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The influence of climate change, technological progress and political change on agricultural land use: calculated scenarios for the Upper Danube catchment area

By Martin Henseler, Alexander Wirsig, Tatjana Krimly and Stephan Dabbert

Abstract

Both climate and agricultural policy changes are commonly seen as important drivers for agricultural production. In this study, scenarios of climate and political change were calculated for the Upper Danube catchment area using the regional optimization model ACRE. Two political scenarios were calculated for the year 2020. One scenario assumes the continuation of the Common Agricultural Policy reform 2003 the other assumes a strong shift away from payments of the first pillar to payments of the second pillar of the CAP. Both scenarios were combined with four different scenarios of climate change and technological progress derived from ICCP SRES assumptions and the ACCELERATES project. The results of the scenario calculations were analysed with respect to their implications for the whole catchment area as well as for selected districts. Climate change and technological progress both cause small changes in agricultural land use: fodder crop area tends to be converted to cash crop area, and intensive grasslands tend to be converted into extensive grasslands. Climate change and technological progress increase crop productivity, and consequently, total gross margin increases. The impact of climate change might get stronger toward the end of the century which is beyond the scope of the investigations presented here. The impact of climate change might thus switch from bringing net benefits in the short to medium term to bringing net losses for the area investigated in the long run.global change, regional model, climate change, agricultural policy scenarios, agricultural land use, Agricultural and Food Policy, Environmental Economics and Policy, Land Economics/Use,

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Citations

  1. (2004). A comprehensive set of high-resolution grids of monthly climate for Europe and the globe: the observed record (1901-2000) and 16 scenarios (2001-2100). Working paper.
  2. (2002). A research concept to develop integrative techniques, scenarios and strategies regarding Global Changes of the water cycle.
  3. (1996). Agro-climatic change and European suitability: regional modelling at monthly time steps.
  4. (2006). Anwendung des Regionalmodells ACRE in zwei interdisziplinären Projekten.
  5. (2007). COM (Commission of the European Communities) (2007): Preparing for the “Health Check” of the CAP reform. Communication from the Commission to the European Parliament and the Council,
  6. (2004). Correlation analysis of climate variables and wheat yield data on various aggregation levels in Germany and the EU 15 using GIS and statistical methods, with a focus on heat wave years. Diploma Thesis.
  7. (2007). Crop yield data from calculations with the ROIMPEL crop growth model for the Upper Danube basin.
  8. (2006). Downscaling of land use change scenarios to assess the dynamics of European landscapes.
  9. (2005). Ein Nichtlineares Prozessanalytisches Agrarsektormodell für das Einzugsgebiet der Oberen Donau – Ein Beitrag zum Decision-Support-System Glowa-Danubia. PhD-Thesis,
  10. Environmental Agency) (2004): Impacts of Europe’s changing climate – An indicator based assessment. Summary.
  11. (1984). EPIC: a new model for assessing erosion’s effect on soil productivity.
  12. (2007). Fourth assessment report – Climate Change.
  13. (2006). Future European agricultural landscapes – What can we learn from existing quantitative land use scenario studies? In: Agriculture,
  14. (2005). Future scenarios of European Agricultural Land Use I. Estimating changes in crop productivity.
  15. (2008). Heinrich von Thünen-Institut - Institut für Marktanalyse und Agrarhandelspolitik
  16. (2005). Impacts of global changes on agricultural land-use in the German Elbe region : results of an operational modelling tool for planning, monitoring and agri-environmental policy counselling. In:
  17. (2004). Integrated Ecohydrological Analysis of a Temperate Developed Region - The Elbe River Basin
  18. (2003). Integrating Agri-Environmental Programs into Regional Production Models – An Extension of Positive Mathematical Programming. In:
  19. (1994). IPCC – Technical Guidelines for Assessing Climate Change Impacts and Adaptations.
  20. (2006). Klimaänderungen und die Folgen für die Landwirtschaft.
  21. (2004). Landwirtschaft unter dem Einfluss des Globalen Wandels sowie sich ändernde gesellschaftliche
  22. (2008). Market scenario” and “Local Stewardship scenario” correspond in terminology of EURALIS to “Global Economy scenario” and “Regional Communities scenario”, respectively.
  23. (2005). Ministry of Consumer Protection Food and Agriculture
  24. (1995). Positive Mathematical Programming. In:
  25. Report commissioned by the Federal Environmental Agency, Germany (UFOPLAN 201 41 253), Potsdam Institute of Climate Impact Research,
  26. (2006). Socio-economic scenario development for the assessment of climate change impacts on agricultural land use: a pairwise comparison approach.
  27. (2000). Special Report on Emissions Scenarios.
  28. (2003). Studie zur klimatischen Entwicklung im Land Brandenburg bis 2055 und deren Auswirkungen auf den Wasserhaushalt, die Forst- und Landwirtschaft sowie die Ableitung erster Perspektiven. Potsdam Institute for Climate Change Impacts,
  29. (2006). The impact of different policy environments on agricultural land use in Europe. In: Agriculture,
  30. (2003). Trends in maize, rice, and wheat yields for 188 nations over the past 40 years: a prevalence of linear growth.
  31. (2006). What can scenario modelling tell us about future European scale agricultural land use, and what not? In: