This document summarizes a presentation on assessing household vulnerability to climate change. It outlines methods to identify hotspots where climate impacts and vulnerability intersect. Factors like changes in growing conditions, food systems, and the length of the growing period are analyzed under different climate scenarios to 2030 and 2050. Mapping analyses identify areas with the highest exposure to climate hazards and food insecurity. The presentation also discusses research opportunities to better understand household impacts, incorporate risk and equity issues, and identify appropriate adaptation options.

1. Assessing household level
vulnerability to climate change
M. Herrero, P. K. Thornton, P. Ericksen, M. Rufino, A. Notenbaert
CCAFS Science Meeting
Cancun, Mexico | 1-2 December 2010

2. Outline
– Background
– Some definitions
– Methodology
– Some results
– Future research

3. Systems are changing…
 Population / Urbanization / Incomes / Diets
 Increased competition for natural resources
 Climate change –
 warmer and
 more variable
 Trade / exchange of
knowledge and
products

4. The target is moving!
An example of the changing nature of production systems
W. Africa 1966 – pastoral system 2004 – crop-livestock system

5. ..and then climate change….

6. An example of climate-induced livelihood transitions
20º
Areas where cropping of
an indicator cereal may 0º
become unviable
between now and 2050
and where farmers may
have to rely more on
livestock as a livelihood -20º
strategy
Jones & Thornton (2008)
0º 20º 40º

7. A game of winners and losers…
Simulated percentage maize production changes to 2030 and 2050, by
country and system
Mixed Mixed Mixed
National rainfed rainfed rainfed
Production temperate humid arid
2030 2050 2030 2050 2030 2050 2030 2050
Burundi 9.1 9.1 14.4 18.1 -1.8 -8.8 - -
Kenya 15.0 17.8 33.3 46.5 -4.6 -9.8 -1.1 -8.4
Rwanda 10.8 14.9 13.4 18.8 5.4 3.6 1.1 2.7
Tanzania -3.1 -8.1 7.5 8.7 -1.6 -6.4 -5.1 -11.1
Uganda -2.2 -8.6 4.9 3.1 -4.6 -12.9 -1.1 -6.3
Mean of 4 combinations of GCM and emissions scenario
Winners
Losers
Thornton et al. (2010)

8. There are always trade-offs

9. Monthly calendar of different activities of the system
Wa, Upper West, Ghana
Dry Rainy Dry Weather calendar
Groundnuts
Yams Cropping calendar
Sorghum
Cut & Crop
Critical Grazing Feeding calendar
Carry residue
Energy Prot. & Ene. Family’s nutrition
Food security
deficit deficit
Very
High Low High Low High Low High Cash demands
high
Gonzalez-Estrada et al. 2006

10. ...from vulnerability mapping to assessing
household level impacts...
directly linked to adaptation options

11. Adaptation to climate change: definitions
IPCC (2007)
Initiatives and measures to reduce the vulnerability of natural and
human systems against actual or expected climate change
effects
IPCC (2001)
‘adjustment in ecological, social, or economic systems in response
to actual or expected climatic stimuli and their effects or
impacts’
This implies implementation of:
“processes, practices, or structures to moderate or offset potential
damages or to take advantage of opportunities associated
with changes in climate”

12. Adaptation options will depend
largely on the how we shape the
world
• Several options exist though largely dependent on our
vision of world development and how it plays out in
different regions
• Lots of scenarios and uncertainty!
• Different paradigms of agricultural development
(industrial vs pro-poor smallholders, large vs family
farms)
• Globalisation and trade patterns
• Consumption patterns
• Carbon constraints
• Roles and incentives for technology adoption
• Growth in other sectors
• Power relationships

13. Mapping Climate Vulnerability and Poverty in Africa
Many people who have
contributed least to climate
change may suffer the
greatest livelihood
consequences
ILRI with the African
Centre for Technology
Studies (ACTS) and The
Energy Resources Institute
(TERI)
Thornton et al 2006

14. Climate Change Risk / Impact Vulnerability
Different Biophysical Social
scenarios of vulnerability vulnerability
the future
14 indicators
Changes in
growing
conditions to Data reduction analysis
2050  4 factors, combined
into one “overall”
vulnerability indicator
Hot-spots
Hot-spots
Hot-spots of climate risk
AND vulnerability

15. Assessing climate change
Used the length of growing period as a proxy for
agricultural impacts
• Calculate the water balance via available soil water,
runoff, water deficiency (assume a soil water holding
capacity of 100 mm)
• Count the number of days per year when the ratio
of actual to potential evapo-transpiration ratio (Ea/Et)
> 0.5 and Tav > 9 °C

16. Where are the impacts?
Assess the impact of
climate change on agro-
ecological characteristics
by looking at changes in
the length of growing
period (LGP)
Days
Data adapted from
Thornton et al., 2006

17. Where are the impacts?
Data adapted from Thornton et al., 2006 % change in LGP

18. What systems are mostly
affected?
Livestock based systems
Mixed irrigated systems
Mixed rainfed systems
Data adapted from
Thornton et al., 2006

