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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. |
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Title |
The uncertainty of crop yield projections is reduced by improved temperature response functions |
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Journal Article |
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Year |
2017 |
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Nature Plants |
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Nature Plants |
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3 |
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17102 |
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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 |
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2017-08-28 |
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CropM, ft_macsur |
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MA @ admin @ |
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5173 |
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Tao, F.; Zhang, Z.; Zhang, S.; Rötter, R.P.; Shi, W.; Xiao, D.; Liu, Y.; Wang, M.; Liu, F.; Zhang, H. |
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Title |
Historical data provide new insights into response and adaptation of maize production systems to climate change/variability in China |
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Journal Article |
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Year |
2016 |
Publication |
Field Crops Research |
Abbreviated Journal |
Field Crops Research |
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185 |
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1-11 |
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Keywords |
china; climate variability; grain yield; impact; maize; northeast china; tropical maize; wheat yields; heat-stress; crop yields; temperature; impacts; sensitivities; hybrids; trends |
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Extensive studies had been conducted to investigate the impacts of climate change on maize growth and yield in recent decades; however, the dynamics of crop husbandry in response and adaptation to climate change were not taken into account. Based on field observations spanning from 1981 to 2009 at 167 agricultural meteorological stations across China, we found that solar radiation and temperature over the observed maize growth period had decreasing trends during 1981-2009, and maize yields were positively correlated with these climate variables in major production regions. The decreasing trends in solar radiation and temperature during maize growth period were mainly ascribed to the adoption of late maturity cultivars with longer reproductive growth period (RGP). The adoption of late maturing cultivars with longer RGP contributed substantially to grain yield increase during the last three decades. The climate trends during maize growth period varied among different production areas. During 1981-2009, decreases in mean temperature, precipitation and solar radiation over maize growth period jointly reduced yield most by 13.2-17.3% in southwestern China, by contrast in northwestern China increases in mean temperature, precipitation and solar radiation jointly increased yield most by 12.9-14.4%. Our findings highlight that the adaptations of maize production system to climate change through shifts of sowing date and genotypes are underway and should be taken into accounted when evaluating climate change impacts. (C) 2015 Elsevier B.V. All rights reserved. |
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2016-10-31 |
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0378-4290 |
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CropM, ft_macsur |
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MA @ admin @ |
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4816 |
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Tao, F.; Zhang, Z.; Zhang, S.; Rötter, R.P. |
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Title |
Variability in crop yields associated with climate anomalies in China over the past three decades |
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Journal Article |
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Year |
2016 |
Publication |
Regional Environmental Change |
Abbreviated Journal |
Reg Environ Change |
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16 |
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6 |
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1715-1723 |
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Adaptation; Climate change; Climate extremes; Drought; Impacts and vulnerability |
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We used simple and explicit methods, as well as improved datasets for climate, crop phenology and yields, to address the association between variability in crop yields and climate anomalies in China from 1980 to 2008. We identified the most favourable and unfavourable climate conditions and the optimum temperatures for crop productivity in different regions of China. We found that the simultaneous occurrence of high temperatures, low precipitation and high solar radiation was unfavourable for wheat, maize and soybean productivity in large portions of northern, northwestern and northeastern China; this was because of droughts induced by warming or an increase in solar radiation. These climate anomalies could cause yield losses of up to 50 % for wheat, maize and soybeans in the arid and semi-arid regions of China. High precipitation and low solar radiation were unfavourable for crop productivity throughout southeastern China and could cause yield losses of approximately 20 % for rice and 50 % for wheat and maize. High temperatures were unfavourable for rice productivity in southwestern China because they induced heat stress, which could cause rice yield losses of approximately 20 %. In contrast, high temperatures and low precipitation were favourable for rice productivity in northeastern and eastern China. We found that the optimum temperatures for high yields were crop specific and had an explicit spatial pattern. These findings improve our understanding of the impacts of extreme climate events on agricultural production in different regions of China. |
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2016-06-20 |
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1436-3798 1436-378x |
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CropM, ft_macsur |
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MA @ admin @ |
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4757 |
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Tao, F.; Rötter, R.P.; Palosuo, T.; Hernández, C.G.; Mínguez, M.I.; Semenov, M.; Kersebaum, K.C.; Nendel, C.; Cammarano, D.; Hoffmann, H.; Ewert, F.; Dambreville, A.; Martre, P.; Rodríguez, L.; Ruiz-Ramos, M.; Gaiser, T.; Höhn, J.G.; Ferrise, R.; Bindi, M.; Schulman, A. |
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Using crop model ensembles to design future climate-resilient barley cultivars |
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2016 |
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Berlin (Germany) |
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International Crop Modelling Symposium iCROPM 2016, 2016-05-15 to 2016-05-17, Berlin, Germany |
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MA @ admin @ |
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4898 |
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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. |
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Soil nitrogen mineralisation simulated by crop models across different environments and the consequences for model improvement |
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Conference Article |
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2016 |
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Berlin (Germany) |
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International Crop Modelling Symposium iCROPM 2016, 2016-05-15 to 2016-05-17, Berlin, Germany |
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MA @ admin @ |
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4903 |
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