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6. AgMIP-Wheat multi-model simulations on climate change impact and adaptation for global wheat

Author

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

Published
2023
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8. An integrated approach to maintaining cereal productivity under climate change

Author

Reynolds, Matthew P., Quilligan, Emma, Aggarwal, Pramod K., Bansal, Kailash C., Cavalieri, Anthony J., Chapman, Scott C., Chapotin, Saharah M., Datta, Swapan K., Duveiller, Etienne, Gill, Kulvinder S., Jagadish, Krishna S.V., Joshi, Arun K., Koehler, Ann-Kristin, Kosina, Petr, Krishnan, Srivalli, Lafitte, Renee, Mahala, Rajendra S., Muthurajan, Raveendran, Paterson, Andrew H., Prasanna, Boddupalli M., Rakshit, Sujay, Rosegrant, Mark W., Sharma, Indu, Singh, Ravi P., Sivasankar, Shoba, Vadez, Vincent, Valluru, Ravi, Vara Prasad, P.V., and Yadav, Om Prakash

Published
2016
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9. Climate Change Impact and Adaptation for Wheat Protein

Author

Asseng, Senthold, Martre, Pierre, Maiorano, Andrea, Rötter, 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, Sanctis, Giacomo De, Dumont, Benjamin, Rezaei, Ehsan Eyshi, Fereres, Elias, Ferrise, Roberto, Garcia-Vila, Margarita, Gayler, Sebastian, Gao, Yujing, Horan, Heidi, Hoogenboom, Gerrit, Izaurralde, R. César, Jabloun, Mohamed, Jones, Curtis D, Kassie, Belay T, Kersebaum, Kurt-Christian, Klein, Christian, Koehler, Ann-Kristin, Liu, Bing, Minoli, Sara, Martin, Manuel Montesino San, Müller, 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, Velde, Marijn Van der, Wallach, Daniel, Wang, Enli, Webber, Heidi, Wolf, Joost, Xiao, Liujun, Zhang, Zhao, Zhao, Zhigan, Zhu, Yan, and Ewert, Frank

Subjects
Meteorology And Climatology
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
2018
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10. The Uncertainty of Crop Yield Projections Is Reduced by Improved Temperature Response Functions

Author

Wang, Enli, Martre, Pierre, Zhao, Zhigan, Ewert, Frank, Maiorano, Andrea, Rotter, Reimund P, Kimball, Bruce A, Ottman, Michael J, White, Jeffrey W, Reynolds, Matthew P, Alderman, Phillip D, Aggarwal, Pramod K, Anothai, Jakarat, Basso, Bruno, Biernath, Christian, Cammarano, Davide, Challinor, Andrew J, De Sanctis, Giacomo, Doltra, Jordi, Fereres, Elias, Garcia-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, Muller, Christoph, Naresh Kumar, Soora, Nendel, Claas, O'Leary, Garry, Oleson, Jorgen E, Palosuo, Tara, Priesack, Eckhart, Eyshi, Rezaei, Ehsan, Ripoche, Dominique, Ruane, Alex C, Semenov, Mikhail A, Scherbak, Lurii, Stockle, Claudio, Stratonovitch, Pierre, Streck, Thilo, Supit, Iwan, Tao, Fulu, Thorburn, Peter, Waha, Katharina, Wallach, Daniel, Wang, Zhimin, Wolf, Joost, Zhu, Yan, and Asseng, Senthold

Subjects
Meteorology And Climatology
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 is greater than 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
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11. 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 P, Asseng, Senthold, Ewert, Frank, Alderman, Phillip D, 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, Elias, Garcia-Vila, Margarita, Gayler, Sebastian, Hohenheim, Gerrit, Hunt, Leslie A, Izaurralde, Roberto C, Jabloun, Mohamed, Jones, Curtis D, Kassie, Belay T, Kersebaum, Kurt T, Koehler, Ann-Kristin, Mueller, 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, Roetter, Reimund P, Semenov, Mikhail A, Stoeckle, Claudio, Stratonovitch, Pierre, Streck, Thilo, Supit, Iwan, Tao, Fulu, Thorburn, Peter, Waha, Katharina, Wang, Enli, White, Jeffrey W, Wolf, Joost, Zhao, Zhigan, and Zhu, Yan

Subjects
Meteorology And Climatology
Abstract

The 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
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14. Statistical Analysis of Large Simulated Yield Datasets for Studying Climate Effects

