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

–  Background

–  Some definitions

–  Methodology

–  Some results

–  Future research

Outline

Systems are changing…

  Population / Urbanization / Incomes / Diets

  Increased competition for natural resources

  Climate change –   warmer and   more variable

  Trade / exchange of knowledge and products

W. Africa 1966 – pastoral system 2004 – crop-livestock system

The target is moving! An example of the changing nature of production systems

..and then climate change….

0º

20º

-20º

0º 20º 40º

An example of climate-induced livelihood transitions

Areas where cropping of an indicator cereal may become unviable between now and 2050 and where farmers may have to rely more on livestock as a livelihood strategy

Jones & Thornton (2008)

National Production

Mixed rainfed

temperate

Mixed rainfed humid

Mixed rainfed

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

A game of winners and losers…

Simulated percentage maize production changes to 2030 and 2050, by country and system

Mean of 4 combinations of GCM and emissions scenario

Thornton et al. (2010)

Winners Losers

There are always trade-offs

Rainy Dry Dry

Groundnuts

Yams

Sorghum

Grazing Critical Crop residue

Cut & Carry

Prot. & Ene. deficit

Food security Energy deficit

Family’s nutrition

Feeding calendar

Cropping calendar

Weather calendar

Monthly calendar of different activities of the system

Cash demands Very high

Low High High Low Low High High

Wa, Upper West, Ghana

Gonzalez-Estrada et al. 2006

...from vulnerability mapping to assessing household level impacts...

directly linked to adaptation options

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”

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

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

Changes in growing

conditions to 2050

Climate Change Risk / Impact

Different scenarios of

the future

Biophysical vulnerability

Social vulnerability

14 indicators

Data reduction analysis 4 factors, combined

into one “overall” vulnerability indicator

Hot-spots

Hot-spots

Hot-spots of climate risk AND vulnerability

Vulnerability

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

Assessing climate change

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)

Data adapted from Thornton et al., 2006

Days

Where are the impacts?

% change in LGP Data adapted from Thornton et al., 2006

What systems are mostly affected?

Livestock based systems

Mixed irrigated systems

Mixed rainfed systems

Data adapted from Thornton et al., 2006

14 vulnerability indicators used in ILRI study Data at different scales: country, province, 18 km2

Natural capital

•  Crop suitability (FAO, GLC2000) •  Soil degradation (GLASOD) •  Water availability (FAO Water Atlas)

Physical capital

•  Market access (ILRI)

Social capital

•  Human poverty index (HDR) •  Governance (World Bank)

Human capital

•  Stunting (FAO, CIESIN) •  Infant mortality (CIESIN) •  Wasting (CIESIN) •  Public health expenditure (HDR) •  Malaria risk (MARA) •  HIV/AIDS prevalence (HDR)

Financial capital

•  Agriculture as % of GDP (World Bank) •  Imports vs Exports (World Bank)

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

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

Highest vulnerability quartile (4)

Second-highest vulnerability quartile (3)

Possibly severe LGP loss (>20% to 2050)

•  Some MRA systems in Sahel •  Mixed rainfed and highland perennial systems in Great Lakes region of E Africa •  LGA systems in parts of E Africa

•  MRA, LGA systems in large parts of Sahel •  Livestock systems and some mixed systems in parts of E and southern Africa •  Coastal systems in E and parts of southern Africa

Possibly moderate LGP loss (5-20% to 2050)

•  Mixed systems in parts of E Africa

•  Coastal systems of parts of W Africa •  Tree crop systems in parts of W Africa •  Forest-based systems in central Africa •  Root-based and root-mixed systems in south central Africa

Synthesis of hot-spots MRA, mixed rainfed arid-semairid systems LGA, rangeland arid-semiarid systems

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

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

Analysis of Food Security Outcomes COMPONENTS & Elements

Food  Security,  i.e.  stability  over  4me  for:  

FOOD  UTILISATION  

FOOD    ACCESS  

• Affordability  • Alloca.on  • Preference  

• Nutri.onal  Value  • Social  Value  • Food  Safety  

FOOD    AVAILABILITY  

• Produc.on  • Distribu.on  • Exchange  

Assessing Food Systems OUTCOMES Under different scenarios

Production

Distribution

Inter-Regional Exchange

Intra-Caribbean Exchange

Affordability

Allocation

Preference

Food Safety

Incr

ease

D

ecre

ase

Nutritional Value

Social Value

Global Caribbean

Caribbean Order From Strength

Caribbean TechnoGarden

Caribbean Adapting Mosaic

per scenario

Source: GECAFS (2006) Prototype Scenarios for the Caribbean. GECAFS Rpt 2.

++

+ 0

_

_ _

Hazard exposure

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

Vulnerability

Addressing complexity

Herrero et al, Science (2010)

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

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

What’s the likely impact of food/feed crop interventions?

Site: Sodo, Ethiopia

Profit: Birr 2,381 Livestock: 1 cow, 1 ox

Site: Sodo, Ethiopia

Critical Adequate

Current management

Food security

Cow feeding

Labour/capital

Cash

Soil fertility

Food security

Cow feeding

Labour/capital

Cash

Soil fertility

Site: Sodo, Ethiopia

Critical Adequate

Intervention 1 Food crop

Application of fertilizer to maize plots.

Food security

Cow feeding

Labour/capital

Cash

Soil fertility

Site: Sodo, Ethiopia

Critical Adequate

Intervention 2 Feed crop

Replace native grassland with improved pasture.

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)

Thank you !

For more information:

m.herrero@cgiar.org

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