Transcript Food security scenarios - Global Environmental Change and Food

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
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•
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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
VISIONS
Scenarios Narratives
DEMOGRAPHIC
ECONOMIC
IDENTIFICATION
BREAKING POINTS
TRANSPORTATION
GOVERNANCE
CULTURAL
Angela Pereira: JRC
VISIONS OF VENICE, 2050
Tonight I’ll tell you
about 4 cities
Veniexia,
Venusia,
Venetia, Vinegia
Marco Polo tells Kublai Kan…
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
Emigration
increases
Gotham City
A ‘new Venice’
in the mainland
is created to
preserve
the cultural heritage
Visions of Venice 2050
Venice became a cultural park and a museum
city: one of the 4 most important tourist
destinations of the world
Corporations
dominate economy
and city life
Carnival takes place 4
times a year
Venezia Inc.
Floods and high tides
become tourist
attractions
Venice is a stage
where the whole
population acts in
a gigantic
performance
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
Aggregate demand series scaled so 1973=100
200
180
160
Agent based:
120
Discontinuities
Large range of results
100
80
60
40
20
0
J- J- J- J- J- J- J- J- J- J- J- J- J- J- J- J- J- J- J- J- J- J- J- J- J73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97
Climate change impacts
Simulation Date
250
BetaMH
100
GammaMH
DeltaMH
50
2041
2039
2037
2035
2033
2031
2029
2027
2025
2023
2021
0
2019
Smooth scenarios
Modest range
AlphaMH
150
2017
Dynamic simulation:
200
2015
Relative Demand
140
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
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
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
++
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
Health Facilities
GDPpc
Roads
Maize Consumption
Infant Mortality
Maize Production
HIV
Base
Gt2025
Gt2050
Market Forces in South Africa
Unemployment
Health Facilities
GDPpc
Roads
Maize Consumption
Infant Mortality
Maize Production
HIV
Base
Gt2025
Gt2050
Scenario range: GT - MF
Unemployment
Health Facilities
GDPpc
2025
2050
Roads
Maize Consumption
Infant Mortality
Maize Production
HIV
Scenarios of food security
Global drivers of food security and
local indicators of livelihood security
GLOBAL
LOCAL
Climate (disasters)
1
2
Financial/monetary
6
13
Technology
5
4
3
10
8
9
7
Distribution/ equity
12
14
Natural resources
11
15
Knowledge
Market mechanisms
17
18
16
19
Conflict/ instability
Health
20
21
Communication/ publicity
Categories included in local indicators:
1. Financial/monetary
–
–
–
Access to financial support
Remittances
Multiple sources of household income
2. Natural resources
22
Institutions
–
–
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
• 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
Reliability of food
Food distribution
5
6
7
Unemployment GDP per capita Maize
Maize
(%)
(PPP$)
consumption/c production
apita
(t/ha)
Estimated
HIV+ %
pregnant
women
Infant mortality Road density
per 1000
km/km2
Primary health
care facilities,
pop/facility
South Africa
59.10
5916
95.06
2.93
24.8
41.8
0.22
4352
Western cape
74.50
9381
97.05
4.5*
8.6
26.8
0.14
531
Eastern cape
60.80
2856
92.25
2.90
21.7
58.2
0.29
780
Northern cape
59.00
6513
95.01
9*
15.9
31.5
0.18
152
Free state
59.10
5185
94.39
2.70
30.1
45.1
0.22
298
Kwazulu-natal
53.30
4563
94.91
3.81
33.5
44.7
0.33
629
North west
53.70
3509
94.49
2.16
25.2
35.2
0.2
474
Gauteng
64.40
11862
91.92
2.81
29.8
43.5
0.23
438
Mpumalanga
58.30
6105
94.23
3.34
29.2
41.2
0.2
386
Limpopo
44.90
2019
92.89
2.83
14.5
57
0.2
664
Indicator number 1
Food availability
2
3
4
* irrigated
8
GDP per capita (PPP$)
Limpopo
Mpumalanga
Western cape
Western cape
Eastern cape
Northern cape
Eastern cape
Free state
Kwazulu-natal
Gauteng
Northern cape
North west
Gauteng
North west
Kwazulu-natal
Free state
Mpumalanga
Limpopo
Estimated HIV+ % pregnant women
Limpopo Western cape
Eastern cape
Mpumalanga
Western cape
Eastern cape
Northern cape
Northern cape
Free state
Kwazulu-natal
Gauteng
Free state
North west
Gauteng
North west
Kwazulu-natal
Mpumalanga
Limpopo
Food security
Availability
>T
Reliability
Access
+
>T
+
>T
Distribution
+ >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