Author

Makowski, David, primary, Asseng, Senthold, additional, Ewert, Frank, additional, Bassu, Simona, additional, Durand, Jean-Louis, additional, Martre, Pierre, additional, Adam, Myriam, additional, Aggarwal, Pramod K., additional, Angulo, Carlos, additional, Baron, Christian, additional, Basso, Bruno, additional, Bertuzzi, Patrick, additional, Biernath, Christian, additional, Boogaard, Hendrik, additional, Boote, Kenneth J., additional, Brisson, Nadine, additional, Cammarano, Davide, additional, Challinor, Andrew J., additional, Conijn, Sjakk J. G., additional, Corbeels, Marc, additional, Deryng, Delphine, additional, De Sanctis, Giacomo, additional, Doltra, Jordi, additional, Gayler, Sebastian, additional, Goldberg, Richard, additional, Grassini, Patricio, additional, Hatfield, Jerry L., additional, Heng, Lee, additional, Hoek, Steven, additional, Hooker, Josh, additional, Hunt, Tony L. A., additional, Ingwersen, Joachim, additional, Izaurralde, Cesar, additional, Jongschaap, Raymond E. E., additional, Jones, James W., additional, Kemanian, Armen R., additional, Kersebaum, Christian, additional, Kim, Soo-Hyung, additional, Lizaso, Jon, additional, Müller, Christoph, additional, Kumar, Naresh S., additional, Nendel, Claas, additional, O'Leary, Garry J., additional, Olesen, Jorgen E., additional, Osborne, Tom M., additional, Palosuo, Taru, additional, Pravia, Maria V., additional, Priesack, Eckart, additional, Ripoche, Dominique, additional, Rosenzweig, Cynthia, additional, Ruane, Alexander C., additional, Sau, Fredirico, additional, Semenov, Mickhail A., additional, Shcherbak, Iurii, additional, Steduto, Pasquale, additional, Stöckle, Claudio, additional, Stratonovitch, Pierre, additional, Streck, Thilo, additional, Supit, Iwan, additional, Tao, Fulu, additional, Teixeira, Edmar I., additional, Thorburn, Peter, additional, Timlin, Denis, additional, Travasso, Maria, additional, Rötter, Reimund, additional, Waha, Katharina, additional, Wallach, Daniel, additional, White, Jeffrey W., additional, Williams, Jimmy R., additional, and Wolf, Joost, additional

Published
2015
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15. Uncertainty of Wheat Water Use: Simulated Patterns and Sensitivity to Temperature and CO2

Author

Cammarano, Davide, Roetter, Reimund P, Asseng, Senthold, Ewert, Frank, Wallach, Daniel, Martre, Pierre, Hatfield, Jerry L, Jones, James W, Rosenzweig, Cynthia E, Ruane, Alex C, Boote, Kenneth J, Thorburn, Peter J, Kersebaum, Kurt Christian, Aggarwal, Pramod K, Angulo, Carlos, Basso, Bruno, Bertuzzi, Patrick, Biernath, Christian, Brisson, Nadine, Challinor, Andrew J, Doltra, Jordi, Gayler, Sebastian, Goldberg, Richie, Heng, Lee, and Steduto, Pasquale

Subjects
Meteorology And Climatology
Abstract

Projected global warming and population growth will reduce future water availability for agriculture. Thus, it is essential to increase the efficiency in using water to ensure crop productivity. Quantifying crop water use (WU; i.e. actual evapotranspiration) is a critical step towards this goal. Here, sixteen wheat simulation models were used to quantify sources of model uncertainty and to estimate the relative changes and variability between models for simulated WU, water use efficiency (WUE, WU per unit of grain dry mass produced), transpiration efficiency (Teff, transpiration per kg of unit of grain yield dry mass produced), grain yield, crop transpiration and soil evaporation at increased temperatures and elevated atmospheric carbon dioxide concentrations ([CO2]). The greatest uncertainty in simulating water use, potential evapotranspiration, crop transpiration and soil evaporation was due to differences in how crop transpiration was modelled and accounted for 50 of the total variability among models. The simulation results for the sensitivity to temperature indicated that crop WU will decline with increasing temperature due to reduced growing seasons. The uncertainties in simulated crop WU, and in particularly due to uncertainties in simulating crop transpiration, were greater under conditions of increased temperatures and with high temperatures in combination with elevated atmospheric [CO2] concentrations. Hence the simulation of crop WU, and in particularly crop transpiration under higher temperature, needs to be improved and evaluated with field measurements before models can be used to simulate climate change impacts on future crop water demand.

