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Saetnan, E.; Kipling, P.; Scollan, D.; Bartley, D.; Bellocchi, G.; Hutchings, J.; Dalgaard, T.; van den Pol-van Dasselaar, A. |
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MACSUR LiveM – a knowledge-hub for integrated modelling of climate change impacts on livestock production systems: lessons learned and future developments |
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2014 |
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LiveM |
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Livestock, Climate Change and Food Security, Madrid, Spain, 2014-05-19 to 2014-05-20 |
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MA @ admin @ |
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2781 |
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Salamon, P.; Banse, M.; Köchy, M. |
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Title |
MACSUR: Modelling European Agriculture with Climate Change for Food Security |
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Conference Article |
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2014 |
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Hub |
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23rd World Outlook Conference, Seville, Spain, 2014-05-12 to 2014-05-13 |
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MA @ admin @ |
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2782 |
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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. |
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Title |
Why do global long-term scenarios for agriculture differ? An overview of the AgMIP Global Economic Model Intercomparison |
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Journal Article |
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2014 |
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Agricultural Economics |
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Agric. Econ. |
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45 |
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1 |
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3-3 |
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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 |
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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. |
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2016-10-31 |
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English |
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0169-5150 |
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TradeM, ft_macsur |
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MA @ admin @ |
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4822 |
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Author |
Sandars, L.; Audsley, E. |
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Title |
Optimal Land-use Future Scenarios Nordic Area |
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Conference Article |
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2014 |
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Trade M |
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TradeM International Workshop 2014 »Economics of integrated assessment approaches for agriculture and the food sector«, Hurdalsjøen, Norway, 2014-11-25 to 2014-11-27 |
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MA @ admin @ |
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2785 |
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Author |
Sandhu, H.; Porter, J.R.; Wratten, S. |
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Title |
Experimental assessment of ecosystem services in agriculture |
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Book Chapter |
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Year |
2013 |
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122-135 |
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CropM; |
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Wratten, S.; Sandhu, H.; Cullen, R.; Costanza, R. |
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Ecosystem Services in Agricultural and Urban Landscapes |
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MA @ admin @ |
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2786 |
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