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.
1,288
datasets available to search
ShareScore release 0.7.1
Dataset results
1,288 results for “threatened”
Data from: Will Current Protected Areas Harbour Refugia for Threatened Arctic Vegetation Types until 2050? A First Assessment
<p>We present predictions of Arctic vegetation for 2050 based on a combination of climate models (namely, EC-Earth3-Veg, IPSL-CM6A-LR, and MRI-ESM2-0), emission scenarios (names, SSP126 and SSP585) and tree dispersal rate scenarios (unrestricted, 20km and 5km) based on the methods of Pearson et al. (2013) and the new raster version of the Circumpolar Arctic Vegetation Map (CAVM) (Raynolds et al. 2019). We additionally present a dataset summarising total areas for each vegetation type in the CAVM and the forecasted models based on the computation of zonal histograms in ArcGIS (zonal_histogram_results.csv), for the total Arctic as well as only within protected areas, defined by the Map of Arctic Protected Areas (CAFF and PAME 2017). We also present a potential map of refugia for what we deem the realistic model (IPSL, SSP585, 20 km tree dispersal) as a raster file. Refugia were identified as regions where the vegetation remained the same between the CAVM and the predictions. Additionally, we present a map of model agreement, showing the degree to which other models agree with the vegetation classification for our refugia.</p> <p>All predictions named according to the tree dispersal rate, climate model, and emissions scenario, preceded by the term "pred". For example: "pred_unres_mri_585" represents the unrestricted tree dispersal, MRI-ESM-0 climate model, and SSP585 scenario-based prediction. The MRI-ESM-0 x SSP585 combination had gaps in data which results in a lack of predictions in some areas; this affects 3 models.</p> <p>Further details and all code associated with these datasets are found <a href="https://github.com/PlekhanovaElena/Arctic_vegetation_prediction">here</a>.</p>
Population genomics reveals differences in genetic structure between two endemic arboreal rodent species in threatened cloud forest habitat
<p>SNPs obtained by UNEAK pipeline for <em>Habromys schmidlyi </em>and <em>Reithrodontomys microdon</em>. </p> <p>Pleae cite as: </p> <p>Colunga-Salas P., T Marines-Macías, G Hernández-Canchola, S Barbosa, C Ramírez, JB Searle, L León-Paniagua. 2022. <strong>Population genomics reveals differences in genetic structure between two endemic arboreal rodent species in threatened cloud forest habitat</strong>. Mammalian Reasearch. Doi: 10.1007/s13364-022-00667-x</p>
Throw trap and electrofishing data collected during 1996–2022 from the Everglades, Florida, United States for the publication "Hydrology-mediated ecological function of a large wetland threatened by an invasive predator"
Asian swamp eels (Monopterus albus/javanensis complex) were first reported from Florida in 1997 and the Everglades in 2007; swamp eels have been established in Taylor Slough of Everglades National Park since 2014. This dataset incorporates plot-level mean densities (# of individuals per square meter) of common aquatic animals collected during 1996–2022 from 24 sites across four regions of the Everglades: Taylor Slough, Shark River Slough, Water Conservation Area 3, and the C-111 Panhandle. Prey species included are the six most common small fishes prior to swamp eel invasion of Taylor Slough (1996–2009) and the three common decapod species (two crayfish species and grass shrimp). An annual index of mean wet season electrofishing catch-per-unit-effort of swamp eels, Mayan cichlids (Mayaheros uruphthalmus), and the three other large 'top predator' fishes (Amia calva, Lepisosteus platyrhincus, Micropterus salmoides) is included for plots where electrofishing was performed from 1997-2021. Hydrologic measures used in analyses are included.
