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.
22,710
datasets available to search
ShareScore release 0.7.1
Dataset results
22,710 results for “Plant”
Marsh plant species shoot height, weight and diameters for Rowley River tidal creeks associated with long term fertilization experiments, Rowley and Ipswich, MA.
Marsh plant species shoot height, weight and diameters for Rowley River tidal creeks associated with long term fertilization experiments, Rowley and Ipswich, MA. The TIDE project aims to simulate eutrophication on a large scale by the addition of NO3- aiming to reach 70μM concentrations from May to September every year during the growing season. This fertilization of the marsh has been going on at Sweeney Creek since the 2004 growing season through 2012 and at Clubhead Creek in 2005 and from 2009 till 2019.
Plant heights at control and fertilized plots in a Spartina alterniflora-dominated marsh, Law's Point, Rowley River, Plum Island Ecosystem LTER, MA (1999-2025).
Plant heights are measured during the growing season in permanent plots at a Spartina alterniflora-dominated salt marsh on the Rowley River within the Plum Island Ecosystems (PIE) LTER site. Plant heights are converted to plant weight using an algorithm to generate a non-destructive estimate of aboveground plant biomass.
Aboveground plant biomass and density in control and fertilized plots in a Spartina alterniflora-dominated marsh, Rowley River, Plum Island Ecosystem LTER, MA (1999-2025).
Aboveground plant biomass and density is determined non-destructively during the growing season in permanent control and fertilized plots in a Spartina alterniflora-dominated salt marsh at Laws Point on the Rowley River within the Plum Island Ecosystems (PIE) LTER site.
Plant aboveground biomass dry weight record for Space for Time plots in PIE LTER.
Aboveground biomass measurements were conducted annually near peak biomass to evaluate aboveground plant production and determine differences in relation to other biotic and abiotic factors. In a 0.053 m2 plot, aboveground biomass was clipped to the soil surface at Space For Time plots, dried, and weighed to capture dry weight.
Plant heights from permanent plots in a Spartina alterniflora-dominated marsh, Nelson Island, Parker River National Wildlife Refuge, Plum Island Ecosystems LTER, MA (2019-2025).
Plant heights are measured during the growing season in permanent plots at a Spartina alterniflora-dominated salt marsh on Nelson Island, Parker River National Wildlife Refuge, within the Plum Island Ecosystems (PIE) LTER site. Plant heights are converted to plant weight using an algorithm to generate a non-destructive estimate of aboveground plant biomass.
Plant Removal Study: Recovery of Vegetation Following Disturbance at the Sevilleta National Wildlife Refuge, New Mexico
In 1995, a removal study was initiated at the Sevilleta LTER to examine the response of vegetation following the removal of dominant species. Five sites were selected that were dominated by either blue grama (site 1), blue and black grama (site 2), black grama (site 3), black grama and creosote (site 4), or creosote (site 5). A sixth site was later added in the blue grama community along the foothills of the Los Pinos Mountains (site 6). At sites 1, 3, 5, and 6, five 3m x 4m plots had all plants of the dominant species removed; five 3m x 4m plots were controls. At site 2, 5 plots had blue grama removed, 5 plots had black grama removed, and 5 plots were controls. At site 4, 5 plots had black grama removed, 5 plots had creosote removed, and 5 plots were controls. Initial cover prior to removal was estimated by species for each plot. Grass was removed using a shovel to collect above-ground biomass and crowns just below the soil surface. Shrubs were removed using large clippers to collect above-ground biomass to the soil surface. All biomass removed was bagged, dried, and weighed. Plot maintenance or removal of the target dominant species is performed annually or as needed. Rain gauges were installed at each site and the corners of the areas containing each set of plots GPS'd. Plot corners are marked by nails and are flagged periodically to aid identification and minimize foot traffic in the plots. Each northeast nail has a metal tag with site and plot number on it. Erosion bridges (1 m long) were installed in plots 1, 3 and 5 (removals and controls) at sites 1-5. Initial measurements were made in 1996.
