This dataset consists of coccolithophore abundances in the North Atlantic that were collected from 37 CTD casts during three RRS Discovery cruises (D350, D351, D354) in the spring and summer of 2010. Water samples (0.2-1 L) were collected from CTD casts and filtered through cellulose nitrate (0.8 µm) and polycarbonate (0.45 µm or 0.8 µm) filters, rinsed with trace ammonium solution, oven dried (30-40 °C, 6-12 h) and stored in Millipore PetriSlides. The filters were examined using a Leo 1450VP scanning electron microscope, with coccolithophores identified following Young et al. (2003), and enumerated from 225 fields of view (Daniels et al., 2012). The detection limit was estimated to be 0.2-1.1 cells mL-1. The samples were collected to investigate coccolithophore community dynamics in the North Atlantic as part of the Irminger Basin Iron Study (IBIS)(D350, D354), Extended Ellett Line (EEL)(D351) and a NERC Fellowship. Samples were collected on D350 by Martine Couapel, on D351 by Stuart Painter and on D354 by Alex Poulton and Mike Lucas. In the lab, samples were prepared and processed by Chris Daniels, Elena Maher and Jonathan Hurst, and were analysed for coccolithophore abundances by Chris Daniels and Jeremy Mirza. The data are held at the British Oceanographic Data Centre (BODC). Daniels, C. J., Tyrrell, T., Poulton, A. J., and Pettit, L.: The influence of lithogenic material on particulate inorganic carbon measurements of coccolithophores in the Bay of Biscay, Limnol. Oceanogr., 57, 145-153, doi:10.4319/lo.2012.57.1.0145, 2012. Young, J. R., Geisen, M., Cros, L., Kleijne, A., Sprengel, C., Probert, I., and Ostergaard, J.: A guide to extant coccolithophore taxonomy, J. Nannoplankt. Res. Special Issue, 1, 1-132, 2003.

GreenSeas was an EU FP7 programme funded to advance the quantitative knowledge of how planktonic marine ecosystems, including phytoplankton, bacterioplankton and zooplankton, will respond to environmental and climate changes. To achieve this GreenSeas employed a combination of observation data, numerical simulations and a cross-disciplinary synthesis to develop a high quality, harmonized and standardized plankton and plankton ecology long time-series, data inventory and information service. This contribution to the programme developed a number of indices to characterize quantitatively the seasonality of phytoplankton (Platt and Sathyendranath, 2008, Racault et al., 2014a). Specifically, indices that relate to the study of timing of periodic biological events as influenced by the environment are referred to as phytoplankton phenology. These indices include: timings of initiation, peak, and termination as well as the duration of the phytoplankton growing period. Changes in phytoplankton phenology (triggered by variations in climate) can profoundly alter: (1) the efficiency of the biological pump, with inevitable impact of the global carbon cycle; and (2) the interactions across trophic levels, which can engender trophic mismatch with major impacts on the survival of commercially important fish and crustacean larvae. Phenology indices were estimated using the R2010.0 reprocessing of Level 3 Mapped chlorophyll-a concentration from the Sea-viewing Wide Field-of-view (SeaWiFS) sensor. The chlorophyll-a data were retrieved from NASA Ocean Color Web http://oceancolor.gsfc.nasa.gov for the period 1997-2008 at 9 km spatial resolution and 8-day temporal resolution. Linear interpolation was applied to map the chlorophyll-a concentration onto a 1degreex1degree fixed grid. The phenology indices were estimated following the method described in Racault et al. (2012). Missing chlorophyll-a data were reduced from the time-series prior to estimating the timing of ecological events. Missing values were filled by interpolating spatially adjacent values (average of 3 × 3 pixels on the 9km grid), when these were available. Any remaining missing values were filled by interpolating temporally adjacent values (average of previous and following 8-day composites), when these were available. Otherwise the value was not filled. A 3-week running mean was applied to remove small peaks in chlorophyll-a. The timings of initiation and end of the phytoplankton growing period were detected as the weeks when the chlorophyll concentration in a particular year rose above the long-term median value plus 5% and later fell below this same threshold (Racault et al., 2012). The duration of the growing season is defined as the number of weeks between initiation and end.

