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Source: Long et al. (2006, Science, Vol. 312, 1918-1921)

Slides for GGR 314, Global Warming Chapter 5: Agricultural Impacts Course taught by Danny Harvey Department of Geography University of Toronto.

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Source: Long et al. (2006, Science, Vol. 312, 1918-1921)

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  1. Slides for GGR 314,Global WarmingChapter 5: Agricultural ImpactsCourse taught byDanny HarveyDepartment of GeographyUniversity of Toronto

  2. Exhibit 5-1: A FACE plot for soybeans (left) and an infrared image (right) showing the higher leaf temperature in the plot, which has been exposed to higher CO2 concentration (550 ppmv, vs 380 ppmv ambient) Source: Long et al. (2006, Science, Vol. 312, 1918-1921)

  3. Exhibit 5-2: Plant stomata, through which CO2 enters and water vapour escapes. Source: left, http://www.bing.com/images/search?q=stomata&view=detail&id=F8C46AC057692AF7CD26BB8EE4BFAA273478D8D3&first=0 right, Wikipedia, article on stomata

  4. Exhibit 5-3: Impact on rate of photosynthesis of leaf temperature and atmospheric CO2 concentration for typical C3 (left) and C4 (right) plants. Source: Sage and Pearcy (2000, Adv. Photosyn. Resp., Vol. 9., 497)

  5. Exhibit 5-4:Comparison of the increase in crop yield from experiments in greenhouses (circles and solid lines) at various CO2 concentrations, with FACE results at 550 ppmv (squares with error bars). Each circular datapoint represents the results of many individual experiments, divided into 1000 ppmv CO2 increments. Left: soybeans and wheat (two C3 crops). Right: maize and sorghum combined (two C4 crops). Source: Long et al. (2006, Science, Vol. 312, 1918-1921)

  6. Exhibit 5-5: Impact of temperature changes (combined with favourable precipitation changes) on rice and corn yields in tropical regions (top) and on corn and wheat yields in temperate regions (bottom). Source: Easterling and Apps (2005, Climatic Change, Vol 70, 165-189)

  7. Exhibit 5-6: Trend in grain yield averaged over various regions Source: Hazell and Wood (2008, Phil. Trans. Royal Soc. B, 363, pp495–515)

  8. Exhibit 5-7: Land areas (Gha, billions of hectares) and phytomass flows (EJ/yr) in the world agricultural system Source: Wirsenius (2003, J. Ind Ecol., Vol. 7, 47-80)

  9. Exhibit 5-8: Trends in absolute and per capita world meat consumption Source: Harvey (2010, Energy and the New Reality, Vol 1., Earthscan)

  10. Exhibit 5-9:Estimated impact of changes in climate trends from 1980-2008 on yields of major crops in major regions. In most regions, the decreases due to climatic trends are superimposed on large increases due improved agricultural technology and techniques. The grey bars show the most likely changes and the horizontal lines indicate the uncertainty of the estimate (i.e., the true changes are thought to lie anywhere within the changes spanned by the lines) Source: Lobell et al. (2011, Science, Vol. 333, 616-620)

  11. Exhibit 5-10: Linear trend in growing season temperatures (divided by the interannual standard deviations) at grid cells with at least 1% coverage by maize, wheat, rice, or soybeans. Source: Lobell et al. (2011, Science, Vol. 333, 616-620)

  12. Exhibit 5-11: Linear trend in growing season precipitation (divided by the interannual standard deviations) at grid cells with at least 1% coverage by maize, wheat, rice, or soybeans. Source: Lobell et al. (2011, Science, Vol. 333, 616-620)

  13. Exhibit 5-12: Relationship between temperature and corn yield in the US. The top part of the figure shows the impact on the log of yield when the corn is exposed to 24 hours of the various temperatures shown on the horizontal scale. The data with uncertainties are shown in grey, while the various solid lines represent different ways of approximating the data. The lower part of the figure shows the number of days during the growing season (averaged over all counties) in which corn in the US is exposed to the various temperatures. Source: Schlenker and Roberts (2009, Proc. Nat. Acad. Sci., Vol. 106, 15594-15598)

