IPCC Fourth Assessment Report: Climate Change 2007
Climate Change 2007: Working Group II: Impacts, Adaptation and Vulnerability

5.6.5 Food security and vulnerability

All four dimensions of food security, namely food availability (i.e., production and trade), stability of food supplies, access to food, and food utilisation (FAO, 2003a) will likely be affected by climate change. Importantly, food security will depend not only on climate and socio-economic impacts, but also, and critically so, on changes to trade flows, stocks and food-aid policy. Climate change impacts on food production (food availability) will be mixed and vary regionally (FAO, 2003b, 2005c). For instance, a reduction in the production potential of tropical developing countries, many of which have poor land and water resources, and are already faced with serious food insecurity, may add to the burden of these countries (e.g., Hitz and Smith, 2004; Fischer et al., 2005a; Parry et al., 2005). Globally, the potential for food production is projected to increase with increases in local average temperature over a range of 1 to 3°C, but above this it is projected to decrease. Changes in the patterns of extreme events, such as increased frequency and intensity of droughts and flooding, will affect the stability of, as well as access to, food supplies. Food insecurity and loss of livelihood would be further exacerbated by the loss of cultivated land and nursery areas for fisheries through inundation and coastal erosion in low-lying areas (FAO, 2003c).

Climate change may also affect food utilisation, notably through additional health consequences (see Chapter 8). For example, populations in water-scarce regions are likely to face decreased water availability, particularly in the sub-tropics, with implications for food processing and consumption; in coastal areas, the risk of flooding of human settlements may increase, from both sea level rise and increased heavy precipitation. This is likely to result in an increase in the number of people exposed to vector-borne (e.g., malaria) and water-borne (e.g., cholera) diseases, thus lowering their capacity to utilise food effectively.

A number of studies have quantified the impacts of climate change on food security at regional and global scales (e.g., Fischer et al., 2002b, 2005b; Parry et al., 2004, 2005; Tubiello and Fischer, 2006). These projections are based on complex modelling frameworks that integrate the outputs of GCMs, agro-ecological zone data and/or dynamic crop models, and socio-economic models. In these systems, impacts of climate change on agronomic production potentials are first computed; then consequences for food supply, demand and consumption at regional to global levels are computed, taking into account different socio-economic futures (typically SRES scenarios). A number of limitations, however, make these model projections highly uncertain. First, these estimates are limited to the impacts of climate change mainly on food availability; they do not cover potential changes in the stability of food supplies, for instance, in the face of changes to climate and/or socio-economic variability. Second, projections are based on a limited number of crop models, and only one economic model (see legend in Table 5.6), the latter lacking sufficient evaluation against observations, and thus in need of further improvements.

Table 5.6. The impacts of climate change and socio-economic development paths on the number of people at risk of hunger in developing countries (data from Parry et al., 2004; Tubiello et al., 2007b). The first set of rows in the table depicts reference projections under SRES scenarios and no climate change. The second set (CC) includes climate change impacts, based on Hadley HadCM3 model output, including positive effects of elevated CO2 on crops. The third (CC, no CO2) includes climate change, but assumes no effects of elevated CO2. Projections from 2020 to 2080 are given for two crop-modelling systems: on the left, AEZ (Fischer et al., 2005b); on the right, DSSAT (Parry et al., 2004), each coupled to the same economic and food trade model, BLS (Fischer et al., 2002a, 2005b). The models are calibrated to give 824 million undernourished in 2000, according to FAO data.

