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45 results for “mountain glaciers”
Glacier Inventory and Elevation Change Data for the Shule River, Heihe River, and Shiyang River Basins in the Qilian Mountains (1990-2020)
<p>This dataset contains comprehensive glacier inventory data and elevation change measurements for the Qilian Mountains, specifically covering the Shule River, Heihe River, and Shiyang River basins. The dataset includes:</p> <ol> <li> <p>Glacier inventory data for the years 1990, 1995, 2000, 2005, 2010, 2015, and 2020. The inventory provides detailed information on glacier attributes such as area, length, orientation, and other essential characteristics for each of the target years.</p> </li> <li> <p>Elevation change data for glaciers within the Qilian Mountains during the periods 2000-2010 and 2010-2020. This data tracks changes in glacier surface elevation, providing valuable insights into glacier mass balance and regional climate change impacts.</p> </li> </ol> <p>The data is critical for understanding the response of glaciers to climate change over the past three decades and will support ongoing research in glaciology, hydrology, and environmental monitoring.</p>
A regionally resolved inventory of High Mountain Asia surge-type glaciers, derived from a multi-factor remote sensing approach
<p>This file is the .csv database compiling surge-type glaciers automatically identified in Guillet et al (2022).</p> <p>File format is compliant with the Randolph Glacier Inventory (RGI) V6.0.</p> <p>If you have questions about the dataset - please refer to the following reference or contact Dr. Guillet.</p> <table> <tbody> <tr> <td>Guillet, G., King, O., Lv, M., Ghuffar, S., Benn, D., Quincey, D., & Bolch, T. (2022). A regionally resolved inventory of High Mountain Asia surge-type glaciers, derived from a multi-factor remote sensing approach. <em>The Cryosphere</em>, <em>16</em>(2), 603-623.</td> </tr> <tr> <td> </td> </tr> </tbody> </table> <p> </p>
Similar vegetation-geomorphic disturbance feedbacks shape unstable glacier forelands across mountain regions
<p>Glacier forelands are among the most rapidly changing landscapes on Earth. Stable ground is rare as geomorphic processes move sediments across large areas of glacier forelands for decades to centuries following glacier retreat. Yet, most ecological studies sample exclusively on stable terrain to fulfil chronosequence criteria, thus missing potential feedbacks between geomorphic disturbances and vegetation colonization. By influencing vegetation and soil development, such vegetation-geomorphic disturbance feedbacks could be crucial to understand glacier foreland ecosystem development in a changing climate. We surveyed vegetation and environmental properties, including geomorphic disturbance intensities, in 105 plots located on both stable and unstable moraine terrain in two geomorphologically active glacier forelands in New Zealand and Switzerland. Our plot data showed that geomorphic disturbance intensities changed permanently from high/moderate to low/stable when vegetation reached cover values around 40%. Around this cover value, species with response and effect traits adapted to geomorphic disturbances dominated. This suggests that such species can act as 'biogeomorphic' ecosystem engineers that stabilize ground through positive feedback loops. Across floristic regions, biogeomorphic ecosystem engineer traits creating ground stabilization, such as mat growth and association with mycorrhiza, are remarkably similar. Non-metric multidimensional scaling revealed a linked sequence of decreasing geomorphic disturbance intensities and changing species composition from pioneer to late successional species. We interpret this linked geomorphic disturbance-vegetation succession sequence as 'biogeomorphic succession', a common successional pathway in unstable river and coastal ecosystems across the world. Soil and vegetation development were related to this sequence, and only advanced once biogeomorphic ecosystem engineer species covered 40–45% of a plot, indicating a crucial role of biogeomorphic ecosystem engineer stabilization. Different topoclimatic conditions could explain variance in biogeomorphic succession timescales and ecosystem engineer root traits between the glacier forelands. As glacier foreland ground is widely unstable, we propose to consider glacier forelands as 'biogeomorphic ecosystems' in which ecosystem structure and function are shaped by geomorphic disturbances and their feedbacks with adapted plant species, similar to rivers and coasts.</p>
