balance of biocrusts is strongly affected by both the environment (mostly air temperature and CO2 concentration) and physiology, such as temperature response of respiration. However, the relative impacts of these drivers vary across regions with different climates. Uncertainty in driving factors may lead to unrealistic carbon balance estimates, particularly in temperate climates, and may be explained by seasonal variation of physiology due to acclimation.
Alexander J. Norton, A. Anthony Bloom, Nicholas C. Parazoo, Paul A. Levine, Shuang Ma, Renato K. Braghiere, and T. Luke Smallman
Biogeosciences, 20, 2455–2484, https://doi.org/10.5194/bg-20-2455-2023, https://doi.org/10.5194/bg-20-2455-2023, 2023
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This study explores how the representation of leaf phenology affects our ability to predict changes to the carbon balance of land ecosystems. We calibrate a new leaf phenology model against a diverse range of observations at six forest sites, showing that it improves the predictive capability of the processes underlying the ecosystem carbon balance. We then show how changes in temperature and rainfall affect the ecosystem carbon balance with this new model.
Libo Wang, Vivek K. Arora, Paul Bartlett, Ed Chan, and Salvatore R. Curasi
Biogeosciences, 20, 2265–2282, https://doi.org/10.5194/bg-20-2265-2023, https://doi.org/10.5194/bg-20-2265-2023, 2023
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Plant functional types (PFTs) are groups of plant species used to represent vegetation distribution in land surface models. There are large uncertainties associated with existing methods for mapping land cover datasets to PFTs. This study demonstrates how fine-resolution tree cover fraction and land cover datasets can be used to inform the PFT mapping process and reduce the uncertainties. The proposed largely objective method makes it easier to implement new land cover products in models.
Jennifer A. Holm, David M. Medvigy, Benjamin Smith, Jeffrey S. Dukes, Claus Beier, Mikhail Mishurov, Xiangtao Xu, Jeremy W. Lichstein, Craig D. Allen, Klaus S. Larsen, Yiqi Luo, Cari Ficken, William T. Pockman, William R. L. Anderegg, and Anja Rammig
Biogeosciences, 20, 2117–2142, https://doi.org/10.5194/bg-20-2117-2023, https://doi.org/10.5194/bg-20-2117-2023, 2023
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Unprecedented climate extremes (UCEs) are expected to have dramatic impacts on ecosystems. We present a road map of how dynamic vegetation models can explore extreme drought and climate change and assess ecological processes to measure and reduce model uncertainties. The models predict strong nonlinear responses to UCEs. Due to different model representations, the models differ in magnitude and trajectory of forest loss. Therefore, we explore specific plant responses that reflect knowledge gaps.
Veronika Kronnäs, Klas Lucander, Giuliana Zanchi, Nadja Stadlinger, Salim Belyazid, and Cecilia Akselsson
Biogeosciences, 20, 1879–1899, https://doi.org/10.5194/bg-20-1879-2023, https://doi.org/10.5194/bg-20-1879-2023, 2023
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In a future climate, extreme droughts might become more common. Climate change and droughts can have negative effects on soil weathering and plant health.
In this study, climate change effects on weathering were studied on sites in Sweden using the model ForSAFE, a climate change scenario and an extreme drought scenario. The modelling shows that weathering is higher during summer and increases with global warming but that weathering during drought summers can become as low as winter weathering.
Agustín Sarquis and Carlos A. Sierra
Biogeosciences, 20, 1759–1771, https://doi.org/10.5194/bg-20-1759-2023, https://doi.org/10.5194/bg-20-1759-2023, 2023
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Although plant litter is chemically and physically heterogenous and undergoes multiple transformations, models that represent litter dynamics often ignore this complexity. We used a multi-model inference framework to include information content in litter decomposition datasets and studied the time it takes for litter to decompose as measured by the transit time. In arid lands, the median transit time of litter is about 3 years and has a negative correlation with mean annual temperature.
Qi Guan, Jing Tang, Lian Feng, Stefan Olin, and Guy Schurgers
Biogeosciences, 20, 1635–1648, https://doi.org/10.5194/bg-20-1635-2023, https://doi.org/10.5194/bg-20-1635-2023, 2023
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Understanding terrestrial sources of nitrogen is vital to examine lake eutrophication changes. Combining process-based ecosystem modeling and satellite observations, we found that land-leached nitrogen in the Yangtze Plain significantly increased from 1979 to 2018, and terrestrial nutrient sources were positively correlated with eutrophication trends observed in most lakes, demonstrating the necessity of sustainable nitrogen management to control eutrophication.
