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1. Rice Management Decisions Using Process-Based Models With Climate-Smart Indicators

Author

Arenas-Calle, Laura N., Heinemann, Alexandre B., Soler da Silva, Mellissa A., dos Santos, Alberto Baeta, Ramirez-Villegas, Julian, Whitfield, Stephen, Challinor, Andrew J., Arenas-Calle, Laura N., Heinemann, Alexandre B., Soler da Silva, Mellissa A., dos Santos, Alberto Baeta, Ramirez-Villegas, Julian, Whitfield, Stephen, and Challinor, Andrew J.

Abstract

Irrigation strategies are keys to fostering sustainable and climate-resilient rice production by increasing efficiency, building resilience and reducing Greenhouse Gas (GHG) emissions. These strategies are aligned with the Climate-Smart Agriculture (CSA) principles, which aim to maximize productivity whilst adapting to and mitigating climate change. Achieve such mitigation, adaptation, and productivity goals- to the extent possible- is described as climate smartness. Measuring climate smartness is challenging, with recent progress focusing on the use of agronomic indicators in a limited range of contexts. One way to broaden the ability to measure climate-smartness is to use modeling tools, expanding the scope of climate smartness assessments. Accordingly, and as a proof-of-concept, this study uses modeling tools with CSA indicators (i.e., Greenhouse Intensity and Water Productivity) to quantify the climate-smartness of irrigation management in rice and to assess sensitivity to climate. We focus on a field experiment that assessed four irrigation strategies in tropical conditions, Continuous Flooding (CF), Intermittent Irrigation (II), Intermittent Irrigation until Flowering (IIF), and Continuous soil saturation (CSS). The DNDC model was used to simulate rice yields, GHG emissions and water inputs. We used model outputs to calculate a previously developed Climate-Smartness Index (CSI) based on water productivity and greenhouse gas intensity, which score on a scale between−1 (lack of climate-smartness) to 1 (high climate smartness) the climate-smartness of irrigation strategies. The CSS exhibited the highest simulation-based CSI, and CF showed the lowest. A sensitivity analysis served to explore the impacts of climate on CSI. While higher temperatures reduced CSI, rainfall mostly showed no signal. The climate smartness decreasing in warmer temperatures was associated with increased GHG emissions and, to some extent, a reduction in Water Productivity (WP). Overall, CSI

Published
2022

2. Improving the representation of sugarcane crop in the Joint UK Land Environment Simulator (JULES) model for climate impact assessment

Author

Vianna, Murilo S., Williams, Karina W., Littleton, Emma W., Cabral, Osvaldo, Cerri, Carlos Eduardo P., De Jong van Lier, Quirijn, Marthews, Toby R., Hayman, Garry, Zeri, Marcelo, Cuadra, Santiago V., Challinor, Andrew J., Marin, Fabio R., Galdos, Marcelo V., Vianna, Murilo S., Williams, Karina W., Littleton, Emma W., Cabral, Osvaldo, Cerri, Carlos Eduardo P., De Jong van Lier, Quirijn, Marthews, Toby R., Hayman, Garry, Zeri, Marcelo, Cuadra, Santiago V., Challinor, Andrew J., Marin, Fabio R., and Galdos, Marcelo V.

Abstract

Bioenergy from sugarcane production is considered a key mitigation strategy for global warming. Improving its representation in land surface models is important to further understand the interactions between climate and bioenergy production, supporting accurate climate projections and decision-making. This study aimed to calibrate and evaluate the Joint UK Land Environment Simulator (JULES) for climate impact assessments in sugarcane. A dataset composed of soil moisture, water and carbon fluxes and biomass measurements from field experiments across Brazil was used to calibrate and evaluate JULES-crop and JULES-BE parametrizations. The ability to predict the spatiotemporal variability of sugarcane yields and the impact of climate change was also tested at five Brazilian microregions. Parameters related to sugarcane allometry, crop growth and development were derived and tested for JULES-crop and JULES-BE, together with the response to atmospheric carbon dioxide, temperature and low-water availability (CTW-response). Both parametrizations showed comparable performance to other sugarcane dynamic models, with a root mean squared error of 6.75 and 6.05 t ha−1 for stalk dry matter for JULES-crop and JULES-BE, respectively. The parametrizations were also able to replicate the average yield patterns observed in the five microregions over 30 years when the yield gap factors were taken into account, with the correlation (r) between simulated and observed interannual variability of yields ranging from 0.33 to 0.56. An overall small positive trend was found in future yield projections of sugarcane using the new calibrations, with exception of the Jataí mesoregion which showed a clear negative trend for the SSP5 scenario from the years 2070 to 2100. Our simulations showed that an abrupt negative impact on sugarcane yields is expected if daytime temperatures above 35°C become more frequent. The newly calibrated version of JULES can be applied regionally and globally to help under

Published
2022

3. CGIAR modeling approaches for resource-constrained scenarios: I. Accelerating crop breeding for a changing climate

Author

Ramirez-Villegas, Julian, Molero Milan, Anabel, Alexandrov, Nickolai, Asseng, Senthold, Challinor, Andrew J., Crossa, José, van Eeuwijk, Fred, Ghanem, Michel Edmond, Grenier, Cécile, Heinemann, Alexandre, Wang, Jiankang, Juliana, Philomin, Kehel, Zakaria, Kholova, Jana, Koo, Jawoo, Pequeno, Diego, Quiroz, Roberto, Rebolledo Cid, Maria Camila, Sukumaran, Sivakumar, Vadez, Vincent, White, Jeffrey W., Reynolds, Matthew P., Ramirez-Villegas, Julian, Molero Milan, Anabel, Alexandrov, Nickolai, Asseng, Senthold, Challinor, Andrew J., Crossa, José, van Eeuwijk, Fred, Ghanem, Michel Edmond, Grenier, Cécile, Heinemann, Alexandre, Wang, Jiankang, Juliana, Philomin, Kehel, Zakaria, Kholova, Jana, Koo, Jawoo, Pequeno, Diego, Quiroz, Roberto, Rebolledo Cid, Maria Camila, Sukumaran, Sivakumar, Vadez, Vincent, White, Jeffrey W., and Reynolds, Matthew P.

Abstract

Crop improvement efforts aiming at increasing crop production (quantity, quality) and adapting to climate change have been subject of active research over the past years. But, 'to what extent can breeding gains be achieved under a changing climate, at a pace sufficient to usefully contribute to climate adaptation, mitigation and food security?'. Here, we address this question by critically reviewing how model‐based approaches can be used to assist breeding activities, with particular focus on all CGIAR (formerly the Consultative Group on International Agricultural Research but now known simply as CGIAR) breeding programs. Crop modeling can underpin breeding efforts in many different ways, including assessing genotypic adaptability and stability, characterizing and identifying target breeding environments, identifying tradeoffs among traits for such environments, and making predictions of the likely breeding value of the genotypes. Crop modeling science within the CGIAR has contributed to all of these. However, much progress remains to be done if modeling is to effectively contribute to more targeted and impactful breeding programs under changing climates. In a period in which CGIAR breeding programs are undergoing a major modernization process, crop modelers will need to be part of crop improvement teams, with a common understanding of breeding pipelines and model capabilities and limitations, and common data standards and protocols, to ensure they follow and deliver according to clearly defined breeding products. This will, in turn, enable more rapid and better‐targeted crop modeling activities, thus directly contributing to accelerated and more impactful breeding efforts.

Published
2020

4. A new model of ozone stress in wheat including grain yield loss and plant acclimation to the pollutant

Author

Droutsas, I., Challinor, A. J., Arnold, S. R., Mikkelsen, Teis Nørgaard, Hansen, E. M. Ø., Droutsas, I., Challinor, A. J., Arnold, S. R., Mikkelsen, Teis Nørgaard, and Hansen, E. M. Ø.

Abstract

Surface ozone (O3) is an important air pollutant globally and enhanced concentrations lead to crop yield penalties in many parts of the world. Crop models simulate production and yield and they are often used for various applications. However, most of the existing models neglect the effect of O3 and only limited parameterization schemes exist. In addition, the existing O3 modelling approaches do not take into account the plant acclimation to the pollutant as a mechanism of survival and maintenance of performance. Here, we introduce a simple modelling method to simulate the O3 damage to wheat with consideration of the plant acclimation process. The O3 parameterization scheme was incorporated into the GLAM-Parti crop model, resulting in a new model version GLAM-ROC (i.e. GLAM – Relative Ozone Concentrations). The new model simulates the effect of O3 on crop growth and development and was evaluated against data from control-environment chambers with high O3 concentration levels and variable duration of exposure to the pollutant. GLAM-ROC successfully reproduced the observed plant response to O3 as well as the final biomass and yield. The incorporation of plant acclimation allowed the prediction of crop yield loss at variable duration of O3 exposure. The statistical response formula neglected the acclimation process and overestimated the relative O3 damage to yield by 56.5%, when fumigation increased from 32 to 106 days. We conclude that the plant acclimation to chronic O3 environment is significant and should be taken into account for the effect of O3 on wheat performance and yield.

Published
2020

5. CGIAR modeling approaches for resource-constrained scenarios: I. Accelerating crop breeding for a changing climate

Author

Ramirez-Villegas, Julian, Molero Milan, Anabel, Alexandrov, Nickolai, Asseng, Senthold, Challinor, Andrew J., Crossa, José, van Eeuwijk, Fred, Ghanem, Michel Edmond, Grenier, Cécile, Heinemann, Alexandre, Wang, Jiankang, Juliana, Philomin, Kehel, Zakaria, Kholova, Jana, Koo, Jawoo, Pequeno, Diego, Quiroz, Roberto, Rebolledo Cid, Maria Camila, Sukumaran, Sivakumar, Vadez, Vincent, White, Jeffrey W., Reynolds, Matthew P., Ramirez-Villegas, Julian, Molero Milan, Anabel, Alexandrov, Nickolai, Asseng, Senthold, Challinor, Andrew J., Crossa, José, van Eeuwijk, Fred, Ghanem, Michel Edmond, Grenier, Cécile, Heinemann, Alexandre, Wang, Jiankang, Juliana, Philomin, Kehel, Zakaria, Kholova, Jana, Koo, Jawoo, Pequeno, Diego, Quiroz, Roberto, Rebolledo Cid, Maria Camila, Sukumaran, Sivakumar, Vadez, Vincent, White, Jeffrey W., and Reynolds, Matthew P.

Abstract

Crop improvement efforts aiming at increasing crop production (quantity, quality) and adapting to climate change have been subject of active research over the past years. But, 'to what extent can breeding gains be achieved under a changing climate, at a pace sufficient to usefully contribute to climate adaptation, mitigation and food security?'. Here, we address this question by critically reviewing how model‐based approaches can be used to assist breeding activities, with particular focus on all CGIAR (formerly the Consultative Group on International Agricultural Research but now known simply as CGIAR) breeding programs. Crop modeling can underpin breeding efforts in many different ways, including assessing genotypic adaptability and stability, characterizing and identifying target breeding environments, identifying tradeoffs among traits for such environments, and making predictions of the likely breeding value of the genotypes. Crop modeling science within the CGIAR has contributed to all of these. However, much progress remains to be done if modeling is to effectively contribute to more targeted and impactful breeding programs under changing climates. In a period in which CGIAR breeding programs are undergoing a major modernization process, crop modelers will need to be part of crop improvement teams, with a common understanding of breeding pipelines and model capabilities and limitations, and common data standards and protocols, to ensure they follow and deliver according to clearly defined breeding products. This will, in turn, enable more rapid and better‐targeted crop modeling activities, thus directly contributing to accelerated and more impactful breeding efforts.

