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.
269
datasets available to search
ShareScore release 0.9.0
Dataset results
269 results for “Vegetation Cover”
Annual precipitation and photo-derived vegetation and litter cover (2013-2021) used for analysis in the manuscript “Growing grasses in the desert: Multi-scale Interactions and State Change Reversal in Drylands”
This dataset contains water year precipitation collected from meteorological stations, litter and vegetation cover values derived from overhead photos, and litter and soil accumulation in lateral photos in a long-term experiment (2013-2021) of cross-scale interactions (CSIs) at the Jornada Basin LTER site in southern New Mexico, U.S.A. Manipulations were initiated in 2013 at 15 experimental blocks, each with 4 treatment plots: plant-scale herbicide of mesquite shrubs, patch-scale connectivity modifiers (ConMods), herbicide + ConMods, control without manipulations. Litter, soil, and vegetation cover were estimated using repeat overhead photographs of microplots within treatment and control plots. Litter and soil accumulation were estimated from lateral photos of ConMods. This dataset utilized QuickBird imagery from 2011 to assess ground cover classes within the Jornada Basin, focusing on bare ground, herbaceous, and shrub cover. Daily precipitation data collected from 13 meteorological stations were used to calculate water year (1 October-30 September) precipitation from 2013 through 2021. This dataset provides supporting data for the manuscript "Growing grasses in the desert: Multi-scale Interactions and State Change Reversal in Drylands" by Peters et al.
Vegetation Cover in the Clearcut Site at Harvard Forest 2010-2013
We used the line-intercept method to monitor the expansion of vegetation cover at our site, post-clearcut. This dataset was also used to calculate leaf area at the site from 2010 to 2012 and also in upscaling leaf gas exchange measurements collected during the 2010 and 2012 growing seasons. The data was used in two publications listed below (as of June 2014) and numerous poster presentations. Data collection was done during the REU summer programs, with Prof. William’s graduate students and postdocs acting as guides/mentors to the REU students.
University of Oregon Great Basin Vegetation Cover Study, Southeastern Oregon, 2023.
This data package contains qualitative and quantitative environmental and vegetation survey data used to investigate connections between cattle grazing intensity and vegetation cover in the Great Basin region of Eastern Oregon. The experimental design utilized a piosphere approach to select plots of different grazing intensity in pastures stratified by recent burn history. Surveys were completed in 340 plots around 43 water sources in the summer of 2023. Surveys consisted of recording site characteristics (e.g. slope, aspect, human impacts) as well as measuring plant species cover, cattle and other ungulate dung counts, biocrust development, and soil stability and texture. Plants were generally identified to species where possible, allowing for comparisons between species as well as identification of trends among functional groups (shrubs, annual grasses, perennial grasses, annual forbs, perennial forbs, trees).
Critical slowing down: vegetation height, cover and composition assess resilience of tidal fresh, brackish and salt marshes following experimental disturbance at twelve sites across the estuarine landscape
We investigated the relative recovery rates of vegetation cover, vegetation height and community composition over a period of >10 years after experimental disturbance in 12 tidal marshes (two oligohaline, three mesohaline and seven polyhaline sites) across the estuarine landscape on the coast of Georgia, USA. Vegetation was removed from three by three meter plots (four per site) with herbicide in 2006 followed by repeated clipping through 2009. Vegetation height, cover and composition was assessed in experimental and control plots (4 of each per site) from 2010 to 2020. The goal of the study was to assess how quickly the sites recovered from disturbance, how this varied in different types of marshes, and how results varied depending on whether recovery was assessed by vegetation height, cover or composition.
Hierarchical herbivore exclosure vegetation canopy cover at 3 sites across grassland-shrubland ecotones, 2022
The goal of this dataset is to examine long-term effects of multiple herbivore groups on canopy cover of plants across a shrub encroachment gradient (i.e., Ecotone Study) using herbivore exclusion treatments. Plots (2x2-m) were controls (open to all herbivores), large herbivore exclusion (lagomorph, rodent access), or full exclusion (no herbivore access). Plots were established in 2001 across grassland-shrubland ecotones in patches of black grama (Bouteloua eriopoda with >75% cover). Biomass of B. eriopoda was physically removed from the center 40x40-cm2 patch of each treatment to simulate disturbance. We sampled the controls and herbivore exclosure plots in summer 2022 to evaluate the long-term influence of herbivore exclusion on B. eriopoda recovery and overall canopy cover.