Future Ocean Warming May Threaten Key Photosynthetic Microbes
<h2>Description</h2> <p>The datasets supporting the conclusions of this article, including field measurements of <em>Prochlorococcus</em> division rates, are available in this repository. </p> <p>The R code performs the following tasks:</p> <ul> <li>Loads data from various sources, including lab experiments, dilution experiments, and in-situ measurements.</li> <li>Calculates thermal norm predictions using different models (Eppley, Hinshelwood, Eppley-Norberg) to predict division rates based on temperature.</li> <li>Generates figures to visualize the results, including latitudinal and temperature effects on division rates, model predictions compared with observed data, and changes in primary production under different emission scenarios.</li> <li>Fits the Hinshelwood model to culture data and extracts best-fit parameters.</li> <li>Performs bootstrapping to estimate uncertainty in the Hinshelwood model parameters.</li> <li>Calculates confidence intervals for the bootstrapped parameters.</li> </ul> <h2>R Scripts</h2> <ul> <li><strong>Ribalet_main.R:</strong> This script contains the main analysis code, including data loading, model fitting, figure generation, and bootstrapping.</li> <li><strong>Ribalet_fitting.R:</strong> This script defines functions for fitting different growth models to the data and estimating model parameters.</li> </ul> <h2>Requirements</h2> <ul> <li>R version 4.4.2 (2024-10-31)<br>Platform: aarch64-apple-darwin20<br>Running under: macOS Sequoia 15.1.1</li> <li>Matrix products: default<br>BLAS: /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib <br>LAPACK: /Library/Frameworks/R.framework/Versions/4.4-arm64/Resources/lib/libRlapack.dylib; LAPACK version 3.12.0</li> <li>attached base packages:<br>[1] parallel stats graphics grDevices utils datasets <br>[7] methods base </li> <li>other attached packages:<br> [1] DEoptim_2.2-8 arrow_15.0.1 ggpubr_0.6.0 lubridate_1.9.3<br> [5] forcats_1.0.0 stringr_1.5.1 dplyr_1.1.4 purrr_1.0.2 <br> [9] readr_2.1.5 tidyr_1.3.1 tibble_3.2.1 ggplot2_3.5.1 <br>[13] tidyverse_2.0.0</li> </ul> <h2>Installation</h2> <p>Install the required R packages:</p> <div> <div>Code snippet</div> <div> <div> <pre><code>install.packages(c("tidyverse", "ggpubr", "arrow", "DEoptim")) </code></pre> </div> </div> </div> <h2>Usage</h2> <p>The scripts will generate figures and output files in the same directory.</p> <h2>Input Data</h2> <p>The code requires the following input data files:</p> <ul> <li>culture.csv</li> <li>dilution.csv</li> <li>abundance.csv</li> <li>mpm.csv</li> <li>model_results.parquet</li> <li>bootstrap_projections.csv</li> <li>modeled-thermal-traits.tsv</li> <li>sst.parquet</li> <li>culture_syn.csv</li> </ul> <p>Please ensure that these files are present in the same directory as the R script files.</p> <h2>Output Data</h2> <p>The code generates the following output files:</p> <ul> <li>Figures: Figure1.png, Figure2.png, Figure3.png, FigureS1.png, FigureS2.png, FigureS3.png, FigureS4.png, FigureS5.png, FigureS6.png, FigureS9.png, FigureS11.png, FigureS12.png, FigureS13.png, FigureS14.png, FigureS15.png</li> <li>CSV files: bootstrap_parameters.csv, cultures_thermal_reactions.csv</li> </ul> <h2>License</h2> <p>This code is licensed under the MIT License.</p>
Mammals under pressure: presence data for assessing extinction of endemic, threatened, and mammals subject to use, in Colombia
<p>This is the first dataset that provides a complete compilation of mammal records based on camera traps, human observations, and specimens deposited in biological collections in Colombia. We compiled a dataset with unpublished information, including 97,943 records corresponding to 136 species, of which 38 are endemic, 92 are identified as species subject to use by humans in the literature, and 33 are categorized either as Data Deficient or threatened according to international or unofficial national assessments. The information comes from 31 out of 32 departments of Colombia and constitutes relevant input for future distribution and conservation assessments. Most records (n=96,417, 98.44%) come from non-invasive sampling methods such as camera traps. However, we highlight the contribution of museum specimens (n= 1,332), especially for small and medium-sized species, many of them with restricted distributions in the country. This dataset constitutes a joint collaborative and interinstitutional effort that serves as the basis for cooperative work to comprehensively assess the current conservation status of all mammal species in Colombia.</p>