Published
2020

6. CGIAR modeling approaches for resource-constrained scenarios : I. Accelerating crop breeding for a changing climate

Author

Ramirez-Villegas, Julian, Molero Milan, Anabel, Alexandrov, Nickolai, Asseng, Senthold, Challinor, Andrew J., Crossa, Jose, van Eeuwijk, Fred, Ghanem, Michel Edmond, Grenier, Cecile, Heinemann, Alexandre B., Wang, Jiankang, Juliana, Philomin, Kehel, Zakaria, Kholova, Jana, Koo, Jawoo, Pequeno, Diego, Quiroz, Roberto, Rebolledo, Maria C., Sukumaran, Sivakumar, Vadez, Vincent, White, Jeffrey W., Reynolds, Matthew, Ramirez-Villegas, Julian, Molero Milan, Anabel, Alexandrov, Nickolai, Asseng, Senthold, Challinor, Andrew J., Crossa, Jose, van Eeuwijk, Fred, Ghanem, Michel Edmond, Grenier, Cecile, Heinemann, Alexandre B., Wang, Jiankang, Juliana, Philomin, Kehel, Zakaria, Kholova, Jana, Koo, Jawoo, Pequeno, Diego, Quiroz, Roberto, Rebolledo, Maria C., Sukumaran, Sivakumar, Vadez, Vincent, White, Jeffrey W., and Reynolds, Matthew

Abstract

Crop improvement efforts aiming at increasing crop production (quantity, quality) and adapting to climate change have been subject of active research over the past years. But, the question remains ‘to what extent can breeding gains be achieved under a changing climate, at a pace sufficient to usefully contribute to climate adaptation, mitigation and food security?’. Here, we address this question by critically reviewing how model-based approaches can be used to assist breeding activities, with particular focus on all CGIAR (formerly the Consultative Group on International Agricultural Research but now known simply as CGIAR) breeding programs. Crop modeling can underpin breeding efforts in many different ways, including assessing genotypic adaptability and stability, characterizing and identifying target breeding environments, identifying tradeoffs among traits for such environments, and making predictions of the likely breeding value of the genotypes. Crop modeling science within the CGIAR has contributed to all of these. However, much progress remains to be done if modeling is to effectively contribute to more targeted and impactful breeding programs under changing climates. In a period in which CGIAR breeding programs are undergoing a major modernization process, crop modelers will need to be part of crop improvement teams, with a common understanding of breeding pipelines and model capabilities and limitations, and common data standards and protocols, to ensure they follow and deliver according to clearly defined breeding products. This will, in turn, enable more rapid and better-targeted crop modeling activities, thus directly contributing to accelerated and more impactful breeding efforts.

Published
2020

7. Climate change impact and adaptation for wheat protein

Author

Asseng, Senthold, Martre, Pierre, Maiorano, Andrea, Roetter, Reimund P., O'Leary, Garry J., Fitzgerald, Glenn J., Girousse, Christine, Motzo, Rosella, Giunta, Francesco, Babar, M. Ali, Reynolds, Matthew P., Kheir, Ahmed M. S., Thorburn, Peter J., Waha, Katharina, Ruane, Alex C., Aggarwal, Pramod K., Ahmed, Mukhtar, Balkovic, Juraj, Basso, Bruno, Biernath, Christian, Bindi, Marco, Cammarano, Davide, Challinor, Andrew J., De Sanctis, Giacomo, Dumont, Benjamin, Rezaei, Ehsan Eyshi, Fereres, Elias, Ferrise, Roberto, Garcia-Vila, Margarita, Gayler, Sebastian, Gao, Yujing, Horan, Heidi, Hoogenboom, Gerrit, Izaurralde, R. Cesar, Jabloun, Mohamed, Jones, Curtis D., Kassie, Belay T., Kersebaum, Kurt-Christian, Klein, Christian, Koehler, Ann-Kristin, Liu, Bing, Minoli, Sara, San Martin, Manuel Montesino, Mueller, Christoph, Kumar, Soora Naresh, Nendel, Claas, Olesen, Jørgen Eivind, Palosuo, Taru, Porter, John R., Priesack, Eckart, Ripoche, Dominique, Semenov, Mikhail A., Stockle, Claudio, Stratonovitch, Pierre, Streck, Thilo, Supit, Iwan, Tao, Fulu, Van der Velde, Marijn, Wallach, Daniel, Wang, Enli, Webber, Heidi, Wolf, Joost, Xiao, Liujun, Zhang, Zhao, Zhao, Zhigan, Zhu, Yan, Ewert, Frank, Asseng, Senthold, Martre, Pierre, Maiorano, Andrea, Roetter, Reimund P., O'Leary, Garry J., Fitzgerald, Glenn J., Girousse, Christine, Motzo, Rosella, Giunta, Francesco, Babar, M. Ali, Reynolds, Matthew P., Kheir, Ahmed M. S., Thorburn, Peter J., Waha, Katharina, Ruane, Alex C., Aggarwal, Pramod K., Ahmed, Mukhtar, Balkovic, Juraj, Basso, Bruno, Biernath, Christian, Bindi, Marco, Cammarano, Davide, Challinor, Andrew J., De Sanctis, Giacomo, Dumont, Benjamin, Rezaei, Ehsan Eyshi, Fereres, Elias, Ferrise, Roberto, Garcia-Vila, Margarita, Gayler, Sebastian, Gao, Yujing, Horan, Heidi, Hoogenboom, Gerrit, Izaurralde, R. Cesar, Jabloun, Mohamed, Jones, Curtis D., Kassie, Belay T., Kersebaum, Kurt-Christian, Klein, Christian, Koehler, Ann-Kristin, Liu, Bing, Minoli, Sara, San Martin, Manuel Montesino, Mueller, Christoph, Kumar, Soora Naresh, Nendel, Claas, Olesen, Jørgen Eivind, Palosuo, Taru, Porter, John R., Priesack, Eckart, Ripoche, Dominique, Semenov, Mikhail A., Stockle, Claudio, Stratonovitch, Pierre, Streck, Thilo, Supit, Iwan, Tao, Fulu, Van der Velde, Marijn, Wallach, Daniel, Wang, Enli, Webber, Heidi, Wolf, Joost, Xiao, Liujun, Zhang, Zhao, Zhao, Zhigan, Zhu, Yan, and Ewert, Frank

Published
2019

8. Climate change impact and adaptation for wheat protein

Author

Asseng, Senthold, Martre, Pierre, Maiorano, Andrea, Roetter, Reimund P., O'Leary, Garry J., Fitzgerald, Glenn J., Girousse, Christine, Motzo, Rosella, Giunta, Francesco, Babar, M. Ali, Reynolds, Matthew P., Kheir, Ahmed M. S., Thorburn, Peter J., Waha, Katharina, Ruane, Alex C., Aggarwal, Pramod K., Ahmed, Mukhtar, Balkovic, Juraj, Basso, Bruno, Biernath, Christian, Bindi, Marco, Cammarano, Davide, Challinor, Andrew J., De Sanctis, Giacomo, Dumont, Benjamin, Rezaei, Ehsan Eyshi, Fereres, Elias, Ferrise, Roberto, Garcia-Vila, Margarita, Gayler, Sebastian, Gao, Yujing, Horan, Heidi, Hoogenboom, Gerrit, Izaurralde, R. Cesar, Jabloun, Mohamed, Jones, Curtis D., Kassie, Belay T., Kersebaum, Kurt-Christian, Klein, Christian, Koehler, Ann-Kristin, Liu, Bing, Minoli, Sara, San Martin, Manuel Montesino, Mueller, Christoph, Kumar, Soora Naresh, Nendel, Claas, Olesen, Jørgen Eivind, Palosuo, Taru, Porter, John R., Priesack, Eckart, Ripoche, Dominique, Semenov, Mikhail A., Stockle, Claudio, Stratonovitch, Pierre, Streck, Thilo, Supit, Iwan, Tao, Fulu, Van der Velde, Marijn, Wallach, Daniel, Wang, Enli, Webber, Heidi, Wolf, Joost, Xiao, Liujun, Zhang, Zhao, Zhao, Zhigan, Zhu, Yan, Ewert, Frank, Asseng, Senthold, Martre, Pierre, Maiorano, Andrea, Roetter, Reimund P., O'Leary, Garry J., Fitzgerald, Glenn J., Girousse, Christine, Motzo, Rosella, Giunta, Francesco, Babar, M. Ali, Reynolds, Matthew P., Kheir, Ahmed M. S., Thorburn, Peter J., Waha, Katharina, Ruane, Alex C., Aggarwal, Pramod K., Ahmed, Mukhtar, Balkovic, Juraj, Basso, Bruno, Biernath, Christian, Bindi, Marco, Cammarano, Davide, Challinor, Andrew J., De Sanctis, Giacomo, Dumont, Benjamin, Rezaei, Ehsan Eyshi, Fereres, Elias, Ferrise, Roberto, Garcia-Vila, Margarita, Gayler, Sebastian, Gao, Yujing, Horan, Heidi, Hoogenboom, Gerrit, Izaurralde, R. Cesar, Jabloun, Mohamed, Jones, Curtis D., Kassie, Belay T., Kersebaum, Kurt-Christian, Klein, Christian, Koehler, Ann-Kristin, Liu, Bing, Minoli, Sara, San Martin, Manuel Montesino, Mueller, Christoph, Kumar, Soora Naresh, Nendel, Claas, Olesen, Jørgen Eivind, Palosuo, Taru, Porter, John R., Priesack, Eckart, Ripoche, Dominique, Semenov, Mikhail A., Stockle, Claudio, Stratonovitch, Pierre, Streck, Thilo, Supit, Iwan, Tao, Fulu, Van der Velde, Marijn, Wallach, Daniel, Wang, Enli, Webber, Heidi, Wolf, Joost, Xiao, Liujun, Zhang, Zhao, Zhao, Zhigan, Zhu, Yan, and Ewert, Frank

Published
2019

9. Global wheat production with 1.5 and 2.0°C above pre-industrial warming

Author

Liu, Bing, Martre, Pierre, Ewert, Frank, Porter, John R., Challinor, Andy J, Müller, Christoph, Ruane, Alex C, Waha, Katharina, Thorburn, Peter J, Aggarwal, Pramod K, Ahmed, Mukhtar, Balkovič, Juraj, Basso, Bruno, Biernath, Christian, Bindi, Marco, Cammarano, Davide, De Sanctis, Giacomo, Dumont, Benjamin, Espadafor, Mónica, Eyshi Rezaei, Ehsan, Ferrise, Roberto, Garcia-Vila, Margarita, Gayler, Sebastian, Gao, Yujing, Horan, Heidi, Hoogenboom, Gerrit, Izaurralde, Roberto C, Jones, Curtis D, Kassie, Belay T, Kersebaum, Kurt C, Klein, Christian, Koehler, Ann-Kristin, Maiorano, Andrea, Minoli, Sara, Montesino San Martin, Manuel, Naresh Kumar, Soora, Nendel, Claas, O'Leary, Garry J, Palosuo, Taru, Priesack, Eckart, Ripoche, Dominique, Rötter, Reimund P, Semenov, Mikhail A, Stöckle, Claudio, Streck, Thilo, Supit, Iwan, Tao, Fulu, Van der Velde, Marijn, Wallach, Daniel, Wang, Enli, Webber, Heidi, Wolf, Joost, Xiao, Liujun, Zhang, Zhao, Zhao, Zhigan, Zhu, Yan, Asseng, Senthold, Liu, Bing, Martre, Pierre, Ewert, Frank, Porter, John R., Challinor, Andy J, Müller, Christoph, Ruane, Alex C, Waha, Katharina, Thorburn, Peter J, Aggarwal, Pramod K, Ahmed, Mukhtar, Balkovič, Juraj, Basso, Bruno, Biernath, Christian, Bindi, Marco, Cammarano, Davide, De Sanctis, Giacomo, Dumont, Benjamin, Espadafor, Mónica, Eyshi Rezaei, Ehsan, Ferrise, Roberto, Garcia-Vila, Margarita, Gayler, Sebastian, Gao, Yujing, Horan, Heidi, Hoogenboom, Gerrit, Izaurralde, Roberto C, Jones, Curtis D, Kassie, Belay T, Kersebaum, Kurt C, Klein, Christian, Koehler, Ann-Kristin, Maiorano, Andrea, Minoli, Sara, Montesino San Martin, Manuel, Naresh Kumar, Soora, Nendel, Claas, O'Leary, Garry J, Palosuo, Taru, Priesack, Eckart, Ripoche, Dominique, Rötter, Reimund P, Semenov, Mikhail A, Stöckle, Claudio, Streck, Thilo, Supit, Iwan, Tao, Fulu, Van der Velde, Marijn, Wallach, Daniel, Wang, Enli, Webber, Heidi, Wolf, Joost, Xiao, Liujun, Zhang, Zhao, Zhao, Zhigan, Zhu, Yan, and Asseng, Senthold

