Abstract
Pelagic sargassum (S fluitans and S natans) algal blooms and beach landings have become a regular occurrence in the Tropical Atlantic Basin since 2011; they have a variety of impacts on the marine ecosystem and blue economy. To reduce the impacts and enable effective management, forecasting and monitoring of the blooms are essential. Challenges associated with use of satellite imagery for sargassum detection in the Tropical Atlantic are spatial resolution and cloud cover, which is particularly dense in this region due to the inter-tropical convergence zone, tropical storms and hurricanes. Successful models of forecasting and prediction of pelagic sargassum are hindered by unreliable satellite data, uncertainty around windage and as well as growth and mortality. In the longer term, we aim to improve the forecast models of pelagic sargassum mat movements in open oceans by introducing evidence of the speed of travel, changing mat morphology, and size and health status of sargassum mats. To achieve this, we deployed eight trackers on floating sargassum mats in the Western Tropical Atlantic. In addition, we explore the coincidence of surface currents, wind stress and sea surface temperature as a parameter for growth on the tracker pathways. When used in conjunction with both remote sensing methods and climate data (wind, current and sea temperature), we find that GPS tracker data can facilitate more reliable monitoring of sargassum transport pathways, helps to overcome satellite-based challenges as well as model based uncertainties, and may improve the accuracy and general utility of sargassum early warning systems.
Original language | English |
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Article number | 125010 |
Journal | Environmental Research Communications |
Volume | 5 |
Issue number | 12 |
DOIs | |
Publication status | Published - 1 Dec 2023 |
ASJC Scopus subject areas
- Food Science
- General Environmental Science
- Agricultural and Biological Sciences (miscellaneous)
- Geology
- Earth-Surface Processes
- Atmospheric Science
Keywords
- detecting
- forecasting
- GPS tracking
- macroalgae
- remote sensing
- sargassum