Transcript Food System Futures - ifstal

Food System Futures: dealing
with uncertainty and complexity
Professor Charles Godfray, Dr. Monika Zurek &
Dr Joost Vervoort
IFSTAL
Oxford, Mar 10th 2016
Charles Godfray
Department of Zoology & Director, Oxford
Martin Programme on the Future of Food
Food prices
FAO Food
Price Index
Nominal
(1990 = 100;
Jan 1990 to Feb 2016)
Real
UN Food and Agriculture Organisation 2014
Future population growth
(medium fecundity assumption)
Estimate with
95 & 80%
confidence
limits
2100
2050
Billion
people
Now
23% chance
of peak
before 2100
Data
Forecast
UN Population Division, World Population Prospects, 2015 Revision
Per capital calorie demand kcal d-1
Calorie demand increases with income
Meat consumption
Meat consumption
Developed nations
China
India
Africa
1970
1980
1990
Per capita GDP 1990$ yr-1
Tilman et al. 2011 PNAS
FAO 2009
2000
Percentage of water withdrawal for agriculture
No
data
<
25%
2540%
40
-60%
6075%
7590%
FAO Aquastat 2007
Coming challenge
•
Continuing demand growth
•
Urbanisation & mega-cities
•
Hunger & under-nutrition
•
Obesity & over-nutrition
•
Pressures on agriculture
•
•
Water scarcity
•
Competition for land and soil
degradation
Resilience to shocks
•
Climate change
•
Pests and diseases
•
Human
Making projections about the food system
•
Statistical extrapolation
•
Expert judgement
•
Market models
•
•
Computable General Equilibrium
•
Partial Equilibrium
Scenario techniques
AgMip Project Results Dec 2013
Price
60%
Area
40%
Effect of climate
change on yield
20%
Additional 20%
effect of
0%
climate
change
-20%
in 2050
-40%
Production
Trade Consumption
-60%
Endogenous
adjustment
Nelson et al, PNAS 2013
IMPACT:
a partial
equilibrium
model of the
food system
Daniel Mason D’Cruz &
Sherman Robinson
(IFPRI)
•
International Food Policy Research Institute (IFPRI)
•
281 food producing area (geopolitical & water basin)
•
115 countries, their economies linked by trade
•
40 commodities (all major crops)
•
Humans that make decisions based on food costs and income
•
Farmers that make decisions based on commodity prices
•
Economic and population growth exogenous
•
Can be linked to water and global circulation models
•
Calculates world market price for each commodity that clears
markets given net global trade sums to zero
Diet-related health & climate change
Team led by
Marco Springmann
Pete Scarborough
& Mike Rayner
From DPH, Oxford
Couple a global
health model to
a food economic
model (IMPACT),
itself driven by
climate and crop
Models.
Deaths due to climate change
Avoided deaths, climate change
Avoided deaths, no climate change
Causes of death
Risk categories
Fruit & veg
Underweight
Obese
Meat
Total
Overweight
Distribution of climate-change related deaths
Springmann et al. March 2, 2016 The Lancet
DOI: 10.1016/S0140-6736(15)01156-3
Caveats
•
500m death high emission scenario
•
Uncertainties in agricultural models; especially over extreme events
•
Assumptions in economic models
•
Simplifications in health models (results robust in sensitivity analysis)
Conclusions
•
Modest reductions in consumption but 28% drop in avoided deaths
•
Diets matter and food system approach needed
•
Recent WHO estimates of disease burden of climate change too low
•
Further argument for mitigation
•
Adopt broad-focus on weight-related risk factor
•
Greater research focus on fruit and vegetable production and levers
of diet change
Fraction global population living in cities
67%
50%
30%
Data
Forecast
UN Population Division, World Urbanisation Prospects, 2014 Revision
Distribution of large global cities and their growth rates
UN Population Division, World Urbanisation Prospects, 2014 Revision
Developing country cereal trade
Exporting nations
Million
tonnes
-
-
-
Alexandratos & Bruinsma 2014 (FAO)
Developing country cereal trade
Exporting nations
Million
tonnes
-
-
-
Importing nations
Alexandratos & Bruinsma 2014 (FAO)
Developing country cereal trade
Exporting nations
Million
tonnes
-
Net imports
-
-
Importing nations
Alexandratos & Bruinsma 2014 (FAO)
Egypt
Indonesia
Algeria
Brazil
Japan
Turkey
Iran
EU
Nigeria
United States
Mexico
South Korea
Yemen
Philippines
Bangladesh
0
2
4
6
8
10
Wheat imports (million MT)
Index Mundi 2014
FAO Food Price Index (1990 = 100; Jan 1990 to May 2015)
Nominal
Real
UN Food and Agriculture Organisation 2014
Haiti
Cote d’Ivoire
Food
riots
Sudan
Cameroon
Yemen
Mozambique
Mozambique Egypt Mauritania
Algeria
Libya
Egypt
Saudi Arabia
Tunisia
Sudan
Somalia
Yemen
Tunisia
Oman
Morocco
India
Iraq
Bahrain
Sudan
Syria
Uganda
Mauritania
India
Somalia
Burundi
2004
2006
2008
2010
2012
2014
Lagi, Bertrand & Bar-Yam 2011
Scenario development and
influencing change in Food
systems
Monika Zurek
ECI, Food Systems Group, University of Oxford
Given all the various issues with the food
system………..
…..how can we decide on and influence change in the
system?
…..how can we deal with uncertainty about the future,
the complexity of the system, understanding the impact
of our decisions and deciding on a way forward?
Washington Post, 30 M
Sources of Uncertainty when thinking about the
Future
Ignorance Understanding is limited
The unexpected and the novel
Surprise can alter directions
Volition
Human choice matters
Source: P. Raskin
MA: Four Working Groups
Condition
and Trends
 What is the
current
condition and
historical
trends of
ecosystems and
their services?
 What have
been the
consequences
of changes in
ecosystems for
human wellbeing?
Sub-Global
Scenarios
Responses
 Given plausible
changes in
primary
drivers, what
will be the
consequences
for ecosystems,
their services,
and human
well-being?
 What can we
do to enhance
well-being and
conserve
ecosystems?
 All of the above, at regional,
national, local scales
Methods to deal with Complexity and Uncertainty
Zurek &
Henrichs
2007
Scenario Definitions
Plausible stories about how the future might
unfold from existing patterns, new factors and
alternative human choices. The stories can be told
in the language of both words and numbers
(Raskin, 2005).

