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Agriculture

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Abstract

Agriculture is highly exposed to climate change. The severity of impacts on agricultural systems usually varies by geographic, natural, and socioeconomic factors. We match results from a bio-physical process model with the climate change scenario of the COIN (Cost of Inaction) project to derive climate induced yield impacts on major crops and permanent grassland in Austria. An economic calculation is applied to estimate average annual changes of production values and costs for the periods 2016–2045 and 2036–2065. Results feed into a computable general equilibrium (CGE) model to assess economy-wide effects. Uncertainties are addressed in the study and are mainly due to high spatial and sectoral aggregation as well as the unknown autonomous adaptation behaviour of farmers. Our analysis indicates moderately higher outputs and value added at the sector level. This results in a positive impact on the rest of the Austrian economy. The aggregated results conceal adverse regional and farm type specific impacts.

Keywords

  • Gross Domestic Product
  • Climate Change Impact
  • Climate Change Scenario
  • Base Period
  • Baseline Scenario

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Fig. 8.1
Fig. 8.2

Notes

  1. 1.

    Both projects have been funded by the Austrian Climate Research Programme (ACRP).

  2. 2.

    More details on the ‘Sensitivity of Austrian agricultural regions to climatic factors’ are provided in the Supplementary Material to this chapter.

  3. 3.

    A detailed account of recent years with exceptional climate conditions is presented in the Supplementary Material ‘Bio-physical impacts up to now’.

  4. 4.

    Alpine meadows and pastures are not considered due to data and model restrictions.

  5. 5.

    A detailed description of the climate change data and the matching procedure is provided in the Supplementary Material ‘Climate change data for agriculture’.

  6. 6.

    The validation procedure and results are discussed in the Supplementary Material ‘Validation of the bio-physical process model EPIC’.

  7. 7.

    In the CGE model, the period 2016–2045 is represented by the year 2030 and the period 2036–2065 is represented by the year 2050.

  8. 8.

    In the CGE model, all impacts are considered in relative terms (in % relative to the base year) because the economic gross margin calculation and the CGE model use different databases.

  9. 9.

    Note that change rates of mean annual crop and grassland forage yields refer to periods of 30 years and do not refer to annual changes.

  10. 10.

    More detailed results are presented in the Supplementary Material ‘Results of statistical meta-models of yield responses’.

  11. 11.

    Gross output value is the sum of sectoral intermediate demand and gross value added. Summing up gross value added across sectors and correcting for indirect taxes gives Gross Domestic Product (GDP).

  12. 12.

    More detailed results are presented in the Supplementary Material ‘Additional macroeconomic effects: GDP, welfare, and public budgets’.

  13. 13.

    A more detailed discussion is presented in the Supplementary Material ‘Sector-specific uncertainties’.

  14. 14.

    See e.g. Special Issue of Agricultural Economics, Volume 45, Issue 1, January 2014.

  15. 15.

    More details on the ‘Bio-physical impacts up to now’ are provided in the Supplementary Material.

  16. 16.

    More details on the ensembles of 31 climate models are presented in Chap. 5.

  17. 17.

    More details on the ‘likelihood’ of such drought scenarios are provided in the Supplementary Material of Chap. 5.

  18. 18.

    Note that changes in crop yields and agricultural production value cannot be directly compared to the results in Sect. 8.3.2.3 in the main text due to differences in data inputs.

  19. 19.

    Note that crop and temporary grassland forage yield changes are calculated for three climate regions whereas permanent grassland forage yield changes are calculated at the national level.

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Acknowledgements

This research has been supported by the research project COIN—Cost of Inaction funded by the Austrian Climate and Energy Fund within the Austrian Climate Research Programme as well as by the Doctoral School of Sustainable Development (dokNE) at the University of Natural Resources and Life Sciences, Vienna (Austria). The work on this chapter benefited from scientific input of the JPI-FACCE project MACSUR—Modelling European Agriculture with Climate Change for Food Security (http://www.macsur.eu) and the Federal Ministry of Agriculture, Forestry, Environment and Water Management of Austria (Contract No. 100875). We are especially thankful to the project leaders Karl Steininger and Martin König, to the scientific advisory board established within the project COIN, i.e. Reimund Schwarze, Roger Street, and Paul Watkiss, and to two anonymous reviewers for helpful comments.

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Mitter, H. et al. (2015). Agriculture. In: Steininger, K., König, M., Bednar-Friedl, B., Kranzl, L., Loibl, W., Prettenthaler, F. (eds) Economic Evaluation of Climate Change Impacts. Springer Climate. Springer, Cham. https://doi.org/10.1007/978-3-319-12457-5_8

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