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.
3,105
datasets available to search
ShareScore release 0.7.1
Dataset results
3,105 results for “vegetation”
Vegetation and Ground Cover of Permanent Plots for Upper Phillips Creek Marsh, Nassawadox, VA 1990-2014
Juncus roemerianus, the black needlerush, is a commonly found salt marsh plant. It exists especially in areas of little tidal inundation and low salinities. As such, it may play an important role in the accretion of marshes where sediment sources are not readily accessible. Biogenic accretion of marshes is a slow process representing the net result of production and decomposition. To study the process effectively requires long-term observations and experiments. We will initiate research at this site by selecting locations for study, collecting preliminary data on the locations, and designing long-term experiments. Plots for long-term observations will allow for analyses of changes in dominance of cover by plant species. We will choose plots to include the interface between J. roemerianus and other species and will follow changes at the interface. Also attached is an unpublished manuscript (PDF/A format) containing details of the data and some analyses.
Long-Term Fertilization Plots in Swale Vegetation on Hog Island, VA 2015 -
Nutrient enrichment plots were installed on Hog Island in 2015 (Moulton, 2017) following a modified Nutrient Network (nutnet.org) protocol. Plots followed a randomized design with three plot treatments (N = nitrogen, P = phosphorus, NP = nitrogen + phosphorus, and C = Control), replicated five times per treatment (N = 20 total experimental units, n = 5 per treatment). Each unit was 3 m2 with 1 m walkways. Units were subdivided into four 1 m2 subplots. N, P, and NP are applied in two applications, 30 days apart, at a rate of 10 g m-2 yr-1. N was added in the form of slow release urea (46-0-0) and P in the form of triple phosphate (0-45-0). Aboveground vegetation was harvested to ground level within a 0.1 x 1 m frame and extrapolated to represent plot level productivity (g m-2). Samples were dried for 72 h at 60 C and weighed (g). Species composition was sampled using areal cover estimation (%) of each species, bare ground, and dead plant material, such that total cover of each plot summed to 100%. Species cover was assessed in 1 m2 sub plots that had not previously been used for destructive sampling.
Simulations from the SEIB-DGVM dynamic global vegetation model for the Vegetation Carbon Turnover Intercomparison
<p>Outputs from the SEIB-DGVM dynamic global vegetation model. One forced by CRU-NCEP v5 climate data for the period 1901-2014 and one forced by bias-corrected IPSL-CM5A-LR RCP 8.5 climate data for the period 1901-2099. Only potential natural vegetation was simulated, i.e. no human land-use. Both simulations are at 0.5 x 0.5 degree spatial resolution. Carbon turnover fluxes for live vegetation for each individual turnover-causing process in the model were outputted individually. For a full description of the simulations, please refer to the accompanying paper.</p>
Fig. 2. Analine-blue stained vegetative features. A. A in An assessment of the taxonomic status of the Mediterranean endemic genus Acrodiscus Zanardini (Halymeniales, Rhodophyta)
Fig. 2. Analine-blue stained vegetative features. A. A transapical longitudinal section indicative of its multiaxial structure. B. The anticlinal orientation of pseudo-dichotomous cortical filaments. C. Mostly paired cortical cells in surface view. D. Longitudinally aligned, peripherally inverwoven medullary filaments. Scale bars: A, D = 20 μm; B–C = 10 μm.
Vegetation cover fractions for the City of Berlin dervided from Landsat 5, Landsat 7 and Landsat 8 data between 1988 and 2018
<p>Fractional vegetation cover dataset used in the study "Green growth? On the relation between population density, land use and vegetation cover fractions in a city using a 30-years Landsat time series".</p> <p>Landsat satellite imagery (Landsat-5 TM (Thematic Mapper), Landsat-7 ETM+ (Enhanced Thematic Mapper) and Landsat-8 OLI (Operational Land Imager)) was acquired for seven years between 1988 and 2018. Imagery was pre-processed and a regression-based unmixing approach was performed in order to generate fraction maps of vegetated and non-vegetated surfaces. For complete method description please see:</p> <p>Wellmann, T., Schug, F., Haase, D., Pfulgmacher, D., van der Linden, S. (2020). Green growth? On the relation between population density, land use and vegetation cover fractions in a city using a 30-years Landsat time series. <em>Landscape and Urban Planning</em></p>
Top-down and bottom-up vegetal and animal product metabolic profiles for 29 european countries (EU27 + United Kingdom + Norway).
