three decades of Integrated Assessment: the way forward

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three decades of Integrated Assessmentthe way
forward

• Jan Rotmans
• Egmond aan Zee, 11-03-2009

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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
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INTEGRATED ASSESSMENT
Interdisciplinary process of combining different
strands of disciplinary knowledge to coherently
represent complex societal problems of interest
to decision-makers
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RELEVANT RESEARCH FIELDS
RISK ANALYSIS
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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
• 2000-
• IA-models for sustainable development

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IMPORTANCE of INTEGRATED ASSESSMENT
importance
Agenda setting
Strategical policy making
Political decision making
Implementation
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IA MODEL FOR CLIMATE CHANGE
Pressure
Atmospheric
climate
State
processes
Impact
Response
forcing
feedback
human interventions
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METHODS OF INTEGRATED ASSESSMENT
Analytical methods
Participatory methods
natural scientific basis
social-scientific basis

• models
• scenarios
• uncertainty / risk analysis

• dialogue method
• policy exercises
• mutual learning

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EVOLUTION OF IA-TOOLS

• from
• supply-driven to demand-driven
• mono-disciplinary to inter-disciplinary
• technocratic to participatory
• objective to subjective
• certainty to uncertainty
• predictive to explorative

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EVOLUTION OF IA-TOOLS

• Shackley Winne (1998)
• we used to build
• truth machines
• but now we build
• heuristic tools

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INTEGRATED ASSESSMENT

• Insights from two decades of sustainability
  assessment
• 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

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INTEGRATED ASSESSMENT

• Limits of current paradigm
• rational actor paradigm
• standard equilibrium approximation
• single scale representation
• market failures rather than system failures

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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

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NEXT GENERATION OF ISA-TOOLS

• methodological challenges
• uncertainty
• social-cultural dimension
• multiple scaling
• stakeholder representation
• discontinuities and surprises
• transition dynamics

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MULTIPLE SCALING
Various modelling approaches to multiple scaling

• Grid-based models
• system dynamics type of models
• Cellular Automata models
• intelligent cell communication models
• 3. Multiple scale models
• land allocation regression models

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Integrated Dynamic Model
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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

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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

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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

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Recommendation

• Why not try combinations of system dynamics,
• cellular automata and multiple scale models?

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UNCERTAINTY
Source refers to the origin of
uncertainty Type how uncertainty manifests
itself in a particular context
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TYPOLOGY OF UNCERTAINTIES
inexactness
Natural randomness
lack of observations/ measurements
Value diversity
unreliability
practically immeasurable
Behavioural variability
Uncertainty due to lack of knowledge
Uncertainty due to variability
conflicting evidence
Societal randomness
ignorance
structural uncertainty
indeterminacy
Technological surprise

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SOURCES AND TYPES OF UNCERTAINTY IN IA-MODELING
inexactness
Uncertainty due
to variability
ignorance
indeterminacy
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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

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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

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SCALE REPRESENTATION OF AGENTS
Macro level (landscape) (trans-)national
authorities
Meso level (regimes) institutions/organisations
Micro level (niches) individual agents
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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

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AGENT MODEL
Personality

• Abilities
• time
• money
• age
• children

Peers
Locus of control threshold
Uncertainty
Location
Cognitive processing
Deliberation
Imitation
Repetition
Social comparison
Mental map
time source dest. loc. p visitors
conflict
Decision
Experience
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Transition dynamics

• macro-meso-micro level dynamics
• four different stages of transition
• co-evolution, emergence and self-organisation
• niche- and regime players
• transformative change

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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

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Initial results
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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

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ISA conceptual framework
Scoping stage shared interpretation of what
sustainability means
Learning and evaluating stage learning-by-doing
and doing-by-learning
Envisioning stage sustainability vision with
pathways
Experimental stage testing visions, pathways and
policy options
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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