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FIGURE 5 in Notes on the species of Perkinsiana (Polychaeta: Sabellidae) from Antarctica with the description of P. brigittae sp. nov.
FIGURE 5. Latitudinal distribution of Perkinsiana species.
Figure 2 from: Piazza P, Blazewicz-Paszkowycz M, Ghiglione C, Alvaro M, Schnabel K, Schiaparelli S (2014) Distributional records of Ross Sea (Antarctica) Tanaidacea from museum samples stored in the collections of the Italian National Antarctic Museum (MNA) and the New Zealand National Institute of Water and Atmospheric Research (NIWA). ZooKeys 451: 49-60. https://doi.org/10.3897/zookeys.451.8373
Figure 2 - Map of sampling stations. Green dots: samples stored at the MNA. Blue dots: samples stored at the NIWA.
Figure 1 from: Adams B, Wall D, Virginia R, Broos E, Knox M (2014) Ecological Biogeography of the Terrestrial Nematodes of Victoria Land, Antarctica. ZooKeys 419: 29-71. https://doi.org/10.3897/zookeys.419.7180
Figure 1 - Victoria Land, Antarctica. Labeled areas represent study locations and major geographic features referenced in the tables and text. Box inset of the McMurdo Dry Valleys is rotated 180 °and expanded in Figure 2.
Figure 2 from: Adams B, Wall D, Virginia R, Broos E, Knox M (2014) Ecological Biogeography of the Terrestrial Nematodes of Victoria Land, Antarctica. ZooKeys 419: 29-71. https://doi.org/10.3897/zookeys.419.7180
Figure 2 - McMurdo Dry Valleys, Antarctica. Labeled areas represent study locations and major geographic features referenced in the tables and text.
Supplementary material 2 from: Grewe F, Lagostina E, Wu H, Printzen C, Lumbsch HT (2018) Population genomic analyses of RAD sequences resolves the phylogenetic relationship of the lichen-forming fungal species Usnea antarctica and Usnea aurantiacoatra. MycoKeys 43: 91-113. https://doi.org/10.3897/mycokeys.43.29093
Overview of RADseq results after individual steps of RAD analyses :
Figure 3 from: Grewe F, Lagostina E, Wu H, Printzen C, Lumbsch HT (2018) Population genomic analyses of RAD sequences resolves the phylogenetic relationship of the lichen-forming fungal species Usnea antarctica and Usnea aurantiacoatra. MycoKeys 43: 91-113. https://doi.org/10.3897/mycokeys.43.29093
Figure 3 Genomic variation by non-parametric DAPC. ADAPC plot of the densities of U.antarctica (blue) and U.aurantiacoatra (green) on the first retained discriminant function B Bar plot of group membership probabilities.
Figure 2 from: Grewe F, Lagostina E, Wu H, Printzen C, Lumbsch HT (2018) Population genomic analyses of RAD sequences resolves the phylogenetic relationship of the lichen-forming fungal species Usnea antarctica and Usnea aurantiacoatra. MycoKeys 43: 91-113. https://doi.org/10.3897/mycokeys.43.29093
Figure 2 Pairwise Gst, G'st and D distribution. Pairwise values of Nei's Gst (green), Hedrick's G'st (blue) and Jost's D (yellow) are plotted by their frequency.
Figure 1 from: Grewe F, Lagostina E, Wu H, Printzen C, Lumbsch HT (2018) Population genomic analyses of RAD sequences resolves the phylogenetic relationship of the lichen-forming fungal species Usnea antarctica and Usnea aurantiacoatra. MycoKeys 43: 91-113. https://doi.org/10.3897/mycokeys.43.29093
Figure 1 Phylogenetic tree inferred from the U.antarctica and U.aurantiacoatraRADseq data. The clades of each species are highlighted by brackets. Bootstrap values are indicated at the branches. The unit of branch length is substitutions per site. Note that branches leading to both major clades were abbreviated by 0.4 substitutions per site.