Vivek K. Arora, Christian Seiler, Libo Wang, and Sian Kou-Giesbrecht
Biogeosciences, 20, 1313–1355, https://doi.org/10.5194/bg-20-1313-2023, https://doi.org/10.5194/bg-20-1313-2023, 2023
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The behaviour of natural systems is now very often represented through mathematical models. These models represent our understanding of how nature works. Of course, nature does not care about our understanding. Since our understanding is not perfect, evaluating models is challenging, and there are uncertainties. This paper illustrates this uncertainty for land models and argues that evaluating models in light of the uncertainty in various components provides useful information.
Benjamin S. Felzer
Biogeosciences, 20, 573–587, https://doi.org/10.5194/bg-20-573-2023, https://doi.org/10.5194/bg-20-573-2023, 2023
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The future of the terrestrial carbon sink depends upon the legacy of past land use, which determines the stand age of the forest and nutrient levels in the soil, both of which affect vegetation growth. This study uses a modeling approach to determine the effects of land-use legacy in the conterminous US from 1750 to 2099. Not accounting for land legacy results in a low carbon sink and high biomass, while water variables are not as highly affected.
Cited articles
Amthor, J. S., Bar-Even, A., Hanson, A. D., Millar, A. H., Stitt, M., Sweetlove, L. J., and Tyerman, S. D.: Engineering strategies to boost crop productivity by cutting respiratory carbon loss, Plant Cell, 31, 297–314, https://doi.org/10.1105/tpc.18.00743, 2019.
Betzelberger, A. M., Gillespie, K. M., McGrath, J. M., Koester, R. P., Nelson, R. L., and Ainsworth, E. A.: Ozone exposure response for U.S. soybean cultivars: Linear reductions in photosynthetic potential, biomass, and yield, Plant Physiology, American Society of Plant Biologists, 160, 1827–1839, https://doi.org/10.1104/pp.112.205591, 2012.
Beven, K.: A manifesto for the equifinality thesis, J. Hydrol., 320, 18–36, https://doi.org/10.1016/j.jhydrol.2005.07.007, 2006.
Biswas, D. K., Xu, H., Li, Y. G., Sun, J. Z., Wang, X. Z., Han, X. G., and Jiang, G. M.: Assessing the genetic relatedness of higher ozone sensitivity of modern wheat to its wild and cultivated progenitors/relatives, J. Exp. Bot., 59, 951–963, https://doi.org/10.1093/jxb/ern022, 2008.
Bland, S.: SEI-DO3SE/pyDO3SE-open: V4.39.11 (v4.39.11), Zenodo [code], https://doi.org/10.5281/zenodo.11620482, 2024.
Brewster, C., Fenner, N., and Hayes, F.: Chronic ozone exposure affects nitrogen remobilization in wheat at key growth stages, Sci. Total Environ., 908, 168288, https://doi.org/10.1016/j.scitotenv.2023.168288, 2024.
Büker, P., Morrissey, T., Briolat, A., Falk, R., Simpson, D., Tuovinen, J.-P., Alonso, R., Barth, S., Baumgarten, M., Grulke, N., Karlsson, P. E., King, J., Lagergren, F., Matyssek, R., Nunn, A., Ogaya, R., Peñuelas, J., Rhea, L., Schaub, M., Uddling, J., Werner, W., and Emberson, L. D.: DO3SE modelling of soil moisture to determine ozone flux to forest trees, Atmos. Chem. Phys., 12, 5537–5562, https://doi.org/10.5194/acp-12-5537-2012, 2012.
Campbell, G. S. and Norman, J. M.: An introduction to Environmental Biophysics, Second Edition, Springer, New York, 286 pp., https://doi.org/10.1007/978-1-4612-1626-1, 1998.
Clark, D. B., Mercado, L. M., Sitch, S., Jones, C. D., Gedney, N., Best, M. J., Pryor, M., Rooney, G. G., Essery, R. L. H., Blyth, E., Boucher, O., Harding, R. J., Huntingford, C., and Cox, P. M.: The Joint UK Land Environment Simulator (JULES), model description – Part 2: Carbon fluxes and vegetation dynamics, Geosci. Model Dev., 4, 701–722, https://doi.org/10.5194/gmd-4-701-2011, 2011.
