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Cropping frequency and area response to climate variability can exceed yield response

Nature Climate Change volume 6, pages 601–604 (2016)Cite this article

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Abstract

The sensitivity of agricultural output to climate change has often been estimated by modelling crop yields under climate change scenarios or with statistical analysis of the impacts of year-to-year climatic variability on crop yields1,2. However, the area of cropland and the number of crops harvested per growing season (cropping frequency) both also affect agricultural output and both also show sensitivity to climate variability and change3,4,5,6,7,8,9. We model the change in agricultural output associated with the response of crop yield, crop frequency and crop area to year-to-year climate variability in Mato Grosso (MT), Brazil, a key agricultural region. Roughly 70% of the change in agricultural output caused by climate was determined by changes in frequency and/or changes in area. Hot and wet conditions were associated with the largest losses and cool and dry conditions with the largest gains. All frequency and area effects had the same sign as total effects, but this was not always the case for yield effects. A focus on yields alone may therefore bias assessments of the vulnerability of agriculture to climate change. Efforts to reduce climate impacts to agriculture should seek to limit production losses not only from crop yield, but also from changes in cropland area and cropping frequency.

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Figure 1: Changes in Mato Grosso agricultural output from response of crop yield, crop frequency and crop area to interannual climate variability.

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References

  1. Rosenzweig, C. et al. Assessing agricultural risks of climate change in the 21st century in a global gridded crop model intercomparison. Proc. Natl Acad. Sci. USA 111, 3268–3273 (2014).

    Article  CAS  Google Scholar 

  2. Auffhammer, M. & Schlenker, W. Empirical studies on agricultural impacts and adaptation. Energy Econ. 46, 555–561 (2014).

    Article  Google Scholar 

  3. Mondal, P. et al. Winter crop sensitivity to inter-annual climate variability in central India. Climatic Change 126, 61–76 (2014).

    Article  Google Scholar 

  4. Mondal, P., Jain, M., DeFries, R. S., Galford, G. L. & Small, C. Sensitivity of crop cover to climate variability: insights from two Indian agro-ecoregions. J. Environ. Manage. 148, 21–30 (2015).

    Google Scholar 

  5. Seifert, C. A. & Lobell, D. B. Response of double cropping suitability to climate change in the United States. Environ. Res. Lett. 10, 024002 (2015).

    Article  Google Scholar 

  6. Waha, K. et al. Adaptation to climate change through the choice of cropping system and sowing date in sub-Saharan Africa. Glob. Environ. Change 23, 130–143 (2013).

    Article  Google Scholar 

  7. Koide, N. et al. Prediction of rice production in the Philippines using seasonal climate forecasts. J. Appl. Meteorol. Climatol. 52, 552–569 (2013).

    Article  Google Scholar 

  8. Naylor, R. L., Falcon, W. P., Rochberg, D. & Wada, N. Using El Niño/Southern Oscillation climate data to predict rice production in Indonesia. Climatic Change 50, 255–265 (2001).

    Article  Google Scholar 

  9. Sakamoto, T., Van Nguyen, N., Ohno, H., Ishitsuka, N. & Yokozawa, M. Spatio–temporal distribution of rice phenology and cropping systems in the Mekong Delta with special reference to the seasonal water flow of the Mekong and Bassac rivers. Remote Sens. Environ. 100, 1–16 (2006).

    Article  Google Scholar 

  10. Iizumi, T. & Ramankutty, N. How do weather and climate influence cropping area and intensity? Glob. Food Secur. 4, 46–50 (2015).

    Article  Google Scholar 

  11. Schlenker, W. & Roberts, M. J. Nonlinear temperature effects indicate severe damages to US crop yields under climate change. Proc. Natl Acad. Sci. USA 106, 15594–15598 (2009).

    Article  CAS  Google Scholar 

  12. Lobell, D. B., Schlenker, W. & Costa-Roberts, J. Climate trends and global crop production since 1980. Science 333, 616–620 (2011).

    Article  CAS  Google Scholar 

  13. Urban, D. W., Roberts, M. J., Schlenker, W. & Lobell, D. B. The effects of extremely wet planting conditions on maize and soybean yields. Climatic Change 130, 247–260 (2015).

    Article  CAS  Google Scholar 

  14. Ray, D. K., Gerber, J. S., MacDonald, G. K. & West, P. C. Climate variation explains a third of global crop yield variability. Nature Commun. 6, 1–9 (2015).

    Article  Google Scholar 

  15. Iizumi, T. et al. Impacts of El Niño Southern Oscillation on the global yields of major crops. Nature Commun. 5, 3712 (2014).

    Article  CAS  Google Scholar 

  16. Gourdji, S. M., Sibley, A. M. & Lobell, D. B. Global crop exposure to critical high temperatures in the reproductive period: historical trends and future projections. Environ. Res. Lett. 8, 024041 (2013).