This dataset consists of silicon isotope data from deep-sea sediment cores taken off southeast Iceland. Samples of sea sponges were collected using piston cores and sediment cores aboard the RV Celtic Explorer in 2008 and dried or frozen for transportation. Organic matter was removed and samples were preserved for later analysis. Sample analysis occurred in 2012 as part of a comprehensive study of the carbon cycle. The data collected form the field component of the NERC-funded project "Unravelling the carbon cycle using silicon isotopes in the oceans". The project aimed to investigate deep sea sponges and the silicon they produce, in an effort to piece together the links between the supply of vital nutrients in different parts of the ocean and the crucial role other marine organisms play in absorbing CO2 from the atmosphere and storing it in deep sea sediments as organic carbon. The Discovery Science project was composed of New Investigators (FEC) Grant reference NE/J00474X/1 led by Dr. Katherine Rosemary Hendry of Cardiff University, School of Earth and Ocean Sciences. The project ran from 26 January 2012 to 30 September 2013. The silicon isotope data have been received by BODC as raw files, and will be processed and quality controlled using in-house BODC procedures and made available online in the near future. The raw files are available on request.

Macrofauna and polychaete species abundance data were obtained from replicate megacore samples collected from inside the Whittard Canyon (N.E. Atlantic) and the adjacent slope to the west of the canyon during cruise JC036 in June and July 2009. Four sites were sampled, three in the Whittard Canyon branches (Western, Central and Eastern) and one site on the slope to the west of the canyon. Five deployments were conducted in the Western branch, six in the Central and Eastern branches and five at the slope site. One extra deployment was made in the Central and Eastern branches to compensate for the failure to recover sufficient cores. All sites were located at 3500 m depth. Samples were collected using a Megacorer fitted with eight large (100 mm internal diameter) core tubes. Core slices from the same sediment layer from one deployment were pooled to make one replicate sample. The number of cores pooled per deployment ranged from 3 to 7 and the area of seabed sampled varied accordingly. The top three sediment horizons (i.e. 0–1, 1–3 and 3–5 cm), were analysed in toto. Macrofauna were identified to higher taxa levels, and polychaetes to species level and counts of species/taxa recorded for each site. AphiaIDs have been assigned to the samples - where identification was only possible to genus or family level, the aphiaIDs for genus and family have been supplied. The supplied aphaIDs are those that were acceptable at the time of the analysis and not their more recent superseding terms. This cruise was part of the HERMIONE project and the data formed the basis of L. Gunton's PhD thesis 'Deep-Sea Macrofaunal Biodiversity of the Whittard Canyon (NE Atlantic)'.

The Iodide in the ocean project brings together marine and atmospheric scientists in order to address uncertainties in the marine iodine flux and associated ozone sink. Specifically, it aims to quantify the dominant controls on the sea surface iodide distribution and improve parameterisation of the sea-to-air iodine flux and of ozone deposition. It contains data from a combination of laboratory experiments, field measurements and ocean and atmospheric modelling from three cruises as well as worldwide sea surface measurements from 1967-2018 from published manuscripts, published and unpublished data supplied by the originators themselves or provided by repositories. Iodide, iodate and total iodine concentrations were measured on three cruises: BOBBLE, June to July 2016 in the Bay of Bengal, Sagar-Kanya33 in September 2016 in the Arabian Sea and ISOE9 in January to February 2017 in the Indian and Southern Oceans. Samples were taken from Niskin bottles on conductivity-temperature-depth (CTD) profilers. Laboratory experiments consisted of phytoplankton cultures to measure rates of iodate incorporation and iodide production. This work was carried out by Lucy Carpenter (PI), Claire Hughes (Co-PI) , Liselotte Tinel, and Helmke Hepach at York University, Mark Evans (Co-PI) at the University of Edinburgh. It was funded by the NERC Discovery Science project Iodide in the ocean: distribution and impact on iodine flux and ozone loss (parent grant reference NE/N009983/1 with child grants NE/N009444/1 and NE/N01054X/1 led by Stephen Ball and David Stevens respectively).

