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.
1,723
datasets available to search
ShareScore release 0.7.1
Dataset results
1,723 results for “alpine”
Sub-Alpine Lake (>600 m) High-Frequency Water Temperature, DOC (2007-2021), and Weather Station (Fall 2023) Dataset, Maine, USA.
We collected high-frequency surface and bottom water temperature in a set of nine high-elevation lakes in Maine, USA from 2007-2021. High-elevation is defined >600m above sea level. Dissolved organic carbon concentration data for the same time period and set of lakes is modified from Nelson, S.J., R.A. Hovel, J.F. Daly, A.L. Gavin, S. Dykema, and W.H. McDowell. 2021. Northeastern Mountain Ponds Geochemistry Compilation 1978-2019 ver 1. Environmental Data Initiative. https://doi.org/10.6073/pasta/8b51d651da0e0cff8c6ad853ef69ec3b. Air temperature and precipitation data were collected from a weather station deployed in the Mountain Pond watershed in Fall 2023 to aid comparison with low and high resolution PRISM datasets.
Academics for Land Protection in New England (ALPINE) GIS Data 2015-2018
Academics for Land Protection in New England (ALPINE) is a network of academic institutions committed to increasing the pace of land protection in New England to address the region’s environmental challenges and to support nature and people. ALPINE seeks to expand the role that academic institutions play in conserving the New England landscape by sharing experiences and resources among faculty and staff, students, administrations, and alumni. This dataset contains point locations of colleges that are participants in ALPINE and parcels of natural land owned by participating schools who submitted data to the ALPINE coordinator.
Snow depth sensor measurement data for Upper Sub Alpine site, 2010 - 2015.
Effects of infrared heaters on snow accumulation, snowmelt, and snow–atmosphere energy exchange were examined at Niwot Ridge, Colorado (CO). These .zip data files contains hourly snow depth measurements collected using Judd snow depth sensors for water year 2010-2015 (1 October 2009 – 30 September 2015) at the Upper Sub Alpine site, located just southeast of the Tundra Lab, below treeline in the Niwot Ridge Long-Term Ecological Research (NWTLTER) project area. The file contains both level 0 and level 1 (see details in “Process Description” below) hourly snow depth data measured in centimeters, and an accompanying metadata file.
CO2 NEE and ER + air and soil meteorological and climate parameters in Alpine grasslands, Gran Paradiso National Park, 2017-2019
<p>The dataset “fluxes_meteoclimate_nivolet_V0” is a .csv file reporting CO<sub>2</sub> Net Ecosystem Exchange (NEE) and Ecosystem Respiration (ER) measured at Nivolet Plain, Gran Paradiso National Park, Italy, in a high-altitude Alpine grassland environment (about 2700 m.a.s.l.) using the flux chamber method, during the 2017, 2018 and 2019 vegetative seasons (July-September), approximately twice a month. NEE is measured with a transparent flux chamber, while ER with a shaded chamber. Data represent the average values and the corresponding standard deviations obtained from four sites at different altitudes and geological substrate of the soil. Each average value is obtained as a mean over a set of more than 20 point-measures for each site and each sampling date. Flux data are complemented by measurements of soil temperature and volumetric water content, air temperature and moisture, and solar radiance. The four sites are characterized by soils developed over carbonates (carb) (45.500212N-7.152213E), glacial deposits (glac) (45.490167N-7.139916E), gneiss rocks (gnei) (45.490256N-7.149253E) and alluvial deposits (allu) (45.492656 N-7.146092 E).</p> <p>Other relevant shortcuts used in the .csv table: Std = Standard deviation; VWC% = Volumetric Water Content %. Meteorological and climate variables recorded during the measurement of NEE and during the measurement of ER bring the suffix NEE and ER respectively (es. Pressure_NEE (hPa) = atmospheric pressure recorded during the measurement of Net Ecosystem Exchange).</p>
A long term hourly eddy covariance dataset of consistently processed CO2 and H2O Fluxes from the Tibetan Alpine Steppe at Nam Co (2005 - 2019)
