Entropy-Ecological Cycles Theory (EECT): A Social-Ecological Framework for Predicting Ecosystem Collapse and Promoting Sustainable Renewal

Abstract The Entropy-Ecological Cycles Theory (EECT) provides a novel framework for predicting ecosystem collapse and fostering sustainable renewal by integrating ecological and social dynamics. We introduce the Ecological Entropy Index (EEI), calculated using Shannon entropy, salinity, biodiversity, and energy flow, weighted via Sobol sensitivity analysis and validated with satellite data (Landsat, MODIS). Analysis of Lake Urmia (Iran) shows EEI rising from 2.0 (1990) to 4.9 (2024), nearing a collapse threshold of 5.0, with a 50% biodiversity loss and salinity increase to 310 g/L. Validation in the Aral Sea (EEI = 4.2), Pantanal wetlands, and Mekong Delta confirms global applicability. Social factors, such as migration driven by ecosystem collapse, amplify EEI, laying the foundation for a Social-Ecological Entropy Index (SEEI) in EECT-IV. Circular economy interventions (e.g., water recycling) reduce EEI by 10–15%, aligning with Sustainable Development Goal 15 (SDG 15). Real-time monitoring via Google Earth Engine dashboards enhances management. Data and code are available on Figshare ([insert DOI]), supporting open science. This study invites global collaboration to advance EECT-IV for biodiversity conservation.