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Climatic Change

, Volume 128, Issue 3–4, pp 215–227 | Cite as

Interactively modelling land profitability to estimate European agricultural and forest land use under future scenarios of climate, socio-economics and adaptation

  • Eric Audsley
  • Mirek Trnka
  • Santiago Sabaté
  • Joan Maspons
  • Anabel Sanchez
  • Daniel Sandars
  • Jan Balek
  • Kerry Pearn
Article

Abstract

Studies of climate change impacts on agricultural land use generally consider sets of climates combined with fixed socio-economic scenarios, making it impossible to compare the impact of specific factors within these scenario sets. Analysis of the impact of specific scenario factors is extremely difficult due to prohibitively long run-times of the complex models. This study produces and combines metamodels of crop and forest yields and farm profit, derived from previously developed very complex models, to enable prediction of European land use under any set of climate and socio-economic data. Land use is predicted based on the profitability of the alternatives on every soil within every 10’ grid across the EU. A clustering procedure reduces 23,871 grids with 20+ soils per grid to 6,714 clusters of common soil and climate. Combined these reduce runtime 100 thousand-fold. Profit thresholds define land as intensive agriculture (arable or grassland), extensive agriculture or managed forest, or finally unmanaged forest or abandoned land. The demand for food as a function of population, imports, food preferences and bioenergy, is a production constraint, as is irrigation water available. An iteration adjusts prices to meet these constraints. A range of measures are derived at 10’ grid-level such as diversity as well as overall EU production. There are many ways to utilise this ability to do rapid What-If analysis of both impact and adaptations. The paper illustrates using two of the 5 different GCMs (CSMK3, HADGEM with contrasting precipitation and temperature) and two of the 4 different socio-economic scenarios (“We are the world”, “Should I stay or should I go” which have contrasting demands for land), exploring these using two of the 13 scenario parameters (crop breeding for yield and population) . In the first scenario, population can be increased by a large amount showing that food security is far from vulnerable. In the second scenario increasing crop yield shows that it improves the food security problem.

Keywords

Abandoned Land Unmanaged Forest Available Water Capacity NUTS2 Level Farm Profit 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

This work was supported by the CLIMSAVE Project (Climate change integrated assessment methodology for cross-sectoral adaptation and vulnerability in Europe; www.climsave.eu) funded under the Seventh Framework Programme of the European Commission (Contract No. 244031).). The Czech participation was co-funded through Ministry of Education projects no. 7E10033 and KONTAKT II LD130030 with Jan Balek’s work being funded through project Building up a multidisciplinary scientific team focused on drought, No. CZ.1.07/2.3.00/20.0248

Supplementary material

10584_2014_1164_MOESM1_ESM.docx (4.2 mb)
ESM 1 (DOCX 4296 kb)

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Copyright information

© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  • Eric Audsley
    • 1
  • Mirek Trnka
    • 2
    • 3
  • Santiago Sabaté
    • 4
    • 5
  • Joan Maspons
    • 4
  • Anabel Sanchez
    • 4
  • Daniel Sandars
    • 1
  • Jan Balek
    • 2
    • 3
  • Kerry Pearn
    • 1
  1. 1.Cranfield UniversityCranfieldUK
  2. 2.Institute of Agriculture Systems and BioclimatologyMendel University in BrnoBrnoCzech Republic
  3. 3.Global Change Research CentreBrnoCzech Republic
  4. 4.CREAF (Centre de Recerca Ecològica i Aplicacions Forestals)Universitat Autònoma de BarcelonaBellaterra (Barcelona)Spain
  5. 5.Ecology DepartmentUniversity of BarcelonaBarcelonaSpain

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