Download - Food security scenarios
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Food security scenarios
Gina Ziervogel and Tom Downing
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• 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
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Why scenarios?
• Jeremiah– Warnings of impending doom– Visualisation of desirable futures
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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
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Methodologies
• Visions and back-casting• Model simulation and probability• Worst case• Stakeholder-led/interactive• Role playing, gaming
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Examples
• Climate change (IPCC)• Venetian visions (Ulysses)• IFPRI coupled model• Agent-based water demand (FIRMA)
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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
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IPCC: Global mean surface temperature
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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
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SCENARIOS FOR VENICE, 2050
CURRENT DRIVING FORCES
VISIONSScenarios Narratives
DEMOGRAPHIC
ECONOMIC
TRANSPORTATION
CULTURAL
IDENTIFICATIONBREAKING POINTS
GOVERNANCE
Angela Pereira: JRC
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VISIONS OF VENICE, 2050
Marco Polo tells Kublai Kan…
Tonight I’ll tell you about 4 cities
Veniexia, Venusia, Venetia, Vinegia
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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
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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
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IFPRICoupled Water-Food System
Model• Business as usual
– Trend projection
• Alternatives– Water scarcity– Sustainable water
• Key indicators– Water use– Food prices
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Interactive, behavioural scenarios
0
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J-73
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Climate change impacts
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AlphaMH
BetaMH
GammaMH
DeltaMH
Agent based:DiscontinuitiesLarge range of results
Dynamic simulation:Smooth scenariosModest range
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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
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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
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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
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Great Transitions in South Africa
Unemployment
GDPpc
Maize Consumption
Maize Production
HIV
Infant Mortality
Roads
Health Facilities
Base Gt2025 Gt2050
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Market Forces in South Africa
Unemployment
GDPpc
Maize Consumption
Maize Production
HIV
Infant Mortality
Roads
Health Facilities
Base Gt2025 Gt2050
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Scenario range: GT - MFUnemployment
GDPpc
Maize Consumption
Maize Production
HIV
Infant Mortality
Roads
Health Facilities 2025
2050
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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
1
2
3 4
6
5
10 9
8
16
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12 11
20
19 18
17
21
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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
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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
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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
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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
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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
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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$)
Maize consumption/capita
Maize production (t/ha)
Estimated HIV+ % pregnant women
Infant mortality per 1000
Road density km/km2
Primary health care facilities, pop/facility
South Africa 59.10 5916 95.06 2.93 24.8 41.8 0.22 4352
Western cape 74.50 9381 97.05 4.5* 8.6 26.8 0.14 531
Eastern cape 60.80 2856 92.25 2.90 21.7 58.2 0.29 780
Northern cape 59.00 6513 95.01 9* 15.9 31.5 0.18 152
Free state 59.10 5185 94.39 2.70 30.1 45.1 0.22 298
Kwazulu-natal 53.30 4563 94.91 3.81 33.5 44.7 0.33 629
North west 53.70 3509 94.49 2.16 25.2 35.2 0.2 474
Gauteng 64.40 11862 91.92 2.81 29.8 43.5 0.23 438
Mpumalanga 58.30 6105 94.23 3.34 29.2 41.2 0.2 386
Limpopo 44.90 2019 92.89 2.83 14.5 57 0.2 664
* irrigated
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GDP per capita (PPP$)
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
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Food security
Availability Access Reliability Distribution
+ + +>T >T >T >T
Analytical models reflect conceptual framework:Can have significant effect on results
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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