| Records |
| Author |
Rötter, R.P.; Höhn, J.K.; Palosuo, T.; Kassie, B.T.; Paff, K.; Tao, F.; Chen, Y.; Asseng, S.; et al. |
| Title |
Yield gap and variability analysis for different aro-technologies for maize and wheat (YGV study) |
Type |
Conference Article |
| Year |
2015 |
Publication |
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Pages |
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| Keywords |
CropM; |
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Place of Publication |
Ithaca (U.S.A.) |
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Conference |
2nd Global Food Security Conference, 2015-10-10- to 2015-10-15, Ithaca |
| Notes |
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Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
2770 |
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| Author |
Ruiz-Ramos, M. |
| Title |
Les modèles de culture face au changement climatique : les enjeux des projets nationaux, européens et internationaux |
Type |
Conference Article |
| Year |
2015 |
Publication |
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| Keywords |
CropM |
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Conference |
Xe Colloque STICS. March 24-26, Rennes, France, 2015-03-24 to 2015-04-26 |
| Notes |
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Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
2772 |
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| Author |
Ruiz-Ramos, M.; Rodríguez, A.; Dosio, A.; Goodess, C.; Harpham, C.; Mínguez, I.; Sánchez-Sánchez, E. |
| Title |
Improving crop simulations by bias reduction of RCM climate change projections: Evaluation on the present climate |
Type |
Conference Article |
| Year |
2013 |
Publication |
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| Volume |
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Pages |
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| Keywords |
CropM |
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Conference |
International Conference On Regional Climate - CORDEX 2013 A partnership between WCRP, the European Commission and IPCC 4th-7th. November 2013, Brussels, Belgium, 2013-11-04 to 2013-11-07 |
| Notes |
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Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
2773 |
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| Author |
Ruiz-Ramos, M.; Pérez-Lopez, D.; Sánchez-Sánchez, E.; Centeno, A.; Dosio, A.; Rodríguez, A. |
| Title |
Improving modelled impacts on the flowering of temperate fruit trees in the Iberian Peninsula of climate change projections for 21st century |
Type |
Conference Article |
| Year |
2013 |
Publication |
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Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
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| Keywords |
CropM |
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Conference |
European GeoSciences Union (EGU), General Assembly 2013, 2013-04-07 to 2013-04-12 |
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Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
2774 |
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| Author |
von Lampe, M.; Willenbockel, D.; Ahammad, H.; Blanc, E.; Cai, Y.; Calvin, K.; Fujimori, S.; Hasegawa, T.; Havlik, P.; Heyhoe, E.; Kyle, P.; Lotze-Campen, H.; Mason, d’C., Daniel; Nelson, G.C.; Sands, R.D.; Schmitz, C.; Tabeau, A.; Valin, H.; van der Mensbrugghe, D.; van Meijl, H. |
| Title |
Why do global long-term scenarios for agriculture differ? An overview of the AgMIP Global Economic Model Intercomparison |
Type |
Journal Article |
| Year |
2014 |
Publication |
Agricultural Economics |
Abbreviated Journal |
Agric. Econ. |
| Volume |
45 |
Issue |
1 |
Pages |
3-3 |
| Keywords |
Computable general equilibrium; Partial equilibrium; Meta-analysis; Socioeconomic pathway; Climate change; Bioenergy; Land use; Model; intercomparison; land-use change; food demand; crop productivity; climate-change; future |
| Abstract |
Recent studies assessing plausible futures for agricultural markets and global food security have had contradictory outcomes. To advance our understanding of the sources of the differences, 10 global economic models that produce long-term scenarios were asked to compare a reference scenario with alternate socioeconomic, climate change, and bioenergy scenarios using a common set of key drivers. Several key conclusions emerge from this exercise: First, for a comparison of scenario results to be meaningful, a careful analysis of the interpretation of the relevant model variables is essential. For instance, the use of real world commodity prices differs widely across models, and comparing the prices without accounting for their different meanings can lead to misleading results. Second, results suggest that, once some key assumptions are harmonized, the variability in general trends across models declines but remains important. For example, given the common assumptions of the reference scenario, models show average annual rates of changes of real global producer prices for agricultural products on average ranging between -0.4% and +0.7% between the 2005 base year and 2050. This compares to an average decline of real agricultural prices of 4% p.a. between the 1960s and the 2000s. Several other common trends are shown, for example, relating to key global growth areas for agricultural production and consumption. Third, differences in basic model parameters such as income and price elasticities, sometimes hidden in the way market behavior is modeled, result in significant differences in the details. Fourth, the analysis shows that agro-economic modelers aiming to inform the agricultural and development policy debate require better data and analysis on both economic behavior and biophysical drivers. More interdisciplinary modeling efforts are required to cross-fertilize analyses at different scales. |
| Address |
2016-10-31 |
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| Language |
English |
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Edition |
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| ISSN |
0169-5150 |
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Article |
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| Notes |
TradeM, ft_macsur |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4822 |
| Permanent link to this record |
