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Dr. Roberto Ferrise
Department of AGRIculture, food, environment and forestry - University of Florence (DAGRI) Piazzale delle Cascine, 18 50144 Firenze. Italy

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0 Precision Agriculture
0 Crop modelling
0 Agrometeorology
0 ecophysiology
0 climate change impact assessment

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climate change impact assessment
Crop modelling

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Conference paper
Published: 25 June 2021 in Precision agriculture ’21
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ACS Style

R. Ferrise; G. Trombi; G. Padovan; S. Costafreda-Aumedes; E. Di Giuseppe; M. Pasqui; J. Moretto; F. Morari. 3. A simple web-based tool for optimizing nitrogen variable rate application in durum wheat. Precision agriculture ’21 2021, 1 .

AMA Style

R. Ferrise, G. Trombi, G. Padovan, S. Costafreda-Aumedes, E. Di Giuseppe, M. Pasqui, J. Moretto, F. Morari. 3. A simple web-based tool for optimizing nitrogen variable rate application in durum wheat. Precision agriculture ’21. 2021; ():1.

Chicago/Turabian Style

R. Ferrise; G. Trombi; G. Padovan; S. Costafreda-Aumedes; E. Di Giuseppe; M. Pasqui; J. Moretto; F. Morari. 2021. "3. A simple web-based tool for optimizing nitrogen variable rate application in durum wheat." Precision agriculture ’21 , no. : 1.

Journal article
Published: 07 October 2020 in Field Crops Research
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Durum wheat is one of the most important crops in the Mediterranean basin. The choice of the cultivar and the sowing time are key management practices that ensure high yield. Crop simulation models could be used to investigate the genotype × environment × sowing window (G × E×SW) interactions in order to optimize farmers’ actions. The aim of this study was to evaluate the performance of the wheat model SiriusQuality in simulating durum wheat yields in Mediterranean environments and its potential to explore the G × E×SW interactions. SiriusQuality was assessed in multiple growing seasons at seven sites located in Italy, Spain and Morocco, where locally adapted cultivars were grown. The model showed good ability in predicting anthesis and maturity date (Pearson r >0.8), as well as above ground biomass and grain yield (6 % < nRMSE < 18 %). The model was then used to find the optimal 30-day sowing window to maximize grain yields at four sites, two were located in Italy (Florence, Foggia), and the other two were in Spain (Santaella) and Morocco (Sidi El Aydi) respectively. Among the cultivars, on the average between all sowing window, Amilcar had the best performance in Foggia (+33 % compared to the traditional cultivar Simeto) and in Sidi El Aydi (+22 % compared to Karim), Karim in Florence (+19 % compared to Creso) and in Santaella (+6 % compared to Amilcar). Instead Creso and Simeto showed the lowest production at all locations. The results showed that an earlier sowing window compared to the traditional one would have a positive effect on wheat yields in all environments tested, because of increased maximum leaf area index, grain number and size, and grain filling duration. Moreover, with earlier sowing, grain filling coincides with higher soil water availability, reducing the water stress and increasing the accumulation of dry mass in grains. In cooler and wetter locations, cultivars characterized by higher leaf area index and radiation use efficiency had the higher number of grains, while in the hottest and driest locations, short-cycle cultivars with high grain dry matter potential (e.g. through enhanced “stay green” capacity) should be preferred.

ACS Style

Gloria Padovan; Pierre Martre; Mikhail A. Semenov; Alberto Masoni; Simone Bregaglio; Domenico Ventrella; Ignacio J. Lorite; Cristina Santos; Marco Bindi; Roberto Ferrise; Camilla Dibari. Understanding effects of genotype × environment × sowing window interactions for durum wheat in the Mediterranean basin. Field Crops Research 2020, 259, 107969 .

AMA Style

Gloria Padovan, Pierre Martre, Mikhail A. Semenov, Alberto Masoni, Simone Bregaglio, Domenico Ventrella, Ignacio J. Lorite, Cristina Santos, Marco Bindi, Roberto Ferrise, Camilla Dibari. Understanding effects of genotype × environment × sowing window interactions for durum wheat in the Mediterranean basin. Field Crops Research. 2020; 259 ():107969.

Chicago/Turabian Style

Gloria Padovan; Pierre Martre; Mikhail A. Semenov; Alberto Masoni; Simone Bregaglio; Domenico Ventrella; Ignacio J. Lorite; Cristina Santos; Marco Bindi; Roberto Ferrise; Camilla Dibari. 2020. "Understanding effects of genotype × environment × sowing window interactions for durum wheat in the Mediterranean basin." Field Crops Research 259, no. : 107969.

Preprint content
Published: 14 September 2020
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Calibration, the estimation of model parameters based on fitting the model to experimental data, is among the first steps in many applications of system models and has an important impact on simulated values. Here we propose and illustrate a novel method of developing guidelines for calibration of system models. Our example is calibration of the phenology component of crop models. The approach is based on a multi-model study, where all teams are provided with the same data and asked to return simulations for the same conditions. All teams are asked to document in detail their calibration approach, including choices with respect to criteria for best parameters, choice of parameters to estimate and software. Based on an analysis of the advantages and disadvantages of the various choices, we propose calibration recommendations that cover a comprehensive list of decisions and that are based on actual practices. Highlights We propose a new approach to deriving calibration recommendations for system models Approach is based on analyzing calibration in multi-model simulation exercises Resulting recommendations are holistic and anchored in actual practice We apply the approach to calibration of crop models used to simulate phenology Recommendations concern: objective function, parameters to estimate, software used

ACS Style

Daniel Wallach; Taru Palosuo; Peter Thorburn; Zvi Hochman; Emmanuelle Gourdain; Fety Andrianasolo; Senthold Asseng; Bruno Basso; Samuel Buis; Neil Crout; Camilla Dibari; Benjamin Dumont; Roberto Ferrise; Thomas Gaiser; Cecile Garcia; Sebastian Gayler; Afshin Ghahramani; Santosh Hiremath; Steven Hoek; Heidi Horan; Gerrit Hoogenboom; Mingxia Huang; Mohamed Jabloun; Per-Erik Jansson; Qi Jing; Eric Justes; Kurt Christian Kersebaum; Anne Klosterhalfen; Marie Launay; Elisabet Lewan; Qunying Luo; Bernardo Maestrini; Henrike Mielenz; Marco Moriondo; Hasti Nariman Zadeh; Gloria Padovan; Jørgen Eivind Olesen; Arne Poyda; Eckart Priesack; Johannes Wilhelmus Maria Pullens; Budong Qian; Niels Schuetze; Vakhtang Shelia; Amir Souissi; Xenia Specka; Amit Kumar Srivastava; Tommaso Stella; Thilo Streck; Giacomo Trombi; Evelyn Wallor; Jing Wang; Tobias K.D. Weber; Lutz Weihermueller; Allard de Wit; Thomas Woehling; Liujun Xiao; Chuang Zhao; Yan Zhu; Sabine J. Seidel. The chaos in calibrating crop models. 2020, 1 .

AMA Style

Daniel Wallach, Taru Palosuo, Peter Thorburn, Zvi Hochman, Emmanuelle Gourdain, Fety Andrianasolo, Senthold Asseng, Bruno Basso, Samuel Buis, Neil Crout, Camilla Dibari, Benjamin Dumont, Roberto Ferrise, Thomas Gaiser, Cecile Garcia, Sebastian Gayler, Afshin Ghahramani, Santosh Hiremath, Steven Hoek, Heidi Horan, Gerrit Hoogenboom, Mingxia Huang, Mohamed Jabloun, Per-Erik Jansson, Qi Jing, Eric Justes, Kurt Christian Kersebaum, Anne Klosterhalfen, Marie Launay, Elisabet Lewan, Qunying Luo, Bernardo Maestrini, Henrike Mielenz, Marco Moriondo, Hasti Nariman Zadeh, Gloria Padovan, Jørgen Eivind Olesen, Arne Poyda, Eckart Priesack, Johannes Wilhelmus Maria Pullens, Budong Qian, Niels Schuetze, Vakhtang Shelia, Amir Souissi, Xenia Specka, Amit Kumar Srivastava, Tommaso Stella, Thilo Streck, Giacomo Trombi, Evelyn Wallor, Jing Wang, Tobias K.D. Weber, Lutz Weihermueller, Allard de Wit, Thomas Woehling, Liujun Xiao, Chuang Zhao, Yan Zhu, Sabine J. Seidel. The chaos in calibrating crop models. . 2020; ():1.

Chicago/Turabian Style

Daniel Wallach; Taru Palosuo; Peter Thorburn; Zvi Hochman; Emmanuelle Gourdain; Fety Andrianasolo; Senthold Asseng; Bruno Basso; Samuel Buis; Neil Crout; Camilla Dibari; Benjamin Dumont; Roberto Ferrise; Thomas Gaiser; Cecile Garcia; Sebastian Gayler; Afshin Ghahramani; Santosh Hiremath; Steven Hoek; Heidi Horan; Gerrit Hoogenboom; Mingxia Huang; Mohamed Jabloun; Per-Erik Jansson; Qi Jing; Eric Justes; Kurt Christian Kersebaum; Anne Klosterhalfen; Marie Launay; Elisabet Lewan; Qunying Luo; Bernardo Maestrini; Henrike Mielenz; Marco Moriondo; Hasti Nariman Zadeh; Gloria Padovan; Jørgen Eivind Olesen; Arne Poyda; Eckart Priesack; Johannes Wilhelmus Maria Pullens; Budong Qian; Niels Schuetze; Vakhtang Shelia; Amir Souissi; Xenia Specka; Amit Kumar Srivastava; Tommaso Stella; Thilo Streck; Giacomo Trombi; Evelyn Wallor; Jing Wang; Tobias K.D. Weber; Lutz Weihermueller; Allard de Wit; Thomas Woehling; Liujun Xiao; Chuang Zhao; Yan Zhu; Sabine J. Seidel. 2020. "The chaos in calibrating crop models." , no. : 1.

