Spreading and transport of the Maximum Salinity Core Layer (MSCL), defined as water with salinity higher than 36 psu, is investigated from hydrographic data sets collected along twelve cross-sections by the Sea education Association (SEA) between Tahiti and the equator from 2008 and 2015, the ARGO data objectively mapped from JAMSTEC and satellite remote sensing. Aquarius sea surface salinity data show that the MSCL occupied an area averaged over time of about 6.7 106 km² with an increase of the occupancy in 2015. The variation of the area occupied by the MSCL at the surface does not show any seasonal cycle. Hydrographic dataset are used to show the extent of the MSCL below the surface. The SEA dataset exhibits the spreading of the MSCL northward of Tahiti between isopycnals 24 σt and 25 σt and is observed as far north as 4°S. The MSCL is observed at the surface as far north as 12°S and the disappearance of the MSCL from the surface is due to input of fresher water from the equatorial region or from the west. Even tough ARGO data have a poorer vertical resolution, comparison with SEA dataset shows that the core of the MSCL is well determined. But ARGO data has a better time resolution and monthly data are available from 2001 to 2017. ARGO data allow us to visualize the whole volume of the MSCL and the westward extension of the MSCL. Geostrophic currents are calculated from ARGO data relative to the surface where surface currents are adjusted to velocities provided by the satellite derived OSCAR data set. The transport calculation shows that most of the water north of Tahiti is transported westward with the highest volume during an El Niño year.

Ulla von Ammon

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Environmental DNA (eDNA) analyses are powerful for describing marine biodiversity but must be optimized for their effective use in routine monitoring. To maximize eDNA detection probabilities of sparsely distributed populations, water samples are usually concentrated from larger volumes and filtered using fine-pore membranes, often a significant cost-time bottleneck in the workflow. This study aimed to streamline eDNA sampling by investigating plankton net versus bucket sampling, direct versus sequential filtration including self-preserving filters. Biodiversity was assessed using metabarcoding of the small ribosomal subunit (18S rRNA) and mitochondrial cytochrome c oxidase I (COI) genes. Multi-species detection probabilities were estimated for each workflow using a probabilistic occupancy modelling approach. Significant workflow-related differences in biodiversity metrics were reported. Highest amplicon sequence variant (ASV) richness was attained by the bucket sampling combined with self-preserving filters, comprising a large portion of micro-plankton. Less diversity but more metazoan taxa were captured in the net samples combined with 5 µm pore size filters. Pre-filtered 1.2 µm samples yielded few or no unique ASVs. The highest average (~32%) metazoan detection probabilities in the 5 µm pore size net samples confirmed the effectiveness of pre-concentrating plankton for biodiversity screening. These results contribute to streamlining eDNA sampling protocols for uptake and implementation in marine biodiversity research and surveillance.