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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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Schmid, E. |
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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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5036 |
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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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2205 |
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Schönhart et al. |
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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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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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4844 |
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Schönhart, M. |
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Title |
Uncertainties from Climate Change on Farms and Ecosystem Services of a Grassland Dominated Austrian Landscape |
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2016 |
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FACCE MACSUR Reports |
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9 C6 - |
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Sp9-9 |
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MACSUR 1: development of a method to analysefarm and landscape scale impacts of CC, mitigationand adaptation effects– cropland dominated landscape, crop choice and soilmanagement– climate model uncertainty• Now: test and improve the robustness of the method– grassland landscape, cropland expansion and livestock– uncertainty analysis– variability of weather conditions High spatial resolution creates interfaces to disciplinarymodels and indicators• Challenging data & modelling demand• Increasing productivity can increase intensification pressures• Threatened permanent (extensive) grasslands and landscape elements, but• subject to resource constraints, costs and prices• Future RDP and environmental policy design (e.g. WFD) may need to takechanging productivity into account• Future research: analyze uncertainties & environmentalimpacts• Ensembles of crop and grassland models• Sensitivity analysis on economic input parameters• Qualitative surveys with agricultural experts and farmers |
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MA @ admin @ |
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4832 |
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