<p>The data set contains nearly 15 years of eddy covariance data from an alpine steppe ecosystem on the central Tibetan Plateau. The data was processed following standardized quality control methods to allow for comparability between the different years of our record and with other data sets. To ensure meaningful estimates of ecosystem atmosphere exchange, careful application of the following correction procedures and analyses was necessary: (1) Due to the remote location, continuous maintenance of the eddy covariance (EC) system was not always possible, so that cleaning and calibration of the sensors was performed irregularly. Furthermore, the high proportion of bare soil and high wind speeds led to accumulation of dirt in the measurement path of the infrared gas analyzer (IRGA). The installation of the sensor in such a challenging environment resulted in a considerable drift in CO2 and H2O gas density measurements. If not accounted for, this concentration bias may distort the estimation of the carbon uptake. We applied a modified drift correction procedure following Fratini et al. (2014) which, instead of a linear interpolation between calibration dates, uses the CO2 concentration measurements from the Mt. Waliguan atmospheric observatory as reference time series. (2) We applied rigorous quality filtering of the calculated fluxes to retain only fluxes which represent actual physical processes. (3) During the long measurement period, there were several buildings constructed in the near vicinity of the EC system. We investigated the influence of these obstacles on the turbulent flow regime to identify fluxes with uncertain land cover contribution and exclude them from subsequent computations. (4) We calculated the de-facto standard correction for instrument surface heating during cold conditions (hereafter called sensor self heating correction) following Burba et al. (2008) and a revision of the original method following Frank and Massman (2020). (5) Subsequently, we applied the traditional and widely used gap filling procedure following Reichstein et al. (2005) to provide a more complete overview of the annual net ecosystem CO2 exchange. (6) We estimated the flux uncertainty by calculating the random flux error (RE) following Finkelstein and Sims (2001) and by using the standard deviation of the fluxes used for gap filling (NEE_fsd) as a measure for spatial and temporal variation.</p> <p>References:</p> <ol> <li>Burba, G. G., McDermitt, D. K., Grelle, A., Anderson, D., and XU, L. (2008). Addressing the influence of instrument surface heat exchange on the measurements of CO2 flux from open-path gas analyzers, Global Change Biology, 14, 1854-1876, <a href="https://doi.org/10.1111/j.1365-2486.2008.01606.x">https://doi.org/10.1111/j.1365-2486.2008.01606.x</a>.</li> <li>Finkelstein, P. L. and Sims, P. F. (2001). Sampling error in eddy correlation flux measurements, J. Geophys. Res. Atmos., 106, 3503–3509, doi:10.1029/2000JD900731.</li> <li>Frank, J. M. and Massman, W. J.: A new perspective on the open-path infrared gas analyzer self-heating correction, Agricultural and Forest Meteorology, 290, 107986, doi:10.1016/j.agrformet.2020.107986, 2020.</li> <li>Fratini, G., McDermitt, D. K., and Papale, D. (2004). Eddy-covariance flux errors due to biases in gas concentration measurements: origins, quantification and correction, Biogeosciences, 11, 1037-1051, <a href="https://doi.org/10.5194/bg-11-1037-2014">https://doi.org/10.5194/bg-11-1037-2014</a>.</li> <li>Reichstein, M., Falge, E., Baldocchi, D., Papale, D., Aubinet, M., Berbigier, P., Bernhofer, C., Buchmann, N., Gilmanov, T., Granier, A., Grunwald, T., Havrankova, K., Ilvesniemi, H., Janous, D., Knohl, A., Laurila, T., Lohila, A., Loustau, D., Matteucci, G., Meyers, T., Miglietta, F., Ourcival, J.-m., Pumpanen, J., Rambal, S., Rotenberg, E., Sanz, M., Tenhunen, J., Seufert, G., Vaccari, F., Vesala, T., Yakir, D., and valentini, R. (20050. On the separation of net ecosystem exchange into assimilation and ecosystem respiration: review and improved algorithm, Global Change Biology, 11, 1424-1439, <a href="https://doi.org/10.1111/j.1365-2486.2005.001002.x">https://doi.org/10.1111/j.1365-2486.2005.001002.x</a>.</li> </ol>
Net Ecosystem Exchange, Ecosystem Respiration and meteoclimatic data of Alpine grasslands at Nivolet Plain, Gran Paradiso National Park, Italy 2017-2023
<p>This dataset presents georeferenced measurements collected at the Nivolet Plain in Gran Paradiso National Park (GPNP), western Italian Alps. The dataset includes the Net Ecosystem Exchange (NEE), Ecosystem Respiration (ER) and meteo-climatic variables, i.e. air and soil temperature, air relative humidity, soil volumetric water content, atmospheric pressure and solar irradiance. The measurements were conducted between 2017 and 2023 at five different sites at an elevation of approximately 2550-2750 meters a.s.l.</p> <p>To estimate NEE and ER, we employed the flux chamber method, measuring the temporal variation of carbon dioxide (CO2) concentration inside the chamber over a period of about 90 seconds. We used a customized portable non-steady-state dynamic flux chamber, paired with an InfraRed Gas Analyzer (IRGA) and a portable weather station. Measurements were taken at around 20 points per site during the snow-free season, spanning from June to October.