Effective ecosystem-based management strategies that prevent further degradation of the ecosystem state and negative impacts on societies are needed but require cross-disciplinary and complex understandings of social–ecological systems (SES). This study defines, evaluates, and operationalises the concept of social–ecological (SE) indicators using the butterfly model based on the DAPSI(W)R(M) framework, linking drivers, activities, pressures, state changes, impacts on human welfare, and responses as measures. A review of 148 indicators developed under the marine strategy framework directive (MSFD), including contributions from HELCOM, OSPAR, the European Environment Agency, and marine-relevant UN sustainable development goals (SDGs), was conducted. Indicators were assessed across four key dimensions: mapping along the DAPSI(W)R(M) cause-effect chain; indicator complexity; normative basis; and the relationship between the indicator and its indicandum. Based on the analysis and a literature study, an SE indicator definition was developed requiring SE indicators to be compound or explicitly connect the ecological and social dimensions. Only nine of the analysed indicators qualify as SE indicators by making traceable connexions across both dimensions of the butterfly model. Existing compound indices, such as the ocean health index (OHI) and its regional adaptation, the Baltic health index (BHI), illustrate how nested, goal-oriented indices can operationalise SE integration while also highlighting challenges related to transparency and aggregation due to their nested nature. Pathways for adapting existing non-SE indicators into SE indicators are outlined, drawing on ongoing work in the SEADITO project (2024–2027) that develops SE modelling tools for the European Digital Twin of the Ocean (EU DTO). To enable compound SE indicators and support implementation within emerging digital twins of the earth, such as the EU DTO, additional criteria for SE indicators are proposed, consisting of the addition of crosscutting interlinkages and digital readiness, respectively, in addition to existing criteria of measurability, sensitivity, specificity, scalability, transferability, and precision. By clarifying what makes an indicator SE and identifying concrete development pathways, this study advances the methodological foundation for integrating SES analysis into marine spatial planning and ecosystem-based management in an era in which digital twins of the earth are accelerating the digital infrastructure for SES.
Armoškaitė et al. (Wed,) studied this question.