Plausible descriptions of how the future may
develop, based on a coherent and internally
consistent set of assumptions about key
relationships and driving forces (Nakicenovic
2000).

A tool for ordering one’s perceptions about
alternative future environments in which one’s
decision might be played out (Schwartz 1996).

Plausible alternative futures, each an example
of what might happen under particular
assumptions (MA, 2005).

Possible purposes of a scenarios exercise

Science / Research
 to integrate information from different fields
 to explore possible developments

Education / Public Information
 to educate and teach public on new developments
 to raise awareness of policy-makers, stakeholders

Strategic Planning / Decision Support
 to gather different views and to identify issues
 to frame strategic issues, to identify alternatives
 to support policy measure development
 Stakeholder involvement depends on purpose
Types of scenarios

Qualitative vs. quantitative scenarios, or a combination

Exploratory vs. anticipatory scenarios

Baseline vs. alternative/policy scenarios
Source: Ecosystems and
Human Wellbeing: A
Handbook for
Practitioners (2010)
Anatomy of
Scenarios
Key Dimensions
•Multi-dimensional
space of variables
Boundaries
•Spatial
•Thematic
•Temporal
Current Situation
•Historic context
•Institutional description
•Quantitative accounts
Driving
Forces
•Trends
•Processes
Image of
the
Future
Critical Uncertainties
•Resolution alters course of events
Plot
•Captures dynamics
•Communicates effectively
Source: P. Raskin 2002
Options for comparing Example from the Millennium Ecosystem Assessment scenarios
across the scenarios
Look for future
developments that are
the same in all
scenarios
Same trend of rising world population up to 2050 in all scenarios, then
stabilization; exact population numbers in 2050 differ.
Global forest area declines up to 2050 in all scenarios: velocity of
trends differs.
Look for uncertain
future developments,
which differ across
scenarios
Number of malnourished children in 2050 differs widely among
scenarios.
Quality and quantity of available water resources by 2050 differ
widely among regions and across scenarios.
Identify trade-offs
described in the
scenarios
Risk of trading off long-term environmental sustainability for fast
improvement in human systems (Global Orchestration).
Risk of trading off solutions to global environmental problems
(requiring global cooperation) for improving local environments
(focusing on local solutions only) (Adapting Mosaic).
Risk of trading off biodiversity conservation for food security (Global
Orchestration).
Identify policy options
that make sense in all
scenarios
Major investments in public goods and poverty reduction, together
with elimination of harmful trade barriers and subsidies.
Widespread use of adaptive ecosystem management and investment in
education.
Significant investments in technologies to use ecosystem services more
efficiently, along with widespread inclusion of ecosystem services in
markets.
Source:
Ecosystems and
Human
Wellbeing: A
Handbook for
Practitioners
(2010)
Scenario exercises: used both in scientific
assessments as well as the business
community