<p>This repository contains the data needed to reproduce the results in:</p> <p>Cadillo-Benalcazar, J.; Renner, A. Giampietro, M. (2020). A multiscale integrated analysis of the factors characterizing the sustainability of food systems in Europe. Journal of Environmental Management. Volume 271, 1 October 2020, 110944. <a href="https://doi.org/10.1016/j.jenvman.2020.110944">https://doi.org/10.1016/j.jenvman.2020.110944</a></p> <p>Renner, A.; Cadillo-Benalcazar, J.; Benini, L., Giampietro, M. (2020). Environmental pressure of the European agricultural system: Anticipating the biophysical consequences of internalization. Ecosystem services. Special Issue: Agro-futures. Volume 46, December 2020, 101195. <a href="https://doi.org/10.1016/j.ecoser.2020.101195">https://doi.org/10.1016/j.ecoser.2020.101195</a></p>
Automated vegetation cover estimation from close-range photogrammetric point clouds in mountain terrain for comparison of vegetation location properties - Dataset
<p>Vegetation cover data of the used plots, showing values for manually digitized, in-situ, and photogrammetric methods.</p>
Model outputs for the paper "Drastic Vegetation Change in the Guajira Peninsula (Colombia) during the Neogene" submitted to Paleoceanography and Paleoclimatology
<p>We provide the netcdf files used to plot precipitation figures over South America in the paper. Four files are provided. Three files are for "preindustrial", "no Andes" and "open Central American Seaway" experiments that were carried out with the fully coupled model IPSL-CM4 (Marti et al., 2010). One file contains the outputs from a Miocene simulation carried out with NCAR CESM in Zhou et al. (2018).</p> <p>References :</p> <p>Marti, Olivier, P. Braconnot, J.-L. Dufresne, J. Bellier, R. Benshila, S. Bony, P. Brockmann, et al. 2010. « Key Features of the IPSL Ocean Atmosphere Model and Its Sensitivity to Atmospheric Resolution ». <em>Climate Dynamics</em> 34 (1): 1‑26. https://doi.org/10.1007/s00382-009-0640-6.</p> <p>Zhou, Haoran, Brent R. Helliker, Matthew Huber, Ashley Dicks, et Erol Akçay. 2018. « C4 Photosynthesis and Climate through the Lens of Optimality ». <em>Proceedings of the National Academy of Sciences</em> 115 (47): 12057‑62. https://doi.org/10.1073/pnas.1718988115.</p> <p> </p>
Dataset for: African manatee (Trichechus senegalensis) habitat suitability at Lake Ossa, Cameroon using trophic state models and predictions of submerged aquatic vegetation
<p>See research article here: https://onlinelibrary.wiley.com/doi/epdf/10.1002/ece3.8202</p> <p>Aim: The present study aims at investigating the past and current trophic status of Lake Ossa and evaluating its potential impact on African manatee health.</p> <p>Location: Lake Ossa is known as a refuge for the threatened African manatees in Cameroon. Little information exists on the water quality and health of the ecosystem as reflected by its chemical and biological characteristics.</p> <p>Methods: Aquatic biotic and abiotic parameters including water clarity, nitrogen, phosphorous and chlorophyll concentrations were measured monthly during four months at each of 18 water sampling stations evenly distributed across the lake. These parameters were then compared with historical values obtained from the literature to examine the dynamic trophic state of Lake Ossa.</p> <p>Results: Results indicate that Lake Ossa’s trophic state parameters doubled in only three decades (from 1985 to 2016), moving from a mesotrophic to a eutrophic state. The decreasing nutrient gradient moving from the mouth of the lake (in the south) to the north indicates that the flow of the adjacent Sanaga River is the primary source of nutrient input. Further analysis suggests that the poor transparency of the lake is not associated with chlorophyll concentrations but rather with the suspended sediments brought-in by the Sanaga River. Consequently, our model demonstrated that despite nutrient enrichment, less than 5% of the lake bottom surface sustained submerged aquatic vegetation. Thus, shoreline emergent vegetation is the primary food available for the local manatee population. During the dry season, water recedes drastically and disconnects from the dominant shoreline emergent vegetation, decreasing accessibility for manatees.</p> <p>Main conclusions: The current study revealed major environmental concerns (eutrophication and sedimentation) that may negatively impact habitat quality for manatees. Efficient land use and water management across the entire watershed may be necessary to mitigate such issues.</p>
Dataset of host, habitat and vegetation parameters in relation to gastrointestinal parasite infections of small mammalian hosts in Madagascar
<p>The dataset contains information on the endoparasite infection status of 903 individuals of four small mammal species (<em>Microcebus murinus</em>, <em>M. ravelobensis</em>, <em>Eliurus myoxinus</em>, <em>Rattus rattus</em>) in relation to host-specific (sex, body condition, population density) and habitat-specific factors (degree of habitat fragmentation, fragment size, distance to the edge of the fragment, percentage of edge habitat, vegetation structure).</p>
