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Food security scenarios

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?.

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Food security scenarios

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  1. Food security scenarios Gina Ziervogel and Tom Downing

  2. 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

  3. Why scenarios? • Jeremiah • Warnings of impending doom • Visualisation of desirable futures

  4. 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

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

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

  7. 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

  8. IPCC: Global mean surface temperature

  9. 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

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

  11. VISIONS OF VENICE, 2050 Tonight I’ll tell you about 4 cities Veniexia, Venusia, Venetia, Vinegia Marco Polo tells Kublai Kan…

  12. Visions of Venice 2050 Tourism has trickled to a small fraction 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 Emigration increases Gotham City

  13. Visions of Venice 2050 Venice became a cultural park and a museum city: one of the 4 most important tourist destinations of the world Venice is a stage where the whole population acts in a gigantic performance Corporations dominate economy and city life Floods and high tides become tourist attractions Carnival takes place 4 times a year Venezia Inc.

  14. IFPRICoupled Water-Food System Model • Business as usual • Trend projection • Alternatives • Water scarcity • Sustainable water • Key indicators • Water use • Food prices

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

  16. 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

  17. South Africa is similarto Africa in the GlobalScenarios Group Income and equity are major driversAgricultural changesare modest, greaterwater stress in SouthAfrica

  18. 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

  19. 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

  20. 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

  21. 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

  22. 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

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

  24. South African provincial indicators

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

  26. 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

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