Raw reads for the assembly of Gambusia holbrooki genome.

The ClimateFish database collates abundance data of 15 fish species proposed as candidate indicators of climate change in the Mediterranean Sea. An initial group of eight Mediterranean indigenous species (Epinephelus marginatus, Thalassoma pavo, Sparisoma cretense, Coris julis, Sarpa salpa, Serranus scriba, Serranus cabrilla and Caranx crysos) with wide distribution, responsiveness to temperature conditions and easy identification were selected by a network of Mediterranean scientists joined under the CIESM programme ‘Tropical Signals’ (https://www.ciesm.org/marine/programs/tropicalization.htm; Azzurro et al. 2010). Soon after, and thanks to the discussion with other expert groups and projects, C. crysos was no longer considered, and Lessepsian fishes (Red Sea species entering the Mediterranean through the Suez Canal) were included, namely: Fistularia commersonii, Siganus luridus, Siganus rivulatus, Pterois miles, Stephanolopis diaspros, Parupeneus forskali, Pempheris rhomboidea and Torquigener flavimaculosus. Considering the trend of increase of these species in the Mediterranean Sea (Golani et al. 2021) and their projected distribution according to climate change scenarios (D’Amen and Azzurro, 2020), more data on these tropical invaders are expected to come in the future implementation of the study. Data were collected according to a simplified visual census methodology (Garrabou et al. 2019) along standard transects of five minutes performed at a constant speed of 10m/min, corresponding approximately to an area of 50x5m. Four different depth layers were surveyed:  0-3m, 5-10 m, 11-20 m, 21-30 m. So far, the ClimateFish database includes fish counts collected along 3142 transects carried out in seven Mediterranean countries between 2009 and 2021, for a total number of 101'771 observed individuals belonging to the 15 fish species. Data were collected by a large team of researchers which joined in a common monitoring strategy supported by different international projects, which are acknowledged below. This database, when associated with climate data, offers new opportunities to investigate spatio-temporal effects of climate change in the Mediterranean Sea and test the effectiveness of each species as a possible climate change indicator.   Contacts: ernesto.azzurro(at)cnr.it   References: Azzurro E., Maynou F., Moschella P. (2010). A simplified visual census methodology to detect variability trends of coastal mediterranean fishes under climate change scenarios. Rapp. Comm. int. Mer Médit., 39. D’Amen, M. and Azzurro, E. (2020). Lessepsian fish invasion in Mediterranean marine protected areas: a risk assessment under climate change scenarios. ICES Journal of Marine Science, 77(1), pp.388-397. Garrabou, J., Bensoussan, N., Azzurro, E. (2019). Monitoring climate-related responses in Mediterranean marine protected areas and beyond: five standard protocols. Golani D.,  Azzurro E.,  Dulčić J.,  Massutí E., Orsi-Relini L.  (2021).  Atlas of Exotic Fishes in the Mediterranean Sea.  2nd edition  [F. Briand, Ed.]  365 pages.  CIESM Publishers, Paris, Monaco. ISBN number  978-92-990003-5-9   

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**

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.

The ESA Sea State Climate Change Initiative (CCI) project has produced global daily merged multi-sensor time-series of along-track satellite altimeter significant wave height data (referred to as Level 3 (L3) data) with a particular focus for use in climate studies. This dataset contains the Version 3 Remote Sensing Significant Wave Height product, which provides along-track data at approximately 6 km spatial resolution. It has been generated from upstream Sea State CCI L2P products, edited and merged into daily products, retaining only valid and good quality measurements from all altimeters over one day, with simplified content (only a few key parameters). This is close to what is delivered in Near-Real Time by the CMEMS (Copernicus - Marine Environment Monitoring Service) project. It covers the date range from 2002-2021. The altimeter data used in the Sea State CCI dataset v3 come from multiple satellite missions (Envisat, CryoSat-2, Jason-1, Jason-2, Jason-3, SARAL, Sentinel-3A), therefore spanning over a shorter time range than version 1.1. Unlike version 1.1, this version 3 involved a complete and consistent retracking of all the included altimeters. Many altimeters are bi-frequency (Ku-C or Ku-S) and only measurements in Ku band were used, for consistency reasons, being available on each altimeter but SARAL (Ka band).

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.

The Programme Ocean Multidisciplinaire Meso Echelle (POMME) was designed to describe and quantify the role of mesoscale processes in the subduction of mode waters in the Northeast Atlantic. Intensive situ measurements were maintained during 1 year (September 2000 - October 2001), over a 8 degrees square area centered on 18 degrees W, 42 degrees N. In order to synthesized the in-situ physical observations, and merge them with satellite altimetry and surface fluxes datasets, a simplified Kalman filter has been designed. Daily fields of temperature, salinity, and stream function were produced on a regular grid over a full seasonal cycle. We propose here the gridded fields (KA_ files) and the in-situ datasets used by the analysis (Data_ files).

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

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).