TURN DO WN THE H E AT: C L IM AT E E X T RE ME S , R EGION A L IMPA C TS, A N D TH E C A SE FOR R ESILIENCE
households are particularly vulnerable to food price increases. Hertel, Burke, and Lobell (2010) show that, by 2030, poverty implications because of food price rises in response to productivity shocks have the strongest adverse effects on non-agricultural, self-employed households and urban households, with poverty increases by up to one third in Malawi, Uganda, and Zambia. On the contrary, in some exporting regions (for example, Australia, New Zealand, and Brazil) aggregate trade gains would outweigh the negative effect of direct crop losses. Overall, Hertel et al. (2010) expect global trade to shrink, which leads to an overall efficiency loss and climate change impacts on crop production are projected to decrease global welfare by $123 billion, which would be the equivalent of approximately 18 percent of the global crops sector GDP. In contrast to other regions assessed in this study, no poverty reduction for any stratum of society is projected in most countries in Sub-Saharan Africa when assuming a low or medium agricultural productivity scenario. Similarly, in a scenario approaching 3.5°C above pre-industrial levels by the end of the century, Ahmed, Diffenbaugh, and Hertel (2009) project that urban wage-labor-dependent populations across the developing world may be most affected by once-in-30year climate extremes, with an average increase of 30 percent in poverty compared to the base period. This study finds that the poverty rate for this group in Malawi, for example, is estimated to as much as double following a once-in-30-year climate event, compared to an average increase in poverty of 9.2 percent among
rural agricultural households. The work by Thurlow, Zhu, and Diao (2012) is consistent with this claim that urban food security is highly sensitive to climatic factors; it indicates that two-fifths of additional poverty caused by climate variability is in urban areas. Of a sample of 16 countries across Latin America, Asia, and Africa examined in a study by Ahmed et al. (2009), the largest “poverty responses” to climate shocks were observed in Africa. Zambia’s national poverty rate, for example, was found to have increased by 7.5 percent over 1991–92, classified as a severe drought year, and 2.4 percent over 2006–07, classified as a severe flood year (Thurlow et al. 2012). (See Box 3.3).
Livestock Climate change is expected to have impacts on livestock production in Sub-Saharan Africa, which would have implications for the many households that are involved in some way in the livestock industry across the Sub-Saharan African region (see Figure 3.17). These households can rely on livestock for food (such as meat and milk and other dairy products), animal products (such as leather), income, or insurance against crop failure (Seo and Mendelsohn 2007). In Botswana, pastoral agriculture represents the chief source of livelihood for over 40 percent of the nation’s residents, with cattle representing an important source of status and well-being for the vast majority of Kalahari residents (Dougill, Fraser, and Mark 2010).
Box 3.3: Agricultural Production Declines and GDP Several historical case studies have identified a connection between rainfall extremes and reduced GDP because of reduced agricultural yields. Kenya suffered annual damages of 10–16 percent of GDP because of flooding associated with the El Niño in 1997–98 and the La Niña drought 1998–2000. About 88 percent of flood losses were incurred in the transport sector and 84 percent of drought losses in hydropower and industrial production (World Bank 2004, cited in Brown 2011). Barrios et al. (2008) provide evidence that both rainfall and temperature have significantly contributed to poor economic growth in Africa. Dell, Jones, and Olken (2012) show that historical temperature increases have had substantial negative effects on agricultural value added in developing countries. The authors find that a 1°C higher temperature in developing countries is associated with 2.66-percent lower growth in agricultural output. For developed countries, the temperature effect is substantially smaller and not statistically significant (0.22 percent lower growth in agricultural output for each additional 1°C of temperature). These results support Jones and Olken (2010), who also found that 1°C higher temperature in developing countries negatively affects agricultural production. Dell and Jones (2012) in turn estimate that, in poor countries, each degree of warming can reduce economic growth by an average of 1.3 percentage points (Dell and Jones 2012) and export growth by 2.0–5.6 percentage points (Jones and Olken 2010). Dell and Jones (2012) expect that (at least in one scenario studied) this temperature effect may be particularly pronounced in Sub-Saharan Africa. While climate change poses a long-term risk to crop production and ecosystem services, Brown, Meeks, Hunu, and Yu (2011) present evidence that high levels of hydroclimatic variability, especially where it leads to drought, tends to have the most significant influence, with increasing poverty counts strongly associated (99 percent) with severe drought. Based on regression analysis and an index of rainfall extremes and taking into account GDP growth and agricultural production, Brown et al. (2011) find a significant and negative correlation between drought and GDP growth per capita: a 1-percent increase in the area of a Sub-Saharan African country experiencing moderate drought correlates with a 2–4 percent decrease in GDP growth. Agricultural value added (meaning the percentage of GDP from agriculture, including forestry, fishing, and hunting) and poverty headcount at $1/day were also observed to be significantly and negatively affected. This is consistent with evidence at the household scale.
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