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Welcome to today’s What is The Future For Cities podcast and its Research episode; my name is Fanni, and today I will introduce a research paper by summarising it. The episode really is just a short summary of the original paper, and, in case it is interesting enough, I would encourage everyone to check out the whole paper.

Our summary today works with the article titled An adaptive learning process for developing and applying sustainability indicators with local communities from 2005 by Mark Reed, Evan Fraser, and Andrew J. Dougill, published in the Ecological Economics journal by Science Direct. Since we are investigating the future of cities, I thought it would be interesting to see an investigation into sustainability measurements and indicators from top-down and bottom-up perspectives. This article proposes a process combining best practices of the different paradigms as a holistic approach for measuring progress towards sustainable development.

We need tools that can both measure and help progress towards a broad range of social, environmental and economic goals. Therefore, the selection and interpretation of sustainability indicators has become an integral part of international and national policies. However, it is increasingly claimed that indicators provide few benefits to users. This is partly a problem of scale with most existing indicators being based on a top-down definition for sustainability. This may miss the local level and communities. Moreover, communities are unlikely to invest in collecting data on sustainability indicators unless this is linked to action that provides immediate and clear local benefits.

Thus, it is widely agreed that local communities need to participate in all stages of project planning and implementation of indicators. In other words, indicators must not only be relevant to local people, but the collection, interpretation and presentation also must be easily understood and used by them. Not to mention the need for their evolution as communities, circumstances and environments change. Consequently, sustainability indicators can go far beyond simply measuring progress – they can stimulate a process to enhance the overall understanding of environment and social problems, facilitate community capacity building, and help guide policy and development projects. On the other hand, participatory approaches must be handled with care as locals may not understand the global consequences of their decisions. What is needed is to provide a balance between community and higher level actions.

The literature on sustainability indicators falls into two broad methodological paradigms: one that is expert-led and top-down, and one that is community-based and bottom-up. The top-down usually reduces understandings in landscape, ecology, conservation biology, or even in economics, and it uses explicitly quantitative indicators missing the complexity of human perspectives and experiences. The bottom-up draws more on the social sciences emphasizing the importance of understanding the local context to set goals and establish priorities, and that sustainability monitoring should be a continuous learning process for both researchers and the community.

There are strengths and weaknesses in both approaches. Indicators from the top-down approach are usually collected rigorously, scrutinised by experts, and assess with statistical tools exposing trends. However, this approach often fails to engage with local communities. Indicators from the bottom up tend to be rooted in an understanding of local context and are derived by systematically understanding local perceptions of the environment and society. However, there is a danger of missing capacity to reliably and accurately monitor sustainability. Therefore, there is an increasing awareness and academic debate on the need to combine these methodologies and capture both repertoires. Unfortunately, there is a missing consensus on how to them. This paper aims to help such an effort.

There are basic steps used by both paradigms. Sustainability indicator frameworks must help those developing indicators to establish the human and environmental context that they are working in, with identifying key stakeholders and thought leaders and defining the area or system that is relevant to the problem being studied. Such frameworks also must provide guidance on how to set management goals for sustainable development, with scenario analysis to discover global and local targets from the top-down and bottom-up, and identify problems needed to be solved. They need to provide methods to choose the indicators that will measure progress holistically, accurately and objectively and indicators that can be applied locally by citizens and stakeholders. Finally, data in all framework are collected and analysed and can be used by communities to monitor changes.

Empirical research from around the world shows the benefits of engaging local communities in sustainability monitoring. However, there remains important ways in which the skills fo the expert can augment local knowledge. By empirically testing indicators developed through participatory research, it is possible to retain community ownership of indicators whilst improving accuracy, reliability, and sensitivity. It may also be possible to develop quantitative thresholds through reductionist research that can improve the usefulness of sustainability indicators. By combining quantitative and qualitative approaches in this way, it is possible to enhance learning by both community members and researchers.

Based on their findings, the authors proposed an adaptive learning process integrating bottom-up and top-down approaches with the best practices. This approach emphasises communication and perspective sharing to develop adaptive strategies in response to changing social and environmental conditions. This is a conceptual framework that describes the order in which different tasks fit into an iterative sustainability assessment cycle. The process does not prescribe tools for these tasks, but emphasises the need for methodological flexibility and triangulation, adapting a diverse sustainability toolkit to dynamic and heterogenous local conditions, something that remains a key research skill in engaging communities in any sustainable development initiative.

Following the proposed adaptive learning process, practitioners must first identify system boundaries and invite relevant stakeholders to take part in the sustainability assessment. The conceptual model of the system can be expanded to describe its wider context historically and in relation to other linked systems to identify opportunities, causes of existing system problems and the likelihood of future shocks. Based on this context, goals can be established to help stakeholders move towards a more sustainable future. Next, practitioners need to work with local users to develop strategies to reach these goals. Then, the practitioners could identify potential indicators that can monitor progress towards sustainability goals with the involvement of the locals and also creating local indicators if possible. These indicators must be evaluated by local communities and empirically tested by practitioners to ensure their accuracy, reliability and sensitivity.

After the finalisation of the appropriate indicators, it can be beneficial to establish baselines for the indicators from which the progress can be monitored. Data on these indicators must be then collected, analysed and disseminated to assess progress towards sustainability goals. Although this data analysis is usually the domain of experts, decision support systems can facilitate analysis and interpretation by local communities. If necessary, information collected from monitoring indicators can then be used to adjust management strategies and sustainability goals. Alternatively, goals may change in response to changing needs and priorities of the stakeholders that initially set them. For this reason, the sustainability process must be iterative. The adjustment of strategies can lead back to the earlier step of specifying goals for sustainable development, continuing the cycle.

By integrating approaches from different methodological frameworks, the proposed framework builds on the strengths of each and provides a more holistic approach for sustainability indicator development and application. It is possible to build on the strengths of both top-down reductionist and scientific methods to measure sustainability, and bottom-up, community-driven participatory methods in the adaptive learning process. Therefore, the proposed new framework can be viewed as both a combination of different methods that are tailored to distinct tasks and as an integration of methods to accomplish the same task. Naturally, to do this process is not easy. But by using this process, more appropriate and relevant sustainability indicators can be established.

As the most important things, I would like to highlight 3 aspects:

1. Sustainability indicators are usually from top-down or bottom-up approaches but these can be combined for a better and more relevant set of indicators.
2. The frameworks need to reflect and involve the context and the stakeholders, help to set management goals for sustainable development and choose the proper indicators, and progress can be measured with data within the indicators.
3. Sustainability indicator frameworks, as presented here, can be iterative and adaptive learning processes tailored to the specific community, with the involvement of people and experts, continuously assessing the progress and changing accordingly.

Additionally, it would be great to talk about the following questions:

1. How can be decision-makers encouraged to use such a combined approach involving more stakeholders?
2. How can be people encouraged to participate more in such assessments and provide their experiences and knowledge about their environment?
3. What can you say about your environment that can be more sustainable? How can you express this to decision-makers to be involved in the conversation?

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