Abstract

Efforts to limit global warming to below 2°C in relation to the pre-industrial level are under way, in accordance with the 2015 Paris Agreement. However, most impact research on agriculture to date has focused on impacts of warming >2°C on mean crop yields, and many previous studies did not focus sufficiently on extreme events and yield interannual variability. Here, with the latest climate scenarios from the Half a degree Additional warming, Prognosis and Projected Impacts (HAPPI) project, we evaluated the impacts of the 2015 Paris Agreement range of global warming (1.5 and 2.0°C warming above the pre-industrial period) on global wheat production and local yield variability. A multi-crop and multi-climate model ensemble over a global network of sites developed by the Agricultural Model Intercomparison and Improvement Project (AgMIP) for Wheat was used to represent major rainfed and irrigated wheat cropping systems. Results show that projected global wheat production will change by -2.3% to 7.0% under the 1.5°C scenario and -2.4% to 10.5% under the 2.0°C scenario, compared to a baseline of 1980-2010, when considering changes in local temperature, rainfall, and global atmospheric CO2 concentration, but no changes in management or wheat cultivars. The projected impact on wheat production varies spatially; a larger increase is projected for temperate high rainfall regions than for moderate hot low rainfall and irrigated regions. Grain yields in warmer regions are more likely to be reduced than in cooler regions. Despite mostly positive impacts on global average grain yields, the frequency of extremely low yields (bottom 5 percentile of baseline distribution) and yield inter-annual variability will increase under both warming scenarios for some of the hot growing locations, including locations from the second largest global wheat producer-India, which supplies more than 14% of global wheat. The projected global impact of warming <2°C on wheat production is ther

Published
2019

10. Invited review:Intergovernmental Panel on Climate Change, agriculture, and food—A case of shifting cultivation and history

Author

Porter, John R., Challinor, Andrew J., Henriksen, Christian Bugge, Howden, Stuart Mark, Martre, Pierre, Smith, Pete, Porter, John R., Challinor, Andrew J., Henriksen, Christian Bugge, Howden, Stuart Mark, Martre, Pierre, and Smith, Pete

Abstract

Since 1990, the Intergovernmental Panel on Climate Change (IPCC) has produced five Assessment Reports (ARs), in which agriculture as the production of food for humans via crops and livestock have featured in one form or another. A constructed database of the ca. 2,100 cited experiments and simulations in the five ARs was analyzed with respect to impacts on yields via crop type, region, and whether adaptation was included. Quantitative data on impacts and adaptation in livestock farming have been extremely scarce in the ARs. The main conclusions from impact and adaptation are that crop yields will decline, but that responses have large statistical variation. Mitigation assessments in the ARs have used both bottom-up and top-down methods but need better to link emissions and their mitigation with food production and security. Relevant policy options have become broader in later ARs and included more of the social and nonproduction aspects of food security. Our overall conclusion is that agriculture and food security, which are two of the most central, critical, and imminent issues in climate change, have been dealt with an unfocussed and inconsistent manner between the IPCC five ARs. This is partly a result of not only agriculture spanning two IPCC working groups but also the very strong focus on projections from computer crop simulation modeling. For the future, we suggest a need to examine interactions between themes such as crop resource use efficiencies and to include all production and nonproduction aspects of food security in future roles for integrated assessment models.

Published
2019

11. Global wheat production with 1.5 and 2.0°C above pre‐industrial warming

Author

National Science Foundation (US), National Natural Science Foundation of China, International Food Policy Research Institute (US), CGIAR (France), Institut National de la Recherche Agronomique (France), Federal Ministry of Education and Research (Germany), Biotechnology and Biological Sciences Research Council (UK), China Scholarship Council, Department of Agriculture and Water Resources (Australia), Ministero delle Politiche Agricole Alimentari e Forestali, Gorgan University, Victoria State Government, National Institute of Food and Agriculture (US), Federal Ministry of Food and Agriculture (Germany), German Research Foundation, Academy of Finland, LabEx Agro, Natural Resources Institute Finland, Liu, Bing, Martre, Pierre, Ewert, Frank, Porter, John R., Challinor, Andrew J., Müller, Christoph, Ruane, Alexander C., Waha, Katharina, Thorburn, Peter, Aggarwal, Pramod K., Ahmed, Mukhtar, Balkovič, Jurajb, Basso, Bruno, Biernath, Christian, Bindi, Marco, Cammarano, Davide, De Sanctis, Giacomo, Dumont, Benjamin, Espadafor, Mónica, Rezaei, Ehsan Eyshi, Ferrise, Roberto, García Vila, Margarita, Gayler, Sebastian, Gao, Yujing, Horan, Heidi, Hoogenboom, Gerrit, Izaurralde, Roberto C., Jones, Curtis D., Kassie, Belay T., Kersebaum, Kurt C., Klein, Christian, Koehler, Ann-Kristin, Maiorano, Andrea, Minoli, Sara, Montesino San Martin, Manuel, Kumar, Soora Naresh, Nendel, Claas, O'Leary, Garry, Palosuo, Taru, Priesack, Eckart, Ripoche, Dominique, Rötter, Reimund P., Semenov, Mikhail A., Stöckle, Claudio, Streck, Thilo, Supit, Iwan, Tao, Fulu, Van der Velde, Marijn, Wallach, Daniel, Wang, Enli, Webber, Heidi, Wolf, Joost, Xiao, Liujun, Zhang, Zhao, Zhao, Zhigan, Zhu, Yan, Asseng, Senthold, National Science Foundation (US), National Natural Science Foundation of China, International Food Policy Research Institute (US), CGIAR (France), Institut National de la Recherche Agronomique (France), Federal Ministry of Education and Research (Germany), Biotechnology and Biological Sciences Research Council (UK), China Scholarship Council, Department of Agriculture and Water Resources (Australia), Ministero delle Politiche Agricole Alimentari e Forestali, Gorgan University, Victoria State Government, National Institute of Food and Agriculture (US), Federal Ministry of Food and Agriculture (Germany), German Research Foundation, Academy of Finland, LabEx Agro, Natural Resources Institute Finland, Liu, Bing, Martre, Pierre, Ewert, Frank, Porter, John R., Challinor, Andrew J., Müller, Christoph, Ruane, Alexander C., Waha, Katharina, Thorburn, Peter, Aggarwal, Pramod K., Ahmed, Mukhtar, Balkovič, Jurajb, Basso, Bruno, Biernath, Christian, Bindi, Marco, Cammarano, Davide, De Sanctis, Giacomo, Dumont, Benjamin, Espadafor, Mónica, Rezaei, Ehsan Eyshi, Ferrise, Roberto, García Vila, Margarita, Gayler, Sebastian, Gao, Yujing, Horan, Heidi, Hoogenboom, Gerrit, Izaurralde, Roberto C., Jones, Curtis D., Kassie, Belay T., Kersebaum, Kurt C., Klein, Christian, Koehler, Ann-Kristin, Maiorano, Andrea, Minoli, Sara, Montesino San Martin, Manuel, Kumar, Soora Naresh, Nendel, Claas, O'Leary, Garry, Palosuo, Taru, Priesack, Eckart, Ripoche, Dominique, Rötter, Reimund P., Semenov, Mikhail A., Stöckle, Claudio, Streck, Thilo, Supit, Iwan, Tao, Fulu, Van der Velde, Marijn, Wallach, Daniel, Wang, Enli, Webber, Heidi, Wolf, Joost, Xiao, Liujun, Zhang, Zhao, Zhao, Zhigan, Zhu, Yan, and Asseng, Senthold

Abstract

Efforts to limit global warming to below 2°C in relation to the pre‐industrial level are under way, in accordance with the 2015 Paris Agreement. However, most impact research on agriculture to date has focused on impacts of warming >2°C on mean crop yields, and many previous studies did not focus sufficiently on extreme events and yield interannual variability. Here, with the latest climate scenarios from the Half a degree Additional warming, Prognosis and Projected Impacts (HAPPI) project, we evaluated the impacts of the 2015 Paris Agreement range of global warming (1.5 and 2.0°C warming above the pre‐industrial period) on global wheat production and local yield variability. A multi‐crop and multi‐climate model ensemble over a global network of sites developed by the Agricultural Model Intercomparison and Improvement Project (AgMIP) for Wheat was used to represent major rainfed and irrigated wheat cropping systems. Results show that projected global wheat production will change by −2.3% to 7.0% under the 1.5°C scenario and −2.4% to 10.5% under the 2.0°C scenario, compared to a baseline of 1980–2010, when considering changes in local temperature, rainfall, and global atmospheric CO2 concentration, but no changes in management or wheat cultivars. The projected impact on wheat production varies spatially; a larger increase is projected for temperate high rainfall regions than for moderate hot low rainfall and irrigated regions. Grain yields in warmer regions are more likely to be reduced than in cooler regions. Despite mostly positive impacts on global average grain yields, the frequency of extremely low yields (bottom 5 percentile of baseline distribution) and yield inter‐annual variability will increase under both warming scenarios for some of the hot growing locations, including locations from the second largest global wheat producer—India, which supplies more than 14% of global wheat. The projected global impact of warming <2°C on wheat production is therefore not