Similar vegetation-geomorphic disturbance feedbacks shape unstable glacier forelands across mountain regions
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Data from: The last 50 years of climate-induced melting of the Maliy Aktru glacier (Altai Mountains, Russia) revealed in a primary ecological succession
In this article, we report and discuss the results obtained from a survey of plants, microorganisms (bacteria and fungi), and soil elements along a chronosequence in the first 600 m of the Maliy Aktru glacier's forefront (Altai Mountains, Russia). Many glaciers of the world show effects of climate change. Nonetheless, except for some local reports, the ecological effects of deglaciation have been poorly studied and have not been quantitatively assessed in the Altai Mountains. Here, we studied the ecological changes of plants, fungi, bacteria, and soil elements that take the form of a primary ecological succession and that took place over the deglaciated soil of the Maliy Aktru glacier during the last 50 year. According to our measurements, the glacier lost about 12 m per year during the last 50 years. Plant succession shows clear signs of changes along the incremental distance from the glacier forefront. The analysis of the plant α‐ and β‐diversity confirmed an expected increase of them with increasing distance from the glacier forefront. Moreover, the analysis of β‐diversity confirmed the hypothesis of the presence of three main stages of the plant succession: (a) initial (pioneer species) from 30 to 100 m; (b) intermediate (r‐selected species) from 110 to 120–150 m; and (c) final (K‐selected species) from 150 to 550. Our study also shows that saprotrophic communities of fungi are widely distributed in the glacier retreating area with higher relative abundances of saprotroph ascomycetes at early successional stages. The evolution of a primary succession is also evident for bacteria, soil elements, and CO2 emission and respiration. The development of biological communities and the variation in geochemical parameters represent an irrefutable proof that climate change is altering soils that have been long covered by ice.
Data from: Historical retreat of alpine glaciers in the Ahklun Mountains, western Alaska
The Ahklun Mountains support the only extant glaciers in western Alaska. The glaciers were originally mapped by the U.S. Geological Survey using photogrammetry methods based on 1972 - 1973 aerial photos. We surveyed for presence or absence of the glaciers by fixed-wing aircraft in 2006. Of 109 glaciers originally mapped, 10 (9%) had disappeared. Using aerial imagery of a subset of 76 glaciers at three time steps between 1957 - 2009, we determined the average rate of areal loss was 45% over 52 years. At this rate, it is likely that all Ahklun Mountain glaciers will be extinguished by the end of the current century.
On following pages: 48. Mutable Shrew (Sorex mutabilis); 49. Verapaz Shrew (Sorex veraepacis); 50. Rock Shrew (Sorex Mexican Long-tailed Shrew (Sorex oreopolus); 55. Orizaba Long-tailed Shrew (Sorex orizabae); 56. Chestnut-bellied Shrew (Sorex rohweri): 60. South-eastern Shrew (Sorex longirostris); 61. Masked Shrew (Sorex cinereus); 62. Maryland Shrew Mountain Shrew (Sorex milleri): 66. Preble's Shrew (Sorex preblei); 67. Prairie Shrew (Sorex hayden); 68. Pribilof Island Saint Lawrence Island Shrew (Sorex jackson); 72. Kamchatka Shrew (Sorex camtschaticus); 73. Paramushir Shrew (Sorex (Sorex ornatus); 77. American Water Shrew (Sorex palustris); 78. Western Water Shrew (Sorex navigaton; 79. Glacier Bay Baird's Shrew (Sorex bairdi); 83. Pacific Shrew (Sorex pacificus); 84. Fog Shrew (Sorex sonomae); 85. New Mexico Shrew dispan; 51. Smoky Shrew (Sorex fumeus); 52. Inyo Shrew (Sorex tenellus); 53. Dwarf Shrew (Sorex nanus); 54. (Sorex ventralis); 57. Veracruz Shrew (Sorex veraecrucis); 58. Ixtlan Shrew (Sorex ixtlanensis); 59. Olympic Shrew (Sorex fontinalis); 63. Mount Lyell Shrew (Sorex lyell); 64. Zacatecas Shrew (Sorex emarginatus), 65. Carmen Shrew (Sorex pribilofensis); 69. Barren Ground Shrew (Sorex ugyunak); 70. Portenko's Shrew (Sorex portenkol); 71. leucogasten; 74. American Pygmy Shrew (Sorex hoyi); 75. Vagrant Shrew (Sorex vagrans); 76. Ornate Shrew Water Shrew (Sorex alaskanus); 80. Eastern Water Shrew (Sorex albibarbis); 81. Marsh Shrew (Sorex bendiril); 82. (Sorex neomexicanus); 86. Montane Shrew (Sorex monticolus). in Soricidae