Groundwater is a globally-threatened keystone ecosystem
<p>Global maps of groundwater diversity, interactions between groundwater and surface water and global surface diversity linked into two maps.</p>
Dataset from: Spatially heterogeneous shifts in vegetation phenology induced by climate change threaten the integrity of the avian migration network
<p>Original data and code for the study:</p> <p>Wei, J., Xu, F., Cole, E. F., Sheldon, B. C., de Boer, W. F., Wielstra, B., Fu, H., Gong, P., & Si, Y. (2024, Accepted). Spatially heterogeneous shifts in vegetation phenology induced by climate change threaten the integrity of the avian migration network. Global Change Biology.</p> <p>The dataset mainly contains data showing the climate change-induced heterogeneous shifts in vegetation phenology and the migration integrity change from 2000 to 2020 for 16 Asian herbivorous waterfowl species. These data were derived from the following resources available in the public domain.</p> <p>The Global Lakes and Wetlands Database is available from “https://www.worldwildlife.org/pages/global-lakes-and-wetlands-database”. The global land cover datasets are available from European Space Agency (ESA) Climate Change Initiative (CCI) products, “https://maps.elie.ucl.ac.be/CCI/viewer/download.php”. The Global Multi-resolution Terrain Elevation Data are available from “https://www.usgs.gov/centers/eros/science/terrain-monitoring-and-modeling”. The Moderate Resolution Imaging Spectroradiometer (MODIS) Terra surface reflectance product is available from “https://modis.gsfc.nasa.gov/data/dataprod/mod09.php”. The bird distribution maps are available from Birdlife International, “https://www.birdlife.org/”. The bird foraging attribute data are available from EltonTraits 1.0, “https://figshare.com”. The bird occurrence data are available from eBird Basic Dataset (EBD), “https://science.ebird.org/en/use-ebird-data/download-ebird-data-products”. The Hackett backbone phylogenetic trees are available from “https://birdtree.org/”.</p> <p>The code contains the R scripts and MATLAB scripts that we used for this study.</p> <p>For details please see the file “Readme.txt”, and the research paper.</p>
Scaling landscape fire history in sagebrush: Wildfires not historically frequent in the main population of threatened Gunnison Sage-grouse
<p>The main population of ∼5,000 Threatened Gunnison sage-grouse (GUSG; Centrocercus minimus) in Colorado depends on sagebrush that are killed by wildfires, with recovery taking decades, so frequent fire is a threat, but did it occur historically? Early land surveys showed that the historical (preindustrial) fire rotation (FR), the expected period to burn area equal to a focal land area, was 90-143 years in GUSG ranges, which is not frequent fire (≤25 years). However, recent research, based on fire scars on trees at ten sites near sagebrush, suggested some frequent fire historically in the main population. That study was not spatial, essential to estimate FR, so spatial data were created in GIS with land-survey reconstructions, survey dates, fire-scar sites, Thiessen polygons around sites, and sagebrush. The previous study assumed fires that burned 2+ sites likely burned across sagebrush. Historical FRs were calculated several ways over a common period. A recovery estimate of FR was 90-135 years, a land-survey estimate 82-131 years, and three spatial scar-based estimates 93-107 years, showing agreement. However, comparing land-survey and fire-scar results showed that using fire scars spatially only 43% matched land surveys. Detailed analysis showed that 10 fire-scar sites were insufficient to detect historical fire sizes and distributions across the large 168,753 ha sagebrush area. An adequate historical fire reconstruction could require ∼45-60 fire-scar sites, making only ∼30,000 ha of sagebrush feasible. Using the two remaining methods, which cross-validate, showed frequent fire did not occur historically in the study area, as historical FRs were 82-135 years. </p>
Habitat Protection Indexes - new monitoring measures for the conservation of threatened marine habitats - Datasets and supporting files
