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.

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

L’objectif de cette étude est d’illustrer à l’aide d’indicateurs les conséquences de choix de gestion imposés par cinq scénarios socioéconomiques prospectifs appliqués à une large zone forestière pour les 60 prochaines années. Le cas d’étude choisi est la zone centrée sur la commune de Pontenx-les-Forges dans le sud-ouest de la France et couvrant 101000 hectares. Cet article présente une description de la zone d’étude et des itinéraires sylvicoles mis en œuvre par les propriétaires forestiers selon des scénarios. À l’aide d’un simulateur pilotant deux modèles de croissance, l’évolution de la zone d’étude à l’échelle de chaque parcelle est synthétisée par 9 indicateurs sur une période de 60 ans : le volume sur pied, le carbone sur pied, le volume total exploité, la valeur commerciale sur pied, le volume de l’arbre moyen, la vulnérabilité au vent et au feu, et des indices de biodiversité. Un des principaux résultats de cette étude est de montrer l’amplitude des changements pour la production et le volume sur pied : selon les scénarios les récoltes annuelles peuvent varier de 50 % dès 2030. Par conséquent, d’autres indicateurs sont impactés comme la biodiversité, la vulnérabilité au vent ou au feu. Pourtant, l’espèce dominante est maintenue et le comportement partiellement conservateur des types de propriétaires est pris en compte. En conclusion, des améliorations pour de futures simulations sont envisagées ; dans ce but, des synergies avec la télédétection sont nécessaires pour la collecte des données d’initialisation sur de larges territoires, ce qui permettra d’améliorer la précision des résultats.

Analysis of tuna stomach contents

Shom manages a network of permanent digital coastal tide-gauges on French coasts: the RONIM Sea Level Observation Network. Most tide-gauge observatories are partnered with one or more local partners.<br /><br /> Four main types of data are available for download:<br /> - “Raw high frequency" data: raw observations neither validated nor evaluated, obtained directly from the sensor. 1-minute measurement; integration time 15 seconds (on the minute); sampling period: 1 second.<br /><br /> - "Raw non-real time" data: raw observations neither validated nor evaluated, obtained directly from the sensor. 10-minute measurement; integration time 121 seconds (around every 10 minutes); sampling period: 1 second.<br /><br /> - "Validated non-real time" data: observations checked and validated by Shom from the "Raw non-real time" data. 10-minute measurement; integration time 121 seconds (around every 10 minutes); sampling period: 1 second.<br /><br /> - "Validated hourly" data: observations checked and validated by Shom, generated from "Validated non-real time" data. Hourly measurement obtained from the Vondrak filter with triangular weighting. The hourly height cannot be calculated in the event of an observation gap greater than 1.5 hours.

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).

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.

ddRAD genotyping was used to evaluate population connectivity and putative loci under selection in honeycomb worm from 13 sites spanning its distribution in the Atlantic and Mediterranean coasts.

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.