2bRAD genotyping will be used to estimate genetic diversity and connectivity among populations of Sabellaria alveolata. We will relate population genetic parameters with reef state characteristics.

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.

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.

Shom manages a network of permanent digital coastal tide-gauges on French coasts: the RONIM Sea Level Observation Network. Most tide-gauge observatories are partnered with one or more local partners.<br /><br /> Four main types of data are available for download:<br /> - “Raw high frequency" data: raw observations neither validated nor evaluated, obtained directly from the sensor. 1-minute measurement; integration time 15 seconds (on the minute); sampling period: 1 second.<br /><br /> - "Raw non-real time" data: raw observations neither validated nor evaluated, obtained directly from the sensor. 10-minute measurement; integration time 121 seconds (around every 10 minutes); sampling period: 1 second.<br /><br /> - "Validated non-real time" data: observations checked and validated by Shom from the "Raw non-real time" data. 10-minute measurement; integration time 121 seconds (around every 10 minutes); sampling period: 1 second.<br /><br /> - "Validated hourly" data: observations checked and validated by Shom, generated from "Validated non-real time" data. Hourly measurement obtained from the Vondrak filter with triangular weighting. The hourly height cannot be calculated in the event of an observation gap greater than 1.5 hours.

Whole genome pooled sequencing of individuals from 4 populations and 3 different color phenotype in order to uncover the genetic variants linked to color expression in the pearl oyster P. margaritifera.

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.

Analysis of tuna stomach contents

The BEAT+ tool builds on the EEA assessment tools developed and applied in the context of assessing the degree of contamination (CHASE+), eutrophication (HEAT+) and biodiversity (BEAT+) in Europe's seas. BEAT+ makes use of the same data sets and threshold values used in these assessments but recombines these in a new framework that addresses 'biodiversity condition'. BEAT+ has been designed to provide an assessment of the spatial variability of a range of biodiversity components by combining existing biodiversity indicators. The tool integrates data from normalised indicators to identify worst case status measures for different biodiversity components. The results are then linked to a standard gridE based Spatial Assessment Unit (SAU) which is used both for biodiversity and for pressures assessments (Andersen et al., 2014). These grid-based SAUs not only allow alignment of indicators for biodiversity and for pressures but provide a means for combining large assessment areas (e.g. for wide‐ranging species) with point data collected from biological surveys e.g. WFD monitoring. BEAT+ tool works by calculating a Biological Quality Ratio (BQR) which is an aggregated score of indicator outcomes within a grid square. To allow objective comparison, the indicator outcomes are normalised to a scale of 0 to 1, with five status classes at equal intervals on that scale (from Bad starting at 0, Poor at 0.2, Medium at 0.4, Good at 0.6 and High at 0.8). By this means, indicators based on different biological criteria can be aggregated in a consistent way. This metadata refers to dataset providing the results of classification of biodiversity status using the BEAT+ tool. The status is evaluated in five classes, where High and Good are recognised as ‘non-problem areas’ and Moderate, Poor and Bad are recognised as ‘problem areas’. The dataset covers: - BQR Assessment of all marine mammals combined (mainly focused on coastal and relatively stable inshore populations of seals, dolphins and porpoises) - BQR Assessment of seabirds and wading birds - BQR Assessment of commercial fish (as these have agreed targets defined on biomass and fishing mortality) - BQR Assessment of pelagic habitats - BQR Assessment of benthic habitats - BQR Assessment of worst-performing biodiversity groups - An overall synthesis of the Biological Quality Ratios (BQR) values (showing which are the worst -lowest- BQR values in each assessment grid cell. The ‘worst’ value is used here to identify the biological group most at risk, rather than averaging over all groups to avoid over-­emphasis on groups with more intensive monitoring). As reference, please consult the ETC/ICM Report 3/2019: Biodiversity in Europe's seas: https://www.eionet.europa.eu/etcs/etc-icm/products/biodiversity-in-europes-seas. The indicator BEAT+ Integrated Assessment Worst Case BQR has been used in the EEA report 17/2019 "Marine Messages II": https://www.eea.europa.eu/publications/marine-messages-2.

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.

This dataset is the coastal zone land surface region from Europe, derived from the coastline towards inland, as a series of 10 consecutive buffers of 1km width each. The coastline is defined by the extent of the Corine Land Cover 2018 (raster 100m) version 20 accounting layer. In this version all Corine Land Cover pixels with a value of 523, corresponding to sea and oceans, were considered as non-land surface and thus were excluded from the buffer zone.