Grass seedling survival and microhabitat vegetation cover among herbivore exclusion treatments across grassland-shrubland ecotones at 3 sites, 2022 and 2023
The aim of this study is to reveal how mammalian herbivores differentially affect the survival of grass seedlings depending on herbivore taxa (cattle, oryx, lagomorphs, rodents) and microhabitat vegetation structure surrounding grass seedlings. This dataset includes data tracking the survival of grass seedlings among herbivore exclusion treatments across grassland, ecotone, and shrubland habitats. Seedling survival trials were established at 3 spatial blocks associated with the Ecotone Study: JER Pastures 9 and 12, and CDRRC Pasture 3. Survival trials were conducted on Pasture 12 in 2022, and on Pastures 3, 9, and 12 in 2023. Each spatial block contained 3 sites (grassland, ecotone, shrubland) that were further subdivided into 5 replicate plots (n = 45 plots). Two trays (1 control open to all herbivores, 1 caged allowing only rodent access) of 25 seedlings each were buried at ground level at each plot and their condition (i.e., alive & undamaged, alive & herbivore damaged, senesced or absent via herbivory, senesced due to environmental stress, resprouted following herbivory, unknown fate, or herbivory following senescence) recorded every 3 days for a total of 15 days. Microhabitat vegetation cover surrounding the seedling trays was collected using ocular estimates of cover across plant functional types (e.g., perennial grasses, forbs, sub-shrubs, shrubs, etc.) within 1 square-meter PVC quadrats placed on both the east and west face of seedling trays established in the field. Maximum height of vegetative (non-reproductive) plant tissue of each functional type was additionally recorded to gauge the level of grass seedling concealment.
Urban forest canopy cover, vegetation, and site characteristics, Twin Cities Metro Area, 2022 and 2023.
This data was primarily collected to assess forest quality within the Minneapolis-St. Paul (MSP) Metropolitan Area and to link above-ground and below-ground properties as part of the goals of the MSP-LTER Urban Tree Canopy research group. Here, we sampled vegetation on 48 circular plots with a 12.5 m radius distributed across 18 parks, registering the date of sampling, park and management agency names, the plot number, and geolocation (latitude, longitude, and elevation). The plots were randomly selected based on GEDI (Global Ecosystem Dynamics Investigation instrument) 2021 footprints in the MSP Metropolitan Area along accessible forested areas inside public parks, where the management agency allowed sampling. In each plot, we measured forest structure and diversity metrics, species names and abundance, DBH, height, distance from the plot center, the height where each individual canopy starts, and the relative position, exposure, and density of each canopy. We also measured understory plant structure and diversity in 4 subplots per plot, totaling 192 subplots. In these subplots, we surveyed all individual plants with heights over 20 cm, recording species names and abundance, plant basal diameter, plant height, and the total number of branches. Furthermore, we assessed the canopy openness above each subplot by calculating percent DIFN (diffuse non-interceptance) from fish eye pictures of the canopy at 1.3 meters over the subplot.
Global monthly percentage of vegetation cover (MODIS FCover MODV1A product: America, Pacific)
<p>Monthly Global FCover product generated from MODIS data. Dataset represent monthly gap-filled FCover estimates the period 2000-2015 over Pacific and America. FCover was estimated using linear spectral mixture analysis and interpolated using empirical orthogonal functions algorithm to take advantage of all non-missing available pixels in both the spatial and temporal dimensions to gap-fill missing satellite observations. The global product of vegetation cover (as percentage of cover) based on MODIS images with monthly variation can be used as a critical support for several indicators related to ecologically based modelling.</p>
30 m Normalized Difference Vegetation Index Maps of Pure Pixels over China for Estimation of Fractional Vegetation Cover (2014, 2018, 2022)
<p>Using multi-angle remote sensing data, we generated 30-m maps for the normalized difference vegetation index (NDVI) of fully-covered vegetation (<em>Vv</em>) and bare soils (<em>Vs</em>) across China in 2014, 2018 and 2022. These pixel-wise <em>Vv</em> and <em>Vs</em> maps can be integrated with the vegetation index (VI)-based model to facilitate the accurate and rapid estimation of fractional vegetation cover (FVC) across various spatial resolutions and large scales. The products were produced using a multi-angle algorithm (MultiVI), which effectively addressed the spatial variability inherent in <em>Vv</em> and <em>Vs</em> and enhanced the accuracy of FVC estimations in comparison to traditional statistical methods. The estimated FVC demonstrated a root mean square deviation (RMSD) of approximately 0.1 when evaluated against field-measured FVC across different experimental sites.</p>
Percent cover of under- and mid-story vegetation and seedling counts in the Future of Oak Forests project at Black Rock Forest, Cornwall, NY.
