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Schönhart et al. |
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Title |
Integrated Assessment of Climate Change Impacts on Farms and Ecosystems in a Grassland Dominated Austrian Landscape |
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2016 |
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FACCE MACSUR Reports |
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8 |
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SP8-16 |
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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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4844 |
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Schmidhuber, J. |
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Title |
The Food Equation”: Taking a long/term View on World Agriculture, Climate Change and Food Security |
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2015 |
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FACCE MACSUR Reports |
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4 |
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SP4-15 |
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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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MA @ admin @ |
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2205 |
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Author |
Schmid, E. |
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Title |
Integrated land use modelling — a course for doctoral students |
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2017 |
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FACCE MACSUR Reports |
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10 |
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T4.1-4.2-XC4.3-4.4-D |
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TradeM |
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The course on “Integrated land use modelling” took place at BOKU Vienna between 24. – 28. April 2017. It was a five-days course capturing many aspects in quantitative integrated land use modelling using GAMS (see course outline). 10 students have participated the course coming from several countries. Students finishing the course have received 3 ECTS points. The course was offered by BOKU and the Doctoral Certificate Program in Agricultural Economics (https://www.agraroekonomik.de/index.html ). |
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MA @ admin @ |
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5036 |
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Author |
Schils, R. |
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Title |
Yield gap analysis of cereals in Europe supported by local knowledge |
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2015 |
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FACCE MACSUR Reports |
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5 |
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Sp5-57 |
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The increasing demand for food requires a sustainable intensification of crop production in underperforming areas. Many global and local studies have addressed yield gaps, i.e. the difference between potential or water-limited yields and actual yields. Global studies generally rely on generic models combined with a grid-based approach. Although using a consistent method, it has been shown they are not suitable for local yield gap assessment. Local studies generally exploit knowledge of location-specific conditions and management, but are less comparable across locations due to different methods. To overcome these inconsistencies, the Global Yield Gap Atlas (GYGA, www.yieldgap.org) proposes a consistent bottom-up approach to estimate yield gaps. This paper outlines the implementation of GYGA for estimating yield gaps of cereals across Europe. For each country, climate zones are identified which represent the major growing areas. Within these climate zones, weather stations are selected with >=15 years of daily data. For dominant soil types within a buffer zone around the weather stations, the potential and water-limited yields are simulated with a crop model, using local knowledge on management. Actual yields are derived from sub-national statistics. Yield gaps are scaled up from buffer zones to climate zones and countries. We will present the first results for selected regions in Europe, and discuss methodological issues on location specific weather and upscaling from weather station buffer zones to climate zones and countries. Furthermore we will look ahead at the implementation of the yield gap cross cutting activity (XC9) in MACSUR-2. 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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2172 |
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Author |
Schils, R. |
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Title |
Yield gaps of cereals across Europe |
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2017 |
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FACCE MACSUR Reports |
Abbreviated Journal |
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10 |
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Xc9.1-D1 |
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The increasing global demand for food requires a sustainable intensification of crop production in low-yielding areas. Actions to improve crop production in these regions call for accurate spatially explicit identification of yield gaps, i.e. the difference between potential or water-limited yield and actual yield. The Global Yield Gap Atlas (GYGA) project proposes a consistent bottom-up approach to estimate yield gaps. For each country, a climate zonation is overlaid with a crop area map. Within climate zones with important crop areas, weather stations are selected with at least 10 years of daily data. For each of the 3 dominant soil types within a 100 km zone around the weather stations, the potential and water-limited yields are simulated with the WOFOST crop model, using location-specific knowledge on crop systems. Data from variety trials or other experiments, approaching potential or water-limited yields, are used for validation and calibration of the model. Actual yields are taken from sub-national statistics. Yields and yield gaps are scaled up to climate zones and subsequently to countries. The average national simulated wheat yields under rainfed conditions varied from around 5 to 6 t/ha/year in the Mediterranean to nearly 12 t/ha/year on the British Isles and in the Low Countries. The average actual wheat yield varied from around 2 to 3 t/ha/year in the Mediterranean and some countries in East Europe to nearly 9 t/ha/year on the British Isles and in the Low Countries. The average relative yield gaps varied from around 10% to 30% in many countries in Northwest Europe to around 50% to 70% in some countries in the Mediterranean and East Europe. The paper will elaborate on results per climate zone and soil type, and will also include barley and maize. Furthermore we will relate yield gaps to nitrogen use. |
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XC, CropM |
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MA @ admin @ |
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4960 |
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