Why dealing with uncertainty and complexity?

Complexity and uncertainty are cross-cutting themes influencing the entire process of urban adaptation and resilience planning in the face of climate change. It is important to take these terms into account to know how to handle their associated challenges during urban adaptation and resilience planning. Taking proper account of uncertainty and complexity in designing and implementing climate adaptation and resilience plans and policies increases the capacity to adapt to (un)expected circumstances.

Why is it a key challenge?

Complexity

In general, complexity refers to a changing vision on what reality, real knowledge and understanding is about. Whereas (eco)systems – such as cities, organizations, societies, river deltas, nature reserves, infrastructures weather systems etc. – in the past (modernist view) were regarded as closed, more or less independent systems, a ‘complexity view’ of the world acknowledges that such systems are fundamentally open1)Cilliers, P., & Spurrett, D. (1999). Complexity and post-modernism: Understanding complex systems. South African Journal of Philosophy, 18(2), 258-274.. They are embedded within and in continuous interaction with their environment. Moreover, they are continuously moving from one state to another, from order, to disorder and new order. “This continuous movements leads to irreversible and non-linear change, to be described herein as emergence and self-organization, and adaptation and co-evolution”2)Boonstra, B. (2015). Planning strategies in an age of active citizenship: a post-structuralist agenda for self-organization in spatial planning. InPlanning.. Due to the innumerable interactions within a system (i.e. a city) and between a system and its environment (i.e. a city region or an urban-rural interface), complexity thinking reflects a fundamental shift in the extent to which systems can be understood. In the academic literature this is well illustrated by saying that in the past we looked at complicated (but understandable) systems, and now we look at complex (and non-understandable/predictable) systems. “Complex systems are systems that can produce unexpected dynamics, because of nonlinear interactions among components”3)Cilliers, P., & Spurrett, D. (1999). Complexity and post-modernism: Understanding complex systems. South African Journal of Philosophy, 18(2), 258-274..

Complexity is a key theme within the climate change agenda. Wise et al. (2014)4)Wise, R.M., Fazey, I., Stafford Smith, M., Park, S.E., Eakin, H.C., Archer Van Garderen, E.R.M., Campbell, B. (2014). Reconceptualising adaptation to climate change as part of pathways of change and response. Glob. Environ. Change 28, 325–336. detected a clear change in climate adaptation science from a problem-orientated to a decision-orientated focus. The aim is shifting towards supporting decision-makers assessing and implementing alternative policy options in a complex, dynamic and highly uncertain socio-ecological system. In this sense, adaptation pathway or route map approaches are being further developed. This approach addresses more the processes of decision making and focuses less on the outcome. It also stresses the adaptive nature of the decision process under high uncertainty and inter-temporal complexity.

What is the added value of turning towards such a complexity view within the climate change adaptation and resilience fields? Instead of putting effort into predicting the future, this shifts research and policy towards understanding relationships and appreciating diversity and interdependencies. These themes are central to climate change agendas. Moreover it helps policy makers to prepare for unknown cause-effect relationships and unpredictable futures. By doing so, the approach is not to aim to reduce complexity, but rather appreciate the dynamic multiplicity of contemporary networked societies and urban systems. This can help to strengthen adaptation and resilience activities.

Following the complexity view, policy developers and decision makers are confronted with so called complex (environmental) problems, sometimes even characterized as “wicked”5)Head, B. W., & Alford, J. (2015). Wicked problems: Implications for public policy and management. Administration & Society, 47(6), 711-739. or “super wicked”6)Levin, K., Cashore, B., Bernstein, S., & Auld, G. (2012). Overcoming the tragedy of super wicked problems: constraining our future selves to ameliorate global climate change. Policy Sciences, 45(2), 123-152. problems. “Wicked problems are generally seen as associated with social pluralism (multiple interests and values of stakeholders), institutional complexity (the context of inter-organizational cooperation and multilevel governance), and scientific uncertainty (fragmentation and gaps in reliable knowledge)”7)Head, B. W., & Alford, J. (2015). Wicked problems: Implications for public policy and management. Administration & Society, 47(6), 711-739.8)This definition illustrates how uncertainty raises complexity.. In addition Funtowicz and Ravetz9)adapted from Van Der Sluijs, J. P. (2012). Uncertainty and dissent in climate risk assessment: A post-normal perspective. Nature and culture, 7(2), 174-195 provide a very helpful typology of complex (environmental) problems by distinguishing six typical issues that decision makers have to face in complex policy making situations:

  • Decisions should be made in an early stage, before enough scientific evidence is in place
  • The error costs of decisions are high
  • Many different values, and values are in dispute
  • Large uncertainties within the knowledge base
  • Assessment dominated by models, scenarios and assumptions
  • Many hidden value loadings in problem frames, assumptions and chosen indicators. Such wicked problems, which include climate change, require decision-making processes that take into account pluralist and self-organizing networks of interdependent governmental, private, non-governmental, and societal actors. Controlled top-down decision making within neatly confined governmental structures are no longer appropriate to answer the challenges faced.