<p>The supporting datasets, scripts, and supplementary information for the manuscript, "Habitat Protection Indexes - new monitoring measures for the conservation of threatened marine habitats," are available within this repository.</p> <p>We conduct an analysis on the coverage of protected areas that cover six threatened marine and coastal and developed two indexes, the Local Proportion of Habitat Protected Index and the Global Proportion of Habitat Protected Index, describing the protection of these habitats locally and globally. The habitats considered are the following: cold corals, warm water corals, knolls and seamounts, mangroves, saltmarshes, and seagrasses.</p> <p>The index scores of each jurisdiction are made available for download in the dataset: <em>habitat_protection_indexes_average.csv</em></p> <p>The habitat specific index scores for each jurisdiction are made available for download in the dataset: <em>habitat_protection_indexes.csv. </em></p> <p>Column name descriptions are available in the text file: <em>Column_name_descriptions_20220301</em></p> <p>The scripts used to run the workflow to calculate the indexes, create figures, and calculate statistics for the manuscript are also included. The script <em>01_Workflow sources</em> the first 9 scripts in the <em>scripts</em> folder to calculate the indexes which relies on the functions script within the functions folder. The rest of the scripts in the folder create the figures and calculate the statistics for the manuscript.</p> <p>A readme pdf file is included here to ease with reproducing the workflow, but we strongly suggest to please visit our github (<a href="https://github.com/jkumagai96/Marine_Habitat_protection">https://github.com/jkumagai96/Marine_Habitat_protection</a>) to reproduce the entire calculation where we provide detailed information on how to run the workflow and package management.</p>
The Threatening English Language (TEL) Corpus
<p>TEL is the Threatening English Language corpus. It is a collection of 309 written texts compiled from the publicly-available portion of CTARC (the Communicated Threat Assessment Research Corpus, compiled by Tammy Gales), MFT (the Malicious Forensic Texts corpus, compiled by Andrea Nini), and the written portion of CoJO (the Corpus of Judicial Opinions, compiled by Julia Muschalik). Additional texts are from ForensicLing.com (the forensic linguistic data site hosted by Tammy Gales and Dakota Wing). Basic metadata is supplied for each text where known from the original case research. We wish to thank our graduate student fellows who helped compile the texts and metadata: Nicole Harris, Annina van Riper, Zara Rabinko, and Zachary Boudreaux.</p> <p>Total texts: 309<br> Total estimated authors: 203<br> Total word count: 54,167</p> <p>METADATA KEY</p> <p>TG = Tammy Gales (public portion of CTARC)<br> AN = Andrea Nini (MFT)<br> JM = Julia Muschalik (written portion of CoJo)<br> FL = ForensicLing.com (Tammy Gales and Dakota Wing)</p> <p>Name###_## = file name, case number, text number within case<br> File name might be threat recipient or author; remaining info is about the author, where known</p>
Fig. 3. Hibiscus hareyae. A in Discovered online: Hibiscus hareyae sp. nov. of sect. Lilibiscus (Malvaceae), threatened in coastal thicket at Lindi, Tanzania
Fig. 3. Hibiscus hareyae. A leaves and inflorescence from above showing epicalyces; B flower from below showing white inner petal markings. From Suleiman et al. 5526 (K). PHOTOS: A IAIN DARBYSHIRE, B TORAL SHAH.
Fig. 2. Hibiscus hareyae. A in Discovered online: Hibiscus hareyae sp. nov. of sect. Lilibiscus (Malvaceae), threatened in coastal thicket at Lindi, Tanzania
Fig. 2. Hibiscus hareyae. A habit, leafy shoot; B full-sized leaf, abaxial surface; C flowering shoot; D petal; E anther; F anther, inner face; G anther, dorsal face showing filament insertion; H pedicel, epicalyx and calyx; J pedicel detail-indumentum; K calyx margin – indumentum; L epicalyx lobe — indumentum. From Milne-Redhead & Taylor 7481. DRAWN BY ANDREW BROWN.
Image 1 in Parasitic associations of a threatened Sri Lankan rainforest rodent, Mus mayori pococki (Rodentia: Muridae)
Image 1. Photomicrographs of the intestinal parasitic eggs & the larva detected in faecal samples of Mus mayori.
Figure 7 in A conservation palaeobiological approach to assess faunal response of threatened biota under natural and anthropogenic environmental change
Figure 7. Box plots show the distribution of relative abundances of the associations across the six facies types.
Figure 3 in A conservation palaeobiological approach to assess faunal response of threatened biota under natural and anthropogenic environmental change
Figure 3. Sampling locations of three expeditions in 2015–2017. The first (September–October 2015) and second expeditions (July 2016) were searching for living Pontocaspian molluscs in particular. The third expedition consisted of six transects sampled by GeoEcoMar in 2017 in search of any living mollusc. In the legend w/wo means with or without.
