Transcript Multiple-scale Modelling - Integrated Assessment of Agriculture and

three decades of Integrated Assessment:
the way forward
Jan Rotmans
Egmond aan Zee, 11-03-2009
SUSTAINABILITY PARADOX
It would be naive to suppose that the
unsustainability problems humankind is faced
with could be solved with current tools and
methods (models!) that were applied –
or seemed to work - in the past
Rotmans, 2002
INTEGRATED ASSESSMENT
Interdisciplinary process of combining
different strands of disciplinary knowledge
to coherently represent complex societal
problems of interest to decision-makers
RELEVANT RESEARCH FIELDS
RISK ANALYSIS
TECHNOLOGY
ASSESSMENT
INTEGRATED
ASSESSMENT
POLICY
ANALYSIS
HISTORY
• Early Seventies Club of Rome
first global computer simulation models linking
population, pollution and resource depletion
• 1980s
IA-models for environmental issues, e.g. acid rain
• 1990s
IA-models for global climate change
• 2000IA-models for sustainable development
IMPORTANCE of INTEGRATED ASSESSMENT
Agenda setting
Strategical
policy making
Political
Implementation
decision making
IA MODEL FOR CLIMATE CHANGE
Social and economic processes
Land cover
processes
Atmospheric
& climate
processes
Processes of economic and
Pressure
State
Impact
ecological impacts
Interventions
forcing
feedback
human interventions
Response
METHODS OF INTEGRATED ASSESSMENT
Analytical methods
natural scientific basis
• models
• scenarios
• uncertainty / risk
analysis
Participatory methods
social-scientific basis
• dialogue method
• policy exercises
• mutual learning
EVOLUTION OF IA-TOOLS
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•
•
•
•
•
supply-driven
mono-disciplinary
technocratic
objective
certainty
predictive
from
to
to
to
to
to
to
demand-driven
inter-disciplinary
participatory
subjective
uncertainty
explorative
EVOLUTION OF IA-TOOLS
Shackley & Winne (1998)
we used to build
truth machines
but now we build
heuristic tools
INTEGRATED ASSESSMENT
Insights from two decades of sustainability assessment:
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generic tool for integrated assessment is not possible
diversity of tools hinders practical use in policy-setting
inter (and trans-)disciplinary approach is required
subjectivity and plurality of sustainability needs to be
incorporated in our tools
• current paradigm underlying integrated assessment
has reached its limits
INTEGRATED ASSESSMENT
Limits of current paradigm:
• rational actor paradigm
• standard equilibrium approximation
• single scale representation
• market failures rather than system failures
NEW PARADIGM EMERGING
• inter- and transdisciplinary
• complex systems theory as overarching mechanism
co-evolution, emergence and self-organization
• evolutionary management approach
forget about command-and-control
• co-production of knowledge
• learning-by-doing and doing-by-learning
• system innovation rather than system optimization
NEXT GENERATION OF ISA-TOOLS
methodological challenges
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•
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uncertainty
social-cultural dimension
multiple scaling
stakeholder representation
discontinuities and surprises
transition dynamics
MULTIPLE SCALING
Various modelling approaches to multiple scaling
1. Grid-based models
system dynamics type of models
2. Cellular Automata models
intelligent cell communication models
3. Multiple scale models
land allocation regression models
Integrated
Dynamic
Model
Cellular Automata Modelling
• dynamics is more determined by macroscopic trends
than by microscale dynamics
• rules for determining the suitability are controversial
• rules behind 'clustering mechanism' are not well known
• reliability of CA models on macro-scale seems low,
just as reliability on the long time scale
Grid-Based IA Modelling
• social, demographic, economic and technological driving
forces are not represented at the grid level
• states and impacts changes are represented at the grid level
(e.g. 0.5 x 0.5)
• no dynamic interactions among the grid cells
• grid cell output suggests more precision than can be fulfilled
Multiple-scale Modelling
• relatively coarse scale on which land use trends are
calculated and the land use driving mechanisms that
act over longer distance
• relatively fine scale on which the local land use patterns
are calculated, taking local constraints into account
• the dynamics of changing land use is based on
correlations and not on causal mechanisms
• quasi-static method which is more directed towards the
spatial than the temporal component
Recommendation
Why not try combinations of system dynamics,
cellular automata and multiple scale models?
