Page 179 - Climate Change and Food Systems

Figure 6 indicates where rainfed maize is currently cultivated, and where crop model analysis was utilized. The DSSAT crop model was applied to cells containing at least 30 ha of a crop, out
of a total of approximately 8 500 ha per gridcell. Analysis was likewise applied within a few pixels of the gridcells that were selected for analysis by the “30 hectare” rule. Note the areas of no data (<1 ha) where maize is no longer cultivated, which will most likely remain the case in the future.
Figure 7 shows the results of this analysis using crop models combined with climate models. This Figure focuses on the areas of East Africa where maize is mostly grown. Significant regional variations as well as variations between GCMs were observed, as shown in Figure 7. Overall,
the models suggest a slight positive change in production of rainfed maize due to climate change in East Africa, although certain countries will do better than others. Generally, Uganda appears
to be consistently adversely affected in terms of maize production, while the impact in Ethiopia is mostly positive.
figure 6
Rainfed maize areas (ha) for East Africa, 2000
The ECHAM model seems to be the most pessimistic of the four in terms of rainfed maize productivity, with significant yield reduction visible across southern Tanzania and the central parts of Ethiopia.
Understanding and interpreting Crop Model Maps (an application to rainfed maize in East Africa)
By examining the detailed climate productivity change maps, it is possible to identify climate hotspots (areas which are projected to suffer large losses) and climate opportunities (areas which may have large gains or areas that were previously unsuitable but can become suitable for crop production at some point).
Climate hotspots are areas that will become unproductive (shown in red) or have high yield losses (shown in dark orange) as a result of climate change. These only qualify as “hotspots” if they are the main crop in terms of income or consumption for those growing them. One GCM, the CNRM model, concludes that the area in western Kenya is one of those hotspots. Because the other
GCMs are more optimistic about production in that location, the area is considered to be a possible hotspot. But if the CNRM GCM proved, over time, to be accurate, then farmers in that location would be under severe hardship, which would make that particular region of Kenya a legitimate hotspot.
Climate hotspots require special attention, because unless farmers find tools with which to adapt, they will likely become impoverished, possibly inducing climate migration – either to towns and cities, or to areas seen to present climate opportunities.
Climate opportunities are those areas that could come into production (shown in blue) or have significant yield increases (shown in dark green)
as a result of climate change. The models appear to be generally in agreement in the central part
of Kenya, with the appearance of new areas for producing rainfed maize. Climate opportunities are generally the result of one of two possibilities: first, that rainfall has increased in an area where rainfall had been too low to sustain production; or second,
chapter 5: climate change impact on key crops in africa: using crop models and general equilibrium models to bound the predictions
Sources: SPAM (Spatial Production Allocation Model) (You and Wood, 2006; You, Wood, and Wood-Sichra, 2006, 2009)
Note: ha = hectare
<1 ha
<1 to 10 ha
10 to 30 ha
30 to 100 ha 100 to 500 ha 500to3000ha > 3 000 ha
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