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.
8,171
datasets available to search
ShareScore release 0.9.0
Dataset results
8,171 results for “mountains”
Fungal community structure associated with seedlings that established post-fire and adjacent resprouting shrubs at Finger Mountain and Nome Creek, Alaska
This dataset contains characterizations of fungal community structure associated with seedlings that established after fire and adjacent resprouting shrubs. It also includes variables that describe proximity to the closest resprouting shrub, fire severity, vegetation, and substrate associated with seedlings and adjacent resprouting shrubs harvested at Finger Mountain and Nome Creek in 2009.
ARISA profiles for root-associated fungal communities associated with seedlings that established after fire and adjacent shrubs harvested at Finger Mountain and Nome Creek in 2009
This dataset contains the ARISA profiles of the root-associated fungal communities associated with seedlings that established after the 2004 fires and the closest resprouting shrub.
Fine root dynamics along an elevational gradient in the southern Appalachian mountains in the Coweeta Hydrologic Laboratory from 1993 to 1994
Annual rates of fine root mass appearance and disappearance were calculated from samples of fine roots taken in soil cores over time on the five gradient plots.
Fine root dynamics along an elevational gradient in the southern Appalachian mountains in the Coweeta Hydrologic Laboratory from 1994 to 1995 (lengths of fine root segments)
The lengths of fine root segments visible in photographs of roots growing against the windows of minirhizotron boxes were measured.
Microclimate data from stations within the Great Smoky Mountains National Park, NC
This dataset contains measurements of air temperature, relative humidity, soil temperature, soil bulk electrical conductivity, and soil volumetric water content from a sites located in the Great Smoky Mountains National Park, NC. Soil temperature, soil bulk electrical conductivity, and soil volumetric water are measured at 0-30cm and 30-60cm below ground surface at locations 25 meters above gradient and 25 meters below gradient of a central transect location where air temperature and relative humidity are measured at 1.5 meters above ground surface. Measurements are taken every 60 seconds with average, minimum, and maximum values saved hourly to the output table.
Late-Holocene paleofloods in the Upper Little Tennessee River valley, Southern Blue Ridge Mountains, USA.
We derive a paleoflood chronology for the past 2000 years from three stratigraphic sections of overbank sediments with dates from radiocarbon, luminescence, 137Cs techniques, and historical records. Particle sizes were measured in 6-15 year intervals in post-1870 sediments and in 45-170 year intervals in pre-1870 sediments using an automatic laser analyzer. The sedimentological characteristics of ad 1948-2009 deposits were compared with gaging records, demonstrating that fine sand content and sorting discern time intervals of large floods, but flood magnitudes are not well resolved. This modern analog was applied to pre-1870 sediments and revealed two periods in the last 2000 years with large floods during AD 650-850 and AD 1100-1350, which are times when the regional tree-ring record showed extreme wetness and no severe or extreme droughts. Our findings indicate flood-prone phases of transitional climate at the beginning and end of the "Medieval Warm Period" (MWP), and relatively subdued flooding during the "Little Ice Age" (LIA), possibly correlated with rearrangement of macro-scale atmospheric circulation patterns between the MWP and the LIA. (Wang, L. and Leigh, D.S. 2012. Late Holocene paleofloods in the Upper Little Tennessee River Valley, Southern Blue Ridge Mountains, USA. The Holocene, 22(9): 1061-1066. DOI: 10.1177/0959683612437863.)
White Mountain National Forest Boundary: GIS Shapefile
This dataset contains the White Mountain National Forest Boundary. The boundary was extracted from the National Forest boundaries coverage for the lower 48 states, including Puerto Rico developed by the USDA Forest Service - Geospatial Service and Technology Center. The coverage was projected from decimal degrees to UTM zone 19. This dataset includes administrative unit boundaries, derived primarily from the GSTC SOC data system, comprised of Cartographic Feature Files (CFFs), using ESRI Spatial Data Engine (SDE) and an Oracle database. The data that was available in SOC was extracted on November 10, 1999. Some of the data that had been entered into SOC was outdated, and some national forest boundaries had never been entered for a variety of reasons. The USDA Forest Service, Geospatial Service and Technology Center has edited this data in places where it was questionable or missing, to match the National Forest Inventoried Roadless Area data submitted for the President's Roadless Area Initiative. Data distributed as shapefile in Coordinate system EPSG:26919 - NAD83 / UTM zone 19N.
Calling activity of Birds in the White Mountain National Forest: Audio Recordings (2016 and 2018)
We collected 410 10-minute sound recordings of birds in and near the Hubbard Brook Experimental Forest in New Hampshire. Recordings, which encompassed most of the bird breeding season in each of two years, included 130,776 vocalizations from 46 taxa. In the associated publication, we report species lists, rarefaction curves, and vocalization descriptions. We also provide analyses of habitat associations, phenology, and spatial patterning in vocalization activity. These data were gathered as part of the Hubbard Brook Ecosystem Study (HBES). The HBES is a collaborative effort at the Hubbard Brook Experimental Forest, which is operated and maintained by the USDA Forest Service, Northern Research Station.