Letters
Published: 28 May 2019 in Proceedings of the National Academy of Sciences
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ACS Style

Helena Kahiluoto; Janne Kaseva; Jørgen E. Olesen; Kurt Christian Kersebaum; Margarita Ruiz-Ramos; Anne Gobin; Jozef Takáč; Francoise Ruget; Roberto Ferrise; Jan Balek; Pavol Bezak; Gemma Capellades; Camilla Dibari; Hanna Mäkinen; Claas Nendel; Domenico Ventrella; Alfredo Rodríguez; Marco Bindi; Mirek Trnka. Reply to Snowdon et al. and Piepho: Genetic response diversity to provide yield stability of cultivar groups deserves attention. Proceedings of the National Academy of Sciences 2019, 116, 10627 -10629.

AMA Style

Helena Kahiluoto, Janne Kaseva, Jørgen E. Olesen, Kurt Christian Kersebaum, Margarita Ruiz-Ramos, Anne Gobin, Jozef Takáč, Francoise Ruget, Roberto Ferrise, Jan Balek, Pavol Bezak, Gemma Capellades, Camilla Dibari, Hanna Mäkinen, Claas Nendel, Domenico Ventrella, Alfredo Rodríguez, Marco Bindi, Mirek Trnka. Reply to Snowdon et al. and Piepho: Genetic response diversity to provide yield stability of cultivar groups deserves attention. Proceedings of the National Academy of Sciences. 2019; 116 (22):10627-10629.

Chicago/Turabian Style

Helena Kahiluoto; Janne Kaseva; Jørgen E. Olesen; Kurt Christian Kersebaum; Margarita Ruiz-Ramos; Anne Gobin; Jozef Takáč; Francoise Ruget; Roberto Ferrise; Jan Balek; Pavol Bezak; Gemma Capellades; Camilla Dibari; Hanna Mäkinen; Claas Nendel; Domenico Ventrella; Alfredo Rodríguez; Marco Bindi; Mirek Trnka. 2019. "Reply to Snowdon et al. and Piepho: Genetic response diversity to provide yield stability of cultivar groups deserves attention." Proceedings of the National Academy of Sciences 116, no. 22: 10627-10629.

Research article
Published: 24 December 2018 in Proceedings of the National Academy of Sciences
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Food security relies on the resilience of staple food crops to climatic variability and extremes, but the climate resilience of European wheat is unknown. A diversity of responses to disturbance is considered a key determinant of resilience. The capacity of a sole crop genotype to perform well under climatic variability is limited; therefore, a set of cultivars with diverse responses to weather conditions critical to crop yield is required. Here, we show a decline in the response diversity of wheat in farmers’ fields in most European countries after 2002–2009 based on 101,000 cultivar yield observations. Similar responses to weather were identified in cultivar trials among central European countries and southern European countries. A response diversity hotspot appeared in the trials in Slovakia, while response diversity “deserts” were identified in Czechia and Germany and for durum wheat in southern Europe. Positive responses to abundant precipitation were lacking. This assessment suggests that current breeding programs and cultivar selection practices do not sufficiently prepare for climatic uncertainty and variability. Consequently, the demand for climate resilience of staple food crops such as wheat must be better articulated. Assessments and communication of response diversity enable collective learning across supply chains. Increased awareness could foster governance of resilience through research and breeding programs, incentives, and regulation.

ACS Style

Helena Kahiluoto; Janne Kaseva; Jan Balek; Jørgen E. Olesen; Margarita Ruiz-Ramos; Anne Gobin; Kurt Christian Kersebaum; Jozef Takáč; Francoise Ruget; Roberto Ferrise; Pavol Bezak; Gemma Capellades; Camilla Dibari; Hanna Mäkinen; Claas Nendel; Domenico Ventrella; Alfredo Rodríguez; Marco Bindi; Mirek Trnka. Decline in climate resilience of European wheat. Proceedings of the National Academy of Sciences 2018, 116, 123 -128.

AMA Style

Helena Kahiluoto, Janne Kaseva, Jan Balek, Jørgen E. Olesen, Margarita Ruiz-Ramos, Anne Gobin, Kurt Christian Kersebaum, Jozef Takáč, Francoise Ruget, Roberto Ferrise, Pavol Bezak, Gemma Capellades, Camilla Dibari, Hanna Mäkinen, Claas Nendel, Domenico Ventrella, Alfredo Rodríguez, Marco Bindi, Mirek Trnka. Decline in climate resilience of European wheat. Proceedings of the National Academy of Sciences. 2018; 116 (1):123-128.

Chicago/Turabian Style

Helena Kahiluoto; Janne Kaseva; Jan Balek; Jørgen E. Olesen; Margarita Ruiz-Ramos; Anne Gobin; Kurt Christian Kersebaum; Jozef Takáč; Francoise Ruget; Roberto Ferrise; Pavol Bezak; Gemma Capellades; Camilla Dibari; Hanna Mäkinen; Claas Nendel; Domenico Ventrella; Alfredo Rodríguez; Marco Bindi; Mirek Trnka. 2018. "Decline in climate resilience of European wheat." Proceedings of the National Academy of Sciences 116, no. 1: 123-128.

Primary research articles
Published: 07 December 2018 in Global Change Biology
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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°C 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 are therefore not evenly distributed and will affect regional food security across the globe as well as food prices and trade. This article is protected by copyright. All rights reserved.

ACS Style

Bing Liu; Pierre Martre; Frank Ewert; John R. Porter; Andy J. Challinor; Christoph Müller; Alex C. Ruane; Katharina Waha; Peter J. Thorburn; Pramod K. Aggarwal; Mukhtar Ahmed; Juraj Balkovič; Bruno Basso; Christian Biernath; Marco Bindi; Davide Cammarano; Giacomo De Sanctis; Benjamin Dumont; Mónica Espadafor; Ehsan Eyshi Rezaei; Roberto Ferrise; Margarita Garcia‐Vila; Sebastian Gayler; Yujing Gao; Heidi Horan; Gerrit Hoogenboom; Roberto Izaurralde; Curtis D. Jones; Belay T. Kassie; Kurt Christian Kersebaum; Christian Klein; Ann‐Kristin Koehler; Andrea Maiorano; Sara Minoli; Manuel Montesino San Martin; Soora Naresh Kumar; Claas Nendel; Garry J. O’Leary; Taru Palosuo; Eckart Priesack; Dominique Ripoche; Reimund P. Rötter; Mikhail Semenov; Claudio Stöckle; Thilo Streck; Iwan Supit; Fulu Tao; Marijn Van Der Velde; Daniel Wallach; Enli Wang; Heidi Webber; Joost Wolf; Liujun Xiao; Zhao Zhang; Zhigan Zhao; Yan Zhu; Senthold Asseng. Global wheat production with 1.5 and 2.0°C above pre‐industrial warming. Global Change Biology 2018, 25, 1428 -1444.

AMA Style

Bing Liu, Pierre Martre, Frank Ewert, John R. Porter, Andy J. Challinor, Christoph Müller, Alex C. Ruane, Katharina Waha, Peter J. Thorburn, Pramod K. Aggarwal, Mukhtar Ahmed, Juraj Balkovič, Bruno Basso, Christian Biernath, Marco Bindi, Davide Cammarano, Giacomo De Sanctis, Benjamin Dumont, Mónica Espadafor, Ehsan Eyshi Rezaei, Roberto Ferrise, Margarita Garcia‐Vila, Sebastian Gayler, Yujing Gao, Heidi Horan, Gerrit Hoogenboom, Roberto Izaurralde, Curtis D. Jones, Belay T. Kassie, Kurt Christian Kersebaum, Christian Klein, Ann‐Kristin Koehler, Andrea Maiorano, Sara Minoli, Manuel Montesino San Martin, Soora Naresh Kumar, Claas Nendel, Garry J. O’Leary, Taru Palosuo, Eckart Priesack, Dominique Ripoche, Reimund P. Rötter, Mikhail Semenov, Claudio Stöckle, Thilo Streck, Iwan Supit, Fulu Tao, Marijn Van Der Velde, Daniel Wallach, Enli Wang, Heidi Webber, Joost Wolf, Liujun Xiao, Zhao Zhang, Zhigan Zhao, Yan Zhu, Senthold Asseng. Global wheat production with 1.5 and 2.0°C above pre‐industrial warming. Global Change Biology. 2018; 25 (4):1428-1444.

