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41 results for “Glacial Lakes”
Methane concentrations and oxidation rates in land-terminating glacial runoff: measurements from three glacial rivers and a paraglacial lake in Iceland and a literature review
<div> <p>This dataset contains methane measurements from Icelandic lakes and rivers during the summer of 2018 and 2019. This includes data from net methane oxidation assays with sediment and overlying water from one paraglacial lake and one glacial river, and surface methane concentration data from grab samples in 3 glacial streams and 15 Icelandic lakes (1 of which is paraglacial). The dataset also contains methane concentration data from a synthesis of relevant aquatic ecosystems, used to compare against the original measurements collected. </p> </div> <div> <p>Data and Literature Review Synthesis is supplement to Strock et al. 2024 <em>Oxidation is a potentially significant methane sink in land-terminating glacial runoff</em> published in Nature Scientific Reports. </p> <div> <p>This study was funded by: National Geographic Society Changing Polar Systems grant (CP4-162R-18); In-kind support from the U.S. Geological Survey; Dickinson College Research and Development; Churchill Exploration Fund at Dickinson College </p> </div> </div>
Glacial Lake Dataset for the Third Pole
<p>A complete glacial lake dataset compiled for the whole Third Pole, in which 63,727 glacial lakes (≥900 m<sup>2</sup>) with a combined area of 2,122.01 ± 1.26 km<sup>2</sup> were included. Please see data description document for more information.</p>
Global glacial lake bathymetry data
<p>This dataset collects globally published bathymetric data for glacial lakes, recording attributes such as glacial lake name, location, type, year of survey, corresponding area, volume, maximum water depth, and source.</p>
Database of Himalayan glacial lakes
<p>This dataset contains a shapefile of 2231 Himalayan glacial lakes ranging in size between 875 m<sup>2</sup> to 5.6 km<sup>2</sup>. The lakes were manually digitized using high-resolution imagery in GoogleEarth in 2015. The dataset has been mapped and used by <a href="https://doi.org/10.1088/1748-9326/11/7/074005">Schwanghart et al. (2016)</a>. In addition, the dataset contains a shapefile of the great circle that describes the Himalayan Arc (<a href="http://10.1130/dx.doi.org/0091-7613(2001)029<0791:HPITHA>2.0.CO;2">Bendick and Bilham, 2001</a>) as well as a polygon shape which segments the Himalayan arc along the the great circle into 99 polygon.</p> <p><strong>References</strong></p> <p>Bendick, R. and Bilham, R.: How perfect is the Himalayan arc?, Geology, 29, 791–794, <a href="https://doi.org/10.1130/0091-7613(2001)029<0791:HPITHA>2.0.CO;2">https://doi.org/10.1130/0091-7613(2001)029<0791:HPITHA>2.0.CO;2</a>, 2001.</p> <p>Schwanghart, W., Worni, R., Huggel, C., Stoffel, M., and Korup, O.: Uncertainty in the Himalayan energy–water nexus: estimating regional exposure to glacial lake outburst floods, Environ. Res. Lett., 11, 074005, <a href="https://doi.org/10.1088/1748-9326/11/7/074005">https://doi.org/10.1088/1748-9326/11/7/074005</a>, 2016.</p>
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>
Inventory of glacial lakes in Svalbard 1936-2020
<p>Table consist a information about changes of the glacial lakes in the Svalbard Archipelago since the termination of the Little Ice Age. Shapefiles are additional part of this table and shows a spatial distribution of included lakes. To search a specific lake you have to choose ID.</p> <p>This study is a contribution to the National Science Centre project ‘GLAVE’ (Award No. UMO-2020/38/E/ST10/00042)</p>
Glacial Lake Image Dataset for "Efficient glacial lake mapping by leveraging deep transfer learning and a new annotated glacial lake dataset"