Strategic planning exercises during cold war period
Future studies in 1970s (e.g. Club of Rome)
Royal Dutch Shell develops scenarios method for
business planning in 1970/80s
Scenarios used as conflict management tool
(Montefleur scen. in SA, Colombia)
Scenarios exercises as part of integrated, global,
environmental assessments, such as the IPCC, GEO,
MA in 1990s and 2000s
IPCC SRES scenarios
Millennium Ecosystem Assessment
Scenarios
World Development
globalization
regionalizatio
n
Global
Orchestration
Order from
Strength
TechnoGarde
n
Adapting
Mosaic
reactiv
e
Now new scenarios work in IPCC:
Ecosyste
m
Manag
ement
 Shared Socio-economic Pathways (SSPs)
proacti
 Representative concentration pathways (RCPs)
ve
Forward looking exercises on the future of food –
some examples
Stakeholder
Workshop Narratives
GLOBIOM
Quantified
Explorative
Scenarios
EU case
studies
Fuzzy
Cognit
ive
Modell
ing
Transition
Pathways
GLOBIOM
Quantified
Transition
Pathways
Local case
studies
 Review of
existing food
system
scenarios
 Synthesis of
scenarios on
sustainable
food and
nutrition
security for
the EU
Thank you!
[email protected]
Stepping into food scenarios:
foresight, policy guidance and
games in food systems
Joost Vervoort
Environmental Change Institute, University of Oxford
CGIAR Programme on Climate Change, Agriculture and Food Security
(CCAFS)
FP7 TRANSMANGO
H2020 SUSFANS
Future Earth FTI Seeds of Good Anthropocenes
Overview
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Using scenarios for policy guidance in food systems
The potential of games
Why game co-design?
Examples & ideas
Questions for FS governance games
• 2013, Vervoort et al. 2014)
Using scenarios for food systems policy guidance
• CGIAR’s CCAFS programme: scenarios developed
with stakeholders and models in 7 global regions
(East & West Africa, South &Southeast Asia, Latin
America, the Pacific)
 Using scenarios to formulate many major
national and regional policies
• FP7 TRANSMANGO: future of EU food system,
scenarios + transition pathways – diversity of local
case studies + EU-level policy
 Local and EU-level strategy impacts
• H2020 SUSFANS: multi-model FNS toolbox for
testing policy options under different scenarios
 For policy makers, private sector, civil society
Using scenarios for policy and investment guidance
Two approaches:
• 1. start with plan,
develop scenarios;
test across
scenarios
(Honduras)
• 2. Develop
scenarios, develop
plans in individual
scenarios, test
across scenarios
(Bangladesh)
Draft plan
Develop
scenarios
Develop
scenarios
Test plan in
scenarios
Robust plan
Robust plan
Scenarios
Test elements
Inspire plan across
elements
scenarios
Scenarios for policy impact
• Crucial to integrate scenarios and planning
• For major governance challenges – involving non-state actors
in policy design; integrating actor agendas; integrating across
system levels and scales;
• Success factors: process co-design, targeted collaboration,
trust, inclusiveness, legitimate & credible but adaptable
scenarios, researcher flexibility
• Challenges – simple but unfamiliar; against dominant planning
cultures, difficult issues etc.
GAMES
• Massive field of business and research - an
explosion of ‘indie’ creativity recently
• Digital, board games, role playing, Alternate
Reality Games, Augmented Reality, Virtual
Reality
