| Records |
| Author |
Elsgaard, L.; Børgesen, C.D.; Olesen, J.E.; Siebert, S.; Ewert, F.; Peltonen-Sainio, P.; Rötter, R.P.; Skjelvåg, A.O. |
| Title |
Shifts in comparative advantages for maize, oat and wheat cropping under climate change in Europe |
Type |
Journal Article |
| Year |
2012 |
Publication |
Food Additives & Contaminants: Part A |
Abbreviated Journal |
Food Addit. Contam. Part A |
| Volume |
29 |
Issue |
10 |
Pages |
1514-1526 |
| Keywords |
Agriculture/*economics/trends; Animals; Avena/chemistry/economics/*growth & development/microbiology; *Climate Change/economics; Crops, Agricultural/chemistry/economics/*growth & development/microbiology; Europe; *Food Safety; Forecasting/methods; Fungi/growth & development/metabolism; Humans; Models, Biological; Models, Economic; Mycotoxins/analysis/biosynthesis; Soil Pollutants/adverse effects/analysis; Spatio-Temporal Analysis; Triticum/chemistry/economics/*growth & development/microbiology; Uncertainty; Weather; Zea mays/chemistry/economics/*growth & development/microbiology |
| Abstract |
Climate change is anticipated to affect European agriculture, including the risk of emerging or re-emerging feed and food hazards. Indirectly, climate change may influence such hazards (e.g. the occurrence of mycotoxins) due to geographic shifts in the distribution of major cereal cropping systems and the consequences this may have for crop rotations. This paper analyses the impact of climate on cropping shares of maize, oat and wheat on a 50-km square grid across Europe (45-65°N) and provides model-based estimates of the changes in cropping shares in response to changes in temperature and precipitation as projected for the time period around 2040 by two regional climate models (RCM) with a moderate and a strong climate change signal, respectively. The projected cropping shares are based on the output from the two RCMs and on algorithms derived for the relation between meteorological data and observed cropping shares of maize, oat and wheat. The observed cropping shares show a south-to-north gradient, where maize had its maximum at 45-55°N, oat had its maximum at 55-65°N, and wheat was more evenly distributed along the latitudes in Europe. Under the projected climate changes, there was a general increase in maize cropping shares, whereas for oat no areas showed distinct increases. For wheat, the projected changes indicated a tendency towards higher cropping shares in the northern parts and lower cropping shares in the southern parts of the study area. The present modelling approach represents a simplification of factors determining the distribution of cereal crops, and also some uncertainties in the data basis were apparent. A promising way of future model improvement could be through a systematic analysis and inclusion of other variables, such as key soil properties and socio-economic conditions, influencing the comparative advantages of specific crops. |
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1944-0049 1944-0057 |
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MA @ admin @ |
Serial |
4585 |
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| Author |
Challinor, A.; Martre, P.; Asseng, S.; Thornton, P.; Ewert, F. |
| Title |
Making the most of climate impacts ensembles |
Type |
Journal Article |
| Year |
2014 |
Publication |
Nature Climate Change |
Abbreviated Journal |
Nat. Clim. Change |
| Volume |
4 |
Issue |
2 |
Pages |
77-80 |
| Keywords |
uncertainty; model; adaptation |
| Abstract |
Increasing use of regionally and globally oriented impacts studies, coordinated across international modelling groups, promises to bring about a new era in climate impacts research. Coordinated cycles of model improvement and projection are needed to make the most of this potential. |
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1758-678x 1758-6798 |
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Commentary |
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MA @ admin @ |
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4516 |
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Bassu, S.; Brisson, N.; Durand, J.-L.; Boote, K.; Lizaso, J.; Jones, J.W.; Rosenzweig, C.; Ruane, A.C.; Adam, M.; Baron, C.; Basso, B.; Biernath, C.; Boogaard, H.; Conijn, S.; Corbeels, M.; Deryng, D.; De Sanctis, G.; Gayler, S.; Grassini, P.; Hatfield, J.; Hoek, S.; Izaurralde, C.; Jongschaap, R.; Kemanian, A.R.; Kersebaum, K.C.; Kim, S.-H.; Kumar, N.S.; Makowski, D.; Müller, C.; Nendel, C.; Priesack, E.; Pravia, M.V.; Sau, F.; Shcherbak, I.; Tao, F.; Teixeira, E.; Timlin, D.; Waha, K. |
| Title |
How do various maize crop models vary in their responses to climate change factors |
Type |
Journal Article |
| Year |
2014 |
Publication |
Global Change Biology |
Abbreviated Journal |
Glob. Chang. Biol. |
| Volume |
20 |
Issue |
7 |
