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Trnka, M.; Feng, S.; Semenov, M.A.; Olesen, J.E.; Kersebaum, K.C.; Roetter, R.P.; Semeradova, D.; Klem, K.; Huang, W.; Ruiz-Ramos, M.; Hlavinka, P.; Meitner, J.; Balek, J.; Havlik, P.; Buntgen, U. |
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Title |
Mitigation efforts will not fully alleviate the increase in water scarcity occurrence probability in wheat-producing areas |
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Journal Article |
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Year |
2019 |
Publication |
Science Advances |
Abbreviated Journal |
Sci. Adv. |
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Volume |
5 |
Issue |
9 |
Pages |
eaau2406 |
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Keywords |
climate-change impacts; sub-saharan africa; atmospheric co2; crop; yields; drought; agriculture; variability; irrigation; adaptation; carbon |
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Abstract |
Global warming is expected to increase the frequency and intensity of severe water scarcity (SWS) events, which negatively affect rain-fed crops such as wheat, a key source of calories and protein for humans. Here, we develop a method to simultaneously quantify SWS over the world’s entire wheat-growing area and calculate the probabilities of multiple/sequential SWS events for baseline and future climates. Our projections show that, without climate change mitigation (representative concentration pathway 8.5), up to 60% of the current wheat-growing area will face simultaneous SWS events by the end of this century, compared to 15% today. Climate change stabilization in line with the Paris Agreement would substantially reduce the negative effects, but they would still double between 2041 and 2070 compared to current conditions. Future assessments of production shocks in food security should explicitly include the risk of severe, prolonged, and near- simultaneous droughts across key world wheat-producing areas. |
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2020-02-14 |
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ISSN |
2375-2548 |
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CropM, ft_macsur |
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Call Number |
MA @ admin @ |
Serial |
5227 |
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Author |
Trnka, M.; Hlavinka, P.; Semenov, M.A. |
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Title |
Adaptation options for wheat in Europe will be limited by increased adverse weather events under climate change |
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Journal Article |
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Year |
2015 |
Publication |
Journal of the Royal Society Interface |
Abbreviated Journal |
J. R. Soc. Interface |
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Volume |
12 |
Issue |
112 |
Pages |
20150721 |
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Keywords |
climate change; extreme events; food security; winter wheat |
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Abstract |
Ways of increasing the production of wheat, the most widely grown cereal crop, will need to be found to meet the increasing demand caused by human population growth in the coming decades. This increase must occur despite the decrease in yield gains now being reported in some regions, increased price volatility and the expected increase in the frequency of adverse weather events that can reduce yields. However, if and how the frequency of adverse weather events will change over Europe, the most important wheat-growing area, has not yet been analysed. Here, we show that the accumulated probability of 11 adverse weather events with the potential to significantly reduce yield will increase markedly across all of Europe. We found that by the end of the century, the exposure of the key European wheat-growing areas, where most wheat production is currently concentrated, may increase more than twofold. However, if we consider the entire arable land area of Europe, a greater than threefold increase in risk was predicted. Therefore, shifting wheat production to new producing regions to reduce the risk might not be possible as the risk of adverse events beyond the key wheat-growing areas increases even more. Furthermore, we found a marked increase in wheat exposure to high temperatures, severe droughts and field inaccessibility compared with other types of adverse events. Our results also showed the limitations of some of the presently debated adaptation options and demonstrated the need for development of region-specific strategies. Other regions of the world could be affected by adverse weather events in the future in a way different from that considered here for Europe. This observation emphasizes the importance of conducting similar analyses for other major wheat regions. |
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2016-10-31 |
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1742-5689 1742-5662 |
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CropM, ft_macsur |
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MA @ admin @ |
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4819 |
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Author |
Valin, H.; Sands, R.D.; van der Mensbrugghe, D. and; Nelson, G.C.; Ahammad, H.; Blanc, E.; Bodirsky; Benjamin; Fujimori, S.; Hasegawa, T.; Havlik, P.; and Heyhoe, E.; Kyle, P.; Mason-D’Croz, D.; Paltsev; Sergey; Rolinski, S.; Tabeau, A.; van Meijl, H. and; von Lampe, M.; Willenbockel, D. |
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Title |
The future of food demand: Understanding differences in global economic models |
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Journal Article |
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Year |
2014 |
Publication |
Agricultural Economics |
Abbreviated Journal |
Agric. Econ. |
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45 |
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1 |
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51-67 |
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Keywords |
world food demand; socioeconomic pathways; climate change; computable general equilibrium; partial equilibrium; systems |
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Abstract |
Understanding the capacity of agricultural systems to feed the world population under climate change requires projecting future food demand. This article reviews demand modeling approaches from 10 global economic models participating in the Agricultural Model Intercomparison and Improvement Project (AgMIP). We compare food demand projections in 2050 for various regions and agricultural products under harmonized scenarios of socioeconomic development, climate change, and bioenergy expansion. In the reference scenario (SSP2), food demand increases by 59-98% between 2005 and 2050, slightly higher than the most recent FAO projection of 54% from 2005/2007. The range of results is large, in particular for animal calories (between 61% and 144%), caused by differences in demand systems specifications, and in income and price elasticities. The results are more sensitive to socioeconomic assumptions than to climate change or bioenergy scenarios. When considering a world with higher population and lower economic growth (SSP3), consumption per capita drops on average by 9\% for crops and 18% for livestock. The maximum effect of climate change on calorie availability is -6% at the global level, and the effect of biofuel production on calorie availability is even smaller. |
