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.

Ce projet s’attache à étudier les phénomènes Natech imputables à des inondations/tsunami en considérant deux échelles spatiales d’analyse : l’échelle du site industriel et l’échelle du territoire. Ces deux échelles permettent d’appréhender la problématique des Natechs d’une part d’un point de vue essentiellement « vulnérabilité » et d’autre part, grâce à une analyse plus globale et profonde qui fait résonner la notion de résilience territoriale. Le travail est basé sur une analyse a posteriori (au Japon) et a priori (en France) des pratiques de gestion des événements Natech auprès des parties prenantes (industriels, collectivités, services de l’état…). Pour cela, en France et au Japon, des questionnaires, des visites et des entretiens ont été réalisés sur des territoires touchés ou potentiellement concernés par le phénomène Natech inondation/tsunami. Ces données sont employées : -à l’échelle du site industriel, pour modéliser l’impact du phénomène naturel sur l’installation (par le biais notamment d’arbres de défaillances), puis produire deux outils d’aide à la décision (diagnostic de l’Etude de danger et diagnostic du Plan d’Opération Interne lors d’un événement Natech inondation) -à l’échelle du territoire pour modéliser le processus Natech, identifier 3 zones de fragilité, définir 5 scénarios de choc. Puis, en considérant que la résilience globale d’un territoire dépend notamment de la résilience des acteurs qui le constituent proposer un outil d’audit des parties prenantes du territoire afin d’estimer la résilience de chacun d’entre eux, les pistes de progrès et, in fine, améliorer la résilience du territoire qui les héberge. Mots-clefs : Natech, Science du danger, arbres de défaillance, aide à la décision, résilience territoriale.

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.

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.

PPRIF

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

La Région Nouvelle-Aquitaine accompagne les acteurs publics et privés dans leur transition énergétique et écologique à l'horizon 2030. Avec ses 11 ambitions, la feuille de route Néo Terra guide l'action régionale et celle de ses partenaires pour la mise en œuvre d'actions concrètes. Un engagement collectif pour la Nouvelle-Aquitaine de demain.

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.

Ce jeu de données représente sous forme de polygones, les espaces situés à moins de 200m de terrains en nature de bois et forêt, appelés "zones exposées au risque feu de forêt", dont les paramètres sont précisés par l'article R133-5 du Code forestier. Ces zones sensibles au risque d'incendie de forêt comprennent les formations forestières ainsi que la zone périphérique de 200m de large les entourant. Sur cet ensemble s'applique une règlementation particulière afin d'y réduire le risque. Notamment concernant l'obligation légale de débroussaillement qui s'applique dans ces espaces, cette cartographie est annexée aux plan locaux d'urbanisme ou aux documents d'urbanisme en tenant lieu (article L134-15 du Code forestier).

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.