Food security scenarios

Gina Ziervogel and Tom Downing

• Why scenarios?

• A pilot example– Global Scenario Group South African food security– Provincial level downscaling

• Toward a research agenda– Livelihood based scenarios– Characteristic syndromes in global storylines

Why scenarios?

• Jeremiah– Warnings of impending doom– Visualisation of desirable futures

Scenarios: Why and what?

Why: The limits of prediction– Complex socio-environmental processes– Surprise and the kinks of history

What:• Vision of a future time

– Sufficiently beyond the present to not be inherently predictable• Internally consistent

– Plausible relationships between elements, multiple attributes• Semi-quantitative

– Associated with indicators or supported by formal models• Appropriate

– Target time period, place, people– Relevant policy issue

Methodologies

• Visions and back-casting• Model simulation and probability• Worst case• Stakeholder-led/interactive• Role playing, gaming

Examples

• Climate change (IPCC)• Venetian visions (Ulysses)• IFPRI coupled model• Agent-based water demand (FIRMA)

Climate change

• Projections of global climate change• Based on:

– Socio-economic scenarios of the future– Greenhouse gas emissions interpreted from the

global scenarios– Global GHG emissions atmospheric

concentrations– Global climate models

IPCC: Global mean surface temperature

GHG Scenarios:Special Report on Emissions

Scenarios• Designed to bracket greenhouse gas

emissions, and hence climate change scenarios

• Government-scientist task force• Did not include sensitivity to climate impacts• Spawned UK Foresight scenarios, and others• Poor foundation for climate vulnerability

– The poorest region when climate change occurs is as rich as the OECD is now

SCENARIOS FOR VENICE, 2050

CURRENT DRIVING FORCES

VISIONSScenarios Narratives

DEMOGRAPHIC

ECONOMIC

TRANSPORTATION

CULTURAL

IDENTIFICATIONBREAKING POINTS

GOVERNANCE

Angela Pereira: JRC

VISIONS OF VENICE, 2050

Marco Polo tells Kublai Kan…

Tonight I’ll tell you about 4 cities

Veniexia, Venusia, Venetia, Vinegia

Visions of Venice 2050

Living conditions have deteriorated…Air and water pollution significantly affect human and ecosystem health Traditional activities close down Building Decay

A ‘new Venice’ in the mainland is created to preserve the cultural heritage

Tourism has trickled to a small fraction

Emigration increases

Gotham City

Visions of Venice 2050

Venezia Inc.

Venice became a cultural park and a museum city: one of the 4 most important tourist destinations of the world

Floods and high tides become tourist attractions

Venice is a stage where the whole population acts in a gigantic performance

Corporations dominate economy and city life

Carnival takes place 4 times a year

IFPRICoupled Water-Food System

Model• Business as usual

– Trend projection

• Alternatives– Water scarcity– Sustainable water

• Key indicators– Water use– Food prices

Interactive, behavioural scenarios

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Agent based:DiscontinuitiesLarge range of results

Dynamic simulation:Smooth scenariosModest range

South African food security

• GSG: key indicators for food security• RSA: anomalies to Africa?• Mapping GSG to RSA Food security

indicators• Results

– Great transitions– Market forces

• Observations

GSG Indicator South Africa

Pop growth rate =

Urban fraction =

Income per capita +++

Agriculture value added ++

International equity +++

National equity +++

Gini +++

Hunger, % +++

Harvested area ++

Production ++

N Fertiliser ++

Yield =

Calorie intake ++

Water withdrawls/resources +++

Water stress, % +

Freight intensity ++

South Africa is similarto Africa in the GlobalScenarios Group

Income and equity are major drivers

Agricultural changesare modest, greaterwater stress in SouthAfrica

Food security indicators

• Matrix of drivers from GSG for South Africa• Range of plausible future values for food

security indicators• Current values• Expert judgement as to relative influence of

drivers within a consistent storyline• Check consistency between scenarios• …Stakeholder dialogues

Great Transitions in South Africa

Unemployment

GDPpc

Maize Consumption

Maize Production

HIV

Infant Mortality

Roads

Health Facilities

Base Gt2025 Gt2050

Market Forces in South Africa

Unemployment

GDPpc

Maize Consumption

Maize Production

HIV

Infant Mortality

Roads

Health Facilities

Base Gt2025 Gt2050

Scenario range: GT - MFUnemployment

GDPpc

Maize Consumption

Maize Production

HIV

Infant Mortality

Roads

Health Facilities 2025

2050

7

GLOBAL

Climate (disasters)

Technology

Distribution/ equity

Market mechanisms

Conflict/ instability

Communication/ publicity

LOCAL Financial/monetary

Natural resources

Knowledge

Health

Institutions

Scenarios of food security Global drivers of food security and

local indicators of livelihood security

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Categories included in local indicators: 1. Financial/monetary