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0169-5150 |
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TradeM, ft_macsur |
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Call Number |
MA @ admin @ |
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4752 |
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van Bussel, L.G.J.; Ewert, F.; Zhao, G.; Hoffmann, H.; Enders, A.; Wallach, D.; Asseng, S.; Baigorria, G.A.; Basso, B.; Biernath, C.; Cammarano, D.; Chryssanthacopoulos, J.; Constantin, J.; Elliott, J.; Glotter, M.; Heinlein, F.; Kersebaum, K.-C.; Klein, C.; Nendel, C.; Priesack, E.; Raynal, H.; Romero, C.C.; Rötter, R.P.; Specka, X.; Tao, F. |
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Title |
Spatial sampling of weather data for regional crop yield simulations |
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Journal Article |
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Year |
2016 |
Publication |
Agricultural and Forest Meteorology |
Abbreviated Journal |
Agricultural and Forest Meteorology |
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220 |
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101-115 |
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Keywords |
Regional crop simulations; Winter wheat; Upscaling; Stratified sampling; Yield estimates; climate-change scenarios; water availability; growth simulation; potential impact; food-production; winter-wheat; model; resolution; systems; soil |
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Field-scale crop models are increasingly applied at spatio-temporal scales that range from regions to the globe and from decades up to 100 years. Sufficiently detailed data to capture the prevailing spatio-temporal heterogeneity in weather, soil, and management conditions as needed by crop models are rarely available. Effective sampling may overcome the problem of missing data but has rarely been investigated. In this study the effect of sampling weather data has been evaluated for simulating yields of winter wheat in a region in Germany over a 30-year period (1982-2011) using 12 process-based crop models. A stratified sampling was applied to compare the effect of different sizes of spatially sampled weather data (10, 30, 50,100, 500, 1000 and full coverage of 34,078 sampling points) on simulated wheat yields. Stratified sampling was further compared with random sampling. Possible interactions between sample size and crop model were evaluated. The results showed differences in simulated yields among crop models but all models reproduced well the pattern of the stratification. Importantly, the regional mean of simulated yields based on full coverage could already be reproduced by a small sample of 10 points. This was also true for reproducing the temporal variability in simulated yields but more sampling points (about 100) were required to accurately reproduce spatial yield variability. The number of sampling points can be smaller when a stratified sampling is applied as compared to a random sampling. However, differences between crop models were observed including some interaction between the effect of sampling on simulated yields and the model used. We concluded that stratified sampling can considerably reduce the number of required simulations. But, differences between crop models must be considered as the choice for a specific model can have larger effects on simulated yields than the sampling strategy. Assessing the impact of sampling soil and crop management data for regional simulations of crop yields is still needed. |
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ISSN |
0168-1923 |
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CropM, ft_macsur |
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MA @ admin @ |
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4673 |
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van Bussel, L.G.J.; Stehfest, E.; Siebert, S.; Müller, C.; Ewert, F. |
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Title |
Simulation of the phenological development of wheat and maize at the global scale |
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Journal Article |
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2015 |
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Global Ecology and Biogeography |
Abbreviated Journal |
Glob. Ecol. Biogeogr. |
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24 |
Issue |
9 |
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1018-1029 |
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Keywords |
Agricultural management; crop calendars; cultivar; variety characteristics; global crop modelling; global harvest dates; phenology; climate-change; winter-wheat; annual crops; photoperiod sensitivity; geographical variation; temperature; responses; adaptation; cultivars; model |
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AimTo derive location-specific parameters that reflect the geographic differences among cultivars in vernalization requirements, sensitivity to day length (photoperiod) and temperature, which can be used to simulate the phenological development of wheat and maize at the global scale. LocationGlobal. Methods Based on crop calendar observations and literature describing the large-scale patterns of phenological characteristics of cultivars, we developed algorithms to compute location-specific parameters to represent this large-scale pattern. Vernalization requirements were related to the duration and coldness of winter, sensitivity to day length was assumed to be represented by the minimum and maximum day lengths occurring at a location, and sensitivity to temperature was related to temperature conditions during the vegetative development phase of the crop. Results Application of the derived location-specific parameters resulted in high agreement between simulated and observed lengths of the cropping period. Agreement was especially high for wheat, with mean absolute errors of less than 3 weeks. In the main maize cropping regions, cropping periods were over- and underestimated by 0.5-1.5 months. We also found that interannual variability in simulated wheat harvest dates was more realistic when accounting for photoperiod effects. Main conclusions The methodology presented here provides a good basis for modelling the phenological characteristics of cultivars at the global scale. We show that current global patterns of growing season length as described in cropping calendars can be largely reproduced by phenology models if location-specific parameters are derived from temperature and day length indicators. Growing seasons can be modelled more accurately for wheat than for maize, especially in warm regions. Our method for computing parameters for phenology models from temperature and day length offers opportunities to improve the simulation of crop productivity by crop simulation models developed for large spatial areas and for long-term climate impact projections that account for adaptation in the selection of varieties |
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1466-822x |
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CropM, ft_macsur |
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MA @ admin @ |
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4729 |
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