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493 results for “glacial”
FIGURE 11 in Glacial Relicts? A New Scorpion from Mount Olympus, Greece (Euscorpiidae: Euscorpius)
FIGURE 11. Euscorpius olympus, sp. nov., holotype Ƌ (AMNH), metasomal segments I–IV, dorsal (A, D), lateral (B, E) and ventral (C, F) aspects. Scale bar = 2 mm.
FIGURE 5 in Glacial Relicts? A New Scorpion from Mount Olympus, Greece (Euscorpiidae: Euscorpius)
FIGURE 5. Euscorpius olympus, sp. nov., habitus, dorsal (A, C) and ventral (B, D) aspects. A, B. Paratype Ƌ (AMNH). C, D. Paratype ♀ (AMNH). Scale bar = 10 mm
FIGURE 1. A in Glacial Relicts? A New Scorpion from Mount Olympus, Greece (Euscorpiidae: Euscorpius)
FIGURE 1. A. Map of the Western Palearctic with international borders. Shaded orange rectangle indicates area in B. Dashed orange line indicates boundary of outermost records of Euscorpius Thorell, 1876. B. Map of eastern Greece. Dashed grey line illustrates putative glacial refugia (Médail and Diadema, 2009). Colored symbols represent locality records of Euscorpius olympus, sp. nov. (red triangle), Euscorpius kinzelbachi Tropea et al., 2014 (yellow squares), and Euscorpius aff. sicanus (blue circles).
FIG. 7 in Rediscovery of the wingless Podolian subendemic weevil Humeromima rufipes (Boheman, 1834) (Coleoptera, Curculionidae, Entiminae), a relict from the Last Glacial Maximum
FIG. 7. — Alpha-diversity characteristics of the grass litter Entiminae community (Humeromima rufipes (Boheman, 1834) and co-occurring species) in Western Podolia: A, evenness of the community evaluated using Shannon and Simpson indices; B, top 10 grass litter Entiminae species in Western Podolia. Abbreviations: Invsimpson, 1/Simpson (inverted Simpson); n, the total number of specimens per sample; Sobs, the number of observed species.
FIG. 6 in Rediscovery of the wingless Podolian subendemic weevil Humeromima rufipes (Boheman, 1834) (Coleoptera, Curculionidae, Entiminae), a relict from the Last Glacial Maximum
FIG. 6. — Habitats of Humeromima rufipes (Boheman, 1834): A, meadow steppe, near Burshtyn, Kasova Hora, IFR; B, rock steppe, near Buchyna, Mts. Drancha, LWI; C, rock steppe, near Kuropatnyky, IFR; D, grass steppe, near Kyikiv, LWI; E, meadow steppe, near Mokrotyn, Mt. Harai, LWI; F, meadow steppe, Yaktoriv, Mt. Chekhova, LWI.
FIG. 4 in Rediscovery of the wingless Podolian subendemic weevil Humeromima rufipes (Boheman, 1834) (Coleoptera, Curculionidae, Entiminae), a relict from the Last Glacial Maximum
FIG. 4. — Humeromima rufipes (Boheman, 1834), morphology, female (27365, Mt. Chekhova): A, head, dorsal view; B, head, lateral view; C, head, ventral view; D, scales of elytra; E, maxilla; F, labium, ventral view; G, labium, lateral view; H, antenna; I, head, (cleared specimen); J, fore leg; K, middle leg; L, hind leg; M, tarsus, dorsal and lateral; N, mesonotum; O, coxal cavities, ventral view; P, coxal cavities, lateral view; Q, sterna of pterothorax and ventrites (cleared specimen). Abbreviations: as-am, anterior margin of antennal scrobes; la-te, lacinial teeth; li, ligula; li-ca, cavity of ligula; ocs, occipital sutures; pp, prosternal process; pr, prosternellum; pta, posterior tentorial arms; ptp, posterior tentorial pits; tm3-lo, tarsomere 3 lobes. Scale bars:A-C, H, J-O, 200 µm; D, µm; E-G, 50 µm; I, Q, 300 µm.