Conibear, L., Butt, E. W., Knote, C., Spracklen, D. V., and Arnold, S. R.: Current and Future Disease Burden From Ambient Ozone Exposure in India, GeoHealth, 2, 334–355, https://doi.org/10.1029/2018GH000168, 2018.
Danielsson, H., Karlsson, G. P., Karlsson, P. E., and Pleijel, H. H.: Ozone uptake modelling and flux-response relationships–an assessment of ozone-induced yield loss in spring wheat, Atmos. Environ., 37, 475–485, https://doi.org/10.1016/S1352-2310(02)00924-X, 2003.
de Pury, D. G. G. and Farquhar, G. D.: Simple Scaling of Photosynthesis from Leaves to Canopies Without the Errors of Big-Leaf Models, Funct. Plant Biol., 24, 537–557, https://doi.org/10.1111/j.1365-3040.1997.00094.x, 1997.
Droutsas, I., Challinor, A. J., Arnold, S. R., Mikkelsen, T. N., and Hansen, E. M. Ø.: A new model of ozone stress in wheat including grain yield loss and plant acclimation to the pollutant, Eur. J. Agron., 120, 126125, https://doi.org/10.1016/j.eja.2020.126125, 2020.
Emberson, L. D., Ashmore, M. R., Cambridge, H. M., Simpson, D., and Tuovinen, J.-P.: Modelling stomatal ozone flux across Europe, Environ. Pollut., 109, 403–413, https://doi.org/10.1016/S0269-7491(00)00043-9, 2000.
Emberson, L. D., Ashmore, M. R., Simpson, D., Tuovinen, J.-P., and Cambridge, H. M.: Modelling and mapping ozone deposition in Europe, Water Air Soil Poll., 577–582, 2001.
Emberson, L. D., Pleijel, H., Ainsworth, E. A., van den Berg, M., Ren, W., Osborne, S., Mills, G., Pandey, D., Dentener, F., Büker, 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.
Ewert, F. and Porter, J. R.: Ozone effects on wheat in relation to CO2: Modelling short-term and long-term responses of leaf photosynthesis and leaf duration, Glob. Change Biol., 6, 735–750, https://doi.org/10.1046/j.1365-2486.2000.00351.x, 2000.
Farage, P. K., Long, S. P., Lechner, E. G., and Baker, N. R.: The sequence of change within the photosynthetic apparatus of wheat following short-term exposure to ozone, Plant Physiol., 95, 529–535, https://doi.org/10.1104/pp.95.2.529, 1991.
Farquhar, G. D., von Caemmerer, S., and Berry, J. A.: A biochemical model of photosynthetic CO2 assimilation in leaves of C3 species, Planta, 149, 78–90, https://doi.org/10.1007/BF00386231, 1980.
Feng, Y., Nguyen, T. H., Alam, M. S., Emberson, L., Gaiser, T., Ewert, F., and Frei, M: Identifying and modelling key physiological traits that confer tolerance or sensitivity to ozone in winter wheat, Environmental Pollution, Elsevier Ltd, 304, 119251, https://doi.org/10.1016/j.envpol.2022.119251, 2022.
Feng, Y., Alam, M. S., Yan, F., and Frei, M.: Alteration of carbon and nitrogen allocation in winter wheat under elevated ozone, Plant Sci., 338, 111924, https://doi.org/10.1016/j.plantsci.2023.111924, 2024.
Feng, Z., Kobayashi, K., and Ainsworth, E. A.: Impact of elevated ozone concentration on growth, physiology, and yield of wheat (Triticum aestivum L.): a meta-analysis, Glob. Change Biol., 14, 2696–2708, https://doi.org/10.1111/j.1365-2486.2008.01673.x, 2008.
Feng, Z., Pang, J., Kobayashi, K., Zhu, J., and Otr, R. D.: Differential responses in two varieties of winter wheat to elevated ozone concentration under fully open-air field conditions, Glob. Change Biol., 17, 580–591, https://doi.org/10.1111/j.1365-2486.2010.02184.x, 2011.