Black Rock Forest established a series of 12, 0.56 ha plots in 2005 to assess impacts of the loss of tree in the genus Quercus on the forest ecosystem (entitled the Future of Oak Forests experiment). Three trunk girdling treatments, with control plots were instituted in 2008. Each plot also contained an ~10m by ~15m deer exclosure to assess the impact of herbivory post-disturbance. In 2006 and 2008, before exclosures were erected, pre-treatment surveys were conducted in all unexclosed (n=120) quadrats. Surveys of all 240 understory quadrats were conducted annually in late summer (August to September) from 2009 to 2018 and then again in 2021. At each quadrat, trained observers identified all vascular plants to species and assigned each species a percent cover value. The percent cover of moss was also recorded but moss species were not identified. Counts of tree seedlings and some woody shrubs were also recorded in addition to percent cover values. Seedlings were considered saplings, and therefore not counted, once they reached 1.3 m tall (breast height).
Quadrat vegetation cover data on 1m x 1m plots from the long-term Small Mammal Exclusion Study (SMES) at Jornada Basin LTER, 1995-2020
This data package contains vegetation cover from plots with various levels of herbivore exclusion on the Jornada Experimental Range (JER) and Chihuahuan Desert Rangeland Research Center (CDRRC) in Dona Ana County, southern New Mexico, USA. Study sites were established in 1995; one in black grama grassland and the other in creosotebush shrubland to compare the impact of herbivores on ecosystem processes between these vegetation types. Parallel studies were established at the Sevilleta LTER site (New Mexico, USA) and Mapimi Biosphere Reserve (Durango, Mexico). Each study site is 1 km by 0.5 km in area. Four replicate experimental blocks were randomly located at the grassland study site to measure vegetation responses using exclusion treatments including a) all mammalian herbivores, including cattle, lagomorphs, and rodents, b) lagomorphs and cattle only, c) cattle only, and d) control accessible to all herbivores. Because grazing cattle are excluded from the entire creosote site, only three replicate experimental blocks were randomly located there including a) all mammalian herbivores, including lagomorphs, and rodents, b) lagomorphs only, and c) control accessible to all herbivores. Thirty-six sampling points were positioned at 5.8-meter intervals on a systematically located 6 by 6 point grid within each plot. A permanent one-meter by one-meter vegetation measurement quadrat is located at each of the 36 points. At each quadrat, percent cover by individual plant species is measured. Other measurements include height (cm) of each species in the quadrat, and plant condition (living or dead). Data were collected in the spring and fall of every year from 1995 to 2005. After 2005, sampling frequency changed to every 5 years in the fall. This study is ongoing.
Aboveground vegetation cover and biomass in plots with experimentally altered precipitation variability at the Jornada Basin LTER site, 2009-ongoing
This dataset contains cover and biomass data collected starting in 2012 for a long-term precipitation variability manipulation experiment at the Jornada Basin LTER site in southern New Mexico, U.S.A. The study was designed to assess the effect of interannual variability in precipitation on average aboveground net primary productivity (ANPP) in Chihuahuan Desert grasslands. The study began in 2009, has five annual precipitation treatments, and contains 50 plots (10 per treatment). This experiment uses precipitation shelters and irrigation treatments to manipulate water inputs to 2.5 x 2.5 meter plots in a desert grassland. There are high, low, and ambient (control) precipitation variability treatments. Ambient plots receive natural precipitation each year, while variability treatments alternate between 20% and 180% (high variability), or 50% and 150% (low variability) of ambient precipitation each year. Plant cover measurements are made annually in each plot, from which biomass or net primary production are derived. This is an ongoing study and the dataset will be updated yearly.
Aboveground vegetation cover and biomass in plots with experimentally altered precipitation and nutrient inputs at the Jornada Basin LTER site, 2006-ongoing
This dataset contains cover and biomass data collected starting in 2006 for a long-term precipitation and nutrient manipulation experiment at the Jornada Basin LTER site in southern New Mexico, U.S.A. This experiment uses precipitation shelters and irrigation treatments to manipulate water inputs, and fertilization treatments to alter nitrogen input to 2.5 x 2.5 meter plots in a desert grassland. Plant cover measurements are made annually in each plot, from which biomass or net primary production are derived. This is an ongoing study and the dataset will be updated yearly.