SEV-LTER quadrat plant species cover and height all sites and experiments
This dataset includes plant species cover and height data measured in 1 m x 1 m quadrats at several sites and experiments under the Sevilleta LTER program. Quadrat locations span four distinct ecosystems and their ecotones: creosotebush dominated Chihuahuan Desert shrubland (est. winter 1999), black grama-dominated Chihuahuan Desert grassland (est. winter 1999), blue grama-dominated Plains grassland (est. winter 2002), and pinon-juniper woodland (est. winter 2003). Data on plant cover and height for each plant species are collected per individual plant or patch (for clonal plants) within 1 m x 1 m quadrats. These data inform population dynamics of foundational and rare plant species. In addition, using plant allometries, these non-destructive measurements of plant cover and height can be used to calculate net primary production (NPP), a fundamental ecosystem variable that quantifies rates of carbon consumption and fixation. Estimates of plant species cover, total plant biomass, or NPP can inform understanding of biodiversity, species composition, and energy flow at the community scale of biological organization, as well as spatial and temporal responses of plants to a range of ecological processes and direct experimental manipulations. The cover and height of individual plants or patches are sampled twice yearly (spring and fall) in permanent 1m x 1m plots within each site or experiment. This dataset includes core site monitoring data (CORE, GRIDS, ISOWEB, TOWER), observations in response to wildfire (BURN), and experimental treatments of extreme drought and delayed monsoon rainfall (EDGE), physical disturbance to biological soil crusts on the soil surface (CRUST), interannual variability in precipitation (MEANVAR), intra-annual variability via additions of monsoon rainfall (MRME), additions of nitrogen as ammonium nitrate (FERTILIZER), additions of nitrogen x phosphorus x potassium (NutNet), and interacting effects of nighttime warming, nitrogen addition, and El Ni
SEV-LTER quadrat plant species biomass all sites and experiments
This dataset includes estimated plant aboveground live biomass data measured in 1 m x 1 m quadrats at several sites and experiments under the Sevilleta LTER program. Quadrat locations span four distinct ecosystems and their ecotones: creosotebush dominated Chihuahuan Desert shrubland (est. winter 1999), black grama-dominated Chihuahuan Desert grassland (est. winter 1999), blue grama-dominated Plains grassland (est. winter 2002), and pinon-juniper woodland (est. winter 2003). Data on plant cover and height for each plant species are collected per individual plant or patch (for clonal plants) within 1 m x 1 m quadrats. These data inform population dynamics of foundational and rare plant species. Biomass is estimated using plant allometries from non-destructive measurements of plant cover and height, and can be used to calculate net primary production (NPP), a fundamental ecosystem variable that quantifies rates of carbon consumption and fixation. Estimates of plant species cover, total plant biomass, or NPP can inform understanding of biodiversity, species composition, and energy flow at the community scale of biological organization, as well as spatial and temporal responses of plants to a range of ecological processes and direct experimental manipulations. The cover and height of individual plants or patches are sampled twice yearly (spring and fall) in permanent 1m x 1m plots within each site or experiment. This dataset includes core site monitoring data (CORE, GRIDS, ISOWEB, TOWER), observations in response to wildfire (BURN), and experimental treatments of extreme drought and delayed monsoon rainfall (EDGE), physical disturbance to biological soil crusts on the soil surface (CRUST), interannual variability in precipitation (MEANVAR), intra-annual variability via additions of monsoon rainfall (MRME), additions of nitrogen as ammonium nitrate (FERTILIZER), additions of nitrogen x phosphorus x potassium (NutNet), and interacting effects of nighttime warming, nitroge
Floral traits of animal-pollinated Sevilleta plant species
Concern about pollinator populations is widespread, with bees documented to be in decline due to factors including habitat loss, disease, and pesticides. In addition, climate change may be an important cause of bee population losses, but few studies have examined bee abundance relationships with climate variables. Importantly, bees may respond directly to climate or may exhibit indirect responses to climate via changes in plant phenology or community composition. This study collected floral trait data to complement the Sevilleta LTER pollinator monitoring, plant phenology, and plant biomass datasets, with the aim of examining whether floral resource availability mediates bee responses to climate. For 71 common, animal-pollinated flowering plant species, we measured floral traits relevant to pollination in June–October 2018 and April–August 2019 within sites representing four ecosystem types at the Sevilleta National Wildlife Refuge: Plains grassland, Chihuahuan Desert grassland, Chihuahuan Desert shrubland, and piñon-juniper woodland. On a minimum of 5 individuals per plant species, we recorded the total number of open flowers and the corolla width of flowers, along with plant height and vegetative cover. These data may be used in combination with the Sevilleta LTER pollinator monitoring, phenology, and biomass datasets to examine how bee and floral resource abundance, diversity, and phenology vary across years and whether these changes correspond with one another, as well as to consider relationships among climate, floral resource abundance/diversity, and bee abundance/diversity.
