Your SlideShare is downloading. ×
Sustainability, Environment and Climate Change: Crop Production and Health Impacts - Professor Tim Wheeler, University of Reading
Upcoming SlideShare
Loading in...5
×

Thanks for flagging this SlideShare!

Oops! An error has occurred.

×

Saving this for later?

Get the SlideShare app to save on your phone or tablet. Read anywhere, anytime - even offline.

Text the download link to your phone

Standard text messaging rates apply

Sustainability, Environment and Climate Change: Crop Production and Health Impacts - Professor Tim Wheeler, University of Reading

1,613
views

Published on

Published in: Education, Technology

0 Comments
0 Likes
Statistics
Notes
  • Be the first to comment

  • Be the first to like this

No Downloads
Views
Total Views
1,613
On Slideshare
0
From Embeds
0
Number of Embeds
0
Actions
Shares
0
Downloads
29
Comments
0
Likes
0
Embeds 0
No embeds

Report content
Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
No notes for slide
  • Undernutrition: when the body contains lower than normal amounts of one or more nutrients, i.e. deficiencies in macronutrients and/or micronutrients. ‘Undernutrition encompasses stunting, wasting and deficiencies of essential vitamins and minerals (collectively referred to as micronutrients).’Malnutrition: an abnormal physiological condition caused by deficiencies, excesses or imbalances in energy, protein and/or other nutrients.
  • Some studies are global in extentParry: regression fits to crop model at many sites. Extrapolate to countries. HadCM3 climate changeWBDR: ?Cline: Parry approach AND panel regression. Several climate models. Consensus result.
  • Currently crop simulations are available for a small number of major crops – wheat, maize, soybean, rice and groundnut. Although these crops make up around 85% of the global diet, it still leaves 15% unaccounted for, contributes to the nutritional quality of the diet.
  • Without adaptation, climate model uncertainty affects the magnitude of CC impact.With adaptation, climate model uncertainty affects sign of change.
  • Transcript

    • 1. Sustainability, environment and climate change:crop production and health impacts
      Tim Wheeler, Tom Osborne, Gillian Rose, Walker Institute
      Sari Kovats, Simon Lloyd, LSHTM
      t.r.wheeler@reading.ac.uk
    • 2. Climate variability and change present threats and opportunities to the environment and sustainability of food systems, and hence will affect links between agriculture, nutrition and health
      • How can projections of climate-induced changes in crop production be linked to nutrition?
      • 3. Current methods and their limitations
      • 4. Sources of uncertainty in projections
      • 5. Appropriate levels of complexity
    • Climate to crops to nutrition
      calories
      nutritional contribution to diet
      food safety / contamination
      climate
      energy
      economy
      global agriculture
      crop
      regulation
      water resources
      natural ecosystems
      pollution
      soil
      social systems
    • 6. Climate to crops to malnutrition
      Climate
      Crops (Reading)
      Food (Southampton)
      Health
      (LSHTM)
      Simon Lloyd, LSHTM
    • 7. Climate change
    • 8. Climate change assessments
      climate
      model
      Climate
      Assessment
      crop
      response
      crop
      model
      Crop
      impact
      adaptation
    • 9. Crop responses to climate
    • 10. 10 – 5
      5 – 2.5
      2.5 – 0
      0 – -2.5
      -2.5 – -5
      -5 – -10
      -10 – -20
      Projections of crop impacts
      Potential change in cereal yields (%)
      No data
      Parry et al 2004
      World Bank Development Review 2010
    • 11. 1. Underpinning knowledge
      Research
      - qualitative impacts across the sector
      - broad-scale patterns of crop growing areas
      - responses of plant physiology to climate
      - site-specific impacts on crop productivity
      - short-term climate variability
      - representing uncertainty in impacts
      - combining detailed local impacts with large spatial coverage
      good
      mediocre
      or patchy
      poor
    • 12. 2. Spatial and temporal scale
      global climate model
      regional climate model
      crop data
    • 13. 3. Climate variability
      W. Australia wheat production
    • 14. Limitations (cont ...)
      4. Major crops only (wheat, maize, soyabean, rice)
      5. Productivity focus
      6. Adaptive capacity of cropping systems underestimated
      and more ...
    • 15. Sources of uncertainty
      Climate model uncertainty
      GHG emissions uncertainty
      Crop model uncertainty
      Ensemble of:
      climate model X GHG emissions scenario X crop model
    • 16. Using probabilistic climate forecasts
      Model average
      63 ensemble members
      713 kg ha-1
      Observed
      775 kg ha-1
      Use of DEMETER multi-model ensemble for groundnut yield in Gujarat, 1998 from Challinor et al (2005)
    • 17. Expand modelling system to cover limitations?
      Appropriate level of complexity
    • 18. Climate model uncertainty
      Relative importance of different sources of uncertainty in climate projections of surface air temperature
      Orange is internal variability
      (natural variability, ENSO, NAO,…)
      Green is GHG scenario uncertainty
      Blue is model uncertainty
      (with same forcing)
      from Hawkins and Sutton, 2008
    • 19. Simple correlations between rainfall and yield
      Seasonal rainfall and groundnut yield for all India
      Time trend removed. r2 = 0.52, p < 0.0001 rainfall yield
    • 20. Patterns of seasonal rainfall and yield of groundnut in India
      District level groundnut yields (kg ha-1)
      Mean of 1966 - 1990
      Data source: ICRISAT
      Sub-divisional level seasonal rainfall (JJAS, cm)
      Mean of 1966 - 1990
      Data source: IITM
    • 21. Intermediate complexity crop model
      Challinor et al 2004
      Osborne, 2010
    • 22. Intermediate complexity crop model
    • 23. Adaptation & uncertainty
      A1B, 2050
    • 24. Conclusions
      How can projections of climate-related changes in crop production be linked to nutrition?
      • Link quantitative models. These can only represent a very simple view of food baskets
      • 25. Can explore sources of uncertainty in these projections
      • 26. The challenge for research is to expand the modeling system, whilst using the appropriate level of complexity within the model
    • Thank you
      Contact:
      Tim Wheeler t.r.wheeler@reading.ac.uk