FIG. 5 in Rediscovery of the wingless Podolian subendemic weevil Humeromima rufipes (Boheman, 1834) (Coleoptera, Curculionidae, Entiminae), a relict from the Last Glacial Maximum
FIG. 5. — Humeromima rufipes (Boheman, 1834), morphology: A, aedeagus, lateral view; B, aedeagus, dorsal view; C, male sternite 8; D, male sternite 8 and 9; E, endophallus armatute; F, female terminalia; G, female sternite 8 and ovipositor; H, apical part of female terminalia (magnified); I, spermatheca. Abbreviations: buc, bursa copulatrix; co, collum; co-mf, membranous formation in apical half of collum; dp, dorsal plate; ds, ductus spermaticus; es, endophallic sclerite; fst8-ap, apodeme of female sternite 8; fst8-lm, lamina of female sternite 8; fst8-se, setae of female sternite 8; lov, lateral ostial valves; ml-al, apical lobes of median lobe; ml-amp, apical membranous plate of median lobe; ml-ap, apodemes of median lobe; ml-app, apical preostial process; mst8, male sternite 8; mst9-ca, caput of apodeme of sternite 9; no, nodulus (= corpus); oss, ostial sclerite; ra, ramus; sg, spermathecal gland; ut, uterus; va, vagina. Scale bars: A, B, 100 µm; C, E, I, 50 µm; D, F-H, 200 µm; I, Q, 300 µm.
FIG. 3 in Rediscovery of the wingless Podolian subendemic weevil Humeromima rufipes (Boheman, 1834) (Coleoptera, Curculionidae, Entiminae), a relict from the Last Glacial Maximum
FIG. 3. — Humeromima rufipes (Boheman, 1834): A, dorsal, ventral, lateral habitus of female (27761, Luka); B, dorsal, ventral, lateral habitus of male (27732, 0.5 km E Kyikiv). Scale bar: 1 mm.
FIG. 1 in Rediscovery of the wingless Podolian subendemic weevil Humeromima rufipes (Boheman, 1834) (Coleoptera, Curculionidae, Entiminae), a relict from the Last Glacial Maximum
FIG. 1. — Distribution of Humeromima rufipes (Boheman, 1834): A, occurrences plotted as heat points, alongside paleoenvironmental data for central Europe; B, extent of occurrence (EOO) and Area of occupancy (AOO); C, temporal plot of occurrence data showing the number of years since the last collection of H. rufipes in each historic locality.
FIG. 2 in Rediscovery of the wingless Podolian subendemic weevil Humeromima rufipes (Boheman, 1834) (Coleoptera, Curculionidae, Entiminae), a relict from the Last Glacial Maximum
FIG. 2. — Humeromima rufipes (Boheman, 1834): A, lectotype, male, habitus dorsal, lateral, ventral view and labels. Photo credit: by Anna Jerve (NHRS); B, habitus of historical specimen (male) from most remote location in Romania. Photo credit: by Kevin Weissing (SDEI). Scale bars: 1 mm.
Basin-scale spatio-temporal development of glacial lakes in the Hindukush-Karakoram-Himalayas
<p>This dataset offers detailed inventories of glacial lakes for the years 1990, 2000, 2010, and 2020 in the Hindu Kush Himalaya (HKH) region. Landsat satellite imagery was utilised to map glacial lakes, encompassing all lakes that are equal to or exceed 0.0036 km² in size.</p> <p>In the latest inventory from 2020, we identified a total of 19,284 glacial lakes, encompassing a cumulative area of 1191.81 ± 209.21 km². The investigation encompasses comprehensive mapping at the sub-basin level over the whole study area, facilitating regional-scale evaluations of glacial lake distribution and expansion. The findings reveal a significant rise in glacial lakes over the last thirty years, with a 9.31% increase in the number of lakes and a 10.09% increase in total lake area within the HKH region.</p>
Last Glacial Maximum (LGM) climate forcing and ocean dynamical feedback and their implications for estimating climate sensitivity
