WGS for Iatlantic projet ( ) for assessing past and present connectivity

In order to better characterize the genetic diversity of Cetaceans and especially the common Dolphin from the Bay of Biscay, sequences from the mitochondrial Cytochrome B region were obtained from water samples acquired close to groups of dolphins.

Raw reads for the assembly of Gambusia holbrooki genome.

This dataset provides detections of fronts derived from high resolution remote sensing SST observations by SEVIRI L3C from OSISAF over Western Europe region. The data are available through HTTP and FTP; access to the data is free and open. In order to be informed about changes and to help us keep track of data usage, we encourage users to register at: https://forms.ifremer.fr/lops-siam/access-to-esa-world-ocean-circulation-project-data/ This dataset was generated by OceanDataLab and is distributed by Ifremer / CERSAT in the frame of the World Ocean Circulation (WOC) project funded by the European Space Agency (ESA).

The ESA Sea State Climate Change Initiative (CCI) project has produced global multi-sensor time-series of along-track satellite synthetic aperture radar (SAR) integrated sea state parameters (ISSP) data from Sentinel-1 (referred to as SAR WV onboard Sentinel-1 Level 2P (L2P) ISSP data) with a particular focus for use in climate studies. This dataset contains the Sentinel-1 SAR Remote Sensing Integrated Sea State Parameter product (v1.0), which forms part of the ESA Sea State CCI version 3.0 release. This product provides along-track primary significant wave height measurements and secondary sea state parameters, calibrated with CMEMS model data and reference in situ measurements at 20km resolution every 100km, processed using the Pleskachevsky et. al., 2021 emprical model, separated per satellite and pass, including all measurements with flags and uncertainty estimates. These are expert products with rich content and no data loss. The SAR Wave Mode data used in the Sea State CCI SAR WV onboard Sentinel-1 Level 2P (L2P) ISSP v3 dataset come from the Sentinel-1 satellite missions spanning from 2014 to 2021 (Sentinel-1 A, Sentinel-1 B).

Phenotypic plasticity, the ability of a single genotype to produce multiple phenotypes, is important for survival when species are faced with novel conditions. Theory predicts that range-edge populations will have greater phenotypic plasticity than core populations, but empirical examples from the wild are rare. The honeycomb worm, Sabellaria alveolata (L.), constructs the largest biogenic reefs in Europe, which support high biodiversity and numerous ecological functions. In order to assess the presence, causes and consequences of intraspecific variation in developmental plasticity and thermal adaptation in the honeycomb worm, we carried out common-garden experiments using the larvae of individuals sampled from along a latitudinal gradient covering the entire range of the species. We exposed larvae to three temperature treatments and measured phenotypic traits throughout development. We found phenotypic plasticity in larval growth rate but local adaptation in terms of larval period. The northern and southern range-edge populations of S. alveolata showed phenotypic plasticity for growth rate: growth rate increased as temperature treatment increased. In contrast, the core range populations showed no evidence of phenotypic plasticity. We present a rare case of range-edge plasticity at both the northern and southern range limit of species, likely caused by evolution of phenotypic plasticity during range expansion and its maintenance in highly heterogeneous environments. This dataset presents the raw image data collected for larval stages of Sabellaria alveolata from 5 populations across Europe and Northern Africa, exposed to 15, 20 and 25 C. Included are also opercular crown measurements used to estimate de size classes of individuals present in each population.  All measurements made with the images collected are presented in an Excel spreadsheet, also available here.

French Zostera Marina et Zostera Noltei abundance data are collected during monitoring surveys on the English Channel / Bay of Biscay coasts. Protocols are impletmented in the Water Framework Directive. Data are transmitted in a Seadatanet format (CDI + ODV) to EMODnet Biology european database. 35 ODV files have been generated from period 01/01/2004 to 31/12/2021 for Z. Marina and from 01/01/2011 to 31/12/2021 for Z. Noltei.  

