Scenario development Part 1: Concepts Kasper Kok Wageningen University, the Netherlands ATV Vintermøde Vingsted 5-6 Marts 2013
The overarching problem The world is now moving through a period of extraordinary turbulence; the speed and magnitude of global change, the increasing connectedness of social and natural systems at the planetary level, and the growing complexity of societies and their impacts upon the biosphere result in a high level of uncertainty and unpredictability (Gallopin, 2002) High speed of change Increased connectedness Growing complexity Lead to: High uncertainty Unpredictability
Complex or wicked problems Wicked problem: A problem that is difficult or impossible to solve because of incomplete, contradictory, and changing requirements. Because of complex interdependencies, the effort to solve one aspect may create other problems. Complex problem: A problem with many relationships between parts that give rise to collective behaviour of the system.
Methods and tools to tackle complex problems relevant to scenarios Methods: 1. Multi-scale Focus on cross-scale interactions 2. Participation - Social learning, negotiation, stakeholder perspectives 3. Interdisciplinarity Focus on better integration of social factors Tools: 1. Models Spatially explicit 2. Scenarios multi-scale, participatory storylines
Interdisciplinarity: The SCENE Model / PPP Society (People) Institutions Environment (Planet) Economy (Profit)
Interdisciplinarity: Bridging Paradigms Man and wellbeing man versus environment wellbeing versus welfare Nature and Environment environment versus economy Economy and welfare
Interdisciplinarity: A societal problem Deforestation Environmental Social Economic Soil erosion Desertification Loss biodiversity Migration patterns Happiness Cultural identity Price of timber Price of crops CBA analysis is integrated by nature
Interdisciplinarity: an integrated view Multi-scale Multi-theme Multi-sectoral and thus Multi-disciplinary
Examples of functional scales Log time (years) Landscape Forest century Tree Stand decade year months Leaf Branch Crown days cm m 100m 100km Log space (meters)
Analogy with land use systems (according to ecologists) Log time (years) Agroecological Zone Watershed century decade Village year months Farm Plot Field days m 10m 1000m 100km Log space (meters)
Ecosystem = Land use system Both consider interactions of flora and fauna Both are complex systems Ecosystems are goal free Humans drive land use change - traditions - cultural identity Land use systems are open - information flow - energy flow (manpower, fertilisers)
Conclusions - scale Scale has been on the (land use modelling) agenda for > 20 years, but it is still relevant! Attention shifted from multi-scale to cross-scale, and from downscaling to upscaling Multi-scale methods and models are now common Ecological theory is still dominating, but new concepts are being developed The scale concept is intrinsically linked to: Non-linearities Feedbacks Aggregation/disaggregation
Scenarios - background Scenario comes from the dramatic arts. In theater: it is an outline of the plot; for a movie: a scenario details relevant to the plot (before 1940s) Roots trace back to the Manhattan project (1940s) Kahn & Weiner used scenarios in a series of strategic studies for military planning purposes (1950s) Scenarios were refined at Royal Dutch/Shell and Shell became a leader of the scenario approach to business planning (1970s and 1980s). First scientific scenarios: Limits to Growth (1972) First global environmental scenarios: Global Scenario Group (1990s) Today, scenario development is used in a large variety of different contexts ranging from political decision-making, to business planning, to local community management, and to global environmental understanding
Scenarios when to use? Low uncertainty High uncertainty High causality Predictive Explorative Low causality Projective Speculative
Scenarios when to use? Scenarios are a good tool when: Uncertainty is high, and Controllability is low, or Complexity is high, or Causality is high
Scenarios - definition There are many definitions, with only partial agreement. Two important ones are: Scenarios are plausible descriptions of how the future may develop, based on a coherent and internally consistent set of assumptions about key relationships and driving forces. (focus on system description) Scenarios are credible, challenging, and relevant stories about how the future might unfold that can be told in both words and numbers. (focus on value for end users and other stakeholders)
Scenarios - purpose Environmental scientists (focus on results): Scenarios are a good tool for an integrated analysis of a complex problem. Scenarios provide in-depth insight in complex societal problems. Social scientists (focus on process): Scenarios are a good tool for communication, conflict management, and long-term participation. Scenarios provide an excellent tool for communication.
