Published December 31, 2022 | Version v1

Dataset of micro-phytoplankton biodiversity in the Eastern Channel area from 1987 to 2019.

  • 1. IFREMER, Laboratoire Environnement Ressource Normandie, LER/N, Avenue du Général de Gaulle, 14520, Port-en-Bessin, France
  • 2. IFREMER, Laboratoire Environnement Ressource Dinard, France
  • 3. IFREMER, Laboratoire Environnement Ressource Boulogne sur Mer, France
  • 4. Normandie Universités, Université de Caen Normandie, Centre de Recherches en Environnement Côtier (CREC) - Station Marine, BP49, 54, rue du Docteur Charcot, 14530, Luc-sur-Mer, France

Description

Micro-phytoplankton communities are widely influenced by the environment and seasonal cycling. The French-English Channel is a system between the East Atlantic and the North Sea with contrasted coastal areas along the French coast. In a context of changing environment, it is crucial to understand the causes and consequences of environmental variability on marine compartments whose phytoplankton represent the first link.

Thanks to various monitoring programs such as REPHY (REPHY – French Observation And Monitoring Program For Phytoplankton And Hydrology In Coastal Waters, 2021) and RHLN (Regional Observation and Monitoring programs for Phytoplankton and Hydrology in the eastern English Channel), datasets of micro-phytoplankton diversity are available since the late 80s at a national scale.

Here, we present a subset of these datasets on micro-phytoplankton community. It gathers diversity and abundance from 1987 to 2019. Compared to the main dataset, a taxonomical review was done to ensure a correct spatial and temporal homogenization of the taxonomical denomination (description below). We also focus on 6 monitored stations along the French Channel coast; Antifer ponton pétrolier, Cabourg, Géfosse, Donville, At so and St Cast – Les Hébihens (gathering of two times series geographically close). A graphical visual of the sampling history (for the FLORTOT standard protocol) is available in the uploaded image below.

The dataset comes from a national-wide standard protocol of water sampling (Neaud-Masson, 2016). All records are stored in the Quadrige² platform, the reference information system for coastal waters in France. A compilation of the various results obtained at the French national scale was done on the last 30 years of monitoring (Belin and Soudant, 2018). The sampling is done at water surface (0-1 meter) around the high tide period (+/- 2 hours), it is fixed through lugol acid on arrivals at the lab and analysed through reversed microscopy by experts trained through a similar 2 years learning process. The taxa are identified to the lowest taxonomic level possible and names are updated according to the WORMs’ denomination base. Since 2015, evaluations (International Phytoplankton Intercomparison - IPI) are being implemented at the European scale, coordinated by the Marine Institute of Galway, to reduce identification deviations and biases between laboratories.

The columns are described as following:

  • #1 : Taxa_Name

Due to the extent of the initial dataset, both in space and time, a work of homogenization in the taxa’s denomination was applied. Therefore, associated with this dataset, we made available a table that summarizes changes applied in the nominations. It displays all the taxa initially present in the REPHY database (first column), the change in denomination applied if needed as they are not at the same resolution between stations’ laboratories, or because two species are now grouped into a common denomination. There is an “X” if the taxa is not relevant, rare, or not a phytoplankton or protist of interest and therefore it means the taxa was deleted and is not in the given dataset (second column) and potential comments or justifications (third column). It has been build and reviewed several times by the phytoplankton experts from the three Ifremer laboratories covering the stations (Dinard, Port en Bessin and Boulogne sur Mer).

  • #2 to 5 : Date, Day, Month, Year

Temporal description of the samples. Details of the sampling history are given in the image below.

  • #6 : Season

Defined as Spring = March to May; Summer = June to August; Autumn = September to November; Winter = December (Y) to February (Y+1)

  • #7 and 8 : Julian_days and week number
  • #9 and 10 : Station_FullName and Station_Code

In the REPHY monitoring program, stations are both describe by full name locations and codes. The same level of detail was kept available in this version, with : Antifer ponton pétrolier (010-P-001), Cabourg (010-P-109), Géfosse (014-P-023), Donville (018-P-054), At so (006-P-001) and St Cast – Les Hébihens (022-P-002)

  • #11: Parameter

FLORTOT (standard samples, all micro-phytoplanktonic species are identified). FLORPAR (partially identified samples in area identified as under any sanitary risk). FLORIND (additional samples taken for toxic species monitoring, or for species reaching 100 000 cells per liter or producing toxins are identified).

  • #12 : Results

Abundance (in cells.L-1), whose level of detection (lowest value) through the microscopy approach is at 100 cells per liter.

  • #13 : Class.worms2019

The taxa’s class according to the World Register of Marine Species 2019 (https://www.marinespecies.org/)

  • #14 : Rank

Taxa's taxonomical rank : Species, Genus, Family, e-species (aka: group of similar species), e-genus (aka : group of similar genus), Class, subclass, Order, Phylum, Other.

 

Files

Base_phyto_Channel.csv

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Additional details

References

  • Belin, C., Soudant, D., 2018. Trente années d'observation des micro-algues et des toxines d'algues sur le littoral. Quae.
  • Neaud-Masson, N., 2016. Observation et dénombrement du phytoplancton marin par microscopie optique photonique-Spécifications techniques et méthodologiques appliquées au REPHY. Doc. Méthode.
  • REPHY – French Observation And Monitoring Program For Phytoplankton And Hydrology In Coastal Waters, ., 2021. REPHY dataset - French Observation and Monitoring program for Phytoplankton and Hydrology in coastal waters. Metropolitan data. https://doi.org/10.17882/47248