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Sandars et al. |
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A comparison of greenhouse gas (GHG) emissions from dairy farms by four systems models with eight agro-climatic scenarios |
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2016 |
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FACCE MACSUR Reports |
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8 |
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SP8-15 |
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LiveM2016: International livestock modelling conference – Modelling grassland-livestock systems under climate change |
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no |
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MA @ admin @ |
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4861 |
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Author |
Sandars, D. |
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Optimal Land-use Future Scenarios Nordic Area |
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2015 |
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FACCE MACSUR Reports |
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4 |
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SP4-14 |
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TradeM International Workshop 2014 »Economics of integrated assessment approaches for agriculture and the food sector«, 25–27 November 2014, Hurdalsjø, Norway |
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no |
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MA @ admin @ |
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2204 |
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Sandars, D. |
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Understanding Europe’s future ability to feed itself within an uncertain climate change and socio economic scenario space |
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2015 |
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FACCE MACSUR Reports |
Abbreviated Journal |
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5 |
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Sp5-54 |
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Europe’s ability to feed its population depends on the balance of agricultural productivity (yields and land suitability) and demand which are affected by future climate and socio-economic change (arising from changing food demand; prices; technology change etc). Land use under 2050 climate change and socio-economic scenarios can be rapidly and systematically quantified with a modelling system that has been developed from meta-models of optimal cropping and crop and forest yields derived from the outputs of the previously developed complex models (Audsley et al; 2015). Profitability of each possible land use is modelled for every soil in every grid across the EU. Land use in a grid is then allocated based on profit thresholds set for intensive agriculture extensive agriculture, managed forest and finally unmanaged forest or unmanaged land. The European demand for food as a function of population, imports, food preferences and bioenergy, is a production constraint, as is irrigation water available. The model iterates until demand is satisfied (or cannot be met at any price). Results are presented as contour plots of key variables. For example, given a 40% increase in population from the baseline socio-economic scenario, adapting by increasing crop yields by 40% will leave a 38% probability that the 2050 future climate will be such that we cannot feed ourselves – considering “all” the possible climate scenarios. No Label |
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MACSUR Science Conference 2015 »Integrated Climate Risk Assessment in Agriculture & Food«, 8–9+10 April 2015, Reading, UK |
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MA @ admin @ |
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2169 |
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Sándor et al. |
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Global Research Alliance on Greenhouse Gases – benchmark and ensemble crop and grassland model estimates |
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2016 |
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FACCE MACSUR Reports |
Abbreviated Journal |
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8 |
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SP8-14 |
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Conference presentation PDF |
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LiveM2016: International livestock modelling conference – Modelling grassland-livestock systems under climate change |
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no |
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MA @ admin @ |
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4848 |
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Author |
Sándor, R. |
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Sensitivity and uncertainty analysis of grassland models in Europe and Israel |
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2015 |
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FACCE MACSUR Reports |
Abbreviated Journal |
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5 |
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Sp5-55 |
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Grassland models are valuable tools to test hypotheses on grassland ecosystem functioning. In the frame of FACCE MACSUR LiveM, a model intercomparison was conducted using a dataset from an observational and experimental network of nine multi-year grassland sites spread across Europe (France, Italy, Germany, Switzerland, The Netherlands, and United Kingdom) and Israel, and a suite of nine models to understand grassland functioning in the region. Grassland-specific approaches were compared to approaches mainly conceived to simulate crops and plant functional types. Model evaluation against actual measurements was performed before and after model calibration. The calibrated models were used to analyze their sensitivity to independent variations of temperature, precipitation and [CO2]. The results show to which extent calibration can accommodate model discrepancies. The sensitivity of simulated gross primary production to [CO2] and temperature is an important outcome, considering the fundamental effect of rising temperature and [CO2] on the C cycling of terrestrial ecosystems in the Euro-Mediterranean region. Overall, alternative models exhibit a different sensitivity to climate change factors, with different performances over different conditions. Explained by the basic processes of each model and also induced by different calibration methods, this difference is indicative that more models can be complementary and deliver greater insights than if they were applied individually. No Label |
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MACSUR Science Conference 2015 »Integrated Climate Risk Assessment in Agriculture & Food«, 8–9+10 April 2015, Reading, UK |
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MA @ admin @ |
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2170 |
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