This action provides funding in the amount of $749,972 to florida state university

Florida State University received $749,972 in funding from the Environmental Protection Agency (EPA) Region 4 under the Geographic Programs - South Florida Geographic Initiatives Program (CFDA 66.484) for a five-year project period (August 1, 2025 through July 31, 2030). The project will enhance ecological resiliency in the South Florida Gulf by conducting comprehensive research on Karenia brevis harmful algal blooms through remote sensing techniques, machine learning algorithms, and data/image fusion methodologies. The university will evaluate historical bloom characteristics using in-situ monitoring data and satellite imagery, develop a predictive regional model to forecast long-term bloom dynamics based on contributing factors, and assess the impact of various climate pathways on bloom characteristics.

The deliverables include performance and final reports, a unified homogenized database with consistent spatial and temporal resolution documenting K. brevis, contributing factors, and identified hotspots and hotmoments under historical conditions. Expected outcomes will provide decision-makers with scientific insights into the contributing factors of harmful algal bloom recurrence along the South Florida Gulf coast, advance understanding of relationships between K. brevis growth and anthropogenic activities, oceanographic phenomena and climate change, and generate findings to inform ongoing restoration programs. The project will directly benefit Florida state citizens and residents through improved environmental management capabilities and ecological restoration efforts. No subawards are included in this assistance agreement.

Description

This action provides funding in the amount of $749,972 to florida state university. The purpose of this project is to enhance ecological resiliency in the south florida gulf. Activities include evaluating historical characteristics of brevis blooms based on in-situ monitoring data and satellite imagery by applying remote sensing techniques, machine learning algorithms and data/image fusion, developing a regional model that predicts long-term dynamics of karenia brevis blooms based on a set of contributing factors via machine learning algorithms and time series models, and to study the impact of various climate pathways on the characteristics of karenia brevis blooms using the developed model. Anticipated deliverables include a performance and final reports, unified homogenized database with consistent spatial and temporal resolution related to k. Brevis, the contributing factors and identified hotspots and hot moments under historical conditions. Expected outcomes include helping decision makers identify the contributing factors to the recurrence of harmful algal blooms along the south florida gulf, advancing scientific understanding of the relationships between the k. Brevis growth and anthropogenic activities, oceanographic phenomena and climate change, and providing insights for the ongoing restoration programs. Direct beneficiaries include state of florida citizens and residents.activities:-subrecipient:no subawards are included in this assistance agreement.outcomes:-