This framework proposes a structured approach to enhance rural self-sufficiency in dispersed settlements, indicating potential pathways for intervention.
Rural territories characterised by dispersed settlement systems face mounting challenges related to demographic decline, economic fragility, ecological degradation, and the erosion of local knowledge systems. In this context, rural self-sufficiency has re-emerged as a strategic objective; yet it remains inadequately operationalised within spatial planning and territorial assessment practices. This paper proposes a bioregional framework for operationalising rural self-sufficiency in dispersed territories, integrating ecological, morphological, socio-productive, cultural, and governance dimensions across multiple spatial scales. The framework is structured around a tiered system of 108 indicators, hierarchised into priority, secondary, and aspirational levels, combined with a multi-scalar territorial reading articulated through five nested frames—ranging from municipal systems to local productive units. Rather than constituting a mere checklist for immediate quantitative evaluation, the indicator system functions as a structured diagnostic universe, enabling progressive operationalisation based on data availability and governance capacity. To bridge the gap between diagnosis and action, the framework introduces 34 strategic drivers and 28 spatial artefacts, conceived as reversible and context-sensitive interventions. The framework is demonstrated through the case of Arbo (Galicia, Spain), illustrating its capacity to structure territorial diagnosis and articulate coherent pathways from analytical interpretation to strategic spatial intervention. The proposed approach contributes a replicable methodological tool for bioregional and rural planning in dispersed settlement systems. The study contributes to advancing bioregional planning by demonstrating how extensive indicator universes can be rendered operational through selective tiering and multi-scalar deployment.
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Lima et al. (2026) studied this question.
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