Supplementary material 1 from: Grewe F, Lagostina E, Wu H, Printzen C, Lumbsch HT (2018) Population genomic analyses of RAD sequences resolves the phylogenetic relationship of the lichen-forming fungal species Usnea antarctica and Usnea aurantiacoatra. MycoKeys 43: 91-113. https://doi.org/10.3897/mycokeys.43.29093
Origin of samples used for this study :
Figure 4 from: Grewe F, Lagostina E, Wu H, Printzen C, Lumbsch HT (2018) Population genomic analyses of RAD sequences resolves the phylogenetic relationship of the lichen-forming fungal species Usnea antarctica and Usnea aurantiacoatra. MycoKeys 43: 91-113. https://doi.org/10.3897/mycokeys.43.29093
Figure 4 Clustered fineRADstructure co-ancestry matrix. A Full dataset including U.antarctica collected on the Antarctic Peninsula in addition to U.antarctica and U.aurantiacoatra collected on King George Island and Elephant Island B Reduced dataset with all U.antarctica and U.aurantiacoatra collected on King George Island and Elephant Island. Two major clades are corresponding to the two species U.antarctica (top-left) and U.aurantiacoatra (bottom-right). The top and left trees were calculated from the co-ancestry matrix to sort the individuals by their population structure. The matrix is diagonally split into the top-right half showing raw data and the bottom-left half displaying aggregated data.
Supplementary material 3 from: Grewe F, Lagostina E, Wu H, Printzen C, Lumbsch HT (2018) Population genomic analyses of RAD sequences resolves the phylogenetic relationship of the lichen-forming fungal species Usnea antarctica and Usnea aurantiacoatra. MycoKeys 43: 91-113. https://doi.org/10.3897/mycokeys.43.29093
Correlation of RADseq results after individual steps of RAD analyses :
Geochemistry of Cryoconite Holes, Troll Blue Ice Area, Antarctica
<p><strong>Introduction</strong></p> <p>Cryoconite holes, snow and glacier ice were sampled in eight localities of blue ice in the vicinity of Troll Station, Antarctica during December 2019 and January 2020. The samples were collected as part of the Research Council of Norway-funded BIOICE Project (Grant No. 288402) by Prof. Andy Hodson and Dr Aga Nowak.</p> <p>Data are available as a single Excel spreadsheet with two tabs: one containing the chemistry data and the other containing the location and dimension of the holes, where available.</p> <p><strong>Contact</strong>: Andrew.Hodson@unis.no</p> <p><strong>Methods</strong></p> <p>Cryoconite holes in the Troll blue ice area are typically covered by an ice lid, even during summer, when subsurface melting is caused by light penetration through the ice and its absorption by underlying debris particles. Access to the underlying water was therefore achieved first by drilling through the ice lid with a 5 cm Kovacs ice auger. The auger was cleaned at each site before use and the ice chips from the lid were sampled, taking care to ensure a depth-integrated sample was collected in each case. Once the lid was penetrated, a syringe was used to extract water from the hole beneath the lid. Samples of glacier ice were taken by drilling the ice auger into the glacier beside the holes.</p> <p> </p> <p>Samples for major ion analysis (here Ca<sup>2+</sup>, Mg<sup>2+</sup>, Na<sup>+</sup>, K<sup>+</sup>, Cl<sup>-</sup>, SO<sub>4</sub><sup>2-</sup>) were syringe-filtered through 0.45 µm Whatman Puradisc Aqua 30 filters and stored in 50 mL Corning centrifuge tubes after being rinsed with filtrate. The analysis was conducted on Dionex DX90 Ion Chromatographs (University of Sheffield, UK) calibrated in the range 0.01-2 mg L<sup>-1 </sup>for cations and in the range 0.25-2 mg L<sup>-1 </sup>for anions. Precision errors for these ions were all <2% for mid-range standards, while the detection limit was ≤ 0.01 mg L<sup>-1</sup> for cations and 0.05 mg L<sup>-1</sup> for anions (calculated as three times the standard deviation of ten blanks). All ions described above are reported in mg L<sup>-1</sup>.