Published
2016
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16. Multi-Wheat-Model Ensemble Responses to Interannual Climate Variability

Author

Ruane, Alex C, Hudson, Nicholas I, Asseng, Senthold, Camarrano, Davide, Ewert, Frank, Martre, Pierre, Boote, Kenneth J, Thorburn, Peter J, Aggarwal, Pramod K, and Angulo, Carlos

Subjects
Meteorology And Climatology
Abstract

We compare 27 wheat models' yield responses to interannual climate variability, analyzed at locations in Argentina, Australia, India, and The Netherlands as part of the Agricultural Model Intercomparison and Improvement Project (AgMIP) Wheat Pilot. Each model simulated 1981e2010 grain yield, and we evaluate results against the interannual variability of growing season temperature, precipitation, and solar radiation. The amount of information used for calibration has only a minor effect on most models' climate response, and even small multi-model ensembles prove beneficial. Wheat model clusters reveal common characteristics of yield response to climate; however models rarely share the same cluster at all four sites indicating substantial independence. Only a weak relationship (R2 0.24) was found between the models' sensitivities to interannual temperature variability and their response to long-termwarming, suggesting that additional processes differentiate climate change impacts from observed climate variability analogs and motivating continuing analysis and model development efforts.

Published
2016
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17. Author Correction: The uncertainty of crop yield projections is reduced by improved temperature response functions

Author

Wang, Enli, Martre, Pierre, Zhao, Zhigan, Ewert, Frank, Maiorano, Andrea, Rötter, Reimund P., Kimball, Bruce A., Ottman, Michael J., Wall, Gerard W., White, Jeffrey W., Reynolds, Matthew P., Alderman, Phillip D., Aggarwal, Pramod K., Anothai, Jakarat, Basso, Bruno, Biernath, Christian, Cammarano, Davide, 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., 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, Alex 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

Published
2017
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18. Statistical Analysis of Large Simulated Yield Datasets for Studying Climate Effects

Author

Makowski, David, Asseng, Senthold, Ewert, Frank, Bassu, Simona, Durand, Jean-Louis, Martre, Pierre, Adam, Myriam, Aggarwal, Pramod K, Angulo, Carlos, Baron, Chritian, Basso, Bruno, Bertuzzi, Patrick, Biemath, Christian, Boogaard, Hendrik, Boote, Kenneth J, Brisson, Nadine, Cammarano, Davide, Challinor, Andrew J, Conijn, Sjakk J. G, Corbeels, Marc, Deryng, Delphine, De Sanctis, Giacomo, Doltra, Jordi, Gayler, Sebastian, Goldberg, Richard A, Grassini, Patricio, Hatfield, Jerry L, Heng, Lee, Hoek, Steven, Hooker, Josh, Hunt, Tony L. A, Ingwersen, Joachim, Izaurralde, Cesar, Jongschaap, Raymond E. E, and Rosenzweig, Cynthia

Subjects
Statistics And Probability, Meteorology And Climatology
Abstract

Many studies have been carried out during the last decade to study the effect of climate change on crop yields and other key crop characteristics. In these studies, one or several crop models were used to simulate crop growth and development for different climate scenarios that correspond to different projections of atmospheric CO2 concentration, temperature, and rainfall changes (Semenov et al., 1996; Tubiello and Ewert, 2002; White et al., 2011). The Agricultural Model Intercomparison and Improvement Project (AgMIP; Rosenzweig et al., 2013) builds on these studies with the goal of using an ensemble of multiple crop models in order to assess effects of climate change scenarios for several crops in contrasting environments. These studies generate large datasets, including thousands of simulated crop yield data. They include series of yield values obtained by combining several crop models with different climate scenarios that are defined by several climatic variables (temperature, CO2, rainfall, etc.). Such datasets potentially provide useful information on the possible effects of different climate change scenarios on crop yields. However, it is sometimes difficult to analyze these datasets and to summarize them in a useful way due to their structural complexity; simulated yield data can differ among contrasting climate scenarios, sites, and crop models. Another issue is that it is not straightforward to extrapolate the results obtained for the scenarios to alternative climate change scenarios not initially included in the simulation protocols. Additional dynamic crop model simulations for new climate change scenarios are an option but this approach is costly, especially when a large number of crop models are used to generate the simulated data, as in AgMIP. Statistical models have been used to analyze responses of measured yield data to climate variables in past studies (Lobell et al., 2011), but the use of a statistical model to analyze yields simulated by complex process-based crop models is a rather new idea. We demonstrate herewith that statistical methods can play an important role in analyzing simulated yield data sets obtained from the ensembles of process-based crop models. Formal statistical analysis is helpful to estimate the effects of different climatic variables on yield, and to describe the between-model variability of these effects.