Chicago/Turabian Style

Bing Liu; Pierre Martre; Frank Ewert; John R. Porter; Andy J. Challinor; Christoph Müller; Alex C. Ruane; Katharina Waha; Peter J. Thorburn; Pramod K. Aggarwal; Mukhtar Ahmed; Juraj Balkovič; Bruno Basso; Christian Biernath; Marco Bindi; Davide Cammarano; Giacomo De Sanctis; Benjamin Dumont; Mónica Espadafor; Ehsan Eyshi Rezaei; Roberto Ferrise; Margarita Garcia‐Vila; Sebastian Gayler; Yujing Gao; Heidi Horan; Gerrit Hoogenboom; Roberto Izaurralde; Curtis D. Jones; Belay T. Kassie; Kurt Christian Kersebaum; Christian Klein; Ann‐Kristin Koehler; Andrea Maiorano; Sara Minoli; Manuel Montesino San Martin; Soora Naresh Kumar; Claas Nendel; Garry J. O’Leary; Taru Palosuo; Eckart Priesack; Dominique Ripoche; Reimund P. Rötter; Mikhail Semenov; Claudio Stöckle; Thilo Streck; Iwan Supit; Fulu Tao; Marijn Van Der Velde; Daniel Wallach; Enli Wang; Heidi Webber; Joost Wolf; Liujun Xiao; Zhao Zhang; Zhigan Zhao; Yan Zhu; Senthold Asseng. 2018. "Global wheat production with 1.5 and 2.0°C above pre‐industrial warming." Global Change Biology 25, no. 4: 1428-1444.

Primary research article
Published: 13 November 2018 in Global Change Biology
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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.

ACS Style

Senthold Asseng; Pierre Martre; Andrea Maiorano; Reimund P. Rötter; Garry J. O’Leary; Glenn J. Fitzgerald; Christine Girousse; Rosella Motzo; Francesco Giunta; M. Ali Babar; Matthew Paul Reynolds; Ahmed M. S. Kheir; Peter J. Thorburn; Katharina Waha; Alex C. Ruane; Pramod K. Aggarwal; Mukhtar Ahmed; Juraj Balkovič; Bruno Basso; Christian Biernath; Marco Bindi; Davide Cammarano; Andrew J. Challinor; Giacomo De Sanctis; Benjamin Dumont; Ehsan Eyshi Rezaei; Elias Fereres; Roberto Ferrise; Margarita Garcia‐Vila; Sebastian Gayler; Yujing Gao; Heidi Horan; Gerrit Hoogenboom; Roberto Izaurralde; Mohamed Jabloun; Curtis D. Jones; Belay T. Kassie; Kurt Christian Kersebaum; Christian Klein; Ann‐Kristin Koehler; Bing Liu; Sara Minoli; Manuel Montesino San Martin; Christoph Müller; Soora Naresh Kumar; Claas Nendel; Jørgen E. Olesen; Taru Palosuo; John R. Porter; Eckart Priesack; Dominique Ripoche; Mikhail Semenov; Claudio Stöckle; Pierre Stratonovitch; Thilo Streck; Iwan Supit; Fulu Tao; Marijn Van Der Velde; Daniel Wallach; Enli Wang; Heidi Webber; Joost Wolf; Liujun Xiao; Zhao Zhang; Zhigan Zhao; Yan Zhu; Frank Ewert. Climate change impact and adaptation for wheat protein. Global Change Biology 2018, 25, 155 -173.

AMA Style

Senthold Asseng, Pierre Martre, Andrea Maiorano, Reimund P. Rötter, Garry J. O’Leary, Glenn J. Fitzgerald, Christine Girousse, Rosella Motzo, Francesco Giunta, M. Ali Babar, Matthew Paul Reynolds, Ahmed M. S. Kheir, Peter J. Thorburn, Katharina Waha, Alex C. Ruane, Pramod K. Aggarwal, Mukhtar Ahmed, Juraj Balkovič, Bruno Basso, Christian Biernath, Marco Bindi, Davide Cammarano, Andrew J. Challinor, Giacomo De Sanctis, Benjamin Dumont, Ehsan Eyshi Rezaei, Elias Fereres, Roberto Ferrise, Margarita Garcia‐Vila, Sebastian Gayler, Yujing Gao, Heidi Horan, Gerrit Hoogenboom, Roberto Izaurralde, Mohamed Jabloun, Curtis D. Jones, Belay T. Kassie, Kurt Christian Kersebaum, Christian Klein, Ann‐Kristin Koehler, Bing Liu, Sara Minoli, Manuel Montesino San Martin, Christoph Müller, Soora Naresh Kumar, Claas Nendel, Jørgen E. Olesen, Taru Palosuo, John R. Porter, Eckart Priesack, Dominique Ripoche, Mikhail Semenov, Claudio Stöckle, Pierre Stratonovitch, Thilo Streck, Iwan Supit, Fulu Tao, Marijn Van Der Velde, Daniel Wallach, Enli Wang, Heidi Webber, Joost Wolf, Liujun Xiao, Zhao Zhang, Zhigan Zhao, Yan Zhu, Frank Ewert. Climate change impact and adaptation for wheat protein. Global Change Biology. 2018; 25 (1):155-173.

Chicago/Turabian Style

Senthold Asseng; Pierre Martre; Andrea Maiorano; Reimund P. Rötter; Garry J. O’Leary; Glenn J. Fitzgerald; Christine Girousse; Rosella Motzo; Francesco Giunta; M. Ali Babar; Matthew Paul Reynolds; Ahmed M. S. Kheir; Peter J. Thorburn; Katharina Waha; Alex C. Ruane; Pramod K. Aggarwal; Mukhtar Ahmed; Juraj Balkovič; Bruno Basso; Christian Biernath; Marco Bindi; Davide Cammarano; Andrew J. Challinor; Giacomo De Sanctis; Benjamin Dumont; Ehsan Eyshi Rezaei; Elias Fereres; Roberto Ferrise; Margarita Garcia‐Vila; Sebastian Gayler; Yujing Gao; Heidi Horan; Gerrit Hoogenboom; Roberto Izaurralde; Mohamed Jabloun; Curtis D. Jones; Belay T. Kassie; Kurt Christian Kersebaum; Christian Klein; Ann‐Kristin Koehler; Bing Liu; Sara Minoli; Manuel Montesino San Martin; Christoph Müller; Soora Naresh Kumar; Claas Nendel; Jørgen E. Olesen; Taru Palosuo; John R. Porter; Eckart Priesack; Dominique Ripoche; Mikhail Semenov; Claudio Stöckle; Pierre Stratonovitch; Thilo Streck; Iwan Supit; Fulu Tao; Marijn Van Der Velde; Daniel Wallach; Enli Wang; Heidi Webber; Joost Wolf; Liujun Xiao; Zhao Zhang; Zhigan Zhao; Yan Zhu; Frank Ewert. 2018. "Climate change impact and adaptation for wheat protein." Global Change Biology 25, no. 1: 155-173.

Journal article
Published: 12 October 2018 in Nature Communications
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Understanding the drivers of yield levels under climate change is required to support adaptation planning and respond to changing production risks. This study uses an ensemble of crop models applied on a spatial grid to quantify the contributions of various climatic drivers to past yield variability in grain maize and winter wheat of European cropping systems (1984–2009) and drivers of climate change impacts to 2050. Results reveal that for the current genotypes and mix of irrigated and rainfed production, climate change would lead to yield losses for grain maize and gains for winter wheat. Across Europe, on average heat stress does not increase for either crop in rainfed systems, while drought stress intensifies for maize only. In low-yielding years, drought stress persists as the main driver of losses for both crops, with elevated CO2 offering no yield benefit in these years. Drivers of crop yield variability require quantification, and historical records can help in improving understanding. Here, Webber et al. report that drought stress will remain a key driver of yield losses in wheat and maize across Europe, and benefits from CO2 will be limited in low-yielding years.

ACS Style

Heidi Webber; Frank Ewert; Jørgen E. Olesen; Christoph Müller; Stefan Fronzek; Alex C. Ruane; Maryse Bourgault; Pierre Martre; Behnam Ababaei; Marco Bindi; Roberto Ferrise; Robert Finger; Nándor Fodor; Clara Gabaldón-Leal; Thomas Gaiser; Mohamed Jabloun; Kurt-Christian Kersebaum; Jon I. Lizaso; Ignacio J. Lorite; Loic Manceau; Marco Moriondo; Claas Nendel; Alfredo Rodríguez; Margarita Ruiz-Ramos; Mikhail Semenov; Stefan Siebert; Tommaso Stella; Pierre Stratonovitch; Giacomo Trombi; Daniel Wallach. Diverging importance of drought stress for maize and winter wheat in Europe. Nature Communications 2018, 9, 1 -10.

AMA Style

Heidi Webber, Frank Ewert, Jørgen E. Olesen, Christoph Müller, Stefan Fronzek, Alex C. Ruane, Maryse Bourgault, Pierre Martre, Behnam Ababaei, Marco Bindi, Roberto Ferrise, Robert Finger, Nándor Fodor, Clara Gabaldón-Leal, Thomas Gaiser, Mohamed Jabloun, Kurt-Christian Kersebaum, Jon I. Lizaso, Ignacio J. Lorite, Loic Manceau, Marco Moriondo, Claas Nendel, Alfredo Rodríguez, Margarita Ruiz-Ramos, Mikhail Semenov, Stefan Siebert, Tommaso Stella, Pierre Stratonovitch, Giacomo Trombi, Daniel Wallach. Diverging importance of drought stress for maize and winter wheat in Europe. Nature Communications. 2018; 9 (1):1-10.

