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Hlavinka, P.; Trnka, M.; Kersebaum, K.C.; Cermák, P.; Pohanková, E.; Orság, M.; Pokorný, E.; Fischer, M.; Brtnický, M.; Žalud, Z. |
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Title |
Modelling of yields and soil nitrogen dynamics for crop rotations by HERMES under different climate and soil conditions in the Czech Republic |
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Journal Article |
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Year  |
2014 |
Publication |
Journal of Agricultural Science |
Abbreviated Journal |
J. Agric. Sci. |
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Volume |
152 |
Issue |
02 |
Pages |
188-204 |
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Keywords |
winter oilseed rape; spring barley; central-europe; growth; simulation; wheat; adaptation; impact; water; agriculture |
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Abstract |
The crop growth model HERMES was used to model crop rotation cycles at 12 experimental sites in the Czech Republic. A wide range of crops (spring and winter barley, winter wheat, maize, potatoes, sugar beet, winter rape, oats, alfalfa and grass), cultivated between 1981 and 2009 under various soil and climatic conditions, were included. The model was able to estimate the yields of field crop rotations at a reasonable level, with an index of agreement (IA) ranging from 0.82 to 0.96 for the calibration database (the median coefficient of determination (R-2) was 0.71), while IA for verification varied from 0.62 to 0.93 (median R-2 was 0.78). Grass yields were also estimated at a reasonable level of accuracy. The estimates were less accurate for the above-ground biomass at harvest (the medians for IA were 0.76 and 0.72 for calibration and verification, respectively, and analogous medians of R-2 were 0.50 and 0.49). The soil mineral nitrogen (N) content under the field crops was simulated with good precision, with the IA ranging from 0.49 to 0.74 for calibration and from 0.43 to 0.68 for verification. Generally, the soil mineral N was underestimated, and more accurate results were achieved at locations with intensive fertilization. Simulated yields, soil N, water and organic carbon (C) contents were compared with long-term field measurements at Ne. mc. ice, located within the fertile Moravian lowland. At this station, all of the observed parameters were reproduced with a reasonable level of accuracy. In the case of the organic C content, HERMES reproduced a decrease ranging from c. 85 to 77 tonnes (t)/ha (for the 0-0.3 m soil layer) between the years 1980 and 2007. In spite of its relatively simple approach and restricted input data, HERMES was proven to be robust across various conditions, which is a precondition for its future use for both theoretical and practical purposes. |
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0021-8596 1469-5146 |
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CropM |
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MA @ admin @ |
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4626 |
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García-López, J.; Lorite, I.J.; García-Ruiz, R.; Domínguez, J. |
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Title |
Evaluation of three simulation approaches for assessing yield of rainfed sunflower in a Mediterranean environment for climate change impact modelling |
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Journal Article |
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Year |
2014 |
Publication |
Climatic Change |
Abbreviated Journal |
Clim. Change |
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124 |
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1-2 |
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147-162 |
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winter-wheat; water-stress; irrigation management; high-temperature; oil quality; oilcrop-sun; crop model; responses; variability; growth |
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The determination of the impact of climate change on crop yield at a regional scale requires the development of new modelling methodologies able to generate accurate yield estimates with reduced available data. In this study, different simulation approaches for assessing yield have been evaluated. In addition to two well-known models (AquaCrop and Stewart function), a methodological proposal considering a simplified approach using an empirical model (SOM) has been included in the analysis. This empirical model was calibrated using rainfed sunflower experimental field data from three sites located in Andalusia, southern Spain, and validated using two additional locations, providing very satisfactory results compared with the other models with higher data requirements. Thus, only requiring weather data (accumulated rainfall from the beginning of the season fixed on September 1st, and maximum temperature during flowering) the approach accurately described the temporal and spatial yield variability observed (RMSE = 391 kg ha(-1)). The satisfactory results for assessing yield of sunflower under semi-arid conditions obtained in this study demonstrate the utility of empirical approaches with few data requirements, providing an excellent decision tool for climate change impact analyses at a regional scale, where available data is very limited. |
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0165-0009 1573-1480 |
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CropM |
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MA @ admin @ |
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4622 |
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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. |
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Title |
Rising temperatures reduce global wheat production |
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Journal Article |
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Year |
2014 |
Publication |