Published
2015

19. Multimodel Ensembles of Wheat Growth: Many Models are Better than One

Author

Martre, Pierre, Wallach, Daniel, Asseng, Senthold, Ewert, Frank, Jones, James W, Rotter, Reimund P, Boote, Kenneth J, Ruane, Alexander C, Thorburn, Peter J, Cammarano, Davide, Hatfield, Jerry L, Rosenzweig, Cynthia, Aggarwal, Pramod K, Angulo, Carlos, Basso, Bruno, Bertuzzi, Patrick, Biernath, Christian, Brisson, Nadine, Challinor, Andrew J, Doltra, Jordi, Gayler, Sebastian, Goldberg, Richie, Grant, Robert F, Heng, Lee, Hooker, Josh, Hunt, Leslie A, Ingwersen, Joachim, Izaurralde, Roberto C, Kersebaum, Kurt Christian, Kumar, Soora Naresh, Nendel, Claas, O'Leary, Garry, Olesen, Jorgen E, Osborne, Tom M, Palosuo, Taru, and Priesack, Eckart

Subjects
Meteorology And Climatology, Earth Resources And Remote Sensing
Abstract

Crop models of crop growth are increasingly used to quantify the impact of global changes due to climate or crop management. Therefore, accuracy of simulation results is a major concern. Studies with ensembles of crop model scan give valuable information about model accuracy and uncertainty, but such studies are difficult to organize and have only recently begun. We report on the largest ensemble study to date, of 27 wheat models tested in four contrasting locations for their accuracy in simulating multiple crop growth and yield variables. The relative error averaged over models was 2438 for the different end-of-season variables including grain yield (GY) and grain protein concentration (GPC). There was little relation between error of a model for GY or GPC and error for in-season variables. Thus, most models did not arrive at accurate simulations of GY and GPC by accurately simulating preceding growth dynamics. Ensemble simulations, taking either the mean (e-mean) or median (e-median) of simulated values, gave better estimates than any individual model when all variables were considered. Compared to individual models, e-median ranked first in simulating measured GY and third in GPC. The error of e-mean and e-median declined with an increasing number of ensemble members, with little decrease beyond 10 models. We conclude that multimodel ensembles can be used to create new estimators with improved accuracy and consistency in simulating growth dynamics. We argue that these results are applicable to other crop species, and hypothesize that they apply more generally to ecological system models.

Published
2015
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22. 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, and Asseng, Senthold

Subjects
1.5°C warming, climate change, extreme low yields, food security, model ensemble, wheat production
Published
2019

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

Author

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

Published
2019
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26. Multimodel ensembles improve predictions of crop–environment–management interactions

Author

Wallach, Daniel, primary, Martre, Pierre, additional, Liu, Bing, additional, Asseng, Senthold, additional, Ewert, Frank, additional, Thorburn, Peter J., additional, van Ittersum, Martin, additional, Aggarwal, Pramod K., additional, Ahmed, Mukhtar, additional, Basso, Bruno, additional, Biernath, Christian, additional, Cammarano, Davide, additional, Challinor, Andrew J., additional, De Sanctis, Giacomo, additional, Dumont, Benjamin, additional, Eyshi Rezaei, Ehsan, additional, Fereres, Elias, additional, Fitzgerald, Glenn J., additional, Gao, Y., additional, Garcia‐Vila, Margarita, additional, Gayler, Sebastian, additional, Girousse, Christine, additional, Hoogenboom, Gerrit, additional, Horan, Heidi, additional, Izaurralde, Roberto C., additional, Jones, Curtis D., additional, Kassie, Belay T., additional, Kersebaum, Kurt C., additional, Klein, Christian, additional, Koehler, Ann‐Kristin, additional, Maiorano, Andrea, additional, Minoli, Sara, additional, Müller, Christoph, additional, Naresh Kumar, Soora, additional, Nendel, Claas, additional, O'Leary, Garry J., additional, Palosuo, Taru, additional, Priesack, Eckart, additional, Ripoche, Dominique, additional, Rötter, Reimund P., additional, Semenov, Mikhail A., additional, Stöckle, Claudio, additional, Stratonovitch, Pierre, additional, Streck, Thilo, additional, Supit, Iwan, additional, Tao, Fulu, additional, Wolf, Joost, additional, and Zhang, Zhao, additional

Published
2018
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29. The climate-smart village approach: framework of an integrative strategy for scaling up adaptation options in agriculture

Author

Aggarwal, Pramod K., primary, Jarvis, Andy, additional, Campbell, Bruce M., additional, Zougmoré, Robert B., additional, Khatri-Chhetri, Arun, additional, Vermeulen, Sonja J., additional, Loboguerrero, Ana Maria, additional, Sebastian, Leocadio S., additional, Kinyangi, James, additional, Bonilla-Findji, Osana, additional, Radeny, Maren, additional, Recha, John, additional, Martinez-Baron, Deissy, additional, Ramirez-Villegas, Julian, additional, Huyer, Sophia, additional, Thornton, Philip, additional, Wollenberg, Eva, additional, Hansen, James, additional, Alvarez-Toro, Patricia, additional, Aguilar-Ariza, Andrés, additional, Arango-Londoño, David, additional, Patiño-Bravo, Victor, additional, Rivera, Ovidio, additional, Ouedraogo, Mathieu, additional, and Yen, Bui Tan, additional

