HAN-SHEN CHEN2026-10-162026-10-162026-09-01Pure ID: 15386420Pure UUID: d1f0d937-4044-4439-ab18-62400c44e43d10.1016/j.indic.2026.101318https://www.scopus.com/pages/publications/105038724417https://scholars.csmu.edu.tw/handle/123456789/26363Small Island Developing States (SIDS) face a critical “development paradox”: economic reliance on tourism often compromises ecological security, which is essential for sustainability. However, existing assessment tools suffer from a “biophysical bias” in accounting and lack predictive capability in “data-scarce” environments. This study establishes a hybrid diagnostic-prognostic framework integrating the Emergy Ecological Footprint (EEF) with the Grey prediction model GM (1,1) to bridge these gaps. Empirically applied to Liuqiu Island, Taiwan (2010–2029), the framework yields three pivotal insights. First, the diagnosis reveals a structural “metabolic rift”: imported food consumption accounts for the largest share of the footprint (52.37%), indicating the dominant role of consumption-driven pressure in the island's ecological system. Second, regarding future trends, the model provides indicative trend projections, despite limited longitudinal data. The forecast suggests a potential shift around 2022, where the ecological security status may move from “Slightly Unsafe” (Grade 3) to “Relatively Safe” (Grade 2), although this pattern should be interpreted as a model-derived projection rather than as causal evidence of policy effects. Finally, this study demonstrates that the hybrid framework can serve as a proactive, trend-based early warning reference, supporting island managers in transitioning from retrospective accounting to more forward-looking, evidence-informed decision-making under rigid resource constraints.enEcological security and early warning in data-scarce islandsA hybrid emergy-grey predictive frameworkjournal article