Chicago/Turabian Style

Heidi Webber; Frank Ewert; Jørgen E. Olesen; Christoph Müller; Stefan Fronzek; Alex C. Ruane; Maryse Bourgault; Pierre Martre; Behnam Ababaei; Marco Bindi; Roberto Ferrise; Robert Finger; Nándor Fodor; Clara Gabaldón-Leal; Thomas Gaiser; Mohamed Jabloun; Kurt-Christian Kersebaum; Jon I. Lizaso; Ignacio J. Lorite; Loic Manceau; Marco Moriondo; Claas Nendel; Alfredo Rodríguez; Margarita Ruiz-Ramos; Mikhail Semenov; Stefan Siebert; Tommaso Stella; Pierre Stratonovitch; Giacomo Trombi; Daniel Wallach. 2018. "Diverging importance of drought stress for maize and winter wheat in Europe." Nature Communications 9, no. 1: 1-10.

Journal article
Published: 09 October 2018 in Agricultural and Forest Meteorology
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Climate change is expected to severely affect cropping systems and food production in many parts of the world unless local adaptation can ameliorate these impacts. Ensembles of crop simulation models can be useful tools for assessing if proposed adaptation options are capable of achieving target yields, whilst also quantifying the share of uncertainty in the simulated crop impact resulting from the crop models themselves. Although some studies have analysed the influence of ensemble size on model outcomes, the effect of ensemble composition has not yet been properly appraised. Moreover, results and derived recommendations typically rely on averaged ensemble simulation results without accounting sufficiently for the spread of model outcomes. Therefore, we developed an Ensemble Outcome Agreement (EOA) index, which analyses the effect of changes in composition and size of a multi-model ensemble (MME) to evaluate the level of agreement between MME outcomes with respect to a given hypothesis (e.g. that adaptation measures result in positive crop responses). We analysed the recommendations of a previous study performed with an ensemble of 17 crop models and testing 54 adaptation options for rainfed winter wheat (Triticum aestivum L.) at Lleida (NE Spain) under perturbed conditions of temperature, precipitation and atmospheric CO2 concentration. Our results confirmed that most adaptations recommended in the previous study have a positive effect. However, we also showed that some options did not remain recommendable in specific conditions if different ensembles were considered. Using EOA, we were able to identify the adaptation options for which there is high confidence in their effectiveness at enhancing yields, even under severe climate perturbations. These include substituting spring wheat for winter wheat combined with earlier sowing dates and standard or longer duration cultivars, or introducing supplementary irrigation, the latter increasing EOA values in all cases. There is low confidence in recovering yields to baseline levels, although this target could be attained for some adaptation options under moderate climate perturbations. Recommendations derived from such robust results may provide crucial information for stakeholders seeking to implement adaptation measures.

ACS Style

A. Rodríguez; M. Ruiz-Ramos; Taru Palosuo; T.R. Carter; Stefan Fronzek; I.J. Lorite; Roberto Ferrise; N. Pirttioja; Marco Bindi; P. Baranowski; S. Buis; D. Cammarano; Y. Chen; B. Dumont; F. Ewert; T. Gaiser; P. Hlavinka; H. Hoffmann; J.G. Höhn; F. Jurecka; K.C. Kersebaum; J. Krzyszczak; M. Lana; Altaaf Mechiche-Alami; J. Minet; M. Montesino; C. Nendel; J.R. Porter; F. Ruget; Mikhail Semenov; Z. Steinmetz; P. Stratonovitch; I. Supit; F. Tao; M. Trnka; A. de Wit; R.P. Rötter. Implications of crop model ensemble size and composition for estimates of adaptation effects and agreement of recommendations. Agricultural and Forest Meteorology 2018, 264, 351 -362.

AMA Style

A. Rodríguez, M. Ruiz-Ramos, Taru Palosuo, T.R. Carter, Stefan Fronzek, I.J. Lorite, Roberto Ferrise, N. Pirttioja, Marco Bindi, P. Baranowski, S. Buis, D. Cammarano, Y. Chen, B. Dumont, F. Ewert, T. Gaiser, P. Hlavinka, H. Hoffmann, J.G. Höhn, F. Jurecka, K.C. Kersebaum, J. Krzyszczak, M. Lana, Altaaf Mechiche-Alami, J. Minet, M. Montesino, C. Nendel, J.R. Porter, F. Ruget, Mikhail Semenov, Z. Steinmetz, P. Stratonovitch, I. Supit, F. Tao, M. Trnka, A. de Wit, R.P. Rötter. Implications of crop model ensemble size and composition for estimates of adaptation effects and agreement of recommendations. Agricultural and Forest Meteorology. 2018; 264 ():351-362.

Chicago/Turabian Style

A. Rodríguez; M. Ruiz-Ramos; Taru Palosuo; T.R. Carter; Stefan Fronzek; I.J. Lorite; Roberto Ferrise; N. Pirttioja; Marco Bindi; P. Baranowski; S. Buis; D. Cammarano; Y. Chen; B. Dumont; F. Ewert; T. Gaiser; P. Hlavinka; H. Hoffmann; J.G. Höhn; F. Jurecka; K.C. Kersebaum; J. Krzyszczak; M. Lana; Altaaf Mechiche-Alami; J. Minet; M. Montesino; C. Nendel; J.R. Porter; F. Ruget; Mikhail Semenov; Z. Steinmetz; P. Stratonovitch; I. Supit; F. Tao; M. Trnka; A. de Wit; R.P. Rötter. 2018. "Implications of crop model ensemble size and composition for estimates of adaptation effects and agreement of recommendations." Agricultural and Forest Meteorology 264, no. : 351-362.

Original research article
Published: 08 August 2018 in Frontiers in Plant Science
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Soil organic carbon (SOC) has a vital role to enhance agricultural productivity and for mitigation of climate change. To quantify SOC effects on productivity, process models serve as a robust tool to keep track of multiple plant and soil factors and their interactions affecting SOC dynamics. We used soil-plant-atmospheric model viz. DAISY, to assess effects of SOC on nitrogen (N) supply and plant available water (PAW) under varying N fertilizer rates in winter wheat (Triticum aestivum) in Denmark. The study objective was assessment of SOC effects on winter wheat grain and aboveground biomass accumulation at three SOC levels (low: 0.7% SOC; reference: 1.3% SOC; and high: 2% SOC) with five nitrogen rates (0–200 kg N ha-1) and PAW at low, reference, and high SOC levels. The three SOC levels had significant effects on grain yields and aboveground biomass accumulation at only 0–100 kg N ha-1 and the SOC effects decreased with increasing N rates until no effects at 150–200 kg N ha-1. PAW had significant positive correlation with SOC content, with high SOC retaining higher PAW compared to low and reference SOC. The mean PAW and SOC correlation was given by PAW% = 1.0073 × SOC% + 15.641. For the 0.7–2% SOC range, the PAW increase was small with no significant effects on grain yields and aboveground biomass accumulation. The higher winter wheat grain and aboveground biomass was attributed to higher N supply in N deficient wheat production system. Our study suggested that building SOC enhances agronomic productivity at only 0–100 kg N ha-1. Maintenance of SOC stock will require regular replenishment of SOC, to compensate for the mineralization process degrading SOC over time. Hence, management can maximize realization of SOC benefits by building up SOC and maintaining N rates in the range 0–100 kg N ha-1, to reduce the off-farm N losses depending on the environmental zones, land use and the production system.

ACS Style

Bhim B. Ghaley; Henk Wösten; Jørgen E. Olesen; Kirsten Schelde; Sanmohan Baby; Yubaraj K. Karki; Christen D. Børgesen; Pete Smith; Jagadeesh Yeluripati; Roberto Ferrise; Marco Bindi; Peter Kuikman; Jan-Peter Lesschen; John R. Porter. Simulation of Soil Organic Carbon Effects on Long-Term Winter Wheat (Triticum aestivum) Production Under Varying Fertilizer Inputs. Frontiers in Plant Science 2018, 9, 1158 .

AMA Style

Bhim B. Ghaley, Henk Wösten, Jørgen E. Olesen, Kirsten Schelde, Sanmohan Baby, Yubaraj K. Karki, Christen D. Børgesen, Pete Smith, Jagadeesh Yeluripati, Roberto Ferrise, Marco Bindi, Peter Kuikman, Jan-Peter Lesschen, John R. Porter. Simulation of Soil Organic Carbon Effects on Long-Term Winter Wheat (Triticum aestivum) Production Under Varying Fertilizer Inputs. Frontiers in Plant Science. 2018; 9 ():1158.

Chicago/Turabian Style

Bhim B. Ghaley; Henk Wösten; Jørgen E. Olesen; Kirsten Schelde; Sanmohan Baby; Yubaraj K. Karki; Christen D. Børgesen; Pete Smith; Jagadeesh Yeluripati; Roberto Ferrise; Marco Bindi; Peter Kuikman; Jan-Peter Lesschen; John R. Porter. 2018. "Simulation of Soil Organic Carbon Effects on Long-Term Winter Wheat (Triticum aestivum) Production Under Varying Fertilizer Inputs." Frontiers in Plant Science 9, no. : 1158.