Published
2018
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30. Erratum: The uncertainty of crop yield projections is reduced by improved temperature response functions

Author

Wang, Enli, primary, Martre, Pierre, additional, Zhao, Zhigan, additional, Ewert, Frank, additional, Maiorano, Andrea, additional, Rötter, Reimund P., additional, Kimball, Bruce A., additional, Ottman, Michael J., additional, Wall, Gerard W., additional, White, Jeffrey W., additional, Reynolds, Matthew P., additional, Alderman, Phillip D., additional, Aggarwal, Pramod K., additional, Anothai, Jakarat, additional, Basso, Bruno, additional, Biernath, Christian, additional, Cammarano, Davide, additional, Challinor, Andrew J., additional, De Sanctis, Giacomo, additional, Doltra, Jordi, additional, Fereres, Elias, additional, Garcia-Vila, Margarita, additional, Gayler, Sebastian, additional, Hoogenboom, Gerrit, additional, Hunt, Leslie A., additional, Izaurralde, Roberto C., additional, Jabloun, Mohamed, additional, Jones, Curtis D., additional, Kersebaum, Kurt C., additional, Koehler, Ann-Kristin, additional, Liu, Leilei, additional, Müller, Christoph, additional, Kumar, Soora Naresh, additional, Nendel, Claas, additional, O’Leary, Garry, additional, Olesen, Jørgen E., additional, Palosuo, Taru, additional, Priesack, Eckart, additional, Rezaei, Ehsan Eyshi, additional, Ripoche, Dominique, additional, Ruane, Alex C., additional, Semenov, Mikhail A., additional, Shcherbak, Iurii, additional, Stöckle, Claudio, additional, Stratonovitch, Pierre, additional, Streck, Thilo, additional, Supit, Iwan, additional, Tao, Fulu, additional, Thorburn, Peter, additional, Waha, Katharina, additional, Wallach, Daniel, additional, Wang, Zhimin, additional, Wolf, Joost, additional, Zhu, Yan, additional, and Asseng, Senthold, additional

Published
2017
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31. Climate action for food security in South Asia? Analyzing the role of agriculture in nationally determined contributions to the Paris agreement.

Author

Amjath-Babu, T. S., Aggarwal, Pramod K., and Vermeulen, Sonja

Subjects
*FOOD security, *EMISSION control, *PROFITABILITY, *AGRICULTURAL development, PARIS Agreement (2016)
Abstract

The Nationally Determined Contributions (NDCs) submitted under the Paris Agreement propose a country's contribution to global mitigation efforts and domestic adaptation initiatives. This paper provides a systematic analysis of NDCs submitted by South Asian nations, in order to assess how far their commitments might deliver meaningful contributions to the global 2°C target and to sustainable broad-based adaptation benefits. Though agriculture-related emissions are prominent in emission profiles of South Asian countries, their emission reduction commitments are less likely to include agriculture, partly because of a concern over food security. We find that income-enhancing mitigation technologies that do not jeopardize food security may significantly augment the region's mitigation potential. In the case of adaptation, analysis shows that the greatest effort will be directed towards protecting the cornerstones of the 'green revolution' for ensuring food security. Development of efficient and climate-resilient agricultural value chains and integrated farming bodies will be important to ensuring adaptation investment. Potentially useful models of landscape level climate resilience actions and ecosystem-based adaptation are also presented, along with estimates of the aggregate costs of agricultural adaptation. Countries in the region propose different mixes of domestic and foreign, and public and private, adaptation finance to meet the substantial gaps. Key policy insights Though substantial potential for mitigation of agricultural emissions exists in South Asia, governments in the region do not commit to agricultural emissions reductions in their NDCs. Large-scale adoption of income-enhancing technologies is the key to realizing agricultural mitigation potential in South Asia, whilst maintaining food security. Increasing resilience and profitability through structural changes, value chain interventions, and landscape-level actions may provide strong options to build adaptive capacity and enhance food security. Both private finance (autonomous adaptation) and international financial transfers will be required to close the substantial adaptation finance gap [ABSTRACT FROM AUTHOR]

Published
2019
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32. Climate change impact and adaptation for wheat protein.