Herbaceous vegetation size and cover data in grasshopper survey quadrats at the Jornada Basin LTER site, 1984 to 1985
This dataset contains annual herbaceous plant data collected in association with grasshopper surveys during 1984 and 1985 as part of the Jornada Basin LTER program. Annual herbaceous plant data was collected from Jornada grasshopper plots on the east bajada of the Dona Ana Mts. Three plots were situated on the bajada parallel to and 200 m south of the LTER-I transect. Two additional sets of three plots were located 5 km and 10 km south of the LTER transect. Each plot is composed of two 50 m belt transects, each divided into ten 5-meter-squared quadrats. Annual plants were measured in the northeast 1 square meter of each quadrat. All individuals of each species were counted and measured. A mean diameter, height, and the total number of individuals per 1-square-meter quadrat were recorded. Measurements were taken in May, July, and September of 1984, and in May and September of 1985. This dataset consists of the date of collection, plot number, transect number, quadrat number, plant species code, mean plant diameter, and mean plant height. This dataset is complete.
PIE LTER salt marsh vegetation cover data from regularly monitored quadrats along transects in Rowley, MA.
Marsh vegetation cover data from quadrats along transects in salt marsh sites in Rowley, MA. The transects are intended to study long term changes in marsh vegetation. Four sites ((12 transects) were originally set up to study the impact of salt marsh haying. Two of these sites (labeled McH and EPH) were regularly hayed until 2002. The other two (PUH and CC) were reference sites. Two additional sites labeled RM and RR (8 transects) were originally set up to track invasion by Phragmites australis.
Data and code for the manuscript "From white to green: Snow cover loss and increased vegetation productivity in the European Alps"
<p>Data and code used for the manuscript "From white to green: Snow cover loss and increased vegetation productivity in the European Alps" by Rumpf et al., submitted December 2021 to Science</p> <p>See file ReadMe.txt for a description of the content and the original publication for further explanations.</p> <p>You are free to use these data and code for scientific purposes but are obliged to cite the above-mentioned publication.<br> For further questions, contact sabine.rumpf@unibas.ch</p>
Arctic vegetation cover fractions derived from Landsat time series (1984-2020) for the greater Mackenzie Delta Region (Western Canadian Arctic)
<p>Data to the publication by Nill et al. (2022) "<em>Arctic shrub expansion revealed by Landsat-derived multitemporal<br> vegetation cover fractions in the Western Canadian Arctic"</em></p> <p>The dataset features Landsat-derived fractional cover estimates of Arctic plant functional types (shrub, evergreen trees, herbaceous, lichen) and other land cover (barren, water) in the greater Mackenzie Delta Region, Canada.<br> We utilized regression-based unmixing based on synthetic training data in order to build multitemporal Kernel Ridge Regression (KRR) models for estimating fractional cover and validated our predictions based on independent very-high-resolution imagery (please be referred to publication for details).<br> <br> <strong>Dataset information</strong><br> The fraction cover predictions ("krr-avg") are provided separately for each epoch (1984-1990, 1991-1996, ..., 2015-2020) and class/cover type. The decadal change images ("dec-cng") between 1984 and 2020 are provided separately for each class/cover type. The naming convention of the files is as follows:</p> <p>XXXX-XXXX_YYY-YYY_int16-10e3_class-Z-Z</p> <ul> <li>XXXX-XXXX = epoch, e.g. 2015-2020</li> <li>YYY-YYY = dataset ("krr-avg" = fraction cover, "dec-cng" = decadal fraction cover change)</li> <li>Z-Z = class ID and associated class name (sh = shrub, cf = coniferous, hb = herbaceous, lc = lichen, wt = water, br = barren)</li> </ul> <p>The fraction cover values are % scaled by 10,000. For instance, a value of 1234 refers to 12.34%. Further image metadata:</p> <ul> <li><strong>Datatype:</strong> Signed 16-bit integer (Int16) </li> <li><strong>Data format: </strong>GeoTiff (.tif)</li> <li><strong>No data value:</strong> -9999</li> <li><strong>Projection:</strong> EPSG:3573 with custom central meridian; WKT string: 'PROJCS["WGS 84 / North Pole LAEA Canada",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],PROJECTION["Lambert_Azimuthal_Equal_Area"],PARAMETER["latitude_of_center",90],PARAMETER["longitude_of_center",-135],PARAMETER["false_easting",0],PARAMETER["false_northing",0],UNIT["metre",1],AXIS["Easting",EAST],AXIS["Northing",NORTH]]'</li> </ul> <p><strong>Publication</strong><br> Nill, L., Grünberg, I., Ullmann, T., Gessner, M., Boike, J. & Hostert, P. (2022): Arctic shrub expansion revealed by Landsat-derived multitemporal vegetation cover fractions in the Western Canadian Arctic. Remote Sensing of Environment, 2022, 281. https://doi.org/10.1016/j.rse.2022.113228</p> <p><strong>Further information</strong><br> For further information, please see the publication or contact Leon Nill (leon.nill@geo.hu-berlin.de).<br> A web-visualization of this dataset is available <a href="https://ows.geo.hu-berlin.de/webviewer/arctic-shrub/">here</a>.</p>