</p> <p>The dataset is provided in a comma-separated text file (.csv) format. Each record corresponds to a single measurement point, with semicolons used as separators. The "NA" notation indicates values that are not available or have been excluded during quality control processes (e.g., due to battery failure). We use point as decimal separator.</p> <p>The sign convention for the fluxes is: a negative value indicates a CO2 flux from the atmosphere to the ecosystem, while a positive value represents a CO2 flux from the soil/ecosystem to the atmosphere. Consequently, ER values are positive, while NEE values can be positive or negative. The units for NEE and ER fluxes are molCO2 m-2 day-1 and μmolCO2 m-2 second-1. The first values in each record of the dataset indicate the observation details (sampling date, site, etc.), followed by the corresponding measured or calculated variables. NEE and ER values were estimated from the slope of the linear regression of CO2 concentration over time (ppm s-1) using a laboratory calibration curve.</p> <p>The calibration curve was created by relating known and pre-set CO2 fluxes (within the range expected in the field) with the corresponding measured slopes. The flux values were then scaled up based on the area of the chamber base (0.036 m2) and adjusted using the ratio of atmospheric pressure and air temperature during the measurement to those recorded during the calibration in the laboratory.</p>
The potential of low-cost UAVs and open-source photogrammetry software for high-resolution monitoring of alpine glaciers: A case study from the Kanderfirn (Swiss Alps)
<p>This dataset contains high-resolution orthophotos (5 x 5 cm) and digital surface models (25 x 25 cm) of the Kandernfirn Glacier located in the Swiss Alps. Aerial images were aquired with a self-developed fixed-wing Unmanned Aerial Vehicle during ten surveys on five different days in 2017 and 2018. The open-source photogrammetry software OpenDroneMap (version 0.4.1) was used for image processing.</p> <p>The orthophotos and digital surface models were validated through dGNSS point measurements of ground control points. Please refer to the corresponding paper for information on the horizontal and vertical accuracy of the files.</p>
Indicative distribution map for Ecosystem Functional Group T6.5 Tropical alpine grasslands and herbfields
<p>This archive contains indicative distribution maps and profiles for <strong>T6.5 Tropical alpine grasslands and herbfields</strong>, a ecosystem functional group (EFG, level 3) of the <a href="https://global-ecosystems.org/">IUCN Global Ecosystem Typology</a> (v2.0). Please refer to Keith <em>et al.</em> (2020) for details.</p> <p>The descriptive profiles provide brief summaries of key ecological traits and processes, maps are indicative of global distribution patterns, and are not intended to represent fine-scale patterns. The maps show areas of the world containing major (value of 1, coloured red) or minor occurrences (value of 2, coloured yellow) of each ecosystem functional group. Minor occurrences are areas where an ecosystem functional group is scattered in patches within matrices of other ecosystem functional groups or where they occur in substantial areas, but only within a segment of a larger region. Given bounds of resolution and accuracy of source data, the maps should be used to query which EFG are likely to occur within areas, rather than which occur at particular point locations. Detailed methods and references for the maps are included in the profile (xml format).</p>
Indicative distribution map for Ecosystem Functional Group T6.4 Temperate alpine grasslands and shrublands
<p>This archive contains indicative distribution maps and profiles for <strong>T6.4 Temperate alpine grasslands and shrublands</strong>, a ecosystem functional group (EFG, level 3) of the <a href="https://global-ecosystems.org/">IUCN Global Ecosystem Typology</a> (v2.0). Please refer to Keith <em>et al.</em> (2020) for details.</p> <p>The descriptive profiles provide brief summaries of key ecological traits and processes, maps are indicative of global distribution patterns, and are not intended to represent fine-scale patterns. The maps show areas of the world containing major (value of 1, coloured red) or minor occurrences (value of 2, coloured yellow) of each ecosystem functional group. Minor occurrences are areas where an ecosystem functional group is scattered in patches within matrices of other ecosystem functional groups or where they occur in substantial areas, but only within a segment of a larger region. Given bounds of resolution and accuracy of source data, the maps should be used to query which EFG are likely to occur within areas, rather than which occur at particular point locations. Detailed methods and references for the maps are included in the profile (xml format).</p>
Water stable isotope, temperature and electrical conductivity dataset (snow, ice, rain, surface water, groundwater) from a high alpine catchment (2019-2021).