Hubbard Brook Experimental Forest and Adirondack Mountains: In-stream large wood and riparian forest structure, 2002-2019
This dataset presents data on the in-stream large wood in 16 stream reaches in the Hubbard Brook Experimental Forest as well as the riparian forest structure and composition at these streams. It also provides data on the large wood in 13 stream reaches in old-growth forests in the Adirondack Mountains of New York.
Calling activity of Birds in the White Mountain National Forest: Manifest of 99,778 acoustic recordings from bird plots in the Hubbard Brook Forest: 2016 - 2023
During 2016 - 2023, during the bird breeding season, we collected 99,778 files of bioacoustic recordings in and near the Hubbard Brook Experimental Forest in New Hampshire. Here, we provide a manifest of the sound files. Most files are one-hour recordings collected at 32 kHz and saved in FLAC format (~ 25 MB per file, ~ 13 TB total). Typical recording configuration was 05:00 - 08:00 and 17:30 - 20:30 local time. The full sound files have been saved in three respositories: two copies at Dartmouth College (Ayres lab) and one copy at the Macauley Library, Cornell Laboratory of Ornithology. The full sound files are available upon request. The file attributes within the manifest include date, start time, and recorder group: e.g., Main, 10ha, Oven, VW, AshBirch, and Ridge. Each recorder group had 5 - 20 recorders at plots separated by >100 m. Coordinates of each recorder are associated with plot names within metadata. The bird species expected to occur in these recordings are those from Holmes et al. (2021). These data were gathered as part of the Hubbard Brook Ecosystem Study (HBES). The HBES is a collaborative effort at the Hubbard Brook Experimental Forest, which is operated and maintained by the USDA Forest Service, Northern Research Station. Holmes, R., S. Sillett, and M. Hallworth. 2021. Bird species recorded within the Hubbard Brook Experimental Forest and vicinity (1963-2020; updated January 2021). ver 1. Environmental Data Initiative. https://doi.org/10.6073/pasta/da6cbb1ed8142d52a9d72762983742d8 (Accessed 2024-10-24).
Statistically downscaled future precipitation for the Luquillo Mountains, Puerto Rico
This dataset contains climate predictions that serve as the basis for the analysis in Ramseyer et al. (2019), which projected a trend toward drier conditions in eastern Puerto Rico during the mid- and late-21st century. The analysis was informed by computing nine atmospheric variables, which had been shown by previous research to related to precipitation in Puerto Rico (Ramseyer and Mote 2016) from four GCMs. These nine variables were used to train an artificial neural network (ANN) to predict the binary occurrence of a wet (>= 5 mm of precipitation) versus dry (<5 mm) day using in-situ daily precipitation observations from El Verde Field Station in northeast Puerto Rico. The nine atmospheric variables used to train the ANN were: 1000- 850-, 700-, and 500-hPa daily specific humidity, 1000–700-hPa bulk wind shear (BWS), the Gálvez-Davison Index (GDI), and the GDI's three component terms (the column buoyancy index, mid-level warming index, and a trade-wind inversion index). These same nine variables were then extracted on a daily basis from four GCMs for the eastern Caribbean early rainfall season (April-July) between 2041-2060 and 2081-2100, and fed through the ANN. These data are the daily predicted values of wet (1) or dry (0) conditions for each of the four GCMs in the ensemble. Because ERS total precipitation at El Verde is strongly correlated with the percentage of ERS dry days (R2=0.95 for years with <10% missing data), the GCM predictions were used to estimate future ERS precipitation using the following formula: ERS precipitation (mm) = 3373-37.6*(ERS dry-day percentage) Applying this formula to each of the GCM dry-day projections yielded an ensemble mean ERS precipitation total of 771 mm by 2041-2060 and 974 mm by 2081-2100. See Ramseyer et al. (2019) for a complete description of the neural network and its predictions. Ramseyer, C., P. Miller, and T. Mote, 2019: Future precipitation variability during the early rainfall season in the El Yunque National Fore
Holocene insect fossil data for Indian Peaks Wilderness and Rocky Mountain National Park, 1985 and 1993.
Insect fossil assemblages were analyzed from the Indian Peaks Wilderness and Rocky Mountain National Park. Assemblages span the last 10,000 years revealing climate change and the response of both insects and vegetation in the montane to upper subalpine zones. The Longs Peak Inn Bog site (LPIB) yielded insect assemblages ranging in age from recent to 3500 yr BP. This insect fossil record suggests climatic cooling at about 1800 yr BP and between 250 and 300 yr BP (AD 1700-1850). The bog may experience colder microclimates than the surrounding forests, yielding insect assemblages reflective of the colder, local microclimate. Also, alpine and upper subalpine insects may have been washed into the catchment basin of the bog from nearby slopes. Assemblages from four additional Front Range sites suggested a climatic optimum between 9000 and 7000 BP. Faunal evidence indicates a tree-limit decline at 4500 BP. Declining forest-tundra insect ratios, combined with the conifer macrofossil record, suggest a climatic deterioration from 4500 to 3100 BP followed by a rapid amelioration, from 3000 to 2000 BP. A gradual decline in the forest-tundra ratios occurred after 2000 BP, reaching 1:1 ratios at or before 1000 BP.
