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.

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.

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.

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.

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.

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.

This dataset presents the resulting assessment grid (based on the EEA reference grid) with the classification of chemical status of the transitional, coastal and marine waters in the context of the Water Framework Directive (WFD) and the Marine Strategy Framework Directive (MSFD). This classification has been performed using the CHASE+ tool, with classifications of the matrices ‘water’, ‘sediment’ and ‘biota’ and indicators of ‘biological effects’, as well as an integrated classification of chemical status, combining results of all matrices. The chemical status is evaluated in five classes, where NPAhigh and NPAgood are recognised as ‘non-problem areas’ and PAmoderate, PApoor and PAbad are recognised as ‘problem areas’. This is the assessment made excluding concentrations of metals. The overall area of interest used is based on the marine regions and subregions under the Marine Strategy Framework Directive. Additionally, Norwegian (Barent Sea and Norwegian Sea) and Icelandic waters (’Iceland Sea’) have been added (see Surrounding seas of Europe). Note that within the North East Atlantic region only the subregions within EEZ boundaries (~200 nm) have been included. This dataset underpins the findings and cartographic representations published in the report "Contaminants in Europe's Seas" (EEA, 2019).

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.

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.

This dataset presents the resulting assessment grid (based on the EEA reference grid) with the classification of chemical status of the transitional, coastal and marine waters in the context of the Water Framework Directive (WFD) and the Marine Strategy Framework Directive (MSFD). This classification has been performed using the CHASE+ tool, with classifications of the matrices ‘water’, ‘sediment’ and ‘biota’ and indicators of ‘biological effects’, as well as an integrated classification of chemical status, combining results of all matrices. The chemical status is evaluated in five classes, where NPAhigh and NPAgood are recognised as ‘non-problem areas’ and PAmoderate, PApoor and PAbad are recognised as ‘problem areas’. This is the assessment made excluding concentrations of polybrominated diphenyl ethers (PBDEs) The overall area of interest used is based on the marine regions and subregions under the Marine Strategy Framework Directive. Additionally, Norwegian (Barent Sea and Norwegian Sea) and Icelandic waters (’Iceland Sea’) have been added (see Surrounding seas of Europe). Note that within the North East Atlantic region only the subregions within EEZ boundaries (~200 nm) have been included. This dataset underpins the findings and cartographic representations published in the report "Contaminants in Europe's Seas" (EEA, 2019): https://www.eea.europa.eu/publications/contaminants-in-europes-seas.