Original article
Published: 10 July 2018 in Mitigation and Adaptation Strategies for Global Change
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The need to reduce the expected impact of climate change, finding sustainable ways to maintain or increase the carbon (C) sequestration capacity and productivity of agricultural systems, is one of the most important challenges of the twenty-first century. Olive (Olea europaea L.) groves can play a fundamental role due to their potential to sequester C in soil and woody compartments, associated with widespread cultivation in the Mediterranean basin. The implementation of field experiments to assess olive grove responses under different conditions, complemented by simulation models, can be a powerful approach to explore future land-atmosphere C feedbacks. The DayCent biogeochemical model was calibrated and validated against observed net ecosystem exchange, net primary productivity, aboveground biomass, leaf area index, and yield in two Italian olive groves. In addition, potential changes in C-sequestration capacity and productivity were assessed under two types of management (extensive and intensive), 35 climate change scenarios (ΔT-temperature from + 0 °C to + 3 °C; ΔP-precipitation from 0.0 to − 20%), and six areas across the Mediterranean basin (Brindisi, Coimbra, Crete, Cordoba, Florence, and Montpellier). The results indicated that (i) the DayCent model, properly calibrated, can be used to quantify olive grove daily net ecosystem exchange and net primary production dynamics; (ii) a decrease in net ecosystem exchange and net primary production is predicted under both types of management by approaching the most extreme climate conditions (ΔT = + 3 °C; ΔP = − 20%), especially in dry and warm areas; (iii) irrigation can compensate for net ecosystem exchange and net primary production losses in almost all areas, while ecophysiological air temperature thresholds determine the magnitude and sign of C-uptake; (iv) future warming is expected to modify the seasonal net ecosystem exchange and net primary production pattern, with higher photosynthetic activity in winter and a prolonged period of photosynthesis inhibition during summer compared to the baseline; (v) a substantial decrease in mitigation capacity and productivity of extensively managed olive groves is expected to accelerate between + 1.5 and + 2 °C warming compared to the current period, across all Mediterranean areas; (vi) adaptation measures aimed at increasing soil water content or evapotranspiration reduction should be considered the mostly suitable for limiting the decrease of both production and mitigation capacity in the next decades.

ACS Style

L. Brilli; E. Lugato; M. Moriondo; B. Gioli; Piero Toscano; A. Zaldei; L. Leolini; C. Cantini; G. Caruso; R. Gucci; P. Merante; Camilla Dibari; Roberto Ferrise; M. Bindi; Sergi Costafreda-Aumedes. Carbon sequestration capacity and productivity responses of Mediterranean olive groves under future climates and management options. Mitigation and Adaptation Strategies for Global Change 2018, 24, 467 -491.

AMA Style

L. Brilli, E. Lugato, M. Moriondo, B. Gioli, Piero Toscano, A. Zaldei, L. Leolini, C. Cantini, G. Caruso, R. Gucci, P. Merante, Camilla Dibari, Roberto Ferrise, M. Bindi, Sergi Costafreda-Aumedes. Carbon sequestration capacity and productivity responses of Mediterranean olive groves under future climates and management options. Mitigation and Adaptation Strategies for Global Change. 2018; 24 (3):467-491.

Chicago/Turabian Style

L. Brilli; E. Lugato; M. Moriondo; B. Gioli; Piero Toscano; A. Zaldei; L. Leolini; C. Cantini; G. Caruso; R. Gucci; P. Merante; Camilla Dibari; Roberto Ferrise; M. Bindi; Sergi Costafreda-Aumedes. 2018. "Carbon sequestration capacity and productivity responses of Mediterranean olive groves under future climates and management options." Mitigation and Adaptation Strategies for Global Change 24, no. 3: 467-491.

Journal article
Published: 01 June 2018 in Field Crops Research
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L. Leolini; M. Moriondo; G. Fila; Sergi Costafreda-Aumedes; Roberto Ferrise; Marco Bindi. Late spring frost impacts on future grapevine distribution in Europe. Field Crops Research 2018, 222, 197 -208.

AMA Style

L. Leolini, M. Moriondo, G. Fila, Sergi Costafreda-Aumedes, Roberto Ferrise, Marco Bindi. Late spring frost impacts on future grapevine distribution in Europe. Field Crops Research. 2018; 222 ():197-208.

Chicago/Turabian Style

L. Leolini; M. Moriondo; G. Fila; Sergi Costafreda-Aumedes; Roberto Ferrise; Marco Bindi. 2018. "Late spring frost impacts on future grapevine distribution in Europe." Field Crops Research 222, no. : 197-208.

Journal article
Published: 01 June 2018 in Field Crops Research
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ACS Style

H. Mäkinen; J. Kaseva; Miroslav Trnka; J. Balek; Kurt Christian Kersebaum; C. Nendel; Anne Gobin; Jørgen E. Olesen; Marco Bindi; Roberto Ferrise; M. Moriondo; A. Rodríguez; M. Ruiz-Ramos; J. Takáč; P. Bezák; Domenico Ventrella; F. Ruget; G. Capellades; H. Kahiluoto. Sensitivity of European wheat to extreme weather. Field Crops Research 2018, 222, 209 -217.

AMA Style

H. Mäkinen, J. Kaseva, Miroslav Trnka, J. Balek, Kurt Christian Kersebaum, C. Nendel, Anne Gobin, Jørgen E. Olesen, Marco Bindi, Roberto Ferrise, M. Moriondo, A. Rodríguez, M. Ruiz-Ramos, J. Takáč, P. Bezák, Domenico Ventrella, F. Ruget, G. Capellades, H. Kahiluoto. Sensitivity of European wheat to extreme weather. Field Crops Research. 2018; 222 ():209-217.

Chicago/Turabian Style

H. Mäkinen; J. Kaseva; Miroslav Trnka; J. Balek; Kurt Christian Kersebaum; C. Nendel; Anne Gobin; Jørgen E. Olesen; Marco Bindi; Roberto Ferrise; M. Moriondo; A. Rodríguez; M. Ruiz-Ramos; J. Takáč; P. Bezák; Domenico Ventrella; F. Ruget; G. Capellades; H. Kahiluoto. 2018. "Sensitivity of European wheat to extreme weather." Field Crops Research 222, no. : 209-217.

Journal article
Published: 01 February 2018 in Field Crops Research
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ACS Style

Heidi Webber; Jeffrey W. White; Bruce A. Kimball; Frank Ewert; Senthold Asseng; Ehsan Eyshi Rezaei; Paul J. Pinter; Jerry L. Hatfield; Matthew Paul Reynolds; Behnam Ababaei; Marco Bindi; Jordi Doltra; Roberto Ferrise; Henning Kage; Belay T. Kassie; Kurt Christian Kersebaum; Adam Luig; Jørgen E. Olesen; Mikhail Semenov; Pierre Stratonovitch; Arne M. Ratjen; Robert L. LaMorte; Steven W. Leavitt; Douglas J. Hunsaker; Gerard W. Wall; Pierre Martre. Physical robustness of canopy temperature models for crop heat stress simulation across environments and production conditions. Field Crops Research 2018, 216, 75 -88.

AMA Style

Heidi Webber, Jeffrey W. White, Bruce A. Kimball, Frank Ewert, Senthold Asseng, Ehsan Eyshi Rezaei, Paul J. Pinter, Jerry L. Hatfield, Matthew Paul Reynolds, Behnam Ababaei, Marco Bindi, Jordi Doltra, Roberto Ferrise, Henning Kage, Belay T. Kassie, Kurt Christian Kersebaum, Adam Luig, Jørgen E. Olesen, Mikhail Semenov, Pierre Stratonovitch, Arne M. Ratjen, Robert L. LaMorte, Steven W. Leavitt, Douglas J. Hunsaker, Gerard W. Wall, Pierre Martre. Physical robustness of canopy temperature models for crop heat stress simulation across environments and production conditions. Field Crops Research. 2018; 216 ():75-88.

Chicago/Turabian Style

Heidi Webber; Jeffrey W. White; Bruce A. Kimball; Frank Ewert; Senthold Asseng; Ehsan Eyshi Rezaei; Paul J. Pinter; Jerry L. Hatfield; Matthew Paul Reynolds; Behnam Ababaei; Marco Bindi; Jordi Doltra; Roberto Ferrise; Henning Kage; Belay T. Kassie; Kurt Christian Kersebaum; Adam Luig; Jørgen E. Olesen; Mikhail Semenov; Pierre Stratonovitch; Arne M. Ratjen; Robert L. LaMorte; Steven W. Leavitt; Douglas J. Hunsaker; Gerard W. Wall; Pierre Martre. 2018. "Physical robustness of canopy temperature models for crop heat stress simulation across environments and production conditions." Field Crops Research 216, no. : 75-88.