Uncertainty

There is less structured literature available on the policy maker and decision-maker perspective on uncertainty. Following the IPCC definitions, it mainly concerns institutional and market behavior and decision making and stakeholder management. Institutional and market behavior encompass both trends and macro-economic dynamics (such as crises, treaties, or even ‘black-swan events’), as well the question how policies and regulations are being developed in a multi-interest context. The latter aspect refers to the fact that very often the exact consequences of new policies and associated incentives are unclear, often due to the interaction with other regulation and the question whether policies are implemented according their original goals. So called street-level bureaucracy10)Lipsky, M. (1980). Street-level Bureaucracy – Dilemmas of the Individual in Public Services. New York: Russell Sage Foundation., path dependency11)Sorensen, A. (2015). Taking path dependence seriously: an historical institutionalist research agenda in planning history. Planning Perspectives, 20(1), pp. 17-38 and public failure12)Peters, B. G. (2002). The Politics of Tool Choice. In L. M. Salamon & O. V. Elliott (Eds.), The tools of government: guide to the new governance (pp. 552-564). Oxford: Oxford University Press. are main factors preventing laws and regulations from resulting in the intended effects. These three bodies of literature provide evidence that policy making and policy implementation are often far from (economically) rational processes. The literature on street-level bureaucracy for instances stresses that people implementing and dealing with new plans and regulations very often have their own practical realities. These realities, rather than official plans and institutions guide their behavior. Path dependency refers to the process of designing plans and new institutions. Although one might expect that these designing process is thoroughly based on serving rational policy ambitions, evidence shows that many new rules and regulations reflect how governments were dealing with policy issues before. New rules and regulations (including adaptation plans) might thus include the risk of perpetuation of old business, rather than driving radical change. Finally, public failure refers to bureaucracy and the influence that individuals within government can have on the designing process of new policies, plans and regulations. This influence, however, might be positive or negative.

Uncertainties related to decision making show close interaction with what is called in the literature science/policy interfaces. These are defined as “social processes which encompass relationships between scientists and other actors in the policy process, and which allow for exchanges, co-evolution, and joint construction of knowledge with the aim of enriching decision making”13)Van den Hove, 2007 in Kunreuther H., S. Gupta, V. Bosetti, R. Cooke, V. Dutt, M. Ha-Duong, H. Held, J. Llanes-Regueiro, A. Patt, E. Shittu, & E. Weber, (2014). Integrated Risk and Uncertainty Assessment of Climate Change Response Policies. In: Climate Change 2014: Mitigation of Climate Change. Contribution of Working Group III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Edenhofer, O., R. Pichs-Madruga, Y. Sokona, E. Farahani, S. Kadner, K. Seyboth, A. Adler, I. Baum, S. Brunner, P. Eickemeier, B. Kriemann, J. Savolainen, S. Schlömer, C. von Stechow, T. Zwickel and J.C. Minx (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA..Typical uncertainties occurring in the science-policy interface are14)Van den Hove, 2007 in Kunreuther H., S. Gupta, V. Bosetti, R. Cooke, V. Dutt, M. Ha-Duong, H. Held, J. Llanes-Regueiro, A. Patt, E. Shittu, & E. Weber, (2014). Integrated Risk and Uncertainty Assessment of Climate Change Response Policies. In: Climate Change 2014: Mitigation of Climate Change. Contribution of Working Group III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Edenhofer, O., R. Pichs-Madruga, Y. Sokona, E. Farahani, S. Kadner, K. Seyboth, A. Adler, I. Baum, S. Brunner, P. Eickemeier, B. Kriemann, J. Savolainen, S. Schlömer, C. von Stechow, T. Zwickel and J.C. Minx (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.:

  • “Paradigmatic uncertainty results from the absence of prior agreement on the framing of problems, on methods for scientifically investigating them, and on how to combine knowledge from disparate research traditions. Such uncertainties are especially common in cross-disciplinary, application-oriented research and assessment for meeting policy objectives.
  • Epistemic uncertainty results from lack of information or knowledge for characterizing phenomena. Others have noted that producing more knowledge may exacerbate uncertainty, especially when actors disagree about how to frame a problem for scientific investigation.
  • Translational uncertainty results from scientific findings that are incomplete or conflicting, so that they can be invoked to support divergent policy positions. In such circumstances, protracted controversy often occurs, as each side challenges the methodological foundations of the other’s claims in a process called ‘experimenters’ regress’.”

