Cette étude vise à établie un état des lieux de la filière bois-forêt girondine afin d'adapter les actions du Département et sa stratégie de soutien à la filière.

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

Les ministères chargés de l'écologie (Meeddm) et de l'agriculture (Maap) ont confié au Gip Ecofor une mission d'expertise collective scientifique et technique à visée prospective sur « l'avenir du massif forestier des Landes de Gascogne ». Son objectif est de mobiliser la connaissance autour d'options envisageables pour assurer l'avenir du massif forestier landais et de la partager avec l'ensemble des parties intéressées. Les document disponibles sont les rapports finaux des groupes de travail et d'experts.

Analysis of tuna stomach contents

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.

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.

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.

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 dataset on Natura 2000 sites was created in 2014 by Cogea for the European Marine Observation and Data Network. It is entirely based on spatial data from the European Environmental Agency (EEA), plus additional info, links and selected EEA data joined to the feature attributes, as well as a calculation by Cogea of marine and coastal location of features. It is available for viewing and download on EMODnet - Human Activities web portal (www.emodnet-humanactivities.eu). Natura 2000 is an ecological network composed of sites designated under the Birds Directive (Special Protection Areas, SPAs) and the Habitats Directive (Sites of Community Importance, SCIs, and Special Areas of Conservation, SACs). The dataset covers the whole EU. Following the United Kingdom’s withdrawal from the EU on 31 January 2020, it ceased to be part of the EEA’s institutional networks and governance. In the webmap the EEA dataset has been filtered by Cogea to show only (i) marine sites, i.e. sites with a marine area percentage higher than 0 (as calculated by the EEA) and (ii) sites that, even if not identified as marine by the EEA, intersect the EEA coastline or that are within a distance of 1 km from the coastline (using a 1 km inner buffer from the EEA coastline). In both cases the COAST_MAR field value=1. The EEA coastline dataset is available at https://www.eea.europa.eu/data-and-maps/data/eea-coastline-for-analysis-2. Compared with the previous version, this one includes the updated dataset 'Natura 2000 End 2020', published by the EEA in July 2021. For further information (e.g. biogeographic region, directive, habitats, sites, impact, management, species and metadata) please visit the EEA's website hosting the Natura 2000 tabular data.

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.