Fronts are ubiquitous discrete features of the global ocean often associated with enhanced vertical velocities, in turn boosting primary production and so forth. Fronts thus form dynamical and ephemeral ecosystems where numerous species meet across all trophic levels. Fronts are also targeted by fisheries. Capturing ocean fronts and studying their long-term variability in relation with climate change is thus key for marine resource management and spatial planning. The Mediterranean Sea and the Southwest Indian Ocean are natural laboratories to study front-marine life interactions due to their energetic flow at sub-to-mesoscales, high biodiversity (including endemic and endangered species) and numerous conservation initiatives. Based on remotely-sensed Sea Surface Temperature and Height, we compute thermal fronts (2003-2020) and attracting Lagrangian Coherent Structures (1994-2020), in both regions over several decades. We advocate for the combined use of both thermal fronts and attracting Lagrangian Coherent Structures to study front-marine life interactions. The resulting front database differs from other alternatives by its high spatio-temporal resolution, long time coverage, and relevant thresholds defined for ecological provinces.

'''DEFINITION''' The OMI_EXTREME_SL_IBI_slev_mean_and_anomaly_obs indicator is based on the computation of the 99th and the 1st percentiles from in situ data (observations). It is computed for the variable sea level measured by tide gauges along the coast. The use of percentiles instead of annual maximum and minimum values, makes this extremes study less affected by individual data measurement errors. The annual percentiles referred to annual mean sea level are temporally averaged and their spatial evolution is displayed in the dataset omi_extreme_sl_ibi_slev_mean_and_anomaly_obs, jointly with the anomaly in the target year. This study of extreme variability was first applied to sea level variable (Pérez Gómez et al 2016) and then extended to other essential variables, sea surface temperature and significant wave height (Pérez Gómez et al 2018). '''CONTEXT''' Sea level (SLEV) is one of the Essential Ocean Variables most affected by climate change. Global mean sea level rise has accelerated since the 1990’s (Abram et al., 2019, Legeais et al., 2020), due to the increase of ocean temperature and mass volume caused by land ice melting (WCRP, 2018). Basin scale oceanographic and meteorological features lead to regional variations of this trend that combined with changes in the frequency and intensity of storms could also rise extreme sea levels up to one meter by the end of the century (Vousdoukas et al., 2020, Tebaldi et al., 2021). This will significantly increase coastal vulnerability to storms, with important consequences on the extent of flooding events, coastal erosion and damage to infrastructures caused by waves (Boumis et al., 2023). The increase in extreme sea levels over recent decades is, therefore, primarily due to the rise in mean sea level. Note, however, that the methodology used to compute this OMI removes the annual 50th percentile, thereby discarding the mean sea level trend to isolate changes in storminess. The Iberian Biscay Ireland region shows positive sea level trend modulated by decadal-to-multidecadal variations driven by ocean dynamics and superposed to the long-term trend (Chafik et al., 2019). '''COPERNICUS MARINE SERVICE KEY FINDINGS''' The completeness index criteria is fulfilled by 57 stations in 2021, two more than those available in 2021 (55), recently added to the multi-year product INSITU_GLO_PHY_SSH_DISCRETE_MY_013_053. The mean 99th percentiles reflect the great tide spatial variability around the UK and the north of France. Minimum values are observed in the Irish eastern coast (e.g.: 0.66 m above mean sea level in Arklow Harbour) and the Canary Islands (e.g.: 0.93 and 0.96 m above mean sea level in Gomera and Hierro, respectively). Maximum values are observed in the Bristol and English Channels (e.g.: 6.26, 5.58 and 5.17 m above mean sea level in Newport, St. Malo and St. Helier, respectively). The annual 99th percentiles standard deviation reflects the south-north increase of storminess, ranging between 1-2 cm in the Canary Islands to 12 cm in Newport (Bristol Channel). Although less pronounced and general than in 2021, negative or close to zero anomalies of 2022 99th percentile still prevail throughout the region this year reaching up to -14 cm in St.Helier (Jersey Island, Channel Islands), or -12 cm in St. Malo. Positive anomalies of 2022 99th percentile are found in the northern part of the region (Irish eastern coast and west Scotland coast) and at a couple of stations in Southern England, with values reaching 9 cm in Bangor (Northern Ireland) and 6 cm in Portsmouth (South England). '''DOI (product):''' https://doi.org/10.48670/moi-00253

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.