This dataset contains measurements of temperature, salinity, raised/non-raised mackerel egg numbers, raised/non-raised horse mackerel egg numbers as well as adult fish total length, weight, maturity and sex. Data were obtained on the RV Bjarni Sæmundsson which sampled North of Scotland to Iceland. The project altogether obtained data along the Portuguese coast from February and continued until July to the waters west of Scotland. The egg survey was carried out from the 02/05/2016 to 13/05/2016 with the adult mackerel sampling taking place on 11/05/2016. A total of 4 pelagic trawl hauls were carried out to collect adult mackerel samples using a pelagic WB trawl. Sampling of the fish eggs was carried out with a High Speed Plankton Sampler Gulf VII, which had a 280 micron mesh sized net and an opening diameter of 20cm. A small skrips-depressor of 30 kg was also attached to the sampler. Water filtered during each haul was measured using an internal Valeport electronic flowmeter. An external flowmeter was in turn mounted on the frame, as well as a Seabird 911 plus CTD attached with an altimeter, which measured depth, temperature and salinity. Samples were sorted for fish eggs using the spray method and mackerel eggs were staged according to the sampling protocol. For quality assurance, 10% of the samples were checked and sorted again. All eggs were counted and identified to species level. The data were obtained as a part of an international Atlantic survey, carried out by 10 different European institutes to monitor the spatial and seasonal distribution of Atlantic mackerel and horse mackerel. Planning and coordination of the survey was made within the ICES Working Group for Mackerel and Horse Mackerel Egg Surveys (WGMEGS). In 2016 the following countries participated in this survey: The Faroes, Denmark, Germany, Ireland, Norway, Portugal, Scotland, Spain, the Netherlands and Iceland. The data present here has been obtained by Marine Research Institute in Iceland.

Fish catch data comprising species identification, abundance and length. Weight, sexual maturity and age are also recorded for a sub-sample of the total catch. The data were obtained from a number of sea lochs in the Forth of Lorne and the Isle of Mull, north west Scotland, typically on a monthly basis between 1969 and 1973. The data were obtained from fish caught by bottom and mid-water otter type trawls (including Seine, Agassiz and beam trawls). Collectively, these data form an unique insight into the fish population history of this region. The original data were collected under the overall supervision of John Gordon, at the Scottish Marine Biological Association (SMBA).

Zooplankton and fish catch statistics comprising species identification and abundance. A proportion of the data relate to unidentified species and estimated abundances (or an indication of abundance magnitude) are often recorded. The data were obtained from the North Atlantic Ocean, predominantly in the region of the Bay of Biscay, between 1973 and 1984. This data set is based upon samples obtained by mid-water trawls from research vessels. It incorporates digital data recorded in field notebooks and reports, together with the results of a retrospective study in 2010 of preserved specimens from the catches. The original data were collected by John Mauchline at the Scottish Marine Biological Association (SMBA) and re-examined in 2010 by scientists at the Scottish Association for Marine Science (SAMS).

The deep sea benthic biodiversity dataset encompasses a wide range of benthic sampling and observational activities carried out by the Scottish Association for Marine Science (SAMS) since 1973. Data include analyses of samples obtained by fish trawls, benthic imagery and core sampling. The principle regions covered are the Arctic, North Atlantic & Rockall Trough and the Portuguese coast. Sampling has been carried out on numerous cruises, funded through various initiatives (ranging from NERC to commercially-funded ventures). A wide range of methods and equipment were used to obtain the information. These include Agassiz trawls, bed hop cameras, dredges, grabs, epibenthic sledges, corers and landers. These data help to build up a temporal and spatial record of regional biodiversity and consequently are a valuable tool to monitor the state of marine habitats.

Fish catch data comprising species identification, abundance and length. Weight, sexual maturity and age are also recorded for a sub-sample of the total catch. The data were obtained from a number of sea lochs in the Forth of Lorne and the Isle of Mull, north west Scotland, typically on a monthly basis between 1967 and 1971. The data were obtained from fish caught in a number of ways including trawls behind small boats and vessels, by divers, and from individuals on beaches. They do not include samples collected using bottom or mid-water otter type trawls (Seine, Agassiz or beam). Collectively, these data form an unique insight into the fish population history of this region. The original data were collected under the overall supervision of John Gordon, at the Scottish Marine Biological Association (SMBA).