Author

Asseng, Senthold, Martre, Pierre, Maiorano, Andrea, Rötter, 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, Balkovič, Juraj, Basso, Bruno, and Biernath, Christian

Subjects
WHEAT proteins, CROP yields, PLANT diversity, CLIMATE change, VEGETATION & climate, HIGH temperature (Weather)
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. 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 could boost global wheat yield by 7% and protein yield by 2%, but grain protein concentration would be reduced by −1.1% points, representing a relative change of −8.6%. [ABSTRACT FROM AUTHOR]

Published
2019
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33. Similar estimates of temperature impacts on global wheat yield by three independent methods

Author

Liu, Bing, primary, Asseng, Senthold, additional, Müller, Christoph, additional, Ewert, Frank, additional, Elliott, Joshua, additional, Lobell, David B., additional, Martre, Pierre, additional, Ruane, Alex C., additional, Wallach, Daniel, additional, Jones, James W., additional, Rosenzweig, Cynthia, additional, Aggarwal, Pramod K., additional, Alderman, Phillip D., additional, Anothai, Jakarat, additional, Basso, Bruno, additional, Biernath, Christian, additional, Cammarano, Davide, additional, Challinor, Andy, additional, Deryng, Delphine, additional, Sanctis, Giacomo De, additional, Doltra, Jordi, additional, Fereres, Elias, additional, Folberth, Christian, additional, Garcia-Vila, Margarita, additional, Gayler, Sebastian, additional, Hoogenboom, Gerrit, additional, Hunt, Leslie A., additional, Izaurralde, Roberto C., additional, Jabloun, Mohamed, additional, Jones, Curtis D., additional, Kersebaum, Kurt C., additional, Kimball, Bruce A., additional, Koehler, Ann-Kristin, additional, Kumar, Soora Naresh, additional, Nendel, Claas, additional, O’Leary, Garry J., additional, Olesen, Jørgen E., additional, Ottman, Michael J., additional, Palosuo, Taru, additional, Prasad, P. V. Vara, additional, Priesack, Eckart, additional, Pugh, Thomas A. M., additional, Reynolds, Matthew, additional, Rezaei, Ehsan E., additional, Rötter, Reimund P., additional, Schmid, Erwin, additional, Semenov, Mikhail A., additional, Shcherbak, Iurii, additional, Stehfest, Elke, additional, Stöckle, Claudio O., additional, Stratonovitch, Pierre, additional, Streck, Thilo, additional, Supit, Iwan, additional, Tao, Fulu, additional, Thorburn, Peter, additional, Waha, Katharina, additional, Wall, Gerard W., additional, Wang, Enli, additional, White, Jeffrey W., additional, Wolf, Joost, additional, Zhao, Zhigan, additional, and Zhu, Yan, additional

Published
2016
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34. Challenges and Responses to Ongoing and Projected Climate Change for Dryland Cereal Production Systems throughout the World.

Author

O'Leary, Garry J., Aggarwal, Pramod K., Calderini, Daniel F., Connor, David J., Craufurd, Peter, Eigenbrode, Sanford D., Xue Han, and Hatfield, Jerry L.

Subjects
*CROPS, *SUSTAINABILITY, *PRODUCTION (Economic theory), *CLIMATE change, *GRAIN
Abstract

Since the introduction of mechanized production in both developed and developing countries, crops and their management have undergone significant adaptation resulting in increased productivity. Historical yield increases in wheat have occurred across most regions of the world (20-88 kg ha-1 year-1), but climate trends threaten to dampen or reverse these gains such that yields are expected to decrease by 5-6% despite rising atmospheric CO2 concentrations. Current and projected climatic factors are temporally and spatially variable in dryland cereal production systems throughout the world. Productivity gains in wheat in some locations have been achieved from traditional agronomic practices and breeding. Continued improvement in all cereal production regions and locations of the world requires technical advances, including closer monitoring of soils, water conservation strategies, and multiple sowing times using different crops to reduce risks. The management of disease, pests, and weeds will be an added challenge, especially in areas of higher precipitation. Excellent progress has been achieved in Asia and there is much potential in Sub-Saharan Africa. Technical solutions seem within our grasp but must be implemented in the context of variable social, economic, regulatory, and administrative constraints, providing opportunities for cross fertilization and global collaboration to meet them. [ABSTRACT FROM AUTHOR]

Published
2018
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35. Climate Variability and Change in Bihar, India: Challenges and Opportunities for Sustainable Crop Production.

