Environmental correlates of seasonal and interannual variations in holopelagic sargassum biomass in the Caribbean Sea

The Great Atlantic Sargassum Belt was established in 2011, resulting in the unprecedented accumulation of pelagic sargassum in the North Equatorial Recirculation Region (NERR), leading to severe sargassum influxes for the Caribbean. These influxes have been causing socio-economic challenges for the Caribbean region, particularly impacting the fisheries and tourism industries that are critical to the region’s economy. Since then, sargassum abundance inside the Caribbean has varied both seasonally - peaking in the summer months - and inter-annually, with much higher abundance in some years than others (e.g. 2018). Caribbean Sargassum variability appears to reflect the combined effects of upstream biomass supply, current-driven connectivity, seasonal atmospheric forcing, and interannual climate-ocean variability. This was determined by mixed-effects models performed using a Cosinor Model with Generalized Linear Mixed Modelling and a correlation matrix. Lagrangian analyses using currents and windage were also conducted to understand the connection between the ‘upstream’ NERR and the Caribbean, and integrated with the linear model analysis. We find that the Caribbean and the NERR have different seasonal and inter-annual variation. This is partly due to the connectivity between the two regions which helps explains movement from the source region into the Caribbean, and we find that drift from the NERR subject to 0% windage best explains Sargassum biomass in the Caribbean. At the seasonal scale, the variables linked to Sargassum variation in the Caribbean are NERR Sargassum biomass and Caribbean surface winds and sea surface salinity (SSS), along with the position of the Inter-tropical Convergence Zone (ITCZ) which contributes to the shifts in the timing of seasonal peaks. On the inter-annual scale, the Atlantic Meridional Mode (AMM) is linked to sargassum variability. Our findings can thus help improve models to forecast sargassum strandings in the Caribbean at the seasonal timescale, contributing to improved management.