This dataset containing traits of marine fish is based on fish taxa observed during international scientific bottom-trawl surveys regularly conducted in the Northeast Atlantic, Northwest Atlantic and the Northeast Pacific. These scientific surveys target primarily demersal (bottom-dwelling) fish species, but pelagic species are also regularly recorded. The overarching aim of this dataset was to collect information on ecological traits for as many fish taxa as possible and to find area-specific trait values to account for intraspecific variation in traits, especially for widely distributed species. We collected traits for species, genera and families. The majority of trait values were sourced from FishBase (Froese and Pauly, 2019), and have been supplemented with values from the primary literature.

Excel file containing CPR data from Standard Areas B4,C3,C4,D3,D4,D5,E4,F4 for the plankton Calanus finmarchicus and helgolandicus, total traverse (small) copepods, total large copepods, Phytoplankton Colour Index and Cnidaria (presence denoted by a 1, absence by a zero). All taxa are from 1980, except Cnidaria which are from 2011. Dataset is in the format of sample level data, with each row being a discrete sample, with a sample being 3m3 filtered seawater, and 10nm of tow. For each row, a sample has the following information, starting at column a: Standard area of sample, sample id, latitude (decimal degrees) of sample mid point, longitude (decimal degrees) of sample midpoint, sample midpoint date and local time, year of sample, month of sample, then plankton abundance values (or PCI index or cnidaria presence/absence). All taxa have been looked for during the period this dataset spans, so zero values represent true absence.

This is a compilation of OSPAR habitat point data for the northeast Atlantic submitted by OSPAR contracting parties. The compilation is coordinated by the UK's Joint Nature Conservation Committee, working with a representative from each of the OSPAR coastal contracting parties. This public dataset does not contain records relating to sensitive species (e.g. Ostrea edulis) in specific areas, or where data are restricted from public release by the owner's use limitations. This version (v2020) was published in July 2021.

The development of the ecosystem approach and models for the management of ocean marine resources requires easy access to standard validated datasets of historical catch data for the main exploited species. They are used to measure the impact of biomass removal by fisheries and to evaluate the models skills, while the use of standard dataset facilitates models inter-comparison. North Atlantic albacore tuna is exploited all year round by longline and in summer and autumn by surface fisheries and fishery statistics compiled by the International Commission for the Conservation of Atlantic Tunas (ICCAT). Catch and effort with geographical coordinates at monthly spatial resolution of 1° or 5° squares were extracted for this species with a careful definition of fisheries and data screening. In total, thirteen fisheries were defined for the period 1956-2010, with fishing gears longline, troll, mid-water trawl and bait fishing. However, the spatialized catch effort data available in ICCAT database represent a fraction of the entire total catch. Length frequencies of catch were also extracted according to the definition of fisheries above for the period 1956-2010 with a quarterly temporal resolution and spatial resolutions varying from 1°x 1° to 10°x 20°. The resolution used to measure the fish also varies with size-bins of 1, 2 or 5 cm (Fork Length). The screening of data allowed detecting inconsistencies with a relatively large number of samples larger than 150 cm while all studies on the growth of albacore suggest that fish rarely grow up over 130 cm. Therefore, a threshold value of 130 cm has been arbitrarily fixed and all length frequency data above this value removed from the original data set.

NOAA High-resolution Blended Analysis of Daily SST and Ice. Data is from Sep 1981 and is on a 1/4 deg global grid.

JRA55-do is a surface dataset for driving ocean-sea ice models and used in phase 2 of OMIP (OMIP-2). JRA55-do corrects the atmospheric reanalysis product JRA-55 (Kobayashi et al., 2015) using satellite and other atmospheric reanalysis products. The merits of JRA55-do are the high horizontal resolution (~55 km) and temporal interval (3 h). An assessment by Tsujino et al. (2020) implies that JRA55-do can suitably replace the current CORE/OMIP-1 dataset. This reanalysis of atmospheric variables is provided by the Japanese Meteorological Agency starting in the year 1958 and will be used to drive the coupled NEMO-ERSEM model in the hindcast configuration.

HydroWASTE is a spatially explicit global database of 58,502 wastewater treatment plants (WWTPs) and their characteristics. This database was developed by combining national and regional datasets with auxiliary information to derive or complete missing characteristics, including the amount of people served, the flow rate of effluents, and the level of treatment of processed wastewater. The HydroSHEDS river network with streamflow estimates was used to geo-reference plant outfall locations and to assess the distribution of wastewaters at a global scale. All wastewater treatment plants are co-registered to the global river network of the HydroRIVERS database via their estimated outfall locations.

This layer shows the current known extent and distribution of Seagrass meadows in European waters, collated by EMODnet Seabed Habitats. The polygons portion was last updated in 2019. The points were added in Sept 2021. The purpose was to produce a data product that would provide the best compilation of evidence for the essential ocean variable (EOV) known as Seagrass cover and composition (sub-variable: Areal extent of seagrass meadows), as defined by the Global Ocean Observing System (GOOS). Seagrasses provide essential habitat and nursery areas for many marine fauna. There are approximately 72 seagrass species that belong to four major groups: Zosteraceae, Hydrocharitaceae, Posidoniaceae and Cymodoceaceae. Zostera beds and Cymodecea meadows are named on the OSPAR Threatened or Declining Habitats list. Posidonia beds are protected under Annex I of the EU Habitats Directive. This data product should be considered a work in progress and is not an official product.

This layer shows the current known extent and distribution of macroalgal canopy in European waters, collated by EMODnet Seabed Habitats. The polygons portion was last updated in 2019. The points were added in Sept 2021. The purpose was to produce a data product that would provide the best compilation of evidence for the essential ocean variable (EOV) known as Macroalgal canopy cover and composition (sub-variable: Areal extent), as defined by the Global Ocean Observing System (GOOS). Kelp and fucoid brown algae are the dominant species that comprise macroalgal forests. This data product should be considered a work in progress and is not an official product.

The Task Force on Hemispheric Transport of Air Pollution (TF HTAP) is an international scientific cooperative effort to improve the understanding of the intercontinental transport of air pollution across the Northern Hemisphere. TF HTAP was organized in 2005 under the auspices of the UNECE Convention on Long-range Transboundary Air Pollution (LRTAP Convention) and reports to the Convention’s EMEP Steering Body. However, participation is open to all interested experts, both inside and outside the UNECE region. TF HTAP organizes scientific cooperation in the areas of emissions inventories and projections, analysis of ambient monitoring and remote sensing, global and regional modeling, and impact assessment to understand the intercontinental flows of ozone and its precursors, fine particles and their components, mercury, and persistent organic pollutants (POPs). The main questions of interest to the TF HTAP relate to the benefits of international cooperation to decrease air pollution emissions: - How do air pollution concentrations (or deposition) in one region of the world change as emissions change in other regions or the world? - How do changes in emissions outside a region affect the health, ecosystem, and climate impacts of air pollution within a given region? - How does the feasibility of further emissions control differ in different regions of the world?