Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
11
datasets available to search
ShareScore release 0.9.0
Dataset results
11 results for “retrogressive thaw slump”
Data from: Microsite conditions in retrogressive thaw slumps may facilitate increased seedling recruitment in the Alaskan Low Arctic
In Low Arctic tundra, thermal erosion of ice-rich permafrost soils (thermokarst) has increased in frequency since the 1980s. Retrogressive thaw slumps (RTS) are thermokarst disturbances forming large open depressions on hillslopes through soil wasting and vegetation displacement. Tall (> 0.5 m) deciduous shrubs have been observed in RTS a decade after disturbance. RTS may provide conditions suitable for seedling recruitment, which may contribute to arctic shrub expansion. We quantified in situ seedling abundance, and size and viability of soil seedbanks in greenhouse trials for two RTS chronosequences near lakes on Alaska's North Slope. We hypothesized recent RTS provide microsites for greater recruitment than mature RTS or undisturbed tundra. We also hypothesized soil seedbanks demonstrate quantity-quality trade-offs: younger seedbanks contain smaller numbers of mostly viable seed that decrease in viability as seed accumulates over time. We found five times as many seedlings in younger RTS as in older RTS, including birch and willow, and no seedlings in undisturbed tundra. Higher seedling counts were associated with bare soil, warmer soils, higher soil available nitrogen, and less plant cover. Seedbank viability was unrelated to size. Older seedbanks were larger at one chronosequence, with no difference in percent germination. At the other chronosequence, germination was lower from older seedbanks but seedbank size was not different. Seedbank germination was positively associated with in situ seedling abundance at one RTS chronosequence, suggesting post-disturbance revegetation from seedbanks. Thermal erosion may be important for recruitment in tundra by providing bare microsites that are warmer, more nutrient rich, and less vegetated than in undisturbed conditions. Differences between two chronosequences in seedbank size, viability, and species composition suggest disturbance interacts with local conditions to form seedbanks. RTS may act as seedling nurseries to benefit many arctic species as climate changes, particularly those that do not produce persistent seed.
Lakeshore retrogressive thaw slumps (thermocirques) in West Siberian Arctic
<p>The dataset represents georeferenced polygons of mapped retrogressive thaw slumps (thermocirques) in the West Siberian Arctic.</p><p>The columns in the attribute table represent the area, edge elevation values, and slope angle.</p><p>The methodology of the data collection is described in Leibman et al., 2023.</p>
An Updated Inventory of Retrogressive Thaw Slumps Along the Vulnerable Qinghai-Tibet Engineering Corridor
<p>An inventory of 875 retrogressive thaw slumps over a landscape of 54000 km<sup>2</sup>, along the Qinghai-Tibet Engineering Corridor underlain by permafrost, was compiled using remote sensing and DeepLabv3+, a kind of deep learning model. The file in the format of Geopackage/GPKG contains the boundary of each retrogressive thaw slump as vectors in the Coordinate Reference System of EPSG:32646 - WGS 84. The associated attribute table includes probability, time of the satellite images, source of the satellite images, the near roads labels, year of initiation, longitude and latitude, area (units: m<sup>2</sup>), Deep Learning model. The corresponding names for the table fields are ‘Probability’, ‘Year-month’, ‘Source Image’, ‘Near roads’, ‘Initial year’, ‘Longitude’, ‘Latitude’, ‘Area’, ‘Deep Learning model’. The ‘Probability’, having values of ‘High’, ‘Medium’ and ‘Low’, measures how much we are sure about the mapped RTSs.</p>
Data from: Microsite conditions in retrogressive thaw slumps may facilitate increased seedling recruitment in the Alaskan Low Arctic
Open the record for dataset details and reuse information.