Sevilleta plant phenology predicts stability of primary production from 2002 to 2020.
The temporal stability of plant productivity affects species’ access to resources, exposure to stressors, and strength of interactions with other species in the community, including support to the food web. The magnitude of temporal stability may depend on how a species allocates resources across phenological stages, such as vegetative growth versus reproduction. Understanding whether and how plant phenological traits correlate with the long-term stability of plant biomass is particularly important in highly variable environments, such as drylands. We evaluated whether phenological traits predict the temporal stability of plant species productivity by correlating 18 years of monthly phenology observations with biannual estimates of aboveground plant biomass for 98 plant species from semi-arid grasslands and shrublands. We then paired these phenological traits with potential climate drivers to identify abiotic contexts that favor specific phenological strategies among plant species. Phenological traits strongly predicted the stability of plant species biomass. Plant species with longer annual vegetative phenophases had more stable production over time but also failed to fruit in a greater proportion of years, indicating a growth-reproduction trade-off. Earlier leaf- out dates, longer fruiting duration, and longer time lags between leaf and fruit production also predicted greater temporal stability. Species with stability-promoting traits began growing in drier conditions than their counterparts and experienced greater exposure to stress, evaluated by the wider range of temperatures and precipitation during biologically active periods. Our results suggest that bet-hedging strategies which spread resource acquisition and reproduction over longer time periods help to stabilize plant species productivity in variable environments.
Nitrogen addition alters plant competition directly more than indirectly through soil microbes.
Eutrophication, the excessive addition of nutrients to ecosystems, is a pervasive component of global environmental change that can alter community dynamics. Although nitrogen addition experiments have widely documented important declines in plant diversity and shifts in plant species composition, the underlying causes of these outcomes are widely debated. Nitrogen inputs may directly affect plant competition for light or soil water or may influence plant species indirectly by altering the composition of soil microbes. In a 28-year field nitrogen addition experiment, we tested whether nitrogen-induced changes to soil microbes could indirectly alter the outcome of competition between codominant foundation plant species. In the field, long-term addition of inorganic nitrogen slowed the competitive take-over of blue grama grass (Bouteloua gracilis) by black grama grass (B. eriopoda) and thereby stabilized the ecotone between two grassland ecosystems in central New Mexico, USA.
Consumer Front Plant Trait Sampling in Two Virginia Coast Salt Marshes, 2018
A consumer front forms when dense aggregations of herbivores form at the edge of a resource. The front then propagates through the ecosystem in search of additional resources. In U.S. Atlantic salt marshes, the purple marsh crab, Sesarma reticulatum, creates consumer fronts as it grazes the smooth cordgrass, Spartina alterniflora. Sesarma fronts typically form at the heads of tidal creeks and create distinct zonation between the low marsh, tall-form Spartina zones and the high marsh, short-form Spartina zones, with a denuded band of mudflat in between. Over time, Sesarma consumer fronts are moving directionally inland towards the short-form zone and away from the tall-form zone. This movement inland allows for tall-form Spartina to revegetate, preventing further marsh loss. However, it remains unknown why these consumer fronts are moving inland. To test the hypothesis that plant traits (i.e., nutritional quality, palatability) are driving the Sesarma consumer front inland, we collected Spartina from consumer fronts at 8 unique creekheads across two marsh systems on the Eastern Shore of Virginia (4 consumer fronts at Upper Phillips Creek and 4 at Upshur Creek). Spartina was collected from 15 replicate quadrats (0.0625m^2) from the tall-form low marsh zones (TSA) and from the short-form low marsh zones (SSA) at each creekhead. The short-form zone was delineated into two additional zones, an interior (SSA-I) and an exterior (SSA-E), to assess if there were any differences in plant traits between Spartina being actively grazed (SSA-E, adjacent to consumer front) and those that have not been grazed (SSA-I, 2 meters from consumer front). Collected Spartina plants were then processed for a series of plant traits that can influence herbivore preference.