On following pages: 48. Mutable Shrew (Sorex mutabilis); 49. Verapaz Shrew (Sorex veraepacis); 50. Rock Shrew (Sorex Mexican Long-tailed Shrew (Sorex oreopolus); 55. Orizaba Long-tailed Shrew (Sorex orizabae); 56. Chestnut-bellied Shrew (Sorex rohweri): 60. South-eastern Shrew (Sorex longirostris); 61. Masked Shrew (Sorex cinereus); 62. Maryland Shrew Mountain Shrew (Sorex milleri): 66. Preble's Shrew (Sorex preblei); 67. Prairie Shrew (Sorex hayden); 68. Pribilof Island Saint Lawrence Island Shrew (Sorex jackson); 72. Kamchatka Shrew (Sorex camtschaticus); 73. Paramushir Shrew (Sorex (Sorex ornatus); 77. American Water Shrew (Sorex palustris); 78. Western Water Shrew (Sorex navigaton; 79. Glacier Bay Baird's Shrew (Sorex bairdi); 83. Pacific Shrew (Sorex pacificus); 84. Fog Shrew (Sorex sonomae); 85. New Mexico Shrew dispan; 51. Smoky Shrew (Sorex fumeus); 52. Inyo Shrew (Sorex tenellus); 53. Dwarf Shrew (Sorex nanus); 54. (Sorex ventralis); 57. Veracruz Shrew (Sorex veraecrucis); 58. Ixtlan Shrew (Sorex ixtlanensis); 59. Olympic Shrew (Sorex fontinalis); 63. Mount Lyell Shrew (Sorex lyell); 64. Zacatecas Shrew (Sorex emarginatus), 65. Carmen Shrew (Sorex pribilofensis); 69. Barren Ground Shrew (Sorex ugyunak); 70. Portenko's Shrew (Sorex portenkol); 71. leucogasten; 74. American Pygmy Shrew (Sorex hoyi); 75. Vagrant Shrew (Sorex vagrans); 76. Ornate Shrew Water Shrew (Sorex alaskanus); 80. Eastern Water Shrew (Sorex albibarbis); 81. Marsh Shrew (Sorex bendiril); 82. (Sorex neomexicanus); 86. Montane Shrew (Sorex monticolus).
Trans-CAUNet: A Swin Transformer-Based Network for Automated Extracting Mountain Glaciers with Multisource Remote Sensing Imagery
<p>Trans-CAUNet: A Swin Transformer-Based <a>Network</a> for Automated Extracting Mountain Glaciers with Multisource Remote Sensing Imagery</p> <p>Original remote sensing images</p> <div> </div>
Data for "A thermal-hydro-mechanical model for evaluating the stability of mountain glaciers"
<p>This dataset details the data produced in our study "A thermal-hydro-mechanical model for evaluating the stability of mountain glaciers".</p>
Data from: Historical retreat of alpine glaciers in the Ahklun Mountains, western Alaska
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Data from: The last 50 years of climate-induced melting of the Maliy Aktru glacier (Altai Mountains, Russia) revealed in a primary ecological succession
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Meteorological records in Laohugou Glacier over the Qilian Mountains, northeastern Tibetan Plateau
<p>Meteorological records in Laohugou Glacier over the Qilian Mountains, northeastern Tibetan Plateau</p>
Predicting hydrologic responses to climate changes in highly glacierized and mountainous region Upper Indus Basin
<p><span>The Upper Indus Basin (UIB) is a major source of supplying water to different areas because of snow and glaciers melt and</span><span> is also enduring the regional impacts of global climate change. The expected changes in temperature, precipitation, and snowmelt </span><span>could be reasons for further escalation of the problem. </span><span>Therefore, estimation of hydrological processes </span><span>is </span><span>critical for UIB. The objectives of this paper were to estimate the impacts of climate change on water resources and future projection for surface water under different climatic scenarios using Soil and Water Assessment Tool (SWAT). The methodology includes</span><span>:</span><span> (i) development of SWAT model using </span><span>land cover, soil and meteorological data; (ii) calibration of the model using daily flow data from </span><span>1978-1993; (iii) model validation for the time 1994-2003; (iv) bias correction of Regional Climate Model (v) </span><span>utilization of </span><span>bias corrected RCM for future assessment under RCP4.5 and RCP8.5 </span><span>for mid (2041-2070) and late century (2071-2100). The results of the study revealed a strong correlation between simulated and observed flow </span><span>with R<sup>2</sup> and NSE equals 0.85 each for daily flow</span><span>. For validation, R<sup>2</sup> and NSE were found to be 0.84 and 0.80 respectively. Compared to baseline period (1976-2005), the result of RCM showed an