1. The avoided impacts of climate change on crop production Tom Osborne Thanks to: Simon Gosling, Gillian Fraser, Helen Greatrex, Tim Wheeler, Nigel Arnell

2. Emissions scenarios CO 2 concentration Local change in climate Future crop yields Global warming Regional crop production A1B, and AVOID mitigation scenarios Pattern-scaling based upon GCMs echam5, hadcm3, ipsl, cgcm31,ccsm30 GLAM crop model at 0.5 resolution Maize, soybean, wheat MAGICC @ 2030,2040,2050,… (Yield GLAM x Area observed )

4. Global-GLAM crop model Original GLAM developed by Challinor et al (2004). Process-based crop growth and development with daily timestep. Crops: soybean, maize, wheat. Climate: 0.5 resolution using CRU based climate data. Daily weather generator. Extent: suitable grid cells and sowing date determined by separate algorithm. Varieties: 3 for maize and soybean, 1 for wheat Rain-fed simulation only. No irrigation.

6. 1961-90 baseline: soybean

7. Wheat

8. Business-as-usual impact of climate change by 2050 on wheat production

9. Percentage of 2050 business-as-usual impact avoided with scenario: A1B-2016-5-L

14. CO2 fertilisation alters effectiveness (relative and absolute) of AVOID scenarios

15. Maize

22. Soybean

29. Conclusions Wheat – Effect of mitigation varies regionally – CO 2 fertilisation influences effectiveness of mitigation – Interaction with climate change Maize – Relative effectiveness of scenarios unaffected by GCM or adaptation (as represented here) Soybean – Mitigation effectiveness insensitive to CO2 and adaptation – Positive CC impacts (S Asia) reduced by mitigation

30. Thank you

31. 1961-90 baseline: maize Inter-annual variability Spatial variability

32. 1961-90 baseline: wheat