Figure 1 in A conservation palaeobiological approach to assess faunal response of threatened biota under natural and anthropogenic environmental change
Figure 1. Location of study area along the Romanian Black Sea coast with core locations indicated by black stars. (a) Danube Delta and RSL (modified after Vespremeanu-Stroe et al., 2017). (b) RSL bathymetry with location of study cores (modified after Dimitriu et al., 2008). Two current marine outlets are indicated by white arrows; a third outlet (Gura Portiţa) was closed in the 1970s and is indicated by a dashed white arrow.
Figure 6 in A conservation palaeobiological approach to assess faunal response of threatened biota under natural and anthropogenic environmental change
Figure 6. Overview of the 20 most abundant mollusc species grouped according to the results of Kendall's W coefficient of concordance (for k = 4). (a) Valvata piscinalis (RGM.1309841, Core C7, depth 6 cm). (b) Dreissena polymorpha (RGM.1309827, C7 – 6 cm). (c) Dreissena bugensis (RGM.1309846, C5 – 18 cm). (d) Adacna fragilis (RGM.1309835, C2 – 18 cm). (e) Monodacna colorata s.l. (RGM.1309823, C7 – 14 cm). (f) Rissoa membranacea (RGM.1309830, C3 – 48 cm). (g) Hypanis plicata (RGM.1309845, C9 – 3 cm). (h) Clathrocaspia knipowitschii (RGM.1309843, C11 – 102 cm). (i) Mytilaster minimus (RGM.1309838, C3 – 24 cm). (j) Ecrobia maritima (RGM.1309831, C3 – 48 cm). (k) Cerastoderma glaucum (RGM.1309844, C13 – 24 cm). (l) Abra segmentum (RGM.1309821, C1 – 48 cm). (m) Parthenia interstincta (RGM.1309832, C3 – 48 cm). (n) Lentidium mediterraneum (RGM.1309837, C4 – 12 cm). (o) Retusa truncatula (RGM.1309828, C2 – 42 cm). (p) Gyraulus crista (RGM.1309840, C5 – 54 cm). (q) Potamopyrgus antipodarum (RGM.1309836, C2 – 18 cm). (r) Lithoglyphus naticoides (RGM.1309842, C5 – 18 cm). (s) Theodoxus fluviatilis (RGM.1309826, C11 – 66 cm). (t) T. fluviatilis (RGM.1309824, C11 – 78 cm). (u) Theodoxus danubialis (RGM.1309839, C3 – 24 cm). (v) T. danubialis (RGM.1309834, C2 – 30 cm). Scale bars are 1 mm.
Figure 2 in A conservation palaeobiological approach to assess faunal response of threatened biota under natural and anthropogenic environmental change
Figure 2. Overview of core data. From left to right each core: core photograph, lithology, facies, fauna relative abundance per species group based on origin, evolution and estimated palaeosalinities.
Figure 5 in A conservation palaeobiological approach to assess faunal response of threatened biota under natural and anthropogenic environmental change
Figure 5. NMDS ordination plot of species compositions across samples grouped into lake regions (stress = 0.173). Optimum salinity and grain size were fitted as two-dimensional smooth surfaces to illustrate the associations with species composition. Species are marked with numbers: 1 – Planorbis planorbis, 2 – Clathrocaspia knipowitschii, 3 – Potamopyrgus antipodarum, 4 – Theodoxus danubialis, 5 – Planorbarius corneus, 6 – Abra segmentum, 7 – Rissoa membranacea, 8 – Valvata macrostoma, 9 – Hypanis plicata, 10 – Mytilaster minimus, 11 – Ecrobia maritima, 12 – Parthenia interstincta, 13 – Cerastoderma glaucum and 14 – Lentidium mediterraneum.
Figure 8 in A conservation palaeobiological approach to assess faunal response of threatened biota under natural and anthropogenic environmental change
Figure 8. Snapshot reconstructions of the evolution of the RSL and their mollusc biota. The names of major sand barriers are indicated in yellow, while those of deltaic lobes are in black. The names in parentheses and italic font are currently inactive lobes. Pie charts indicate the relative abundance of the three associations in the time interval of ±50 years of the indicated snapshot: blue – Association I (freshwater); green – Association II (Pontocaspian), orange – Association III (marine), grey – rest of the group. Water colours indicate a salinity gradient: blue is Black Sea influence (18 psu); green is river influence (0 psu). Note the freshening of the system and according changes in species associations with the decreasing influence of mesohaline waters from the Black Sea.
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.