Page 185 - Climate Change and Food Systems

Southern Africa
Table 7 shows regional tabulations of productivity changes for various crops based on the crop model results for Southern Africa. Rainfed rice
is generally predicted to be unchanged. Rainfed maize is mostly negatively affected, though moderately so, except in the ECHAM model. ECHAM was the model which predicted the largest temperature increases.
Rainfed wheat shows yield increases because it is grown mostly in colder areas, and a temperature increase under such circumstances could boost productivity (Table 7). Rainfed soybeans and rainfed sorghum both show yield losses, probably as a result of temperature increases stressing these crops in the currently cultivated areas.
West Africa
Table 8 shows the weighted tabulations of productivity change for crops grown in West Africa, based on the crop model analysis. Only rainfed rice shows positive change. Yield reductions for rainfed maize and groundnuts are less than 10 percent, with an average of around 5 percent, and rainfed soybeans show around 6 percent reduction.
Overall, rainfed sorghum shows large yield reductions in all regions of Africa. Irrigated rice and irrigated wheat have large yield reductions, with wheat having larger reductions than rice. Yield productivity losses for irrigated crops are the result of temperature increases.
4. IMPACT model results
The IMPACT model is a global partial equilibrium food and agricultural model. Three different economic-demographic scenarios were examined using the IMPACT model: 1) pessimistic, with high population growth and low GDP per capita growth scenario for the world; 2) optimistic, with low population growth, high income scenario; and 3) baseline, which is between the two.
Yield results from four climate model/ Special Report on Emissions Scenarios (SRES) combinations: CSIRO A1B, CSIRO B1, MIROC
A1B, and MIROC B1 were incorporated. SRES scenarios are IPCC predictions for how the world might evolve in terms of technology, governance and responsiveness to curbing emissions of GHGs. B1 is a lower emission scenario than A1B.
The units in IMPACT are countries, rather than the gridcells used in the crop models. The IMPACT model works by solving global supply and demand equations. One of the important questions that the IMPACT modelling approach attempts to answer is whether the world will produce sufficient food to feed the growing population, which will generally earn greater incomes. The results indicate that it will, but the demand for food will drive food prices higher relative to the price of other goods.
Table 9 shows the price changes projected by the IMPACT model between 2000 and 2050. Of all the food commodities, the world price of maize is projected to have the highest increase, doubling without climate change, and tripling according to one of the climate models. Millet prices will have the most minimal change, rising only 8 percent in three of the five climate scenarios evaluated.
Depending on which scenario is analysed, the maize price increase is followed by sweet potatoes and yams for MIROC A1B and CSIRO B1; sugar cane for MIROC B1; sweet potatoes and maize show the same level of price change under CSIRO A1B. Under no climate change scenario, sorghum top the price increase (Table 9).
4.1 Maize
In most of the graphs presented in this section, the economic-demographic scenarios are represented by three different colours. In each bar on the graph, we include only the results expected with climate change; the X’s indicate the cases in
which we have assumed no climate change. As
in Table 9, the four climate model/SRES scenario combinations are CSIRO A1B, CSIRO B1, MIROC A1B, and MIROC B1.
Important issues to note are: whether there is much variation between climate models (sometimes the bars are very flat, indicating little
chapter 5: climate change impact on key crops in africa: using crop models and general equilibrium models to bound the predictions
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