Dataset and Scripts for: RefPlantNLR: a comprehensive collection of experimentally validated plant NLRs (v.20200528_415)
<p><strong>RefPlantNLR v.20200528_415</strong></p> <p><strong>See </strong>bioRxiv 2020.07.08.193961; doi: <a href="https://doi.org/10.1101/2020.07.08.193961">https://doi.org/10.1101/2020.07.08.193961</a></p> <p>SUPPLEMENTAL DATA</p> <p>Table S1: Description of RefPlantNLR.</p> <p>Table S2: Plant orders represented in RefPlantNLR.</p> <p>Supplemental dataset 1: Amino acid sequences of RefPlantNLR entries (fasta format). This file contains 415 amino acid sequences.</p> <p>Supplemental dataset 2: CDS sequences of RefPlantNLR entries (fasta format). This file contains 400 CDS sequences. CDS sequences could not be retrieved for 15 RefPlantNLR entries.</p> <p>Supplemental dataset 3: Annotated genomic sequences of RefPlantNLR entries (GenBank flat file format). This file contains 329 genomic loci containing the gene models of 344 RefPlantNLR entries and 56 RefPlantNLR mRNA entries lacking genomic information.</p> <p>Supplemental dataset 4: InterProScan annotation of the RefPlantNLR amino acid sequences (GFF3 format). This file contains the InterProScan annotation of 415 amino acid sequences.</p> <p>Supplemental dataset 5: InterProScan annotation of the RefPlantNLR CDS sequences (GFF3 format). This file contains the InterProScan annotation of the 400 CDS sequences.</p> <p>Supplemental dataset 6: Amino acid sequences of the extracted RefPlantNLR NB-ARC domains (fasta format). This file contains 424 NB-ARC domain (SUPERFAMILY signature SSF52540) amino acid sequences belonging to 415 RefPlantNLR entries.</p> <p>Supplemental dataset 7: Amino acid sequences of the unique RefPlantNLR extracted NB-ARC domains (fasta format). This file contains 347 unique NB-ARC domain (SUPERFAMILY signature SSF52540) amino acid sequences.</p> <p>Supplemental dataset 8: Clustal Omega alignment of the unique RefPlantNLR extracted NB-ARC domains (PHYLIP format). This file contains the Clustal Omega alignment of 346 unique NB-ARC domains (SUPERFAMILY signature SSF52540) with all positions with less than 95% coverage removed. Pb1 was omitted from this alignment.</p> <p>Supplemental dataset 9: NB-ARC domain phylogeny of the RefPlantNLR entries using the Maximum likelihood method (Newick format). This file contains the phylogenetic analysis of the NB-ARC domain of the RefPlantNLR entries using the JTT method.</p> <p>Supplemental dataset 10: Amino acid sequences of the non-redundant RefPlantNLR entries (fasta format). This file contains 235 amino acid sequences representing the non-redundant RefPlantNLR entries at a 90% amino acid identity threshold per genus according to the NB-ARC domain.</p> <p>Supplemental dataset 11: Amino acid sequences of the NB-ARC domains of the non-redundant RefPlantNLR entries (fasta format). This file contains 241 amino acid sequences representing the extracted NB-ARC domains of the 235 non-redundant RefPlantNLR.</p> <p>Appendix S1: R script used to generate annotations and figures.</p> <p>Appendix S2: InterProScan descriptions used for generating annotations.</p>
Data and R code for Tansley review New Phytologist 2021: "An integrated framework of plant form and function: The belowground perspective"
<p>The files in this archive are related to the paper of Weigelt, Mommer, Andraczek et al. (2021) An integrated framework of plant form and function: The belowground perspective. Tansley Review New Phytologist. The paper developed and tested a new conceptual framework of plant form and function linking above and belowground traits of 2510 species. We found that an integrated, whole-plant trait space required as much as four axes. The two main axes represented the fast-slow ‘conservation’ gradient on which leaf and fine-root traits were well aligned, and the ‘collaboration’ gradient in roots. The two additional axes were separate, orthogonal plant size axes for height and rooting depth.