Annual inventories of retrogressive thaw slumps across the Qinghai-Tibet Plateau from 2016 to 2022
<p>The dataset is retrogressive thaw slump inventories with annual intervals across the plateau from 2016 to 2022. It contains the boundaries of thaw slumps delineated yearly based on the PlanetScope Scenes with high resolution (3-5 m). The inventories were compiled semi-automatically by combining deep-learning detection and manual delineation. We assigned a unique ID to every RTS in 2022 and the corresponding polygons in previous years. For RTSs merged into one in 2022, we assigned the same ID to make them traceable. We also clustered the RTSs based on the locations. It is the first of this kind to provide annual large-scale thaw slump observations across the QTP and can potentially be a benchmark for monitoring permafrost and evaluating its impact. The vector file in shapefile format contains the boundary of each hot melt collapse. The name of the file is “QTP_RTS_YYYY”, with the ‘YYYY’ representing the year of the boundaries. Relevant attribute tables include unique numbers, area (units: m<sup>2</sup>), longitude and latitude, and clusters that RTSs are in, with the corresponding names of the table fields 'id', 'Area', 'Longitude', 'Latitude' and 'Cluster'.</p>
Retrogressive thaw slump (RTS) inventory in central Qinghai-Tibet Plateau (northwest of Beiluhe basin)
<p>A new retrogressive thaw slump (RTS) inventory in central Qinghai–Tibet Plateau (QTP) were generated based on visual interpretation of nine satellite images (WV-2, Google Earth image, Ziyuan-3, Gaofen-2, Gaofen-1) and field investigations. A total 459 RTSs were confirmed with an accumulative area of 1199.49 ha (in time slice of 2018-2020). To reduce the uncertainty in identifying the RTS boundaries, all of the images were spatially corrected based on a reference image, which was obtained on 29 December 2015. The RTS inventory published by Luo et al., (2022) and Xia et al., (2022) were refered when we conduct visual interpretation. Note: the RTSs were distingusihed into active RTSs (TYPE=Y) and non-active RTSs (TYPE=N). Those RTSs were neither active nor non-active RTSs when their area increase vary from 0 to 0.01 ha or less than 0 (TYPE=T). The field named "area_ha", "perime_km" are the area and perimeter of the RTSs in the attribute tables of shapefiles. The units of area and perimeters are hectare (ha) and kilometer (km), respectively. The field named "type" indicates the status of RTSs. The "Y" and "N" are means the RTS is belongs to active RTS and non-active, respectively.</p>
Microsite conditions in retrogressive thaw slumps may facilitate increased seedling recruitment in the Alaskan Low Arctic
Open the record for dataset details and reuse information.
The retrogressive thaw slump (RTS) inventory in permafrost region of the QTP
<p>This dataset contain the retrogressive thaw slump (RTS) inventory in permafrost region of the Qinghai–Tibet Plateau (QTP) based on field investigations and the manual interpretation of the Gaofen-1 and Gaofen-2 images. RTSs were visually detected based on the presence of recently exposed sediments, poorly developed vegetation, and distinct headwalls. To avoid misdelineation of the RTS, the entire permafrost region of the QTP was divided into a large number of grids measuring 5 × 5 km each. Grids with slope degrees below 1° or higher than 15° were excluded because RTSs are rarely found at these slopes according to our previous study and field investigations. RTSs in the remaining grids were detected and sketched by the first author and then examined by at least two other experienced authors. Once a RTS was identified, it was assigned a unique number and classified based on its initiation such as next to a river (R), by lake erosion (L), and after the occurrence of active-layer detachment slide.</p>
Data of publication Carbon Dioxide Release from Retrogressive Thaw Slumps in Siberia
<p>This is the publication of data for the publication Beer et al., Carbon Dioxide Release from Retrogressive Thaw Slumps in Siberia, submitted to the Journal Environmental Research Letters in 2023.</p> <p>There are three variables included in the file results_thawslump_extrapolation_23092022.xlsx file: area of all thaw slumps, 0-100 cm carbon stocks of all thaw slumps, and annual CO2 release from all thaw slumps. In the mat-file there is even more information on soil temperature and CO2 production and emissions for a complete uncertainty assessment.</p>
Spatial predictions of retrogressive thaw slump susceptibility in the Northern Hemisphere permafrost region
<p>Here, we provide a raster file of the RTS susceptibility map in the Northern Hemisphere. The map is a result of a scientific study by Makopoulou et al. (2024, in review). File is provided in TIFF-format. </p>
Retrogressive thaw slumps on the Tibetan Plateau from 1986 to 2020
<p>The degradation of permafrost on the Tibetan Plateau (TP) exacerbates the expansion of retrogressive thaw slumps (RTSs), posing a threat to the stability of infrastructure. Based on time-series Landsat images, we used a combination of machine learning automatic classification and manual delineation to identify 3537 RTSs in the permafrost region of TP from 1986 to 2020, the data also provided detailed information on RTSs area and annual disturbance time.</p>
ScienceDex guides
Understand access before you commit
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.