<p><strong>Citation:</strong> Zhu, J., & Poulsen, C. J. (2021). Last Glacial Maximum (LGM) climate forcing and ocean dynamical feedback and their implications for estimating climate sensitivity. <em>Clim. Past</em>, <em>17</em>(1), 253–267. <a href="https://doi.org/10.5194/cp-17-253-2021">https://doi.org/10.5194/cp-17-253-2021</a></p> <p>Casename:</p> <ul> <li>FCM_PI: b.e12.B1850C5.f19_g16.iPI.01</li> <li>FCM_LGM: b.e12.B1850C5.f19_g16.i21ka.03</li> <li>SOM_PI: e.e12.E1850C5.f19_g16.PI.02</li> <li>SOM_GHG: e.e12.E1850C5.f19_g16.PI.21kaGHG.02</li> <li>SOM_ICE: e.e12.E1850C5.f19_g16.PI.21kaICE.02</li> <li>SOM_2CO2: e.e12.E1850C5.f19_g16.PIx2.02</li> <li>ATM_PI: f.e12.F1850C5.f19_g16.iPI.01</li> <li>ATM_GHG: f.e12.F1850C5.f19_g16.iPI.21kaGHG_ERF</li> <li>ATM_ICE: f.e12.F1850C5.f19_g16.iPI.21kaICE_ERF</li> <li>ATM_2CO2: f.e12.F1850C5.f19_g16.iPI.01.x2</li> </ul> <p><strong>Boundary condition files and the restart files are also provided as .zip files (bc.zip & rest.zip).</strong></p> <p><strong>Check out the Github repository for the setup of the LGM simulation</strong> (i.e., the entire CESM case folder): <a href="https://github.com/jiang-zhu/icesm1.2_lgm_cheyenne">https://github.com/jiang-zhu/icesm1.2_lgm_cheyenne</a></p> <p><strong>[NEW IN V3] More monthly data for PMIP4 (cmorized) are provided (files starting with `PMIP4.NCAR.CESM1.2-FV2`).</strong></p>
500-yr Projections of Thwaites Glacier, Antarctica, with MALI, including glacial isostatic adjustment
<p>This archive contains model code, results, and analysis scripts for<br> reproducing the material presented in the manuscript "Stabilizing effect of<br> bedrock uplift on retreat of Thwaites Glacier, Antarctica, at centennial<br> timescales" by Cameron Book, et al. Questions should be directed to Matt<br> Hoffman (mhoffman@lanl.gov).</p> <p>This archive contains the following directories:</p> <p>|-- MALI_code<br> |-- PIGL_control<br> |-- analysis<br> |-- control<br> |-- run_setup<br> |-- N1<br> |-- N2<br> |-- N3<br> |-- N4<br> `-- PIGL_N3</p> <p><br> 'MALI_code' is a snapshot of the MALI repository used for these simulations,<br> commit 454e0fc8bf384bee1c1560d6c3eaa5fae43bfdda.<br> This commit is present in an older MALI repository that is no longer<br> maintained, at https://github.com/MPAS-Dev/MPAS-Model<br> MALI is currently maintained on Github at https://github.com/MALI-Dev/E3SM<br> Building MALI requires the Albany multiphysics library, which is available<br> at https://github.com/sandialabs/Albany. The simulations presented use Albany<br> master from March 5, 2021.</p> <p>'analysis' contains the scripts used to process the model output and produce<br> the figures and results presented in the manuscript. Filepaths will have to<br> be adjusted to your local layout.</p> <p>'run_setup' is a directory of files and scripts necessary to reproduce the<br> model simulations presented. The GIA model giapy is in the file<br> 'giascript.py'. giapy can also be found on Github at https://github.com/skachuck/giapy</p> <p>'control' is the control run with the GIA model disabled. It corresponds to<br> the run labeled CTRL in the manuscript.</p> <p>'PIGL_control' is the control run using the high melt forcing. It corresponds<br> to the run labeled HM-CTRL in the manuscript.</p> <p>The five run directories included here (N1-N4, PIGL_N3) are the standard<br> ensemble described in the manuscript. (There is a separate archive for the<br> runs briefly mentioned that exclude the elastic response of the lithosphere.)<br> The individual runs have the following correspondence to the manuscript:<br> N1=TYP<br> N2=BEST2<br> N3=VLV-THIN<br> N4=VLV<br> PIGL_N3=HM-VLV-THIN<br> Within each run directory, are the following model output files:<br> globalStats.nc: MALI global, scalar time-series<br> iceload_all.nc: Thwaites Glacier ice load on the GIA grid<br> output_*.nc: MALI spatial output fields, separated by century<br> uplift_GIA_all.nc: GIA output on GIA grid</p>
Clumped-isotope constraint on upper-tropospheric cooling during the Last Glacial Maximum
<p>Ice cores and other paleotemperature proxies, together with general circulation models, have provided information on past surface temperatures and the atmosphere's composition in different climates. Little is known, however, about past temperatures at high altitudes, which play a crucial role in Earth's radiative energy budget. Paleoclimate records at high-altitude sites are sparse, and the few that are available show poor agreement with climate model predictions. These disagreements could be due to insufficient spatial coverage, spatiotemporal biases, or model physics; new records that can mitigate or avoid these uncertainties are needed. Here, we constrain the change in upper-tropospheric temperature at the global scale during the Last Glacial Maximum (LGM) using the clumped-isotope composition of molecular oxygen trapped in polar ice cores. Aided by global three-dimensional chemical transport modeling, we exploit the intrinsic temperature sensitivity of the clumped-isotope composition of atmospheric oxygen to infer that the upper troposphere (effective mean altitude 10 – 11 km) was 6-9ºC cooler during the LGM than during the late preindustrial Holocene. A complementary energy balance approach supports a minor or negligible steepening of atmospheric lapse rates during the LGM, which is consistent with a range of climate model simulations. Proxy-model disagreements with other high-altitude records may stem from inaccuracies in regional hydroclimate simulation, possibly related to land-atmosphere feedbacks.</p>
Results of the geochemical and magnetic studies on cryodust from glacial cores of the Southern Spitsbergen (Svalbard, Norway)
<p>Results of the geochemical and magnetic studies on natural mineral aerosol deposited and trapped in glaciers (cryodust). Samples were collected from glacial cores taken from five glaciers of Southern Spitsbergen (Svalbard, Norway). </p> <p>The samples were collected by means of a hand-operated Kovacs Enterprise® Mark II coring system. Samples (90 mm in diameter) were packed into polyethylene bags, secured, and transported to the Polish Polar Station Hornsund. The core samples were rinsed using deionized water (Polwater DL100; Norm PN-EN ISO 117 3696:1999; conductivity <0.06 μS/cm) and melted at room temperature in the closed new polyethylene bags. After melting samples were filtered through pre-rinsed sterile Millipore Mixed Cellulose Esters filters (white gridded and 0.45 𝜇𝜇m pore size). After filtration, the filters with residuum were dryer at the temperature of 60<sup>o</sup>C.</p> <p>Solid particulates of cryodust were subjected to analysis by Electron MicroProbe (EMP) with special attention paid to their internal structure. A scanning electron microscope (SEM) fitted with a backscattered electron (BSE) detector was used to trace grains topography and composition. Special attention was given to monazite chemical dating. Magnetic methods comprised analyses of magnetic susceptibility <em>κ</em> vs temperature <em>T</em> variations and determination of magnetic hysteresis parameters.</p> <p>More about the methodology, analyses and results can be found here: <a href="https://doi.org/10.3390/atmos11121325">https://doi.org/10.3390/atmos11121325</a></p>
Modelled basal melt rate underneath the Antarctic Lambert–Amery glacial system
<p>This is the modelled basal melt rates in six experiments using different geothermal heat flux (GHF) maps as forcing for an offline coupling between a forward model and an inverse model. The forward model consists of a thermomechanical steady state model using an improved shallow ice approximation in equilibrium with the subglacial hydrological system. The inverse model is solved using 3D full Stokes model.</p> <p>The six GHF maps are from Martos et al. (2017), Shen et al. (2020), An et al. (2015), Shapiro and Ritzwoller (2004), Purucker (2012) and Li et al. (2021).</p> <p>Each filename includes the family name of the first author of the GHF map that is used. For instance, basal_meltrate_an.nc provides the modelled basal melt rates using An et al. (2015) GHF. </p> <p>Files are provided in netcdf format. The netcdf files have 2D grids only. The unit of modelled basal melt rate is mm/yr. The value outside our modelled domain is given as 9.96921e36. The positive value inside our modelled domain represents basal melt rate, while negative represents basal freeze rate.</p> <p>For more information, please see the following paper that is currently accepted by The Cryosphere:</p> <p>H. Kang et al.: Evaluation of six geothermal heat flux maps for the Antarctic Lambert–Amery glacial system, The Cryosphere, 2022.</p> <p> </p>
Dataset: Global range dynamics of the Bearded Vulture (Gypaetus barbatus) from the Last Glacial Maxima to climate change scenarios
