Abstract
The United Nations’ Agenda 2030 marks significant progress towards sustainable development by making explicit the intention to integrate previously separate social, economic and environmental agendas. Despite this intention, the Sustainable Development Goals (SDGs) which were adopted to implement the agenda, are fragmented in their formulation and largely sectoral. We contend that while the design of the SDG monitoring is based on a systems approach, it still misses most of the dynamics and complexity relevant to sustainability outcomes. We propose that insights from the study of social-ecological systems offer a more integrated approach to the implementation of Agenda 2030, particularly the monitoring of progress towards sustainable development outcomes. Using five key features highlighted by the study of social-ecological systems (SESs) relevant to sustainable development: (1) social-ecological feedbacks, (2) resilience, (3) heterogeneity, (4) nonlinearity, and (5) cross-scale dynamics. We analyze the current set of SDG indicators based on these features to explore current progress in making them operational. Our analysis finds 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. Our findings suggest limited use of complex SES science in the current design of SDG monitoring, but combining our findings with recent studies of methods to operationalize SES features suggests future directions for sustainable development monitoring for the current as well as post 2030 set of indicators.
Highlights
The major challenges currently facing the world, including persistent poverty, rising inequalities, biodiversity loss, and climate change, are increasingly recognized as the emergent outcomes of complex social and ecological interactions [1,2,3,4]
The study of complex adaptive systems has highlighted that interactions between individual and diverse components or actors results in emergent behavior or properties at a macro-level that cannot be predicted from micro-level components or properties [37,38,39]
We clarify the core features and explain how we applied each feature to evaluate the Sustainable Development Goals (SDGs) indicators. Through this analysis of current indicators, we present a set of recommendations to harness the potential value that may be added by an social-ecological systems (SESs) perspective
Summary
The major challenges currently facing the world, including persistent poverty, rising inequalities, biodiversity loss, and climate change, are increasingly recognized as the emergent outcomes of complex social and ecological interactions [1,2,3,4]. The study of complex adaptive systems has highlighted that interactions between individual and diverse components or actors results in emergent behavior or properties at a macro-level that cannot be predicted from micro-level components or properties [37,38,39] This challenges the assumption underlying many system approaches, that micro-level monitoring of separate social, economic, and ecological variables can be reconstructed to understand sustainability outcomes including trade-offs or possible future scenarios. SES is defined as complex adaptive systems, with strong interdependence and irreducibility between social and ecological systems across multiple scales Recent reviews of this literature have highlighted key features that constitute complex SES relevant to sustainable development, including the importance of social-ecological interactions and feedbacks, non-linear dynamics, cross-scale (spatial and temporal) dynamics, diversity, and resilience [22,27,41]. Sustainability 2019, 11, 1190 recommendations for sustainable development monitoring for the current set of indicators, as well as future improvements post-2030
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