Author

Tesfaye, Kindie, Aggarwal, Pramod K., Mequanint, Fasil, Shirsath, Paresh B., Stirling, Clare M., Khatri-Chhetri, Arun, and Rahut, Dil Bahadur

Abstract

Climate change and associated uncertainties have serious direct and indirect consequences for crop production and food security in agriculture-based developing regions. Long-term climate data analysis can identify climate risks and anticipate new ones for planning appropriate adaptation and mitigation options. The aim of this study was to identify near-term (2030) and mid-term (2050) climate risks and/or opportunities in the state of Bihar, one of India's most populous and poorest states, using weather data for 30 years (1980-2009) as a baseline. Rainfall, maximum and minimum temperatures, and evapotranspiration will all increase in the near- and mid-term periods relative to the baseline period, with the magnitude of the change varying with time, season and location within the state. Bihar's major climate risks for crop production will be heat stress due to increasing minimum temperatures in the rabi (winter) season and high minimum and maximum temperatures in the spring season; and intense rainfall and longer dry spells in the kharif (monsoon) season. The increase in annual and seasonal rainfall amounts, and extended crop growing period in the kharif season generally provide opportunities; but increasing temperature across the state will have considerable negative consequences on (staple) crops by affecting crop phenology, physiology and plant-water relations. The study helps develop site-specific adaptation and mitigation options that minimize the negative effects of climate change while maximizing the opportunities. [ABSTRACT FROM AUTHOR]

Published
2017
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36. Assessment of Large Seed Banks Requirement for Drought Risk Management in South Asia.

Author

Khatri-Chhetri, Arun and Aggarwal, Pramod K.

Abstract

Agriculture in South Asia is largely dependent on rainfall, where about two-thirds of the cultivable lands lack irrigation facilities. In recent years, increasing frequency and severity of droughts have had a severe impact on rainfed agriculture and livelihood of millions of farmers in the region. There are numerous drought adaptation and mitigation options available for rainfed agriculture. A seed bank is one of those options that can play an important role in minimizing the effect of droughts on crop production. This paper assesses the need for seed banks in rainfed/partially irrigated areas of South Asia for the purpose of drought risk management. The need for additional seeds of the main crops or suitable alternative crops for re-sowing/planting after drought-induced losses of the main crop was assessed by using long-term gridded rainfall data and crop information. Results show that very limited rainfed areas in South Asia require additional seeds of main or alternative crops for drought risk management once in five to seven years' drought return period. About 90 percent of such areas in South Asia may require additional seeds for drought risk management once in 10 years or more. The timing and severity of droughts during cropping season and cost/benefits of seed bank maintenance play a major role in choosing additional seeds for the main crops and/or alternate crops for maintenance in the large seed banks. This study shows that, despite the large investment requirement, maintenance of large seed banks for drought risks management is economically viable for the limited areas in South Asia. [ABSTRACT FROM AUTHOR]

Published
2017
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38. Multimodel ensembles of wheat growth: many models are better than one

Author

Martre, Pierre, primary, Wallach, Daniel, additional, Asseng, Senthold, additional, Ewert, Frank, additional, Jones, James W., additional, Rötter, Reimund P., additional, Boote, Kenneth J., additional, Ruane, Alex C., additional, Thorburn, Peter J., additional, Cammarano, Davide, additional, Hatfield, Jerry L., additional, Rosenzweig, Cynthia, additional, Aggarwal, Pramod K., additional, Angulo, Carlos, additional, Basso, Bruno, additional, Bertuzzi, Patrick, additional, Biernath, Christian, additional, Brisson, Nadine, additional, Challinor, Andrew J., additional, Doltra, Jordi, additional, Gayler, Sebastian, additional, Goldberg, Richie, additional, Grant, Robert F., additional, Heng, Lee, additional, Hooker, Josh, additional, Hunt, Leslie A., additional, Ingwersen, Joachim, additional, Izaurralde, Roberto C., additional, Kersebaum, Kurt Christian, additional, Müller, Christoph, additional, Kumar, Soora Naresh, additional, Nendel, Claas, additional, O'leary, Garry, additional, Olesen, Jørgen E., additional, Osborne, Tom M., additional, Palosuo, Taru, additional, Priesack, Eckart, additional, Ripoche, Dominique, additional, Semenov, Mikhail A., additional, Shcherbak, Iurii, additional, Steduto, Pasquale, additional, Stöckle, Claudio O., additional, Stratonovitch, Pierre, additional, Streck, Thilo, additional, Supit, Iwan, additional, Tao, Fulu, additional, Travasso, Maria, additional, Waha, Katharina, additional, White, Jeffrey W., additional, and Wolf, Joost, additional

Published
2014
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44. Similar estimates of temperature impacts on global wheat yield by three independent methods (vol 6, pg 1130, 2016)