Feng, Z., Tang, H., Uddling, J., Pleijel, H., Kobayashi, K., Zhu, J., Oue, H., and Guo, W.: A stomatal ozone flux-response relationship to assess ozone-induced yield loss of winter wheat in subtropical China, Environ. Pollut., 164, 16–23, https://doi.org/10.1016/j.envpol.2012.01.014, 2012.
Feng, Z., Wang, L., Pleijel, H., Zhu, J., and Kobayashi, K.: Differential effects of ozone on photosynthesis of winter wheat among cultivars depend on antioxidative enzymes rather than stomatal conductance, Sci. Total Environ., 572, 404–411, https://doi.org/10.1016/j.scitotenv.2016.08.083, 2016.
Feng, Z., Uddling, J., Tang, H., Zhu, J., and Kobayashi, K.: Comparison of crop yield sensitivity to ozone between open-top chamber and free-air experiments, Glob. Change Biol., 24, 2231–2238, https://doi.org/10.1111/gcb.14077, 2018.
Feng, Z., Agathokleous, E., Yue, X., Oksanen, E., Paoletti, E., Sase, H., Gandin, A., Koike, T., Calatayud, V., Yuan, X., Liu, X., De Marco, A., Jolivet, Y., Kontunen-Soppela, S., Hoshika, Y., Saji, H., Li, P., Li, Z., Watanabe, M., and Kobayashi, K.: Emerging challenges of ozone impacts on Asian plants: Actions are needed to protect ecosystem health, Ecosystem Health and Sustainability, 7, 1911602. https://doi.org/10.1080/20964129.2021.1911602, 2021.
Feng, Z., Xu, Y., Kobayashi, K., Dai, L., Zhang, T., 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, 47–56, https://doi.org/10.1038/s43016-021-00422-6, 2022.
Gelang, J., Pleijel, H., Sild, E., Danielsson, H., Younis, S., Selldén, G., and Wallin, G.: Rate and duration of grain filling in relation to flag leaf senescence and grain yield in spring wheat (Triticum aestivum) exposed to different concentrations of ozone, Physiol. Plantarum, 110, 366–375, https://doi.org/10.1111/j.1399-3054.2000.1100311.x, 2000.
Grandjean, A. and Fuhrer, J.: Growth and leaf senescence in spring wheat (Triticum aestivum) grown at different ozone concentrations in open-top field chambers, Environ. Pollut., 59, 299–314, 1989.
Guan, X., Song, L., Wang, T. C., Turner, N., and Li, F.: Effect of Drought on the Gas Exchange, Chlorophyll Fluorescence and Yield of Six Different-Era Spring Wheat Cultivars, J. Agron. Crop Sci., 201, 253–266, https://doi.org/10.1111/jac.12103, 2015.
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.2019.03.001, 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.: Modeling the effects of tropospheric ozone on the growth and yield of global staple crops with DSSAT v4.8.0, Geosci. Model Dev., 17, 2547–2567, https://doi.org/10.5194/gmd-17-2547-2024, 2024.
Herman, J. and Usher, W.: SALib: An open-source Python library for sensitivity analysis, J. Open Source Softw., 2, 97, https://doi.org/10.21105/joss.00097, 2017.
Huang, H., Huang, J., Li, X., Feng, J., Zhuo, W., Wu, Y., Niu, Q., Su, W., and Yin, Y.: A dataset of winter wheat aboveground biomass in China during 2007–2015 based on data assimilation, Scientific Data, Springer US, 9, 1–11, https://doi.org/10.1038/s41597-022-01305-6, 2022.
Hussain, A. and Bangash, R.: Impact of Climate Change on Crops' Productivity across Selected Agro-ecological Zones in Pakistan, The Pakistan Development Review, 56, 163–187, https://www.jstor.org/stable/26875191, 2017.
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, Cambridge University Press, https://doi.org/10.1017/9781009157896, 2021.
Iwanaga, T., Usher, W., and Herman, J.: Toward SALib 2.0: Advancing the accessibility and interpretability of global sensitivity analyses, Socio-Environ. Syst. Model., 4, 18155, https://doi.org/10.18174/sesmo.18155, 2022.
Jaggi, M., Ammann, C., Neftel, J., and Fuhrer, J.: Environmental control of profiles of ozone concentration in a grassland canopy, Atmos. Environ., 40, 5496–5507, https://doi.org/10.1016/j.atmosenv.2006.01.025, 2006.
