List of fish stocks referenced for the year 2018. The repository includes 477 stocks. Each stock is identified by a unique key in accordance with the ICES codification in use. Each record contains a stock identifier, a species or group of species identifier according to the ASFIS/FAO classification, the English stock name, the Latin name of the species, the assessment area according to the FAO codification of fishing sectors. When the stock assessment area groups a series of sectors, the first and last sectors in the series are separated by a dash.

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.

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

Analysis of tuna stomach contents

The maps show the network of protected marine areas (AMP) in mainland France, used to inform users of sea conditions and to inform authorities via display boards in port offices or any other public location. A protected marine area is a defined area at sea intended to protect the natural environment on a long-term basis. The list of protected marine areas is not exhaustive and not all such areas are visible due to the chart scale.

Ces travaux ont été réalisés dans le cadre de la Directive Territoriale d'Aménagement et de Développement Durable (DTADD) portée par la Préfecture de la région ex-Aquitaine. La partie I de ces travaux porte sur les valeurs du massif forestier des Landes de Gascogne. Le massif est dépositaire d’importantes valeurs et fonctions non marchandes d’intérêt général notamment : paysagères, naturalistes, hydrologiques et climatiques. Ce rapport explique également que les modes de valorisation du territoire, autres que ceux liés à la production de bois d’œuvre et d’industrie, interfèrent étroitement avec la présence même de la forêt de production : l'activité touristique, l'arrivée de nouveaux habitants et l'économie induite, ainsi que le foncier forestier.

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.

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.

Frise chronologique des millésimes de modes d'occupation des sols produits par les régions françaises et par le programme Corine Land Cover.

L’objectif général de ce projet de thèse est d’analyser et d’évaluer les données sources (actuelles et potentielles) des matrices de changements d’occupation du sol afin d’améliorer la robustesse de l’inventaire. Il s’agit d’expertiser par une démarche scientifique la pertinence des travaux réalisés annuellement pour l’inventaire UTCATF. En particulier, il s’agit de comprendre les causes des incertitudes des données sources ; compiler les données disponibles et leurs métadonnées ; étudier qualitativement les dynamiques paysagères décrites ; et redéfinir un cadre méthodologique permettant d’estimer des taux de changements plus pertinent.