Author

Liu, Bing, Asseng, Senthold, Muller, Christoph, Ewert, Frank, Elliott, Joshua, Lobell, David B., Martre, Pierre, Ruane, Alex C., Wallach, Daniel, Jones, James W., Rosenzweig, Cynthia, Aggarwal, Pramod K., Alderman, Phillip D., Anothai, Jakarat, Basso, Bruno, Biernath, Christian, Cammarano, Davide, Challinor, Andy, Deryng, Delphine, Sanctis, Giacomo, Doltra, Jordi, Fereres, Elias, Folberth, Christian, Garcia-Vila, Margarita, Gayler, Sebastian, Hoogenboom, Gerrit, Hunt, Leslie A., Izaurralde, Roberto C., Jabloun, Mohamed, Jones, Curtis D., Kersebaum, Kurt C., Kimball, Bruce A., Koehler, Ann-Kristin, Kumar, Soora Naresh, Nendel, Claas, O Leary, Garry J., Olesen, Jorgen E., Ottman, Michael J., Palosuo, Taru, Prasad, P. V. Vara, Priesack, Eckart, Pugh, Thomas A. M., Reynolds, Matthew, Rezaei, Ehsan E., Rtter, Reimund P., Schmid, Erwin, Mikhail Semenov, Shcherbak, Iurii, Stehfest, Elke, Stockle, Claudio O., Stratonovitch, Pierre, Streck, Thilo, Supit, Iwan, Tao, Fulu, Thorburn, Peter, Waha, Katharina, Wall, Gerard W., Wang, Enli, White, Jeffrey W., Wolf, Joost, Zhao, Zhigan, and Zhu, Yan

46. The climate-smart village approach: framework of an integrative strategy for scaling up adaptation options in agriculture.

Author

Wollenberg, Eva, Hansen, James, Aggarwal, Pramod K., Khatri-Chhetri, Arun, Jarvis, Andy, Loboguerrero, Ana Maria, Bonilla-Findji, Osana, Martinez-Baron, Deissy, Campbell, Bruce M., Zougmoré, Robert B., Ouedraogo, Mathieu, Vermeulen, Sonja J., Sebastian, Leocadio S., Yen, Bui Tan, Kinyangi, James, Radeny, Maren, Recha, John, Thornton, Philip, Huyer, Sophia, and Ramirez-Villegas, Julian

Subjects
*ADAPTIVE natural resource management, *CLIMATE change, *ECOLOGICAL resilience, *GREENHOUSE effect prevention, *AGRICULTURAL technology, *RURAL geography
Abstract

Increasing weather risks threaten agricultural production systems and food security across the world. Maintaining agricultural growth while minimizing climate shocks is crucial to building a resilient food production system and meeting developmental goals in vulnerable countries. Experts have proposed several technological, institutional and policy interventions to help farmers adapt to current and future weather variability and to mitigate greenhouse gas (GHG) emissions. This paper presents the climate-smart village (CSV) approach as a means of performing agricultural research for development that robustly tests technological and institutional options for dealing with climatic variability and climate change in agriculture using participatory methods. It aims to scale up and scale out the appropriate options and draw out lessons for policy makers from local to global levels. The approach incorporates evaluation of climate-smart technologies, practices, services and processes relevant to local climatic risk management and identifies opportunities for maximizing adaptation gains from synergies across different interventions and recognizing potential maladaptation and trade-offs. It ensures that these are aligned with local knowledge and link into development plans. This paper describes early results in Asia, Africa and Latin America to illustrate different examples of the CSV approach in diverse agroecological settings. Results from initial studies indicate that the CSV approach has a high potential for scaling out promising climate-smart agricultural technologies, practices and services. Climate analog studies indicate that the lessons learned at the CSV sites would be relevant to adaptation planning in a large part of global agricultural land even under scenarios of climate change. Key barriers and opportunities for further work are also discussed. [ABSTRACT FROM AUTHOR]

Published
2018
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47. The climate-smart village approach : framework of an integrative strategy for scaling up adaptation options in agriculture

Author

Aggarwal, Pramod K., Jarvis, Andy, Campbell, Bruce M., Zougmoré, Robert B., Khatri-Chhetri, Arun, Vermeulen, Sonja J., Loboguerrero, Ana Maria, Sebastian, Leocadio S., Kinyangi, James, Bonilla-Findji, Osana, Radeny, Maren, Recha, John, Martinez-Baron, Deissy, Ramirez-Villegas, Julian, Huyer, Sophia, Thornton, Philip, Wollenberg, Eva, Hansen, James, Alvarez-Toro, Patricia, Aguilar-Ariza, Andrés, Arango-Londoño, David, Patiño-Bravo, Victor, Rivera, Ovidio, Ouedraogo, Mathieu, and Yen, Bui Tan

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