</p> <p>This archives contains four files:</p> <ol> <li><strong>Weigelt et al.2021RCode.DataCleaning.txt</strong> - RCode for the complete data processing starting with the downloaded database files from the Plant Trait Database version 5.0 (TRY, Kattge et al. 2020), the Global Root Trait database (GRooT, Guerrero-Ramirez et al. 2020) and a small number of additional data files listed in Table S2 of the original paper. Additional information was later incorporated using FungalRoot Database (Soudzilovkaia et al. 2020), nodDB Database (Tedersoo et al. 2018) and a compiled dataset on rooting depth (Fan et al. 2017). The code processes, cleans and merges the data and produces a final table for PCA analysis of species specific mean traits. This final table is provided as a second file in this archive (Weigelt_et_al_2021_Main.PCA.Matrix.xlsx). A second part of the RCode.DataCleaning extracts species-specific individual trait data where root and shoot traits were measured on the same plant individual or plot. This data was compiled from 43 studies identified in Table S2 of the original publication. The final table for individual trait data is the third file in this archive (Weigelt_et_al_2021_Individual.PCA.Matrix.xlsx).</li> <li><strong>Weigelt_et_al_2021_Main.PCA.Matrix.xlsx</strong> – Datafile with species-specific global mean trait data for 17 traits of 2510 species with at least one root and one shoot trait available. Meta-data is provided in the data file.</li> <li><strong>Weigelt_et_al_2021_Individual.PCA.Matrix.xlsx</strong> – Datafile with species-specific trait data where root and shoot traits were measured on the same individual or plot for 6 traits of 455 species. Meta-data is provided in the data file.</li> <li><strong>Weigelt et al.2021RCode.Analysis.txt – </strong>RCode for all analyses and figures provided in the paper for both the species mean and individual based dataset. The Code is annotated to help reproducibility of the analysis.</li> </ol>
S29 | PHYTOTOXINS | Toxic Plant Phytotoxin (TPPT) Database
<p>This is the collection associated with list S29 PHYTOTOXINS on the NORMAN Suspect List Exchange.</p> <p><a href="https://www.norman-network.com/nds/SLE/">https://www.norman-network.com/nds/SLE/</a></p> <p>S29 PHYTOTOXINS <strong>Toxic Plant Phytotoxin (TPPT) Database</strong></p> <p>A comprehensive toxic plant-phytotoxin (TPPT) database provided by Günthardt et al 2018, DOI: <a href="https://pubs.acs.org/doi/10.1021/acs.jafc.8b01639">10.1021/acs.jafc.8b01639</a><br>More information on the <a href="https://www.agroscope.admin.ch/agroscope/en/home/publications/apps/tppt.html">Agroscope TPPT website</a>.</p> <p>Updated 20/11/2019 to correct InChIKey errors; updated 16/7/2022 to create merged SMILES column for PubChem deposition. 27/6/2025 added new CSV without duplicate CAS headers. </p>
Global Naturalized Alien Flora (GloNAF). Open access data to support research on understanding global plant invasions.
<p>This dataset is a snapshot of the Global Naturalized Alien Flora (GloNAF) database, version 2.02. GloNAF is a continuously updated, curated compilation of alien naturalized vascular plant inventories for geographic regions from around the world. The dataset has 16,429 unique taxa reported as naturalized or invasive and covers 1,343 regions (including 427 islands) from 336 data sources. For each region, the status (invasive, naturalized) is provided as listed in the original source. We provide the scientific names included with the original data source, and the matching accepted name or synonym of the taxon as given in the World Checklist of Vascular Plants (WCVP) Version 12. In addition, we provide an ESRI shapefile of polygons for each region. We also provide several variables that can be used to filter the data according to quality and completeness of alien taxon lists, which vary among the combinations of regions and data sources.</p> <p>The 'glonaf_flora2.csv' file lists the IDs ('taxon_wcvp_id') of all naturalized taxa contained in GloNAF and the regions they occur in. The 'glonaf_taxon_wcvp.csv' lists the original taxon names provided in the source data along with the corresponding accepted taxon name from the WCVP (version 12) for all alien taxa in GloNAF, regardless of their naturalization status. To link taxon names with naturalization records, join the 'id' column of the 'glonaf_taxon_wcvp.csv' file to the 'taxon_wcvp_id' column in 'glonaf_flora2.csv' . Additional information regarding the original source of the data ('glonaf_reference.csv'), specific attributes of the taxon lists ('glonaf_list.csv') and the region ('glonaf_region.csv') can also be joined similarly to 'glonaf_flora2.csv '. </p> <p> </p>
Taxonomic list of Brazilian fruit-bearing plants for human use