Journal article
Published: 01 January 2018 in Agricultural Systems
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Crop growth simulation models can differ greatly in their treatment of key processes and hence in their response to environmental conditions. Here, we used an ensemble of 26 process-based wheat models applied at sites across a European transect to compare their sensitivity to changes in temperature (−2 to +9°C) and precipitation (−50 to +50%). Model results were analysed by plotting them as impact response surfaces (IRSs), classifying the IRS patterns of individual model simulations, describing these classes and analysing factors that may explain the major differences in model responses. The model ensemble was used to simulate yields of winter and spring wheat at four sites in Finland, Germany and Spain. Results were plotted as IRSs that show changes in yields relative to the baseline with respect to temperature and precipitation. IRSs of 30-year means and selected extreme years were classified using two approaches describing their pattern.The expert diagnostic approach (EDA) combines two aspects of IRS patterns: location of the maximum yield (nine classes) and strength of the yield response with respect to climate (four classes), resulting in a total of 36 combined classes defined using criteria pre-specified by experts. The statistical diagnostic approach (SDA) groups IRSs by comparing their pattern and magnitude, without attempting to interpret these features. It applies a hierarchical clustering method, grouping response patterns using a distance metric that combines the spatial correlation and Euclidian distance between IRS pairs. The two approaches were used to investigate whether different patterns of yield response could be related to different properties of the crop models, specifically their genealogy, calibration and process description. Although no single model property across a large model ensemble was found to explain the integrated yield response to temperature and precipitation perturbations, the application of the EDA and SDA approaches revealed their capability to distinguish: (i) stronger yield responses to precipitation for winter wheat than spring wheat; (ii) differing strengths of response to climate changes for years with anomalous weather conditions compared to period-average conditions; (iii) the influence of site conditions on yield patterns; (iv) similarities in IRS patterns among models with related genealogy; (v) similarities in IRS patterns for models with simpler process descriptions of root growth and water uptake compared to those with more complex descriptions; and (vi) a closer correspondence of IRS patterns in models using partitioning schemes to represent yield formation than in those using a harvest index. Such results can inform future crop modelling studies that seek to exploit the diversity of multi-model ensembles, by distinguishing ensemble members that span a wide range of responses as well as those that display implausible behaviour or strong mutual similarities

ACS Style

Stefan Fronzek; Nina Pirttioja; Timothy R. Carter; Marco Bindi; Holger Hoffmann; Taru Palosuo; Margarita Ruiz-Ramos; Fulu Tao; Miroslav Trnka; Marco Acutis; Senthold Asseng; Piotr Baranowski; Bruno Basso; Per Bodin; Samuel Buis; Davide Cammarano; Paola Deligios; Marie-France Destain; Benjamin Dumont; Frank Ewert; Roberto Ferrise; Louis François; Thomas Gaiser; Petr Hlavinka; Ingrid Jacquemin; Kurt Christian Kersebaum; Chris Kollas; Jaromir Krzyszczak; Ignacio Lorite; Julien Minet; M Ines Minguez; Manuel Montesino; Marco Moriondo; Christoph Müller; Claas Nendel; Isik Öztürk; Alessia Perego; Alfredo Rodríguez; Alex C. Ruane; Françoise Ruget; Mattia Sanna; Mikhail Semenov; Cezary Sławiński; Pierre Stratonovitch; Iwan Supit; Katharina Waha; Enli Wang; Lianhai Wu; Zhigan Zhao; Reimund Rötter. Classifying multi-model wheat yield impact response surfaces showing sensitivity to temperature and precipitation change. Agricultural Systems 2018, 159, 209 -224.

AMA Style

Stefan Fronzek, Nina Pirttioja, Timothy R. Carter, Marco Bindi, Holger Hoffmann, Taru Palosuo, Margarita Ruiz-Ramos, Fulu Tao, Miroslav Trnka, Marco Acutis, Senthold Asseng, Piotr Baranowski, Bruno Basso, Per Bodin, Samuel Buis, Davide Cammarano, Paola Deligios, Marie-France Destain, Benjamin Dumont, Frank Ewert, Roberto Ferrise, Louis François, Thomas Gaiser, Petr Hlavinka, Ingrid Jacquemin, Kurt Christian Kersebaum, Chris Kollas, Jaromir Krzyszczak, Ignacio Lorite, Julien Minet, M Ines Minguez, Manuel Montesino, Marco Moriondo, Christoph Müller, Claas Nendel, Isik Öztürk, Alessia Perego, Alfredo Rodríguez, Alex C. Ruane, Françoise Ruget, Mattia Sanna, Mikhail Semenov, Cezary Sławiński, Pierre Stratonovitch, Iwan Supit, Katharina Waha, Enli Wang, Lianhai Wu, Zhigan Zhao, Reimund Rötter. Classifying multi-model wheat yield impact response surfaces showing sensitivity to temperature and precipitation change. Agricultural Systems. 2018; 159 ():209-224.

Chicago/Turabian Style

Stefan Fronzek; Nina Pirttioja; Timothy R. Carter; Marco Bindi; Holger Hoffmann; Taru Palosuo; Margarita Ruiz-Ramos; Fulu Tao; Miroslav Trnka; Marco Acutis; Senthold Asseng; Piotr Baranowski; Bruno Basso; Per Bodin; Samuel Buis; Davide Cammarano; Paola Deligios; Marie-France Destain; Benjamin Dumont; Frank Ewert; Roberto Ferrise; Louis François; Thomas Gaiser; Petr Hlavinka; Ingrid Jacquemin; Kurt Christian Kersebaum; Chris Kollas; Jaromir Krzyszczak; Ignacio Lorite; Julien Minet; M Ines Minguez; Manuel Montesino; Marco Moriondo; Christoph Müller; Claas Nendel; Isik Öztürk; Alessia Perego; Alfredo Rodríguez; Alex C. Ruane; Françoise Ruget; Mattia Sanna; Mikhail Semenov; Cezary Sławiński; Pierre Stratonovitch; Iwan Supit; Katharina Waha; Enli Wang; Lianhai Wu; Zhigan Zhao; Reimund Rötter. 2018. "Classifying multi-model wheat yield impact response surfaces showing sensitivity to temperature and precipitation change." Agricultural Systems 159, no. : 209-224.

Journal article
Published: 01 January 2018 in Agricultural Systems
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This work was financially supported by the Spanish National Institute for Agricultural and Food Research and Technology (INIA, MACSUR01-UPM), the Italian Ministry of Agriculture and Forestry and the Finnish Ministry of Agriculture and Forestry (D.M. 24064/7303/15) through FACCE MACSUR − Modelling European Agriculture with Climate Change for Food Security, a FACCE JPI knowledge hub; MULCLIVAR, from the Spanish Ministerio de Economía y Competitividad (MINECO, CGL2012-38923-C02-02); the Academy of Finland (decisions: 277276 and 277403), the EU FP7 IMPRESSIONS project (grant agreement no. 603416), the NORFASYS project (decision nos. 268277 and 292944) and PLUMES project (decision nos. 277403 and 292836); project IGA AF MENDELU no. 7/2015 with the support of the Specific University Research Grant provided by the Ministry of Education, Youth Sports of the Czech Republic; the Ministry of Education, Youth Sports of the Czech Republic within the National Sustainability Programme I (NPU I), grant number LO1415 NAZV QJ1310123 the Polish National Centre for Research and Development in frame of the projects: LCAgri, contract number BIOSTRATEG1/271322/3/NCBR/2015 and GyroScan, contract number BIOSTRATEG2/298782/11/NCBR/2016.Adaptation of crops to climate change has to be addressed locally due to the variability of soil, climate and the specific socio-economic settings influencing farm management decisions. Adaptation of rainfed cropping systems in the Mediterranean is especially challenging due to the projected decline in precipitation in the coming decades, which will increase the risk of droughts. Methods that can help explore uncertainties in climate projections and crop modelling, such as impact response surfaces (IRSs) and ensemble modelling, can then be valuable for identifying effective adaptations. Here, an ensemble of 17 crop models was used to simulate a total of 54 adaptation options for rainfed winter wheat (Triticum aestivum) at Lleida (NE Spain). To support the ensemble building, an ex post quality check of model simulations based on several criteria was performed. Those criteria were based on the “According to Our Current Knowledge” (AOCK) concept, which has been formalized here. Adaptations were based on changes in cultivars and management regarding phenology, vernalization, sowing date and irrigation. The effects of adaptation options under changed precipitation (P), temperature (T), [CO2] and soil type were analysed by constructing response surfaces, which we termed, in accordance with their specific purpose, adaptation response surfaces (ARSs). These were created to assess the effect of adaptations through a range of plausible P, T and [CO2] perturbations. The results indicated that impacts of altered climate were predominantly negative. No single adaptation was capable of overcoming the detrimental effect of the complex interactions imposed by the P, T and [CO2] perturbations except for supplementary irrigation (sI), which reduced the potential impacts under most of the perturbations. Yet, a combination of adaptations for dealing with climate change demonstrated that effective adaptation is possible at Lleida. Combinations based on a cultivar without vernalization requirements showed good and wide adaptation potential. Few combined adaptation options performed well under rainfed conditions. However, a single sI was sufficient to develop a high adaptation potential, including options mainly based on spring wheat, current cycle duration and early sowing date. Depending on local environment (e.g. soil type), many of these adaptations can maintain current yield levels under moderate changes in T and P, and some also under strong changes. We conclude that ARSs can offer a useful tool for supporting planning of field level adaptation under conditions of high uncertainty

ACS Style

M. Ruiz-Ramos; R. Ferrise; A. Rodríguez; Ignacio Lorite; Marco Bindi; T.R. Carter; Stefan Fronzek; Taru Palosuo; N. Pirttioja; Piotr Baranowski; S. Buis; Davide Cammarano; Y. Chen; B. Dumont; F. Ewert; T. Gaiser; P. Hlavinka; H. Hoffmann; J.G. Höhn; F. Jurecka; Kurt Christian Kersebaum; Jaromir Krzyszczak; Marcos Lana; Altaaf Mechiche-Alami; J. Minet; M. Montesino; C. Nendel; J.R. Porter; F. Ruget; Mikhail Semenov; Z. Steinmetz; P. Stratonovitch; I. Supit; F Tao; M. Trnka; A. de Wit; Reimund Rötter. Adaptation response surfaces for managing wheat under perturbed climate and CO2 in a Mediterranean environment. Agricultural Systems 2018, 159, 260 -274.