Digital orthoimagery for fractional vegetation cover at site Alpha from Morgan et al Kuiseb River study
<p>Contains high-resolution digital orthoimagery (RGB and NIR) and derived products for site Alpha, from the following manuscript:</p> <p>Morgan et al. (in prep), Spatiotemporal analysis of vegetation cover change in a large ephemeral river: multi-sensor fusion of unmanned aerial vehicle (UAV) and Landsat imagery.</p>
Dataset for "Phylogenetic structure of European forest vegetation" - Journal of Biogeography (DOI: 10.1111/jbi.14046)
<p>This dataset contains the list of plant occurrences and geographical and environmental attributes of the vegetation-plots analyzed in the paper titled “Phylogenetic structure of European forest vegetation” by Padullés Cubino et al. (2021; Journal of Biogeography; DOI: 10.1111/jbi.14046). </p> <p>The dataset contains 3 tables:</p> <ol> <li>“Table_taxa.csv”: It includes the list of angiosperm plant taxa in selected vegetation plots.</li> <li>“Table_sites.csv”: It includes data on the environmental variables of plots, their classification into different forest types, their location in 1<sup>o</sup> × 1<sup>o</sup> grid cells, and the reference to the original datasets archived in the European Vegetation Archive (EVA; http://euroveg.org/eva-database-participating-databases).</li> <li>“Metadata.csv”: It includes a description of the fields found in the two previous tables.</li> </ol>
Data of LAI-L20C in Vegetation masking effect on future warming and snow albedo feedback in a boreal forest region of northern Eurasia according to MIROC-ESM
<p>Data of LAI-L20C experiment in the research paper: Vegetation masking effect on future warming and snow albedo feedback in a boreal forest region of northern Eurasia according to MIROC-ESM.</p> <p>The paper was submitted to JGR-Atmosphere.</p> <p>Variables are limited to those used in the paper.</p> <ul> <li>snow water equivalent (swe)</li> <li>snow cover fraction (snc)</li> <li>clear-sky downward shortwave radiation at surface (rsdscs)</li> <li>clear-sky upward shortwave radiation at surface (rsuscs)</li> <li>surface air temperature (tas)</li> </ul> <p>See the paper for the detail.</p>
Grazing halos reveal differential ecosystem vulnerabilities in vegetated habitats
<p>Minguito-Frutos_etal_2024.xlsx contains the data to explore the relationship between habitat productivity and sea urchin consumption under different contexts. This relationship is represented by individually-produced sea urchin grazing halos, which are influenced by biotic and abiotic factors. </p> <p>Minguito-Frutos_etal_2024.R contains the R reproducible code to run all the analyses carried out in this study. </p> <p>--------------------------------------------------------------------------------------------------------------------------------------</p> <p><strong>Minguito-Frutos_etal_2025.R</strong> contains the code used in the final version of the manuscript accepted for publication in <em>Ecology</em>. This script includes the final specifications of the linear mixed models (LMMs) fitted in the study, along with all statistical evaluations and the corresponding visualizations.</p>
Twin test 1: Effect of vegetation on urban flows. PIV data from NTUA WT experiment and LDV from KIT WT experiment
<p>The first Twin Test (TW1) of the TWEET-IE project (<a href="http://www.tweet-ie.eu">www.tweet-ie.eu</a>) involved measurements of the flow past a surface mounted cube with openings, representing a building exposed to an atmospheric boundary layer. Tests were performed for smooth building walls but also with modelled vegetation covering the windward façade and the roof of the building. The measurements were performed both at Karlsruhe Institute of Technology (KIT) and the National Technical University of Athens (NTUA), in wind tunnels, at common locations around the building. Laser Doppler Anemometry (LDA) was used at KIT and Particle Image Velocimetry (2C-2D and 3C-2D PIV) at NTUA. In the present data set shows the effect of vegetation on the flow velocities and a comparison of the twin wind tunnel measurements. </p>
FIGURE 4. Sedum sect. Gormania vegetative shoots. A–F in A new species of stonecrop (Sedum section Gormania, Crassulaceae) from northern California
FIGURE 4. Sedum sect. Gormania vegetative shoots. A–F. Dense rosettes with abbreviated distal internodes in sunny locations; A–B. S. laxum subsp. flavidum, forming a dense, compact clone (Zika 25922, Trinity Co.); C. S. laxum subsp. heckneri (Zika 25640, Siskiyou Co.); D. S. oblanceolatum (Zika 25636, Jackson Co., Oregon, type locality); E–F. S. obtusatum subsp. obtusatum; E. Zika 26024 & Brainerd, El Dorado Co., California; F. Zika 26267, Sierra Co., California. G–N. Loose rosettes with well-spaced distal internodes in sunny locations. G–H. Sedum citrinum (Zika 26185); I. S. obtusatum subsp. boreale (Zika 26289, Siskiyou Co.); J–N. S. oregonense; J. Typical highly branched vegetative shoots, well-spaced and forming a loose clone (Zika 25647, Siskiyou Co.); K. Zika 25647; L. Zika 25666, Jackson Co., Oregon; M. Zika 25956, Linn Co., Oregon; N. Zika 25959, Linn Co. Scale bars 1 cm.