</p> <p>Quantification of NH<sub>4</sub><sup>+</sup>, PO<sub>4</sub><sup>3-</sup>, NO<sub>3</sub><sup>-</sup> and Si in the above samples was conducted using a Skalar San++ Continuous Flow Analyser Autoanalyser (University of Sheffield, UK), calibrated in the range 0-3 mg L<sup>-1</sup>. The limit of detection for these ions was ≤ 0.05 mg L<sup>-1</sup> (calculated as three times the standard deviation of ten blanks). These analyses employed standard colorimetric methods (based on The European Standard EN ISO, 1996, 2002, 2004 and 2005). Samples are reported as mgN L<sup>-1</sup>, mgP L<sup>-1</sup> and mgSi L<sup>-1</sup>, accordingly</p> <p>For both dissolved organic and inorganic carbon (DOC and DIC), a 40mL aliquot was filtered through a Whatman Puradisc Aqua 30 0.45 um pore size filter and stored in Sievers-certified sterilised glass vials. DOC and DIC analyses used the membrane conductometric method of the Sievers 5310 Analyser with UV and persulphate digestion (University Centre In Svalbard, Norway) with a detection limit 0.01 mg L<sup>-1</sup> and < 5% precision errors according to repeat analysis of mid-range (0.4 mg L<sup>-1</sup>) Sievers-certified calibration solutions. All samples are reported at mgC L<sup>-1</sup>.</p> <p>Samples for water isotope analysis were collected as unfiltered 20 mL aliquots in a screw-top HDPE bottle. The bottles were subsampled into 1.5 mL vials with septa closures and loaded into the auto-sampler tray of a CDRS (cavity ringdown laser spectroscopy) instrument (L1102-<em>i</em> Picarro water isotope analyzer and A0211 high-precision vaporiser, University of Cambridge). Each sample was injected nine times and the first three injections were rejected to reduce memory effects from the previous sample. Average values from the remaining six injections were averaged when in-run precision was less than ±0.1 for δ<sup>18</sup>O. Internal standards were run after eight samples and the external reproducibility of these standards was <1‰ 2<em>σ</em>. All results are reported in parts per thousand (‰) relative to V-SMOW.</p> <p> </p>
Output from the Glacier Energy and Mass Balance (GEMB v1.0) forced with 3-hourly RACMO fields, Greenland and Antarctica 1979-2014
<p>These model output are those presented in the manuscript that provides the first description of version 1.0 of the open-source Glacier Energy and Mass Balance model. GEMB is a column model of ice sheet and glacier surface-atmospheric energy and mass exchange as well as firn state. GEMB has been integrated into the open-source Ice-Sheet and Sea-level System Model which can be downloaded at https://issm.jpl.nasa.gov/. Here, GEMB is forced with 3-hourly RACMO output from 1979-2014. </p>
Datasets and models about the geophysical characterization of the Mt. Melbourne Volcanic Field (Northern Victoria Land, Antarctica)
<p>Supplementary materials about the geophysical characterization of the Mt. Melbourne Volcanic Field</p>
Phenomenological images (CL-CAM1B) of Crater Lake CALM site, Deception island, Antarctica (2022).
<p>Images acquired by a phenomenological automatic time-lapse camera (CL-CAM1B) located in Crater Lake permafrost and active layer monitoring site in Crater Lake sounders in Deception island, Antarctica, in 2022.</p> <ul> <li>File code: DEC_CL_CAM1B_2022_v100</li> <li>Location code: DEC</li> <li>Site code: CL</li> <li>Instrument code: CAM1B</li> <li>Period: 2022</li> <li>Version: 1.0.0 (jpg images as they were obtained from camera, without processing)</li> <li>Camera/manufacturer: CC5MPX by Campbell Scientific Inc.</li> <li>Resolution/Type/Format: 5Mpixels in RGB in jpg files</li> <li>Frequency: 3 images per day at 14h, 15h and 16h GMT</li> <li>Site: Close to Crater Lake CALM site, in Crater Lake sounders of Deception island, Antarctica.</li> <li>Location: </li> <li>Elevation:</li> <li>Initial dataset date/time: January 14, 2022 14:00h GMT</li> <li>Final dataset date/time: January 9, 2022 16:00h GMT</li> <li>Gaps: None</li> <li>Notes: <ul> <li>Folders: 15</li> <li>Files: 1289</li> <li>Other files: none</li> <li>Folder names structure: year_month</li> <li>Datafiles names structure: Site_camera_year_month_day_hour_minute_second.jpg</li> </ul> </li> </ul>
From atmospheric water isotopes measurement to firn core interpretation in Adelie Land: A case study for isotope-enabled atmospheric models in Antarctica: DATASET
<p>Thoses datasets are associated to the non-published study (at date): From atmospheric water isotopes measurement to firn core interpretation in Adelie Land: A case study for isotope-enabled atmospheric models in Antarctica.</p> <p>- date is in datetime format.</p> <p>- humidite is humidity (in ppmv)</p> <p>- d18 and dD are isotopic compositions (in per mil)</p> <p>- temp is 2-meters temperature in °C</p> <p>- pression is pressure (in mbar)</p> <p>- vitesse_vent is wind speed (in m/s)</p> <p>- direction_vent is wind direction (in °)</p> <p>- RH is relative humidity (in %)</p>
