afd8a811-6e5e-4441-a409-0e6924c36fc4 eng utf8 dataset dataset NERC EDS UK Polar Data Centre +44 (0)1223 221400 British Antarctic Survey, High Cross, Madingley Road Cambridge Cambridgeshire CB3 0ET United Kingdom polardatacentre@bas.ac.uk https://www.bas.ac.uk/team/business-teams/information-services/uk-polar-data-centre/ information pointOfContact 2025-02-12 ISO 19115 Geographic Information - Metadata ISO 19115:2003(E) European Petroleum Survey Group (EPSG) Geodetic Parameter Registry 2008-11-12 publication European Petroleum Survey Group EPSGadministrator@iogp.org https://www.epsg-registry.org/ EPSG Geodetic Parameter Dataset The EPSG Geodetic Parameter Dataset is a structured dataset of Coordinate Reference Systems and Coordinate Transformations, accessible through this online registry. information publisher urn:ogc:def:crs:EPSG::3031 6.18.3 Locations, descriptors, cell observations and model output for snow algae samples, Robert Island, South shetland islands, 2023 2025-02-12 creation 2025-02-12 revision 2025-02-12 publication 2025-02-12 released 1.0 https://doi.org/10.5285/afd8a811-6e5e-4441-a409-0e6924c36fc4 doi GB/NERC/BAS/PDC/02014 https://data.bas.ac.uk/ NE/V000764/1 award NE/V000896/1 award Please cite this item as: Davey, M., Thomson, A., Thomas, N., Gray, A., Smith, A., Colesie, C., Walshaw, C., Fretwell, P., Peck, L., Moulton, H., & Convey, P. (2025). Locations, descriptors, cell observations and model output for snow algae samples, Robert Island, South shetland islands, 2023 (Version 1.0) [Data set]. NERC EDS UK Polar Data Centre. https://doi.org/10.5285/afd8a811-6e5e-4441-a409-0e6924c36fc4 This dataset is a sequential list of all the terrestrial snow and ice samples taken at Robert Island, Antarctica from January 2023 to March 2023. Sample date, location, bloom colour and what the sample was subsequently used for (metabolomics, pigment, DNA, DOC, FTIR, CN), along with cell counts is provided. Cell counts and biometric measurements of Ancylonema are included in the dataset. The samples were taken by small 15ml or 50ml plastic tube sampling in the snow pack or on the icecap hard ice. This was to study the habitat and ecosystem progression over the season and linking this to other satellite or drone or vegetation data. A remote sensing output (red snow algae vector for Robert Island) was also produced. The expedition and sampling was carried out by Matthew Davey (PI), Alex Thomson, Andrew Gray, Hannah Moulton, Charlotte Walshaw with support from INACH, Chile and BAS. This was part of a wider project with Claudia Colesie, Naomi Thomas, Peter Convey, Alison G. Smith, Peter Fretwell, Lloyd Peck. Samples were transferred to UK (SAMS) for further analysis. This project was funded by Standard NERC References: NE/V000764/1 and NE/V000896/1. The past, present and future of snow algae in Antarctica: a threatened terrestrial ecosystem? No credit. completed Davey, Matt Scottish Association for Marine Science, Plant Sciences Researcher author Thomson, Alex Scottish Association for Marine Science, Plant Sciences Researcher author Thomas, Naomi Scottish Association for Marine Science, Plant Sciences Researcher author Gray, Andrew The University of Edinburgh School of GeoSciences Researcher author Smith, Alison University of Cambridge Researcher author Colesie, Claudia The University of Edinburgh School of GeoSciences Researcher author Walshaw, Charlotte The University of Edinburgh School of GeoSciences Researcher author Fretwell, Peter British Antarctic Survey Researcher author Peck, Lloyd British Antarctic Survey Researcher author Moulton, Hannah British Antarctic Survey Researcher author Convey, Peter British Antarctic Survey Researcher author NERC EDS UK Polar Data Centre +44 (0)1223 221400 British Antarctic Survey, High Cross, Madingley Road Cambridge Cambridgeshire CB3 0ET United Kingdom PDCServiceDesk@bas.ac.uk https://www.bas.ac.uk/team/business-teams/information-services/uk-polar-data-centre/ information pointOfContact asNeeded completed EARTH SCIENCE > Biosphere > Plant Taxonomy > Algae EARTH SCIENCE > Cryosphere > Snow/Ice theme Global Change Master Directory (GCMD) Science Keywords 2026-01-27 publication 23 Global Change Data Center, Science and Exploration Directorate, Goddard Space Flight Center (GSFC) National Aeronautics and Space Administration (NASA) Greenbelt MD United States of America https://earthdata.nasa.gov/about/gcmd/global-change-master-directory-gcmd-keywords Global Change Master Directory (GCMD) Keywords The information provided on this page seeks to define how the GCMD Keywords are structured, used and accessed. It also provides information on how users can participate in the further development of the keywords. information publisher Antarctica Ice Algae Microbiology Remote Sensing Robert Island Snow Algae theme Robert Island South Shetland Islands place Habitats and biotopes Meteorological geographical features theme GEMET - INSPIRE themes, version 1.0 2021-01-06 revision otherRestrictions no limitations to public access otherRestrictions no limitations license This dataset is supplied under the