'''DEFINITION''' The indicator of the Kuroshio extension phase variations is based on the standardized high frequency altimeter Eddy Kinetic Energy (EKE) averaged in the area 142-149°E and 32-37°N and computed from the DUACS (https://duacs.cls.fr) delayed-time (reprocessed version DT-2021, CMEMS SEALEVEL_GLO_PHY_L4_MY_008_047, including “my” (multi-year) & “myint” (multi-year interim) datasets) and near real-time (CMEMS SEALEVEL_GLO_PHY_L4_NRT _008_046) altimeter sea level gridded products. The change in the reprocessed version (previously DT-2018) and the extension of the mean value of the EKE (now 27 years, previously 20 years) induce some slight changes not impacting the general variability of the Kuroshio extension (correlation coefficient of 0.988 for the total period, 0.994 for the delayed time period only). '''CONTEXT''' The Kuroshio Extension is an eastward-flowing current in the subtropical western North Pacific after the Kuroshio separates from the coast of Japan at 35°N, 140°E. Being the extension of a wind-driven western boundary current, the Kuroshio Extension is characterized by a strong variability and is rich in large-amplitude meanders and energetic eddies (Niiler et al., 2003; Qiu, 2003, 2002). The Kuroshio Extension region has the largest sea surface height variability on sub-annual and decadal time scales in the extratropical North Pacific Ocean (Jayne et al., 2009; Qiu and Chen, 2010, 2005). Prediction and monitoring of the path of the Kuroshio are of huge importance for local economies as the position of the Kuroshio extension strongly determines the regions where phytoplankton and hence fish are located. Unstable (contracted) phase of the Kuroshio enhance the production of Chlorophyll (Lin et al., 2014). '''CMEMS KEY FINDINGS''' The different states of the Kuroshio extension phase have been presented and validated by (Bessières et al., 2013) and further reported by Drévillon et al. (2018) in the Copernicus Ocean State Report #2. Two rather different states of the Kuroshio extension are observed: an ‘elongated state’ (also called ‘strong state’) corresponding to a narrow strong steady jet, and a ‘contracted state’ (also called ‘weak state’) in which the jet is weaker and more unsteady, spreading on a wider latitudinal band. When the Kuroshio Extension jet is in a contracted (elongated) state, the upstream Kuroshio Extension path tends to become more (less) variable and regional eddy kinetic energy level tends to be higher (lower). In between these two opposite phases, the Kuroshio extension jet has many intermediate states of transition and presents either progressively weakening or strengthening trends. In 2018, the indicator reveals an elongated state followed by a weakening neutral phase since then. '''Figure caption''' Standardized Eddy Kinetic Energy over the Kuroshio region (following Bessières et al., 2013) Blue shaded areas correspond to well established strong elongated states periods, while orange shaded areas fit weak contracted states periods. The ocean monitoring indicator is derived from the DUACS delayed-time (reprocessed version DT-2021, “my” (multi-year) dataset used when available, “myint” (multi-year interim) used after) completed by DUACS near Real Time (“nrt”) sea level multi-mission gridded products. The vertical red line shows the date of the transition between “myint” and “nrt” products used. '''DOI (product):''' https://doi.org/10.48670/moi-00222

The network was initiated by IFREMER from 1993 to 2009 (under the acronym REMORA) to study the rearing performance of the Pacific oyster Crassostrea gigas at a national scale. To do so, the network monitored annually the mortality and growth of standardized batches of 18-month-old oysters. Starting in 1995, the monitoring of the rearing performance of 6-month-old oyster spat was integrated into this network. These sentinel batches were distributed simultaneously each year on 43 sites and were monitored quarterly. These sites were distributed over the main French oyster farming areas and allowed a national coverage of the multiannual evolution of oyster farming performances. Most of the sites were located on the foreshore at comparable levels of immersion. Field studies were carried out by the "Laboratoires Environnement Ressources" (LER) for the sites included in their geographical area of investigation. Following the increase in spat mortality in 2008, the network evolved in 2009 (under the acronym RESCO). From this date, the network selected 13 sites among the 43 sites previously monitored in order to increase the frequency of visits (twice a month) and the number of sentinel batches. More precisely, sentinel batches of oysters corresponding to different origins (wild or hatchery, diploid or triploid) and to two rearing age classes (spat or 18-month-old adults) were selected. The monitoring of environmental variables (temperature, salinity) associated with the 13 sites was also implemented. The actions of the network have thus contributed to disentangle the biotic and abiotic parameters involved in mortality phenomena, taking into account the different compartments (environment / host / infectious agents) likely to interact with the evolution of oyster rearing performance. Finally, since 2015, the network has merged the RESCO and VELYGER networks to adopt the acronym ECOSCOPA. The general objective of this current network is to analyze the causes of spatio-temporal variability of the main life traits (Larval stage - Recruitment - Reproduction - Growth - Survival - Cytogenetic abnormalities) of the cupped oyster in France and to follow their evolution on the long term in the context of climate change. To do this, the network proposes a regular spatio-temporal monitoring of the major proxies of the life cycle of the oyster, organized in three major thematic groups: (1) proxies related to growth, physiological tolerance and survival of experimental sentinel populations over 3 age classes: (2) proxies related to reproduction, larval phase and recruitment of the species throughout its natural range in France, and: (3) proxies related to environmental parameters essential to the species (weather conditions, temperature, salinity, pH, turbidity, chlorophyll a and phytoplankton) at daily or sub-hourly frequencies. Working in a geographical network associating several laboratories, ECOSCOPA provide these monitoring within 8 sites selected among the previous ones to ensure the continuity of the data acquisition. Today, these 8 sites are considered as ecosystems of common interest, contrasted, namely : - The Thau lagoon - The Arcachon basin - The Marennes Oléron basin - The Bourgneuf Bay - The bay of Vilaine - The bay of Brest - The bay of Mont Saint Michel - The bay of Veys The ECOSCOPA network is therefore one of the relevant monitoring tools on a national scale, allowing to objectively measure through different proxies the general state of health of cultivated and wild oyster populations, and this for the different sensitive phases of their life cycle. This network aims at allowing a better evaluation, on the long term, of the biological risks incurred by the sector but also by the ecosystems, in particular under the increasing constraint of climatic and anthropic changes. Figure : Sites monitored by the ECOSCOPA network  