    Article  Google Scholar 

  17. Mendelsohn, R., Nordhaus, W. D. & Shaw, D. The impact of global warming on agriculture: a Ricardian analysis. Am. Econ. Rev. 104, 753–771 (1994).

    Google Scholar 

  18. Ray, D. K. & Foley, J. A. Increasing global crop harvest frequency: recent trends and future directions. Environ. Res. Lett. 8, 044041 (2013).

    Article  Google Scholar 

  19. Municipality Agricultural Data Report (PAM) (Brazilian Institute of Geography and Statistics, 2013); http://www.sidra.ibge.gov.br/bda/acervo/acervo2.asp

  20. Spera, S. et al. Recent cropping frequency, expansion, and abandonment in Mato Grosso, Brazil had selective land characteristics. Environ. Res. Lett. 9, 064010 (2014).

    Article  Google Scholar 

  21. Kummerow, C., Barnes, W., Kozu, T., Shiue, J. & Simpson, J. The tropical rainfall measuring mission (TRMM) sensor package. J. Atmos. Ocean. Technol. 15, 809–817 (1998).

    Article  Google Scholar 

  22. Willmott, C. & Matsuura, K. Terrestrial Air Temperature and Precipitation: Monthly and Annual Time Series (1950–1999) Version 1.02 (Center for Climatic Research, Univ. Delaware, 2001).

    Google Scholar 

  23. de Carvalho, J. R. P., Assad, E. D., de Oliveira, A. F. & da Silveira Pinto, H. Annual maximum daily rainfall trends in the Midwest, southeast and southern Brazil in the last 71 years. Weath. Clim. Extremes 5–6, 7–15 (2014).

    Article  Google Scholar 

  24. Girvetz, E. H. et al. Applied climate-change analysis: the climate wizard tool. PLoS ONE 4, e8320 (2009).

    Article  Google Scholar 

  25. Sakurai, G., Iizumi, T. & Yokozawa, M. Varying temporal and spatial effects of climate on maize and soybean affect yield prediction. Clim. Res. 49, 143–154 (2012).

    Article  Google Scholar 

  26. Gusso, A., Ducati, J. R., Veronez, M. R., Sommer, V. & da Silveira, L. G. Jr Monitoring heat waves and their impacts on summer crop development in Southern Brazil. Agric. Sci. 5, 353–364 (2014).

    Google Scholar 

  27. Richards, P., Pellegrina, H., VanWey, L. & Spera, S. Soybean development: the impact of a decade of agricultural change on urban and economic growth in Mato Grosso, Brazil. PLoS ONE 10, e0122510 (2015).

    Article  Google Scholar 

  28. Oliveira, L. J., Costa, M. H., Soares-Filho, B. S. & Coe, M. T. Large-scale expansion of agriculture in Amazonia may be a no-win scenario. Environ. Res. Lett. 8, 024021 (2013).

    Article  Google Scholar 

  29. New, M., Lister, D., Hulme, M. & Makin, I. A high-resolution data set of surface climate over global land areas. Clim. Res. 21, 1–25 (2002).

    Article  Google Scholar 

  30. Kalnay, E. et al. The NCEP/NCAR 40-year reanalysis project. Bull. Am. Meteorol. Soc. 77, 437–471 (1996).

    Article  Google Scholar 

  31. Cohn, A. et al. Replication Data for: Cropping Frequency and Area Response to Climate Variability can Exceed Yield Response (Harvard Dataverse, 2015).

    Google Scholar 

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Acknowledgements

The authors acknowledge support from NASA grant no. NNX11AH91G.

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Authors and Affiliations

  1. Fletcher School at Tufts University, 160 Packard Avenue, Medford, Massachusetts 02155, USA

    Avery S. Cohn

  2. Institute at Brown for Environment and Society, Brown University, Box 1951, 85 Waterman Street, Providence, Rhode Island 02912, USA

    Leah K. VanWey, Stephanie A. Spera & John F. Mustard

  3. Department of Sociology, Brown University, Box 1916, 112 George Street, Providence, Rhode Island 02912, USA

    Leah K. VanWey

  4. Department of Earth, Environmental and Planetary Sciences, Brown University, Box 1846, 324 Brook Street, Providence, Rhode Island 02912, USA

    Stephanie A. Spera & John F. Mustard

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  1. Avery S. Cohn
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  2. Leah K. VanWey
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Contributions

A.S.C., L.K.V. and J.F.M. designed the research; A.S.C. and L.K.V. performed the research; A.S.C., L.K.V. and S.A.S. analysed the data; A.S.C. and L.K.V. wrote the paper.

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Correspondence to Avery S. Cohn.

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The authors declare no competing financial interests.

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Cohn, A., VanWey, L., Spera, S. et al. Cropping frequency and area response to climate variability can exceed yield response. Nature Clim Change 6, 601–604 (2016). https://doi.org/10.1038/nclimate2934

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