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.

Fish larvae were collected by the continuous plankton recorder (CPR, operated by SAHFOS) all year long between 1951 and 2005 along transects in the Celtic Sea and English Channel. The CPR is towed by ships of opportunity at speeds of 15 to 20 knots, at an approximate depth of 10 m. Water enters the recorder through an aperture of 1.27 cm2, and is filtered through a continuously moving band of silk with an average mesh size of 270 μm.

Temporal series (annual mean values) and Long term Average (LTA) of water discharge for each river mouth where in situ data is available. Different sources can be mixed if any.

The National Centers for Environmental Prediction (NCEP) Climate Forecast System (CFS) is initialized four times per day (0000, 0600, 1200, and 1800 UTC). NCEP upgraded their operational CFS to version 2 on March 30, 2011. This is the same model that was used to create the NCEP Climate Forecast System Reanalysis (CFSR), and the purpose of this dataset is to extend CFSR. The 6-hourly atmospheric, oceanic and land surface analyzed products and forecasts, available at 0.2, 0.5, 1.0, and 2.5 degree horizontal resolutions, are archived here beginning with January 1, 2011 as an extension of CFSR.

Map at 1 degree resolution of 50-year linear trend in sea water temperature at 3 levels: surface, 500m, bottom.

Modelled density of the seapen Kophobelemnon stelliferum in the North East Atlantic. The Random Forest density model trained on data collected by an ROV was constrained by an ensemble of Maxent and Random Forest presence-absence model trained on a larger dataset also collected by an ROV. This species provides structural complexity in an environment where it is lacking and, thus, promotes higher biodiversity where they settle. They are vulnerable to mechanical disturbance of the sediment by fishing gear and a better understanding of their distribution will lead to better management of their population. This work was performed at the University of Plymouth in 2021.