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Author Nendel, C.; Thorburn, P.; Melzer, D.; Cerri, C.E.P.; Claessens, L.; Aggarwal, P.K.; Adam, M.; Angulo, C.; Asseng, S.; Baron, C.; Basso, B.; Bassu, S.; Bertuzzi, P.; Biernath, C.; Boogaard, H.; Boote, K.J.; Brisson, N.; Cammarano, D.; Conijn, S.; Corbeels, M.; Deryng, D.; Sanctis, G.D.; Doltra, J.; Durand, J.L.; Ewert, F.; Gayler, S.; Goldberg, R.; Grant, R.; Grassini, P.; Heng, L.; Hoek, S.B.; Hooker, J.A.U.-, L.A.H.; Ingwersen, J.; Izaurralde, C.; Jongschaap, R.; Kemanian, A.; Kersebaum, K.C.; Lizaso, J.; Makowski, D.; Martre, P.; Müller, C.; Kim, S.H.; Kumar, S.N.; O’Leary, G.; Olesen, J.E.; Osborne, T.; Palosuo, T.; Pravia, M.V.; Priesack, E.; Ripoche, D.A.U.-, R.P.R.; Sau, F.; Semenov, M.A.; Shcherbak, I.; Steduto, P.; Stöckle, C.; Stratonovitch, P.; Streck, T.; Supit, I.; Tao, F.L.; Teixeira, E.; Timlin, D.; Travasso, M.; Waha, K.; Wallach, D.; White, J.W.; Wolf, J.
Title Soil nitrogen mineralisation simulated by crop models across different environments and the consequences for model improvement Type Conference Article
Year 2016 Publication Abbreviated Journal
Volume Issue Pages
Keywords (up)
Abstract
Address
Corporate Author Thesis
Publisher Place of Publication Berlin (Germany) Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference International Crop Modelling Symposium iCROPM 2016, 2016-05-15 to 2016-05-17, Berlin, Germany
Notes Approved no
Call Number MA @ admin @ Serial 4903
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Author Liu, B.; Asseng, S.; Müller, C.; Ewert, F.; Elliott, J.; Lobell, D. B.; Martre, P.; Ruane, A. C.; Wallach, D.; Jones, J. W.; Rosenzweig, C.; Aggarwal, P. K.; Alderman, P. D.; Anothai, J.; Basso, B.; Biernath, C.; Cammarano, D.; Challinor, A.; Deryng, D.; Sanctis, G. D.; Doltra, J.; Fereres, E.; Folberth, C.; Garcia-Vila, M.; Gayler, S.; Hoogenboom, G.; Hunt, L. A.; Izaurralde, R. C.; Jabloun, M.; Jones, C. D.; Kersebaum, K. C.; Kimball, B. A.; Koehler, A.-K.; Kumar, S. N.; Nendel, C.; O’Leary, G. J.; Olesen, J. E.; Ottman, M. J.; Palosuo, T.; Prasad, P. V. V.; Priesack, E.; Pugh, T. A. M.; Reynolds, M.; Rezaei, E. E.; Rötter, R. P.; Schmid, E.; Semenov, M. A.; Shcherbak, I.; Stehfest, E.; Stöckle, C. O.; Stratonovitch, P.; Streck, T.; Supit, I.; Tao, F.; Thorburn, P.; Waha, K.; Wall, G. W.; Wang, E.; White, J. W.; Wolf, J.; Zhao, Z.; Zhu, Y.
Title Similar estimates of temperature impacts on global wheat yield by three independent methods Type Journal Article
Year 2016 Publication Nature Climate Change Abbreviated Journal Nat. Clim. Change
Volume 6 Issue 12 Pages 1130-1136
Keywords (up)
Abstract
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1758-678x ISBN Medium article
Area Expedition Conference
Notes CropM Approved no
Call Number MA @ admin @ Serial 4965
Permanent link to this record
 
 
Author Wang, E.; Martre, P.; Zhao, Z.; Ewert, F.; Maiorano, A.; Rötter, R.P.; Kimball, B.A.; Ottman, M.J.; Wall, G.W.; White, J.W.; Reynolds, M.P.; Alderman, P.D.; Aggarwal, P.K.; Anothai, J.; Basso, B.; Biernath, C.; Cammarano, D.; Challinor, A.J.; De Sanctis, G.; Doltra, J.; Fereres, E.; Garcia-Vila, M.; Gayler, S.; Hoogenboom, G.; Hunt, L.A.; Izaurralde, R.C.; Jabloun, M.; Jones, C.D.; Kersebaum, K.C.; Koehler, A.-K.; Liu, L.; Müller, C.; Naresh Kumar, S.; Nendel, C.; O’Leary, G.; Olesen, J.E.; Palosuo, T.; Priesack, E.; Eyshi Rezaei, E.; Ripoche, D.; Ruane, A.C.; Semenov, M.A.; Shcherbak, I.; Stöckle, C.; Stratonovitch, P.; Streck, T.; Supit, I.; Tao, F.; Thorburn, P.; Waha, K.; Wallach, D.; Wang, Z.; Wolf, J.; Zhu, Y.; Asseng, S.