increase in temperature ranging from 2.36°C to 3.50°C and 2.92°C to 5.23°C for RCP4.5 and RCP8.5 respectively, till the end of 21<sup>st</sup> century. Likewise, the increase in annual average precipitation is 2.4% to 2.5% and 6.0% to 4.6% (mid to late century) under RCP 4.5 and 8.5 respectively. The model simulation results for RCP4.5 showed increase in flow by 19.24% and 16.78% for mid and late century respectively. For RCP8.5, the increase in flow is 20.13% and 15.86% during mid and late century respectively. The model was more sensitive towards available moisture and snowmelt parameters. Thus, SWAT model </span><span>could </span><span>be used as effective tool for climate change valuation and for sustainable management of water resources in future.</span></p>
Predicting hydrologic responses to climate changes in highly glacierized and mountainous region Upper Indus Basin
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Data from: Simple parameterization of aerodynamic roughness lengths and the turbulent heat fluxes at the top of midlatitude August‐one glacier, Qilian Mountains, China
The fluxes of sensible heat (H) and latent heat (LE), which are generally the important parts of the energy and mass balances over glacier surfaces, are widely quantified by the bulk method. However, due to the difficulty of determining the aerodynamic roughness length z0m in this method, H and LE values may still have large uncertainties with significant inaccuracy. To acquire reliable varying and intrinsic z0m values, new simpler parameterizations for z0m values at different ranges of the friction velocity u*b were fitted in this study. The method was implemented using the related meteorological data and glacial sublimation/condensation measured at the top of the August‐one glacier (4817 m a.s.l.) in the Qilian Mountains from 1 July 2016 to 15 August 2017. The parameterization shows that z0m increased sharply when u*b exceeded 0.43 m/s (the approximate threshold value) and that the effect of snowdrift was slight for the hourly z0m values in the range 0.15 ≤ u*b ≤ 0.43 m/s, which could thus be used to calculate the daily z0m. During the wet period (1 July to 24 September 2016 and 5 May to 15 August 2017), the turbulent fluxes calculated by the bulk method showed that net radiation Rnet was the primary source of surface energy (60.7 w/m2), whereas during the dry period (25 September 2016 to 4 May 2017), the main heat sink was the positive H (28.5 w/m2) rather than the negative Rnet (–10.0 w/m2).
Data from: Simple parameterization of aerodynamic roughness lengths and the turbulent heat fluxes at the top of midlatitude August‐one glacier, Qilian Mountains, China
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Rock glacier velocities, Selwyn Mountains, Yukon and NWT, Canada, Version 1
An average of 6 markers were surveyed on each of 15 rock glaciers, once each in 1983 and 1995 using a level (1983) and a theodolite (1995). Measurement error was on the order of 3 percent, however, the greatest variability in observed velocities is explained by the varying locations of the markers on the rock glaciers. Lichen ages were determined by Dyke (1990a), and rock glacier lengths were obtained from 1:50,000 surficial geology maps used to compile the maps in Dyke (1990c-f). Please see the data documentation for further information.
Controls over particle motion and resting times of coarse bed load transport in a glacier-fed mountain stream
<p>Field data bedload monitorning in the Estero Morales</p>
High Mountain Asia Gridded Glacier Thickness Change from Multi-Sensor DEMs V001
This data set contains gridded thickness changes for approximately 650 Himalayan glaciers between 1975 and 2000, and 1040 Himalayan glaciers between 2000 and 2016. The data were derived from KH-9 HEXAGON and ASTER digital elevation models (DEMs), by fitting robust linear trends to time series of elevation pixels over the glacier surfaces.
High Mountain Asia Glacier Thickness Change Mosaics from Multi-Sensor DEMs V001
This data set contains thickness change mosaics that include approximately 650 Himalayan glaciers between 1975 and 2000, and 1040 Himalayan glaciers between 2000 and 2016. The data were derived from HEXAGON KH-9 and ASTER digital elevation models (DEMs), by fitting robust linear trends to time series of elevation pixels over the glacier surfaces.
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.