Agenda 2030 through the complexity lens

The 17 global goals for sustainable development and the Agenda 2030 have mostly been perceived as a significant progress in integrating previously separated social, economic and environmental agendas. Now, however, a new study contend that while the SDGs are based on a systems approach, their monitoring still misses many relevant aspects from social-ecological systems research.

“Sustainability outcomes are more than the sum of the ecological, economic, and the social parts of a system and are in fact also the result of complex interactions, feedbacks, and dynamics within and between systems,” the authors of the new study write.

The researchers behind the study published in the journal Sustainability include Odirilwe Selomane, Belinda Reyers and Reinette Biggs as well as former SRC PhD student Maike Hamann (now at University of Minnesota).

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In the article, the authors first analyse the current set of SDG indicators and then explain why and how insights from the study of social-ecological systems could improve future monitoring of progress towards sustainable development outcomes.

Five key features

In total, Selomane and his colleagues analysed all 243 SDG indicators to assess the potential value that may be added by a social-ecological perspective. This was done by comparing the indicators to five key features of social-ecological systems (SESs) relevant to sustainable development: (1) social-ecological feedbacks, (2) resilience, (3) heterogeneity, (4) nonlinearity, and (5) cross-scale dynamics.

Their analysis found that 59% of the indicators account for heterogeneity, 33% for cross-scale dynamics, 23% for nonlinearities, and 18% and 17%, respectively, for social-ecological feedbacks and resilience.

As seen above, less than a fifth of the SDG indicators account for “feedbacks” between social and ecological systems, e.g., coproduction of ecosystem services and governance of ecosystems. But what are feedbacks, really? They happen when stimuli from components of a system are fed back to their origin through one or a series of interactions, for example, when agricultural activity results in land degradation, which results in reduced agricultural activity, which in turn may result in further land degradation. This low consideration of feedbacks is a problem that has been the subject of many SDG assessments, at least in terms of trade-offs and synergies between the goals.

That only 23 % of the SDG indicators were found to account for nonlinearity is problematic because many studies have showed that unexpected, large and abrupt tipping points in social-ecological systems are common. Despite this understanding, the underlying assumptions behind most sustainable development indicators are that the phenomena they are measuring are linear. For example, the expectation that more food production will result in more food security.

The 42 of 243 indicators (17%) that accounted for resilience were mostly social indicators. Actually, all but 2 of the 42 were social indicators and mainly concerned with laws, public participation in decision making, and coordination of development assistance.

Heterogeneity was found in as many as 59 % of the indicators. Such heterogeneity can include biodiversity, diversity of knowledge systems, diversity of livelihoods, or diversity or options for response to change. Again here, much of the diversity was captured in social indicators.

Practical for monitoring

Altogether, the findings suggest quite limited use of complex social-ecological systems research in the current design of SDG monitoring. The authors conclude that this is a weakness, but also acknowledge that feedbacks, non-linearities, and resilience in social-ecological systems have hitherto not been easy to put into practice. However, they also refer to many recent advances in operationalizing social-ecological system features that could assist in improving future monitoring of progress towards Agenda 2030.

“Our findings highlight that there are areas of progress in making these features practical for sustainability monitoring. They also point to areas of sustainable development with relatively few current indicators capturing the key SES features, where future focus in SES theory development and their approaches could assist,” the authors write.