Jones, H. G.: Plants and microclimate: A quantitative approach to environmental plant physiology, Cambridge University Press, ISBN 0521425247, 1992.
Kohut, R. J., Amundson, R. G., Laurence, J. A., Colavito, L., van Leuken, P., and King, P.: Effects of Ozone and Sulfur Dioxide on Yield of Winter Wheat, Phytopathology, 77, 71–74, https://doi.org/10.1094/Phyto-77-71, 1987.
Kutman, U. B., Yildiz, B., and Cakmak, I.: Effect of nitrogen on uptake, remobilization and partitioning of zinc and iron throughout the development of durum wheat, Plant Soil, 342, 149–164, https://doi.org/10.1007/s11104-010-0679-5, 2011.
Lee, J. D., Drysdale, W. S., Finch, D. P., Wilde, S. E., and Palmer, P. I.: UK surface NO2 levels dropped by 42
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.
Leuning, R.: Modeling stomatal behavior and photosynthesis of Eucalyptus grandis, Aust. J. Plant Physiol., 17, 159–175, 1990.
Leuning, R.: A critical appraisal of combined stomatal models for C3 plants, Plant, Cell Environ., 18, 339–355, 1995.
Li, A., Zhou, Q., and Xu, Q.: Prospects for ozone pollution control in China: An epidemiological perspective, Environ. Pollut., 285, 117670, https://doi.org/10.1016/j.envpol.2021.117670, 2021.
Li, D., Shindell, D., Ding, D., Lu, X., Zhang, L., and Zhang, Y.: Surface ozone impacts on major crop production in China from 2010 to 2017, Atmos. Chem. Phys., 22, 2625–2638, https://doi.org/10.5194/acp-22-2625-2022, 2022.
Li, K., Jacob, D. J., Shen, L., Lu, X., De Smedt, I., and Liao, H.: Increases in surface ozone pollution in China from 2013 to 2019: anthropogenic and meteorological influences, Atmos. Chem. Phys., 20, 11423–11433, https://doi.org/10.5194/acp-20-11423-2020, 2020.
Lim, P. O., Kim, H. J., and Nam, H. G.: Leaf senescence, Annu. Rev. Plant Biol., 58, 115–136, https://doi.org/10.1146/annurev.arplant.57.032905.105316, 2007.
Lin, M., Horowitz, L. W., Payton, R., Fiore, A. M., and Tonnesen, G.: US surface ozone trends and extremes from 1980 to 2014: quantifying the roles of rising Asian emissions, domestic controls, wildfires, and climate, Atmos. Chem. Phys., 17, 2943–2970, https://doi.org/10.5194/acp-17-2943-2017, 2017.
Liu, B., Asseng, S., Liu, L., Tang, L., Cao, W., and Zhu, Y.: Testing the responses of four wheat crop models to heat stress at anthesis and grain filling, Glob. Change Biol., 22, 1890–1903, https://doi.org/10.1111/gcb.13212, 2016.
Liu, S., Mo, X., Lin, Z., Xu, Y., Ji, J., Wen, G., and Richey, J.: Crop yield responses to climate change in the Huang-Huai-Hai Plain of China, Agr. Water Manage., 97, 1195–1209, https://doi.org/10.1016/j.agwat.2010.03.012, 2010.
Liu, Z., Doherty, R. M., Wild, O., O'Connor, F. M., and Turnock, S. T.: Tropospheric ozone changes and ozone sensitivity from the present day to the future under shared socio-economic pathways, Atmos. Chem. Phys., 22, 1209–1227, https://doi.org/10.5194/acp-22-1209-2022, 2022.
LRTAP: Mapping critical levels for vegetation, chapter III of manual on methodologies and criteria for modelling and mapping critical loads and levels and air pollution effects, risks and trends, UNECE Convention on Long-range Transboundary Air Pollution, 2017.
Lu, C. and Fan, L.: Winter wheat yield potentials and yield gaps in the North China Plain, Field Crops Res., 143, 98–105, https://doi.org/10.1016/j.fcr.2012.09.015, 2013.
Luo, Y., Zhang, Z., Li, Z., Chen, Y., Zhang, L., Cao, J., and Tao, F.: Identifying the spatiotemporal changes of annual harvesting areas for three staple crops in China by integrating multi-data sources, Environ. Res. Lett., 15, 074003, https://doi.org/10.1088/1748-9326/ab80f0, 2020.
