using indicators to develop sustainability scenarios
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Using Indicators to Develop Sustainability Scenarios. Presentation For The 20 JunE 2007 CSIN Learning Event Eric Kemp-Benedict Sivan Kartha Stockholm Environment Institute. What Are Scenarios?. Coherent stories of the future told to inform current decision-making - PowerPoint PPT PresentationTRANSCRIPT
PRESENTATION FOR THE 20 JUNE 2007CSIN LEARNING EVENT
ERIC KEMP-BENEDICTSIVAN KARTHA
STOCKHOLM ENVIRONMENT INSTITUTE
Using Indicators to Develop Sustainability Scenarios
What Are Scenarios?
Coherent stories of the future told to inform current decision-making
They include qualitative description, to capture: Cultural influences, values, behaviors Shocks, discontinuities Texture, richness, imagination, insight
They are supported by quantitative analysis, to provide: Definiteness, explicitness, detail Consistency Technical rigor, scientific accuracy
They are not predictive. They describe futures that could be, rather than futures that will be, because…
Predictions about the future rarely come true!
Sources of Uncertainty
IgnoranceOur understanding is limited.
SurpriseComplex, chaotic systems can alter directions in unexpected and novel ways.
VolitionHuman choice matters.
?
Scenarios for Participation
Scenarios can be used to● Expand the range of perspectives considered ● Share understanding and concerns.● Explore and explain competing approaches to
problems ● Uncover assumptions and rigorously test them. ● Expose inconsistencies in thought and
assumptions● Provoke debate● Identify options and make decisions
Scenarios for Information
Scenarios can be used to● Illuminate potential problems, and bring
future problems into focus● Explore alternative responses in the face of
uncertainty, and test them against different possible future paths.
● Clarify and communicate complex information and technical analysis
● Evaluate policies and help us make decisions despite the uncertain future.
Scenario Examples at Global Level
UNEP Global Environment Outlook (GEO)Intergovernmental Panel on Climate Change
(IPCC)Global Scenario Group (GSG)Millennium Ecosystem Assessment (MA) –
partially implementedComprehensive Assessment of Freshwater for
Agriculture (CA)
The Problem With Quantitative Scenarios
Want to engage a diversity of stakeholders Many do not have necessary background Tendency toward extreme views
Over-valuing quantitative inputs Devaluing quantitative inputs
But few techniques exist No standard methods for combining qualitative and
quantitative A key problem: being actively explored
And besides, too many techniques exist A wide variety of techniques for quantitative analysis,
applicable in diverse settings – which is best?
Why Can’t Modeling Be a Separate Activity?
Physical processes In principle, should not be a problem but… Important to reveal uncertainties – sometimes estimable Even for physical processes there are problems (beyond this
talk) See Beck, Environmental Foresight and Modeling: A
ManifestoEconomics, Epidemiology, and other quasi-social
Useful if conclusions not stronger than analysis can support Questionable for scenarios
Social processes Needed assumptions are central to scenarios Self-contained models have a poor track record in practical
applications
Indicator-Driven Development
1. Start with the narrative2. Identify
Mental models embedded in the narrative Indicators that are relevant to the story
3. Design models so that they Calculate a useful subset of the quantitative indicators Make use of available research Reflect or challenge narrative authors’ mental models
(where possible and appropriate)
4. Take an iterative and incremental approachIDD does not give you the model design. It just
gives structure.
Indicators
Used to Characterize Evaluate Discriminate
May be qualitative or quantitativeCan show
Rates of change State of the system
Informal definition: “Anything you want to see on a graph”
Why Indicator-Driven Approach?
Focuses on the quantitative outputs of most use to the model’s ultimate audience
Keeps the scope of analysis manageableSupports a better balance of relevance and
respectability Relevance: Calculates the indicators that are desired Respectability: Uses recognized modeling methods
and tools
Gives coherence to overall study Consistent set of indicators
The Goal
Exogenous Inputs
Indicators
The modeler’s job
Hypothetical Example for a Single Calculation
Causal chain Smooth price fluctuation Stabilize export crop Stabilize farmer
income Lower rural-to-urban migration Model
Empirical model Farmer Income ~ Crop Price, Climate Rural Employment ~ Crop Price, Climate
Migration model Gravity model
Scenarios Vary crop price Vary urban wage and employment Stochastic climate input Estimate migration
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Steps for an Entire Project
1. Specify boundaries2. Select and prioritize indicators3. Decide on a model structure4. Time estimation
a) Estimate timeb) Decide on a schedulec) Revise scope if necessary
5. Do 2-3 iterations ofa) Developb) Testc) Documentd) Release
6. Release final scenarios
Example: Identifying Indicators/Planning
Example: Model Structure
Indicator Non-plantation
biomass production
Specified Inputs Agricultural
production
Additional Inputs
Grazing land area Plantation area Non-biomass
fraction of dung and residues
Example: Estimating Time & Budget
Example: Implementation
Example: Tracking Progress
Conclusion
Indicator-Driven Development can help with Planning a scenario modeling exercise Improving focus Tracking progress
Using indicators to structure a scenario model can Make a project more coherent Better support the goals of the audience for the scenarios
And also… Provide a natural interface with tools such as IISD’s
Dashboard of Sustainability