UNCERTAINTY
Source:
refers to the origin of uncertainty
Type:
how uncertainty manifests itself in
a particular context
TYPOLOGY OF UNCERTAINTIES
Natural randomness
inexactness
lack of
observations/
measurements
Value diversity
Behavioural
variability
Societal
randomness
Uncertainty
due to
variability
practically
immeasurable
Uncertainty
due to lack of
knowledge
conflicting
evidence
ignorance
Technological
surprise
unreliability
indeterminacy
structural
uncertainty
SOURCES AND TYPES OF
UNCERTAINTY IN IA-MODELING
inexactness
Uncertainty in
model quantities
((technical uncertainties)
Uncertainty about
model form
(methodological
uncertainties)
Uncertainty about
model completeness
(epistemological
uncertainties)
uncertainties
in input data
parameter
uncertainties
uncertain
equations
lack of
observations/
measurements
practically
immeasurable
model structure
uncertainties
conflicting
evidence
uncertain levels
of confidence
ignorance
uncertainty about
model validity
indeterminacy
Uncertainty due
to variability
RECOMMENDATION
Build in pluralism into models
• uncertainties can be estimated according to different
perspectives
• perspective-based model routes
• integration of participatory processes and modelling
approaches
AGENT REPRESENTATION
two schools of agent representation:
• emergent behaviour
behaviour of agents ‘emerges’ primarily through
interaction with other agents [genetic algorithms]
• rational behaviour
prescribed rules for agents behaviour according to
rational decision rules [neo-classical economics]
SCALE REPRESENTATION OF AGENTS
Macro level (landscape)
(trans-)national authorities
Meso level (regimes)
institutions/organisations
Micro level (niches)
individual agents
RECOMMENDATION
• combination of emergent behaviour & rational behaviour
deliberative behaviour
• different modes of behaviour under different
circumstances
• automat: decision agent with a cognitive cell, linked to a
memory cell, and external stimuli
AGENT MODEL
Personality
Abilities
-time
-money
-age
-children
Locus of control
threshold
Peers
Intermediaries
Media
Uncertainty
Location
Cognitive processing
Deliberation
Repetition
Imitation
Social comparison
Mental map
time | source | dest. | loc. | p | # visitors | conflict
Decision
Experience
Intermediaries
Peers
Transition dynamics
• macro-meso-micro level dynamics
• four different stages of transition
• co-evolution, emergence and self-organisation
• niche- and regime players
• transformative change
Transition Model
• agent based
• market and physical infrastructure representation
• regime, niche and empowered niche as agents
regime = ICE
niches = hybrid cars, biofuels, hydrogen cars
empowered niche = public transport
• key concept is support for agents from consumers
• landscape developments and lifestyle changes
Fossil Fuel
Signal
Ecological
Signal
I
II
III
Economic
Signal
IV
Physical
Infrastructure
Signal
Initial results
Integrated Sustainability Assessment
‘MATISSE’ definition
ISA is a cyclical, participatory process of scoping, envisioning,
experimenting and learning through which a shared interpretation
of sustainability for a specific context is developed and applied
in an integrated manner in order to explore solutions to persistent
problems of unsustainable development
ISA conceptual framework
Scoping stage [shared
interpretation of what
sustainability means]
Learning
and
evaluating
stage
[learning-bydoing and
doing-bylearning]
Envisioning
stage
[sustainability
vision with
pathways]
Experimental stage
[testing visions, pathways
and policy options]
CONCLUSIONS
• we need a new paradigm for assessing sustainable
development: a transformative paradigm
• we need to invest more effort in improving the
methodological basis of our IA-tools
scaling / agent representation / uncertainty
• we need to invest substantially more in ISA-tools:
innovative, integrated and interactive [ triple-I ]