Рис. 1. Карта района иссΛеΑований. 1 – граница зон раститеΛьности; 2 – граница поΑзон раститеΛьности; 3 – места сбора материаΛа; I – южная тайга; II – среΑняя тайга; III – северная тайга; IV – крайнесеверная тайга; V – ΛесотунΑра; VI – южная тунΑра; VII – северная тунΑра. Fig. 1. Map of the studied area. 1 – boundary of vegetation zones; 2 – boundary of vegetation subzones; 3 – collection points; I – southern taiga; II – middle taiga; III – northern taiga; IV – extremely northern taiga; V – forest tundra; VI – southern tundra; VII – northern tundra. in Fauna and landscape-zonal distribution of Orthoptera in the Komi Republic (Russia)
Рис. 1. Карта района иссΛеΑований. 1 – граница зон раститеΛьности; 2 – граница поΑзон раститеΛьности; 3 – места сбора материаΛа; I – южная тайга; II – среΑняя тайга; III – северная тайга; IV – крайнесеверная тайга; V – ΛесотунΑра; VI – южная тунΑра; VII – северная тунΑра. Fig. 1. Map of the studied area. 1 – boundary of vegetation zones; 2 – boundary of vegetation subzones; 3 – collection points; I – southern taiga; II – middle taiga; III – northern taiga; IV – extremely northern taiga; V – forest tundra; VI – southern tundra; VII – northern tundra.
Assessing Nitrogen Availability in Biobased Fertilizers: Effect of Vegetation on Mineralization Patterns
<p>Biobased nitrogen (N) fertilizers derived from animal manure can substitute synthetic mineral N fertilizer and contribute to more sustainable agriculture. Practitioners need to obtain a reliable estimation of the biobased fertilizers’ N value. This study compared the estimates for pig slurry (PS) and liquid fraction of digestate (LFD) using laboratory incubation and plant-growing experiments. A no-N treatment was used as control and calcium ammonium nitrate (CAN) as synthetic mineral fertilizer. After 100 days of incubation, the addition of PS and LFD resulted in a net N mineralization rate of 10.6 ± 0.3% and 20.6 ± 0.4% of the total applied N, respectively. The addition of CAN showed no significant net mineralization or immobilization (net N release 96 ± 6%). In the pot experiment under vegetation, all fertilized treatments caused N immobilization with a negative net N mineralization rate of −51 ± 11%, −9 ± 4%, and −27 ± 10% of the total applied N in CAN, PS, and LFD treatments, respectively. Compared to the pot experiment, the laboratory incubation without vegetation may have overestimated the N value of biobased fertilizers. Vegetation resulted in a lower estimation of available N from fertilizers, probably due to intensified competition with soil microbes or increased N loss via denitrification.</p>
Climate and vegetation change in a coastal marsh: two snapshots of groundwater dynamics and tidal flooding at Piermont Marsh, NY spanning 20 years
<p>Groundwater hydrology plays an important role in coastal marsh biogeochemical function, in part because groundwater dynamics drive the zonation of macrophyte community distribution. Changes that occur over time, such as sea level rise and shifts in habitat structure are likely altering groundwater dynamics and eco-hydrological zonation. We examined tidal flooding and marsh water table dynamics in 1999 and 2019 and mapped shifts in plant distributions over time, at Piermont Marsh, a brackish tidal marsh located along the Hudson River Estuary near New York City. We found evidence that the marsh surface was flooded more frequently in 2019 than in 1999, and that tides were propagating further into the marsh in 2019, although marsh surface elevation gains were largely matching that of sea level rise. The changes in groundwater hydrology that we observed are likely due to the high tide rising at a rate that is greater than that of mean sea level. In addition, we reported on changes in plant cover by <em>P. australis</em>, which has displaced native marsh vegetation at Piermont Marsh. Although <em>P. australis</em> has increased in cover, wrack deposition and plant die off associated Superstorm Sandy allowed for native vegetation to rebound in part of our focus area. These results suggest that climate change and plant community composition may interact to shape ecohydrologic zonation. Considering these results, we recommend that habitat models consider tidal range expansion and groundwater hydrology as metrics when predicting the impact of sea level rise on marsh resilience.</p>