Luo, Y., Zhang, Z., Zhang, L., and Cao, J.: Spatiotemporal patterns of winter wheat phenology and its climatic drivers based on an improved pDSSAT model, Sci. China Earth Sci., 64, 2144–2160, https://doi.org/10.1007/s11430-020-9821-0, 2021.
Malhi, G. S., Kaur, M., and Kaushik, P.: Impact of Climate Change on Agriculture and Its Mitigation Strategies: A Review, Sustainability, 13, 1318, https://doi.org/10.3390/su13031318, 2021.
Mariën, B., Balzarolo, M., Dox, I., Leys, S., Marchand J. L., Géron, C., Portillo-Estrada, M., AbdElgawad, H., Asard, H., and Campioli, M.: Detecting the onset of autumn leaf senescence in deciduous forest trees of the temperate zone, New Phytol., 224, 166–176, https://doi.org/10.1111/nph.15991, 2019.
Masutomi, Y.: The appropriate analytical solution for coupled leaf photosynthesis and stomatal conductance models for C3 plants, Ecol. Model., 481, 110306, https://doi.org/10.1016/j.ecolmodel.2023.110306, 2023.
Medlyn, B. E., Dreyer, E., Ellsworth, D., Forstreuter, M., Harley, P., Kirschbaum, M., Roux, X., Montpied, P., Strassemeyer, J., Walcroft, A., Wang, K., and Loustau, D.: Temperature response of parameters of a biochemically based model of photosynthesis. II. A review of experimental data, Plant Cell Environ., 25, 1167–1179, https://doi.org/10.1046/j.1365-3040.2002.00891.x, 2002.
Miller, J. D., Arteca, R. N., and Pell, E. J.: Senescence-Associated Gene Expression during Ozone-Induced Leaf Senescence in Arabidopsis, Plant Physiol., 120, 1015, https://doi.org/10.1104/pp.120.4.1015, 1999.
Mulvaney, M. J. and Devkota, P. J.: Adjusting Crop Yield to a Standard Moisture Content, EDIS, University of Florida George A Smathers Libraries, https://doi.org/10.32473/edis-ag442-2020, 2020.
Nagarajan, S., Rane, J., Maheswari, M., and Gambhir, P. N.: Effect of Post-Anthesis Water Stress on Accumulation of Dry Matter, Carbon and Nitrogen and Their Partitioning in Wheat Varieties Differing in Drought Tolerance, J. Agron. Crop Sci., 183, 129–136, https://doi.org/10.1046/j.1439-037x.1999.00326.x, 1999.
Nguyen, T. H., Cappelli, G. A., Emberson, L., Ignacio, G. F., Irimescu, A., Francesco, S., Fabrizio, G., Booth, N., Boldeanu, G., Bermejo, V., Bland, S., Frei, M., Ewert, F., and Gaiser, T.: Assessing the spatio-temporal tropospheric ozone and drought impacts on leaf growth and grain yield of wheat across Europe through crop modeling and remote sensing data, Eur. J. Agron., 153, 127052, https://doi.org/10.1016/j.eja.2023.127052, 2024.
Okrah, A., Li, S., Agathokleous, E., and Feng, Z.: Elevated ozone effects on potato leaf physiology, growth, and yield: a meta-analysis, Environ. Sci. Pollut. Res., 30, 120483–120495, https://doi.org/10.1007/s11356-023-30854-5, 2023.
Osborne, S., Pandey, D., Mills, G., Hayes, F., Harmens, H., Gillies, D., Bücker, P., and Emberson, L.: New Insights into Leaf Physiological Responses to Ozone for Use in Crop Modelling, Plants, 8, 84, https://doi.org/10.3390/plants8040084, 2019.
Osborne, T., Gornall, J., Hooker, J., Williams, K., Wiltshire, A., Betts, R., and Wheeler, T.: JULES-crop: a parametrisation of crops in the Joint UK Land Environment Simulator, Geosci. Model Dev., 8, 1139–1155, https://doi.org/10.5194/gmd-8-1139-2015, 2015.