<p>Data collected in the Otemma forefield in Switzerland (45°56’03”N,7°24’42”) from July 2019 to October 2021.<br> Data were collected by the research teams of Bettina Schaefli<sup>2</sup> and Stuart N. Lane<sup>1</sup>.</p> <p><sup>1</sup> Institute of Earth Surface Dynamics (IDYST), University of Lausanne, 1015 Lausanne, Switzerland</p> <p><sup>2</sup> Institute of Geography (GIUB), University of Bern, 3012 Bern, Switzerland</p> <p>For further information, please contact:</p> <ul> <li>tom.muller.1@unil.ch</li> </ul> <p><strong>Description of the dataset</strong></p> <p>This dataset contains water stable isotope (δ<sup>2</sup>H, δ<sup>17</sup>O, δ<sup>18</sup>O), water temperature and water electrical conductivity (EC) measurements collected from the Otemma glacier catchment.</p> <p>All water isotope samples were collected directly from the source and stored in 12 mL amber glass vials with an air-tight caps. River samples were first collected with an automatic ISCO 6712 portable water sampler with 1L open plastic bottles and transferred in 12 mL vials every one to two weeks. All isotope analysis were performed using a Wavelength-Scanned Cavity Ring Down Spectrometer (Picarro 2140-I, Santa Clara, California, USA) and expressed relative to the international Vienna Standard Mean Ocean Water (VSMOW) standards.</p> <p>All EC and water temperature measurements were performed with a WTW Multi 3510 IDS logger with a IDS TetraCon® 925 probe.</p> <p>The dataset contains measurements performed at various locations within the catchment. A total of approximately 1500 measurements are provided. In the dataset each point correspond to a measurement station (column "<strong>Station</strong>") which we classified in specific class of water (column "<strong>Type</strong>") as follows :</p> <ul> <li><strong>Stream </strong>: samples collected at three locations, from the glacier snout, after a small outwash plain and 2km downstream.</li> <li><strong>Tributary </strong>: 5 hillslopes tributaries originating from small seasonal overland flow or small springs at the base of the morainic hillslope. Those tributaries were monitored weekly. In addition, a few other seasonal lateral streams were sampled in various locations (Type: Other tributaries).</li> <li><strong>Bedrock </strong>: A few exfiltrations directly leaking out of the bedrock outcrop were sampled.</li> <li><strong>Ice </strong>: Ice was sampled either as surface ice (small cores 5 cm deep), as deeper cores (5 to 8m deep) or as meltwater from supraglacial gullies. All solid ice samples were melted at ambiant air temperature in air-tight plastic bags before being transferred into 12 mL vials.</li> <li><strong>Snow </strong>: The snowpack was sampled either at the surface (0 to 5cm) or at about 20 cm depth. Where possible, meltwater leaking from the snowpack was sampled. At 3 locations in 2021, we dug snowpits from which we sampled snow at different layers with depth. All solid snow samples were melted at ambiant air temperature in air-tight plastic bags before being transferred into 12 mL vials</li> <li><strong>Rain </strong>: Rainwater was mostly sampled at our camp site at 2450 m. asl. Rainwater samples represent single rain events which are identified by dry periods of at least one day long.</li> <li><strong>Groundwater </strong>: shallow (2 to 3 meters) fully-screened groundwater wells were installed in the outwash plain and water sampled monthly in the snow-free season.</li> </ul> <p>- GPS coordinates are provided with each point (Swiss coordinate system CH1903+ / LV95<strong> (EPSG: 2056)).</strong></p> <p>- Dates are provided in local timezone (GMT+1 with daylight saving time) and in UTC date format.</p> <p>- Analyitcal error from the Picarro spectrometer is reported as 1 standard deviation.</p> <p>More information can be accessed in the corresponding publication by Müller et al. (to be published in 2023).</p> <p><strong>Data files</strong></p> <ul> <li><em>Otemma_isotope_EC_T_2019_2021.csv</em> : file containing all data with GPS coordinates</li> <li> <p><em>isotope_locations_Otemma.jpg</em> : an overview of the locations of each measurement point</p> </li> <li> <p><em>Otemma_Isotopes_2019-2020.html </em>: interactive plots of all datasets (δ<sup>2</sup>H, EC, temperature), classified by Type.</p> </li> </ul>