Polarimetric Radar Data and Ice Core Data Collected at Hammarryggen Ice Rise, Antarctica
<p><strong>Polarimetric Radar Data and Ice Core Data Collected at Hammarryggen Ice Rise</strong></p> <p><strong>AUTHORS</strong>:<br> Frank PATTYN, Sarah WAUTHY, Sainan SUN, Jean-Louis TISON, Veronica TSIBULSKAYA<br> Laboratoire de Glaciologie<br> Université libre de Bruxelles (ULB)<br> Brussels, Belgium</p> <p><strong>FUNDING</strong>:<br> Project MASS2ANT (Belgian Science Policy Office - BELSPO)</p> <p> </p> <p>DATA FILES ACCOMPAGING PAPER BY REZA ERSHADI et al. (2023)<br> Deciphering the Ice Dynamic History of a Promontory Ice Rise with Triple Junction: A Polarimetric Radar Approach</p> <p><br> <strong>Autonomous Phase Sensitive Radar (ApRES) measurements Hammaryggen Ice Rise</strong><br> <br> FILES: Folders 2018p00 to 2018p14 + ApRESpos.csv<br> Measurements by F. Pattyn and S. Sun</p> <p>Each folder contains the raw ApRES data sampled at the site. The 'Survey' files are single measurements with exactly the same antenna orientation and taken almost a year apart (exact date in the file name). The 'Survey' or 'DATA' files ending on HH, HV, VV, VH are measurements for each of the four antenna orientations for the polarimetric analysis. Each folder is a data point along a survey line perpendicular to the ice divide of the Hammaryggen ice rise, East Antarctica. The geographic positions of the data points <br> are given in the table ApRESpos.csv.</p> <p><br> <strong>Eigen values of c-axes distribution for discrete samples from the Hammaryggen ice core</strong></p> <p>FILE: HammeryggenIceFabric.xls<br> Measurements by S. Wauthy, J.L. Tison and V. Tsibulskaya</p> <p>This table provides the eigen values of c-axes distribution for discrete samples from the Hammaryggen ice core (Wauthy et al., 2023). Data have been collected from discrete 8 cm vertical thin sections. The thin sections were obtained using standard techniques in glaciology (Langway, 1958) and analysed with an Automatic Fabric Analyzer (AFI, Wilson et al., 2003). Raw data from <br> the AFI are at the pixel scale. To derive ice fabric data at the ice grain scale, the FAME software has been used (Hamme and Peternell, 2006). The software delineates grains using image analysis techniques and derives statistics for grain number, size and morphology and ice crystal orientation in space (c-axes). The software calculates eigen vectors and values for the c-axes distribution in each thin section.</p> <p>Column A of the table gives the top depth of each thin section analyzed, columns B to D give the eigen-values of the c-axes distribution used in this paper, to compare to modelled ones.</p> <p>References:</p> <p>Hamme, D.M. and Peternell, M. (2016) FAME software for analysing rock microstructures, Computer and Geosciences, vol. 90, Part A, pp. 24-33. Doi: 10101b/j.cogeo.2016.02.010</p> <p>Langway, C. C. J. (1958). Ice fabrics and the Universal stage, CRREL Technical Report, 62: 16.</p> <p>Wauthy, S., Tison, J.-L., Inoue, M., El Amri, S., Sun, S., Claeys, P., and Pattyn, F.: Physico-chemical properties of the top 120 m of two ice cores in Dronning Maud Land (East Antarctica): an open window on spatial and temporal regional variability of environmental proxies, Earth Syst. Sci. Data Discuss. [preprint], https://doi.org/10.5194/essd-2023-152, in review, 2023</p> <p>Wilson , C.J.L., Russell-Head D.S. and Sim, H.M. (2003) The application of an automated fabric analyser system to the textural evolution of folded ice layers in shear zones, Annals of Glaciology, vol. 37, PP. 7-17</p> <p> </p> <p> </p>
Reconstructing ancient dispersal through Antarctica: a case study of stream-inhabiting beetles
<p>Scripts, data and resulting outputs</p>
Hull fouling marine invasive species pose a very low, but plausible, risk of introduction to East Antarctica in climate change scenarios
Open the record for dataset details and reuse information.
Retrotransposon-based genetic diversity of Deschampsia antarctica Desv. from King George Island (Maritime Antarctic)
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