Pande, P., Hayes, F., Bland, S., Booth, N., Pleijel, H., and Emberson, L. D.: Ozone Dose-Response Relationships for Wheat Can Be Derived Using Photosynthetic-Based Stomatal Conductance Models, Agr. Forest Meteorol., 356, 110150, https://doi.org/10.1016/j.agrformet.2024.110150, 2024.
Penning de Vries, F. W. T.: Simulation of Ecophysiological Processes of Growth in Several Annual Crops, Simulation Monographs, Vol. 29, Netherlands Centre for Agricultural Publishing and Documentation, Int. Rice Res. Inst., 271 pp., ISBN 9022010007, 9789022010006, 1989.
Pleijel, H., Danielsson, H., Emberson, L., Ashmore, M., and Mills, G.: Ozone Risk Assessment for Agricultural Crops in Europe: Further Development of Stomatal Flux and Flux–Response Relationships for European Wheat and Potato, Atmos. Environ., 41, 3022–3040, https://doi.org/10.1016/j.atmosenv.2006.12.002, 2007.
Pleijel, H., Danielsson, H., and Broberg, M. C.: Benefits of the Phytotoxic Ozone Dose (POD) index in dose-response functions for wheat yield loss, Atmos. Environ., 268, 118797, https://doi.org/10.1016/j.atmosenv.2021.118797, 2022.
Qin, X., Zhang, F., Liu, C., Yu, H., Cao, B., Tian, S., Liao, Y., and Siddique, K.: Wheat Yield Improvements in China: Past Trends and Future Directions, Field Crops Res., 177, 117–124, https://doi.org/10.1016/j.fcr.2015.03.013, 2015.
Ronan, A. C., Ducker, J. A., Schnell, J. L., and Holmes, C. D.: Have improvements in ozone air quality reduced ozone uptake into plants?, Elem. Sci. Anth., 8, 2, https://doi.org/10.1525/elementa.399, 2020.
Schauberger, B., Rolinski, S., Schaphoff, S., and Müller, C.: Global Historical Soybean and Wheat Yield Loss Estimates from Ozone Pollution Considering Water and Temperature as Modifying Effects, Agr. Forest Meteorol., 265, 1–15, https://doi.org/10.1016/j.agrformet.2018.11.004, 2019.
Sharkey, T. D., Bernacchi, C. J., Farquhar, G. D., and Singsaas, E. L.: Fitting Photosynthetic Carbon Dioxide Response Curves for C3 Leaves, Plant Cell Environ., 30, 1035–1040, https://doi.org/10.1111/j.1365-3040.2007.01710.x, 2007.
Shi, G., Yang, L., Wang, Y., Kobayashi, K., Zhu, J., Tang, H., Pan, S., Chen, T., Liu, G., and Wang, Y.: Impact of elevated ozone concentration on yield of four Chinese rice cultivars under fully open-air field conditions, Agr. Ecosyst. Environ., 131, 178–184, https://doi.org/10.1016/j.agee.2009.01.009, 2009.
Sillmann, J., Aunan, K., Emberson, L., Bücker, P., van Oort, B. V., O'Neill, C., Otero, N., Pandey, D., and Brisebois, A.: Combined Impacts of Climate and Air Pollution on Human Health and Agricultural Productivity, Environ. Res. Lett., 16, 074001, https://doi.org/10.1088/1748-9326/ac1df8, 2021.
Silvestro, P. C., Pignatti, S., Yang, H., Yang, G., Pascucci, S., Castaldi, F., and Casa, R.: Sensitivity analysis of the AquaCrop and SAFY crop models for the assessment of water-limited winter wheat yield in regional scale applications, PLoS ONE, 12, e0187485, https://doi.org/10.1371/journal.pone.0187485, 2017.
Simpson, D., Benedictow, A., Berge, H., Bergström, R., Emberson, L. D., Fagerli, H., Flechard, C. R., Hayman, G. D., Gauss, M., Jonson, J. E., Jenkin, M. E., Nyíri, A., Richter, C., Semeena, V. S., Tsyro, S., Tuovinen, J.-P., Valdebenito, Á., and Wind, P.: The EMEP MSC-W chemical transport model – technical description, Atmos. Chem. Phys., 12, 7825–7865, https://doi.org/10.5194/acp-12-7825-2012, 2012.
Sitch, S., Cox, P. M., Collins, W. J., and Huntingford, C.: Indirect Radiative Forcing of Climate Change Through Ozone Effects on the Land-Carbon Sink, Nature, 448, 791–795, https://doi.org/10.1038/nature06059, 2007.