<p>Glacial lake dataset for the paper <strong>"Efficient glacial lake mapping by leveraging deep transfer learning and a new annotated glacial lake dataset" (<a title="Persistent link using digital object identifier" href="https://doi.org/10.1016/j.jhydrol.2025.133072" target="_blank" rel="noreferrer noopener">https://doi.org/10.1016/j.jhydrol.2025.133072</a>)</strong></p> <p>The GLID dataset contains a total of 18,367 samples, and the size of each sample is 512*512. Each sample consists of an image and a corresponding label. Four glacial lake types including supraglacial lake, proglacial lake, ice-marginal lake, and unconnected glacial lake are involved. The pixel value of the glacier lake in annotation map is labeled 255 and background is labeled 0.</p> <p>GLID.rar contains the training dataset (16,000 samples), and val.zip contains the validation dataset (2,367 samples).</p> <p>GLID_annotation.zip contains the annotated shapefile of GLID with a CRS of WGS 84.</p> <p>Optical_images_source.xlsx contains the optical images ID/names and acquisition time of each platform (e.g., WV2, LC08, S2B, and GF02) used in GLID.</p> <p>Transferability validation.zip contains the images, labels, and predictions for transferability validation, which is independent of GLID (not used for model training or validation). The file structure is shown below:</p> <p>Transferability validation.zip</p> <ul> <li>images <ul> <li>AS.tif</li> <li>GL.tif</li> <li>NA.tif</li> <li>SA.tif</li> </ul> </li> <li>labels <ul> <li>AS_gt.tif</li> <li>GL_gt.tif</li> <li>NA_gt.tif</li> <li>SA_gt.tif</li> </ul> </li> <li>predictions <ul> <li>AS_pred.tif</li> <li>GL_pred.tif</li> <li>NA_pred.tif</li> <li>SA_pred.tif</li> </ul> </li> </ul> <p>AS, GL, NA, and SA represent Asia, Greenland, North America, and South America, respectively. Four high-quality Landsat-8/9 images (each cloud cover less than 6%) were used for testing, and we manually annotated the glacial lakes in each image as labels. The pixel value of the glacier lake in annotation map is labeled 255 and background is labeled 0. Files in transferability validation.zip have a same CRS of WGS 84.</p> <p>If you find this dataset is helpful in your research, please consider <strong><em>cite </em></strong>this paper:</p> <blockquote> <p><em>Ma D, Li J, Jiang L. 2025. Efficient glacial lake mapping by leveraging deep transfer learning and a new annotated glacial lake dataset. Journal of Hydrology 657: 133072.</em></p> </blockquote>
Mapping of glacial lakes using Sentinel-1 and Sentinel-2 data and a random forest classifier: Strengths and challenges
<p>The water body detection and mapping algorithm named 'glakemap' that I designed was aimed at specifically mapping glacial lakes across alpine regions where their detection and mapping are challenged by many factors such as shadows, cloud cover, turbidity, and ice surface. The algorithm uses Copernicus Sentinel-1 and -2 satellites data and machine learning model (random forest) in an integrated manner to automatically classify glacial lakes from other surface features. In specific, the algorithm takes Sentinel-1 and -2 satellites data as the main inputs. It calculates radar backscatter and Normalised Difference Water Indices (NDWIs) using these datasets, respectively. The radar backscatter and NDWIs products (images) are segmented using a set of rules producing many polygons including lake polygons. Lake polygons are then automatically separated/retained using the random forest model which is trained using features relevant to lakes.</p> <p>The dataset is also available at https://www.mountcryo.org/</p>
Data from: Drivers of contemporary lacustrine fish species richness in the glacial Lake Agassiz basin
