Operational Early Warning Systems and Socio-Ecological Risk in the U.S. Gulf Coast: Integrating Ecosystem Loss and Social Vulnerability, a Scoping Review

Introduction: Early warning systems reduce losses when risk knowledge, forecasting, communication, and response planning operate as an end-to-end chain, yet Gulf Coast warning practice often treats hazard dynamics, ecosystem change, and social vulnerability as separate domains. This study mapped operational early warning systems for climate-relevant hazards across Louisiana, Texas, Mississippi, Alabama, and Florida and examined whether ecosystem protective functions and social vulnerability were integrated into warning thresholds, dissemination design, and preparedness planning. Methods: I conducted a scoping review using the Web of Science Core Collection and Scopus for publications from 2020 through 18 January 2026 and targeted searches of NOAA/NWS/NHC, FEMA IPAWS, CDC/ATSDR SVI, IOOS/GCOOS, USGS, and state coastal agency portals between 15 September 2025 and 18 January 2026. Of 861 identified records, 440 duplicates were removed, 421 titles and abstracts were screened, 121 full texts were assessed, and 25 sources were included in the final charting and synthesis. Results: The review identified 11 operational systems and related platforms spanning the four early warning pillars, but routine socio-ecological integration remained limited. Louisiana showed the strongest documentation of ecosystem monitoring through CPRA and CRMS, while Florida and Texas showed more developed evacuation and dissemination interfaces. Mississippi and Alabama were represented by thinner monitoring and implementation records in the included sample. Across states, ecosystem loss and social vulnerability were used more often as planning context than as repeatable inputs to thresholds, message tailoring, or assistance triggers. Discussion: Gulf Coast practices can be strengthened through formal protocols that connect ecosystem condition and vulnerability indicators to impact-based briefings, multilingual and accessible alert workflows, and tract-sensitive preparedness actions. The findings indicate that implementation can advance by linking existing datasets to defined operational decisions and by evaluating warning performance through reach, accessibility, comprehension, and action feasibility, as well as technical accuracy.