Published
2019

12. Climate change impact and adaptation for wheat protein

Author

International Food Policy Research Institute (US), CGIAR (France), European Commission, Institut National de la Recherche Agronomique (France), National Natural Science Foundation of China, Federal Ministry of Food and Agriculture (Germany), Biotechnology and Biological Sciences Research Council (UK), Innovation Fund Denmark, China Scholarship Council, Ministero delle Politiche Agricole Alimentari e Forestali, Academy of Finland, Finnish Ministry of Agriculture and Forestry, Federal Ministry of Education and Research (Germany), Department of Agriculture and Water Resources (Australia), University of Melbourne, Grains Research and Development Corporation (Australia), National Institute of Food and Agriculture (US), German Research Foundation, Gorgan University, Asseng, Senthold, Martre, Pierre, Maiorano, Andrea, Rötter, Reimund P., O'Leary, Garry, Fitzgerald, Glenn J., Girousse, Christine, Motzo, Rosella, Giunta, Francesco, Babar, M. Ali, Reynolds, Matthew, Kheir, Ahmed, M .S., Thorburn, Peter, Waha, Katharina, Ruane, Alexander C., Aggarwal, Pramod K., Ahmed, Mukhtar, Balkovič, Juraj, Basso, Bruno, Biernath, Christian, Bindi, Marco, Cammarano, Davide, Challinor, Andrew J., De Sanctis, Giacomo, Dumont, Benjamin, Rezaei, Ehsan Eyshi, Fereres Castiel, Elías, Ferrise, Roberto, García Vila, Margarita, Gayler, Sebastian, Gao, Yujing, Horan, Heidi, Hoogenboom, Gerrit, Izaurralde, Roberto C., Jabloun, Mohamed, Jones, Curtis D., Kassie, Belay T., Kersebaum, Kurt C., Klein, Christian, Koehler, Ann-Kristin, Liu, Bing, Minoli, Sara, Montesino San Martin, Manuel, Müller, Christoph, Kumar, Soora Naresh, Nendel, Claas, Olesen, Jørgen E., Palosuo, Taru, Porter, John R., Priesack, Eckart, Ripoche, Dominique, Semenov, Mikhail A., Stöckle, Claudio, Stratonovitch, Pierre, Streck, Thilo, Supit, Iwan, Tao, Fulu, Van der Velde, Marijn, Wallach, Daniel, Wang, Enli, Webber, Heidi, Wolf, Joost, Xiao, Liujun, Zhang, Zhao, Zhao, Zhigan, Zhu, Yan, Ewert, Frank, International Food Policy Research Institute (US), CGIAR (France), European Commission, Institut National de la Recherche Agronomique (France), National Natural Science Foundation of China, Federal Ministry of Food and Agriculture (Germany), Biotechnology and Biological Sciences Research Council (UK), Innovation Fund Denmark, China Scholarship Council, Ministero delle Politiche Agricole Alimentari e Forestali, Academy of Finland, Finnish Ministry of Agriculture and Forestry, Federal Ministry of Education and Research (Germany), Department of Agriculture and Water Resources (Australia), University of Melbourne, Grains Research and Development Corporation (Australia), National Institute of Food and Agriculture (US), German Research Foundation, Gorgan University, Asseng, Senthold, Martre, Pierre, Maiorano, Andrea, Rötter, Reimund P., O'Leary, Garry, Fitzgerald, Glenn J., Girousse, Christine, Motzo, Rosella, Giunta, Francesco, Babar, M. Ali, Reynolds, Matthew, Kheir, Ahmed, M .S., Thorburn, Peter, Waha, Katharina, Ruane, Alexander C., Aggarwal, Pramod K., Ahmed, Mukhtar, Balkovič, Juraj, Basso, Bruno, Biernath, Christian, Bindi, Marco, Cammarano, Davide, Challinor, Andrew J., De Sanctis, Giacomo, Dumont, Benjamin, Rezaei, Ehsan Eyshi, Fereres Castiel, Elías, Ferrise, Roberto, García Vila, Margarita, Gayler, Sebastian, Gao, Yujing, Horan, Heidi, Hoogenboom, Gerrit, Izaurralde, Roberto C., Jabloun, Mohamed, Jones, Curtis D., Kassie, Belay T., Kersebaum, Kurt C., Klein, Christian, Koehler, Ann-Kristin, Liu, Bing, Minoli, Sara, Montesino San Martin, Manuel, Müller, Christoph, Kumar, Soora Naresh, Nendel, Claas, Olesen, Jørgen E., Palosuo, Taru, Porter, John R., Priesack, Eckart, Ripoche, Dominique, Semenov, Mikhail A., Stöckle, Claudio, Stratonovitch, Pierre, Streck, Thilo, Supit, Iwan, Tao, Fulu, Van der Velde, Marijn, Wallach, Daniel, Wang, Enli, Webber, Heidi, Wolf, Joost, Xiao, Liujun, Zhang, Zhao, Zhao, Zhigan, Zhu, Yan, and Ewert, Frank

Abstract

Wheat grain protein concentration is an important determinant of wheat quality for human nutrition that is often overlooked in efforts to improve crop production. We tested and applied a 32‐multi‐model ensemble to simulate global wheat yield and quality in a changing climate. Potential benefits of elevated atmospheric CO2 concentration by 2050 on global wheat grain and protein yield are likely to be negated by impacts from rising temperature and changes in rainfall, but with considerable disparities between regions. Grain and protein yields are expected to be lower and more variable in most low‐rainfall regions, with nitrogen availability limiting growth stimulus from elevated CO2. Introducing genotypes adapted to warmer temperatures (and also considering changes in CO2 and rainfall) could boost global wheat yield by 7% and protein yield by 2%, but grain protein concentration would be reduced by −1.1 percentage points, representing a relative change of −8.6%. Climate change adaptations that benefit grain yield are not always positive for grain quality, putting additional pressure on global wheat production.

Published
2019

13. Climate change impact and adaptation for wheat protein

Author

Asseng, Senthold, Martre, Pierre, Maiorano, Andrea, Roetter, Reimund P., O'Leary, Garry J., Fitzgerald, Glenn J., Girousse, Christine, Motzo, Rosella, Giunta, Francesco, Babar, M. Ali, Reynolds, Matthew P., Kheir, Ahmed M. S., Thorburn, Peter J., Waha, Katharina, Ruane, Alex C., Aggarwal, Pramod K., Ahmed, Mukhtar, Balkovic, Juraj, Basso, Bruno, Biernath, Christian, Bindi, Marco, Cammarano, Davide, Challinor, Andrew J., De Sanctis, Giacomo, Dumont, Benjamin, Rezaei, Ehsan Eyshi, Fereres, Elias, Ferrise, Roberto, Garcia-Vila, Margarita, Gayler, Sebastian, Gao, Yujing, Horan, Heidi, Hoogenboom, Gerrit, Izaurralde, R. Cesar, Jabloun, Mohamed, Jones, Curtis D., Kassie, Belay T., Kersebaum, Kurt-Christian, Klein, Christian, Koehler, Ann-Kristin, Liu, Bing, Minoli, Sara, San Martin, Manuel Montesino, Mueller, Christoph, Kumar, Soora Naresh, Nendel, Claas, Olesen, Jørgen Eivind, Palosuo, Taru, Porter, John R., Priesack, Eckart, Ripoche, Dominique, Semenov, Mikhail A., Stockle, Claudio, Stratonovitch, Pierre, Streck, Thilo, Supit, Iwan, Tao, Fulu, Van der Velde, Marijn, Wallach, Daniel, Wang, Enli, Webber, Heidi, Wolf, Joost, Xiao, Liujun, Zhang, Zhao, Zhao, Zhigan, Zhu, Yan, Ewert, Frank, Asseng, Senthold, Martre, Pierre, Maiorano, Andrea, Roetter, Reimund P., O'Leary, Garry J., Fitzgerald, Glenn J., Girousse, Christine, Motzo, Rosella, Giunta, Francesco, Babar, M. Ali, Reynolds, Matthew P., Kheir, Ahmed M. S., Thorburn, Peter J., Waha, Katharina, Ruane, Alex C., Aggarwal, Pramod K., Ahmed, Mukhtar, Balkovic, Juraj, Basso, Bruno, Biernath, Christian, Bindi, Marco, Cammarano, Davide, Challinor, Andrew J., De Sanctis, Giacomo, Dumont, Benjamin, Rezaei, Ehsan Eyshi, Fereres, Elias, Ferrise, Roberto, Garcia-Vila, Margarita, Gayler, Sebastian, Gao, Yujing, Horan, Heidi, Hoogenboom, Gerrit, Izaurralde, R. Cesar, Jabloun, Mohamed, Jones, Curtis D., Kassie, Belay T., Kersebaum, Kurt-Christian, Klein, Christian, Koehler, Ann-Kristin, Liu, Bing, Minoli, Sara, San Martin, Manuel Montesino, Mueller, Christoph, Kumar, Soora Naresh, Nendel, Claas, Olesen, Jørgen Eivind, Palosuo, Taru, Porter, John R., Priesack, Eckart, Ripoche, Dominique, Semenov, Mikhail A., Stockle, Claudio, Stratonovitch, Pierre, Streck, Thilo, Supit, Iwan, Tao, Fulu, Van der Velde, Marijn, Wallach, Daniel, Wang, Enli, Webber, Heidi, Wolf, Joost, Xiao, Liujun, Zhang, Zhao, Zhao, Zhigan, Zhu, Yan, and Ewert, Frank

Published
2019

14. Invited review:Intergovernmental Panel on Climate Change, agriculture, and food—A case of shifting cultivation and history

Author

Porter, John R., Challinor, Andrew J., Henriksen, Christian Bugge, Howden, Stuart Mark, Martre, Pierre, Smith, Pete, Porter, John R., Challinor, Andrew J., Henriksen, Christian Bugge, Howden, Stuart Mark, Martre, Pierre, and Smith, Pete

Abstract

Since 1990, the Intergovernmental Panel on Climate Change (IPCC) has produced five Assessment Reports (ARs), in which agriculture as the production of food for humans via crops and livestock have featured in one form or another. A constructed database of the ca. 2,100 cited experiments and simulations in the five ARs was analyzed with respect to impacts on yields via crop type, region, and whether adaptation was included. Quantitative data on impacts and adaptation in livestock farming have been extremely scarce in the ARs. The main conclusions from impact and adaptation are that crop yields will decline, but that responses have large statistical variation. Mitigation assessments in the ARs have used both bottom-up and top-down methods but need better to link emissions and their mitigation with food production and security. Relevant policy options have become broader in later ARs and included more of the social and nonproduction aspects of food security. Our overall conclusion is that agriculture and food security, which are two of the most central, critical, and imminent issues in climate change, have been dealt with an unfocussed and inconsistent manner between the IPCC five ARs. This is partly a result of not only agriculture spanning two IPCC working groups but also the very strong focus on projections from computer crop simulation modeling. For the future, we suggest a need to examine interactions between themes such as crop resource use efficiencies and to include all production and nonproduction aspects of food security in future roles for integrated assessment models.

