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The Sargassum spp. inundations across the Atlantic and Caribbean that began in 2011 have continued unabated, and new uses for the biomass are being continuously explored. Mangroves protect shorelines, store carbon, enhance water quality, and promote biodiversity. Their restoration can be hindered by poor soils associated with urbanized coastlines. Sargassum spp. application in the form of mulch, compost, and plant tonics has yielded positive results in a range of plants. As part of transforming the inundations to benefit communities, Sargassum spp. compost (SC) was assessed in mangrove seedling production for restoration. Pure SC was mixed with soil/sand medium, as different treatments, for the production of Rhizophora mangle seedlings in “wet” and “dry” nurseries. Plants in the “wet” nursery performed poorly, with 90–100% of plants in 50 and 100% SC, respectively, dying after 6 weeks. Seedlings in all SC treatments in the “dry” nursery survived with obvious and statistically significant treatment differences. Height and number of leaves indicated the best growth in the 75% SC treatment, while the control (0% SC) had the poorest growth. Seedling health, greatest in the control, was poorest in 50 and 100% SC. Elemental analysis of SC, seedlings, and soil/sand medium indicated that several elements (Na, K, Ca, As, and Se) found in high concentrations in the SC were low in the plants. Overall, low sequestration of elements by mangrove seedlings and the reported ability of mangrove soils to reduce element mobilization through chelation indicate the potential use of Sargassum spp. in soil amelioration for mangrove restoration without proportional contamination of the ecosystem. We see the potential use of nuisance Sargassum spp. blooms to support mangrove restoration, leading to increased benefits to coastal communities being affected by the inundations.

Pelagic Sargassum species have been known for centuries in the Sargasso Sea of the North Atlantic Ocean. In 2011, a new area concentrating high biomass of these brown algae started developing in the Tropical Atlantic Ocean. Since then, massive and recurrent Sargassum influxes have been reported in the Caribbean and off the coast of Western Africa. These Sargassum events have a major negative impact on coastal ecosystems and nearshore marine life, and affect socio-economic sectors, including public health, coastal living, tourism, fisheries, and maritime transport. Despite recent advances in the forecasting of Sargassum events, and elucidation of the seaweed composition, many knowledge gaps remain, including morphotype abundance during Sargassum events, drift of the seaweeds in the months prior to stranding, and influence of sample processing methods on biomass biochemical composition. Using seaweeds harvested on the coasts of Jamaica in summer of 2020, we observed that S. fluitans III was the most abundant morphotype at different times and sampling locations. No clear difference in the geographical origin, or provenance, of the Sargassum mats was observed. The majority of Sargassum backtracked from both north and south of Jamaica experienced ambient temperatures of around 27 °C and salinity in the range of 34-36 psu before stranding. We also showed that cheap (sun) compared to expensive (freeze) drying techniques influence the biochemical composition of biomass. Sun-drying increased the proportion of phenolic compounds, but had a deleterious impact on fucoxanthin content and on the quantities of monosaccharides, except for mannitol. Effects on the content of fucose containing sulfated polysaccharides depended on the method used for their extraction, and limited variation was observed in ash, protein, and fatty acid content within most of the sample locations investigated. These observations are important for the storage and transport of the biomass in the context of its valorisation.