<p><strong>Aim</strong>: Biological communities are the result of a stepwise spatiotemporal filtering process, driven by large-scale historical and local contemporary determinants. The biogeographical pattern and species richness of North American fishes are predominantly determined by historical processes of past glaciations and postglacial dispersal and by contemporary environmental and ecological processes. Here, we evaluate the effects of postglacial dispersal through glacial Lake Agassiz and habitat heterogeneity, as represented by lake surface area, on contemporary freshwater fish species richness patterns of northwestern Ontario lakes.</p> <p><strong>Location</strong>: Northwestern Ontario, Canada</p> <p><strong>Taxon</strong>: Freshwater fishes</p> <p><strong>Methods</strong>: We applied the theory of island biogeography and species-area curves to examine the effects of isolation from the past dispersal corridor of glacial Lake Agassiz and habitat heterogeneity on species richness across 264 contemporary lakes in northwestern Ontario, Canada. While controlling for correlations among the predictor variables, generalized linear models were constructed between species richness, as the response variable and the explanatory variables of lake elevation and surface area and connection to the dispersal corridor of Lake Agassiz.</p> <p><strong>Results</strong>: Differential cover by glacial Lake Agassiz led to variation in fish species richness across contemporary lake basins and species richness is higher in lakes that were covered by Lake Agassiz relative to basins remaining outside of the boundaries of the glacial lake. Lake surface area is the strongest predictor of species richness, while lake elevation is the strongest factor predicting isolation as species richness decreases with increasing altitudes.</p> <p><strong>Main Conclusions</strong>: Habitat heterogeneity and postglacial colonization have led to differences in fish richness within the same geographical region. Fish species richness increases with lake surface area and decreases with elevation, likely driven by greater niche diversity facilitating the assembly of more diverse communities and isostatic rebound and fluctuating levels of Lake Agassiz isolating lakes at high elevations from the dispersal route earlier during the colonization process, respectively. These patterns underscore the importance of incorporating historical and environmental community determinants in biodiversity studies.</p>
Glacial lake inventory over Bhutan Himalaya in 2021
<p>The dataset include shape files of glacial lake inventory 2021 covering Bhutan Himalaya delineated by deep learning from multi-source satellite images with manual refinement</p>
Data from: Origin of the Laurentian Great Lakes fish fauna through upward adaptive radiation cascade prior to the Last Glacial Maximum
Open the record for dataset details and reuse information.
Data from: Drivers of contemporary lacustrine fish species richness in the glacial Lake Agassiz basin
Open the record for dataset details and reuse information.
Historical, abiotic, and biotic drivers influence contemporary lacustrine fish community composition in the glacial Lake Agassiz basin
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Decades of water column temperature, lake level and meteorological data of Lake Lacawac, a pristine glacial lake at Lacawac Biological Field Station in the Pocono mountains, Pennsylvania USA (1992-2019)
Lake Lacawac weather and the lake water column were monitored to observe seasonal and interannual temperature and lake level patterns in response to solar heating, wind-driven water column mixing, precipitation, evaporation, watershed runoff and seepage, and outflow (L. Lacawac has an outflow stream but no inflow stream, and is surrounded on one side by peat bogs). Several studies have shown the lake to have a slow exchange by seepage (slightly more seeping in than out except during dry months). Over the years the raft data have been used to calibrate heat flux, mixing, and evaporation models for the lake, to study zooplankton and phytoplankton distribution and dissolved organic matter flux (photobleaching in the water column, influx from the watershed, and exchange with bottom sediments) and associated UV transparency. The data have also been used to accompany experimental manipulations of lake organisms (algae, zooplankton, fish) in relation to exposure to UV radiation. More recently these lake data have been useful in developing lake indices of climate change.