DNA sequencing of Crassostrea gigas Pacific oyster spat experimentally infected with OsHV-1 virus from oyster basin of Marennes-Oleron

Species distribution models (GAM, Maxent and Random Forest ensemble) predicting the distribution of Solitary Scleractinian fields assemblage in the Celtic Sea. This community is considered ecologically coherent according to the cluster analysis conducted by Parry et al. (2015) on image sample. Modelling its distribution complements existing work on their definition and offers a representation of the extent of the areas of the north-east Atlantic where they can occur based on the best available knowledge. This work was performed at the University of Plymouth in 2021.

A consistent dataset of bottom trawl survey data spanning 47 years in the Bay of Biscay was assembled. The dataset includes data from the current EVHOE survey from 1987 to 2019 and two previous surveys carried out in 1973 and 1976. The recent EVHOE time-series from 1997 is also available from DATRAS (https://www.ices.dk/data/data-portals/Pages/DATRAS.aspx). The catch in numbers and weight (kg) per haul of all Rajiformes species caught in these surveys is provided. Haul information is provided for all hauls, including those with no catch of Rajiformes. Areas of the sampling strata of the survey and spatial polygones of these strata are provided in separate files.

Compilation of published ocean drilling (DSDP, ODP and IODP) records of sedimentation rates, CaCO3, opal and terrigenous accumulation rates that cover the late Miocene and early Pliocene interval. We compiled oceanographic data from DSDP, ODP and IODP expeditions that cover the late Miocene and early Pliocene. Data mining was performed by automatically collecting the Pangaea datasets that correspond to the selected time interval and that have at least one of the following variables: sedimentation rate, dry bulk density, mass accumulation rate (MAR), CaCO3 accumulation rate, bSiO2 accumulation rate (biogenic SiO2) , %CaCO3, %bSiO2. The compilation was then improved by manually adding datasets absent from Pangaea but relevant to our study. The data compilation contains 154 datasets (122 are from Pangaea) from 118 different ocean drilling sites.  Age-depth models have been calibrated to the GTS2020 time scale in order to perform a temporal comparison of the datasets. This step was performed using the Neptune Sandbox Berlin database (Renaudie et al. 2020, Palaeontologia Electronica, DOI:10.26879/1032). The Meta_Data_Table file is a metadata table with the following information : site number, dataset label, site label, publication, elevation, site coordinates, site paleocoordinates (10 Ma), available variables, variables used for labeling, the time scale used in the original publication, and the web link to the original dataset.  The Time_series file is a file that contains the time series of all the variables in all the data sets in this repository.   Each file (.csv) contains a dataset and includes the following information: - Site number - Original link of the dataset - Citation  - List of ages - List of values for each variable 

Metabarcoding data were produced based on samples gathered at Ifremer where the DNA was extracted; PCR libraries were built at Ifremer and Genseq; libraries were sequenced at Novogene. The data to download contain: 1/d emultiplexed raw data, 2/ metadata, and 3) Scripts to process data and taxonomically assign DNA sequences 4) Rmarkdown to analyze communities.