Spatio-temporal variability of pelagic Sargassum landings on the northern Mexican Caribbean

Abstract

The massive influx of pelagic Sargassum (sargasso) has produced environmental, socio-economic, and human health-related problems in several Atlantic countries in the last decade. Predicting sargasso landings to areas of interest is necessary to implement management actions. To date, quantitative assessments of beach-cast volumes are scarce, making it challenging to test prediction models based on remote sensing measurements and environmental variables. In this study, we analyze the variability in sargasso beach-cast accumulation in the northern Mexican Caribbean coast in 2018 and 2019 and its relationship with: (1) wind direction and speed, (2) sea surface temperature, and (3) sargasso biomass measured with MODIS in the southwestern Caribbean Sea and the Mexican Caribbean exclusive economic zone. We use data on the monthly volume of sargasso removed from the beach by seven hotels over a 40 km section of shoreline. The mean monthly volume per kilometer of shoreline was higher in 2018 (1852 m3), but that of 2019 was also significant (1773 m3). Landing patterns were variable, with the peak months differing among sites within years and years within sites. High-volume stranding lasted seven months in 2018 and five in 2019. In both years, high beaching occurred during the summer when the wind direction was between 90° and 180° with wind speeds of 4–8 m s−1. The mean volume in the record-breaking month of 2019 (May = 6565 m3 km−1) was more significant than the highest of 2018 (June = 3816 m3 km−1). MODIS data and landing volumes showed a similar seasonal pattern, but maximum satellite signals occurred at different months than those with maximum beaching. We found a significant (p < 0.05) but low correlation (Kendall tau <0.3) between the volume of sargasso washing ashore and in situ sea surface temperature (SST), and no meaningful relationship between SST measured by MODIS and (1) sargasso abundance measured by MODIS and (2) sargasso landing volumes. The information reported in this study can help to test forecasting models and is valuable for sargasso management and valorization.