Tree Rings, Glacial Lakes State Park Site 1, Minnesota
Both increases in temperature and changes in precipitation may limit future tree growth, but rising atmospheric CO2 could offset some of these stressors through increased plant Water Use Efficiency (WUE). The net balance between the negative impacts of climate change and positive effects of CO2 on tree growth will be most important for systems already at plant physiological limits, where increased climate stress could drive mortality and shifts in range distribution. Here, we quantify the effects of climate, stand structure, and rising CO2 on both annual tree-ring growth increment and WUE at a savanna-forest boundary in the Upper Midwest United States. Taking a Bayesian hierarchical modelling approach, we find that plant WUE increased by ~13-25% over the course of the 20th century, but on average, tree-ring growth increments do not significantly increase. Consistent with higher WUE under increased CO2 and recent wetting, we observe a decrease in sensitivity of tree growth to annual precipitation, leading to 25-65% higher growth under dry conditions compared to trees of similar age and size in the past. However, an emerging interaction between summer maximum temperatures and annual precipitation diminishes the water-savings benefit under hot and dry conditions. Both the decrease in precipitation sensitivity, and the interaction between temperature and precipitation are strongest in open canopy microclimates, suggesting that stand structure may modulate response to future changes. Overall, we find that while higher WUE may provide some water savings benefits to growth under normal drought conditions, near-term future temperature increases combined with drought events could drive growth declines of over 50%. These products are used in the manucript, Heilman et al., 2020, Increased water use efficiency leads to decreased precipitation sensitivity of tree growth, but is offset by high temperatures. Submitted for review. The tree rings in this data package and those in ms
Tree Rings, Glacial Lakes State Park Site 2, Minnesota
Both increases in temperature and changes in precipitation may limit future tree growth, but rising atmospheric CO2 could offset some of these stressors through increased plant Water Use Efficiency (WUE). The net balance between the negative impacts of climate change and positive effects of CO2 on tree growth will be most important for systems already at plant physiological limits, where increased climate stress could drive mortality and shifts in range distribution. Here, we quantify the effects of climate, stand structure, and rising CO2 on both annual tree-ring growth increment and WUE at a savanna-forest boundary in the Upper Midwest United States. Taking a Bayesian hierarchical modelling approach, we find that plant WUE increased by ~13-25% over the course of the 20th century, but on average, tree-ring growth increments do not significantly increase. Consistent with higher WUE under increased CO2 and recent wetting, we observe a decrease in sensitivity of tree growth to annual precipitation, leading to 25-65% higher growth under dry conditions compared to trees of similar age and size in the past. However, an emerging interaction between summer maximum temperatures and annual precipitation diminishes the water-savings benefit under hot and dry conditions. Both the decrease in precipitation sensitivity, and the interaction between temperature and precipitation are strongest in open canopy microclimates, suggesting that stand structure may modulate response to future changes. Overall, we find that while higher WUE may provide some water savings benefits to growth under normal drought conditions, near-term future temperature increases combined with drought events could drive growth declines of over 50%. These products are used in the manucript, Heilman et al., 2020, Increased water use efficiency leads to decreased precipitation sensitivity of tree growth, but is offset by high temperatures. Submitted for review. The tree rings in this data package and those in ms
Tree Rings, Glacial Lakes State Park Site 3, Minnesota
Both increases in temperature and changes in precipitation may limit future tree growth, but rising atmospheric CO2 could offset some of these stressors through increased plant Water Use Efficiency (WUE). The net balance between the negative impacts of climate change and positive effects of CO2 on tree growth will be most important for systems already at plant physiological limits, where increased climate stress could drive mortality and shifts in range distribution. Here, we quantify the effects of climate, stand structure, and rising CO2 on both annual tree-ring growth increment and WUE at a savanna-forest boundary in the Upper Midwest United States. Taking a Bayesian hierarchical modelling approach, we find that plant WUE increased by ~13-25% over the course of the 20th century, but on average, tree-ring growth increments do not significantly increase. Consistent with higher WUE under increased CO2 and recent wetting, we observe a decrease in sensitivity of tree growth to annual precipitation, leading to 25-65% higher growth under dry conditions compared to trees of similar age and size in the