Title The uncertainty of crop yield projections is reduced by improved temperature response functions Type Journal Article
Year 2017 Publication Nature Plants Abbreviated Journal Nature Plants
Volume 3 Issue Pages 17102
Keywords (up)
Abstract Increasing the accuracy of crop productivity estimates is a key element in planning adaptation strategies to ensure global food security under climate change. Process-based crop models are effective means to project climate impact on crop yield, but have large uncertainty in yield simulations. Here, we show that variations in the mathematical functions currently used to simulate temperature responses of physiological processes in 29 wheat models account for >50% of uncertainty in simulated grain yields for mean growing season temperatures from 14 °C to 33 °C. We derived a set of new temperature response functions that when substituted in four wheat models reduced the error in grain yield simulations across seven global sites with different temperature regimes by 19% to 50% (42% average). We anticipate the improved temperature responses to be a key step to improve modelling of crops under rising temperature and climate change, leading to higher skill of crop yield projections. Erratum: doi: 10.1038/nplants.2017.125
Address 2017-08-28
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium article
Area Expedition Conference
Notes CropM, ft_macsur Approved no
Call Number MA @ admin @ Serial 5173
Permanent link to this record
 
 
Author Makowski, D.; Asseng, S.; Ewert, F.; Bassu, S.; Durand, J.L.; Li, T.; Martre, P.; Adam, M.; Aggarwal, P.K.; Angulo, C.; Baron, C.; Basso, B.; Bertuzzi, P.; Biernath, C.; Boogaard, H.; Boote, K.J.; Bouman, B.; Bregaglio, S.; Brisson, N.; Buis, S.; Cammarano, D.; Challinor, A.J.; Confalonieri, R.; Conijn, J.G.; Corbeels, M.; Deryng, D.; De Sanctis, G.; Doltra, J.; Fumoto, T.; Gaydon, D.; Gayler, S.; Goldberg, R.; Grant, R.F.; Grassini, P.; Hatfield, J.L.; Hasegawa, T.; Heng, L.; Hoek, S.; Hooker, J.; Hunt, L.A.; Ingwersen, J.; Izaurralde, R.C.; Jongschaap, R.E.E.; Jones, J.W.; Kemanian, R.A.; Kersebaum, K.C.; Kim, S.-H.; Lizaso, J.; Marcaida, M.; Müller, C.; Nakagawa, H.; Naresh Kumar, S.; Nendel, C.; O’Leary, G.J.; Olesen, J.E.; Oriol, P.; Osborne, T.M.; Palosuo, T.; Pravia, M.V.; Priesack, E.; Ripoche, D.; Rosenzweig, C.; Ruane, A.C.; Ruget, F.; Sau, F.; Semenov, M.A.; Shcherbak, I.; Singh, B.; Singh, U.; Soo, H.K.; Steduto, P.; Stöckle, C.; Stratonovitch, P.; Streck, T.; Supit, I.; Tang, L.; Tao, F.; Teixeira, E.I.; Thorburn, P.; Timlin, D.; Travasso, M.; Rötter, R.P.; Waha, K.; Wallach, D.; White, J.W.; Wilkens, P.; Williams, J.R.; Wolf, J.; Yin, X.; Yoshida, H.; Zhang, Z.; Zhu, Y.
