globalchange  > 气候变化事实与影响
DOI: doi:10.1038/nclimate2181
论文题名:
Agricultural Impacts: Robust uncertainty
作者: Reimund P. Rö; tter
刊名: Nature Climate Change
ISSN: 1758-1364X
EISSN: 1758-7484
出版年: 2014-03-26
卷: Volume:4, 页码:Pages:251;252 (2014)
语种: 英语
英文关键词: Climate-change impacts ; Agriculture
英文摘要:

An up-to-date synthesis of climate change impacts on crop yields shows that the bounds of uncertainty are increasing. So why do estimates of the effect of climate change on crop productivity differ so much?

The challenge of feeding a global population expected to reach 9 to 10 billion by mid-century, while at the same time coping with a changing climate, calls for estimates of how much climate change might affect global food production1. However, attempts to understand and help prepare for the future, such as the assessment of climate change impacts on crop productivity, are inherently uncertain2. In his essay 'On Modern Uncertainty', Bertrand Russell3 emphasized the importance of being aware of the limitations of our knowledge while communicating clearly what we do know, so that informed action can be taken. As they describe in Nature Climate Change, Challinor and colleagues4 follow this advice for crop yields under the impacts of climate change.

Challinor et al. use meta-analysis to summarize climate change impacts on the productivity of three major food crops (wheat, maize and rice) and their adaptation potential as a function of temperature — similar to that reported in the Fourth Assessment Report (AR4) of the Intergovernmental Panel on Climate Change (IPCC)5. The database was extended from 2007 to 2012, more than doubling the number of studies and the number of data points. This is the largest pool of data from diverse modelling studies ever used for a global synthesis of this kind. The work contributes to the food security and food production systems chapter of the Fifth Assessment Report (AR5) of the IPCC, due to be released on 31 March 2014 in Yokohama, Japan.

Although there are similarities between the results of Challinor et al. and those of the earlier AR4 meta-analyses, there are also distinct differences. For example, wheat grown in mid to high latitudes does not only show a positive yield response to local warming (up to 3 °C), as was the case in AR4, but also negative responses. Furthermore, in temperate regions all three crops show a higher risk of yield loss at moderate levels of local warming than was suggested in the earlier AR4 analysis. The considerably larger number of entries used by Challinor and colleagues show a greater spread, or uncertainty range, than AR4 (schematically depicted in Fig. 1) and, without adaptation, significant losses in the aggregate production of wheat, rice and maize are already projected when local warming exceeds 2 °C, both for temperate and tropical regions. This is different from AR4, which suggested such yield loss would occur only when exceeding 3–4 °C local warming.

Figure 1: Schematic illustration of the relationship between total uncertainty, projected ranges of relative yield changes and best fits of aggregate yield changes.
Schematic illustration of the relationship between total uncertainty, projected ranges of relative yield changes and best fits of aggregate yield changes.

The figure refers to model-based results from AR4 (ref. 5) and AR5 (WGII chapter 'Food security and food production systems') and indicatively depicts the main message and novelties of this study4. Figure modified from ref. 6.

  1. Rosenzweig, C. & Parry, M. L. Nature 367, 133138 (1994).
  2. Wheeler, T. & von Braun, J. Science 341, 508513 (2013).
  3. Russell, B. Modern uncertainty. New York American (20 July 1932).
  4. Challinor, A. et al. Nature Clim. Change 4, 287291 (2014).
  5. Easterling, W. E. et al. in IPCC Climate Change 2007: Impacts, Adaptation and Vulnerability (eds Parry, M. L., Canziani, O. F., Palutikof, J. P., van der Linden, P. J. & Hanson, C. E.) 273313 (Cambridge Univ. Press, 2007).
  6. Jones, R. N. Clim. Change 45, 403419 (2000).
  7. Asseng, S. et al. Nature Clim. Change 3, 827832 (2013).
  8. White, J. W. et al. Field Crop. Res. 124, 357368 (2011).
  9. Müller, C. & Robertson, R. D. Agric. Econ. 45, 85101 (2014).
  10. Rosenzweig, C. et al. Agr. Forest Meteorol. 170, 166182 (2013).
  11. http://www.macsur.eu

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Affiliations

  1. Reimund P. Rötter is at MTT Agrifood Research Finland, Lönnrotinkatu 5, FI-50100 Mikkeli, Finland

URL: http://www.nature.com/nclimate/journal/v4/n4/full/nclimate2181.html
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/5185
Appears in Collections:气候变化事实与影响
科学计划与规划
气候变化与战略

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Reimund P. Rö,tter. Agricultural Impacts: Robust uncertainty[J]. Nature Climate Change,2014-03-26,Volume:4:Pages:251;252 (2014).
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