1. Shea and Climate
Jon Lovett
University of Leeds

2. Sahara Dust 2005
http://earthobservatory.nasa.gov/NaturalHazards/shownh.php3?img_id=12836

3. February 2000
http://earthobservatory.nasa.gov/Newsroom/NewImages/Images/seawifs_canary_duststorm_large.jpg

4. 30-07-2008 Early season hurricane formation off Dakar
from EUMETSAT http://www.eumetsat.int/Home/index.htm

5. 08-08-2008 Hurricane Alley in full flow
from EUMETSAT http://www.eumetsat.int/Home/index.htm

6. 04-09-2008 Hurricane Ike reaches category 4 coming out of Hurricane Alley
from EUMETSAT http://www.eumetsat.int/Home/index.htm
Ike

7. 09-09-2008 Hurricane Ike over Cuba
from EUMETSAT http://www.eumetsat.int/Home/index.htm

8. 17-09-2008 Hurricane Ike reaches Europe
from EUMETSAT http://www.eumetsat.int/Home/index.htm

9. 23-09-2008 Heavy rain in Spain: 250 l/m2 in two hours in Sueca in eastern Spain.
Meteosat-9 HRV Europe RGB - 17:00 UTC.

10. http://earthobservatory.nasa.gov/Study/Desertification/

11. http://earthobservatory.nasa.gov/Study/Desertification/

12. IPCC ‘Climate Change 2007’
• Frequency of heavy precipitation events has increased
over most land areas - consistent with warming and
increases of atmospheric water vapour
• Drying in the Sahel, the Mediterranean, southern Africa
and parts of southern Asia
• More intense and longer droughts observed since the
1970s, particularly in the tropics and subtropics

13. high
low
Modelled present day African
plant species richness
Assuming species occur at all
climatically suitable places
Sommer et al. Nees Institute for
Biodiversity of Plants, Bonn
Effect of Climate Change
Africa

14. Patterns of African plant
species richness in 2100
Assuming species move into new
habitats and occur at all
climatically suitable places
Sommer et al. Nees Institute for
Biodiversity of Plants, Bonn
Effect of Climate
Change
Africa

15. Shea presence localities
Distribution data from
John Hall (University of
Wales, Bangor); plot
locations from Burkina
Faso, Mali and Ghana;
one record from
TROPICOS
– 241 points in total (216
paradoxa, 25 nilotica)
– 216 locations to nearest
minute, remainder to
nearest degree
INNOVKAR WP2: Shea distribution under climate change Platts, Poudyal, McClean (February 2011)

16. Analysing present day
distribution
• Using generalised additive models (GAMs), the present
day shea distribution was correlated with climate,
topography, agro-ecological zone data and fire radiative
power
• Predictor variables were chosen using two contrasting
stepwise selection procedures: beginning with a null/full
model, variables were added/removed according to
Akaike/Bayesian Information Criterion, respectively
• Platts, Poudyal, McClean INNOVKAR WP2
INNOVKAR WP2: Shea distribution under climate change Platts, Poudyal, McClean (February 2011)

17. INNOVKAR WP2: Shea distribution under climate change Platts, Poudyal, McClean (February 2011)
Shea distribution (present) predicted by a GAM using
climate, topography, soil constraints and fire
intensity
Shea distribution (present) predicted by a GAM using
climate variables only (mean temperature, moisture
index and driest month rainfall)

18. Climate scenarios
INNOVKAR WP2: Shea distribution under climate change Platts, Poudyal, McClean (February 2011)
Summary of temperature changes forecast according to various IPCC SRES emissions scenarios (IPCC,
2007). A1: maximum energy requirements, with emissions differentiated according to fuel sources (A1Fl,
fossil intensive; A1T, technological development of non-fossil sources; A1B, balance across sources). B1:
minimum energy requirements and low emissions. A2: high energy requirements; emissions less than A1Fl.
B2: low energy requirements, but emission greater than B1. Considered here are SRES scenarios A2 and B2.

19. INNOVKAR WP2: Shea distribution under climate change Platts, Poudyal, McClean (February 2011)
Maps showing modelled climatic suitability for shea under current and future climate
scenarios (extrapolating the GAM predictions)

20. INNOVKAR WP2: Shea distribution under climate change Platts, Poudyal, McClean (February 2011)
Plots showing forecast changes in the number of
10 arc-minute grid cells providing climatically
suitable conditions for shea. Viable conditions are
defined by model predictions of at least 0.5
The two SRES scenarios (A2 and B2) returned
similar results for the first half of the 21st century,
but thereafter the A2 scenario (higher emissions)
resulted in a more rapid increase in the amount of
climate-space suitable for shea, particularly within
its current latitudinal range (0°-15°N).

21. Satellite data and high
resolution modelling
studies show that
storms need
heterogeneous soil to
initiate
In particular, afternoon
convection over dry
Sahel regions needs
this variation in ground
surface to initiate.
Convection forms over
gradients in soil
moisture.

22. Air passage over
forested regions
enhances seasonal
rainfall by up to 10 mm
per day

23. Carbon Estimates
• Shea parkland 20-50 MgC/ ha
• 3.7 million km2 Sahel-Savannah wooded
parkland zone
• = 74,000,000,000 tonnes C (@20 MgC/ ha)
• = 271,000,000,000 tonnes CO2
• World CO2 emissions: 33,376,327,000 tonnes
CO2
• Shea parkland C stock equivalent to more than 8
times global CO2 emissions

24. Conclusion
• Sahelian climate unpredictable
• Climate change models predict a drier
Sahel
• Bioclimatic envelope modelling shows
major shifts in vegetation; with Shea range
expanding
• Vegetation affects Sahel rainfall; and
carbon storage/ sequestration can mitigate
climate change