Ziervogel presentation2

Food security scenarios: 

Food security scenarios Gina Ziervogel and Tom Downing

Slide2: 

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?: 

Why scenarios? Jeremiah Warnings of impending doom Visualisation of desirable futures

Scenarios: Why and what?: 

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: 

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

Examples: 

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

Climate change: 

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: 

IPCC: Global mean surface temperature

GHG Scenarios:Special Report on Emissions Scenarios: 

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: 

SCENARIOS FOR VENICE, 2050 CURRENT DRIVING FORCES VISIONS Scenarios Narratives DEMOGRAPHIC ECONOMIC TRANSPORTATION CULTURAL IDENTIFICATION BREAKING POINTS GOVERNANCE Angela Pereira: JRC

VISIONS OF VENICE, 2050: 

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: 

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: 

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: 

IFPRI Coupled Water-Food System Model Business as usual Trend projection Alternatives Water scarcity Sustainable water Key indicators Water use Food prices

Interactive, behavioural scenarios: 

Interactive, behavioural scenarios Agent based: Discontinuities Large range of results Dynamic simulation: Smooth scenarios Modest range

South African food security: 

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

Slide17: 

South Africa is similar to Africa in the Global Scenarios Group Income and equity are major drivers Agricultural changes are modest, greater water stress in South Africa

Food security indicators: 

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

Slide22: 

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. Health 5. Institutions Households Community National Regional International

Local food security scenarios: 

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 : 

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: 

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: 

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

South African provincial indicators: 

South African provincial indicators

Slide29: 

Food security Availability Access Reliability Distribution + + + >T >T >T >T Analytical models reflect conceptual framework: Can have significant effect on results

Observations: 

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