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latter, the highland systems in southern Africa are likely to be hotspots. As might be expected, the impacts of the A1F1 world on growing periods tend to be most marked in the more marginal areas (the arid-semiarid systems), although there are indications of other areas where model agreement suggests substantial changes also. In the B1 world (Tables 6 and 7), as would be expected, the severity of the impacts is generally less, compared with the A1F1 world. However, the general trend of marginal areas becoming even more marginal (the arid-semiarid systems) is still apparent here. Impacts on the coastal systems are widespread but moderate rather than severe. The outlook for several areas in southern Africa in the B1 world is still for some substantial impacts in rangeland as well as in highland systems. There are also several countries in eastern and southern Africa where a moderate loss of growing days is projected across many of the systems in the country. Figure 10 shows the spread of arid-semiarid mixed systems (MRA) and arid-semiarid rangeland systems (LGA) for projected changes in LGP of at least 20% to 2050, for the HadCM3 model and the A1 and B1 scenarios. For the positive changes on LGP, these are shown in Table 8. This shows all the countries in which at least 2% of the land area is projected to experience a positive gain in LGP (>5%) to 2050 (the actual percentage of each country’s area is shown in brackets). Also shown are the systems in which these changes mostly occur. Thus for Mozambique, for example, using the ECHam4 GCM, the analysis suggests a positive impact on LGP under both the A1 and the B1 scenarios; these occur mostly in the LGA and MRA systems, in 14% of the country in an A1 world and 12% of the country in a B1 world. Such changes are not projected using the HadCM3 GCM. 46
Figure 10. Areas within the LGA and MRA systems projected to undergo >20% reduction in LGP to 2050: HadCM3, A1 (left), B1 (right) 47
Page 1: Mapping climate vulnerability and p
Page 4 and 5: Citation Thornton PK, Jones PG, Owi
Page 6 and 7: egion of eastern Africa, the coasta
Page 8 and 9: Contents Executive summary 3 1 Back
Page 10 and 11: Tables Table 1. AOGCMs in the TYN S
Page 12 and 13: • Research to reduce uncertainty,
Page 14 and 15: 2 Project objectives and activities
Page 16 and 17: 3 Framework for the study The liter
Page 18 and 19: Figure 1. Representation of vulnera
Page 20 and 21: Conceptually, there is still a cons
Page 22 and 23: 4. Climate impacts in sub-Saharan A
Page 24 and 25: Table 1. AOGCMs in the TYN SC 2.0 d
Page 26 and 27: We then prepared similar climate gr
Page 28 and 29: Mapping changes to the probability
Page 30 and 31: confidence in the ability of that G
Page 32 and 33: Figure 5. Length of growing period
Page 34 and 35: Figure 6. Coefficient of variation
Page 36 and 37: Figure 7 (B). Percentage changes in
Page 38 and 39: Figure 7 (D). Percentage changes in
Page 40 and 41: Figure 8 (B). Percentage changes in
Page 42 and 43: • For human population, we now us
Page 44 and 45: Figure 9. Farming/livelihood system
Page 46 and 47: Table 4. Country-by-system breakdow
Page 50 and 51: Table 6. Country-by-system breakdow
Page 52 and 53: Table 8. Positive LGP changes to 20
Page 54 and 55: Figure11. Number of growing seasons
Page 56 and 57: 4.3 Uncertainties in the analysis T
Page 58 and 59: 5. Poverty and vulnerability The se
Page 60 and 61: Table 9. Vulnerability indicators u
Page 62 and 63: datasets (more information on this
Page 64 and 65: political process, civil liberties
Page 66 and 67: the major development issue facing
Page 68 and 69: scenarios. For this synthesis, the
Page 70 and 71: Table 11. Rotated component (or “
Page 72 and 73: Table 12. Synthesis of possible reg
Page 74 and 75: climate change-vulnerability hotspo
Page 76 and 77: contain components that draw far mo
Page 78 and 79: 6.1 A survey of information needs o
Page 80 and 81: unit; the International Red Cross;
Page 82 and 83: predominantly in southern Africa. I
Page 84 and 85: Table 13. Institutional preparednes
Page 86 and 87: particularly so for government and
Page 88 and 89: 6.2 Prospects for a decision suppor
Page 90 and 91: Figure 14. Stages of impact assessm
Page 92 and 93: An ex ante impact assessment might
Page 94 and 95: A second issue relates to the setti
Page 96 and 97: A second key point that these resul
Page 98 and 99:
References AchutaRao K, Covey C, Do
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Food and Agriculture Organisation o
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JRL (2005). GLC 2000 (Global Land C
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Roeckner E, Oberhuber J M, Bacher A
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Acronyms ACTS ASARECA CGIAR DFID EN
Page 108 and 109:
Appendix 2. Candidate vulnerability
Page 110 and 111:
Appendix 3. Country by system CV of
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Appendix 4 List of contacted instit
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112 Note 1. Indicators of Adaptive
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Box 1: Source: IPCC, 2001 1. Adapti
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irrigation and quality of infrastru
Page 120 and 121:
Irrigation rate is measured by net
Page 122 and 123:
moisture, especially in southern, N
Page 124 and 125:
Bryman, A and D. Cramer . 1997. Qua
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Note 2. South-South Cooperation (pr
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• Effective policy frameworks in
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vulnerable countries in 12 selected
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130 Note 3. Climate Change and Heal
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impacts (developing nations). These
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most relevant for the case of HIV/A
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emerging infectious diseases; use o
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Within the Sub-Saharan region, the
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geographical shifts and yield reduc
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142 Note 4. The climate, developmen
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Figure 2 Percentage of undernourish
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The Africa Environment Outlook desc
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Figure 5 Total affected in hydro-me
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Figure 5 Present and future freshwa
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Turner B L, Kasperson R E, Matson P
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Note 5. The Sub-Saharan Africa Chal
Page 158 and 159:
Several useful lessons were learned
Page 160 and 161:
Note 6. The ASARECA priority settin
Page 162 and 163:
Figure 1. Development domains and a
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Note 7. The SLP’s food-feed impac
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Figure 2. Domains in Kenya with hig
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Note 8. The SAKSS poverty targettin
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168 Note 9. Simulating regional pro
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Applications (ICASA). The results f
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