 2020 2050 2080 
 Millions at risk Millions at risk Millions at risk 
A1 663 663 208 208 108 108 
A2 782 782 721 721 768 769 
B1 749 749 239 240 91 90 
B2 630 630 348 348 233 233 
A1 666 687 219 210 136 136 
A2 777 805 730 722 885 742 
B1 739 771 242 242 99 102 
B2 640 660 336 358 244 221 
A1 NA 726 NA 308 NA 370 
A2 794 845 788 933 950 1320 
B1 NA 792 NA 275 NA 125 
B2 652 685 356 415 257 384 

Despite these limitations and uncertainties, a number of fairly robust findings for policy use emerge from these studies. First, climate change is likely to increase the number of people at risk of hunger compared with reference scenarios with no climate change. However, impacts will depend strongly on projected socio-economic developments (Table 5.6). For instance, Fischer et al. (2002a, 2005b) estimate that climate change will increase the number of undernourished people in 2080 by 5-26%, relative to the no climate change case, or by between 5-10 million (SRES B1) and 120-170 million people (SRES A2). The within-SRES ranges are across several GCM climate projections. Using only one GCM scenario, Parry et al. (2004, 2005) estimated small reductions by 2080, i.e., –5% (–10 [B] to –30 [A2] million people), and slight increases of +13-26% (10 [B2] to 30 [A1] million people).

Second, the magnitude of these climate impacts will be small compared with the impacts of socio-economic development (e.g., Tubiello et al., 2007b). With reference to Table 5.6, these studies suggest that economic growth and slowing population growth projected for the 21st century will, globally, significantly reduce the number of people at risk of hunger in 2080 from current levels. Specifically, compared with FAO estimates of 820 million undernourished in developing countries today, Fischer et al. (2002a, 2005b) and Parry et al. (2004, 2005) estimate reductions by more than 75% by 2080, or by about 560-700 million people, thus projecting a global total of 100-240 million undernourished by 2080 (A1, B1 and B2). By contrast, in A2, the number of the hungry may decrease only slightly in 2080, because of larger population projections compared with other SRES scenarios (Fischer et al., 2002a, 2005b; Parry et al., 2004, 2005; Tubiello and Fischer, 2006). These projections also indicate that, with or without climate change, Millennium Development Goals (MDGs) of halving the proportion of people at risk of hunger by 2015 may not be realised until 2020-2030 (Fischer et al., 2005b; Tubiello, 2005).

Third, sub-Saharan Africa is likely to surpass Asia as the most food-insecure region. However, this is largely independent of climate change and is mostly the result of the projected socio-economic developments for the different developing regions. Studies using various SRES scenarios and model analyses indicate that by 2080 sub-Saharan Africa may account for 40-50% of all undernourished people, compared with about 24% today (Fischer et al., 2002a, 2005b; Parry et al., 2004, 2005); some estimates are as high as 70-75% under the A2 and B2 assumptions of slower economic growth (Fischer et al., 2002a; Parry et al., 2004; Tubiello and Fischer, 2006).

Fourth, there is significant uncertainty concerning the effects of elevated CO2 on food security. With reference to Table 5.6, under most future scenarios the assumed strength of CO2 fertilisation would not greatly affect global projections of hunger, particularly when compared with the absolute reductions attributed solely to socio-economic development (Tubiello et al., 2007a,b). For instance, employing one GCM, but assuming no effects of CO2 on crops, Fischer et al. (2002a, 2005b) and Parry et al. (2004, 2005) projected absolute global numbers of undernourished in 2080 in the range of 120-380 million people across SRES scenarios A1, B1 and B2, as opposed to a range of 100-240 million when account is taken of CO2 effects. The exception again in these studies is SRES A2, under which scenario the assumption of no CO2 fertilisation results in a projected range of 950-1,300 million people undernourished in 2080, compared with 740-850 million with climate change and CO2 effects on crops.

Finally, recent research suggests large positive effects of climate mitigation on the agricultural sector, although benefits, in terms of avoided impacts, may be realised only in the second half of this century due to the inertia of global mean temperature and the easing of positive effects of elevated CO2 in the mitigated scenarios (Arnell et al., 2002; Tubiello and Fischer, 2006). Even in the presence of robust global long-term benefits, regional and temporal patterns of winners and losers are highly uncertain and critically dependent on GCM projections (Tubiello and Fischer, 2006).