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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 • • • • • • 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: • • • • 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 • • • • • • 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 ]