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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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The uncertainty of crop yield projections is reduced by improved temperature response functions |
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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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Webber, H.; Zhao, G.; Britz, W.; deVries, W.; Wolf, J.; Gaiser, T.; Hoffmann, H.; Ewert, F. |
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Specification of nitrogen use in regional climate impact assessment studies |
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2015 |
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Montpellier (France) |
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5th International Symposium for Farming Systems Design, Montpellier, France, 2015-09-07 to 2015-09-10, Montpellier |
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2899 |
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Reidsma, P.; Wolf, J.; Kanellopoulos, A.; Schaap, B.F.; Mandryk, M.; Verhagen, J.; Van Ittersum, M.K. |
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Climate change impact and adaptation research requires integrated assessment and farming systems analysis: a case study in the Netherlands |
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2015 |
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FACCE MACSUR Reports |
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6 |
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D-C3.4 |
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Rather than on crop modelling only, climate change impact assessments in agriculture need to be based on integrated assessment and farming systems analysis, and account for adaptation at different levels. With a case study for Flevoland, the Netherlands, we illustrate that 1) crop models cannot account for all relevant climate change impacts and adaptation options, and 2) changes in technology, policy and prices have had and are likely to have larger impacts on farms than climate change. While crop modelling indicates positive impacts of climate change on yields of major crops in 2050, a semi-quantitative and participatory method assessing impacts of extreme events shows that there are nevertheless several climate risks. A range of adaptation measures are, however, available to reduce possible negative effects at crop level. In addition, at farm level farmers can change cropping patterns, and adjust inputs and outputs. Also farm structural change will influence impacts and adaptation. While the 5th IPCC report is more negative regarding impacts of climate change on agriculture compared to the previous report, also for temperate regions, our results show that when putting climate change in context of other drivers, and when explicitly accounting for adaptation at crop and farm level, impacts may be less negative in some regions and opportunities are revealed. These results refer to a temperate region, but an integrated assessment may also change perspectives on climate change for other parts of the world. No Label |
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MA @ admin @ |
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2097 |
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de Wit, A.; Boogaard, H.; van Diepen, K.; van Kraalingen, D.; Rötter, R.; Supit, I.; Wolf, J.; van Ittersum, M. |
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WOFOST developer’s response to article by Stella et al., Environmental Modelling & Software 59 (2014): 44–58 |
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2015 |
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Environmental Modelling & Software |
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Env. Model. Softw. |
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73 |
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57-59 |
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English |
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1364-8152 |
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CropM, ftnotmacsur |
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MA @ admin @ |
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4699 |
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