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2022

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  • Reef-building species are recognized as having an important ecological role and as generally enhancing the diversity of benthic organisms in marine habitats.  However, although these ecosystem engineers have a facilitating role for some species, they may exclude or compete with others. The honeycomb worm Sabellaria alveolata (Linnaeus, 1767) is an important foundation species, commonly found from northwest Ireland to northern Mauritania (Curd et al., 2020), whose reef structures increase the physical complexity of the marine benthos, supporting high levels of biodiversity. Local patterns and regional differences in taxonomic and functional diversity were examined in honeycomb worm reefs from ten sites along the northeastern Atlantic to explore variation in diversity across biogeographic regions and the potential effects of environmental drivers. To characterize the functional diversity at each site, a biological trait analysis (BTA) was conducted (Statzner et al., 1994). Here we present the functional trait database used for the benthic macrofauna found to live in association with honeycomb worm reefs. Eight biological traits (divided into 32 modalities) were selected (Table 1), providing information linked to the ecological functions performed by the associated macrofauna. The selected traits provide information on: (i) resource use and availability (by the trophic group of species, e.g. Thrush et al. 2006); (ii) secondary production and the amount of energy and organic matter (OM) produced based on the life cycle of the organisms (including longevity, maximum size and mode of reproduction, e.g. (Cusson and Bourget, 2005; Thrush et al., 2006) and; (iii) the behavior of the species in general [i.e. how these species occupy the environment and contribute to biogeochemical fluxes through habitat, movement, and bioturbation activity at different bathymetric levels, e.g. (Solan et al., 2004; Thrush et al., 2006; Queirós et al., 2013). Species were scored for each trait modality based on their affinity using a fuzzy coding approach (Chevenet et al., 1994), where multiple modalities can be attributed to a species if appropriate, and allowed for the incorporation of intraspecific variability in trait expression. The information concerning polychaetes was derived primarily from Fauchald et al (1979) and Jumars et al (2015). Information on other taxonomic groups was obtained either from databases of biological traits (www.marlin.ac.uk/biotic) or publications (Naylor, 1972; King, 1974; Caine, 1977; Lincoln, 1979; Holdich and Jones, 1983; Smaldon et al., 1993; Ingle, 1996; San Martín, 2003; Southward, 2008; Gil, 2011; Leblanc et al., 2011; Rumbold et al., 2012; San Martín and Worsfold, 2015; Jones et al., 2018). Map indicating the locations of the 10 study sites in the UK, France and Portugal within the four biogeographic provinces defined by Dinter (2001). (All sites were sampled in 8 different stations, except for UK4 where 5 stations were sampled).

  • 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**

  • French intertidal and subtidal Macroalgae taxa data are collected during monitoring surveys on the English Channel / Bay of Biscay coasts.  Protocols are implemented in the Water Framework Directive. Data are transmitted in a Seadatanet format (CDI + ODV) to EMODnet Biology european database. 131 ODV files have been generated from period 01/01/2006 to 31/12/2021.

  • This dataset gathers isotopic ratios (carbon and nitrogen) and concentrations of both priority (mercury species and polychlorinated biphenyls congeners) and emerging (musks and sunscreens) micropollutants measured in a host-parasite couple (hake Merluccius merluccius muscle and in its parasite Anisakis sp) from the south of Bay of Biscay in 2018. In addition, the hake infection degree measured as the number of Anisakis sp. larvae was added for each hake collected.