Nature Climate Change |
Abbreviated Journal |
Nat. Clim. Change |
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5 |
Issue |
2 |
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143-147 |
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climate-change; spring wheat; dryland wheat; yield; growth; drought; heat; CO2; agriculture; adaptation |
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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. |
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1758-678x |
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CropM, ft_macsur |
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MA @ admin @ |
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4550 |
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Semenov, M.A.; Stratonovitch, P.; Alghabari, F.; Gooding, M.J. |
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Title |
Adapting wheat in Europe for climate change |
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Journal Article |
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Year |
2014 |
Publication |
Journal of Cereal Science |
Abbreviated Journal |
J. Ceareal Sci. |
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59 |
Issue |
3 |
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245-256 |
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A, maximum area of flag leaf area; ABA, abscisic acid; CV, coefficient of variation; Crop improvement; Crop modelling; FC, field capacity; GMT, Greenwich mean time; GS, growth stage; Gf, grain filling duration; HI, harvest index; HSP, heat shock protein; Heat and drought tolerance; Impact assessment; LAI, leaf area index; Ph, phylochron; Pp, photoperiod response; Ru, root water uptake; S, duration of leaf senescence; SF, drought stress factor; Sirius; Wheat ideotype |
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Increasing cereal yield is needed to meet the projected increased demand for world food supply of about 70% by 2050. Sirius, a process-based model for wheat, was used to estimate yield potential for wheat ideotypes optimized for future climatic projections for ten wheat growing areas of Europe. It was predicted that the detrimental effect of drought stress on yield would be decreased due to enhanced tailoring of phenology to future weather patterns, and due to genetic improvements in the response of photosynthesis and green leaf duration to water shortage. Yield advances could be made through extending maturation and thereby improve resource capture and partitioning. However the model predicted an increase in frequency of heat stress at meiosis and anthesis. Controlled environment experiments quantify the effects of heat and drought at booting and flowering on grain numbers and potential grain size. A current adaptation of wheat to areas of Europe with hotter and drier summers is a quicker maturation which helps to escape from excessive stress, but results in lower yields. To increase yield potential and to respond to climate change, increased tolerance to heat and drought stress should remain priorities for the genetic improvement of wheat. |
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0733-5210 |
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Review |
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CropM, ft_macsur |
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MA @ admin @ |
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4543 |
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Müller, C.; Robertson, R.D. |
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Projecting future crop productivity for global economic modeling |
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Journal Article |
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2014 |
Publication |
Agricultural Economics |
Abbreviated Journal |
Agric. Econ. |
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45 |
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1 |
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37-50 |
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climate change; crop modeling; agricultural productivity; land use; greenhouse-gas emissions; soil organic-carbon; sub-saharan africa; climate-change; elevated co2; land-use; system model; wheat yields; maize yields; agriculture |
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Assessments of climate change impacts on agricultural markets and land-use patterns rely on quantification of climate change impacts on the spatial patterns of land productivity. We supply a set of climate impact scenarios on agricultural land productivity derived from two climate models and two biophysical crop growth models to account for some of the uncertainty inherent in climate and impact models. Aggregation in space and time leads to information losses that can determine climate change impacts on agricultural markets and land-use patterns because often aggregation is across steep gradients from low to high impacts or from increases to decreases. The four climate change impact scenarios supplied here were designed to represent the most significant impacts (high emission scenario only, assumed ineffectiveness of carbon dioxide fertilization on agricultural yields, no adjustments in management) but are consistent with the assumption that changes in agricultural practices are covered in the economic models. Globally, production of individual crops decrease by 10-38% under these climate change scenarios, with large uncertainties in spatial patterns that are determined by both the uncertainty in climate projections and the choice of impact model. This uncertainty in climate impact on crop productivity needs to be considered by economic assessments of climate change. |
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0169-5150 |
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CropM, TradeM, ft_macsur |
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MA @ admin @ |
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4533 |
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