Two crucial types of scenarios The goal is to develop and combine: Qualitative scenarios, or narrative storylines. Thus, we expand our mental model beyond conventional thinking and trend extrapolation, and include more surprising developments. The relevant question that scenarios can answer is not whether an event could happen, but what we could do if it did happen. Quantitative scenarios, based on spatially explicit models. Thus, we bring together the state of the art on data and modelling techniques leading to detailed model explorations.
Vend rundt og tal med kollegaen bag ved: I hvilke tilfælde har du brugt scenarier, eller kunne tænke dig at bruge scenarier? Hvad var oplevelsen med scenarier, var det nyttigt?
Scenario development Part 2: Method and example Kasper Kok Wageningen University, the Netherlands ATV Vintermøde Vingsted 5-6 Marts 2013
Story-And-Simulation approach Narrative storylines Model runs
A toolbox of methods
Scenarios examples: semi-quantitative (FCMs)
Scenarios examples: semi-quantitative (FCMs)
Scenarios examples: quantitative spatial models
Scenarios towards a toolbox
SCENES: Water scenarios for Europe Overall aim: To develop and analyse a set of scenarios of Europe s freshwater futures up to 2050, providing a reference point for long-term strategic planning; alert policy makers and stakeholders; and allow river basin managers to test water plans
Scenarios: Exploratory and normative Scenario development in four steps: Step 1: agree on main drivers and uncertainties Step 2: first-order draft of long-term, diverging storylines Step 3: final draft with info from models Step 4: create a set of short-term, converging strategies
Scenarios: Exploring and backcasting Current situation Plausible futures 2050 based on GEO-4 Short-term actions Current situation Exploring Backcasting
Backcasting: a definition Definition: Backcasting involves working backwards from a particular desired future end-point or set of goals to the present, in order to determine the physical feasibility of that future and the policy measures that would be required to reach that point. (Robinson, 2003) The emphasis in backcastsing is upon determining the freedom of action, in a policy sense, with respect to possible futures. (Robinson, 2003)
Backcasting: background Method bears similarities with SCENES overall method (1. develop long-term visions; 2. do backcasting; 3. define action agenda and implementation) Focus much less on forecasting, stories, and models Forecasting part is usually only a vision Vision mostly has normative aspects
Backcasting: key concepts Test how effective policy measures or other actions are, by evaluating them in a number of plausible futures Evaluate the plausibility of the storylines that have been used (can the future endstate envisioned in the story be reached with a set of concrete policy measures?) Identify ultimately a set of (policy) actions that will lead to a more desirable future, independent from the future that is portrayed, i.e. that form a robust strategy. In other words, translate 4 diverging long term scenarios to one set of robust policy actions.
Backcasting: methodology A backcasting exercise consists of the following steps in group work: 1. Define a desirable endpoint 2. Define desirable intermediate milestones and objectives 3. Define obstacles and opportunities given the storyline that you find yourself in. 4. Iterate 2 and 3 5. Identify and specify (policy) actions that need to be taken 6. Iterate 2-5
Backcasting: methodology A backcasting exercise consists of the following steps in plenary: 7. Compare actions across 4 scenarios and identify similarities and differences 8. Construct a robust strategy consisting of (policy) actions that are effective in a large number of backcasting exercises.
Example (hypothetical) A A A A A A Milestone A A Milestone Milestone End point A A Milestone Milestone 2010 2020 2030 2040 2050
Conclusions (the role of scenarios) Scenarios are crucial in understanding and structuring uncertainty, and therefore in addressing complex problems Scale issues are considered but not particularly upscaling of local scenarios deserves more attention Scenarios are usually integrated, but the domination of environmental sciences is worrying Most exercises include stakeholders Models and qualitative products are increasingly combined
Models (quantitative scenarios) Conclusions (tools) Is an excellent tool, but realise the limitations in flexibility, data availability, involvement of non-experts Scenarios (qualitative storylines) Is an excellent tool with growing interest, but realise limitations in quantitative results. Story-And-Simulation (models and narratives) Very resource demanding (time and money). This is normally impossible in any smaller project. A growing set of tools is becoming available to maintain level of creativity and diversity without sacrificing structure and exactness