Published
2019

15. Global wheat production with 1.5 and 2.0°C above pre-industrial warming

Author

Liu, Bing, Martre, Pierre, Ewert, Frank, Porter, John R., Challinor, Andy J, Müller, Christoph, Ruane, Alex C, Waha, Katharina, Thorburn, Peter J, Aggarwal, Pramod K, Ahmed, Mukhtar, Balkovič, Juraj, Basso, Bruno, Biernath, Christian, Bindi, Marco, Cammarano, Davide, De Sanctis, Giacomo, Dumont, Benjamin, Espadafor, Mónica, Eyshi Rezaei, Ehsan, Ferrise, Roberto, Garcia-Vila, Margarita, Gayler, Sebastian, Gao, Yujing, Horan, Heidi, Hoogenboom, Gerrit, Izaurralde, Roberto C, Jones, Curtis D, Kassie, Belay T, Kersebaum, Kurt C, Klein, Christian, Koehler, Ann-Kristin, Maiorano, Andrea, Minoli, Sara, Montesino San Martin, Manuel, Naresh Kumar, Soora, Nendel, Claas, O'Leary, Garry J, Palosuo, Taru, Priesack, Eckart, Ripoche, Dominique, Rötter, Reimund P, Semenov, Mikhail A, Stöckle, Claudio, Streck, Thilo, Supit, Iwan, Tao, Fulu, Van der Velde, Marijn, Wallach, Daniel, Wang, Enli, Webber, Heidi, Wolf, Joost, Xiao, Liujun, Zhang, Zhao, Zhao, Zhigan, Zhu, Yan, Asseng, Senthold, Liu, Bing, Martre, Pierre, Ewert, Frank, Porter, John R., Challinor, Andy J, Müller, Christoph, Ruane, Alex C, Waha, Katharina, Thorburn, Peter J, Aggarwal, Pramod K, Ahmed, Mukhtar, Balkovič, Juraj, Basso, Bruno, Biernath, Christian, Bindi, Marco, Cammarano, Davide, De Sanctis, Giacomo, Dumont, Benjamin, Espadafor, Mónica, Eyshi Rezaei, Ehsan, Ferrise, Roberto, Garcia-Vila, Margarita, Gayler, Sebastian, Gao, Yujing, Horan, Heidi, Hoogenboom, Gerrit, Izaurralde, Roberto C, Jones, Curtis D, Kassie, Belay T, Kersebaum, Kurt C, Klein, Christian, Koehler, Ann-Kristin, Maiorano, Andrea, Minoli, Sara, Montesino San Martin, Manuel, Naresh Kumar, Soora, Nendel, Claas, O'Leary, Garry J, Palosuo, Taru, Priesack, Eckart, Ripoche, Dominique, Rötter, Reimund P, Semenov, Mikhail A, Stöckle, Claudio, Streck, Thilo, Supit, Iwan, Tao, Fulu, Van der Velde, Marijn, Wallach, Daniel, Wang, Enli, Webber, Heidi, Wolf, Joost, Xiao, Liujun, Zhang, Zhao, Zhao, Zhigan, Zhu, Yan, and Asseng, Senthold

Abstract

Efforts to limit global warming to below 2°C in relation to the pre-industrial level are under way, in accordance with the 2015 Paris Agreement. However, most impact research on agriculture to date has focused on impacts of warming >2°C on mean crop yields, and many previous studies did not focus sufficiently on extreme events and yield interannual variability. Here, with the latest climate scenarios from the Half a degree Additional warming, Prognosis and Projected Impacts (HAPPI) project, we evaluated the impacts of the 2015 Paris Agreement range of global warming (1.5 and 2.0°C warming above the pre-industrial period) on global wheat production and local yield variability. A multi-crop and multi-climate model ensemble over a global network of sites developed by the Agricultural Model Intercomparison and Improvement Project (AgMIP) for Wheat was used to represent major rainfed and irrigated wheat cropping systems. Results show that projected global wheat production will change by -2.3% to 7.0% under the 1.5°C scenario and -2.4% to 10.5% under the 2.0°C scenario, compared to a baseline of 1980-2010, when considering changes in local temperature, rainfall, and global atmospheric CO2 concentration, but no changes in management or wheat cultivars. The projected impact on wheat production varies spatially; a larger increase is projected for temperate high rainfall regions than for moderate hot low rainfall and irrigated regions. Grain yields in warmer regions are more likely to be reduced than in cooler regions. Despite mostly positive impacts on global average grain yields, the frequency of extremely low yields (bottom 5 percentile of baseline distribution) and yield inter-annual variability will increase under both warming scenarios for some of the hot growing locations, including locations from the second largest global wheat producer-India, which supplies more than 14% of global wheat. The projected global impact of warming <2°C on wheat production is ther

Published
2019

16. Breeding implications of drought stress under future climate for upland rice in Brazil

Author

Ramirez-Villegas, Julian, Heinemann, Alexandre, Pereira de Castro, Adriano, Breseghello, Flavio, Navarro-Racines, Carlos E., Li, Tao, Rebolledo, Maria Camila, Challinor, Andrew J., Ramirez-Villegas, Julian, Heinemann, Alexandre, Pereira de Castro, Adriano, Breseghello, Flavio, Navarro-Racines, Carlos E., Li, Tao, Rebolledo, Maria Camila, and Challinor, Andrew J.

Abstract

Rice is the most important food crop in the developing world. For rice production systems to address the challenges of increasing demand and climate change, potential and on‐farm yield increases must be increased. Breeding is one of the main strategies toward such aim. Here, we hypothesize that climatic and atmospheric changes for the upland rice growing period in central Brazil are likely to alter environment groupings and drought stress patterns by 2050, leading to changing breeding targets during the 21st century. As a result of changes in drought stress frequency and intensity, we found reductions in productivity in the range of 200–600 kg/ha (up to 20%) and reductions in yield stability throughout virtually the entire upland rice growing area (except for the southeast). In the face of these changes, our crop simulation analysis suggests that the current strategy of the breeding program, which aims at achieving wide adaptation, should be adjusted. Based on the results for current and future climates, a weighted selection strategy for the three environmental groups that characterize the region is suggested. For the highly favorable environment (HFE, 36%–41% growing area, depending on RCP), selection should be done under both stress‐free and terminal stress conditions; for the favorable environment (FE, 27%–40%), selection should aim at testing under reproductive and terminal stress, and for the least favorable environment (LFE, 23%–27%), selection should be conducted for response to reproductive stress only and for the joint occurrence of reproductive and terminal stress. Even though there are differences in timing, it is noteworthy that stress levels are similar across environments, with 40%–60% of crop water demand unsatisfied. Efficient crop improvement targeted toward adaptive traits for drought tolerance will enhance upland rice crop system resilience under climate change.

Published
2018

17. Breeding implications of drought stress under future climate for upland rice in Brazil

Author

Ramirez-Villegas, Julian, Heinemann, Alexandre, Pereira de Castro, Adriano, Breseghello, Flavio, Navarro-Racines, Carlos E., Li, Tao, Rebolledo, Maria Camila, Challinor, Andrew J., Ramirez-Villegas, Julian, Heinemann, Alexandre, Pereira de Castro, Adriano, Breseghello, Flavio, Navarro-Racines, Carlos E., Li, Tao, Rebolledo, Maria Camila, and Challinor, Andrew J.

Abstract

Rice is the most important food crop in the developing world. For rice production systems to address the challenges of increasing demand and climate change, potential and on‐farm yield increases must be increased. Breeding is one of the main strategies toward such aim. Here, we hypothesize that climatic and atmospheric changes for the upland rice growing period in central Brazil are likely to alter environment groupings and drought stress patterns by 2050, leading to changing breeding targets during the 21st century. As a result of changes in drought stress frequency and intensity, we found reductions in productivity in the range of 200–600 kg/ha (up to 20%) and reductions in yield stability throughout virtually the entire upland rice growing area (except for the southeast). In the face of these changes, our crop simulation analysis suggests that the current strategy of the breeding program, which aims at achieving wide adaptation, should be adjusted. Based on the results for current and future climates, a weighted selection strategy for the three environmental groups that characterize the region is suggested. For the highly favorable environment (HFE, 36%–41% growing area, depending on RCP), selection should be done under both stress‐free and terminal stress conditions; for the favorable environment (FE, 27%–40%), selection should aim at testing under reproductive and terminal stress, and for the least favorable environment (LFE, 23%–27%), selection should be conducted for response to reproductive stress only and for the joint occurrence of reproductive and terminal stress. Even though there are differences in timing, it is noteworthy that stress levels are similar across environments, with 40%–60% of crop water demand unsatisfied. Efficient crop improvement targeted toward adaptive traits for drought tolerance will enhance upland rice crop system resilience under climate change.

Published
2018

18. The Hot Serial Cereal Experiment for modeling wheat response to temperature: field experiments and AgMIP-Wheat multi-model simulations

Author

Martre, Pierre, Kimball, Bruce A., Ottman, Michael J., Wall, Gerard W., White, Jeffrey W., Asseng, Senthold, Ewert, Frank, Cammarano, Davide, Maiorano, Andrea, Aggarwal, Pramod K., Anothai, Jakarat, Basso, Bruno, Biernath, Christian, Challinor, Andrew J., De Sanctis, Giacomo, Doltra, Jordi, Dumont, Benjamin, Fereres, Elias, Garcia-Vila, Margarita, Gayler, Sebastian, Hoogenboom, Gerrit, Hunt, Leslie A., Izaurralde, Roberto C., Jabloun, Mohamed, Jones, Curtis D., Kassie, Belay T., Kersebaum, Kurt C., Koehler, Ann-Kristin, Müller, Christoph, Kumar, Soora Naresh, Liu, Bing, Lobell, David B., Nendel, Claas, O'Leary, Garry, Olesen, Jørgen E., Palosuo, Taru, Priesack, Eckart, Rezaei, Ehsan Eyshi, Ripoche, Dominique, Rötter, Reimund P., Semenov, Mikhail A., Stöckle, Claudio, Stratonovitch, Pierre, Streck, Thilo, Supit, Iwan, Tao, Fulu, Thorburn, Peter, Waha, Katharina, Wang, Enli, Wolf, Joost, Zhao, Zhigan, Zhu, Yan, Martre, Pierre, Kimball, Bruce A., Ottman, Michael J., Wall, Gerard W., White, Jeffrey W., Asseng, Senthold, Ewert, Frank, Cammarano, Davide, Maiorano, Andrea, Aggarwal, Pramod K., Anothai, Jakarat, Basso, Bruno, Biernath, Christian, Challinor, Andrew J., De Sanctis, Giacomo, Doltra, Jordi, Dumont, Benjamin, Fereres, Elias, Garcia-Vila, Margarita, Gayler, Sebastian, Hoogenboom, Gerrit, Hunt, Leslie A., Izaurralde, Roberto C., Jabloun, Mohamed, Jones, Curtis D., Kassie, Belay T., Kersebaum, Kurt C., Koehler, Ann-Kristin, Müller, Christoph, Kumar, Soora Naresh, Liu, Bing, Lobell, David B., Nendel, Claas, O'Leary, Garry, Olesen, Jørgen E., Palosuo, Taru, Priesack, Eckart, Rezaei, Ehsan Eyshi, Ripoche, Dominique, Rötter, Reimund P., Semenov, Mikhail A., Stöckle, Claudio, Stratonovitch, Pierre, Streck, Thilo, Supit, Iwan, Tao, Fulu, Thorburn, Peter, Waha, Katharina, Wang, Enli, Wolf, Joost, Zhao, Zhigan, and Zhu, Yan

Abstract

The data set reported here includes the part of a Hot Serial Cereal Experiment (HSC) experiment recently used in the AgMIP-Wheat project to analyze the uncertainty of 30 wheat models and quantify their response to temperature. The HSC experiment was conducted in an open-field in a semiarid environment in the southwest USA. The data reported herewith include one hard red spring wheat cultivar (Yecora Rojo) sown approximately every six weeks from December to August for a two-year period for a total of 11 planting dates out of the 15 of the entire HSC experiment. The treatments were chosen to avoid any effect of frost on grain yields. On late fall, winter and early spring plantings temperature free-air controlled enhancement (T-FACE) apparatus utilizing infrared heaters with supplemental irrigation were used to increase air temperature by 1.3°C/2.7°C (day/night) with conditions equivalent to raising air temperature at constant relative humidity (i.e. as expected with global warming) during the whole crop growth cycle. Experimental data include local daily weather data, soil characteristics and initial conditions, detailed crop measurements taken at three growth stages during the growth cycle, and cultivar information. Simulations include both daily in-season and end-of-season results from 30 wheat models.