<h3>Lista taxonômica de plantas frutíferas para consumo humano, com curadoria da equipe do projeto <a href="https://www.inaturalist.org/projects/pomar-urbano">Pomar Urbano</a>. </h3> <p><em>[see English description below]</em></p> <p><br>As planilhas estão organizadas da seguinte forma:</p> <p><strong>PT_lista_especies_aceitas_v.3.0</strong>: contém os nomes de todas as espécies atualmente indexadas na base de dados do <a href="https://www.inaturalist.org/projects/pomar-urbano">Pomar Urbano</a>.</p> <p><strong>PT_lista_especies_adicionadas_v.3.0</strong>: contém os nomes das novas espécies que passam a integrar a base de dados do Pomar Urbano a partir da versão 3.0.</p> <p><strong>PT_lista_especies_removidas_v3.0</strong>: contém os nomes das espécies removidas da versão 3.0 da lista, e que portanto não fazem mais parte do banco de dados do projeto. </p> <p> </p> <p><strong>Metadados usados nas planilhas:</strong></p> <ul> <li><em>Nome científico</em>: O nome científico completo, com autoria e data, se conhecidos.</li> <li><em>Família</em>: O nome científico completo da família.</li> <li><em>Nome vernacular</em>: nome comum, popular.</li> <li><em>Origem</em><strong>: </strong>Declaração sobre se um organismo foi introduzido em um local e tempo específicos por meio da atividade direta ou indireta dos seres humanos modernos.</li> <li><em>Distribuição geográfica</em>: área geográfica ou região onde uma espécie ocorre no Brasil. Foram considerados como valores válidos para este campo apenas as macrorregiões do Brazil, a saber: S = Sul, SE = Sudeste, CO = Centro-Oeste, NE = Nordeste, N = Norte.</li> <li><em>Última atualização</em>: A data mais recente em que a entrada no catálogo foi alterada, atualizada ou modificada.</li> </ul> <h3>--------------------------------------------------------------------------------------------------------------------------------------<br><br>Taxonomic list of fruit-bearing plants for human consumption, curated by the <a href="https://www.inaturalist.org/projects/pomar-urbano">Pomar Urbano project</a></h3> <p><em>[Vernacular names are presented only in Portuguese; for properly processing in data management tools, downloading a Portuguese language package might be necessary]</em></p> <p>The spreadsheets are organized as follows:</p> <p>EN_list_accepted_species_v.3.0: contains the names of all species currently indexed in the <a href="https://www.inaturalist.org/projects/pomar-urbano">Pomar Urbano</a> database.</p> <p>EN_new_added_species_v.3.0: contains the names of new species that are included in the Pomar Urbano database starting from version 3.0.</p> <p>EN_removed_species_v.3.0: contains the names of species that were present in the version 2.0 of the list and are therefore no longer part of the version 3.</p> <p> </p> <p><strong>Metadata used in the spreadsheets</strong>:</p> <p><em>Scientific Name</em>: The complete scientific name, including authorship and date, if known. <em>ExactMatch</em>: <a href="http://rs.tdwg.org/dwc/terms/scientificName">dwc:scientificName</a>. </p> <p><em>Family</em>: The full scientific name of the family. <em>ExactMatch</em>: <a href="http://rs.tdwg.org/dwc/terms/family">dwc:family.</a></p> <p><em>Vernacular Name</em>: Common or popular name. <em>ExactMatch</em>: <a href="http://rs.tdwg.org/dwc/terms/vernacularName">dwc:vernacularName</a></p> <p><em>Establishment Means</em>: Statement about whether an organism has been introduced to a specific place and time through the direct or indirect activity of modern humans. <em>ExactMatch</em>: <a href="http://rs.tdwg.org/dwc/terms/establishmentMeans">dwc:establishmentMeans</a></p> <p><em>Higher geography</em>: The geographical area or region where a species occurs in Brazil. Only the macroregions of Brazil are considered valid values for this field within this dataset, namely: S = South, SE = Southeast, CO = Central-West, NE = Northeast, N = North. <em>CloseMacth</em>: <a href="http://rs.tdwg.org/dwc/terms/higherGeography">dwc:higherGeography</a></p> <p><em>Last Update</em>: The most recent date on which the catalog entry was changed, updated, or modified. <em>ExactMatch</em>: <a href="http://purl.org/dc/terms/modified">dct:modified</a></p> <p> </p>
Wind power plants layouts according to arbitrary reference points, Thanet, West of Duddon Sands, Ormonde, Westermost Rough, Horns Rev 1 & 2, Anholt, and London Array
