In many species of marine benthic invertebrates, a planktonic larval phase plays a critical role in dispersal. Very little is known about the larval biology of most species, however, in part because species identification has historically been hindered by the microscopic size and morphological similarity among related taxa. This study aimed to determine the taxonomic composition and seasonal distribution of meroplankton in the Barents Sea, across the Polar Front. We collected meroplankton during five time points seasonally and used high-throughput DNA barcoding of individual larvae to obtain species-level information on larval seasonality. We found that meroplankton was highly diverse (72 taxa from eight phyla) and present in the Barents Sea year-round with a peak in abundance in August and November, defying the conventional wisdom that peak abundance would coincide with the spring phytoplankton bloom. Ophiuroids, bivalves and polychaetes dominated larval abundance while gastropods and polychaetes accounted for the bulk of the taxon diversity. Community structure varied seasonally and total abundance was generally higher south of the Polar Front while taxon richness was overall greater to the north. Of the species identified, most were known inhabitants of the Barents Sea. However, the nemertean Cephalothrix iwatai and the brittle star Ophiocten gracilis were abundant in the meroplankton despite never having been previously recorded in the northern Barents Sea. The new knowledge on seasonal patterns of individual meroplanktonic species has implications for understanding environment-biotic interactions in a changing Arctic and provides a framework for early detection of potential newcomers to the system.

See: Descôteaux R, Ershova E, Wangensteen OS, Præbel K, Renaud PE, Cottier F and Bluhm BA (2021) Meroplankton Diversity, Seasonality and Life-History Traits Across the Barents Sea Polar Front Revealed by High-Throughput DNA Barcoding. Front. Mar. Sci. 8:677732. doi: 10.3389/fmars.2021.677732

The FASTQ files are housed on NCBI Sequence Read Archive under BioProject name: PRJNA725248 (https://www.ncbi.nlm.nih.gov/bioproject/PRJNA725248).

The FASTQ files combined with the ngsfilter_XXXX.csv files, the XXXX_metadata.csv files and the MeroInd_Rcode_Bioinformatics.R can be used to produce MOTU tables for all sequencing libraries. Note that R package Mjolnir and its parameterization presented here are equivalent to the OBITools software used in the article related to this dataset. 

Data from the MOTU tables are shown in their processed form in the MeroInd_IndividualData.csv file (variables: Sample, Sequence, Highest.seq, Total.reads, Percent.highest.seq). Generally, the sequence with the highest number of reads in each sample was assumed to correspond to the individual of interest. Note that in a few cases, two individuals were combined into one sample for DNA extraction, amplification and sequencing, and therefore had to be added manually in the MeroInd_IndividualData.csv file. In this case, the two individuals would have different Ind.No but would share the same Sample number. 

The MeroInd_IndividualData.csv, MeroInd_SequenceAssignments.csv, MeroInd_IDMatch.csv, MeroInd_Quantification.csv, MeroInd_Env_Summary.csv and the R code MeroInd_Rcode_DataAnalysis.Rmd are used together to produce the data analysis, figures and tables found in the related article. Note that, due to copyright issues, the temperature, salinity and chlorophyll a data cannot be included here. Most of the code can be run without these data. Please contact corresponding author for information on how to access these data if needed.

The MeroInd_StationInfo.csv datasheet shows the latitude and longitude of each sampling station as well as the dates of collection. 

All photos of individual plankton are included and are named according to Location (N vs S), Month (Nov, Jan, Apr, Jun, Aug), Depth.max, Depth.min, Photo #. 

Example: N_Apr_120_80_003.jpg represents an individual collected between 120-80m at the northern location in April. Photo #3. Note that photo numbers are only unique within a sample.