Prioritizing Climate Chance

Investments aimed at improving agricultural adaptation to climate change inevitably favor some crops and regions over others. An analysis of climate risks for crops in 12 food-Secure regions was conducted to identify adaptation priorities, based on statistical crop models and climate projections for 2030 from 20 general circulation models (Gyms). Results indicate South Asia and Southern Africa as two regions that, without sufficient adaptation measures, will likely suffer negative impacts on several crops that are important to large food-insecure human populations. We also find that uncertainties vary widely by crop, and therefore priorities will depend on the risk attitudes of investment institutions. Adaptation is a key factor that will shape the future severity of climate change impacts on food production (2). Although relatively inexpensive changes, such as shifting planting dates or switching to an existing crop variety, may moderate negative impacts, the biggest benefits will likely result from more costly measures, including the development of new crop varieties and expansion of irrigation (2). These adaptations will require substantial invest-mints by farmers, governments, scientists, and development organizations, all of whom face many other demands on their resources. Prioritization of investment needs, such as through the identification of "climate risk hot spots" Oh is therefore a critical issue but has received limited attention to date.components to science magazines for kids be essential to any prioritization approach: (i) selection of a time scale over which impacts are most relevant to investment decisions, (ii) a clear definition of criteria used for prioritization, and (iii) an ability to evaluate these criteria across a suite of crops and regions. Here, we focus on food security impacts by 2nd—a time period most relevant to large agricultural investments, which typically take 15 to 30 years to realize full returns (4, 5). We consider several different criteria for this time scale. First is the importance of the crop to a region's food-insecure human population [hunger importance (HI)]. Second is the median projected impact of climate change on a crop's production by 2030 (indicated by CO), assuming no adaptation. For this analysis, we generate multiple (i.e., IMO) projections of impacts based on different models of climate change and crop response; in order to capture relevant uncertainties. The projections are then ranked, and the average of the 5th and 51st values are used as the median. A third criterion is the fifth percentile of projected impacts by 2030 (where Com indicates the fifth value of the ranked projections), which we use to represent the lower tail, or "worst case," among the projections. Finally, we consider the 95th percentile of projected impacts by 2030 (where C indicates the 95th value of the ranked projections), which we use to represent the upper tail, or "best case," among the projections. We first identified 12 major food-insecure regions. each of which (i) comprise groups of countries with broadly similar diets and agricultural production systems and (ii) contain a notable share of the world's malnourished individuals as estimated by the Food and Agriculture Organization (MO) (Table r; see fig. Si online for details on regions). For each region, we computed the HI value for each crop by multiplying the number of malnourished individuals by the crop's percent contribution to average per-capital calorie consumption [see supporting online material (SOME) Text Si and table Si J. A hunger importance ranking (HIRE) was then generated by ranking the HI values for all crop-by-region combinations. Rice. maize, and wheat contribute roughly half of the coal-rise currently consumed by the world's poor and