Crossing Treeline: Bacterioplankton community composition in alpine and subalpine lakes of the Rocky Mountain southern ecoregion and associated physical and chemical characteristics
This dataset includes lake water samples collected in the summer of 2016 from 16 different mountain lakes in the Rocky mountains in both Rocky Mountain National Park and the Snowy Range of southern Wyoming. Each lake was sampled twice: once in the early summer when hydrologic connections with the surrounding terrestrial environment were high and again in the late summer when hydrologic connections were low. The main goal of the study was to compare communities of bacterioplankton in alpine and subalpine lakes to determine if communities differed across treeline as soil microbes in the surrounding terrestrial environment were. To do so, we collected water samples from the deepest point of each lake, mixed it with a surface water sample and characterized bacterioplankton communities with 16S sequencing technology. Additionally, we wanted to identify abiotic factors that may correlate with community dissimilarity and characterized a suite of chemical attributes for each lake. Lake characteristics reported included surface temperature, soluble reactive phosphorous (SRP), ammonia (NH3+), pH, total dissolved nitrogen (TDN), total dissolved phosphorus (TDP), and total dissolved organic carbon (DOC), and chlorophyll a (chl-a).
Hummingbird foraging patterns across alpine meadows with RFID-equipped feeders in the HJ Andrews Experimental Forest, 2014-2017
Landscape changes can alter pollinator movement and foraging patterns which can in turn influence demographic processes of plant populations. In the Cascade Mountains of the Pacific Northwest, USA, forests are encroaching on alpine meadows that harbor diverse plant and pollinator communities. Whether encroachment and isolation of sub-meadows will influence pollinator foraging behaviors is unknown. To help assess those behaviors, subcutaneous Passive Integrated Transponders were implanted into 163 Rufous Hummingbirds (Selasphorus rufus), common avian pollinators in western North America and four arrays of five hummingbird feeders were established equipped with Radio Frequency Identification data loggers to passively relocate individuals at points throughout the landscape. The feeder arrays were established on four peaks along Frizzel Ridge in the H. J. Andrews Experimental Forest (Lookout Mountain, M1, M2, and Carpenter Mountain). A center feeder was established in a large, central alpine meadow and four satellite feeders c.a. 250m from the center. The satellite feeders were positioned such that at least one was in the open and connected to the center feeder by open habitat, one was in the open but separated from the center by coniferous forest canopy, and one was placed under coniferous forest canopy. Feeders were maintained for 1.5-12 weeks per year from 2014-2017.
Reciprocal transplant of mosses from Arctic tundra to alpine tundra and associated N2 fixation rates
In the summer of 2018, 12 cores were taken at Toolik Field Station. Six of those cores were retransplanted into their home environment, while six we transplanted to Eight Mile Lake. At Eight Mile Lake, the same procedure was followed. One year later, these transplants were revisited and associated N2 fixation rates were measured for Hylocomium splendens, Pleurozium scheberi and Aulacomnium turgidum using 15N2 gas incubations.