How to deal with uncertainty and complexity?

But how should urban planners deal with complexity and uncertainty? To choose dedicated strategies to handle complexity and uncertainty it is necessary to develop a useful typology of the two themes. By doing this, the origin of particular complexity and uncertainty related challenges can be more easily defined and therefore linked with helpful instruments and methods. This can increase the appreciation of inherent complexity and uncertainty in the field of climate change. Despite this is important to emphasize that uncertainty and complexity should not be a barrier to preparing for the consequences of the occurrence of what might appear to be highly unlikely extreme weather and climate events.

Typologies of complexity and uncertainty

What complexity characteristics should be taken into consideration
Diversity of stakeholders
Openness of the system
Continuous moving of the system
Institutional and organizational complexity
Hidden value loading in problem frames and indicators
Pressure and urgency on decision making processes

 

What uncertainty characteristics should be taken into consideration
System boundaries Boundaries are artificial. Do they encompass the relevant system or are crucial parts of the system left out the analysis?
Conceptual model Proper insight in the (causal) relationships between different components of the (urban or climate) system
Computer model Well-working algorithms and well-defined parameters
Data reliability (input) Quality and origin of the data and compatibility of data sets
Model implementation (throughput) Expertise of people handling the models
Output data Ambiguity of results à has an effect on translational uncertainty
Institutional uncertainty Path dependency, public failure
Implementation uncertainty Street-level bureaucracy. Convergence of intended policy goals and planning aims on the one hand and the implementation of the plans and urban development on the other hand
Paradigmatic uncertainty No clear problem definition and process agreement
Epistemic uncertainty Not enough knowledge to
Translational uncertainty Different interpretations of the same knowledge base possible

Methodologies to handle complexity and uncertainty

Once defined the types of uncertainty and complexity that are currently at stake, the city can choose from several methodologies to actually deal with the challenges.

For now we distinguish between three main methods to be applied: scenario analysis, adaptive policy making and the adaptation pathway approach.

 

Footnotes   [ + ]

1, 3. Cilliers, P., & Spurrett, D. (1999). Complexity and post-modernism: Understanding complex systems. South African Journal of Philosophy, 18(2), 258-274.
2. Boonstra, B. (2015). Planning strategies in an age of active citizenship: a post-structuralist agenda for self-organization in spatial planning. InPlanning.
4. Wise, R.M., Fazey, I., Stafford Smith, M., Park, S.E., Eakin, H.C., Archer Van Garderen, E.R.M., Campbell, B. (2014). Reconceptualising adaptation to climate change as part of pathways of change and response. Glob. Environ. Change 28, 325–336.
5, 7. Head, B. W., & Alford, J. (2015). Wicked problems: Implications for public policy and management. Administration & Society, 47(6), 711-739.
6. Levin, K., Cashore, B., Bernstein, S., & Auld, G. (2012). Overcoming the tragedy of super wicked problems: constraining our future selves to ameliorate global climate change. Policy Sciences, 45(2), 123-152.
8. This definition illustrates how uncertainty raises complexity.
9. adapted from Van Der Sluijs, J. P. (2012). Uncertainty and dissent in climate risk assessment: A post-normal perspective. Nature and culture, 7(2), 174-195
10. Lipsky, M. (1980). Street-level Bureaucracy – Dilemmas of the Individual in Public Services. New York: Russell Sage Foundation.
11. Sorensen, A. (2015). Taking path dependence seriously: an historical institutionalist research agenda in planning history. Planning Perspectives, 20(1), pp. 17-38
12. Peters, B. G. (2002). The Politics of Tool Choice. In L. M. Salamon & O. V. Elliott (Eds.), The tools of government: guide to the new governance (pp. 552-564). Oxford: Oxford University Press.
13, 14. Van den Hove, 2007 in Kunreuther H., S. Gupta, V. Bosetti, R. Cooke, V. Dutt, M. Ha-Duong, H. Held, J. Llanes-Regueiro, A. Patt, E. Shittu, & E. Weber, (2014). Integrated Risk and Uncertainty Assessment of Climate Change Response Policies. In: Climate Change 2014: Mitigation of Climate Change. Contribution of Working Group III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Edenhofer, O., R. Pichs-Madruga, Y. Sokona, E. Farahani, S. Kadner, K. Seyboth, A. Adler, I. Baum, S. Brunner, P. Eickemeier, B. Kriemann, J. Savolainen, S. Schlömer, C. von Stechow, T. Zwickel and J.C. Minx (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.