Published
2018

19. The uncertainty of crop yield projections is reduced by improved temperature response functions

Author

Commonwealth Scientific and Industrial Research Organisation (Australia), Chinese Academy of Sciences, China Scholarship Council, Ministry of Education of the People's Republic of China, Institut National de la Recherche Agronomique (France), European Commission, International Food Policy Research Institute (US), CGIAR (France), Department of Agriculture (US), Federal Ministry of Education and Research (Germany), Deutsche Gesellschaft für Internationale Zusammenarbeit, Danish Council for Strategic Research, Federal Ministry of Food and Agriculture (Germany), Finnish Ministry of Agriculture and Forestry, National Natural Science Foundation of China, Helmholtz Association, Grains Research and Development Corporation (Australia), Texas AgriLife Research, Texas A&M University, National Institute of Food and Agriculture (US), Wang, Enli, Martre, Pierre, Zhao, Zhigan, Ewert, Frank, Maiorano, Andrea, Rötter, Reimund P., Kimball, Bruce A., Ottman, Michael J., Wall, Gerard W., White, Jefrrey W., Reynolds, Matthew, Alderman, Phillip, Aggarwal, Pramod K., Anothai, Jakarat, Basso, Bruno, Biernath, Christian, Cammarano, Davide, Challinor, Andrew J., De Sanctis, Giacomo, Doltra, Jordi, Dumont, Benjamin, Fereres Castiel, Elías, García Vila, Margarita, Gayler, Sebastian, Hoogenboom, Gerrit, Hunt, Leslie A., Izaurralde, Roberto C., Jabloun, Mohamed, Jones, Curtis D., Kersebaum, Kurt C., Koehler, Ann-Kristin, Liu, Leilei, Müller, Christoph, Kumar, Soora Naresh, Nendel, Claas, O'Leary, Garry, Olesen, Jørgen E., Palosuo, Taru, Priesack, Eckart, Rezaei, Ehsan Eyshi, Ripoche, Dominique, Ruane, Alexander C., Semenov, Mikhail A., Shcherbak, Iurii, Stöckle, Claudio, Stratonovitch, Pierre, Streck, Thilo, Supit, Iwan, Tao, Fulu, Thorburn, Peter, Waha, Katharina, Wallach, Daniel, Wang, Zhimin, Wolf, Joost, Zhu, Yan, Asseng, Senthold, Commonwealth Scientific and Industrial Research Organisation (Australia), Chinese Academy of Sciences, China Scholarship Council, Ministry of Education of the People's Republic of China, Institut National de la Recherche Agronomique (France), European Commission, International Food Policy Research Institute (US), CGIAR (France), Department of Agriculture (US), Federal Ministry of Education and Research (Germany), Deutsche Gesellschaft für Internationale Zusammenarbeit, Danish Council for Strategic Research, Federal Ministry of Food and Agriculture (Germany), Finnish Ministry of Agriculture and Forestry, National Natural Science Foundation of China, Helmholtz Association, Grains Research and Development Corporation (Australia), Texas AgriLife Research, Texas A&M University, National Institute of Food and Agriculture (US), Wang, Enli, Martre, Pierre, Zhao, Zhigan, Ewert, Frank, Maiorano, Andrea, Rötter, Reimund P., Kimball, Bruce A., Ottman, Michael J., Wall, Gerard W., White, Jefrrey W., Reynolds, Matthew, Alderman, Phillip, Aggarwal, Pramod K., Anothai, Jakarat, Basso, Bruno, Biernath, Christian, Cammarano, Davide, Challinor, Andrew J., De Sanctis, Giacomo, Doltra, Jordi, Dumont, Benjamin, Fereres Castiel, Elías, García Vila, Margarita, Gayler, Sebastian, Hoogenboom, Gerrit, Hunt, Leslie A., Izaurralde, Roberto C., Jabloun, Mohamed, Jones, Curtis D., Kersebaum, Kurt C., Koehler, Ann-Kristin, Liu, Leilei, Müller, Christoph, Kumar, Soora Naresh, Nendel, Claas, O'Leary, Garry, Olesen, Jørgen E., Palosuo, Taru, Priesack, Eckart, Rezaei, Ehsan Eyshi, Ripoche, Dominique, Ruane, Alexander C., Semenov, Mikhail A., Shcherbak, Iurii, Stöckle, Claudio, Stratonovitch, Pierre, Streck, Thilo, Supit, Iwan, Tao, Fulu, Thorburn, Peter, Waha, Katharina, Wallach, Daniel, Wang, Zhimin, Wolf, Joost, Zhu, Yan, and Asseng, Senthold

Abstract

Increasing the accuracy of crop productivity estimates is a key element in planning adaptation strategies to ensure global food security under climate change. Process-based crop models are effective means to project climate impact on crop yield, but have large uncertainty in yield simulations. Here, we show that variations in the mathematical functions currently used to simulate temperature responses of physiological processes in 29 wheat models account for >50% of uncertainty in simulated grain yields for mean growing season temperatures from 14 °C to 33 °C. We derived a set of new temperature response functions that when substituted in four wheat models reduced the error in grain yield simulations across seven global sites with different temperature regimes by 19% to 50% (42% average). We anticipate the improved temperature responses to be a key step to improve modelling of crops under rising temperature and climate change, leading to higher skill of crop yield projections.

Published
2017

20. The International Heat Stress Genotype Experiment for modeling wheat response to heat: field experiments and AgMIP-Wheat multi-model simulations

Author

Martre, Pierre, Reynolds, Matthew, Asseng, Senthold, Ewert, Frank, Alderman, Phillip, Cammarano, Davide, Maiorano, Andrea, Ruane, Alexander C., Aggarwal, Pramod K., Anothai, Jakarat, Basso, Bruno, Biernath, Christian, Challinor, Andrew J., De Sanctis, Giacomo, Doltra, Jordi, Dumont, Benjamin, Fereres Castiel, Elías, García Vila, Margarita, Gayler, Sebastian, Hoogenboom, Gerrit, Hunt, Leslie A., Izaurralde, Roberto C., Jabloun, Mohamed, Jones, Curtis D., Kassie, Belay T., Kersebaum, Kurt C., Koehler, Ann-Kristin, Müller, Christoph, Kumar, Soora Naresh, Liu, Bing, Lobell, David B., Nendel, Claas, O'Leary, Garry, Olesen, Jørgen E., Palosuo, Taru, Priesack, Eckart, Rezaei, Ehsan Eyshi, Ripoche, Dominique, Rötter, Reimund P., Semenov, Mikhail A., Stöckle, Claudio, Stratonovitch, Pierre, Streck, Thilo, Supit, Iwan, Tao, Fulu, Thorburn, Peter, Waha, Katharina, Wang, Enli, White, Jefrrey W., Wolf, Joost, Zhao, Zhigan, Zhu, Yan, Martre, Pierre, Reynolds, Matthew, Asseng, Senthold, Ewert, Frank, Alderman, Phillip, Cammarano, Davide, Maiorano, Andrea, Ruane, Alexander C., Aggarwal, Pramod K., Anothai, Jakarat, Basso, Bruno, Biernath, Christian, Challinor, Andrew J., De Sanctis, Giacomo, Doltra, Jordi, Dumont, Benjamin, Fereres Castiel, Elías, García Vila, Margarita, Gayler, Sebastian, Hoogenboom, Gerrit, Hunt, Leslie A., Izaurralde, Roberto C., Jabloun, Mohamed, Jones, Curtis D., Kassie, Belay T., Kersebaum, Kurt C., Koehler, Ann-Kristin, Müller, Christoph, Kumar, Soora Naresh, Liu, Bing, Lobell, David B., Nendel, Claas, O'Leary, Garry, Olesen, Jørgen E., Palosuo, Taru, Priesack, Eckart, Rezaei, Ehsan Eyshi, Ripoche, Dominique, Rötter, Reimund P., Semenov, Mikhail A., Stöckle, Claudio, Stratonovitch, Pierre, Streck, Thilo, Supit, Iwan, Tao, Fulu, Thorburn, Peter, Waha, Katharina, Wang, Enli, White, Jefrrey W., Wolf, Joost, Zhao, Zhigan, and Zhu, Yan

Abstract

he data set contains a portion of the International Heat Stress Genotype Experiment (IHSGE) data used in the AgMIP-Wheat project to analyze the uncertainty of 30 wheat crop models and quantify the impact of heat on global wheat yield productivity. It includes two spring wheat cultivars grown during two consecutive winter cropping cycles at hot, irrigated, and low latitude sites in Mexico (Ciudad Obregon and Tlaltizapan), Egypt (Aswan), India (Dharwar), the Sudan (Wad Medani), and Bangladesh (Dinajpur). Experiments in Mexico included normal (November-December) and late (January-March) sowing dates. Data include local daily weather data, soil characteristics and initial soil conditions, crop measurements (anthesis and maturity dates, anthesis and final total above ground biomass, final grain yields and yields components), and cultivar information. Simulations include both daily in-season and end-of-season results from 30 wheat models.

Published
2017

21. Timescales of transformational climate change adaptation in sub-Saharan African agriculture

Author

Rippke, Ulrike, Ramirez-Villegas, Julian, Jarvis, Andy, Vermeulen, Sonja J., Parker, Louis, Mer, Flora, Diekkrüger, Bernd, Challinor, Andrew J., Howden, Mark, Rippke, Ulrike, Ramirez-Villegas, Julian, Jarvis, Andy, Vermeulen, Sonja J., Parker, Louis, Mer, Flora, Diekkrüger, Bernd, Challinor, Andrew J., and Howden, Mark

Abstract

Climate change is projected to constitute a significant threat to food security if no adaptation actions are taken. Transformation of agricultural systems, for example switching crop types or moving out of agriculture, is projected to be necessary in some cases. However, little attention has been paid to the timing of these transformations. Here, we develop a temporal uncertainty framework using the CMIP5 ensemble to assess when and where cultivation of key crops in sub-Saharan Africa becomes unviable. We report potential transformational changes for all major crops during the twenty-first century, as climates shift and areas become unsuitable. For most crops, however, transformation is limited to small pockets (<15% of area), and only for beans, maize and banana is transformation more widespread (â 1/430% area for maize and banana, 60% for beans). We envisage three overlapping adaptation phases to enable projected transformational changes: an incremental adaptation phase focused on improvements to crops and management, a preparatory phase that establishes appropriate policies and enabling environments, and a transformational adaptation phase in which farmers substitute crops, explore alternative livelihoods strategies, or relocate. To best align policies with production triggers for no-regret actions, monitoring capacities to track farming systems as well as climate are needed.

Published
2016

23. The Impact of Parameterized Convection on the Simulation of Crop Processes

Author

Garcia-Carreras, Luis, Challinor, A. J., Parkes, B. J., Birch, C. E., Nicklin, K. J., Parker, D. J., Garcia-Carreras, Luis, Challinor, A. J., Parkes, B. J., Birch, C. E., Nicklin, K. J., and Parker, D. J.

Abstract

Global climate and weather models are a key tool for the prediction of future crop productivity, but they all rely on parameterizations of atmospheric convection, which often produce significant biases in rainfall characteristics over the tropics. The authors evaluate the impact of these biases by driving the General Large Area Model for annual crops (GLAM) with regional-scale atmospheric simulations of one cropping season over West Africa at different resolutions, with and without a parameterization of convection, and compare these with a GLAM run driven by observations. The parameterization of convection produces too light and frequent rainfall throughout the domain, as compared with the short, localized, high-intensity events in the observations and in the convection-permitting runs. Persistent light rain increases surface evaporation, and much heavier rainfall is required to trigger planting. Planting is therefore delayed in the runs with parameterized convection and occurs at a seasonally cooler time, altering the environmental conditions experienced by the crops. Even at high resolutions, runs driven by parameterized convection underpredict the small-scale variability in yields produced by realistic rainfall patterns. Correcting the distribution of rainfall frequencies and intensities before use in crop models will improve the process-based representation of the crop life cycle, increasing confidence in the predictions of crop yield. The rainfall biases described here are a common feature of parameterizations of convection, and therefore the crop-model errors described are likely to occur when using any global weather or climate model, thus remaining hidden when using climate-model intercomparisons to evaluate uncertainty.

