d93d9ae6-4eff-4d9a-9997-d0ed06c3df1b 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 2025-07-14 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 Richness and abundance of plant and animal pathogenic fungi in Patagonian, sub-Antarctic and Maritime Antarctic soil samples collected January-February 2018 2025-07-14 creation 2025-07-14 revision 2025-07-14 publication 2025-07-14 released 1.0 https://doi.org/10.5285/d93d9ae6-4eff-4d9a-9997-d0ed06c3df1b doi GB/NERC/BAS/PDC/02081 https://data.bas.ac.uk/ NE/P003079/1 award Please cite this item as: Newsham, K.K., Biersma, E.M., Prieme, A., Molina-Montenegro, M.A., & Goodall-Copestake, W.P. (2025). Richness and abundance of plant and animal pathogenic fungi in Patagonian, sub-Antarctic and Maritime Antarctic soil samples collected January-February 2018 (Version 1.0) [Data set]. NERC EDS UK Polar Data Centre. https://doi.org/10.5285/d93d9ae6-4eff-4d9a-9997-d0ed06c3df1b 57 soil samples were collected from 12 sites across Patagonia, the sub-Antarctic and the Maritime Antarctic between January and February 2018. The dataset presented here comprises two tables. The first shows the numbers of DNA reads of 105 genera of plant or animal pathogenic fungi in the soil samples. In the second table, for each of the 57 soil samples, seven bioclimatic variable predictors, six measures of soil chemistry, the total number of fungi reads and plant and animal pathogen richness and abundance are given, as well as the relative abundance of each fungal genus in each sample. The data in this second table were inputted into LASSO regression models and species indicator analyses. This research was jointly funded by the NERC-CONICYT award (NE/P003079/1 and PII20150126, respectively) and Danish National Research Foundation award (VOLT, DNRF 168). No credit. completed Newsham, Kevin K British Antarctic Survey Researcher author Biersma, Elisabeth M Natural History Museum of Denmark Researcher author Prieme, Anders University of Copenhagen Researcher author Molina-Montenegro, Marco A University of Talca Researcher author Goodall-Copestake, William P Royal Botanic Garden Edinburgh 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 > Fungi 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 air temperature animal pathogenic fungi emerging pathogens phytopathogens plant pathogenic fungi precipitation soil pH theme Torres del Paine, moraines near Frances Glacier Chile Tierra del Fuego, beach near Porvenir Chile Fuerte Bulnes Chile Busen Region, Pohlia Falls South Georgia Island Busen region, Upper Husdal Valley South Georgia Island Thatcher Peninsula, Maiviken South Georgia Island Tierra del Fuego, pass near Karukinka Natural Park Chile Signy Island, Backslope South Orkney Islands Livingston Island, Hannah Point South Shetland Islands Antarctic Peninsula, Marguerite Bay, Lagoon Island Antarctica Antarctic Peninsula, Marguerite Bay, Léonie Island Antarctica Antarctic Peninsula, Marguerite Bay, Lagotellerie Island Antarctica place Habitats and biotopes theme GEMET - INSPIRE themes, version 1.0 2021-01-06 revision otherRestrictions public access limited according to Article 13(1)(e) of the INSPIRE Directive license Open Government Licence v3.0 otherRestrictions Data released under Open Government Licence V3.0: otherRestrictions This dataset is under embargo until the publication of the relevant manuscript. url url crossReference url url crossReference url url crossReference url url dependency url url dependency url url dependency url url dependency url url dependency url url dependency url url dependency url url dependency url url dependency url url dependency url url crossReference textTable eng utf8 biota -70.252 -70.252 -53.469 -53.469 1981-01-01 2010-12-31 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 text/csv bytes 180224 http://ramadda.data.bas.ac.uk/repository/entry/show?entryid=d93d9ae6-4eff-4d9a-9997-d0ed06c3df1b WWW:LINK-1.0-http--link Get Data Download data download dataset Methodology: Soil samples were collected in January-February 2018 from 12 sites between Torres del Paine (Chile) and Lagotellerie Island (Maritime Antarctica). Four to five samples of barren soils (c. 20 g fresh weight) were sampled 1-2 m from Colobanthus quitensis plants into sterile