Larvae from Pacific oyster, Manila clam, European abalone and great scallop were subjected to two temperatures and two pH over the course of early development. RNAseq data was collected in order to evaluate which genes are modulated in response to stress.

Process-driven seafloor habitat sensitivity (PDS) has been defined from the method developed by Kostylev and Hannah (2007), which takes into account physical disturbances and food availability as structuring factors for benthic communities. It is a conceptual model, relating species’ life history traits to environmental properties. Physical environment maps have been converted into a map of benthic habitat types, each supporting species communities with specific sensitivity to human pressures. It is based on two axes of selected environmental forces. The "Disturbance" (Dist) axis reflects the magnitude of change (destruction) of habitats (i.e. the stability through time of habitats), only due to natural processes influencing the seabed and which are responsible for the selection of life history traits. The "Scope for Growth" (SfG) axis takes into account environmental stresses inducing a physiological cost to organisms and limiting their growth and reproduction potential. This axis estimates the remaining energy available for growth and reproduction of a species (the energy spent on adapting itself to the environment being already taken into account). It can be related to the metabolic theory of the ecology. The process-driven sensitivity (PDS) can be seen as a risk map that combines the two previous axes and reflects the main ecological characteristics of the benthic habitats regarding natural processes. Areas with low disturbance are areas with a naturally low reworking of the sediment, allowing the establishment of a rich sessile epifauna community, with K-strategy species. Areas with low SfG means that the environmental factors, even though there are not limiting, are in lower values, i.e. that it imposes a cost for species to live. In areas combining low disturbance and low SfG, big suspension-feeder species with long life and slow growth can often be found: these species are more vulnerable in case of added disturbance.

Here, our study aimed to first assess the influence of plastic on the bacterial community belonging to water, plastic and the microbiome of the giant clam and on the organism's physiology of this putative sentinel species. Our second objective was to identify bacteria whose abundance varies significantly with plastic concentration. Overall, this study will fill the gap towards a better understanding of the impact of plastic pollution on bacterial community assemblages in both inert and living environments.

The eleven collected wild strains of T. lutea were compared phenotypically, in particular with regard to their pigment and lipid profiles. The genome of each T. lutea strain was also sequenced to investigate the genetic structure and genome organisation of this species. Collected data were summarized in a genome browser to provide easy-to-use support for the scientific community (https://genomes-catalog.ifremer.fr). This provides an important resource- to understand, exploit and predict the biodiversity of this species.

Metagenomic analysis of clams from Sanaga river in Cameroon to describe the virome

ddRAD genotyping was used to evaluate population connectivity and putative loci under selection in honeycomb worm from 13 sites spanning its distribution in the Atlantic and Mediterranean coasts.

Individuals from 5 populations were kept in common garden conditions in order to examine acclimation and adaptation to temperature in the honeycomb worm. Worms were exposed to 5 temperature treatments, and collected for RNAseq analysis. Gene expression patterns were then examined.

Analysis of tuna stomach contents

Successive infections with Vibrio harveyi were conducted in two populations of the European abalone in order to examine which genes may be involved in improved survival to the disease in the St. Malo population.

UWWTD Discharge Points, Jan. 2022 is one of the datasets produced within the frame of the reporting under 11th UWWTD Art.15 reporting period (UWWTD data call 2019). The Urban Waste Water Treatment Directive (UWWTD) (91/271/EEC) obliges Member States to report data on the implementation of the Directive upon request from the European Commission bi-annually. Reported data include receiving areas as designated under UWWTD, agglomerations, urban waste water treatment plants serving the agglomerations and points of discharges. Dataset UWWTD_DischargePoints contains information on individual points of discharge from urban waste water treatment plants or collecting systems, including their coordinates of discharge, link to specific treatment plant, type of receiving area into which the effluent / wastewater is discharged, related waterbody (or river basin), information on the discharge on land and potential reuse of the treated waste water. This dataset includes the reported discharge points which are displayed on the UWWTD maps (https://www.eea.europa.eu/themes/water/european-waters/water-use-and-environmental-pressures/uwwtd/interactive-maps/urban-waste-water-treatment-maps-3). The active discharge points with correct coordinates in the reported data were selected from the source European UWWTD tabular dataset, which is available on the download link https://www.eea.europa.eu/data-and-maps/data/waterbase-uwwtd-urban-waste-water-treatment-directive-7. The definition of the UWWTD Discharge Points dataset attributes (fields) is available on the link https://dd.eionet.europa.eu/datasets/latest/UWWTDArt15/tables/DischargePoints The full (internal) dataset including inactive discharge points is available under "Urban Waste Water Treatment Directive, Discharge points reported under UWWTD data call 2019 - INTERNAL VERSION, Jan. 2022". In comparison to the previous version (Nov. 2020), late redeliveries and corrections provided by several countries during 2021 are included in current revision. Next, the dataset is provided in GeoPackage and ESRI File geodatabase formats instead of shapefile used up to now, to avoid truncation of attribute names.