– Access to financial support– Remittances– Multiple sources of household income

2. Natural resources– Land, water, soil– Amount of food available

3. Knowledge– Local knowledge; access to education– Technical support– Technology

4. Health5. Institutions

– Households– Community– National– Regional – International

Local food security scenarios

• Global level– Human Development Index (HDI)

– Environmental Sustainability Index (ESI)

– PoleStar (produces indicator data for Africa)

• Regional – Southern African Regional Poverty Network (SARPN)

– World Bank Africa Household Survey Databank

• National – Stats SA

• Official agency for collection of national statistics

– Department of Agriculture

– State of Environment Report

Provincial data

• National surveys– 1996 Population census

– October household surveys

– Rural survey

– Income and expenditure survey

– Agricultural surveys and data• Agricultural boards have been abolished in the last 5 years which is

constraining data availability

• Outputs– Bulletin of South African Statistics, 2002

– Bulletin of South African Statistics, 2003

Scenario drivers of food security

• Food availability:– Agricultural area, production, yield, fertiliser, population– Consumption, hunger– Income

• Food access:– Income per capita, equity, agricultural value added– Urban population, freight intensity

• Reliability of food:– Income, equity, urban– Consumption, water stress

• Distribution:– Income, population, equity– Freight intensity

South African food security indicators

Department of Agriculture, Republic of South Africa. 2002. The integrated food security strategy for South Africa.

Food security categories Indicators

Food access 1 Unemployment

Also effective demand: ability of nation and its household to acquire sufficient food on sustainable basis. It addresses issues of purchasing power and consumption behaviour.

2 GDP/capita

Food availability 3 Maize consumption/capita

Effective or continuous supply of food at both national and household level. It is affected by input and output market condition, as well as production capabilities of the agricultural sector

4 Measure of production

Reliability of food 5 HIV infection rates

Utilisation and consumption of safe and nutritious food. 6 Infant mortality

Food distribution 7 Roads

Equitable provision of food to points of demand at the right time and place. This spatial/time aspect of food security relates to the fact that a country might be food secure at the national level, but still have regional pockets of food insecurity, at various periods of the agricultural cycle.

8 Primary health centres

South African provincial indicators

Food access Food availability Reliability of food Food distribution

Indicator number 1 2 3 4 5 6 7 8

Unemployment (%)

GDP per capita (PPP$)

Maize consumption/capita

Maize production (t/ha)

Estimated HIV+ % pregnant women

Infant mortality per 1000

Road density km/km2

Primary health care facilities, pop/facility

South Africa 59.10 5916 95.06 2.93 24.8 41.8 0.22 4352

Western cape 74.50 9381 97.05 4.5* 8.6 26.8 0.14 531

Eastern cape 60.80 2856 92.25 2.90 21.7 58.2 0.29 780

Northern cape 59.00 6513 95.01 9* 15.9 31.5 0.18 152

Free state 59.10 5185 94.39 2.70 30.1 45.1 0.22 298

Kwazulu-natal 53.30 4563 94.91 3.81 33.5 44.7 0.33 629

North west 53.70 3509 94.49 2.16 25.2 35.2 0.2 474

Gauteng 64.40 11862 91.92 2.81 29.8 43.5 0.23 438

Mpumalanga 58.30 6105 94.23 3.34 29.2 41.2 0.2 386

Limpopo 44.90 2019 92.89 2.83 14.5 57 0.2 664

* irrigated

GDP per capita (PPP$)

Western cape

Eastern cape

Northern cape

Free state

Kwazulu-natal

North west

Gauteng

Mpumalanga

Limpopo Western cape

Eastern cape

Northern cape

Free state

Kwazulu-natal

North west

Gauteng

Mpumalanga

Limpopo

Estimated HIV+ % pregnant women

Western cape Eastern cape

Northern cape

Free state

Kwazulu-natal North west

Gauteng

Mpumalanga

Limpopo Western cape

Eastern cape

Northern cape

Free state

Kwazulu-natal

North west

Gauteng

Mpumalanga

Limpopo

Food security

Availability Access Reliability Distribution

+ + +>T >T >T >T

Analytical models reflect conceptual framework:Can have significant effect on results

Observations

• Specificity– Scenarios developed for one purpose may not be adequate

for different policy debates• Heterogeneity

– Many worlds (large and small) fit within a single storyline: there is no one ‘best’ scenario

• Insight– The process of visualising alternative worlds is important

and not easily substituted by reading about a scenario– Local scenarios of food insecurity are needed to address

potential future household and district level vulnerability• Visceral

– A plethora of ways to visual alternative futures is required