PPRIF

The ABYSS project aims at describing deep-sea benthic biodiversity spanning several branches of the tree of life with eDNA metabarcoding tools. To accommodate both micro- and macro biologists, we designed a bioinformatic pipeline based on Illumina read correction with Dada2 allowing analysing metabarcodes from prokaryotic and eukaryotic life compartments.

The dataset presents the potential combined effects of land-based pressures on marine species and habitats estimated using the method for assessment of cumulative effects, for the entire suite of pressures and a selected set of marine species groups and habitats by an index (Halpern et al. 2008). The spatial assessment of combined effects of multiple pressures informs of the risks of human activities on the marine ecosystem health. The methodology builds on the spatial layers of pressures and ecosystem components and on an estimate of ecosystem sensitivity through an expert questionnaire. The raster dataset consists of a division of the Europe's seas in 10km and 100 km grid cells, which values represents the combined effects index values for pressures caused by land-based human activities. The relative values indicate areas where the pressures potentially affect the marine ecosystem. This dataset underpins the findings and cartographic representations published in the report "Marine Messages" (EEA, 2020).

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.

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

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 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.

Individuals from five populations of Sabellaria alveolata (Scotland, France-Saint Michel Bay, France-Biarritz, Portugal, and Morocco) were maintained under common garden conditions to investigate the gene expression response to temperature stress in the honeycomb worm. Worms were exposed to five sequential temperature treatments, and whole-organism samples were collected for RNA-Seq analysis. Gene expression patterns were analyzed to assess thermal acclimation and adaptation across populations.

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.

Ce guide a pour vocation d'informer sur les caractéristiques du risque incendie de forêt propres au massif des Landes de Gascogne, de définir les modalités de prise en compte du risque dans les documents d'urbanisme et de regrouper l'ensemble des réglementations et recommandations ayant trait à la protection contre les incendies. Il a été élaboré par l'Etat en partenariat avec l'Association des Maires des Landes et les organismes concernés par cette problématique.