<p><strong>If this dataset helps your research, please cite it and the papers further below (according to which OWPP you study).</strong></p> <p>This dataset contains the layouts of the Thanet, West of Duddon Sands, Ormonde, Westermost Rough, Horns Rev 1 & 2, Anholt, and London Array offshore wind power plants (OWPPs), which can be utilized in a variety of studies. </p> <p>The X and Y coordinates, in kilometers, were written according to arbitrary reference points. The positions of wind turbine generators (WTGs) and substations (SS) for the OWPPs came from the sources below.</p> <p><strong>Thanet</strong>: WTGs from [1] (page 7), SS based on [3] (page 9).<br><strong>West of Duddon Sands</strong>: WTGs from [2] (page 5), SS based on [3] (page 9).<br><strong>Ormonde</strong>: WTGs and SS from [4] (page 2).<br><strong>Westermost Rough</strong>: WTGs and SS from [5] (page 4).<br><strong>Horns Rev 1</strong>: WTGs and SS from [6] (page 6).<br><strong>Horns Rev 2</strong>: WTGs and SS from [7] (page 5).<br><strong>Anholt</strong>: WTGs and SS from [8] (page 3).<br><strong>London Array</strong>: WTGs from [9] (page 15), SS based on [10] (page 2).</p> <p>From the OWPPs' layout figures [1-9], I used Graph Grabber 2.0.2* to extract the data points. Then, based on visual inspection of layouts in [1-9], I utilized 2D projections to align WTGs that should be aligned. References [1], [2], and [9] do not provide the SS positions. Thus, I carefully overlapped the layouts with other layouts from [3] and [10] to approximate the SS locations.</p> <p>Regarding the arbitrary reference points for the coordinates, although the values in the X and Y axes differ from [1-9], note that the distances among the WTGs are the same from [1-9]. Furthermore, there are no axes in [1,5]. Instead, distances are given, which are enough to obtain the layout. Values in meters were converted to kilometers.</p> <p>As seen in the attachments, the coordinates can be obtained via either "h5" or "csv" files, which can be easily read by Matlab, Julia, and Python, among others. <strong>The name of the datasets in the "h5" file are</strong>: "Thanet", "WDS", "Ormonde", "WMR", "HornsRev1", "HornsRev2", "Anholt", and "LondonArray".</p> <p><strong>Except for the London Array OWPP, the first row in all data matrices represents the SS coordinates, whereas the subsequent rows represent the WTGs. London Array has 2 substations, thus the first and second rows represent their coordinates. In all matrices, the first and second columns are the X and Y coordinates, respectively.</strong></p> <p>*<a href="https://www.quintessa.org/software/downloads-and-demos/graph-grabber-2.0.2">Graph Grabber 2.0.2 | Downloads And Demos | Software | Quintessa Limited | Scientific and Mathematical Consultancy</a></p>
Plant Atlas 2020 — British and Irish vascular plant and charophyte 2 x 2 km grid square locations up to 2019
<p><span>This resource provides the data behind the 2 × 2 km grid square (tetrad) British and Irish distribution maps, for 3,431 taxa, presented in both the Plant Atlas 2020 book and website (</span><a href="http://www.plantatlas2020.org"><span><span>www.plantatlas2020.org</span></span></a><span><span>), up to 2019. These are presence-only data, indicating where a taxon was reported from a tetrad</span></span><span>. These 2 km square presences are based on over 30 million records, collected mainly by volunteer recorders of the Botanical Society of Britain and Ireland (BSBI) between 2000 and 2019, as well as previous nationwide surveys undertaken in the 1950s and 1990s.</span></p>
Plant Atlas 2020 — British and Irish vascular plant and charophyte 10 x 10 km grid square locations, subdivided by survey period, up to 2019
<p><span>This resource provides the data behind the 10 × 10 km grid square (hectad) British and Irish distribution maps, for 3,497 taxa, presented in both the Plant Atlas 2020 book and website (</span><a href="http://www.plantatlas2020.org"><span><span>www.plantatlas2020.org</span></span></a><span><span>), subdivided by time period<a><span>.</span></a> These are presence-only data, indicating where a taxon was reported from a hectad, within a given</span><span><span></span></span></span><span> multi-year period, up to 2019. These time periods cover the 20<sup>th</sup> Century, but also extend back to the earliest botanical records known for Britain and Ireland in the first period (pre-1930). These 10 km square presences are based on over 30 million records, collected mainly by volunteer recorders of the Botanical Society of Britain and Ireland (BSBI) between 2000 and 2019, as well as previous nationwide surveys undertaken in the 1950s and 1990s.</span></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.