  • The Level 4 merged microwave wind product is a complete set of hourly global 10-m wind maps on a 0.25x0.25 degree latitude-longitude grid, spanning 1 Jan 2010 through the end of 2020. The product combines background neutral equivalent wind fields from ERA5, daily surface current fields from CMEMS, and stress equivalent winds obtained from several microwave passive and active sensors to produce hourly surface current relative stress equivalent wind analyses. The satellite winds include those from recently launched L-band passive sensors capable of measuring extreme winds in tropical cyclones, with little or no degradation from precipitation. All satellite winds used in the analyses have been recalibrated using a large set of collocated satellite-SFMR wind data in storm-centric coordinates. To maximize the use of the satellite microwave data, winds within a 24-hour window centered on the analysis time have been incorporated into each analysis. To accomodate the large time window, satellite wind speeds are transformed into deviations from ERA5 background wind speeds interpolated to the measurement times, and then an optical flow-based morphing technique is applied to these wind speed increments to propagate them from measurement to analysis time. These morphed wind speed increments are then added to the background wind speed at the analysis time to yield a set of total wind speeds fields for each sensor at the analysis time. These individual sensor wind speed fields are then combined with the background 10-m wind direction to yield vorticity and divergence fields for the individual sensor winds. From these, merged vorticity and divergence fields are computed as a weighted average of the individual vorticity and divergence fields. The final vector wind field is then obtained directly from these merged vorticity and divergence fields. Note that one consequence of producing the analyses in terms of vorticity and divergence is that there are no discontinuities in the wind speed fields at the (morphed) swath edges. There are two important points to be noted: the background ERA5 wind speed fields have been rescaled to be globally consistent with the recalibrated AMSR2 wind speeds. This rescaling involves a large increase in the ERA5 background winds beyond about 17 m/s. For example, an ERA5 10 m wind speed of 30 m/s is transformed into a wind speed of 41 m/s, and a wind speed of 34 m/s is transformed into a wind speed of about 48 m/s. Besides the current version of the product is calibrated for use within tropical cyclones and is not appropriate for use elsewhere. This dataset was produced in the frame of ESA MAXSS project. The primary objective of the ESA Marine Atmosphere eXtreme Satellite Synergy (MAXSS) project is to provide guidance and innovative methodologies to maximize the synergetic use of available Earth Observation data (satellite, in situ) to improve understanding about the multi-scale dynamical characteristics of extreme air-sea interaction.

  • This dataset provides detections of fronts derived from low resolution optimally interpolated remote sensing microwave SST L4 from REMSS over North Atlantic 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).

  • This dataset consists of metatranscriptomic sequencing reads corresponding to coastal micro-eukaryote communities sampled in Western Europe in 2018 and 2019.

  • This dataset provides Level 4 total current including geostrophy and a data-driven approach for Ekman and near-inertial current, based on a convolution between drifter observation and wind history, to fit empirically a complex and time-lag dependant transfert function between ERA5 wind stress and current 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 Datlas and is distributed by Ifremer / CERSAT in the frame of the World Ocean Circulation (WOC) project funded by the European Space Agency (ESA).

  • This dataset contains the pictures used for morphometric measurements, as well as the elemental compositon and production rates data, of planktonic Rhizaria. Specimens were collected in the bay of Villefranche-sur-Mer in May 2019 and during the P2107 cruise in the California Current in July-August 2021. Analyses of the data can be found at https://github.com/MnnLgt/Elemental_composition_Rhizaria.

  • The data file present detailed individual congener/compound concentrations  for a large variety of hydrophobic organic contaminants including polychlorinated biphenyls (PCBs), organochlorine pesticides (OCPs), legacy and alternative brominated flame retardants (BFRs) and per- and polyfluoroalkyl substances (PFASs) in meso- and bathypelagic organisms collected in the Bay of Biscay, northeast Atlantic, in October 2017. The studied species include 3 crustacean species (Pasiphaea sivado, Sergia robusta, Ephyrina figueirai) and 11 fish species (Xenodermichthys copei, Searsia koefoedi, Myctophum punctatum, Notoscopelus kroeyeri, Lampanyctus crocodilus, Argyropelecus olfersii, Arctozenus risso, Stomias boa, Serrivomer beanii, Chauliodus sloani, Aphanopus carbo). The organisms were collected at night during one single trawling using a 25 m vertical opening pelagic trawl in the deep scattering layer (ca 800 m depth in the water column; 1330 m bottom floor). This dataset was used in the article entitled "A large diversity of organohalogen contaminants reach the meso- and bathypelagic organisms in the Bay of Biscay (northeast Atlantic)" published in Marine Pollution Bulletin.