The ESA Sea State Climate Change Initiative (CCI) project has produced global multi-sensor time-series of along-track satellite synthetic aperture radar (SAR) significant wave height (SWH) data (referred to as SAR WV onboard Sentinel-1 Level 2P (L2P) SWH data) with a particular focus for use in climate studies. This dataset contains the Sentinel-1 SAR Remote Sensing Significant Wave Height product (version 1.0), which is part of the ESA Sea State CCI Version 3.0 release. This product provides along-track SWH measurements at 20km resolution every 100km, processed using the Quach et al statistical model , separated per satellite and pass, including all measurements with flags, corrections and extra parameters from other sources. These are expert products with rich content and no data loss. The SAR Wave Mode data used in the Sea State CCI dataset v3 come from Sentinel-1 satellite missions spanning from 2015 to 2021 (Sentinel-1 A, Sentinel-1 B).

In recent years, large datasets of in situ marine carbonate system parameters (partial pressure of CO2 (pCO2), total alkalinity, dissolved inorganic carbon and pH) have been collated. These carbonate system datasets have highly variable data density in both space and time, especially in the case of pCO2, which is routinely measured at high frequency using underway measuring systems. This variation in data density can create biases when the data are used, for example for algorithm assessment, favouring datasets or regions with high data density. A common way to overcome data density issues is to bin the data into cells of equal latitude and longitude extent. This leads to bins with spatial areas that are latitude and projection dependent (eg become smaller and more elongated as the poles are approached). Additionally, as bin boundaries are defined without reference to the spatial distribution of the data or to geographical features, data clusters may be divided sub-optimally (eg a bin covering a region with a strong gradient). To overcome these problems and to provide a tool for matching in situ data with satellite, model and climatological data, which often have very different spatiotemporal scales both from the in situ data and from each other, a methodology has been created to group in situ data into ‘regions of interest’, spatiotemporal cylinders consisting of circles on the Earth’s surface extending over a period of time. These regions of interest are optimally adjusted to contain as many in situ measurements as possible. All in situ measurements of the same parameter contained in a region of interest are collated, including estimated uncertainties and regional summary statistics. The same grouping is done for each of the other datasets, producing a dataset of matchups. About 35 million in situ datapoints were then matched with data from five satellite sources and five model and re-analysis datasets to produce a global matchup dataset of carbonate system data, consisting of 287,000 regions of interest spanning 54 years from 1957 to 2020. Each region of interest is 100 km in diameter and 10 days in duration. An example application, the reparameterisation of a global total alkalinity algorithm, is shown. This matchup dataset can be updated as and when in situ and other datasets are updated, and similar datasets at finer spatiotemporal scale can be constructed, for example to enable regional studies. This dataset was funded by ESA Satellite Oceanographic Datasets for Acidification (OceanSODA) project which aims at developing the use of satellite Earth Observation for studying and monitoring marine carbonate chemistry. **This version is now superseded by the version 4 with higher spatial and temporal resolution**

The SWISCA Level 2S (L2S) product provides along-track colocation of SWIM wave measuring instrument onto SCAT scatterometer grid, over the global ocean. SWIM and SCAT are both instruments onboard CFOSAT. CFOSAT (Chinese French Ocean SATellite) is a french-chinese mission launched in 2018, whose aim is to provide wind (SCAT instrument) and wave (SWIM instrument) measurements over the sea surface. The SWISCA L2S product is broken down into three different subproducts: - L2A containing the sigma0 of both SWIM and SCAT - L2B containing the wave parameters measured by SWIM and wind vectors measured by SCAT - AUX containing additional ancillary fields such as sea ice concentration (from CERSAT/SSMI), ocean currents (from CMEMS/GlobCurrent), SST and Wind (from ECMWF), rain rate (from IMERG), and WaveWatch3 wave spectra. All SWIM and ancillary observations are resampled onto SCAT scatterometer's geometry (wind vector cells, WVC). The SWISCA level 2S product is generated in delayed mode, a few days after acquisition. It is intended to foster cross analysis of SWIM and SCAT observations, and their combination to improve the retrieval of both wind and wave parameters. The SWISCA L2S product is generated and distributed by Ifremer / CERSAT in the frame of the Ifremer Wind and Wave Operation Center (IWWOC) co-funded by Ifremer and CNES and dedicated to the processing of the delayed mode data of CFOSAT mission.