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 comprises visual line and point transect surveys, stable isotope, sex determination and genetic studies, geolocation tracking, time-depth and morphometrics of specific seabird species in the Atlantic Ocean along the Charlie Gibbs Fracture Zone (CGFZ). Data collection was onboard RRS Discovery Cruise DY080 from 06 June 2017 to 02 July 2017 in the North Atlantic Ocean to complete visual line and point transect surveys of seabirds. Seabirds (Fulmarus glacialis, Ardenna gravis, Oceanodroma leucorhoa) were caught and sampled using non-lethal methods, then released unharmed. Feathers, blood, faeces, stomach contents were sampled and morphometrics and moult scores recorded. Seabirds (Ardenna gravis, Calonectris borealis) were captured and released at breeding colonies to allow tracking of their locations and collection of associated tissue samples at Gough Island (November 2016), Kidney Island (January 2017) and Corvo Island (July 2017) in the South Atlantic Ocean. Birds were fitted with a Migrate Technology F100 geolocator. In addition, to record dive behaviour, a subset of birds were fitted with a Cefas G5 Time Depth Recorder. These loggers were recovered and downloaded after 12 or 24 months. Blood and feather samples were collected from the birds at logger deployment and recovery and morphometrics were also recorded for all of the birds. This is a Natural Environment Research Council (NERC) funded grant, reference no. NE/M017990/1 led by Dr Ewan Wakefield, University of Glasgow (Principal Investigator). Grant funded from 04 January 2016 to 03 January 2021. The core aim of the project was to determine how petrels have been affected by recent changes in the climate, how they affect phytoplankton growth and carbon dioxide levels, and how they may respond to future climate change. BODC are the designated repository for long term storage of datasets. BODC currently hold DY080 visual line transect survey data of seabirds, which are available to users on request.

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.

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 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.