Maps of the diversity and distribution of Raunkiær's life forms in European vegetation
<p>This repository contains raster files (TIF format) with a 50 km × 50 km resolution (over UTM grid EPSG:32633), showcasing the diversity and distribution of Raunkiær’s life forms in European vegetation. The maps are based on two key metrics: (i) the proportion (%) of species within each life form and (ii) the diversity of life forms, including richness and evenness.</p> <p>To generate these maps, we averaged plot-level metric values across a comprehensive dataset comprising 546,501 vegetation plots sourced from the European Vegetation Archive (EVA; Project 163; <a href="https://euroveg.org" target="_new">https://euroveg.org</a>). These plots cover diverse habitats, including 173,190 forests, 260,884 grasslands, 52,517 scrubs, and 59,910 wetlands.</p> <p>The maps encompass the entire dataset, offering a visualization of the geographical distribution patterns of life forms across Europe. Additionally, we created habitat-specific maps by subsetting the dataset to explore unique patterns within each habitat type (forest, grassland, scrub, and wetland).</p> <p>Furthermore, we generated additional maps based on standardised effect sizes (SES) of diversity metrics. Through 500 species identity shuffles without replacement, specific to each habitat type, we examined the deviations from random expectations. SES values outside the range of -1.96 to 1.96 indicate significantly lower or higher metric values than expected at random, respectively. </p> <p> </p> <table> <tbody> <tr> <td><strong>Folder name</strong></td> <td><strong>Description of TIF raster values</strong></td> </tr> <tr> <td>full.div</td> <td>Mean richness and evenness of life forms across all habitat types</td> </tr> <tr> <td>full.mean.rel.prop</td> <td>Mean proportion of each life form across all habitat types</td> </tr> <tr> <td>habitat.div</td> <td>Mean richness and evenness of life forms across separate habitat types (forest, grassland, scrub, and wetland)</td> </tr> <tr> <td>habitat.mean.rel.prop</td> <td>Mean proportion of each life form across separate habitat types (forest, grassland, scrub, and wetland)</td> </tr> <tr> <td>SES.full.div</td> <td>Mean richness and evenness of life forms across all habitat types measured with standardized effect sizes (SES)</td> </tr> <tr> <td>SES.full.mean.rel.prop</td> <td>Mean proportion of each life form across all habitat types measured with standardized effect sizes (SES)</td> </tr> <tr> <td>SES.habitat.div</td> <td>Mean richness and evenness of life forms across separate habitat types (forest, grassland, scrub, and wetland) measured with standardized effect sizes (SES)</td> </tr> <tr> <td>SES.habitat.mean.rel.prop</td> <td>Mean proportion of each life form across separate habitat types (forest, grassland, scrub, and wetland) measured with standardized effect sizes (SES)</td> </tr> </tbody> </table> <p><br>Additional information is available in our publication:<br><br>Midolo, G., Axmanová, I., Divíšek, J., Dřevojan, P., Lososová, Z., Večeřa, M., Karger, D. N., Thuiller, W., Bruelheide, H., Aćić, S., Attorre, F., Biurrun, I., Boch, S., Bonari, G., Čarni, A., Chiarucci, A., Ćušterevska, R., Dengler, J., Dziuba, T., Garbolino, E., Jandt, U., Lenoir, J., Marcenò, C., Rūsiņa, S., Šibík, J., Škvorc, Ž., Stančić, Z., Stanišić-Vujačić, M., Svenning, J. C., Swacha, G., Vassilev, K., & Chytrý, M. (2024) Diversity and distribution of Raunkiær’s life forms in European vegetation.<em> Journal of Vegetation Science. </em>Accepted on the 10th of December 2023</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.