Sulfate reductions rates in alpine wetlands, 2021.
Alpine ecosystems serve as crucial water resources for many areas of the world, and biogeochemical cycling in these regions can influence the chemistry of water flowing into downslope watersheds. Alpine and subalpine wetlands are understudied systems of particular interest since lowland wetlands are known to have high rates of biogeochemical activity that can disproportionally affect carbon (C) and nutrient uptake, sequestration, and transformations within the landscape. Wetland processes play a central role in sulfur (S) transformations and have conditions that can support sulfate reduction. Sulfate reduction determines the sequestration of S in wetlands and interacts closely with a multitude of other element cycles, including iron, carbon, nitrogen, and mercury. As alpine systems warm due to climate change, it is important to characterize the biogeochemical processes at these sites to predict how they may shift in response. Sulfate reduction rates were measured in three wetlands at the Niwot Ridge Long Term Ecological Research site. A new radioactive tracer method was adapted and streamlined to suit alpine soils. This work trials and assesses various methodological approaches, as well as documents sulfate reduction rates from these sites, the first time this process has been measured at Niwot Ridge. Reduction rates at one site were measured three times, to track changes across the Summer 2021 field season.
Alpine and subalpine wetland soil physicochemical characteristics, summer 2020.
To understand patterns in soil biogeochemistry of wetlands at Niwot Ridge, samples were collected and analyzed for a series of physicochemical characteristics during 2020-2021. Samples were collected from 8 wetland sites lying at different elevations from the Saddle into the subalpine. At each site, samples were collected at 4 depth intervals within 5 sampling nodes along transects from the dry edge to saturated center of each system. These soils were analyzed for a suite of physicochemical characteristics, including soil moisture, bulk density, extractable nitrate and ammonium, loss on ignition as a proxy for organic carbon content, pH, total carbon and nitrogen, and adsorbed sulfate. Data will be used to inform future studies on biogeochemistry patterns and processes in alpine wetlands and across the Niwot landscape.
Alpine species transplant experiment within the sensor network, 2019 - 2021.
Weekly monitoring of survival and other fitness traits of 11 transplanted alpine species in addition to, non-transplanted, native, individuals. Individuals were monitored from early June to the end of August for survival and other fitness traits. Beginning in early July individuals from each species were transplanted to grids that were established near existing soil moisture sensors. Individuals were tracked until all had senesced however senescence was only indicated in transplants if it was irregular from native individuals.
Surface and porewater chemistry and sulfur stable isotpes for alpine and subalpine wetland sites, 2021.
To understand patterns in aqueous biogeochemistry of wetlands at Niwot Ridge, samples were collected and analyzed for dissolved anions and stable isotopes of sulfur in 2021. Samples were collected from eight wetland sites representing three wetland types, from the Saddle into the subalpine. At each site, tension lysimeters were placed at visible surface inflow and outflow paths to collect porewater. Water samples were collected from the tension lysimeters and surface pools during four time points through the summer season. Water samples were measured for a suite of dissolved anions using ion chromatography, including dissolved chloride, nitrate, and sulfate. Samples were also measured for dissolved organic carbon. Sulfur from one surface water sample from each site at each time point was precipitated as barium sulfate, and precipitations were analyzed for stable sulfur isotope ratio (δ^34S-SO4^2-) at the Center for Stable Isotope Biogeochemistry at the University of California, Berkeley. Data was used in conjunction with soil biogeochemistry data from 2020 to evaluate patterns in reactants among wetland types.
Silver film response to sulfate reduction activity in alpine and subalpine wetlands, 2022.
Alpine ecosystems serve as crucial water resources for many areas of the world, and biogeochemical cycling in these regions can influence the chemistry of water flowing into downslope watersheds. Alpine and subalpine wetlands are understudied systems of particular interest since lowland wetlands are known to have high rates of biogeochemical activity that can disproportionally affect carbon (C) and nutrient uptake, sequestration, and transformations within the landscape. Wetland processes play a central role in sulfur (S) transformations and have conditions that can support sulfate reduction. Sulfate reduction determines the sequestration of S in wetlands and interacts closely with a multitude of other element cycles, including iron, carbon, nitrogen, and mercury. Previous work in Niwot alpine and subalpine wetlands noted large variability in sulfate reduction rates within wetland soils. Samples taken less than a meter away from each other sometimes showed almost 70x higher or lower rates (Rea, unpublished work). This work sought to adapt a silver film method to quantify sulfate reduction rates over small-scale spatial areas. The method proved valuable as a quick indicator of sulfate reduction activity and was able to visualize soil heterogeneity. However, the silver films were not sensitive enough to quantify sulfate reduction rates in situ.
