| Records |
| Author |
Trnka, M.; Rötter, R.P.; Ruiz-Ramos, M.; Kersebaum, K.C.; Olesen, J.E.; Žalud, Z.; Semenov, M.A. |
| Title |
Adverse weather conditions for European wheat production will become more frequent with climate change |
Type |
Journal Article |
| Year |
2014 |
Publication |
Nature Climate Change |
Abbreviated Journal |
Nat. Clim. Change |
Volume  |
4 |
Issue |
7 |
Pages |
637-643 |
| Keywords |
scenarios; increase; models; variability; responses; extremes; impacts; shifts |
| Abstract |
Europe is the largest producer of wheat, the second most widely grown cereal crop after rice. The increased occurrence and magnitude of adverse and extreme agroclimatic events are considered a major threat for wheat production. We present an analysis that accounts for a range of adverse weather events that might significantly affect wheat yield in Europe. For this purpose we analysed changes in the frequency of the occurrence of 11 adverse weather events. Using climate scenarios based on the most recent ensemble of climate models and greenhouse gases emission estimates, we assessed the probability of single and multiple adverse events occurring within one season. We showed that the occurrence of adverse conditions for 14 sites representing the main European wheat-growing areas might substantially increase by 2060 compared to the present (1981-2010). This is likely to result in more frequent crop failure across Europe. This study provides essential information for developing adaptation strategies. |
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English |
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1758-678x 1758-6798 |
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| Notes |
CropM, ft_macsur |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4545 |
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| Author |
Kersebaum, K.; C, |
| Title |
Results of uncalibrated model runs available (ROTATIONEFFECTS) |
Type |
Report |
| Year |
2014 |
Publication |
FACCE MACSUR Reports |
Abbreviated Journal |
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| Volume |
3 |
Issue |
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Pages |
D-C1.5 |
| Keywords |
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| Abstract |
The study ROTATIONEFFECT aims to compare the output of different models simulating field data sets with multi-year crop rotations including different treatments. Data sets for 5 locations in Europe were distributed to 19 interested modeller groups comprising a total of 201 crop growth seasons. In a first step only minimal information for calibration were provided to the modellers. In total 14 modelling teams sent their “uncalibrated” results as single-year calculations and/or calculations of rotation depending on the capability of the model. 7-10 models were capable to run the rotations as continuous runs. Up to 12 models provided single year simulations of at least one crop. Comparing results of models which provided both single year and continuous runs, show a little lower root mean square error for the continuous rotations runs. Cereal crop yields were generally better simulated than tuber/beet yields. Additionally, the models’ response to various treatments (irrigation/rainfed, nitrogen level, CO2 level, residue management/ tillage, catch crops) were compared to observed differences. First indicators of model performance have been developed and presented at international conferences. No Label |
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no |
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MA @ admin @ |
Serial |
2230 |
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Asseng, S.; Ewert, F.; Rosenzweig, C.; Jones, J.W.; Hatfield, J.L.; Ruane, A.C.; Boote, K.J.; Thorburn, P.J.; Rötter, R.P.; Cammarano, D.; Brisson, N.; Basso, B.; Martre, P.; Aggarwal, P.K.; Angulo, C.; Bertuzzi, P.; Biernath, C.; Challinor, A.J.; Doltra, J.; Gayler, S.; Goldberg, R.; Grant, R.; Heng, L.; Hooker, J.; Hunt, L.A.; Ingwersen, J.; Izaurralde, R.C.; Kersebaum, K.C.; Müller, C.; Naresh Kumar, S.; Nendel, C.; O’Leary, G.; Olesen, J.E.; Osborne, T.M.; Palosuo, T.; Priesack, E.; Ripoche, D.; Semenov, M.A.; Shcherbak, I.; Steduto, P.; Stöckle, C.; Stratonovitch, P.; Streck, T.; Supit, I.; Tao, F.; Travasso, M.; Waha, K.; Wallach, D.; White, J.W.; Williams, J.R.; Wolf, J. |
| Title |
Uncertainty in simulating wheat yields under climate change |
Type |
Journal Article |
| Year |
2013 |
Publication |
Nature Climate Change |
Abbreviated Journal |
Nat. Clim. Change |
| Volume |
3 |
Issue |
9 |
Pages |
827-832 |
| Keywords |
crop production; models; food; co2; temperature; projections; adaptation; scenarios; ensemble; impacts |
