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.

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)'.

This dataset comprises life history models of Scombrids, long lived sea-birds, and Kittiwake birds. Existing datasets for these species were used to produce theory predicting the demographic rates that are correlated with suites of life history traits, and then generate more precise posterior estimates of these demographic rates by fitting a structured population model. These models aim to generate new insights about the relationship between life-history traits of marine species, environmental drivers such as resources and mortality, and resilience to anthropogenic or environmental perturbations. The data were generated by the project titled "Informing population models with evolutionary theory to infer species' conservation status" funded by NERC Discovery Science grant NE/P004180/1 led by Professor Jason Matthiopoulos and Dr Catharine Horswill at University of Glasgow Institute of Biodiversity, Animal Health & Comparative Medicine.

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 the results of the genetic comparison of different species of the genus Jaera, a marine isopod, in the UK and USA. Jaera albifrons, J. forsmani, J. ischiosetosa, J. nordmanni and J. praehirsuta were collected from the underside of rocks at intertidal sites in the the UK. In the USA, J. posthirsuta, J. albifrons, J. ischiosetosa were similarly collected from sites in Maine and Massachusetts. Sample collection took place in 2015 and 2016. Sbf1 gene Restriction site Associated DNA (RAD) libraries were generated from total DNA using Illumina paired end DNA sequencing. In addition, individual microbiomes were characterised for Jaera albifrons, J. ischiosetosa, J. nordmanni, J. posthirsuta from UK populations using 16S rDNA metabarcode amplicon sequencing. The project aimed to assess parallel signatures of evolution across isolated populations and pinpoint regions of elevated genetic differentiation. All sampling and sequencing pipelines were undertaken by Marius Wenzel and Stuart Piertney (University of Aberdeen), with funding from NERC solo grant NE/M015661/1. Data are archived at the National Center for Biotechnology Information (NCBI).

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.