AMA Style

M. Ruiz-Ramos, R. Ferrise, A. Rodríguez, Ignacio Lorite, Marco Bindi, T.R. Carter, Stefan Fronzek, Taru Palosuo, N. Pirttioja, Piotr Baranowski, S. Buis, Davide Cammarano, Y. Chen, B. Dumont, F. Ewert, T. Gaiser, P. Hlavinka, H. Hoffmann, J.G. Höhn, F. Jurecka, Kurt Christian Kersebaum, Jaromir Krzyszczak, Marcos Lana, Altaaf Mechiche-Alami, J. Minet, M. Montesino, C. Nendel, J.R. Porter, F. Ruget, Mikhail Semenov, Z. Steinmetz, P. Stratonovitch, I. Supit, F Tao, M. Trnka, A. de Wit, Reimund Rötter. Adaptation response surfaces for managing wheat under perturbed climate and CO2 in a Mediterranean environment. Agricultural Systems. 2018; 159 ():260-274.

Chicago/Turabian Style

M. Ruiz-Ramos; R. Ferrise; A. Rodríguez; Ignacio Lorite; Marco Bindi; T.R. Carter; Stefan Fronzek; Taru Palosuo; N. Pirttioja; Piotr Baranowski; S. Buis; Davide Cammarano; Y. Chen; B. Dumont; F. Ewert; T. Gaiser; P. Hlavinka; H. Hoffmann; J.G. Höhn; F. Jurecka; Kurt Christian Kersebaum; Jaromir Krzyszczak; Marcos Lana; Altaaf Mechiche-Alami; J. Minet; M. Montesino; C. Nendel; J.R. Porter; F. Ruget; Mikhail Semenov; Z. Steinmetz; P. Stratonovitch; I. Supit; F Tao; M. Trnka; A. de Wit; Reimund Rötter. 2018. "Adaptation response surfaces for managing wheat under perturbed climate and CO2 in a Mediterranean environment." Agricultural Systems 159, no. : 260-274.

Primary research article
Published: 06 November 2017 in Global Change Biology
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Climate change impact assessments are plagued with uncertainties from many sources, such as climate projections or the inadequacies in structure and parameters of the impact model. Previous studies tried to account for the uncertainty from one or two of these. Here, we developed a triple‐ensemble probabilistic assessment using seven crop models, multiple sets of model parameters and eight contrasting climate projections together to comprehensively account for uncertainties from these three important sources. We demonstrated the approach in assessing climate change impact on barley growth and yield at Jokioinen, Finland in the Boreal climatic zone and Lleida, Spain in the Mediterranean climatic zone, for the 2050s. We further quantified and compared the contribution of crop model structure, crop model parameters and climate projections to the total variance of ensemble output using Analysis of Variance (ANOVA). Based on the triple‐ensemble probabilistic assessment, the median of simulated yield change was −4% and +16%, and the probability of decreasing yield was 63% and 31% in the 2050s, at Jokioinen and Lleida, respectively, relative to 1981–2010. The contribution of crop model structure to the total variance of ensemble output was larger than that from downscaled climate projections and model parameters. The relative contribution of crop model parameters and downscaled climate projections to the total variance of ensemble output varied greatly among the seven crop models and between the two sites. The contribution of downscaled climate projections was on average larger than that of crop model parameters. This information on the uncertainty from different sources can be quite useful for model users to decide where to put the most effort when preparing or choosing models or parameters for impact analyses. We concluded that the triple‐ensemble probabilistic approach that accounts for the uncertainties from multiple important sources provide more comprehensive information for quantifying uncertainties in climate change impact assessments as compared to the conventional approaches that are deterministic or only account for the uncertainties from one or two of the uncertainty sources.

ACS Style

F Tao; Reimund Rötter; Taru Palosuo; Carlos Gregorio Hernández Díaz‐Ambrona; M Ines Minguez; Mikhail Semenov; Kurt Christian Kersebaum; Claas Nendel; Xenia Specka; Holger Hoffmann; Frank Ewert; Anaelle Dambreville; Pierre Martre; Lucía Rodríguez; Margarita Ruiz‐Ramos; Thomas Gaiser; Jukka G. Höhn; Tapio Salo; Roberto Ferrise; Marco Bindi; Davide Cammarano; Alan H. Schulman. Contribution of crop model structure, parameters and climate projections to uncertainty in climate change impact assessments. Global Change Biology 2017, 24, 1291 -1307.

AMA Style

F Tao, Reimund Rötter, Taru Palosuo, Carlos Gregorio Hernández Díaz‐Ambrona, M Ines Minguez, Mikhail Semenov, Kurt Christian Kersebaum, Claas Nendel, Xenia Specka, Holger Hoffmann, Frank Ewert, Anaelle Dambreville, Pierre Martre, Lucía Rodríguez, Margarita Ruiz‐Ramos, Thomas Gaiser, Jukka G. Höhn, Tapio Salo, Roberto Ferrise, Marco Bindi, Davide Cammarano, Alan H. Schulman. Contribution of crop model structure, parameters and climate projections to uncertainty in climate change impact assessments. Global Change Biology. 2017; 24 (3):1291-1307.

Chicago/Turabian Style

F Tao; Reimund Rötter; Taru Palosuo; Carlos Gregorio Hernández Díaz‐Ambrona; M Ines Minguez; Mikhail Semenov; Kurt Christian Kersebaum; Claas Nendel; Xenia Specka; Holger Hoffmann; Frank Ewert; Anaelle Dambreville; Pierre Martre; Lucía Rodríguez; Margarita Ruiz‐Ramos; Thomas Gaiser; Jukka G. Höhn; Tapio Salo; Roberto Ferrise; Marco Bindi; Davide Cammarano; Alan H. Schulman. 2017. "Contribution of crop model structure, parameters and climate projections to uncertainty in climate change impact assessments." Global Change Biology 24, no. 3: 1291-1307.

Review
Published: 01 November 2017 in Science of The Total Environment
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Biogeochemical simulation models are important tools for describing and quantifying the contribution of agricultural systems to C sequestration and GHG source/sink status. The abundance of simulation tools developed over recent decades, however, creates a difficulty because predictions from different models show large variability. Discrepancies between the conclusions of different modelling studies are often ascribed to differences in the physical and biogeochemical processes incorporated in equations of C and N cycles and their interactions. Here we review the literature to determine the state-of-the-art in modelling agricultural (crop and grassland) systems. In order to carry out this study, we selected the range of biogeochemical models used by the CN-MIP consortium of FACCE-JPI (http://www.faccejpi.com): APSIM, CERES-EGC, DayCent, DNDC, DSSAT, EPIC, PaSim, RothC and STICS. In our analysis, these models were assessed for the quality and comprehensiveness of underlying processes related to pedo-climatic conditions and management practices, but also with respect to time and space of application, and for their accuracy in multiple contexts. Overall, it emerged that there is a possible impact of ill-defined pedo-climatic conditions in the unsatisfactory performance of the models (46.2%), followed by limitations in the algorithms simulating the effects of management practices (33.1%). The multiplicity of scales in both time and space is a fundamental feature, which explains the remaining weaknesses (i.e. 20.7%). Innovative aspects have been identified for future development of C and N models. They include the explicit representation of soil microbial biomass to drive soil organic matter turnover, the effect of N shortage on SOM decomposition, the improvements related to the production and consumption of gases and an adequate simulations of gas transport in soil. On these bases, the assessment of trends and gaps in the modelling approaches currently employed to represent biogeochemical cycles in crop and grassland systems appears an essential step for future research

ACS Style

Lorenzo Brilli; Luca Bechini; Marco Bindi; Marco Carozzi; Daniele Cavalli; Richard Conant; Cristopher D. Dorich; Luca Doro; Fiona Ehrhardt; Roberta Farina; Roberto Ferrise; Nuala Fitton; Rosa Francaviglia; Peter Grace; Ileana Iocola; Katja Klumpp; Joël Léonard; Raphaël Martin; Raia Silvia Massad; Sylvie Recous; Giovanna Seddaiu; Joanna Sharp; Pete Smith; Ward Smith; Jean-Francois Soussana; Gianni Bellocchi. Review and analysis of strengths and weaknesses of agro-ecosystem models for simulating C and N fluxes. Science of The Total Environment 2017, 598, 445 -470.

AMA Style

Lorenzo Brilli, Luca Bechini, Marco Bindi, Marco Carozzi, Daniele Cavalli, Richard Conant, Cristopher D. Dorich, Luca Doro, Fiona Ehrhardt, Roberta Farina, Roberto Ferrise, Nuala Fitton, Rosa Francaviglia, Peter Grace, Ileana Iocola, Katja Klumpp, Joël Léonard, Raphaël Martin, Raia Silvia Massad, Sylvie Recous, Giovanna Seddaiu, Joanna Sharp, Pete Smith, Ward Smith, Jean-Francois Soussana, Gianni Bellocchi. Review and analysis of strengths and weaknesses of agro-ecosystem models for simulating C and N fluxes. Science of The Total Environment. 2017; 598 ():445-470.

Chicago/Turabian Style

Lorenzo Brilli; Luca Bechini; Marco Bindi; Marco Carozzi; Daniele Cavalli; Richard Conant; Cristopher D. Dorich; Luca Doro; Fiona Ehrhardt; Roberta Farina; Roberto Ferrise; Nuala Fitton; Rosa Francaviglia; Peter Grace; Ileana Iocola; Katja Klumpp; Joël Léonard; Raphaël Martin; Raia Silvia Massad; Sylvie Recous; Giovanna Seddaiu; Joanna Sharp; Pete Smith; Ward Smith; Jean-Francois Soussana; Gianni Bellocchi. 2017. "Review and analysis of strengths and weaknesses of agro-ecosystem models for simulating C and N fluxes." Science of The Total Environment 598, no. : 445-470.