Tao, F., Zhang, S., and Zhang, Z.: Spatiotemporal changes of wheat phenology in China under the effects of temperature, day length and cultivar thermal characteristics, Eur. J. Agron., 43, 201–212, https://doi.org/10.1016/j.eja.2012.06.004, 2012.
Tao, F., Feng, Z., Tang, H., Chen, Y., and Kobayashi, K.: Effects of Climate Change, CO2 and O3 on Wheat Productivity in Eastern China, Singly and in Combination, Atmos. Environ., 153, 182–193, https://doi.org/10.1016/j.atmosenv.2017.01.032, 2017.
Triboi, E. and Triboi-Blondel, A. M.: Productivity and Grain or Seed Composition: A New Approach to an Old Problem – Invited Paper, Eur. J. Agron., 16, 163–186, https://doi.org/10.1016/S1161-0301(01)00146-0, 2002.
Van Oijen, M. and Ewert, F.: The effects of climatic variation in Europe on the yield response of spring wheat cv. Minaret to elevated CO2 and O3: an analysis of open-top chamber experiments by means of two crop growth simulation models, Eur. J. Agron., 10, 249–264, https://doi.org/10.1016/s1161-0301(99)00014-3, 1999.
Vazquez-Cruz, M. A. and Guzman, R.: Global sensitivity analysis by means of EFAST and Sobol' methods and calibration of the reduced state-variable TOMGRO model using genetic algorithms, Comput. Electron. Agric., 100, 1–12, https://doi.org/10.1016/j.compag.2013.10.006, 2014.
Wallach, D.: Crop model calibration: A statistical perspective. Agron. J., 103, 1141–1153, https://doi.org/10.2134/agronj2010.0432, 2011.
Wang, Q. J.: Using Genetic Algorithms to Optimise Model Parameters, Environ. Model. Softw., 12, 27–34, https://doi.org/10.1016/S1364-8152(96)00030-8, 1997.
Yadav, D. S., Mishra, A. K., Rai, R., Chaudhary, N., Mukherjee, A., Agrawal, S. B., and Agrawal, M.: Responses of an Old and a Modern Indian Wheat Cultivar to Future O3 Levels: Physiological, Yield and Grain Quality Parameters, Environ. Pollut., 263, 113939, https://doi.org/10.1016/j.envpol.2020.113939, 2020.
Yang, L., Liu, S., Tsoka, S., and Papageorgiou, L. G.: Mathematical Programming for Piecewise Linear Regression Analysis, Expert Syst. Appl., 44, 156–167, https://doi.org/10.1016/j.eswa.2015.08.034, 2016.
Zhang, X., Xu, W., Zhang, G., Lin, W., Zhao, H., Ren, S., Zhou, G., Chen, J., and Xu, X.: First long-term surface ozone variations at an agricultural site in the North China Plain: Evolution under changing meteorology and emissions, Sci. Total Environ., 860, 160520, https://doi.org/10.1016/j.scitotenv.2022.160520, 2023.
Zhao, P., Zhou, Y., Li, F., Ling, X., Deng, N., Peng, S., and Man, J.: The Adaptability of APSIM-Wheat Model in the Middle and Lower Reaches of the Yangtze River Plain of China: A Case Study of Winter Wheat in Hubei Province, Agronomy, 10, 981, https://doi.org/10.3390/agronomy10070981, 2020.
Zheng, B., Chenu, K., Doherty, A., and Chapman, S.: The APSIM-Wheat Module (7.5 R3008), APSIM Initiative, 44 pp., https://www.apsim.info/documentation/model-documentation/crop-module-documentation/wheat/ (last access: 28 December 2024), 2015.
Zhu, X., Feng, Z., Sun, T., Liu, X., Tang, H., Zhu, J., Guo, W., and Kobayashi, K.: Effects of Elevated Ozone Concentration on Yield of Four Chinese Cultivars of Winter Wheat Under Fully Open-Air Field Conditions, Glob. Change Biol., 17, 2697–2706, https://doi.org/10.1111/j.1365-2486.2011.02400.x, 2011.
Short summary
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.
The DO3SE-Crop model extends the DO3SE to simulate ozone's impact on crops with modules for...
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