past. However, an emerging interaction between summer maximum temperatures and annual precipitation diminishes the water-savings benefit under hot and dry conditions. Both the decrease in precipitation sensitivity, and the interaction between temperature and precipitation are strongest in open canopy microclimates, suggesting that stand structure may modulate response to future changes. Overall, we find that while higher WUE may provide some water savings benefits to growth under normal drought conditions, near-term future temperature increases combined with drought events could drive growth declines of over 50%. These products are used in the manucript, Heilman et al., 2020, Increased water use efficiency leads to decreased precipitation sensitivity of tree growth, but is offset by high temperatures. Submitted for review. The tree rings in this data package and those in ms
Data from: Evolution and diversity of two cisco forms in an outlet of glacial Lake Algonquin
The diversity of Laurentian Great Lakes ciscoes (Coregonus artedi, sensu lato) arose via repeated local adaptive divergence including deepwater ciscoes that are now extirpated or threatened. The nigripinnis form, or Blackfin Cisco, is extirpated from the Great Lakes and remains only in Lake Nipigon. Putative nigripinnis populations were recently discovered in sympatry with artedi in a historical drainage system of glacial Lake Algonquin, the precursor of Lakes Michigan and Huron. Given the apparent convergence on Great Lakes form, we labelled this form blackfin. Here, we test the hypothesis that nigripinnis may have colonized this area from the Great Lakes as a distinct lineage. It would then represent a relict occurrence of the historical diversity of Great Lakes ciscoes. Alternatively, blackfin could have evolved in situ in several lakes. We captured more than 600 individuals in the benthic or pelagic habitat in 14 lakes in or near Algonquin Provincial Park (Ontario, Canada). Fish were compared based on habitat, morphology and genetic variation at 6676 SNPs. Contrary to our expectations, both cisco and blackfin belonged to an Atlantic lineage that colonized the area from the east, not from the Great Lakes. Sympatric cisco and blackfin were closely related while fish from different lakes were genetically differentiated, strongly suggesting the repeated in situ origin of each form. Across lakes, there was a continuum of ecological, morphological and genetic differentiation that could be associated with alternative resources and lake characteristics. This study uncovers a new component of cisco diversity in inland lakes of Canada that evolved independently from ciscoes of the Laurentian Great lakes. The diversity of cisco revealed in this study and across their Canadian range presents a challenge for designating conservation units at the intraspecific level within the framework of the Committee on the Status of Endangered Wildlife in Canada (COSEWIC).
Population collapse in viviparid gastropods of the Lake Victoria ecoregion started before the Last Glacial Maximum
<p>For the purpose of reproducibility, we here provide the datasets and R script supporting the analyses of the paper "Population collapse in viviparid gastropods of the Lake Victoria ecoregion started before the Last Glacial Maximum" by Van Bocxlaer et al. This paper has been accepted for publication in Molecular Ecology on 31 July 2020. In this study, we examine the population structure of the clade of <i>Bellamya</i> gastropods that occupies the Lake Victoria ecoregion with the aim to relate past environmental change with demography and diversification dynamics. The here provided datasets include 1) an alignment of a fragment of the gene cytochrome <i>c</i> oxidase subunit 1 for 60 specimens; 2) genotype data for 321 individuals from 39 localities for 15 microsatellite loci (total dataset); 3) a regrouped genotype dataset (282 specimens from 21 localities for 15 microsatellite loci), which was used for some analyses in our study. Analyses were performed with various programs as reported in our paper. Here we provide input and result files (33 files in total) for these analyses, complemented with an R script that readily allows reproducing the majority of our inquiries.</p>
Annual 30-meter Dataset for Glacial Lakes in High Mountain Asia from 2008 to 2017
<p>We developed a High Mountain Asia (HMA) Glacial Lake Inventory (Hi-MAG) database to characterize the annual coverage of glacial lakes from 2008 to 2017 at 30 m resolution. For the development of the Hi-MAG database, a total of 40,481 satellite images including Landsat 5 TM, Landsat 7 ETM+ and Landsat 8 OLI were used, and a systematic glacial lake detection method that comprised the automated processing using GEE and subsequent manual refinement of these lake mapping results were applied. This is the first glacial lake inventory across the HMA with annual temporal resolution, it can provide details for different types of glacial lakes and evolution patterns. It can be used for studies of the complex interactions between glaciers, climate, and glacial lakes, and GLOFs, potential downstream risks, and water resources.</p>
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
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.