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Assessing the adaptation of arable farmers to climate change              using DEA and bio-economic modeling            A...
Aims and needs  o Explore adaptation measures at farm level  o Consider     •   Current farm practices     •   CC impact i...
Methods: modeling framework                                   CAPRI              4                1                       ...
Application: study areao Study area = Flevoland (the Netherlands)o Mainly, modern arable and dairy systemso Data from 85 i...
Application: yield changes   o A1W2050 : Climate change   o A1W2050+: Climate change + technological development          ...
Application: extremes and adaptation measures Extreme events: o Dry conditions in spring and summer o Prolonged wet condit...
Results: Inputs% change from current situation       Without tech. change       With tech. change
Results: Outputs                                                          % change from current situation                 ...
Results: diffusion of adaptation strategies
Discussion and Conclusions o Prices and expected yield changes (because of increased CO2   concentration and earlier sowin...
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Assessing the adaptation of arable farmers to climate change using DEA and bio-economic modeling. Argyris Kanellopoulos

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Presentation from the WCCA 2011 conference in Brisbane, Australia.

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Assessing the adaptation of arable farmers to climate change using DEA and bio-economic modeling. Argyris Kanellopoulos

  1. 1. Assessing the adaptation of arable farmers to climate change using DEA and bio-economic modeling Argyris Kanellopoulos, Joost Wolf, Maryia Mandryk, Pytrik Reidsma, Ben Schaap and Martin Van Ittersum Plant Production Systems, Wageningen University, P.O. Box 430, 6700 AK Wageningen, The Netherlands* Corresponding author : Argyris Kanellopoulos (argyris.kanellopoulos@wur.nl)
  2. 2. Aims and needs o Explore adaptation measures at farm level o Consider • Current farm practices • CC impact in context of changes in technology, markets • Extreme events in addition to gradual change • Price volatility • Variation among individual farms • Investment decisions
  3. 3. Methods: modeling framework CAPRI 4 1 3 7 Base FSSIM Scenarios DEA FSSIM year1. Outputs = (inputs) 5 62. PMP calibration 23. Non linear cost function WOFOST ACC4. Expected price changes5. Yield changes6. Extreme events & adaptation7. Economic , environmental indicators
  4. 4. Application: study areao Study area = Flevoland (the Netherlands)o Mainly, modern arable and dairy systemso Data from 85 individual arable farms (FADN 2001-2006)o Assess adaptation of arable farmers in a globalized economy with strong temperature rise scenario (A1W) towards 2050
  5. 5. Application: yield changes o A1W2050 : Climate change o A1W2050+: Climate change + technological development Based on WOFOST
  6. 6. Application: extremes and adaptation measures Extreme events: o Dry conditions in spring and summer o Prolonged wet conditions in spring Based on ACC
  7. 7. Results: Inputs% change from current situation Without tech. change With tech. change
  8. 8. Results: Outputs % change from current situation Without tech. change With tech. change (tons) (tons) (tons) (tons) (€) (€) (€) (€)
  9. 9. Results: diffusion of adaptation strategies
  10. 10. Discussion and Conclusions o Prices and expected yield changes (because of increased CO2 concentration and earlier sowing dates) are the most important driving factors o Extreme events pose risks but have relatively low effect on average yields and input levels o Existence of Improved varieties compete adoption of other adaptation strategies o Adaptation measures are more likely to be adopted by large farmers (capital availability) o In general, farmers in Flevoland are currently technically efficient.

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