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  • Coastline for Antarctica created from various mapping and remote sensing sources, provided as polygons with ''land'', ''ice shelf'', ''ice tongue'' or ''rumple'' attribute. This dataset has been generalised from the high resolution vector polygons. Covering all land and ice shelves south of 60S. Suitable for topographic mapping and analysis. Data compiled, managed and distributed by the Mapping and Geographic Information Centre and the UK Polar Data Centre, British Antarctic Survey on behalf of the Scientific Committee on Antarctic Research. Major changes in v7.4 include updates to coastline and ice shelves between Gipps Ice Rise and Ronne Ice Shelf, updated ice shelf fronts for Brunt, Stange and West ice shelves, Pine Island Glacier, and an updated coastline for Adelaide Island.

  • This dataset captures information on the diet composition and mass of Adelie penguin stomach contents at Signy Island, from 1997 to 2020. The monitoring period occurred over four weeks each year and involved sampling adults returning to feed their chicks during the creche period. Sampling took place approximately every five days. Numbers of birds sampled on each occasion varied over the entire period of the dataset from a maximum of eight to a minimum of six, equating to an annual maximum of forty birds and an annual minimum of thirty, depending on the year. All adult penguins were sampled on their return to the colony using the stomach lavage methodology specified in CCAMLR (Commission for the Conservation of Antarctic Marine Living Resources) Ecosystem Monitoring Program (CEMP) Standard Methods A8A. The stomach samples were then weighed and categorised into krill, cephalopods, fish and non-food and identified to species level where possible. Krill carapaces and otoliths were removed and measured. Ecosystems component of BAS Polar Science for Planet Earth Programme, funded by NERC.

  • The dataset comprises of analyses of two sediment cores (LC12 and LC7), extracted from Blaso, a large epishelf lake on the margin of 79 degrees N Ice Shelf, NW Greenland in July-August 2017. The data are used to constrain ice shelf dynamics over the last 8500 calibrated years before present (cal. years B.P., where present is A.D. 1950). Data for the LC7 and LC12 sediment records consist of radiocarbon (14C) chronology data. Overlapping 2 m-long sediment cores were recovered with a UWITEC KOL ''Kolbenlot percussion piston corer to a total sediment depth of 3.74 m (LC7) and 5.24 m (LC12). Accelerator mass spectrometry (AMS) was used for radiocarbon (14C) dating. Core LC7: 87 m water depth; 79.589 degrees N, 22.494 degrees E. Core LC12: 90 m water depth; 79.5948 degrees N, 22.44233 degrees E. This project was funded by the Natural Environment Research Council (NERC) through Standard Grant NE/N011228/1. We thank the Alfred Wegner Institute, and particularly Angelika Humbert and Hicham Rafiq, for their significant logistic support through the iGRIFF project. Additional support was provided from Station Nord (Jorgen Skafte), Nordland Air, Air Greenland and the Joint Arctic Command. Naalakkersuisut, Government of Greenland, provided Scientific Survey (VU-00121) and Export (046/2017) licences for this work

  • The Antarctic mass trends have been collated from a combination of different remote sensing datasets. These are trends of yearly elevation changes over Antarctica for the period 2003-2013 due to the different geophysical processes driving changes in Antarctica: ice dynamics, surface mass balance and glacio-isostatic adjustment (GIA). Net trends can be easily calculated by adding together surface and ice dynamics trends. 20 km gridded datasets have been produced for each process, per year (except the GIA solution which is time-invariant). To convert elevation to mass trends, we also provide the density fields for surface (SMB) and GIA processes used in Martin-Espanol et al (2016). These can be directly multiplied by the dh/dt. To convert dh/dt from ice dynamics, simply multiply by the density of ice. Mass smb = dh/dt smb * d surf Mass ice = dh/dt ice * d ice (not provided) Mass gia = dh/dt gia * d rock NERC grant: NE/I027401/1

  • These data are gonad index (gonad mass/total animal mass) and egg size measurements for two Antarctic marine invertebrates, the starfish Odontaster validus and the brittle star Ophionotus victoriae. Data are for samples hand-collected monthly, where weather permits, by scuba divers from sites near the British Antarctic Survey''s research station at Rothera Point, Adelaide Island. Samples were first collected in 1997 and have continued for 19 years to 2015.

  • We present here the Bedmap3 ice thickness, bed and surface elevation aggregated points and survey lines. The aggregated points consist of statistically-summarised shapefile points (centred on a continent-wide 500 m x 500 m grid) that reports the average values of Antarctic ice thickness, bed and surface elevation from the full-resolution survey data and information on their distribution. The points presented here correspond to the added points since the last release of Bedmap2. The data comes from 14 different data providers and 75 individual surveys. They are available as geopackages and shapefiles. The associated Bedmap datasets are listed here: https://www.bas.ac.uk/project/bedmap/#data This work is supported by the SCAR Bedmap project and the British Antarctic Survey''s core programme: National Capability - Polar Expertise Supporting UK Research

  • This dataset contains bed and surface elevation picks derived from airborne radar collected during the POLARGAP 2015/16 project funded by the European Space Agency (ESA) and with in-kind contribution from the British Antarctic Survey, the Technical University of Denmark (DTU), the Norwegian Polar Institute (NPI) and the US National Science Foundation (NSF). This collaborative project collected ~38,000 line-km of new aerogeophysical data using the 150MHz PASIN radar echo sounding system (Corr et al., 2007) deployed on a British Antarctic Survey (BAS) Twin Otter. The primary objective of the POLARGAP campaign was to carry out an airborne gravity survey covering the southern polar gap beyond the coverage of the GOCE orbit. This dataset covers the South Pole as well as parts of the Support Force, Foundation and Recovery Glaciers. The bed pick data acquired during the POLARGAP survey over the Recovery Lakes is archived at NPI: https://doi.org/10.21334/npolar.2019.ae99f750.

  • This dataset contains Weddell Sea limited region ocean ice shelf model (NEMO) outputs. The included experiments were designed to look at the influence of far-field changes in temperature and salinity to changes in melt rates in the Filchner-Ronne Ice Shelf melt rate. Funding was provided by the Filchner Ice Shelf System project NE/L013770/1.

  • The soil food webs in this collection represent a total of 32 belowground communities studied by Neutel et al. (2007), from two natural successions in sandy dune soils: one on the Waddensea Island of Schiermonnikoog in the north of the Netherlands and the other at Hulshorsterzand, on the Veluwe, in the central Netherlands. The study sites, which constitute the two gradients, represent four consecutive stages in chronosequences of early primary vegetation succession, increasing in aboveground and below-ground productivity. The Jacobians of the 32 food webs (two series, four stages with four replicates per stage) were calculated by Neutel et al. (2007) from observed average biomass data of the respective systems, and inferring steady-state biomass flow data using a procedure described by Hunt et al. (1987). The Jacobians represent the interaction strengths of the species in the two food webs, evaluated at equilibrium.

  • Microclimate data collected hourly at Jane Col, for 12 climatic variables via automatic data loggers, 2007-2016. Data is not available across the entire temporal range for all variables. NERC funded under the British Antarctic Survey National Capability programme, Polar Science for Planet Earth. **Please be advised to use Version 2.0 Data** Version 2.0 (see ''Related Data Set Metadata'' link below) has undergone quality control and includes flags for potential outliers in data.