Terrestrial Laser Scanner observations of snow depth distribution at Col du Lautaret and Col du Lac Blanc mountain sites
<p>This dataset contains snow depth distribution observations obtained in two high mountain experimental sites, Col du Lac Blanc and Col du Lautaret, both located in French Alps. The snow depth distribution maps were generated using a Terrestrial Laser Scanner (TLS) for 10 acquisition dates. Observations obtained in Col du Lac Blanc were acquired in the 2014-15 snow season while Col du Lautaret observations were acquired in 2017-18 snow season. The snow depth maps have a grid cell size of 1x1m. The two study sites have extensions comprised between 17 and 31 ha with elevations ranging from 2000-2100 m a.s.l. (Col du Lautaret)and 2600-2800 m a.s.l. (Col du Lac Blanc)and show a patchy distribution of bare soil and alpine grass. The dataset allows a better understanding of snow related processes in mountain areas.</p>
Fig. 2 in The Psilotreta Banks, 1899 of the Dabie Mountains, east central China, with descriptions of two new species (Insecta: Trichoptera: Odontoceridae)
Fig. 2. Psilotreta furcata sp.nov. A. Head, anterior view. B. Head, dorsal view. C. Maxillary palp. D. Wing veins. E. Male genitalia, left lateral view. F. Male genitalia, dorsal view. G. Male genitalia, ventral view. H. Phallus, left lateral view. I. Segment X, left lateral view. J. Parameres, posterior view. K. Aedeagus, dorsal view. Scale bars: A–C = 200 µm; D = 1 mm; E–K = 250 µm.
Fig. 1. Psilotreta daidalos Malicky 2000. A. Head, anterior view. B. Head, dorsal view. C. Maxillary palp. D. Wing veins. E. Male genitalia, left lateral view. F. Male genitalia, dorsal view. G. Male genitalia, ventral view. H. Phallus, left lateral view. I. Segment X, left lateral view. J. Parameres, ventral view. K in The Psilotreta Banks, 1899 of the Dabie Mountains, east central China, with descriptions of two new species (Insecta: Trichoptera: Odontoceridae)
Fig. 1. Psilotreta daidalos Malicky 2000. A. Head, anterior view. B. Head, dorsal view. C. Maxillary palp. D. Wing veins. E. Male genitalia, left lateral view. F. Male genitalia, dorsal view. G. Male genitalia, ventral view. H. Phallus, left lateral view. I. Segment X, left lateral view. J. Parameres, ventral view. K. Aedeagus, ventral view. Scale bars: A–C = 200 µm; D = 1 mm; E–K = 250 µm.
Fig. 16 in Five new species of Meta Koch, 1836 (Araneae: Tetragnathidae) from Gaoligong Mountains, China
Fig. 16. Distribution records of five new species of the genus Meta Koch, 1836 in Gaoligong Mountains, Yunnan, China.
Fig. 14 in Five new species of Meta Koch, 1836 (Araneae: Tetragnathidae) from Gaoligong Mountains, China
Fig. 14. Meta yinae sp. nov. Paratype ♀ (HNU-Tang-05-08). A. Epigyne, ventral view. B. Vulva, front view. Scale bars: 0.2 mm.
Fig. 8 in Five new species of Meta Koch, 1836 (Araneae: Tetragnathidae) from Gaoligong Mountains, China
Fig. 8. Meta tangi sp. nov. Paratype ♀ (HNU-20071010). A. Epigyne, ventral view. B. Vulva, front view. Scale bars: 0,2 mm.
Fig. 9 in Five new species of Meta Koch, 1836 (Araneae: Tetragnathidae) from Gaoligong Mountains, China
Fig. 9. Meta tangi sp. nov. Left palp of holotype ♂ (A–C); epigyne (D) and vulva (E) of paratype ♀ (HNU-20071010). A. Prolateral view. B. Ventral view. C. Retrolateral view. D. Epigyne, ventral view E. Vulva, front view. Scale bars: 0.2 mm.
Fig. 5 in Five new species of Meta Koch, 1836 (Araneae: Tetragnathidae) from Gaoligong Mountains, China
Fig. 5. Meta longlingensis sp. nov. Left palp of holotype ♂ (HNU-Tang031029). A. Prolateral view. B. Retrolateral view. C. Dorsal view. D. Ventral view. Scale bars: 0.2 mm.
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.