Plankton and environmental monitoring dataset from the Iroise Marine Natural Park (NE Atlantic, 2010-2023)

This dataset presents a long-term monitoring record of phytoplankton (2010-2022) and zooplankton (2010-2023) taxonomic groups, alongside associated environmental parameters (surface and bottom temperature and salinity measurements) from the Iroise Marine Natural Park, France's first Marine Protected Area. The dataset integrates traditional microscopy-based phytoplankton counts with zooplankton imaging data obtained using the ZooScan ((Gorsky et al., 2010)-[https://doi.org/10.1093/plankt/fbp124]), as well as zooplankton biovolume and concentration data. Sampling was conducted seasonally along two main coastal-offshore transects (B and D) and at three coastal stations (Molène, Sein, and Douarnenez), capturing the spatial and temporal dynamics of plankton communities in this unique ecosystem located at the intersection of the English Channel and the Atlantic Ocean. The region is characterized by the seasonal Ushant thermal front, which creates diverse habitats supporting rich plankton communities. Phytoplankton identification was performed consistently by the same taxonomist throughout the study period, resulting in a high-resolution dataset with 573 distinct taxa across the 785 phytoplankton samples. Zooplankton samples (total number of samples = 650) were digitized using the ZooScan imaging system (Gorsky et al., 2010), with organisms automatically sorted using built-in semi automatic algorithms (random forest and convolutional neural networks) of the Ecotaxa platform (Picheral et al., 2017). Expert taxonomists then reviewed and validated the classifications resulting in 103 taxonomic and morphological groups. Individual zooplankton images are accessible through the EcoTaxa web platform for further morphometric analyses. Bibliography Gorsky, G., Ohman, M.D., Picheral, M., Gasparini, S., Stemmann, L., Romagnan, J.-B., Cawood, A., Pesant, S., Garcia-Comas, C., Prejger, F., 2010. Digital zooplankton image analysis using the ZooScan integrated system. J. Plankton Res. 32, 285–303. https://doi.org/10.1093/plankt/fbp124 Picheral, M., Colin, S., Irisson, J.-O., 2017. EcoTaxa, a tool for the taxonomic classification of images. WoRMS Editorial Board, 2025. World Register of Marine Species https://doi.org/10.14284/170 Dataset content The dataset contains three distinct tables all containing both text and numerical data.  The first dataset integrates zooplankton measurements with their corresponding environmental parameters and is organised as follows (see also units_PNMI_data_paper.csv): Metadata information (columns 1-8):Station name (column 1)Transect name (column 2)Coordinates: longitude and latitude (columns 3-4, in DD.dddd)Sampling time: date, year, month, and julian day (columns 5-8)Environmental measurements:Surface and bottom temperature (columns 9-10, in °C)Surface and bottom salinity (columns 11-12, in PSU)Biological data for each taxonomic group:Sample abundance in individuals/m³ (columns 13-116, prefix "conc_" + taxa name)Total biovolume in mm³/m³ (columns 117-220, prefix "tot_biov_" + taxa name)Mean individual biovolume in mm³ (columns 221-324, prefix "mean_biov_" + taxa name)The second dataset contains phytoplankton data and follows a similar organizational structure: Metadata information (columns 1-8):Station name (column 1)Transect name (column 2)Coordinates: longitude and latitude (columns 3-4, in DD.dddd)Sampling time: date, year, month, and julian day (columns 5-8)Environmental measurements:Surface and bottom temperature (columns 9-10, in °C)Surface and bottom salinity (columns 11-12, in PSU)Phytoplankton taxa concentrations:Surface abundance in individuals/L (columns 13-580, prefix "surface_" + taxa name)Bottom abundance in individuals/L (columns 581-1148, prefix "bottom_" + taxa name)Each taxa is provided in the third dataset with the corresponding unique identifier called aphiaID from the World Register of Marine Species ((WoRMS Editorial Board, 2025))-[https://www.zotero.org/google-docs/?PGpX2p], which enables unambiguous species identification across databases. 
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