• History in policy testing (war games..)
• Investigating system dynamics - form of
participatory modelling
• Explore discourses, power, networks…
• Roles, changing identities, interactions
• Stimulate ‘gameful’ attitudes
Beyond scenarios: game cocreation
• Playing a pre-designed game together vs
designing a game
• Help people think about how to capture FS
challenges
• Highlighting framing and boundary judgements
• More ownership
• Harness all the strengths of scenarios
• Power gaps and empathy: Ugandan farmers
and policy makers
• Can be designed very close to policy
(scenarios) – game playing IS the impact
• ‘Modelling’ for FS governance
Examples
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Seeds of Good Anthropocenes (Future Earth) – mixing
novel practices with challenging future scenarios in role
playing game – players play ‘seeds’ and ‘scenarios’
Developing games with game design students
TRANSMANGO game jam with food system actors all
across Europe
Designing a FS governance game
Purpose?
What aspects of food system governance?
Who?
What would a one-sentence description of the game be?
Design
Primary activity?
How many players?
Is the game competitive, collaborative, a mix, or otherwise organized?
What is the objective, and what are the victory conditions?
What information is available?
How does the game’s ‘economy’ work, if relevant?
Story, atmosphere, emotions – link to game mechanics?
Scenarios
Are there different starting conditions representing different scenarios?
Or different levels/settings?
Are the scenarios largely created through internal game play, or through external conditions?
Outputs
Can the game be used to test different policies or strategies and does it generate
recommendations?
Does the game generate insights about actor interactions that could be reported on?
Does the game result in challenging scenarios (it’s a scenario-generator)?
Does the game interact with or connect with information from outside the game setting in some
other way?
Thank you & get in touch!
•
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Vervoort, J. M., D. H. Keuskamp, K. Kok, R. van Lammeren, T. Stolk, T.
Veldkamp, J. Rekveld, R. Schelfhout, B. Teklenburg, A. Cavalheiro Borges,
Jáno, S. kóva, W. Wits, N. Assmann, E. Abdi Dezfouli, K. Cunningham, B.
Nordeman, and H. Rowlands. 2014a. A sense of change: media
designers and artists communicating about complexity in socialecological systems. Ecology and Society 19.
Vervoort, J. M., K. Kok, P. J. Beers, R. Van Lammeren, and R. Janssen.
2012. Combining analytic and experiential communication in
participatory scenario development. Landscape and Urban Planning
107:203-213.
Vervoort, J. M., K. Kok, R. van Lammeren, and T. Veldkamp. 2010.
Stepping into futures: Exploring the potential of interactive media for
participatory scenarios on social-ecological systems. Futures 42:604-616.
Vervoort, J. M., P. K. Thornton, P. Kristjanson, W. Förch, P. J. Ericksen, K.
Kok, J. S. I. Ingram, M. Herrero, A. Palazzo, A. E. S. Helfgott, A. Wilkinson, P.
Havlík, D. Mason-D'Croz, and C. Jost. 2014b. Challenges to scenarioguided adaptive action on food security under climate change. Global
Environmental Change.
[email protected]
Food System Futures: dealing
with uncertainty and complexity
Professor Charles Godfray, Dr. Monika Zurek &
Dr Joost Vervoort