Journal article
Published: 01 October 2017 in European Journal of Agronomy
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Simulation models, informed and validated with datasets from long term experiments (LTEs), are considered useful tools to explore the effects of different management strategies on soil organic carbon (SOC) dynamics and evaluate suitable mitigative options for climate change. But, while there are several studies which assessed a better prediction of crop yields using an ensemble of models, no studies are currently available on the evaluation of a model ensemble on SOC stocks. In this study we assessed the advantages of using an ensemble of crop models (APSIM-NWheat, DSSAT, EPIC, SALUS), calibrated and validated with datasets from LTEs, to estimate SOC dynamics. Then we used the mean of the model ensemble to assess the impacts of climate change on SOC stocks under conventional (CT) and conservation tillage practices (NT: No Till; RT: Reduced Tillage). The assessment was completed for two long-term experiment sites (Agugliano – AN and Pisa – PI2 sites) in Italy under rainfed conditions. A durum wheat (Triticum turgidum subsp. durum (Desf.) Husn.) – maize (Zea mays L.) rotation system was evaluated under two different climate scenarios over the periods 1971–2000 (CP: Present Climate) and 2021–2050 (CF: Future Climate), generated by setting up a statistical model based on canonical correlation analysis. Our study showed a decrease of SOC stocks in both sites and tillage systems over CF when compared with CP. At the AN site, CT lost −7.3% and NT −7.9% of SOC stock (0–40 cm) under CF. At the PI2 site, CT lost −4.4% and RT −5.3% of SOC stocks (0–40 cm). Even if conservation tillage systems were more impacted under future scenarios, they were still able to store more SOC than CT, so that these practices can be considered viable options to mitigate climate change. Furthermore, at the AN site, under CF, NT demonstrated an annual increase of 0.4%, the target value suggested by the 4 per thousand initiative launched at the 21st meeting of the Conference of the Parties in Paris. However, RT at the PI2 needs to be coupled with other management strategies, as the introduction of cover crops, to achieve such target

ACS Style

Ileana Iocola; Simona Bassu; Roberta Farina; Daniele Antichi; Bruno Basso; Marco Bindi; Anna Dalla Marta; Francesco Danuso; Luca Doro; Roberto Ferrise; Luisa Giglio; Fabrizio Ginaldi; Marco Mazzoncini; Laura Mula; Roberto Orsini; Giuseppe Corti; Massimiliano Pasqui; Giovanna Seddaiu; Rodica Tomozeiu; Domenico Ventrella; Giulia Villani; Pier Paolo Roggero. Can conservation tillage mitigate climate change impacts in Mediterranean cereal systems? A soil organic carbon assessment using long term experiments. European Journal of Agronomy 2017, 90, 96 -107.

AMA Style

Ileana Iocola, Simona Bassu, Roberta Farina, Daniele Antichi, Bruno Basso, Marco Bindi, Anna Dalla Marta, Francesco Danuso, Luca Doro, Roberto Ferrise, Luisa Giglio, Fabrizio Ginaldi, Marco Mazzoncini, Laura Mula, Roberto Orsini, Giuseppe Corti, Massimiliano Pasqui, Giovanna Seddaiu, Rodica Tomozeiu, Domenico Ventrella, Giulia Villani, Pier Paolo Roggero. Can conservation tillage mitigate climate change impacts in Mediterranean cereal systems? A soil organic carbon assessment using long term experiments. European Journal of Agronomy. 2017; 90 ():96-107.

Chicago/Turabian Style

Ileana Iocola; Simona Bassu; Roberta Farina; Daniele Antichi; Bruno Basso; Marco Bindi; Anna Dalla Marta; Francesco Danuso; Luca Doro; Roberto Ferrise; Luisa Giglio; Fabrizio Ginaldi; Marco Mazzoncini; Laura Mula; Roberto Orsini; Giuseppe Corti; Massimiliano Pasqui; Giovanna Seddaiu; Rodica Tomozeiu; Domenico Ventrella; Giulia Villani; Pier Paolo Roggero. 2017. "Can conservation tillage mitigate climate change impacts in Mediterranean cereal systems? A soil organic carbon assessment using long term experiments." European Journal of Agronomy 90, no. : 96-107.

Journal article
Published: 01 March 2017 in European Journal of Agronomy
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Realistic estimation of grain nitrogen (N; N in grain yield) is crucial for assessing N management in crop rotations, but there is little information on the performance of commonly used crop models for simulating grain N. Therefore, the objectives of the study were to (1) test if continuous simulation (multi-year) performs better than single year simulation, (2) assess if calibration improves model performance at different calibration levels, and (3) investigate if a multi-model ensemble can substantially reduce uncertainty in reproducing grain N. For this purpose, 12 models were applied simulating different treatments (catch crops, CO2 concentrations, irrigation, N application, residues and tillage) in four multi-year rotation experiments in Europe to assess modelling accuracy. Seven grain and seed crops in four rotation systems in Europe were included in the study, namely winter wheat, winter barley, spring barley, spring oat, winter rye, pea and winter oilseed rape. Our results indicate that the higher level of calibration significantly increased the quality of the simulation for grain N. In addition, models performed better in predicting grain N of winter wheat, winter barley and spring barley compared to spring oat, winter rye, pea and winter oilseed rape. For each crop, the use of the ensemble mean significantly reduced the mean absolute percentage error (MAPE) between simulations and observations to less than 15%, thus a multi–model ensemble can more precisely predict grain N than a random single model. Models correctly simulated the effects of enhanced N input on grain N of winter wheat and winter barley, whereas effects of tillage and irrigation were less well estimated. However, the use of continuous simulation did not improve the simulations as compared to single year simulation based on the multi-year performance, which suggests needs for further model improvements of crop rotation effects

ACS Style

Xiaogang Yin; Kurt Christian Kersebaum; Chris Kollas; Sanmohan Baby; Nicolas Beaudoin; Kiril Manevski; Taru Palosuo; Claas Nendel; Lianhai Wu; Munir Hoffmann; Holger Hoffmann; Behzad Sharif; Cecilia M. Armas-Herrera; Marco Bindi; Monia Charfeddine; Tobias Conradt; Julie Constantin; Frank Ewert; Roberto Ferrise; Thomas Gaiser; Iñaki Garcia de Cortazar-Atauri; Luisa Giglio; Petr Hlavinka; Marcos Lana; Marie Launay; Gaëtan Louarn; Remy Manderscheid; Bruno Mary; Wilfried Mirschel; Marco Moriondo; Isik Öztürk; Andreas Pacholski; Dominique Ripoche-Wachter; Reimund Rötter; Françoise Ruget; Mirek Trnka; Domenico Ventrella; Hans-Joachim Weigel; Jørgen E. Olesen. Multi-model uncertainty analysis in predicting grain N for crop rotations in Europe. European Journal of Agronomy 2017, 84, 152 -165.

AMA Style

Xiaogang Yin, Kurt Christian Kersebaum, Chris Kollas, Sanmohan Baby, Nicolas Beaudoin, Kiril Manevski, Taru Palosuo, Claas Nendel, Lianhai Wu, Munir Hoffmann, Holger Hoffmann, Behzad Sharif, Cecilia M. Armas-Herrera, Marco Bindi, Monia Charfeddine, Tobias Conradt, Julie Constantin, Frank Ewert, Roberto Ferrise, Thomas Gaiser, Iñaki Garcia de Cortazar-Atauri, Luisa Giglio, Petr Hlavinka, Marcos Lana, Marie Launay, Gaëtan Louarn, Remy Manderscheid, Bruno Mary, Wilfried Mirschel, Marco Moriondo, Isik Öztürk, Andreas Pacholski, Dominique Ripoche-Wachter, Reimund Rötter, Françoise Ruget, Mirek Trnka, Domenico Ventrella, Hans-Joachim Weigel, Jørgen E. Olesen. Multi-model uncertainty analysis in predicting grain N for crop rotations in Europe. European Journal of Agronomy. 2017; 84 ():152-165.

Chicago/Turabian Style

Xiaogang Yin; Kurt Christian Kersebaum; Chris Kollas; Sanmohan Baby; Nicolas Beaudoin; Kiril Manevski; Taru Palosuo; Claas Nendel; Lianhai Wu; Munir Hoffmann; Holger Hoffmann; Behzad Sharif; Cecilia M. Armas-Herrera; Marco Bindi; Monia Charfeddine; Tobias Conradt; Julie Constantin; Frank Ewert; Roberto Ferrise; Thomas Gaiser; Iñaki Garcia de Cortazar-Atauri; Luisa Giglio; Petr Hlavinka; Marcos Lana; Marie Launay; Gaëtan Louarn; Remy Manderscheid; Bruno Mary; Wilfried Mirschel; Marco Moriondo; Isik Öztürk; Andreas Pacholski; Dominique Ripoche-Wachter; Reimund Rötter; Françoise Ruget; Mirek Trnka; Domenico Ventrella; Hans-Joachim Weigel; Jørgen E. Olesen. 2017. "Multi-model uncertainty analysis in predicting grain N for crop rotations in Europe." European Journal of Agronomy 84, no. : 152-165.