Published
2015
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24. Technical Summary

Author

Field, C. B., Barros, V. R., Mach, K. J., Mastrandrea, M. D., van Aalst, M., Adger, W. N., Arent, D. J., Barnett, J., Betts, R., Bilir, T. E., Birkmann, J., Carmin, J., Chadee, D. D., Challinor, A. J., Chatterjee, M., Cramer, W., Davidson, D. J., Estrada, Y. O., Gattuso, J. P., Hijioka, Y., Hoegh-Guldberg, O., Huang, H. Q., Insarov, G. E., Jones, R. N., Kovats, R. S., Lankao, P. Romero, Larsen, J. N., Losada, I. J., Marengo, J. A., McLean, R. F., Mearns, L. O., Mechler, R., Morton, J. F., Niang, I., Oki, T., Olwoch, J. M., Opondo, M., Poloczanska, E. S., Pörtner, H. O., Redsteer, M. H., Reisinger, A., Revi, A., Schmidt, D. N., Shaw, M. R., Solecki, W., Stone, D. A., Stone, J. M. R., Strzepek, K. M., Suarez, A. G., Tschakert, P., Valentini, R., Vicuña, S., Villamizar, A., Vincent, K. E., Warren, R., White, L. L., Wilbanks, T. J., Wong, P. P., Yohe, G. W., Field, C. B., Barros, V. R., Mach, K. J., Mastrandrea, M. D., van Aalst, M., Adger, W. N., Arent, D. J., Barnett, J., Betts, R., Bilir, T. E., Birkmann, J., Carmin, J., Chadee, D. D., Challinor, A. J., Chatterjee, M., Cramer, W., Davidson, D. J., Estrada, Y. O., Gattuso, J. P., Hijioka, Y., Hoegh-Guldberg, O., Huang, H. Q., Insarov, G. E., Jones, R. N., Kovats, R. S., Lankao, P. Romero, Larsen, J. N., Losada, I. J., Marengo, J. A., McLean, R. F., Mearns, L. O., Mechler, R., Morton, J. F., Niang, I., Oki, T., Olwoch, J. M., Opondo, M., Poloczanska, E. S., Pörtner, H. O., Redsteer, M. H., Reisinger, A., Revi, A., Schmidt, D. N., Shaw, M. R., Solecki, W., Stone, D. A., Stone, J. M. R., Strzepek, K. M., Suarez, A. G., Tschakert, P., Valentini, R., Vicuña, S., Villamizar, A., Vincent, K. E., Warren, R., White, L. L., Wilbanks, T. J., Wong, P. P., and Yohe, G. W.

Published
2014

25. Technical Summary

Author

Field, C. B., Barros, V. R., Mach, K. J., Mastrandrea, M. D., van Aalst, M., Adger, W. N., Arent, D. J., Barnett, J., Betts, R., Bilir, T. E., Birkmann, J., Carmin, J., Chadee, D. D., Challinor, A. J., Chatterjee, M., Cramer, W., Davidson, D. J., Estrada, Y. O., Gattuso, J. P., Hijioka, Y., Hoegh-Guldberg, O., Huang, H. Q., Insarov, G. E., Jones, R. N., Kovats, R. S., Lankao, P. Romero, Larsen, J. N., Losada, I. J., Marengo, J. A., McLean, R. F., Mearns, L. O., Mechler, R., Morton, J. F., Niang, I., Oki, T., Olwoch, J. M., Opondo, M., Poloczanska, E. S., Pörtner, H. O., Redsteer, M. H., Reisinger, A., Revi, A., Schmidt, D. N., Shaw, M. R., Solecki, W., Stone, D. A., Stone, J. M. R., Strzepek, K. M., Suarez, A. G., Tschakert, P., Valentini, R., Vicuña, S., Villamizar, A., Vincent, K. E., Warren, R., White, L. L., Wilbanks, T. J., Wong, P. P., Yohe, G. W., Field, C. B., Barros, V. R., Mach, K. J., Mastrandrea, M. D., van Aalst, M., Adger, W. N., Arent, D. J., Barnett, J., Betts, R., Bilir, T. E., Birkmann, J., Carmin, J., Chadee, D. D., Challinor, A. J., Chatterjee, M., Cramer, W., Davidson, D. J., Estrada, Y. O., Gattuso, J. P., Hijioka, Y., Hoegh-Guldberg, O., Huang, H. Q., Insarov, G. E., Jones, R. N., Kovats, R. S., Lankao, P. Romero, Larsen, J. N., Losada, I. J., Marengo, J. A., McLean, R. F., Mearns, L. O., Mechler, R., Morton, J. F., Niang, I., Oki, T., Olwoch, J. M., Opondo, M., Poloczanska, E. S., Pörtner, H. O., Redsteer, M. H., Reisinger, A., Revi, A., Schmidt, D. N., Shaw, M. R., Solecki, W., Stone, D. A., Stone, J. M. R., Strzepek, K. M., Suarez, A. G., Tschakert, P., Valentini, R., Vicuña, S., Villamizar, A., Vincent, K. E., Warren, R., White, L. L., Wilbanks, T. J., Wong, P. P., and Yohe, G. W.

Published
2014

26. Food security and food production systems

Author

Porter, John Roy, Xie, Liyong, Challinor, Andrew J., Cochrane, Kevern, Howden, S. Mark, Iqbal, Muhammed Mohsin, Lobell, David B., Travasso, Maria Isabel, Porter, John Roy, Xie, Liyong, Challinor, Andrew J., Cochrane, Kevern, Howden, S. Mark, Iqbal, Muhammed Mohsin, Lobell, David B., and Travasso, Maria Isabel

Published
2014

27. Food security and food production systems

Author

Porter, John Roy, Xie, Liyong, Challinor, Andrew J., Cochrane, Kevern, Howden, S. Mark, Iqbal, Muhammed Mohsin, Lobell, David B., Travasso, Maria Isabel, Porter, John Roy, Xie, Liyong, Challinor, Andrew J., Cochrane, Kevern, Howden, S. Mark, Iqbal, Muhammed Mohsin, Lobell, David B., and Travasso, Maria Isabel

Published
2014

28. Food security and food production systems

Author

Porter, John Roy, Xie, Liyong, Challinor, Andrew J., Cochrane, Kevern, Howden, S. Mark, Iqbal, Muhammed Mohsin, Lobell, David B., Travasso, Maria Isabel, Porter, John Roy, Xie, Liyong, Challinor, Andrew J., Cochrane, Kevern, Howden, S. Mark, Iqbal, Muhammed Mohsin, Lobell, David B., and Travasso, Maria Isabel

Published
2014

29. Food security and food production systems

Author

Porter, John Roy, Xie, Liyong, Challinor, Andrew J., Cochrane, Kevern, Howden, S. Mark, Iqbal, Muhammed Mohsin, Lobell, David B., Travasso, Maria Isabel, Porter, John Roy, Xie, Liyong, Challinor, Andrew J., Cochrane, Kevern, Howden, S. Mark, Iqbal, Muhammed Mohsin, Lobell, David B., and Travasso, Maria Isabel

Published
2014

30. Prediction of seasonal climate-induced variations in global food production

Author

Iizumi, Toshichika, Sakuma, Hirofumi, Yokozawa, Masayuki, Luo, Jing-Jia, Challinor, Andrew J., Brown, Molly E., Sakurai, Gen, Yamagata, Toshio, Iizumi, Toshichika, Sakuma, Hirofumi, Yokozawa, Masayuki, Luo, Jing-Jia, Challinor, Andrew J., Brown, Molly E., Sakurai, Gen, and Yamagata, Toshio

Abstract

Consumers, including the poor in many countries, are increasingly dependent on food imports(1) and are thus exposed to variations in yields, production and export prices in the major food-producing regions of the world. National governments and commercial entities are therefore paying increased attention to the cropping forecasts of important food-exporting countries as well as to their own domestic food production. Given the increased volatility of food markets and the rising incidence of climatic extremes affecting food production, food price spikes may increase in prevalence in future years(2-4). Here we present a global assessment of the reliability of crop failure hindcasts for major crops at two lead times derived by linking ensemble seasonal climatic forecasts with statistical crop models. We found that moderate-to-marked yield loss over a substantial percentage (26-33 of the harvested area of these crops is reliably predictable if climatic forecasts are near perfect. However, only rice and wheat production are reliably predictable at three months before the harvest using within-season hindcasts. The reliabilities of estimates varied substantially by crop-rice and wheat yields were the most predictable, followed by soybean and maize. The reasons for variation in the reliability of the estimates included the differences in crop sensitivity to the climate and the technology used by the crop-producing regions. Our findings reveal that the use of seasonal climatic forecasts to predict crop failures will be useful for monitoring global food production and will encourage the adaptation of food systems to climatic extremes.

Published
2013

31. Addressing uncertainty in adaptation planning for agriculture

Author

Vermeulen, Sonja Joy, Challinor, Andrew J., Thornton, Philip K., Campbell, Bruce M., Eriyagama, Nishadi, Vervoort, Joost M., Kinyangi, James, Jarvis, Andy, Laderach, Peter, Ramirez-Villegas, Julian, Nicklin, Kathryn J., Hawkins, Ed, Smith, Daniel R., Vermeulen, Sonja Joy, Challinor, Andrew J., Thornton, Philip K., Campbell, Bruce M., Eriyagama, Nishadi, Vervoort, Joost M., Kinyangi, James, Jarvis, Andy, Laderach, Peter, Ramirez-Villegas, Julian, Nicklin, Kathryn J., Hawkins, Ed, and Smith, Daniel R.

Abstract

We present a framework for prioritizing adaptation approaches at a range of timeframes. The framework is illustrated by four case studies from developing countries, each with associated characterization of uncertainty. Two cases on near-term adaptation planning in Sri Lanka and on stakeholder scenario exercises in East Africa show how the relative utility of capacity vs. impact approaches to adaptation planning differ with level of uncertainty and associated lead time. An additional two cases demonstrate that it is possible to identify uncertainties that are relevant to decision making in specific timeframes and circumstances. The case on coffee in Latin America identifies altitudinal thresholds at which incremental vs. transformative adaptation pathways are robust options. The final case uses three crop-climate simulation studies to demonstrate how uncertainty can be characterized at different time horizons to discriminate where robust adaptation options are possible. We find that impact approaches, which use predictive models, are increasingly useful over longer lead times and at higher levels of greenhouse gas emissions. We also find that extreme events are important in determining predictability across a broad range of timescales. The results demonstrate the potential for robust knowledge and actions in the face of uncertainty.