19. 14 vulnerability indicators used in ILRI study
Data at different scales: country, province, 18 km2
Physical capital
• Market access (ILRI)
Social capital
Natural capital
• Human poverty index (HDR)
• Crop suitability (FAO, GLC2000) • Governance (World Bank)
• Soil degradation (GLASOD)
• Water availability (FAO Water Atlas)
Human capital
Financial capital • Stunting (FAO, CIESIN)
• Infant mortality (CIESIN)
• Agriculture as % of GDP (World Bank) • Wasting (CIESIN)
• Imports vs Exports (World Bank) • Public health expenditure (HDR)
• Malaria risk (MARA)
• HIV/AIDS prevalence (HDR)

20. Areas within the LGA (arid-semiarid livestock) and MRA (arid-semiarid mixed)
systems projected to undergo >20% reduction in LGP to 2050: HadCM3
(Thornton et al 2006)
A1 B1

21. Quartiles of the overall vulnerability indicator
Mapped at systems level within each country. Quartile 1, “less vulnerable”; quartile 4, “more vulnerable”
Thornton et al 2006

22. Synthesis of hot-spots
MRA, mixed rainfed arid-semairid systems LGA, rangeland arid-semiarid systems
Highest vulnerability Second-highest vulnerability
quartile (4) quartile (3)
Possibly • Some MRA systems in • MRA, LGA systems in large parts of
severe LGP Sahel Sahel
loss (>20% to • Mixed rainfed and highland • Livestock systems and some mixed
2050) perennial systems in Great systems in parts of E and southern
Lakes region of E Africa Africa
• LGA systems in parts of E • Coastal systems in E and parts of
Africa southern Africa
Possibly • Mixed systems in parts of E • Coastal systems of parts of W Africa
moderate LGP Africa • Tree crop systems in parts of W
loss (5-20% to Africa
2050) • Forest-based systems in central
Africa
• Root-based and root-mixed systems
in south central Africa
Use such information as one input to evaluating trade-offs (e.g., numbers of poor versus
density of poor) in relation to specific development criteria

23. CCAFS revisiting this work from a food security
perspective (P. Ericksen leading)
• Broaden the scope, and do from a food security
perspective
• Use ensemble climate scenarios & variability
• Look at changes in vulnerability and food security in
the future
• Don’t use a composite vulnerability indicator but
look at the different dimensions
• Using real impacts on crop and livestock production

24. Analysis of Food Security Outcomes
COMPONENTS & Elements
Food
Security,
i.e.
stability
over
4me
for:
FOOD
FOOD
UTILISATION
ACCESS
• Nutri.onal
Value
• Affordability
• Social
Value
• Alloca.on
• Food
Safety
• Preference
FOOD
AVAILABILITY
• Produc.on
• Distribu.on
• Exchange

25. Assessing Food Systems OUTCOMES
Under different scenarios
per scenario Global
Caribbean
Production
++
Increase
Food Safety Distribution
+
0 Caribbean Order
From Strength
Decrease
_
Social Value Inter-Regional
__
Exchange
Caribbean
TechnoGarden
Nutritional Intra-Caribbean
Value Exchange
Caribbean
Preference Affordability
Adapting Mosaic
Allocation
Source: GECAFS (2006) Prototype Scenarios for the Caribbean. GECAFS Rpt 2.

26. Hazard exposure Vulnerability
Hot-spots of
global change
to 2030, 2050
Hot-spots of change to
2030, 2050
Hot-spots of changes in
hazard exposure & food
system vulnerability
to 2030, 2050

27. Addressing complexity
Herrero et al, Science (2010)

28. Data collection + household
modeling protocol :
 Climate
 Family structure
 Land management
 Livestock management
 Labour allocation
 Family’s dietary pattern
Farm’s sales and

expenses
Herrero et al 2007

29. Site: Sodo, Ethiopia
What’s the likely impact of food/feed crop
interventions?
Plot Crop
Homestead Enset, coffee, kale, sweet potato, maize
Plot1 Maize
Plot 2 Sweet potato, wheat
Plot 3 Maize
Plot 4 Sweet potato
Plot 5 Barley
Plot 6 Maize
Plot 7 Unimproved pasture
Livestock: 1 cow, 1 ox Profit: Birr 2,381

30. Site: Sodo, Ethiopia
Current
management
Food security
Cow feeding
Labour/capital
Cash
Soil fertility
Critical Adequate

31. Site: Sodo, Ethiopia
Intervention 1 Application of fertilizer to
Food crop maize plots.
Food security
Cow feeding
Labour/capital
Cash
Soil fertility
Critical Adequate

32. Site: Sodo, Ethiopia
Intervention 2 Replace native grassland
Feed crop with improved pasture.
Food security
Cow feeding
Labour/capital
Cash
Soil fertility
Critical Adequate

33. Research opportunities
• choice of indicators
• need large scale synthesis study looking at household-level
impacts of adaptation
• incorporating risk and uncertainty
• scenarios and how to represent change in vulnerability status in
the future
• Equity issues and others that define the winners and losers
(gender, location, power structures)
• What are the options?
• Upscaling issues (linking scales)

34. Thank you !
For more information:
m.herrero@cgiar.org
fly less, video-conference more…