During a good part of my early childhood my mother was a frequent visitor of my school’s principal’s office. The point was that as a young child I was maladapted, though teachers disagreed as to what that meant exactly. And although that was the situation when I was 9, I would dare to self-evaluate and say that 30 years later I am rather well-adapted.
As part of the study on Indicator Development, Selection and Use Principles for Climate Change Adaptation M&E we are looking at good practice examples in indicator development to measure climate change adaptation success. This in itself implies that adaptation can also be unsuccessful, which does not necessarily mean that harm is done. It could mean that something ‘just didn’t work’. But there are instances of unsuccessful adaptation that result in people being worse off than before. This is what I would call maladaptation.
Limited consensus on maladaptation
Just as my teachers did not agree on what constituted my maladapted behavior 30 years ago, these days authors also are not in complete agreement as to what maladaptation to climate change means.
Tompkins et al. (2005) argue that maladaptation occurs as the result of miscalculating climate impacts. The authors present maladaptation scenarios caused by various estimation errors on impacts, using coastal infrastructure projects as example. Although telling examples, it does take a rather narrow/technical view of maladaptation.
In other reports, authors see maladaptation as the failure to account for the myriad of systems and feedbacks between sectors and groups, which in turn can lead to poor decisions on adaptive responses (Scheraga et al. 2003; Satterthwaite et al. 2009; Pittock 2011). This extends to interactions with ecological systems, i.e. short term agricultural solutions resulting in the decrease of farmers’ adaptive capacity in the long run (World Bank 2010).
A group composed of 16 international specialists from different countries and fields of expertise, called iMACC (International Initiative on Maladaptation to Climate Change), led a discussion on maladaptation at the Bellagio Center in Italy (November 2012). iMACC defined maladaptation as “an adaptation process that results in increased vulnerability to climate change and/or undermines capacity for future adaptation.”
Ian Davis (ed. 2014) takes a ‘do no harm’ approach to maladaptation; “processes to define strategies and programs to build climate resilience should always incorporate an assessment of their potential negative impacts ... In cases where potential harm is identified, measures to substantially reduce or remove it should be built into the strategy and program design. To avoid creating a false sense of security, or promoting maladaptation, programs should always be based on a multi-hazard, multi-effect assessment.”
What becomes clear is that there isn’t one definition of maladaptation, though authors agree there to be an increase in vulnerability and a decrease in adaptive capacity or willingness to adapt when we talk about maladaptation. Moreover, I think we all agree that with a growing evidence-base of what constitutes 'successful adaptation' we will become better equipped to tackle maladaptation.
How to measure maladaptation?
An earlier discussion on the meaning of the concepts ‘indicator’, ‘measure’ and ‘metric’ showed that there is no clear consensus on these simple terms either, but we are still able to measure our programs’ results without the use of standardized definitions. Which gets me to measuring maladaptation; despite a lack of consensus on what constitutes maladaptation, how do we measure it?! Let us depart from what we all agree on;
1. Maladaptation increases vulnerability. We could make sure at the start of our intervention that we include the most vulnerable and ensure that adaptation actions are targeted to reduce their vulnerability. However, we need to keep in mind that ‘marginalized’ and ‘vulnerable to climate impacts’ is not necessarily the same.
The focus could also be on those elements that increase vulnerability; diminishing livelihoods, decreased access to resources, etc. The complexity here is that maladaptation does not necessarily increase the vulnerability of the intervention’s target population, but of those not part of the intervention. How far outside your target population will you measure? Another issue might be that maladaptation might decrease vulnerability in the short term but not in the long run, or vice versa.
2. A second point of agreement is that maladaptation results in a decrease in adaptive capacity, and/or decrease in the willingness to adapt. At times there is too much of a focus on one timeframe, for example by focusing on short-term coping strategies and missing the longer term impacts of such strategies. Or by focusing on the longer term adaptive strategies, but forgetting the immediate impacts of the adverse effects of climate change. Such a temporal mismatch can very well result in maladaptation and - over time - erode the willingness to adapt of the beneficiaries involved. One possibility would be to measure beyond the project’s targeted ‘timeline of results’.
3. The further development of adaptation ‘good practice’ will also help in avoiding maladaptation, by knowing what has worked and what did not, and why. One point would be to look for synergies between adaptation and broader development agendas / goals. And not just at the national level. Perhaps ask beneficiaries how adaptation interventions relate to other concerns they have, beyond climate change and extreme weather events.
What indicators can be used to measure maladaptation?
Some authors have suggested indicators of vulnerability such as household income levels should be included in ex-ante evaluations. It would be great to get some examples of organizations integrating maladaptation into their evaluations, or even their log frames / theory of change. Is maladaptation something you can even track over the course of a project, just like you would outcomes or outputs?
I look forward to hearing how you - as reader of this blog - approach maladaptation. Is it ‘do no harm’ in adaptation, or does it go beyond the concept of do no harm? And how do you, in your organization, take it into account in adaptation interventions, and how do you measure it?! Which indicators do you use?! We look forward to the discussion!
- Indicator Development, Selection and Use Principles for Climate Change Adaptation M&E, Dennis Bours, Punjanit Leagnavar, 2014.
- Davis, Ian (Ed.), 2012. “Disaster risk management in Asia and the Pacific”. Routledge, Asian Development Bank Institute, Tokyo.
- Pittock, J. 2011: National climate change policies and sustainable water management: conflicts and synergies. Ecology and Society, 16(2), 1-25
- Satterthwaite, D., S. Huq, and H. Reid, M. Pelling, and P. Romero Lankao, 2009: Adapting to climate change in urban areas: the possibilities and constraints in low- and middle-income nations. In: Adapting Cities to Climate Change [Bicknell, J., D. Dodman, and D. Satterthwaite (eds.)]. Earthscan, London, UK, pp. 3-47.
- Scheraga, J.D., K.L. Ebi, J. Furlow, and A.R. Moreno, 2003: From science to policy: developing responses to climate change. In: Climate Change and Human Health Risks and Responses [McMichael, A.J., D. Lendrum, C.F. Corvalan, K.L. Ebi, A. Githeko, J.D. Scheraga (eds.)]. World Health Organization, World Meteorological Organization, United Nations Environment Programme, Copenhagen, Denmark, pp. 237-266.
- Tompkins, E.L., et al. 2005. “Surviving Climate Change in Small Islands - A guidebook”. Tyndall Centre for Climate Change Research. United Kingdom.
- World Bank, 2010. “World Development Report: Development in a Changing Climate - Concept Note”. World Bank, Washington DC, 45pp.