Page 191 - Climate Change and Food Systems

chapter 5: climate change impact on key crops in africa: using crop models and general equilibrium models to bound the predictions
table 11
Change (%) in productivity, Southern Africa, 2010-2050, IMPACT model
Crop
No Climate Change
CSIRO A1B
MIROC A1B
CSIRO B1
MIROC B1
Cassava 26.9
Cotton 155.3
Groundnuts 47.2
Maize 46.3
Millet 243.4
Potatoes 49.4
Rice 119.8
Sorghum 107.0
Soybeans 61.6
Sugar cane 60.2
27.9
165.3
51.6
48.6
243.1
53.1
109.7
108.7
48.9
62.3
42.0
175.1
51.6
53.3
255.6
53.4
115.2
109.9
58.1
66.5
29.0 39.5
155.6 176.5
50.6 55.4
44.2 52.5
247.5 248.5
53.7 52.4
114.1 102.6
107.8 108.7
47.7 64.3
63.2 66.5
Source: Based on analysis conducted for Nelson et al. (2010) Note: Values are for the baseline economic-demographic scenario
Comparing the no climate change scenario
to the average productivity changes of the four climate models, it appears that climate change
will be beneficial, on average, to cassava, cotton, groundnuts, maize, millet, potatoes, sorghum, and sugar cane, but will be detrimental, on average, to rice and soybeans. In the East African case study model, higher prices resulting from the projected negative impact of climate change on yields stimulates increased use of fertilizer, which then leads to higher yields.
For most of the crops shown in Table 11, yields are higher under the MIROC climate model than under the CSIRO climate model. Since this was
not always the case – as in Table 7, which shows
the results of the crop models – it may be that this phenomenon is the result of global impacts of climate change on prices. We see from the price changes shown in Table 9 that global prices tend to be higher in the MIROC model than in the CSIRO model.
Table 12 shows the same type of results as
in Tables 10 and 11, with a focus on West Africa. The B1 scenario (a lower GHG emissions scenario) generally predicts much higher yields than results based on the A1B scenarios (Table 12). As is often the case, the yields in the A1B scenario are lower
than the no climate change scenario, while the yields in the B1 scenario are higher than the no climate change scenario. This is seen for cassava, cotton, groundnuts, soybeans, and sweet potatoes and yams.
In some cases, we also note the price-stimulus effect, reflected in the MIROC yields being higher than CSIRO yields (with the exception of soybeans).
4.4 Malnutrition
Table 13 shows calculations from the IMPACT model for the number of malnourished children under five years of age, and their share in all children under five years of age. In all regions, the number and share of children who are malnourished will be higher with climate change than without climate change.
Both the number and share of malnourished children should fall in each region between 2010 and 2050. This appears to be primarily an income effect, with increased incomes enabling people to more than compensate for food price increases. However, despite the drop in malnutrition rates through time, the projected malnutrition shares
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