Alpine soil islands plant and soil microbial community composition, 2024.
High alpine ecosystems are particularly sensitive to climate-driven change, with vegetation expansion increasingly observed in historically barren soils. In late August and early September 2024, we revisited 50 previously established vegetation plots in Green Lakes Valley (Niwot Ridge LTER) to evaluate patterns of plant colonization and community change over time. Using legacy vegetation data from 2008 and 2015, we assessed changes in plant cover and composition in relation to microtopography and prior plant occurrence. Concurrently, we collected soil samples for 16S and 18S rRNA gene sequencing to characterize bacterial, archaeal, and eukaryotic microbial communities associated with these plots. Vegetation was resampled using spatially referenced 1-meter radius surveys, estimating species incidence and cover and documenting moss, lichen, sedge, and grass diversity. Together, these above- and belowground data provide insight into how priority effects, fine-scale environmental variation, and plant–microbe interactions influence alpine community dynamics, and may inform predictive models of ecosystem responses to ongoing climatic shifts.
Alpine ice sheet glacial cycle simulations aggregated variables
<p>These data contain time-integrated and otherwise time-reduced glacier model output variables.</p> <p><strong>Reference:</strong></p> <ul> <li>Seguinot, J., Ivy-Ochs, S., Jouvet, G., Huss, M., Funk, M., and Preusser, F.: Modelling last glacial cycle ice dynamics in the Alps, <em>The Cryosphere</em>, 12, 3265-3285, doi:<a href="https://doi.org/10.5194/tc-12-3265-2018">10.5194/tc-12-3265-2018</a>, 2018.</li> </ul> <p><strong>File names:</strong></p> <pre><code>alpcyc.{1km|2km}.{epic|grip|md01}.{cp|pp}.agg.nc</code></pre> <ul> <li>Horizontal resolution: <ul> <li><em>1km</em>: 1 km horizontal resolution</li> <li><em>2km</em>: 2 km horizontal resolution</li> </ul> </li> <li>Temperature forcing: <ul> <li><em>epic</em>: EPICA ice core temperature forcing</li> <li><em>grip</em>: GRIP ice core temperature forcing</li> <li><em>md01</em>: MD01-2444 core temperature forcing</li> </ul> </li> <li>Precipitation forcing: <ul> <li><em>cp</em>: constant precipitation</li> <li><em>pp</em>: palaeo-precipitation reduction</li> </ul> </li> </ul> <p><strong>Data format:</strong></p> <p>The data use compressed netCDF format. For quick inspection I recommend ncview. Conversion to GeoTIFF (and other GIS formats) can be achieved with e.g. GDAL::</p> <pre><code>gdal_translate NETCDF:filename.nc:variable filename.variable.tif</code></pre> <p>The list of variables (subdatasets) can be obtained from ncdump or gdalinfo. To convert all variables to separate files use:</p> <pre><code>gdalinfo $filename | grep NETCDF | cut -d '=' -f 2 | egrep -v '(lat|lon|time_bounds)' | while read sub do gdal_translate $sub ${filename%.nc}.${sub##*:}.tif done</code></pre> <p>Variable long names, units, PISM configuration parametres and additional information are contained within the netCDF metadata. Also see <a href="https://doi.org/10.5281/zenodo.1423175">continuous</a> variables.</p> <p><strong>Changelog:</strong></p> <ul> <li>Version 2: <ul> <li>Add age coordinate in kiloyears (ka) before present.</li> <li>Use ka units for covertime, deglacage and maxthkage.</li> </ul> </li> <li>Version 1: <ul> <li>Initial version</li> </ul> </li> </ul>
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.