| Records |
| Author |
Persson, T.; Kværnø, S. |
| Title |
Impact of projected mid-21st century climate and soil extrapolation on simulated spring wheat grain yield in Southeastern Norway |
Type |
Journal Article |
| Year |
2017 |
Publication |
Journal of Agricultural Science |
Abbreviated Journal |
J. Agric. Sci. |
| Volume |
155 |
Issue |
03 |
Pages |
361-377 |
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| Abstract |
The effects of soil variability on regional crop yield under projected climate change are largely unknown. In Southeastern Norway, increased temperature and precipitation are projected for the mid-21st century. Crop simulation models in combination with scaling techniques can be used to determine the regional pattern of crop yield. In the present paper, the CSM-CROPSIM-CERES-Wheat model was applied to simulate regional spring wheat yield for Akershus and Østfold counties in Southeastern Norway. Prior to the simulations, parameters in the CSM-CROPSIM-CERES-Wheat model were calibrated for the spring wheat cvars Zebra, Demonstrant and Bjarne, using cultivar trial data from Southeastern Norway and site-specific weather and soil information. Weather input data for regional yield simulations represented the climate in 1961–1990 and projections of the climate in 2046–2065. The latter were based on four Global Climate Models and greenhouse gas emission scenario A1B in the IPCC 4th Assessment Report. Data on regional soil particle size distribution, water-holding characteristics and organic matter data were obtained from a database. To determine the simulated grain yield sensitivity to soil input, the number of soil profiles used to describe the soilscape in the region varied from 76 to 16, 5 and 1. The soils in the different descriptions were selected by arranging them into groups according to similarities in physical characteristics and taking the soil in each group occupying the largest area in the region to represent other soils in that group. The simulated grain yields were higher under all four projected future climate scenarios than the corresponding average yields in the baseline conditions. On average across the region, there were mostly non-significant differences in grain yield between the soil extrapolations for all cultivars and climate projections. However, for sub-regions grain yield varied by up to 20% between soil extrapolations. These results indicate how projected climate change could affect spring wheat yield given the assumed simulated conditions for a region with similar climate and soil conditions to many other cereal production regions in Northern Europe. The results also provide useful information about how soil input data could be handled in regional crop yield determinations under these conditions. |
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0021-8596 |
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CropM, LiveM, ft_macsur |
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no |
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MA @ admin @ |
Serial |
5009 |
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| Author |
Heinschink, K.; Sinabell, F.; Url, T. |
| Title |
Elements of an Index-based Margin Insurance. An Application to Wheat Production in Austria |
Type |
Report |
| Year |
2017 |
Publication |
WIFO Working Papers |
Abbreviated Journal |
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| Volume |
536 |
Issue |
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Pages |
16 |
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TradeM |
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no |
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MA @ admin @ |
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5016 |
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Leolini, L.; Moriondo, M.; De Cortazar-Atauri, I.; Ruiz-Ramos, M.; Nendel, C.; Roggero, P.P.; Spanna, F.; Ramos, M.C.; Costafreda-Aumedes, S.; Ferrise, R.; Bindi, M. |
| Title |
Modelling different cropping systems |
Type |
Report |
| Year |
2017 |
Publication |
FACCE MACSUR Reports |
Abbreviated Journal |
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| Volume |
10 |
Issue |
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Pages |
C1.4-D |
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Grapevine is a worldwide valuable crop characterized by a high economic importance for the production of high quality wines. However, the impact of climate change on the narrow climate niches in which grapevine is currently cultivated constitute a great risk for future suitability of grapevine. In this context, grape simulation models are considered promising tools for their contribution to investigate plant behavior in different environments. In this study, six models developed for simulating grapevine growth and development were tested by focusing on their performances in simulating main grapevine processes under two calibration levels: minimum and full calibration. This would help to evaluate major limitations/strength points of these models, especially in the view of their application to climate change impact and adaptation assessments. Preliminary results from two models (GrapeModel and STICS) showed contrasting abilities in reproducing the observed data depending on the site, the year and the target variable considered. These results suggest that a limited dataset for model calibration would lead to poor simulation outputs. However, a more complete interpretation and detailed analysis of the results will be provided when considering the other models simulations. |
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CropM |
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no |
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MA @ admin @ |
Serial |
5033 |
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Biewald, A.; Sinabell, F.; Lotze-Campen, H.; Zimmermann, A.; Lehtonen, H. |
| Title |
Global Representative Agricultural Pathways for Europe |
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Report |
| Year |
2017 |
Publication |
FACCE MACSUR Reports |
Abbreviated Journal |
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10 |
Issue |
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Pages |
T1.2-XC16.2 |
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Agricultural elements have been covered in the scenario process on shared socio-economic pathways (SSPs) incompletely and pathways have not been specified for the future development of the European Union. We will therefore devise a general framework on European Representative Agricultural Pathways (EU-RAPs), where we cover different aspects of agricultural development, as for example European and domestic agricultural and environmental policies, or different livestock and crop management systems, and describe future developments of the confederation of the countries of the European Union. For the agricultural elements we distinguish between elements that can be derived from the definitions in the Shared Socioeconomic Pathways, as for example irrigation efficiencies which are linked to technological development, and elements that have to be newly devised such as the development of the Common Agricultural Policy. For the future of the European Union we develop five different worlds which correspond to the SSPs. Finally both frameworks are combined. |
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TradeM |
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MA @ admin @ |
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5034 |
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| Author |
Sharif, B. |
| Title |
Data mining techniques for quantifying and projecting crop yield responses to climate change |
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Book Whole |
| Year |
2017 |
Publication |
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Ph.D. thesis |
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Aarhus University |
Place of Publication |
Aarhus |
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PhD |
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CropM |
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no |
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MA @ admin @ |
Serial |
5165 |
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