Additional file 1: Figure S1. Phylogeny of Alveolata. Proteomes from 89 alveolates genomes and transcriptome assemblies from the MMETSP project ( https://zenodo.org/record/257026/files/ ) were used to create orthologous groups using orthofinder v2.2 with the diamond BLAST similarity search. Single ortholog alignments were pruned using PhyloTreePruner v.1.0 (minimum taxa to keep 44 and support value 0.9) and realigned using mafft v7 and filtered with Gblocks v.0.91b (−b5 = a -p = n). Filtered alignments were concatenated using seqCat.pl and a phylogenetic tree was produced under Maximum Likelihood framework using RAxML v8.2.9 with the PROTGAMMALGF model of sequence evolution and 101 bootstraps. Asterics represent support values of 95 and above. A detailed method can be found in Kayal et al. 2018 BMC Evol. Biol. ( https://doi.org/10.1186/s12862-018-1142-0 ). The full tree can be found at http://mmo.sb-roscoff.fr/jbrowseAmoebophrya/ . Figure S2. SSU rDNA sequence identity (in percentage, relative to A25 and A120 compared to other species). Figure S3. Distribution of k-mer in A25 and A120 genomes. Figure S4. Classification of repeated elements in 3 Amoebophrya genomes (AT5, A25, and A120) using REPET. The x-axis represents the cumulated number of bases of repeated elements in the genome. Figure S5. Conserved motif of the putative splice leader (SL) in A25 and A120. Figure S6. Alignments of gene encoding the putative spliced leader (SL) gene in A25 and A120. Figure S7. Gene orientation change rate in 3 Amoebophrya genomes. Figure S8. Number of orthologs genes shared by selected taxa. Figure S9. Boxplot of the dN/dS ratios of orthologous genes between A25 and A120, calculated using the model average method (MA). Figure S10. Synteny dot-plot obtained by comparison between Amoebophrya A25 and AT5 genomes. Figure S11. Synteny dot-plot obtained by comparison between Amoebophrya A120 and AT5 genomes. Figure S12. Intron length distribution. Figure S13. GC content distribution. Figure S14. Multiple alignments of U2 snRNAs. Figure S15. Multiple alignments of U4 snRNAs. Figure S16. Multiple alignments of U5 snRNAs. Figure S17. Multiple alignments of U6 snRNAs. Figure S18. Secondary structure of Amoebophrya snRNA. Figure S19. Example of introner elements (IEs) in Amoebophrya. Figure S20. Distribution the direct repeats with size ranging between 3 and 8 nucleotides in A25. Figure S21. Distribution of the direct repeats with size ranging between 3 and 8 nucleotides in A120. Figure S22. Composition of direct repeats in introners elements. The diversity in composition of the three (a, b, c) most abundant of direct repeats in introner elements in A25 (up) and A120 (down). Figure S23. Terminal inverted repeat locations around the splicing sites in A25 and A120. The position of inverted repeats according to the location of the splice sites in A25 and A120. Left, the inverted repeats of A120 are located at 1–5 the nucleotides upstream and downstream of the splice sites. Right, the inverted repeats of A25 are located at the 1–6 nucleotides in upstream and downstream of the splice sites. Figure S24. The flowchart for the in silico search of introner elements. Figure S25. Hierarchical clustering analysis (pairwise similarity and OrthoMCL) of all intron families and of the inverted repeats in A25 and A120. Figure S26. Percentage of genes with assigned functions in relation with introns composition. Figure S27. Difference in the proportion of IEs-containing-genes compared to their KEGG assignment in A25 and A120. Figure S28. Distribution of conserved introns. Table S1. RCC number, date and site of isolation of strains considered in this study. Table S2. Metrics of Nanopore runs for the two Amoebophrya strains. Table S3. Search for pathways involved in plastidial functions that are entirely independent of plastid-encoded gene content. Table S4. Number of the different types of introns identified in A25 and A120 genomes. Table S5. Search for RNA editing in A25 and A120 introns. Table S6. Putative Amoebophrya A25 and A120 snRNP homologs. Table S7. Classification into families of non-canonical introns in A25 and A120. Table S8. RNAseq read assembly statistics of Amoebophrya A25 and A120 corresponding samples from the different time of infection and to the free-living stage (dinospore only). Table S9. Total number of contigs belonging to samples from different stages of infection and the proportion of them that were aligned against the genomes of both Amoebophrya A25 and A120. ND corresponds to “not determined” when no measurement was done. Table S10. Metabolic pathway screened in A25 and A120 proteomes.