Open Government Licence v3.0: https://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/ url url crossReference url url crossReference url url largerWorkCitation url url crossReference textTable eng utf8 biota -60.09193 -59.68061 -62.63438 -62.3609 2023-01-07 2023-02-18 It is recommended that careful attention be paid to the contents of any data, and that the author be contacted with any questions regarding appropriate use. If you find any errors or omissions, please report them to polardatacentre@bas.ac.uk. NERC EDS UK Polar Data Centre +44 (0)1223 221400 British Antarctic Survey, High Cross, Madingley Road Cambridge Cambridgeshire CB3 0ET United Kingdom PDCServiceDesk@bas.ac.uk https://www.bas.ac.uk/team/business-teams/information-services/uk-polar-data-centre/ information distributor bytes 1 http://ramadda.data.bas.ac.uk/repository/entry/show?entryid=afd8a811-6e5e-4441-a409-0e6924c36fc4 WWW:LINK-1.0-http--link Get Data Download data download dataset Methodology: Snow algae and ice cap surface samples were collected in 50 ml sterile plastic sample tubes at locations across the north-west part of Robert Island's ice cap (South Shetland Islands, maritime Antarctic; 62°22'44.4"S 59°42'1.78"W) between 7 January 2023 and 18 February 2023. Sampling locations were chosen to encompass a range of snow and ice surface types. 50 ml and 15 ml samples were taken from the top 3 cm of snow or ice weathering crust. Samples were transported within 1 - 3 h to the laboratory at the Chilean (INACH) station Luis Risopatrón, Coppermine Cove, on Robert Island for sample processing, cell counts and field microscopy. Sample tubes were thawed at air temperature (<10 °C) within the research station within 1 - 5 h of sampling. Cell counts were obtained manually by counting auto-fluorescent cells in 2 x 10 µl aliquots from each sample on an Invitrogen Countess 3 FL Automated Cell Counter. The identification of algal cells was based on morphological features observed from the cell counter images. An additional 10 µl aliquot was taken for field microscopy and imaging of the fresh samples using a Dino-lite microscope (Taiwan). Samples for additional microscopy in the UK were prepared by centrifuging a 15 ml aliquot of the sample tube for 2 min at 3,000 rpm, removing the snow-melt supernatant, resuspending the pellet, and transferring it to a 2 ml microfuge tube before being stored at -20 °C. Sample pellets for the metabolomics, pigments, FTIR and total CN were freeze-dried on Robert Island for analysis in the UK. Samples were collected from Robert Island by the RRS Sir David Attenborough (SDA) on 24 February 2023 where they were stored at -20 °C and transported to the UK. Ancylonema cell counts were obtained manually by identifying Ancylonema cells from the Countess 3 FL output images. Due to the poor resolution of the Countess images it was not possible to calculate individual cell counts of other species groups present. An additional 10 µl aliquot was taken for field microscopy and imaging of the fresh samples using a Dino-lite microscope (Taiwan). Biometric measurement of cell length and width for Ancylonema cells were taken from calibrated Dino-lite imagery (n = 570 cells from 37 samples). The extent of algae on the Robert Island ice cap was determined within a WorldView 2 satellite image (Maxar Technologies), taken on 6 February 2023, coincident with our fieldwork. Using the methodology outlined in Gray, A., Krolikowski, M., Fretwell, P., Convey, P., Peck, L. S., Mendelova, M., Smith, A. G., Davey, M. P., 2021. Remote Sensing Phenology of Antarctic Green and Red Snow Algae Using WorldView Satellites. Frontiers in Plant Science, 12, 877-877. https://doi.org/10.3389/FPLS.2021.671981/BIBTEX, algal presence on the ice cap was classified based on chlorophyll-a absorbance within each pixel. This was calculated on a per-pixel basis using Equation 3, which describes the scaled integral of WorldView 2's Band 4 versus Band 3 and Band 5, the centres of which are located within and on either shoulder of the chlorophyll absorption feature. Though this method was originally optimised for detecting algae in snow, it successfully separated every HDRF sample from the background snow or weathering crust, when the equation in Gray et al. 2021 was applied to the collected HDRF spectra. However, an ice cap surface is more complex than a pure snow environment, with snow, weathering crust, glacial ice and different loadings of mineral debris. We do not have enough field spectra from this study to fully deconvolve cell densities based on chlorophyll- a absorption alone. Correlation between the equation in Gray et al. 2021 derived and measured cell densities for the HDRF samples we collected only had an R2 of 0.24. We therefore report a binary presence/absence classification of alg...(7) Data collection: Instrumentation: Automated cell counter Thermo Countess 3. Freeze drier - HarvestRight Home Pro. Data quality: Missing coordinate values are due to coordinates not taken on that field day or location due to weather conditions or battery of GPS unit. asNeeded completed