Biophysical effects of vegetation cover change from satellite and models
<p>Vegetation cover changes associated with land use and land cover change (LULCC) can perturb the local surface energy balance, which in turn can affect the local climate. Land surface models (LSMs) can be used to simulate such land-climate interactions, but their capacity to model these biophysical effects accurately across the globe remain unclear due to the complexity of the phenomena. This dataset provides idealized simulations from four LSMs (JULES, ORCHIDEE, JSBACH and CLM) that are harmonized with estimations obtained from satellite observations, enabling the inter-comparison and benchmarking of LSM performances and which can serve to identify model limitations and prioritize efforts in model development. The dataset provides the change in latent heat flux, in combined sensible and ground heat flux and in net radiation caused by 15 specific vegetation cover transitions on a 1° by 1° grid at monthly time scale for a synthetic year based on data from 2008 until 2012. The dataset was generated from a collaborative effort lead by JRC within the FP7 LUC4C project (luc4c.eu).</p>
SGS-LTER Long-Term Monitoring Project: Vegetation Cover on Small Mammal Trapping Webs on the Central Plains Experimental Range, Nunn, Colorado, USA 1999 -2006, ARS Study Number 118 (Reformatted to the ecocomDP Design Pattern)
This data package is formatted as an ecocomDP (Ecological Community Data Pattern). For more information on ecocomDP see https://github.com/EDIorg/ecocomDP. This Level 1 data package was derived from the Level 0 data package found here: https://pasta.lternet.edu/package/metadata/eml/knb-lter-sgs/140/17. The abstract below was extracted from the Level 0 data package and is included for context: This data package was produced by researchers working on the Shortgrass Steppe Long Term Ecological Research (SGS-LTER) Project, administered at Colorado State University. Long-term datasets and background information (proposals, reports, photographs, etc.) on the SGS-LTER project are contained in a comprehensive project collection within the Digital Collections of Colorado (http://digitool.library.colostate.edu/R/?func=collections&collection_id=3429). The data table and associated metadata document, which is generated in Ecological Metadata Language, may be available through other repositories serving the ecological research community and represent components of the larger SGS-LTER project collection. Additional information and referenced materials can be found: http://hdl.handle.net/10217/83458. The abundance and diversity of small mammals in shortgrass steppe is strongly influenced by the structure and composition of vegetation. Vegetation structure provides cover from predators and harsh abiotic conditions. Plant species composition affects the types of seeds and herbaceous material available to granivores and herbivores, and influences arthropod populations, which are important prey for the omnivorous species that dominate in shortgrass steppe. Both vegetation structure and plant community composition are sensitive to the availability of precipitation as well as the activity of large mammalian herbivores. In 1999, we began measuring vegetation structure and plant community composition on the three grassland and three shrubland trapping webs where we live-trap small mammals
Tree regeneration after fire: Effects of burn severity, CPCRW vegetative cover analysis
This study examines the effects of burn severity on patterns of post-fire tree establishment in the boreal forest. We collected data from 5 separate field experiments examining seedling establishment across different severity levels in 4 burns in central Yukon Territory, Canada, and interior Alaska, USA. The experimental studies focus on the germination, survival, and growth responses of four common tree species, trembling aspen (Populus tremuloides), lodgepole pine (Pinus contorta), white spruce (Picea glauca) and black spruce (Picea mariana). Data on the soil organic layer (depth, moisture, bulk density, pH) were also collected at each site. This file contains visual cover estimates, by species, for 2000-2002 at the CPCRW site. Sample dates are: 4 August 2000 25 July 2001 16 July 2002. Values are percent cover in a 1x1m quadrat, where T=trace (less than 0.5%), out=outside quadrat but inside experimental plot. An additional line is included which give the full species names associated with the 6-letter codes used as column headers.
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.