Title A statistical analysis of three ensembles of crop model responses to temperature and CO2 concentration Type Journal Article
Year 2015 Publication Agricultural and Forest Meteorology Abbreviated Journal Agricultural and Forest Meteorology
Volume 214-215 Issue Pages 483-493
Keywords (up) climate change; crop model; emulator; meta-model; statistical model; yield; climate-change; wheat yields; metaanalysis; uncertainty; simulation; impacts
Abstract Ensembles of process-based crop models are increasingly used to simulate crop growth for scenarios of temperature and/or precipitation changes corresponding to different projections of atmospheric CO2 concentrations. This approach generates large datasets with thousands of simulated crop yield data. Such datasets potentially provide new information but it is difficult to summarize them in a useful way due to their structural complexities. An associated issue is that it is not straightforward to compare crops and to interpolate the results to alternative climate scenarios not initially included in the simulation protocols. Here we demonstrate that statistical models based on random-coefficient regressions are able to emulate ensembles of process-based crop models. An important advantage of the proposed statistical models is that they can interpolate between temperature levels and between CO2 concentration levels, and can thus be used to calculate temperature and [CO2] thresholds leading to yield loss or yield gain, without rerunning the original complex crop models. Our approach is illustrated with three yield datasets simulated by 19 maize models, 26 wheat models, and 13 rice models. Several statistical models are fitted to these datasets, and are then used to analyze the variability of the yield response to [CO2] and temperature. Based on our results, we show that, for wheat, a [CO2] increase is likely to outweigh the negative effect of a temperature increase of +2 degrees C in the considered sites. Compared to wheat, required levels of [CO2] increase are much higher for maize, and intermediate for rice. For all crops, uncertainties in simulating climate change impacts increase more with temperature than with elevated [CO2].
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0168-1923 ISBN Medium Article
Area Expedition Conference
Notes CropM, ft_macsur Approved no
Call Number MA @ admin @ Serial 4714
Permanent link to this record
 
 
Author Asseng, S.; Ewert, F.; Martre, P.; Rötter, R.P.; Lobell, D.B.; Cammarano, D.; Kimball, B.A.; Ottman, M.J.; Wall, G.W.; White, J.W.; Reynolds, M.P.; Alderman, P.D.; Prasad, P.V.V.; Aggarwal, P.K.; Anothai, J.; Basso, B.; Biernath, C.; Challinor, A.J.; De Sanctis, G.; Doltra, J.; Fereres, E.; Garcia-Vila, M.; Gayler, S.; Hoogenboom, G.; Hunt, L.A.; Izaurralde, R.C.; Jabloun, M.; Jones, C.D.; Kersebaum, K.C.; Koehler, A.-K.; Müller, C.; Naresh Kumar, S.; Nendel, C.; O’Leary, G.; Olesen, J.E.; Palosuo, T.; Priesack, E.; Eyshi Rezaei, E.; Ruane, A.C.; Semenov, M.A.; Shcherbak, I.; Stöckle, C.; Stratonovitch, P.; Streck, T.; Supit, I.; Tao, F.; Thorburn, P.J.; Waha, K.; Wang, E.; Wallach, D.; Wolf, J.; Zhao, Z.; Zhu, Y.
Title Rising temperatures reduce global wheat production Type Journal Article
Year 2014 Publication Nature Climate Change Abbreviated Journal Nat. Clim. Change
Volume 5 Issue 2 Pages 143-147
Keywords (up) climate-change; spring wheat; dryland wheat; yield; growth; drought; heat; CO2; agriculture; adaptation
Abstract Crop models are essential tools for assessing the threat of climate change to local and global food production1. Present models used to predict wheat grain yield are highly uncertain when simulating how crops respond to temperature2. Here we systematically tested 30 different wheat crop models of the Agricultural Model Intercomparison and Improvement Project against field experiments in which growing season mean temperatures ranged from 15 °C to 32 °C, including experiments with artificial heating. Many models simulated yields well, but were less accurate at higher temperatures. The model ensemble median was consistently more accurate in simulating the crop temperature response than any single model, regardless of the input information used. Extrapolating the model ensemble temperature response indicates that warming is already slowing yield gains at a majority of wheat-growing locations. Global wheat production is estimated to fall by 6% for each °C of further temperature increase and become more variable over space and time.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1758-678x ISBN Medium Article
Area Expedition Conference
Notes CropM, ft_macsur Approved no
Call Number MA @ admin @ Serial 4550
Permanent link to this record