Published
2013

32. Threats to an ecosystem service:Pressures on pollinators

Author

Vanbergen, Adam J., Garratt, Mike P., Baude, Mathilde, Biesmeijer, Jacobus C., Britton, Nicholas F., Brown, Mark J.F., Brown, Mike, Bryden, John, Budge, Giles E., Bull, James C., Carvell, Claire, Challinor, Andrew J., Connolly, Christopher N., Evans, David J., Feil, Edward J., Greco, Mark K., Heard, Matthew S., Jansen, Vincent A.A., Keeling, Matt J., Kunin, William E., Marris, Gay C., Memmott, Jane, Murray, James T., Nicolson, Susan W., Osborne, Juliet L., Paxton, Robert J., Pirk, Christian W.W., Polce, Chiara, Potts, Simon G., Priest, Nicholas K., Raine, Nigel E., Roberts, Stuart, Ryabov, Eugene V., Shafir, Sharoni, Shirley, Mark D.F., Simpson, Stephen J., Stevenson, Philip C., Stone, Graham N., Termansen, Mette, Wright, Geraldine A., Vanbergen, Adam J., Garratt, Mike P., Baude, Mathilde, Biesmeijer, Jacobus C., Britton, Nicholas F., Brown, Mark J.F., Brown, Mike, Bryden, John, Budge, Giles E., Bull, James C., Carvell, Claire, Challinor, Andrew J., Connolly, Christopher N., Evans, David J., Feil, Edward J., Greco, Mark K., Heard, Matthew S., Jansen, Vincent A.A., Keeling, Matt J., Kunin, William E., Marris, Gay C., Memmott, Jane, Murray, James T., Nicolson, Susan W., Osborne, Juliet L., Paxton, Robert J., Pirk, Christian W.W., Polce, Chiara, Potts, Simon G., Priest, Nicholas K., Raine, Nigel E., Roberts, Stuart, Ryabov, Eugene V., Shafir, Sharoni, Shirley, Mark D.F., Simpson, Stephen J., Stevenson, Philip C., Stone, Graham N., Termansen, Mette, and Wright, Geraldine A.

Abstract

Insect pollinators of crops and wild plants are under threat globally and their decline or loss could have profound economic and environmental consequences. Here, we argue that multiple anthropogenic pressures - including land-use intensification, climate change, and the spread of alien species and diseases - are primarily responsible for insect-pollinator declines. We show that a complex interplay between pressures (eg lack of food sources, diseases, and pesticides) and biological processes (eg species dispersal and interactions) at a range of scales (from genes to ecosystems) underpins the general decline in insect-pollinator populations. Interdisciplinary research on the nature and impacts of these interactions will be needed if human food security and ecosystem function are to be preserved. We highlight key areas that require research focus and outline some practical steps to alleviate the pressures on pollinators and the pollination services they deliver to wild and crop plants., Insect pollinators of crops and wild plants are under threat globally and their decline or loss could have profound economic and environmental consequences. Here, we argue that multiple anthropogenic pressures - including land-use intensification, climate change, and the spread of alien species and diseases - are primarily responsible for insect-pollinator declines. We show that a complex interplay between pressures (eg lack of food sources, diseases, and pesticides) and biological processes (eg species dispersal and interactions) at a range of scales (from genes to ecosystems) underpins the general decline in insect-pollinator populations. Interdisciplinary research on the nature and impacts of these interactions will be needed if human food security and ecosystem function are to be preserved. We highlight key areas that require research focus and outline some practical steps to alleviate the pressures on pollinators and the pollination services they deliver to wild and crop plants.

Published
2013

33. Threats to an ecosystem service:Pressures on pollinators

Author

Vanbergen, Adam J., Garratt, Mike P., Baude, Mathilde, Biesmeijer, Jacobus C., Britton, Nicholas F., Brown, Mark J.F., Brown, Mike, Bryden, John, Budge, Giles E., Bull, James C., Carvell, Claire, Challinor, Andrew J., Connolly, Christopher N., Evans, David J., Feil, Edward J., Greco, Mark K., Heard, Matthew S., Jansen, Vincent A.A., Keeling, Matt J., Kunin, William E., Marris, Gay C., Memmott, Jane, Murray, James T., Nicolson, Susan W., Osborne, Juliet L., Paxton, Robert J., Pirk, Christian W.W., Polce, Chiara, Potts, Simon G., Priest, Nicholas K., Raine, Nigel E., Roberts, Stuart, Ryabov, Eugene V., Shafir, Sharoni, Shirley, Mark D.F., Simpson, Stephen J., Stevenson, Philip C., Stone, Graham N., Termansen, Mette, Wright, Geraldine A., Vanbergen, Adam J., Garratt, Mike P., Baude, Mathilde, Biesmeijer, Jacobus C., Britton, Nicholas F., Brown, Mark J.F., Brown, Mike, Bryden, John, Budge, Giles E., Bull, James C., Carvell, Claire, Challinor, Andrew J., Connolly, Christopher N., Evans, David J., Feil, Edward J., Greco, Mark K., Heard, Matthew S., Jansen, Vincent A.A., Keeling, Matt J., Kunin, William E., Marris, Gay C., Memmott, Jane, Murray, James T., Nicolson, Susan W., Osborne, Juliet L., Paxton, Robert J., Pirk, Christian W.W., Polce, Chiara, Potts, Simon G., Priest, Nicholas K., Raine, Nigel E., Roberts, Stuart, Ryabov, Eugene V., Shafir, Sharoni, Shirley, Mark D.F., Simpson, Stephen J., Stevenson, Philip C., Stone, Graham N., Termansen, Mette, and Wright, Geraldine A.

Abstract

Insect pollinators of crops and wild plants are under threat globally and their decline or loss could have profound economic and environmental consequences. Here, we argue that multiple anthropogenic pressures - including land-use intensification, climate change, and the spread of alien species and diseases - are primarily responsible for insect-pollinator declines. We show that a complex interplay between pressures (eg lack of food sources, diseases, and pesticides) and biological processes (eg species dispersal and interactions) at a range of scales (from genes to ecosystems) underpins the general decline in insect-pollinator populations. Interdisciplinary research on the nature and impacts of these interactions will be needed if human food security and ecosystem function are to be preserved. We highlight key areas that require research focus and outline some practical steps to alleviate the pressures on pollinators and the pollination services they deliver to wild and crop plants., Insect pollinators of crops and wild plants are under threat globally and their decline or loss could have profound economic and environmental consequences. Here, we argue that multiple anthropogenic pressures - including land-use intensification, climate change, and the spread of alien species and diseases - are primarily responsible for insect-pollinator declines. We show that a complex interplay between pressures (eg lack of food sources, diseases, and pesticides) and biological processes (eg species dispersal and interactions) at a range of scales (from genes to ecosystems) underpins the general decline in insect-pollinator populations. Interdisciplinary research on the nature and impacts of these interactions will be needed if human food security and ecosystem function are to be preserved. We highlight key areas that require research focus and outline some practical steps to alleviate the pressures on pollinators and the pollination services they deliver to wild and crop plants.

Published
2013

34. Prediction of seasonal climate-induced variations in global food production

Author

Iizumi, Toshichika, Sakuma, Hirofumi, Yokozawa, Masayuki, Luo, Jing-Jia, Challinor, Andrew J., Brown, Molly E., Sakurai, Gen, Yamagata, Toshio, Iizumi, Toshichika, Sakuma, Hirofumi, Yokozawa, Masayuki, Luo, Jing-Jia, Challinor, Andrew J., Brown, Molly E., Sakurai, Gen, and Yamagata, Toshio

Abstract

Consumers, including the poor in many countries, are increasingly dependent on food imports(1) and are thus exposed to variations in yields, production and export prices in the major food-producing regions of the world. National governments and commercial entities are therefore paying increased attention to the cropping forecasts of important food-exporting countries as well as to their own domestic food production. Given the increased volatility of food markets and the rising incidence of climatic extremes affecting food production, food price spikes may increase in prevalence in future years(2-4). Here we present a global assessment of the reliability of crop failure hindcasts for major crops at two lead times derived by linking ensemble seasonal climatic forecasts with statistical crop models. We found that moderate-to-marked yield loss over a substantial percentage (26-33 of the harvested area of these crops is reliably predictable if climatic forecasts are near perfect. However, only rice and wheat production are reliably predictable at three months before the harvest using within-season hindcasts. The reliabilities of estimates varied substantially by crop-rice and wheat yields were the most predictable, followed by soybean and maize. The reasons for variation in the reliability of the estimates included the differences in crop sensitivity to the climate and the technology used by the crop-producing regions. Our findings reveal that the use of seasonal climatic forecasts to predict crop failures will be useful for monitoring global food production and will encourage the adaptation of food systems to climatic extremes.

Published
2013

35. Addressing uncertainty in adaptation planning for agriculture

Author

Vermeulen, Sonja Joy, Challinor, Andrew J., Thornton, Philip K., Campbell, Bruce M., Eriyagama, Nishadi, Vervoort, Joost M., Kinyangi, James, Jarvis, Andy, Laderach, Peter, Ramirez-Villegas, Julian, Nicklin, Kathryn J., Hawkins, Ed, Smith, Daniel R., Vermeulen, Sonja Joy, Challinor, Andrew J., Thornton, Philip K., Campbell, Bruce M., Eriyagama, Nishadi, Vervoort, Joost M., Kinyangi, James, Jarvis, Andy, Laderach, Peter, Ramirez-Villegas, Julian, Nicklin, Kathryn J., Hawkins, Ed, and Smith, Daniel R.

Abstract

We present a framework for prioritizing adaptation approaches at a range of timeframes. The framework is illustrated by four case studies from developing countries, each with associated characterization of uncertainty. Two cases on near-term adaptation planning in Sri Lanka and on stakeholder scenario exercises in East Africa show how the relative utility of capacity vs. impact approaches to adaptation planning differ with level of uncertainty and associated lead time. An additional two cases demonstrate that it is possible to identify uncertainties that are relevant to decision making in specific timeframes and circumstances. The case on coffee in Latin America identifies altitudinal thresholds at which incremental vs. transformative adaptation pathways are robust options. The final case uses three crop-climate simulation studies to demonstrate how uncertainty can be characterized at different time horizons to discriminate where robust adaptation options are possible. We find that impact approaches, which use predictive models, are increasingly useful over longer lead times and at higher levels of greenhouse gas emissions. We also find that extreme events are important in determining predictability across a broad range of timescales. The results demonstrate the potential for robust knowledge and actions in the face of uncertainty.

Published
2013

36. Prediction of climate-induced variations in global food production levels: current status and future potential of modelling

Author

IIZUMI, TOSHICHIKA, 飯泉, 仁之直, SAKUMA, HIROFUMI, Yokozawa, Masayuki, LUO, JINGJIA, CHALLINOR, ANDREW J, SAKURAI, GEN, YAMAGATA, TOSHIO, 佐久間, 弘文, 横沢, 正幸, 羅, 京佳, 櫻井, 玄, 山形, 俊男, IIZUMI, TOSHICHIKA, 飯泉, 仁之直, SAKUMA, HIROFUMI, Yokozawa, Masayuki, LUO, JINGJIA, CHALLINOR, ANDREW J, SAKURAI, GEN, YAMAGATA, TOSHIO, 佐久間, 弘文, 横沢, 正幸, 羅, 京佳, 櫻井, 玄, and 山形, 俊男

37. Transformative adaptation and implications for transdisciplinary climate change research

Author

Hellin, Jonathan, Amarnath, Giriraj, Challinor, Andrew J., Fisher, Eleanor, Girvetz, Evan H., Guo, Z., Hodur, Janet, Loboguerrero, Ana María, Pacillo, Grazia, Rose, S., Schutz, Tonja, Valencia, L., You, L., Hellin, Jonathan, Amarnath, Giriraj, Challinor, Andrew J., Fisher, Eleanor, Girvetz, Evan H., Guo, Z., Hodur, Janet, Loboguerrero, Ana María, Pacillo, Grazia, Rose, S., Schutz, Tonja, Valencia, L., and You, L.

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