  14. Exhibit 5-13: Same as previous exhibit, except for soybeans and cotton Source: Schlenker and Roberts (2009, Proc. Nat. Acad. Sci., Vol. 106, 15594-15598)

  15. Exhibit 5-14: Changes in US crop yields by 2020-2049 compared to 1960-1989 for 4 different radiative forcing scenarios (B1, B2, A2 and A1, shown in Exhibit 2-19), computed by adding the changes in monthly mean temperature as simulated by the Hadley Centre AOGCM to the distributions of daily temperatures shown in the previous slides (thus, it is assumed that there is no change in the shape of the temperature frequency distribution – all temperatures during a given month in the growing season are shifted by the same amount). Effects of changes in precipitation are also included, but not adaptations or the possible beneficial direct effects of higher CO2 concentration. Source: Schlenker and Roberts (2009, Proc. Nat. Acad. Sci., Vol. 106, 15594-15598)

  16. Exhibit 5-15: Same as in Exhibit 5-14, except that changes by 2070-2099 are shown. Source: Schlenker and Roberts (2009, Proc. Nat. Acad. Sci., Vol. 106, 15594-15598)

  17. Exhibit 5-16: Average change in the number of months with drought in the US over the 30-year period 2036-2065 compared to 1961-1990 based on changes in precipitation only as simulated by 22 different AOGCMs. Strzepek et al (2010, ERL)

  18. Exhibit 5-17: Same as previous Figure, but taking into account warmer temperatures along with changes in precipitation Strzepek et al (2010, ERL)

  19. Exhibit 5-18: Future return periods for droughts that currently occur only once every 100 years Source: IPCC AR4 WG2, Chapter 3, Fig. 3.6)

  20. Exhibit 5-19: Projected impacts by mid-century of global warming on African staple crops. Source: Schlenker and Lobell (2010, ERL)

  21. Exhibit 5-20: 5th, 50th, and 95th percentiles of the expected impacts of global warming on agricultural production in sub-Saharan Africa by mid-century. Source: Schlenker and Lobell (2010, ERL)

  22. Exhibit 5-21: Current water stress in Russia as indicated by the ratio of water withdrawal (in 1995) to the availability of water averaged of the period 1961-1990. The key food-producing region is the region of greatest water stress. Source: Alcamo et al (2007, Glob. Env. Change, Vol 17, 429-444)

  23. Exhibit 5-22: Change in the availability of water between the current climate and the 2070s as simulated by the Hadley Centre AOGCM. Source: Alcamo et al (2007, Glob. Env. Change, Vol 17, 429-444)

  24. Exhibit 5-23: Same as previous, but using the changes in climate as simulated by the ECHAM (German) AOGCM Source: Alcamo et al (2007, Glob. Env. Change, Vol 17, 429-444)

  25. Exhibit 5-24: Impacts on grain production in China in 2020 and 2040 of (i) an optimistic projection of climatic change alone, (ii) climatic change + optimistic CO2 fertilization effects, (iii) climatic change + reduced availability of water (due to increases in urban and industrial demand for water), (iv) climatic change+CO2+reduced water availability, (v) climatic change, reduced water availability + loss of land due to urbanization, and (vi) everything in (v) + CO2 fertilization. Source: Wei et al (2009, Glob. Env. Change, Vol. 19, 34-44)

  26. Exhibit 5-25: Estimate of the impact on crop production (left) and international prices (right) of the 2030 climate compared to the 1990 climate. Worst case: high climatic change, high crop sensitivity, and low CO2 fertilization benefits. Best case: low climatic change and crop sensitivity, maximal CO2 fertilization benefits. Source: Hertel et al. (2010, Glob. Env. Change 20, 577-585)

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