Pages |
2301-2320 |
| Keywords |
Carbon Dioxide/metabolism; *Climate Change; Crops, Agricultural/growth & development/metabolism; Geography; Models, Biological; Temperature; Water/*metabolism; Zea mays/*growth & development/*metabolism; AgMIP; [Co2]; climate; maize; model intercomparison; simulation; uncertainty |
| Abstract |
Potential consequences of climate change on crop production can be studied using mechanistic crop simulation models. While a broad variety of maize simulation models exist, it is not known whether different models diverge on grain yield responses to changes in climatic factors, or whether they agree in their general trends related to phenology, growth, and yield. With the goal of analyzing the sensitivity of simulated yields to changes in temperature and atmospheric carbon dioxide concentrations [CO2 ], we present the largest maize crop model intercomparison to date, including 23 different models. These models were evaluated for four locations representing a wide range of maize production conditions in the world: Lusignan (France), Ames (USA), Rio Verde (Brazil) and Morogoro (Tanzania). While individual models differed considerably in absolute yield simulation at the four sites, an ensemble of a minimum number of models was able to simulate absolute yields accurately at the four sites even with low data for calibration, thus suggesting that using an ensemble of models has merit. Temperature increase had strong negative influence on modeled yield response of roughly -0.5 Mg ha(-1) per °C. Doubling [CO2 ] from 360 to 720 μmol mol(-1) increased grain yield by 7.5% on average across models and the sites. That would therefore make temperature the main factor altering maize yields at the end of this century. Furthermore, there was a large uncertainty in the yield response to [CO2 ] among models. Model responses to temperature and [CO2 ] did not differ whether models were simulated with low calibration information or, simulated with high level of calibration information. |
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1354-1013 |
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Article |
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CropM |
Approved |
no |
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MA @ admin @ |
Serial |
4510 |
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| Author |
Francone, C.; Cassardo, C.; Richiardone, R.; Confalonieri, R. |
| Title |
Sensitivity Analysis and Investigation of the Behaviour of the UTOPIA Land-Surface Process Model: A Case Study for Vineyards in Northern Italy |
Type |
Journal Article |
| Year |
2012 |
Publication |
Boundary-Layer Meteorology |
Abbreviated Journal |
Boundary-Layer Meteorology |
| Volume |
144 |
Issue |
3 |
Pages |
419-430 |
| Keywords |
energy balance; hydrological balance; land-surface model; morris method; vegetation cover; vitis vinifera l.; atmosphere transfer scheme; environmental-models; energy-balance; uncertainty; simulation; canopy |
| Abstract |
We used sensitivity-analysis techniques to investigate the behaviour of the land-surface model UTOPIA while simulating the micrometeorology of a typical northern Italy vineyard (Vitis vinifera L.) under average climatic conditions. Sensitivity-analysis experiments were performed by sampling the vegetation parameter hyperspace using the Morris method and quantifying the parameter relevance across a wide range of soil conditions. This method was used since it proved its suitability for models with high computational time or with a large number of parameters, in a variety of studies performed on different types of biophysical models. The impact of input variability was estimated on reference model variables selected among energy (e.g. net radiation, sensible and latent heat fluxes) and hydrological (e.g. soilmoisture, surface runoff, drainage) budget components. Maximum vegetation cover and maximum leaf area index were ranked as the most relevant parameters, with sensitivity indices exceeding the remaining parameters by about one order of magnitude. Soil variability had a high impact on the relevance of most of the vegetation parameters: coefficients of variation calculated on the sensitivity indices estimated for the different soils often exceeded 100 %. The only exceptions were represented by maximum vegetation cover and maximum leaf area index, which showed a low variability in sensitivity indices while changing soil type, and confirmed their key role in affecting model results. |
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0006-8314 1573-1472 |
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Article |
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CropM |
Approved |
no |
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MA @ admin @ |
Serial |
4470 |
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