Excessive nutrients in surface and ocean waters cause nutrient pollution, which is responsible for water quality degradation in more than 60% of coastal rivers, bays, and seas in the U.S. With a continuous nutrient supply, certain phytoplankton species (e.g., Karenia brevis) can outcompete other species and become disproportionately abundant under distinctive environmental conditions, forming what is commonly known as red tides. The economic impacts of red tides in the U.S. are estimated to be at least tens of million dollars per year. It is imperative to reduce the risk of red tides as a geohazard and to increase the associated resilience of coastal communities. The needs of simulating red tides and estimating their socio-economic impacts may be addressed by using recently developed Earth System Models (ESMs), because ESMs provide simulation results for various Earth system phenomena at multiple scales (e.g., global and regional) and the results may be used directly for understanding red tide occurrence.  

This interdisciplinary project explored for the first time whether the ESMs can be used as a ready-to-use software infrastructure for simulating red tide occurrence. This project also explored whether Earth system modeling results can be used to fill a data gap for estimating socio-economic impacts of red tides, which has not been attempted. This project used the State of Florida as a study site, where red tides have been a serious threat to the ecosystem and economy of many coastal communities. A benchmark problem selected for Earth system modeling was the loop current at the west Florida shelf, because previous research found that the loop current is a necessary condition for a large red tide bloom to occur. Our project found that, while the loop current can be simulated by ESMs with the resolution of 10km, it cannot be simulated by ESMs with the resolution of 100km. It is therefore necessary to select the appropriate ESMs for red tide simulation. We thus developed a prescreening-based subset selection method to first select a subset of ESMs and then use an ensemble modeling approach for improving red tide simulation. We further developed an optimal model weighting approach for estimating ESMs weights to improve simulation results of red tide occurrence. Since the research approaches are mathematically general, they can be used for studying the red tide problems not only in Florida but worldwide, given that ESMs results are readily available for the entire Earth.  

Our project also laid out three approaches of using ESMs results for environmental management of red tide problems at the regional scale. There are still knowledge and data gaps for directly using ESMs results for environmental management, and one of them is related to using ESMs results for socio-economic impact assessment. To fill the gap, we developed an exposure-response model that predicts emergency department visits due to respiratory disease caused by red tides. Using this model, we estimated for years with “high,” “medium,” and “low” HAB activity, and developed multiple scenarios related to climate changes. Using the average cost to patients of an emergency department visit, we modeled the impact of respiratory emergency department visits on the economy using REMI. We predicted that average annual respiratory ED visits from all causes will be between 5,365 and 5,877, and the average annual reduction in GDP will be between $19.8 million and $22.5 million.

This project supported one post-doc, three (two female) graduate students, and four (three female) undergraduate students, and they received interdisciplinary training when working on the project. The post-doc joined the faculty at the Florida Gulf Coast University in 2022, and the graduate students graduated in 2021 and 2022. The PIs of the project incorporated the research results into their classroom teaching and curriculum development. Research results of this project were disseminated to a broad audience in multiple communities. Three peer-reviewed journal articles and two book chapters were published, and a number of presentations were given at international conferences. The project team also outreached to the general public at the local, state, and federal levels. In particular, the research team prepared youtube videos, developed GitHub sites, and Zenodo sites for sharing information, computer codes, and data online by following the FAIR principles to improve the Findability, Accessibility, Interoperability, and Reuse of digital assets.

Last Modified: 01/02/2024
Modified by: Ming Ye