| Abstract |
Projections of climate change impacts on crop yields are inherently uncertain(1). Uncertainty is often quantified when projecting future greenhouse gas emissions and their influence on climate(2). However, multi-model uncertainty analysis of crop responses to climate change is rare because systematic and objective comparisons among process-based crop simulation models(1,3) are difficult(4). Here we present the largest standardized model intercomparison for climate change impacts so far. We found that individual crop models are able to simulate measured wheat grain yields accurately under a range of environments, particularly if the input information is sufficient. However, simulated climate change impacts vary across models owing to differences in model structures and parameter values. A greater proportion of the uncertainty in climate change impact projections was due to variations among crop models than to variations among downscaled general circulation models. Uncertainties in simulated impacts increased with CO2 concentrations and associated warming. These impact uncertainties can be reduced by improving temperature and CO2 relationships in models and better quantified through use of multi-model ensembles. Less uncertainty in describing how climate change may affect agricultural productivity will aid adaptation strategy development and policymaking. |
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1758-678x |
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| Notes |
CropM, ftnotmacsur, IPCC-AR5 |
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no |
| Call Number |
MA @ admin @ |
Serial |
4599 |
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Graef, F.; Sieber, S.; Mutabazi, K.; Asch, F.; Biesalski, H.K.; Bitegeko, J.; Bokelmann, W.; Bruentrup, M.; Dietrich, O.; Elly, N.; Fasse, A.; Germer, J.U.; Grote, U.; Herrmann, L.; Herrmann, R.; Hoffmann, H.; Kahimba, F.C.; Kaufmann, B.; Kersebaum, K.-C.; Kilembe, C.; Kimaro, A.; Kinabo, J.; König, B.; König, H.; Lana, M.; Levy, C.; Lyimo-Macha, J.; Makoko, B.; Mazoko, G.; Mbaga, S.H.; Mbogoro, W.; Milling, H.; Mtambo, K.; Mueller, J.; Mueller, C.; Mueller, K.; Nkonja, E.; Reif, C.; Ringler, C.; Ruvuga, S.; Schaefer, M.; Sikira, A.; Silayo, V.; Stahr, K.; Swai, E.; Tumbo, S.; Uckert, G. |
| Title |
Framework for participatory food security research in rural food value chains |
Type |
Journal Article |
| Year |
2014 |
Publication |
Global Food Security |
Abbreviated Journal |
Global Food Security |
| Volume |
3 |
Issue |
1 |
Pages |
8-15 |
| Keywords |
food security; food value chain; action research; tanzania; research framework |
| Abstract |
Enhancing food security for poor and vulnerable people requires adapting rural food systems to various driving factors. Food security-related research should apply participatory action research that considers the entire food value chain to ensure sustained success. This article presents a research framework that focusses on determining, prioritising, testing, adapting and disseminating food securing upgrading strategies across the multiple components of rural food value chains. These include natural resources, Food production, processing, markets, consumption and waste management. Scientists and policy makers jointly use tools developed for assessing potentials for enhancing regional food security at multiple spatial and temporal scales. The research is being conducted in Tanzania as a case study for Sub-Saharan countries and is done in close collaboration with local, regional and national stakeholders, encompassing all activities across all different food sectors. (C) 2014 Elsevier B.V. All rights reserved. |
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2211-9124 |
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CropM, TradeM |
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no |
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MA @ admin @ |
Serial |
4523 |
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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. |
| 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 |
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Pages |
17102 |
| Keywords |
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| 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 |
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2017-08-28 |
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CropM, ft_macsur |
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no |
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MA @ admin @ |
Serial |
5173 |
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