<p>This dataset consists of Bearded Vulture <em>Gypaetus barbatus </em>occurrence points which were used to develop a distribution model to study its suitable habitat of this species. Using these data, we modelled the current distribution of Bearded Vulture throughout its entire range and projected the Last Glacial Maxima (LGM), Mid-Holocene (MH) and future distribution under 2070s climate change scenarios. We compiled these data from the entire distribution range in Asia, Europe and Africa using different sources: freely accessible online resources including, eBird and GBIF repositories, published reports and grey literature and occurrence data collected by the authors in the field, mostly in Nepal.</p> <p> </p> <p> </p>
Concentrations of the rare earth elements (REE) and Thorium-232 (232Th) in glacial dust from the northern Gulf of Alaska region
<p>Concentrations of the rare earth elements (REE) and Thorium-232 (232Th) are presented for filtered air (dust) samples collected from the northern Gulf of Alaska region, including from Middleton Island (AK)(59.4214 N, 146.3493 W) and the Copper River delta (60.4324 N, 145.0954 W). Size-fractionated samples were collected in November 2019, using a Tisch Volumetric Flow Controlled (VFC) high volume sampler (Tisch Environmental, TE-5170V- BL) outfitted with a Cascade impactor. The six size fractions collected ranged from <0.49 micrometers (um) to >7.2 um in diameter. This sampler technology is discussed in greater detail in Morton et al, 2013. Samples were filtered with acid-washed Whatman 41 (W41) cellulose fiber filters. Additional bulk dust samples were collected in October 2012, using a Thermo Partisol Plus 2025 using Teflon filters. Samples were fully digested using concentrated nitric and hydrofluoric acids, following the approach of Morton et al, 2013. Samples were analyzed using a Thermofisher iCAP inductively coupled plasma mass spectrometer (ICP-MS) in KED mode, with He as a collision cell gas, adapted from the approach of Trommetter et al (2020). Concentrations were determined from standard curves using a REE ICP-MS standard from High-Purity Standards (that also contained 232Th). Three internal standards (Ge, In, and Bi) were added to both samples and standards, to correct for short-term variability in the instrument response and to evaluate stability of mass response during the ICP-MS run. Concentration estimates for the REE and 232Th were blank-corrected using full-process blanks that included filters deployed during times when there was no known dust deposition. Most of the full-process blank concentrations were 100 times or more smaller than the concentrations of our lowest standard (with the exception of Ce, the concentration of which was ~seven times smaller than our lowest standard. This means that our blank concentrations were very low but also not quantified extremely accurately. Our best estimates are that the full-process blanks, including filters, ranged from 0.02 picograms per square centimeter (pg cm-2) for Eu, Tb, and Ho, to 2 pg cm-2 for Ce. These blank concentrations were in all cases 40 times or more smaller than our lowest REE sample concentration for the <0.49 um size fraction with the smallest amount of dust, and ~3 orders of magnitude smaller than the signal of the largest samples. The REE data are also presented in a double-normalized format that first normalizes to concentrations of Post Archean Australian Shale and then normalizes to the mean REE concentration. The normalization approach is slightly modified from that of Serno et al, 2014.</p>
A Seasonally Delayed Sea Ice Response and Arctic Amplification during the Last Glacial Inception
<p>Presented here is the datasets and corresponding codes used in creating Figures of the article "<strong><span>A Seasonally Delayed Sea Ice Response and Arctic Amplification during the Last Glacial Inception</span></strong>".</p>
FIGURE 1 in First study of food webs in a large glacial river: the trophic role of invasive trout
FIGURE 1 | Sampling areas in the Santa Cruz River, Argentina. Upstream area corresponds to the locally known "Labyrinth", and Midstream area correspond to "Estancia San Ramon". Map created by the authors, upper picture taken from Google Earth (R).
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OpenNeuro
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