containers that were stored at c. 4 °C before being frozen at -20 °C, prior to transfer to the lab, also at -20 °C. The samples were defrosted and mixed. Soil pH value was measured in a suspension of 5 g soil and 20 ml of distilled water. Soil C/N ratio was calculated following measurement of total C and N in freeze-dried soils using a TruSpec CN analyser. Water-soluble carbon (C) and nitrogen (N) were extracted from 5 g of fresh soil in 25 ml distilled water for 60 min. After filtration through filter paper, the concentrations of total dissolved organic C were measured using a Shimadzu TOC-L CSH/CSN total organic C analyzer. Total dissolved N was measured with a FIAstar 5000 flow injection analyser after digesting extracts in sulphuric acid with selenium as the catalyst. Dissolved concentrations of NO3--N and NH4+-N were measured using a FIAstar 5000 flow injection analyser using cadmium reduction and indophenol blue and molybdenum blue methods, respectively. DNA was extracted from 0.25 g subsamples of freeze-dried soil using a FastDNA Spin Kit for Soil. The internal transcribed spacer (ITS) 2 region of fungal DNA was amplified using the primers ITS4 and ITS7. PCR amplifications consisted of two steps: (i) primers and template DNA (1 µl) were added to Illustra puReTaq Ready-To-Go PCR Beads and were thermocycled at 94 °C for 2 min, then 35 cycles at 94 °C for 30 s, 56 °C for 30 s and 72 °C for 30 s, followed by an extension step at 72 °C for 5 min and (ii) 2 µl of the diluted PCR product was added to a reaction mixture consisting of 0.15 µl DNA polymerase (AccuPrimeTM Taq DNA Polymerase High Fidelity, Invitrogen), 2 µl 10 x AccuPrimeTM PCR Buffer II, 1 µl (770 nM) of custom-tagged forward and reverse primers and 13.85 µl sterile water. Mixtures were thermocycled at 94 °C for 2 min, then 14 cycles at 94 °C for 30 s, 56 °C for 30 s and 72 °C for 30 s, followed by an extension step at 72 °C for 5 min. Amplicons were purified in 1% agarose gels using a Montage Gel Extraction Kit. The concentrations of amplicons were measured using Qubit dsDNA HS assays and fluorescence was measured using a Qubit fluorometer. Samples, pooled in equimolar amounts, were paired-end sequenced over two Illumina MiSeq flowcells. Demultiplexed sequences from each sample were trimmed of primers using cutadapt 1.18. DADA2 v1.22.0 was subsequently used in R v 4.1.1 for quality filtering, amplicon sequence variant inference and taxon assignment. Quality filtering removed all sequences with ambiguous bases (trncQ=11), >2 expected errors and lengths <50 bp. Error rates were estimated for forward and reverse sequences and amplicon sequence variants inferred before merging with a 30 base pair minimum overlap. Chimeras were removed and taxonomies assigned to resulting amplicon sequence variants using the RDP classifier with the sh_general_release-dynamimc_all_25.07.2023 reference from UNITE. The decontam v1.14.0 package was then used to remove putative contaminants identified in negative controls (threshold value 1.0). Taxonomies and occurrences of the removed amplicon sequence variants were cross-checked through manual inspection. The taxonomy-assigned, decontaminated amplicon sequence variants were clustered into operational taxonomic units (OTUs) at 98% similarity over 90% of sequence length using the BLASTCLUST algorithm in the package blast-legacy v2.2.26. For each OTU, the taxonomies for its constituent amplicon sequence variants were compared to validate the OTU taxonomy used for all subsequent analyses. Le...(20) Data collection: Instruments Qubit fluorometer (Thermofisher, USA) Illumina MiSeq System (Illumina, San Diego, California, USA) TruSpec CN analyser Leco (St Joseph, MI, USA) Shimadzu TOC-L CSH/CSN total organic C analyzer (Shimadzu, Kyoto, Japan) FIAstar 5000 flow injection analyser (Foss Tecator, Hoganas, Sweden) Software R versions 4.1.1 and 4.1.3 R packages: terra v 1.6-47, glmnet v4.1-8, DADA2 v1.22.0, decontam v1.14.0 and indicspecies v1.7.15 Python: cutadapt 1.18 UNITE: RDP classifier with sh_general_release-dynamimc_all_25.07.2023 blast-legacy v2.2.26 Web of Science CHELSA database v. 2.1 CHELSA-BIOCLIM+ database iNEXT package Data quality: Raw data are shown. The data have not been cleaned. asNeeded completed